WO2013049038A1

WO2013049038A1 - Assessment of risk of local recurrence of cancer using telomere health

Info

Publication number: WO2013049038A1
Application number: PCT/US2012/057072
Authority: WO
Inventors: Yun-Ling Zheng; Xin Zhou
Original assignee: Georgetown University
Priority date: 2011-09-28
Filing date: 2012-09-25
Publication date: 2013-04-04

Abstract

Disclosed are compounds, compositions, and methods useful for assessing the risk of local recurrence of cancer. The disclosed methods generally involve measuring or determining a telomere length parameter, such as telomere length variation, and comparing the telomere length parameter to a reference telomere length parameter. The telomere length parameter indicates whether the subject has an increased risk of local recurrence of cancer. The telomere length parameter can also indicate the relative increase in risk of local recurrence of cancer.

Description

ASSESSMENT OF RISK OF LOCAL RECURRENCE OF CANCER USING

TELOMERE HEALTH

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims benefit of U.S. Provisional Application No. 61/540,347, filed September 28, 2011. Application No. 61/540,347, filed September 28, 201 1, is hereby incorporated herein by reference in its entirety.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR

DEVELOPMENT

This invention was made with government support under Grant P30 CA51008 awarded by the National Institutes of Health (NIH), respectively. The government has certain rights in the invention.

FIELD OF THE INVENTION

The present disclosure is directed generally to compositions and methods for assessing cancer risk using telomere health.

BACKGROUND OF THE INVENTION

Breast cancer is the most common cancer in women, with estimated 209,060 new cases of breast cancer diagnosed and 40,230 deaths expected to occur in the US in 2010 (Jemal et al. Cancer Statistics, 2010. CA Cancer J Clin 2010; 60:277-300). With widely implemented population-based mammographic screening, breast cancers are now often detected in early-stages (stage 0 - II) (Hofvind et al. Comparing screening mammography for early breast cancer detection in Vermont and Norway. J Natl Cancer Inst 2008; 100: 1082-91). In the contemporary management of breast cancer, several options exist for local and regional treatment. Patients and their physicians must decide between various surgical options and the dose, volume, and technique of radiotherapy. These decisions may have a significant impact on treatment-related morbidity and survival from breast cancer (Punglia et al. Local therapy and survival in breast cancer. N Engl J Med 2007; 356:2399-405; Palmieri and Perez, Managing the Early and Locally Advanced Breast Cancer Patient at High Risk for

Recurrence: Recent Advances and Nursing Implications 2007; 23(l):29-36). A better understanding of the risk of local recurrence (LR) would facilitate therapeutic decision making. Thus it is highly desirable to have robust biomarkers to identify breast cancer patients who are at high risk of LR.

Currently, treatment decisions for early-stage breast cancer are based on parameters relating to the tumor, including size, margin status, grade and histological features (Solin et al. The significance of the pathology margins of the tumor excision on the outcome of patients treated with definitive irradiation for early stage breast cancer. Int J Radiat Oncol Biol Phys 1991 ; 21 :279-87; Smitt et al. The importance of the lumpectomy surgical margin status in long-term results of breast conservation. Cancer 1995; 76:259-67; Schnitt et al. The relationship between microscopic margins of resection and the risk of local recurrence in patients with breast cancer treated with breast-conserving surgery and radiation therapy. Cancer 1994; 74: 1746-51 ; Pittinger et al. Importance of margin status in outcome of breast- conserving surgery for carcinoma. Surgery 1994; 1 16:605-8; Neuschatz et al. Margin width as a determinant of local control with and without radiation therapy for ductal carcinoma in situ (DCIS) of the breast. Int J Cancer 2001 ; 96 Suppl:97-104; Silverstein et al. The influence of margin width on local control of ductal carcinoma in situ of the breast. N Engl J Med 1999; 340: 1455-61). Patient age also affects the risk of LR (Idvall et al. Histopathological and cell biological characteristics of ductal carcinoma in situ (DCIS) of the breast-a comparison between the primary DCIS and subsequent ipsilateral and contralateral tumours. Breast 2005; 14:290-7; Roka et al. High nuclear grade and negative estrogen receptor are significant risk factors for recurrence in DCIS. Eur J Surg Oncol 2004; 30:243-7; Huston and Simmons. Locally recurrent breast cancer after conservation therapy. Am J Surg 2005;

189:229-35; Silverstein et al. A prognostic index for ductal carcinoma in situ of the breast. Cancer 1996; 77:2267-74)).

Patients with large, high-grade tumors, excision margin < 1 mm, and diagnosed at a young age (<40 years old) are at the highest risk of developing recurrence. Moreover, gene expression profiling of tumors has been shown to separate breast cancers into distinct molecular subtypes with prognostic significance (Perou et al. Molecular portraits of human breast tumours. Nature 2000; 406:747-52; Sorlie et al. Repeated observation of breast tumor subtypes in independent gene expression data sets. Proc Natl Acad Sci U S A 2003;

100:8418-23; van ', V et al. Gene expression profiling predicts clinical outcome of breast cancer. Nature 2002; 415:530-6). Commercially available assays based on gene expression profiling, including Oncotype DX (Genomic Health, Redwood City, CA) and MammaPrint (Agendia, Amsterdam, the Netherlands), may provide useful prognostic information (Paik et al. A multigene assay to predict recurrence of tamoxifen-treated, node-negative breast cancer. N Engl J Med 2004;351 :2817-26; van d, et al. A gene-expression signature as a predictor of survival in breast cancer. N Engl J Med 2002; 347: 1999-2009). However, their value for predicting breast cancer local recurrence was not established (Nuyten et al, Predicting a local recurrence after breast-conserving therapy by gene expression profiling. Breast Cancer Res 2006; 8:R62; Kreike et al. Gene expression profiles of primary breast carcinomas from patients at high risk for local recurrence after breast-conserving therapy. Clin Cancer Res 2006; 12:5705-12; Kreike et al. Local recurrence after breast-conserving therapy in relation to gene expression patterns in a large series of patients. Clin Cancer Res 2009; 15:4181-90). Other studies have found that using a six-immunohistochemical biomarker panel (ER, PR, HER2, CK5/6, EGFR and Ki-67), breast tumors can be grouped into 6 molecular subtypes that have significantly different risk of local recurrence (Voduc et al. Breast cancer subtypes and the risk of local and regional relapse. J Clin Oncol 2010; 28: 1684-91; Millar et al.

Prediction of local recurrence, distant metastases, and death after breast-conserving therapy in early-stage invasive breast cancer using a five-biomarker panel. J Clin Oncol 2009;

27:4701-8).

While most previous studies focused on characterizing clinicopathologic features and tumor markers for the prediction of LR, relative little attention was given to investigations on molecular changes in normal tissue surrounding the tumor as additional biomarkers for identifying patients at high risk of LR. One promising candidate biomarker in the adjacent histologically normal tissues is telomere, the nucleoprotein complexes at the end of eukaryotic chromosomes. Telomeres are specialized structures that protect chromosome ends and are essential for maintaining genome integrity and stability (McEachern et al. Telomeres and their control. Annu Rev Genet 2000; 34:331-58). Telomere shortening is an early and common molecular alterations in epithelial cancers (Engelhardt et al. Telomerase and telomere length in the development and progression of premalignant lesions to colorectal cancer. Clin Cancer Res 1997; 3 : 1931-41 ; Kinouchi et al. Telomere shortening in the colonic mucosa of patients with ulcerative colitis. J Gastroenterol 1998; 33:343-8; O'Sullivan JN, et al. Chromosomal instability in ulcerative colitis is related to telomere shortening. Nat Genet 2002; 32:280-4; Bailey and Murnane Telomeres, chromosome instability and cancer. Nucleic Acids Res 2006; 34:2408-17; van Heek et al. Telomere shortening is nearly universal in pancreatic intraepithelial neoplasia. Am J Pathol 2002; 161 : 1541-7; Meeker et al. Telomere shortening is an early somatic DNA alteration in human prostate tumorigenesis. Cancer Res 2002; 62:6405-9; Meeker et al. Telomere length abnormalities occur early in the initiation of epithelial carcinogenesis. Clin Cancer Res 2004; 10:3317-26; Meeker Telomeres and telomerase in prostatic intraepithelial neoplasia and prostate cancer biology. Urol Oncol 2006; 24: 122-30; Zheng et al. Telomere attrition in cancer cells and telomere length in tumor stroma cells predict chromosome instability in esophageal squamous cell carcinoma: a genome-wide analysis. Cancer Res 2009; 69: 1604-14). Previous studies have found that very short telomere length is a common genetic alteration in pre-malignant breast lesions and early breast cancer cells (Meeker and Argani Telomere shortening occurs early during breast tumorigenesis: a cause of chromosome destabilization underlying malignant transformation? J Mammary Gland Biol Neoplasia 2004; 9:285-96; Meeker et al. Telomere shortening occurs in subsets of normal breast epithelium as well as in situ and invasive carcinoma. Am J Pathol 2004; 164:925-35), and the telomere length in tumor tissues correlate with stage and prognosis in breast cancer (Fordyce et al. Telomere content correlates with stage and prognosis in breast cancer. Breast Cancer Res Treat 2006; 99: 193-202). Furthermore, there are significant differences in telomere length in adjacent histologically normal tissues by the distance to tumor (Heaphy et al. Telomere DNA content and allelic imbalance demonstrate field cancerization in histologically normal tissue adjacent to breast tumors. Int J Cancer 2006; 1 19: 108-16.

It is therefore an object of the present invention to provide a method for assessing risk of cancer and risk of local recurrence of cancer.

It is also an object of the present invention to provide a method that uses telomere health to assess risk of cancer and risk of local recurrence of cancer.

It is also an object of the present invention to provide a method that uses telomere health to inform selection of cancer treatment and to direct cancer treatment.

BRIEF SUMMARY OF THE INVENTION

Disclosed are compounds, compositions, and methods useful for assessing the risk of local recurrence of cancer. The disclosed methods generally involve measuring or determining a telomere health parameter, such as telomere length variation, and comparing the telomere health parameter to a telomere reference health parameter. The telomere health parameter indicates whether the subject has an increased risk of local recurrence of cancer. The telomere health parameter can also indicate the relative increase in risk of local recurrence of cancer. As an example, the disclosed methods can involve measuring or determining a telomere length parameter, such as telomere length variation, and comparing the telomere length parameter to a reference telomere length parameter. The telomere length parameter indicates whether the subject has an increased risk of local recurrence of cancer. The telomere length parameter can also indicate the relative increase in risk of local recurrence of cancer.

In particular, disclosed are methods of assessing a subject comprising measuring a telomere length in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter to assess the health of normal epithelial cells surrounding the cancer cells, and comparing the telomere length parameter with a reference telomere length parameter that is generated from subjects who had no beast cancer local recurrence. The comparison indicates the risk of local recurrence of cancer in the subject. Also disclosed are methods of assessing a subject comprising measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter for the subject, and comparing the telomere length parameter with a reference telomere length parameter. Also disclosed are methods of assessing a subject comprising measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter for the cell, and comparing the telomere length parameter with a reference telomere length parameter.

Also disclosed are methods of treating a subject with cancer comprising measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter for the subject; comparing the telomere length parameter with a reference telomere length parameter, where the comparison indicates the risk of local recurrence of cancer in the subject; and treating the subject with a treatment selected based on the indicated risk of local recurrence of cancer. Also disclosed are methods of treating a subject with cancer comprising treating the subject with a treatment selected based on the indicated risk of local recurrence of cancer, where the risk of local recurrence of cancer was indicated by measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from the subject with cancer, thereby producing a telomere length parameter for the subject; and comparing the telomere length parameter with a reference telomere length parameter, where the comparison indicates the risk of local recurrence of cancer in the subject.

In some forms, the telomere length parameter can be telomere length variation (TLV).

In some forms, the reference telomere length parameter can be a reference telomere length variation. In some forms, the subject has an increased risk of local recurrence of cancer if the chromosome telomere length variation is less than the reference chromosome telomere length variation. In some forms, the smaller the telomere length variation of the cell from the subject the higher the risk of local recurrence of cancer. In some forms, the greater the telomere length variation of the cell from the subject the lower the risk of local recurrence of cancer.

In some forms, if the subject has a chromosome telomere length variation less than the reference chromosome telomere length variation and has a large tumor, the subject has a greater risk of local recurrence of cancer than a subject with a chromosome telomere length variation less than the reference chromosome telomere length variation and a small tumor. In some forms, if the subject has a chromosome telomere length variation less than the reference chromosome telomere length variation and has an estrogen receptor negative tumor, the subject has a greater risk of local recurrence of cancer than a subject with a chromosome telomere length variation less than the reference chromosome telomere length variation and an estrogen receptor positive tumor.

Also disclosed are methods of assessing a subject comprising measuring the telomere length variation in a group of normal epithelial cells from a subject with cancer, thereby producing a telomere length variation for the subject, and comparing the telomere length variation with a reference telomere length variation. The comparison indicates the risk of local recurrence of cancer in the subject. Also disclosed are methods of assessing a subject comprising measuring the length variation of two or more telomeres in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length variation for the subject, and comparing the telomere length variation with a reference telomere length variation. Also disclosed are methods of assessing a subject comprising measuring the length variation of two or more telomeres in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length variation for the cell, and comparing the telomere length variation with a reference telomere length variation. In some forms, the telomere length variation of all telomeres in the cell are measured. In some forms, the telomere length variation of all cells in the group are measured. In some forms, the telomere length variation of all telomeres in all cells of the group are measured. In some forms, the subject has an increased risk of local recurrence of cancer if the chromosome telomere length variation is less than the reference chromosome telomere length variation.

In some forms, the normal epithelial cell can be the same tissue type as the cancer. In some forms, the normal epithelial cell can appear morphologically normal. In some forms, the normal epithelial cell can be a normal epithelial cell adjacent to tumor. In some forms, the telomere length parameter of two or more telomeres in the cell can be measured. In some forms, the group of cells includes two or more cells. In some forms, the group of cells includes 20 or more cells. In some forms, the telomere length parameter can be measured in 20 or more normal epithelial cells adjacent to tumor from the subject.

In some forms, the reference telomere length parameter can be the telomere length parameter in at least one control cell from at least one control subject. In some forms, the reference telomere length parameter can be the median telomere length parameter of three or more control subjects. In some forms, the group of cells includes two or more cells. In some forms, the group of cells includes 20 or more cells. In some forms, the reference telomere length parameter can be based on the telomere length parameter measured in 20 or more control cells from each control subject. In some forms, the control cells can be the same tissue type as the normal epithelial cell. In some forms, the control subjects do not have cancer. In some forms, the subject has breast cancer. In some forms, the control subjects do not have local recurrence of cancer.

In some forms, measuring the length parameter of telomeres can be accomplished by obtaining a sample from the subject, where the sample is a cancer sample; performing telomere analysis on at least one normal epithelial cell from the cancer sample; and quantitating the telomere length parameter. In some forms, performing telomere analysis and quantitating the telomere length parameter can be accomplished by telomere quantitative fluorescent in situ hybridization (QT-FISH). In some forms, quantitating the telomere length parameter can be accomplished by totaling the fluorescent signal from telomere probes from each of the telomeres being measured.

The disclosed methods can further comprise selecting a treatment for the subject based on the indicated risk of local recurrence of cancer. The disclosed methods can further comprise treating the subject with a treatment selected based on the indicated risk of local recurrence of cancer. The disclosed methods can further comprise treating the subject with a more aggressive treatment if the subject has an increased risk of local recurrence of cancer. The disclosed methods can comprise treating the subject with a less aggressive treatment if the subject does not have an increased risk of local recurrence of cancer.

In some forms, the more aggressive treatment can be chemotherapy, radiation therapy, hormonal therapy, or a combination. In some forms, the less aggressive therapy can be surgery alone. In some forms, the treatment can be lumpectomy alone or with any combination of chemotherapy, radiation therapy, and hormonal therapy; or mastectomy alone of with any combination of lymph node dissection, chemotherapy, radiation therapy, and hormonal therapy.

In accordance with the purpose of this invention, as embodied and broadly described herein, this invention relates to methods for assessing cancer risk and risk of local recurrence of cancer based on parameters related to chromosomal telomere health.

Additional advantages of the disclosed methods will be set forth in part in the description which follows, and in part will be understood from the description, or may be learned by practice of the disclosed methods. The advantages of the disclosed methods will be realized and attained by means of the elements and combinations particularly pointed out in the appended claims. It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the invention as claimed.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate several embodiments of the disclosed method and compositions and together with the description, serve to explain the principles of the disclosed method and compositions.

Figure 1 shows a Kaplan-Meier survival curve of patients with high (top line) and low

(bottom line) telomere variation in normal epithelial cells adjacent to the tumor.

DETAILED DESCRIPTION OF THE INVENTION

A better understanding of the risk of local recurrence (LR) would facilitate therapeutic decision making in the management of early breast cancers. While previous studies focused on characterizing clinicopathologic features and tumor markers for the prediction of LR, little attention was given to the molecular changes in normal tissue surrounding the tumor as additional biomarkers for identifying patients at high risk of LR. It was discovered that changes in telomere length in the normal breast epithelial cells surrounding the tumor are associated with the risk of LR were examined.

The present discoveries revealed that telomere length variation in normal breast epithelial cells adjacent to tumor is significantly associated with breast cancer local recurrence. Patients who had large telomere length variation had significantly better 10-year recurrence free survival than patients who had small telomere length variation. Telomere length variation in normal epithelial cells adjacent to tumor can be used as a non-tumor related biomarker for predicting breast cancer local recurrence after breast conserving surgery.

It was discovered that telomere length variation in normal epithelial cells adjacent to tumor is significantly associated with breast cancer local recurrence. Patients who had large telomere length variation had significantly better 10-year recurrence free survival rate (80%) than patients who had small telomere length variation (33%). Telomere length variation in normal epithelial cells adjacent to tumor is a useful non-tumor-related biomarker for predicting breast cancer local recurrence after breast conserving surgery. Because effective treatment modalities exist for the locoregional control of breast cancer, robust biomarkers that can stratify patients into low/high risk group for local recurrence could profoundly affect the treatment of breast cancer.

The disclosed compositions and methods are based in part on the development of non- tumor cell-related molecular markers for better defining surgical margins and for

understanding the risk of local recurrence based on normal breast tissues surrounding the tumor. By using quantitative FISH, telomere length was measured at the individual cell level and calculated telomere length variation (CV%) as a novel phenotype, in addition to traditionally used average telomere length. Telomere length in infiltrative lymphocytes was used to normalize the hybridization variation and relative telomere length, defined as telomere length in cells of interest divided by telomere length of infiltrative lymphocytes, was used in case-control analysis.

A. Definitions

"Telomere health" or "chromosome telomere health" or like terms refers to one or more of a group of parameters that measure telomere health, including, for example, telomere length, telomere length variation among two or more telomeres, and frequency of extremely short or long telomeres.

"Overall telomere health" or like terms refers to a group of parameters that measure overall telomere health, including total telomere length, telomere length variation among the total telomeres in a typical cell of the type being assessed (there is a total of 92 chromosomal arms in a typical human cell, for example), and frequency of extremely short or long telomeres in a typical cell.

"Chromosome telomere health parameter" or "telomere health parameter" or like terms refers to a parameter of telomere health. Relative telomere health is an example of a telomere health parameter.

"Chromosome telomere reference health" or "telomere reference health" or like terms refers to a reference health of the chromosome telomere.

"Chromosome telomere reference health parameter" or "telomere reference health parameter" or like terms refers to a reference parameter of the health of the chromosome telomere.

"Telomere length" or "chromosome telomere length" or like terms refers to the direct or indirect length of a telomere of a chromosome arm. "Total telomere length" or like terms refers to the length, direct or indirect, or all of the telomeres in a cell. In the case of human cells, there are a total of 92 chromosomal arms in a typical human cell. As used herein, length can be, for example, absolute length or an indirect measurement of length as discussed herein.

"Overall telomere length variation" or "telomere length variation" or like terms refers to the coefficient of variation (CV) of the total telomere length in a cell among all of the cells examined. Overall telomere length variation is thus a measure of the variability of telomere lengths among a group of cells. "Reference overall telomere length variation" or "reference telomere length variation" or like terms refers to an overall telomere length variation established from a sample(s) from a subject(s) that is considered a control. A reference overall telomere length variation could be, for example, from healthy individuals, from non- cancerous patients, or from patients that do not have local recurrence of cancer. It is understood that the reference overall telomere length variation can be produced de novo or can be a number previously determined as a reference length.

"Chromosome telomere length parameter" or "telomere length parameter" or like terms refers to a parameter of telomere length. Relative telomere length and telomere length variation are examples of telomere length parameters.

"Reference chromosome telomere length" or "reference telomere length" or like terms refers to a reference length of the chromosome telomere.

"Reference chromosome telomere length parameter" or "reference telomere length parameter" or like terms refers to a reference parameter of the length of the chromosome telomere.

"Relative telomere length" (RTL) or "telomere ratio" or like terms refers to a ratio between the length of at least one telomere of one arm of a chromosome in a cell and the length of the reference nucleic acid sequences, such as the length of all the telomeres of a complete set of chromosome arms (N=92) in a typical human cell or the length of centromeric sequences of chromosome 2, etc. Thus, for example, a telomere ratio could be the signal from the short arm of chromosome X (that is Xp) to the signal of a reference nucleic acid sequence, that is, for example, signals from the telomeres of the 92 arms of the chromosomes from a typical human cell. This would be a chromosome Xp relative telomere length or chromosome Xp telomere ratio.

"CV (coefficient of variation)" or like terms is the percent of the standard deviation of a group of measurements divided by the average value of this group of measurements. For example, if the standard deviation of a group telomere lengths is 9600 and the average length of this group of telomeres is 19200, then the CV of these telomeres is 9600/19200* 100 = 50%. "Risk" or like terms refers to the chance, probability, likelihood, etc. that an event, characteristic, condition, etc. will be present or will occur. Risk can be expressed, for example, numerically, quantitatively, qualitatively, as a ratio, as a percentage, or in other appropriate ways. Risk can be expressed with or without reference to other subjects, states, averages, means, medians, reference values.

"Increased likelihood of local recurrence of cancer" or "increased risk of local recurrence of cancer" or like terms refers to an odds ratio as discussed herein where the condition is local recurrence of cancer. For example, it can be considered a fold likelihood relative to a group, such as a subject that has at least a 1.19, 5.13, or 22.2, fold increase relative to women with high telomere length variation in normal epithelial cells adjacent to tumor, at least a 2.68, 6.13, or 15.31, fold increase relative to women with high telomere length variation in normal epithelial cells adjacent to tumor, or at least a 1.53, 1.05, or 3.41, fold increase relative to women with high telomere length variation in distant normal epithelial cells.

"Odds ratio" (OR) or like terms refers to a ratio of the risk or odds that a subject or a group will have a characteristic or condition relative to another group. For example, a subject can be said to have an odds ratio of 3.0 relative to a group when the subject has a 3.0 fold greater risk or odds of having the characteristic or condition relative to the odds or risk of a subject in the group having the characteristic or condition.

"Adjusted odds ratio" (aOR) or like terms refers to an odds ratio that has taken into account other related factors, such as statistically adjusted, based on one or more

characteristics (such as demographic or lifestyle characteristics) obtained in a subject history from the subject the telomere ratio was obtained from.

"Local recurrence of cancer" or like terms refers to the return of symptoms and/or disease in the vicinity of a previously present disease. For example, if a tumor is removed from the breast and later on (days, months, years) another tumor appears in the general vicinity of the previous tumor, this is considered local recurrence of cancer.

"Large tumor" refers to those tumors that are greater than or equal to 1.5 cm.

"Small tumor" refers to those tumors that are less than 1.5 cm.

"Estrogen receptor negative tumor" refers to any tumor that does not express detectable levels of estrogen receptor.

"Estrogen receptor positive tumor" refers to any tumor that expresses detectable levels of estrogen receptor.

"Normal epithelial cell" refers to epithelial cells that appear morphologically normal. "Same tissue type as the cancer" or like terms refers to a tissue that originates from the same tissue type as the cancer. For example, normal breast tissue or non-cancerous breast tissue is the same tissue type as breast cancer or breast cancer tumor.

"Adjacent normal epithelial cell" or "normal epithelial cell adjacent to tumor" or like terms refers to normal epithelial cells found next to or very close to a cancer cell.

"Control cell" or like terms refer to cells that are used as controls to cells that are assessed or analyzed. One example of control cells are those cells taken from a control subject. As another example, control cells can be normal, healthy, and/or non-cancerous cells or tissue in the subject being tested. Control cells can also be any cells that are not subjected to the experiment, but are instead subjected to a defined set of parameters, or the control cells are based on pre- or post-treatment levels. They can either be run in parallel with or before or after a test run, or they can be a pre-determined standard. Control cells can be used to determine the presence, absence or risk of cancer. For example, reference telomere length can be measured in a control cell and compared to the reference telomere length of a cell being examined. In certain circumstances once a control cell has been tested or measured, it can be used as a standard, in which the control experiment does not have to be performed again. In other circumstances the control cells can be tested in parallel each time a comparison will be made.

"Control subject" refers to subjects that are used as controls to subjects that are assessed or analyzed. For example, control subjects can be those subjects that are normal, healthy, and/or non-cancerous or are not subjected to any testing or treatment. As another example, control subjects can be subjects that do not have local recurrence of cancer. Control subjects can also be subjects pre- or post-treatment.

"Cancer sample" refers to any material or substance from an individual or patient that contains cancer cells or tissue. For example, the sample can be blood, serum, cells, tissue, urine or any other type of fluid.

"Selecting a treatment" refers to selecting, identifying, or designing a treatment. The selection of a treatment is based on the circumstances. For example, a treatment can be selected based on symptoms or biomarkers. A trained professional, such as a doctor or medical professional, can be responsible for selecting a treatment.

"Treatment selected based on the indicated risk of local recurrence of cancer" or like terms refers to selecting a treatment based on the risk of a local recurrence of cancer. That is, the treatment is, at least in part, selected based on or because of the indicated risk of local recurrence of cancer. The risk can be assessed in a variety of ways, such as the disclosed methods. One way in particular is based on the telomere length variation.

"More aggressive treatment" or like terms refers to an increased, stronger, or more effective treatment compared to the previous treatment or compared to what would typically be used. For example, if there is an indication that a subject has an increased risk of cancer recurrence, a more aggressive treatment may be beneficial over the typical treatment. More aggressive treatments can have increased side effects but the therapeutic benefit is more effective.

"Less aggressive treatment" or like terms refers to a decreased or weaker treatment compared to the previous treatment or compared to what would typically be used. For example, if there is an indication that a subject has a decreased risk of cancer recurrence, or does not have an increased risk of cancer recurrence, a less aggressive treatment can be used.

"Lumpectomy" refers to the removal or excision of a lump from a subject's breast. The removal can be a surgical procedure. The lump can be benign or cancerous tissue or cells. A lumpectomy can remove the lump as well as a surrounding border of normal or healthy tissue.

"Chemotherapy" is a standard treatment for cancer. It refers to the use of anticancer drugs, known as chemotherapeutics, to treat or destroy cancer cells.

"Radiation therapy" is a standard treatment for controlling unresectable or inoperable tumors and/or tumor metastases. Radiation therapy can be a high-dose radiation delivered to a target area that will result in the death of reproductive cells in both tumor and normal tissues. Radiation therapy can be days, weeks or months.

"Hormonal therapy" refers to the treatment of a subject by adding, blocking or removing one or more hormones. For example, some breast cancer cells proliferate in response to estrogen and therefore a hormonal therapy of blocking estrogen is the ideal treatment.

"Mastectomy" refers to the partial or complete surgical removal of the breast. One or both breasts can be removed. Mastectomies can be used to treat or prevent breast cancer. "Lymph node dissection" refers to the surgical removal of one or more lymph nodes. The dissected lymph nodes can be used to determine if any cancer cells are present in the lymph nodes.

"Measuring the length of the chromosome telomere" or "measuring telomere length" or "quantitating telomere length" or like terms refers to determining the length of a chromosome telomere by any means, including by directly measuring, such as by determining the number of bases or repeats or other physical ways of quantifying the absolute length of a telomere, as well as by indirectly measuring the length. An indirect measurement of the length refers to measuring something that is a substitute or related or correlated to length, such as the amount of a telomere marker bound to a telomere, or the amount of signal arising from a telomere marker bound to a telomere, such as the amount of fluorescence bound to a telomere via a telomere marker.

Telomere length can be measured by, for example, quantifying the fluorescence using TeloMeter, which is a program that is freely available from John Hopkins University website (internet site bui2.win.ad.jhu.edu/telometer/) or quantitating can arise from the commercially available Isis image software from Metasystems (website www.metasystems.com/).

Telomere length can be expressed in any suitable form. For example, telomere length can be expressed as a number of nucleotides, as a number of telomere sequence repeats, as a length by reference to a standard such as the meter, as a signal or value form an indirect measurement, etc.

It is understood that a single telomere or arm of a telomere can be measured, multiple telomeres can be measured, a specific number or set of telomeres can be measured, etc., up to and including all of the telomeres of each chromosome of a cell of a subject. There are 23 pairs of chromosomes, 46 individual chromosomes, 92 chromosomal arms, and 92 telomeres in a typical human cell.

"Indirect measurement" or like terms refer to a measurement that is representative of something else. For example, the amount of fluorescence signal arising from bound fluorescently labeled probe on a telomere of a chromosome arm is an indirect measurement of the length or the telomere of that chromosome arm.

"Reference length" or like terms refers to a length established from a sample(s) from a subject(s) that is considered a control. A reference length could be, for example, from healthy individuals or from non-cancerous patients. It is understood that the reference length can be produced de novo or can be a number previously determined as a reference length. For example, reference chromosome telomere length can be the average chromosome telomere length in cells from normal subjects of similar type to the cell being assessed, reference chromosome telomere length can be the average chromosome telomere length of the chromosome being assessed in cells from normal subjects of similar type to the cell being assessed, and chromosome reference chromosome telomere length can be the average arm- specific telomere length in cells from normal subjects of similar type to the cell being assessed. "Reference telomere parameters" or like terms refers to a telomere parameters that are produced from a sample(s) from a subject(s) that is considered a control. For example, the sample(s) could be from healthy individuals or from non-cancerous patients. It is understood that the reference telomere parameters can be produced de novo or can be a number previously determined as a reference number.

"Telomere marker" or like terms refers to any molecule or substance that interacts preferentially with a telomere relative to another region of a chromosome. A telomere marker could be, for example, a hybridization probe for a telomere, such as fluorescent labeled telomere sequences of certain length, such as 18 base pairs.

"Shorter" or "shorter length" or like terms refers to, in the context of nucleic acids, chromosomes, telomeres, etc., fewer nucleotides. One nucleic acid, such as a chromosome or a telomere of a chromosome, would be shorter than another nucleic acid if it has at least one fewer nucleotide. "Detectably shorter" or like terms refers to, in the context of nucleic acids, chromosomes, telomeres, etc., detectably fewer nucleotides. Detectably shorter generally is in the context of the manner in which length is measured since different ways of measuring can have different thresholds of detectability.

How much shorter a nucleic acid is than another nucleic acid can be represented by, for example, referring to the representative length of the two nucleic acids as less than or equal to 0.000001, 0.00001, 0.0001, 0.001, 0.01, 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, or 0.95 of the length of one or the other nucleic acid. For example, a nucleic acid that is 900 bases long is 0.9 the length of a nucleic acid that is 1000 bases long.

"Longer" or "longer length" or like terms refers to, in the context of nucleic acids, chromosomes, telomeres, etc., more nucleotides. One nucleic acid, such as a chromosome or a telomere of a chromosome, would be longer than another nucleic acid if it has at least one more nucleotide. "Detectably longer" or like terms refers to, in the context of nucleic acids, chromosomes, telomeres, etc., detectably more nucleotides. Detectably longer generally is in the context of the manner in which length is measured since different ways of measuring can have different thresholds of detectability.

How much longer a nucleic acid is than another nucleic acid can be represented by, for example, referring to the representative length of the two nucleic acids as greater than or equal to 100,000, 10,000, 1,000, 100, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1.9, 1.8, 1.7, 1.6, 1.5, 1.4, 1.3, 1.2, 1.1, 1.09, 1.08, 1.07, 1.06, 1.05, 1.04, 1.03, 1.02, 1.01 of the length of one or the other nucleic acid. For example, a nucleic acid that is 1100 bases long is 1.1 the length of a nucleic acid that is 1000 bases long. "Greater" or like terms refers to more of something than in a comparison value, composition, component, etc. Various measures can be greater than other measures. For example, telomere health, length, such as telomere length, variation, such as variation of telomere length, average, mean, median, deviation, standard deviation, etc. can be measures that are greater than comparison measures. Telomere health would be greater than a comparison telomere health if a measure of telomere health is greater for the telomere than for the measure of telomere health for the comparison telomere. Variation in telomere length would be greater than a comparison variation in telomere length if a measure of variation is greater for the telomere length than for the measure of variation for the comparison telomere length.

"Less" or like terms refers to less or fewer of something than in a comparison value, composition, component, etc. Various measures can be less than other measures. For example, telomere health, length, such as telomere length, variation, such as variation of telomere length, average, mean, median, deviation, standard deviation, etc. can be measures that are less than comparison measures. Telomere health would be less than a comparison telomere health if a measure of telomere health is less for the telomere than for the measure of telomere health for the comparison telomere. Variation in telomere length would be less than a comparison variation in telomere length if a measure of variation is less for the telomere length than for the measure of variation for the comparison telomere length.

"Higher variation" or like terms refers to higher variability in length among a group of measured telomeres. For example, in a group of measured telomeres, if some telomeres are very long and some are very short, then, telomere length variation will be high. In contrast, if all measured telomeres have similar length, then telomere length variation will be low.

How much higher the telomere variation of one group of telomeres is than the telomere variation of another group of telomeres can be represented by referring to the representative measures of two groups of telomeres as less than or equal to 0.1%, 1%, 10%, 20%, 30%, 40%, 50%, 60%, 70%. 80%, 90%, 100%, 200%, 300%, 400%, 500%, 600%, 700%, 800%, 900%, 1000% of the CV of a group or the other group of the telomeres. For example, a group of telomeres that have 60% CV is 10% higher in telomere length variation than a group of telomeres that have 50% CV.

"Subject" or like terms refers to an individual. Thus, the "subject" can include, for example, domesticated animals, such as cats, dogs, etc., livestock (e.g., cattle, horses, pigs, sheep, goats, etc.), laboratory animals (e.g., mouse, rabbit, rat, guinea pig, etc.) mammals, non-human mammals, primates, non-human primates, rodents, birds, reptiles, amphibians, fish, and any other animal. The subject can be a mammal such as a primate or a human. The subject can also be a non-human.

"Sample" or like terms refers to an animal, a plant, a fungus, etc.; a natural product, a natural product extract, etc.; a tissue or organ from an animal; a cell (either within a subject, taken directly from a subject, or a cell maintained in culture or from a cultured cell line); a cell lysate (or lysate fraction) or cell extract; or a solution containing one or more molecules derived from a cell or cellular material (e.g. a polypeptide or nucleic acid), which is assayed as described herein. Useful samples include cancer samples, tissue samples, and organ samples.

"Cancer" or "cancerous" or like terms refer to or describe the physiological condition in mammals in which a population of cells are characterized by unregulated cell growth. Examples of cancer include, but are not limited to, carcinoma, lymphoma, blastoma, sarcoma, and leukemia. More particular examples of such cancers include breast cancer, squamous cell cancer, small-cell lung cancer, non-small cell lung cancer, adenocarcinoma of the lung, squamous carcinoma of the lung, cancer of the peritoneum, hepatocellular cancer, gastrointestinal cancer, pancreatic cancer, glioblastoma, cervical cancer, ovarian cancer, liver cancer, bladder cancer, hepatoma, colon cancer, colorectal cancer, endometrial or uterine carcinoma, salivary gland carcinoma, kidney cancer, liver cancer, prostate cancer, vulval cancer, thyroid cancer, hepatic carcinoma and various types of head and neck cancer.

"Treatment" or "treating" or like terms refer to the medical management of a subject with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder. This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder. In addition, this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder. It is understood that treatment, while intended to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder, need not actually result in the cure, ameliorization, stabilization or prevention. The effects of treatment can be measured or assessed as described herein and as known in the art as is suitable for the disease, pathological condition, or disorder involved. Such measurements and assessments can be made in qualitative and/or quantitative terms. Thus, for example, characteristics or features of a disease, pathological condition, or disorder and/or symptoms of a disease, pathological condition, or disorder can be reduced to any effect or to any amount.

"Patient history" or "subject history" or like terms refers to one or more items in the history of a subject which could be considered relevant to the subject, such as race, age, gender, physical status, such as pre- or post-menopausal, pregnant, diabetic, overweight or obese, smoking, alcohol consumption, family cancer history, or like items.

"Preventive treatment" or "preventative intervention" or like terms for cancer refer to current or future preventive treatment regimes or protocols that are designed to reduce the likelihood of a subject getting a disease or condition or of a subject suffering a recurrence of the disease or condition. In the context of cancer, preventative treatments include current or future preventive treatment regimes or protocols that are designed to reduce the likelihood of a subject getting cancer. Current preventative treatment regimes are those in use by physicians or health care organization. For example, Tamoxifen is prescribed for women who are at high risk of breast cancer or bilateral surgically removal of ovaries are used to reduce the breast or ovarian cancer if a women is at very high risk of breast cancer, i.e., BRCA1 mutation carriers. Preventive treatment/intervention for cancer also refers to clinical protocols to monitor an individual who is at high risk of getting cancer more closely to detect a cancer early. A patient whose cancer is detected in an early stage usually has a better change of cure and survival.

"Fluorescent" or like terms refers to luminescence that is caused by the absorption of radiation at one wavelength followed by nearly immediate reradiation usually at a different wavelength and that ceases almost at once when the incident radiation stops, as understood in the art.

"Mimic" or like terms refers to performing one or more of the functions of a reference object. For example, a molecule mimic performs one or more of the functions of a molecule.

"Obtaining" or like terms refers to getting or acquiring. For example, obtaining a sample includes taking a sample physically from a subject and it also includes receiving a sample which someone else took from a subject, which was for example, stored. Thus, obtaining includes but is not limited to physically collecting a sample.

"Optional" or "optionally" or like terms means that the subsequently described event or circumstance can or cannot occur, and that the description includes instances where the event or circumstance occurs and instances where it does not. For example, the phrase "optionally the composition can comprise a combination" means that the composition may comprise a combination of different molecules or may not include a combination such that the description includes both the combination and the absence of the combination (i.e., individual members of the combination).

The singular forms "a," "an" and "the" or like terms include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to "a pharmaceutical carrier" includes mixtures of two or more such carriers, and the like.

Abbreviations, which are well known to one of ordinary skill in the art, may be used; for example, "h" or "hr" for hour or hours, "g" or "gm" for gram(s), "mL" for milliliters, and "rt" for room temperature, "nm" for nanometers, "M" for molar, and like abbreviations.

"About" modifying, for example, length, ratio, the quantity of an ingredient in a composition, concentrations, volumes, process temperature, process time, yields, flow rates, pressures, and like values, and ranges thereof, refers to variation in the numerical quantity that can occur, for example, through typical measuring and handling procedures used for making compounds, compositions, concentrates or use formulations; through inadvertent error in these procedures; through differences in the manufacture, source, or purity of starting materials or ingredients used to carry out the methods; and like considerations. The term "about" also encompasses amounts that differ due to aging of a composition or formulation with a particular initial concentration or mixture, and amounts that differ due to mixing or processing a composition or formulation with a particular initial concentration or mixture. Whether modified by the term "about" the claims appended hereto include equivalents to these quantities.

The word "or" or like terms means any one member of a particular list and also includes any combination of members of that list.

Specific and preferred values disclosed for lengths, ratios, components, compounds, levels, and like aspects, and ranges thereof, are for illustration only; they do not exclude other defined values or other values within defined ranges. The compositions, apparatus, and methods of the disclosure include those having any value or any combination of the values, specific values, more specific values, and preferred values described herein.

Ranges can be expressed herein as from "about" one particular value, and/or to

"about" another particular value. When such a range is expressed, other forms include from the one particular value and/or to the other particular value. Similarly, when values are expressed as approximations, by use of the antecedent "about," it will be understood that the particular value forms another form. It will be further understood that the endpoints of each of the ranges are significant both in relation to the other endpoint, and independently of the other endpoint. It is also understood that there are a number of values disclosed herein, and that each value is also herein disclosed as "about" that particular value in addition to the value itself. For example, if the value "10" is disclosed, then "about 10" is also disclosed. It is also understood that when a value is disclosed that "less than or equal to" the value,

"greater than or equal to the value" and possible ranges between values are also disclosed, as appropriately understood by the skilled artisan. For example, if the value "10" is disclosed the "less than or equal to 10"as well as "greater than or equal to 10" is also disclosed. It is also understood that the throughout the application, data is provided in a number of different formats, and that this data, represents endpoints and starting points, and ranges for any combination of the data points. For example, if a particular data point "10" and a particular data point 15 are disclosed, it is understood that greater than, greater than or equal to, less than, less than or equal to, and equal to 10 and 15 are considered disclosed as well as between 10 and 15. It is also understood that each unit between two particular units are also disclosed. For example, if 10 and 15 are disclosed, then 1 1, 12, 13, and 14 are also disclosed.

"Comprise" and variations of the word, such as "comprising" and "comprises," means "including but not limited to," and is not intended to exclude, for example, other additives, components, integers or steps.

"Consisting essentially of refers to, for example, the stated subject matter plus other components or steps that do not materially affect the basic and novel properties of the stated subject matter.

Throughout this application, various publications are referenced. The disclosures of these publications in their entireties are hereby incorporated by reference into this application in order to more fully describe the state of the art to which this pertains. The references disclosed are also individually and specifically incorporated by reference herein for the material contained in them that is discussed in the sentence in which the reference is relied upon. Nothing herein is to be construed as an admission that the present invention is not entitled to antedate such disclosure by virtue of prior invention. No admission is made that any reference constitutes prior art. The discussion of references states what their authors assert, and applicants reserve the right to challenge the accuracy and pertinency of the cited documents. It will be clearly understood that, although a number of publications are referred to herein, such reference does not constitute an admission that any of these documents forms part of the common general knowledge in the art. The disclosed methods, compositions, articles, and machines, can be combined in a manner to comprise, consist of, or consist essentially of, the various components, steps, molecules, and composition, and the like, discussed herein.

Disclosed are the components to be used to prepare the disclosed compositions as well as the compositions themselves to be used within the methods disclosed herein. These and other materials are disclosed herein, and it is understood that when combinations, subsets, interactions, groups, etc. of these materials are disclosed that while specific reference of each various individual and collective combinations and permutation of these molecules may not be explicitly disclosed, each is specifically contemplated and described herein. Thus, if a class of molecules A, B, and C are disclosed as well as a class of molecules D, E, and F and an example of a combination molecule, A-D is disclosed, then even if each is not individually recited each is individually and collectively contemplated meaning

combinations, A-E, A-F, B-D, B-E, B-F, C-D, C-E, and C-F are considered disclosed.

Likewise, any subset or combination of these is also disclosed. Thus, for example, the sub- group of A-E, B-F, and C-E would be considered disclosed. This concept applies to all aspects of this application including, but not limited to, steps in methods of making and using the disclosed compositions. Thus, if there are a variety of additional steps that can be performed it is understood that each of these additional steps can be performed with any specific embodiment or combination of embodiments of the disclosed methods.

Compounds and compositions have their standard meaning in the art. It is understood that wherever a particular designation, such as a molecule, substance, marker, cell, or reagent is disclosed, compositions comprising, consisting of, and consisting essentially of these designations are also disclosed.

Unless defined otherwise, all technical and scientific terms used herein have the same meanings as commonly understood by one of skill in the art to which the disclosed method and compositions belong. It is understood that the disclosed method and compositions are not limited to the particular methodology, protocols, and reagents described as these may vary. Although any methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present method and compositions, the particularly useful methods, devices, and materials are as described.

Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the method and compositions described herein. Such equivalents are intended to be encompassed by the following claims. B. Telomeres

Telomeres are specialized DNA-protein structures that cap the ends of linear chromosomes. They are crucial for protecting linear chromosomes and are essential for maintaining the integrity and stability of genomes (McEachern et al. Annu. Rev Genet, 34:331-358, 2000). Telomere-induced chromosomal instability could drive the tumorigenic process by increasing mutation rates for oncogenes and tumor suppressor genes (Maser et al. Science, 297:565-569, 2000).

Disclosed herein, a case-control study of breast cancer, examining telomere length variation in several cell types in and around tumors, showed that telomere length variation in normal epithelial cells adjacent to tumor is significantly associated with breast cancer local recurrence. Patients who had large telomere length variation had significantly better 10-year recurrence free survival rate (80%) than patients who had small telomere length variation (33%).

C. Samples

The disclosed methods use samples that include cells in order to assess telomere health and length parameters. Useful samples include tissue samples, especially tumor biopsies and biopsies from patients with cancer. Numerous methods and techniques are known for obtaining, preparing, storing, and using biological, cell, and tissue samples, and such methods and techniques can be used with the disclosed methods. Samples can be obtained by taking a sample physically from a subject or receiving a sample which someone else took from a subject and which was, for example, stored. Generally, cell and tissue samples for use in the disclosed methods can be obtained form cancer and tumor biopsies, including cell and tissue samples from tumor resection. Such samples preferably will include normal epithelial cells adjacent to a tumor.

Samples should be obtained from subjects having cancer. Such subjects can be subjects in which the risk of local recurrence of cancer is to be assessed. Human subjects are most preferred for the disclosed methods, but samples can also be obtained from other subjects.

D. Nucleic Acids

There are a variety of molecules disclosed herein that are nucleic acid based. For example, nucleic acid based probes can be used to detect, measure, and quatitate telomeres and telomere parameters. The disclosed nucleic acids can be made up of for example, nucleotides, nucleotide analogs, or nucleotide substitutes. Non-limiting examples of these and other molecules are discussed herein. It is understood, for example, that when a vector is expressed in a cell, the expressed mRNA will typically be made up of A, C, G, and U.

Likewise, it is understood that if a nucleic acid molecule is used in a cell or cell environment, it is advantageous that the nucleic acid molecule be made up of nucleotide analogs that reduce the degradation of the antisense molecule in the cellular environment.

1. Probes

Disclosed are compositions including probes, which are capable of interacting with, for example, chromosomes, centromeres, and telomeres. Typically the disclosed probes hybridize with the nucleic acid or region of the nucleic acid or they hybridize with the complement of the nucleic acid or complement of a region of the nucleic acid. For detection and quantitation, probes can have detectable labels. Myriad moieties, compounds, and molecules are known that can be used as detectable labels on nucleic acid based probes.

For detection and quantitation of telomeres, probes that can hybridize specifically to telomere sequences are useful. Telomeres in all vertebrate cells consist of noncoding G-rich hexanucleotide (TTAGGG)_n repeats. Thus, probes that can hybridize to this sequence and repeats of this sequence are useful. To quantitate telomere length, it is useful to have probes that hybridize along the length of telomeres and produce a signal proportional to the number of hexanucleotide repeats. For example, a probe complementary to three repeats (CCCTAA)3 can produce good results.

Preferred probes for use in the disclosed methods can be peptide nucleic acid probes. United States patents 5,539,082; 5,714,331; and 5,719,262 teach how to make and use PNA molecules, each of which is herein incorporated by reference. See also Nielsen et al, Science 254: 1497-1500 (1991).

2. Nucleotides and related molecules

A nucleotide is a molecule that contains a base moiety, a sugar moiety and a phosphate moiety. Nucleotides can be linked together through their phosphate moieties and sugar moieties creating an internucleoside linkage. The base moiety of a nucleotide can be adenin-9-yl (A), cytosin-l-yl (C), guanin-9-yl (G), uracil- 1-yl (U), and thymin-l-yl (T). The sugar moiety of a nucleotide is a ribose or a deoxyribose. The phosphate moiety of a nucleotide is pentavalent phosphate. A non-limiting example of a nucleotide would be 3'- AMP (3'-adenosine monophosphate) or 5'-GMP (5'-guanosine monophosphate).

A nucleotide analog is a nucleotide which contains some type of modification to the base, sugar, or phosphate moieties. Modifications to nucleotides are well known in the art and would include for example, 5-methylcytosine (5-me-C), 5 -hydroxy methyl cytosine, xanthine, hypoxanthine, and 2-aminoadenine as well as modifications at the sugar or phosphate moieties.

Nucleotide substitutes are molecules having similar functional properties to nucleotides, but which do not contain a phosphate moiety, such as peptide nucleic acid (PNA). Nucleotide substitutes are molecules that will recognize nucleic acids in a Watson- Crick or Hoogsteen manner, but which are linked together through a moiety other than a phosphate moiety. Nucleotide substitutes are able to conform to a double helix type structure when interacting with the appropriate target nucleic acid.

It is also possible to link other types of molecules (conjugates) to nucleotides or nucleotide analogs to enhance for example, cellular uptake. Conjugates can be chemically linked to the nucleotide or nucleotide analogs. Such conjugates include but are not limited to lipid moieties such as a cholesterol moiety (Letsinger et al, Proc. Natl. Acad. Sci. USA, 1989, 86, 6553-6556).

A Watson-Crick interaction is at least one interaction with the Watson-Crick face of a nucleotide, nucleotide analog, or nucleotide substitute. The Watson-Crick face of a nucleotide, nucleotide analog, or nucleotide substitute includes the C2, Nl, and C6 positions of a purine based nucleotide, nucleotide analog, or nucleotide substitute and the C2, N3, C4 positions of a pyrimidine based nucleotide, nucleotide analog, or nucleotide substitute.

A Hoogsteen interaction is the interaction that takes place on the Hoogsteen face of a nucleotide or nucleotide analog, which is exposed in the major groove of duplex DNA. The Hoogsteen face includes the N7 position and reactive groups (NH2 or O) at the C6 position of purine nucleotides.

3. Sequences

There are a variety of sequences related to telomeres disclosed herein that are disclosed on Genbank, and these sequences and others are herein incorporated by reference in their entireties as well as for individual subsequences contained therein.

A variety of sequences are provided herein and these and others can be found in Genbank, at webpage www.pubmed.gov. Those of skill in the art understand how to resolve sequence discrepancies and differences and to adjust the compositions and methods relating to a particular sequence to other related sequences. Primers and/or probes can be designed for any sequence given the information disclosed herein and known in the art.

E. Cancer

The tumor of the disclosed methods can be a breast cancer. Thus, the breast tumor can be ductal carcinoma in situ (DCIS), lobular carcinoma in situ (LCIS), infiltrating ductal carcinoma (IDC), infiltrating lobular carcinoma (ILC), medullary carcinoma, inflammatory breast cancer (IBC), tubular carcinoma (TC), colloid carcinoma, metaplastic carcinoma, papillary carcinoma, adenoid cystic carcinoma (ACC), secretory carcinoma, or Paget' s disease of the breast. The breast tumor can be estrogen receptor-negative, progesterone receptor-negative, and HER2-negative (triple-negative breast cancer).

Breast cancers are described along four different classification schemes, or groups, each based on different criteria and serving a different purpose: pathology, grade of tumor, protein & gene expression status, and stage of a tumor.

A pathologist can categorize each tumor based on its histological (microscopic anatomy) appearance and other criteria. The most common pathologic types of breast cancer are invasive ductal carcinoma, malignant cancer in the breast's ducts, and invasive lobular carcinoma, malignant cancer in the breast's lobules. The histological grade of a tumor is determined by a pathologist under a microscope. A well-differentiated (low grade) tumor resembles normal tissue. A poorly differentiated (high grade) tumor is composed of disorganized cells and, therefore, does not look like normal tissue. Moderately differentiated (intermediate grade) tumors are somewhere in between.

Breast cancers can be tested for expression, or detectable effect, of the estrogen receptor (ER), progesterone receptor (PR) and HER2/neu proteins. These tests can be done by immunohistochemistry. The profile of expression of a given tumor helps predict its prognosis, or outlook, and helps an oncologist choose the most appropriate treatment. As disclosed herein, the amount of Bcl-B expression in the cancer cells or the number, or percentage of cells with detectable Bcl-B expression can further be used to predict the prognosis and guide the oncologist to choose the most appropriate treatment.

The currently accepted staging scheme for breast cancer is the TNM classification: Tumor, lymph Node, and Metastases. There are five tumor classification values (Tis, Tl, T2, T3 or T4) which depend on the presence or absence of invasive cancer, the dimensions of the invasive cancer, and the presence or absence of invasion outside of the breast (e.g. to the skin of the breast, to the muscle or to the rib cage underneath). There are four lymph node classification values (NO, Nl, N2 or N3) which depend on the number, size and location of breast cancer cell deposits in lymph nodes. There are two metastatic classification values (M0 or Ml) which depend on the presence or absence of breast cancer cells in locations other than the breast and lymph nodes (so-called distant metastases, e.g. to bone, brain, lung).

Breast cancer is diagnosed by the examination of surgically removed breast tissue. A number of procedures can obtain tissue or cells prior to definitive treatment for histological or cytological examination. Such procedures include fine-needle aspiration, nipple aspirates, ductal lavage, core needle biopsy, and local surgical excision. These diagnostic steps, when coupled with radiographic imaging, are usually accurate in diagnosing a breast lesion as cancer. Occasionally, pre-surgical procedures such as fine needle aspirate may not yield enough tissue to make a diagnosis, or may miss the cancer entirely. Imaging tests are sometimes used to detect metastasis and include chest X-ray, bone scan, Cat scan, MRI, and PET scanning. While imaging studies are useful in determining the presence of metastatic disease, they are not in and of themselves diagnostic of cancer. Only microscopic evaluation of a biopsy specimen can yield a cancer diagnosis. Ca 15.3 (carbohydrate antigen 15.3, epithelial mucin) is a tumor marker determined in blood which can be used to follow disease activity over time after definitive treatment. Blood tumor marker testing is not routinely performed for the screening of breast cancer, and has poor performance characteristics for this purpose.

The mainstay of breast cancer treatment is surgery when the tumor is localized, with possible adjuvant hormonal therapy (with tamoxifen or an aromatase inhibitor),

chemotherapy, and/or radiotherapy. At present, the treatment recommendations after surgery (adjuvant therapy) follow a pattern. Depending on clinical criteria (age, type of cancer, size, metastasis) patients are roughly divided to high risk and low risk cases, with each risk category following different rules for therapy. Treatment possibilities include radiation therapy, chemotherapy, radiation therapy, hormone therapy, and immune therapy. The disclosed methods are useful for identifying patients that can benefit from more aggressive treatment (including adjuvant treatments, for example) and which patients can be spared aggressive treatments.

Radiation has dramatically altered the management of primary breast cancer. Breast conservation, using lumpectomy and radiation therapy, is the treatment of choice in early- stage breast cancer. Cosmetic results are good in most patients, and survival is not compromised. Many patients with locally advanced breast cancer show improvement in local control with radiotherapy, and there is increased survival following radiation. The disclosed methods can be used to guide the selection of the appropriate therapy.

Local recurrence of breast cancer is common. Two-thirds of the breast cancers that come back in the same breast return to the same place, or right near the original cancer. The other third are new cancers. Breast cancer in a separate part of the same breast, or in the other breast, is usually a new cancer. It is not a reoccurrence, but a new first occurrence. About one-third of local breast cancer recurrences are found by mammography alone. Another third are found by physical exam (either a breast self exam or a doctor's examination) alone. And about one-third are found by a combination of mammography and physical exam. About 80% of women who develop a recurrence in the breast have no signs of the cancer elsewhere in their bodies. Local recurrence can follow any form of surgery (lumpectomy, mastectomy, lymph node resection).

Breast cancer, like most human malignancies, is characterized by short or extremely long telomere in tumor cells and chromosomal instability (Baudis BMC Cancer 7:226, 2007; Shih et al. Cancer Res 61 :818-822, 2001 ; Michor et al. Semin Cancer Biol 15:43-49, 2005). It is documented that chromosomal instability preferentially involves specific chromosome arms for each type of human cancer (Baudis BMC Cancer 7:226, 2007). In breast cancer, frequent chromosomal abnormalities in early stage breast tumors involves a few

chromosomal arms, including gains of lq, 8q, 17q, and 20q, and losses of 8p, 9p, 16q and 17p (Baudis BMC Cancer 7:226, 2007; Gorgoulis et al. Mol Med 4:807-822, 1998; An et al. Genes Chromosomes Cancer 17: 14-20, 1996).

Breast cancer, like most human malignancies, is characterized by chromosomal instability (CI ) (Baudis BMC Cancer 7:226, 2007). CIN is featured by losses or gains of entire chromosomes or chromosomal fragments, resulting in aneuploidy, large deletions or gains, and chromosomal rearrangements. CIN is observed as an early event in tumorigenesis (Shih et al. Cancer Res 61 :818-822, 2001 ; Michor et al. Semin Cancer Biol 15:43-49, 2005) and there is abundant evidence of correlation between increasing chromosomal abnormalities and greater tumor aggressiveness. However, the molecular defects underlying CIN, and whether CIN is a cause or a consequence of the malignant phenotype, are not clear.

F. Methods for Cancer Assessment

Disclosed are methods useful for assessing the risk of local recurrence of cancer. The disclosed methods generally involve measuring or determining a telomere health parameter, such as telomere length variation, and comparing the telomere health parameter to a telomere reference health parameter. The telomere health parameter indicates whether the subject has an increased risk of local recurrence of cancer. The telomere health parameter can also indicate the relative increase in risk of local recurrence of cancer. As an example, the disclosed methods can involve measuring or determining a telomere length parameter, such as telomere length variation, and comparing the telomere length parameter to a reference telomere length parameter. The telomere length parameter indicates whether the subject has an increased risk of local recurrence of cancer. The telomere length parameter can also indicate the relative increase in risk of local recurrence of cancer. In particular, disclosed are methods of assessing a subject comprising measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter for the subject, and comparing the telomere length parameter with a reference telomere length parameter. The comparison indicates the risk of local recurrence of cancer in the subject. Also disclosed are methods of assessing a subject comprising measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter for the cell, and comparing the telomere length parameter with a reference telomere length parameter.

Also disclosed are methods of assessing a subject comprising measuring the telomere length variation in a group of normal epithelial cells from a subject with cancer, thereby producing a telomere length variation for the subject, and comparing the telomere length variation with a reference telomere length variation. The comparison indicates the risk of local recurrence of cancer in the subject. Also disclosed are methods of assessing a subject comprising measuring the length variation of two or more telomeres in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length variation for the subject, and comparing the telomere length variation with a reference telomere length variation. Also disclosed are methods of assessing a subject comprising measuring the length variation of two or more telomeres in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length variation for the cell, and comparing the telomere length variation with a reference telomere length variation. In some forms, the telomere length variation of all telomeres in the cell is measured. In some forms, the telomere length variation of all cells in the group is measured. In some forms, the telomere length variation of all telomeres in all cells of the group is measured. In some forms, the subject has an increased risk of local recurrence of cancer if the chromosome telomere length variation is less than the reference chromosome telomere length variation.

In some forms, the reference telomere length parameter can be the telomere length parameter in at least one control cell from at least one control subject. In some forms, the reference telomere length parameter can be the median telomere length parameter of three or more control subjects. In some forms, the reference telomere length parameter can be based on the telomere length parameter measured in 20 or more control cells from each control subject. In some forms, the control cells can be the same tissue type as the normal epithelial cell. In some forms, the control subjects do not have cancer. In some forms, the subject has breast cancer. In some forms, the control subjects do not have local recurrence of cancer.

In some forms, measuring the length parameter of telomeres can be accomplished by obtaining a sample from the subject, where the sample is a cancer sample; performing telomere analysis on at least one normal epithelial cell from the cancer sample; and quantitating the telomere length parameter. In some forms, performing telomere analysis and quantitating the telomere length parameter can be accomplished by telomere quantitative fluorescent in situ hybridization (QT-FISH). In some forms, quantitating the telomere length parameter can be accomplished by totaling the fluorescent signal from telomere probes from each of the telomeres being measured. Telomere quantitative fluorescent in situ

hybridization (QT-FISH) is a quantitative technique for examining telomeres. For example, telomere length can be measured using QT-FISH. QT-FISH is a probe hybridization technique in which a labeled probe specifically hybridizes to, and thereby facilitates visualization and quantitation of, telomeres. QT-FISH is useful for quantitating nucleic acids in a nucleic acid-containing sample such as is contained in, for example, tissues at the single cell level.

Also disclosed are methods of assessing a subject comprising detecting Ki-67 in at least one normal epithelial cell from a subject with cancer, wherein the presence of Ki-67 on the cell indicates an increased risk of local recurrence of cancer. It was discovered that the presence of Ki-67 on normal epithelial cells was correlated with smaller telomere length variation. Thus, Ki-67 can serve as a marker of risk of local recurrence of cancer.

1. Methods of Treatment

The disclosed methods can comprise selecting a treatment for the subject based on the indicated risk of local recurrence of cancer. The disclosed methods can comprise treating the subject with a treatment selected based on the indicated risk of local recurrence of cancer.

The disclosed methods can comprise treating the subject with a more aggressive treatment if the subject has an increased risk of local recurrence of cancer. The disclosed methods can comprise treating the subject with a less aggressive treatment if the subject does not have an increased risk of local recurrence of cancer.

In general, subjects with a lower risk of local recurrence of cancer can be given less aggressive treatments. Local treatments are generally less aggressive. Subjects with a higher risk of local recurrence of cancer can be given more aggressive treatments. Systemic treatments are generally more aggressive. The extent of surgery can also be considered more or less aggressive.

G. Hybridization

The term hybridization typically means a sequence driven interaction between at least two nucleic acid molecules, such as a primer or a probe and a gene. Sequence driven interaction means an interaction that occurs between two nucleotides or nucleotide analogs or nucleotide derivatives in a nucleotide specific manner. For example, G interacting with C or A interacting with T are sequence driven interactions. Typically sequence driven interactions occur on the Watson-Crick face or Hoogsteen face of the nucleotide. The hybridization of two nucleic acids is affected by a number of conditions and parameters known to those of skill in the art. For example, the salt concentrations, pH, and temperature of the reaction all affect whether two nucleic acid molecules will hybridize.

Parameters for selective hybridization between two nucleic acid molecules are well known to those of skill in the art. For example, in some embodiments selective hybridization conditions can be defined as stringent hybridization conditions. For example, stringency of hybridization is controlled by both temperature and salt concentration of either or both of the hybridization and washing steps. For example, the conditions of hybridization to achieve selective hybridization can involve hybridization in high ionic strength solution (6.times.SSC or 6.times.SSPE) at a temperature that is about 12-25°C. below the Tm (the melting temperature at which half of the molecules dissociate from their hybridization partners) followed by washing at a combination of temperature and salt concentration chosen so that the washing temperature is about 5°C to 20°C below the Tm. The temperature and salt conditions are readily determined empirically in preliminary experiments in which samples of reference DNA immobilized on filters are hybridized to a labeled nucleic acid of interest and then washed under conditions of different stringencies. Hybridization temperatures are typically higher for DNA-RNA and RNA-RNA hybridizations. The conditions can be used as described above to achieve stringency, or as is known in the art. (Sambrook et al, Molecular Cloning: A Laboratory Manual, 2nd Ed., Cold Spring Harbor Laboratory, Cold Spring Harbor, N.Y., 1989; Kunkel et al. Methods Enzymol. 1987: 154:367, 1987 which is herein incorporated by reference for material at least related to hybridization of nucleic acids). A preferable stringent hybridization condition for a DNA:DNA hybridization can be at about 68°C (in aqueous solution) in 6XSSC or 6.times.SSPE followed by washing at 68°C

Stringency of hybridization and washing, if desired, can be reduced accordingly as the degree of complementarity desired is decreased, and further, depending upon the G-C or A-T richness of any area wherein variability is searched for. Likewise, stringency of hybridization and washing, if desired, can be increased accordingly as homology desired is increased, and further, depending upon the G-C or A-T richness of any area wherein high homology is desired, all as known in the art.

Another way to define selective hybridization is by looking at the amount

(percentage) of one of the nucleic acids bound to the other nucleic acid. For example, in some embodiments selective hybridization conditions would be when at least about, 60, 65, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 percent of the limiting nucleic acid is bound to the non-limiting nucleic acid. Typically, the non-limiting primer is in for example, 10 or 100 or 1000 fold excess. This type of assay can be performed at under conditions where both the limiting and non-limiting primer are for example, 10 fold or 100 fold or 1000 fold below their ka, or where only one of the nucleic acid molecules is 10 fold or 100 fold or 1000 fold or where one or both nucleic acid molecules are above their ka.

Another way to define selective hybridization is by looking at the percentage of primer that gets enzymatically manipulated under conditions where hybridization is required to promote the desired enzymatic manipulation. For example, in some embodiments selective hybridization conditions would be when at least about, 60, 65, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 percent of the primer is enzymatically manipulated under conditions which promote the enzymatic manipulation, for example if the enzymatic manipulation is DNA extension, then selective hybridization conditions would be when at least about 60, 65, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99, 100 percent of the primer molecules are extended. Preferred conditions also include those suggested by the manufacturer or indicated in the art as being appropriate for the enzyme performing the manipulation.

Just as with homology, it is understood that there are a variety of methods herein disclosed for determining the level of hybridization between two nucleic acid molecules. It is understood that these methods and conditions may provide different percentages of hybridization between two nucleic acid molecules, but unless otherwise indicated meeting the parameters of any of the methods would be sufficient. For example if 80% hybridization was required and as long as hybridization occurs within the required parameters in any one of these methods it is considered disclosed herein.

It is understood that those of skill in the art understand that if a composition or method meets any one of these criteria for determining hybridization either collectively or singly it is a composition or method that is disclosed herein.

H. Actions Based on Identifications

The disclosed methods include the determination, identification, indication, correlation, diagnosis, prognosis, etc. (which can be referred to collectively as

"identifications") of subjects, diseases, conditions, states, etc. based on measurements, detections, comparisons, analyses, assays, screenings, etc. For example, subjects are identified as having a higher or lower risk of local recurrence of cancer and appropriate treatments are identified based on such risk identifications. Such identifications are useful for many reasons. For example, and in particular, such identifications allow specific actions to be taken based on, and relevant to, the particular identification made. For example, prognosis of a particular disease or condition in particular subjects (and the lack of diagnosis of that disease or condition in other subjects) has the very useful effect of identifying subjects that would benefit from treatment, actions, behaviors, etc. based on the prognosis. For example, treatment for a particular disease or condition in subjects identified is significantly different from treatment of all subjects without making such an identification (or without regard to the identification). Subjects needing or that could benefit from the treatment will receive it and subjects that do not need or would not benefit from the treatment will not receive it.

Accordingly, also disclosed herein are methods comprising taking particular actions following and based on the disclosed identifications. For example, disclosed are methods comprising creating a record of an identification (in physical— such as paper, electronic, or other— form, for example). Thus, for example, creating a record of an identification based on the disclosed methods differs physically and tangibly from merely performing a

measurement, detection, comparison, analysis, assay, screen, etc. Such a record is particularly substantial and significant in that it allows the identification to be fixed in a tangible form that can be, for example, communicated to others (such as those who could treat, monitor, follow-up, advise, etc. the subject based on the identification); retained for later use or review; used as data to assess sets of subjects, treatment efficacy, accuracy of identifications based on different measurements, detections, comparisons, analyses, assays, screenings, etc., and the like. For example, such uses of records of identifications can be made, for example, by the same individual or entity as, by a different individual or entity than, or a combination of the same individual or entity as and a different individual or entity than, the individual or entity that made the record of the identification. The disclosed methods of creating a record can be combined with any one or more other methods disclosed herein, and in particular, with any one or more steps of the disclosed methods of

identification.

As another example, disclosed are methods comprising making one or more further identifications based on one or more other identifications. For example, particular treatments, monitorings, follow-ups, advice, etc. can be identified based on the other identification. For example, identification of a subject as having a disease or condition with a high level of a particular component or characteristic can be further identified as a subject that could or should be treated with a therapy based on or directed to the high level component or characteristic. A record of such further identifications can be created (as described above, for example) and can be used in any suitable way. Such further identifications can be based, for example, directly on the other identifications, a record of such other identifications, or a combination. Such further identifications can be made, for example, by the same individual or entity as, by a different individual or entity than, or a combination of the same individual or entity as and a different individual or entity than, the individual or entity that made the other identifications. The disclosed methods of making a further identification can be combined with any one or more other methods disclosed herein, and in particular, with any one or more steps of the disclosed methods of identification.

As another example, disclosed are methods comprising treating, monitoring, following-up with, advising, etc., a subject identified in any of the disclosed methods. Also disclosed are methods comprising treating, monitoring, following-up with, advising, etc., a subject for which a record of an identification from any of the disclosed methods has been made. For example, particular treatments, monitorings, follow-ups, advice, etc. can be used based on an identification and/or based on a record of an identification. For example, a subject identified as having a disease or condition with a high level of a particular component or characteristic (and/or a subject for which a record has been made of such an identification) can be treated with a therapy based on or directed to the high level component or

characteristic. Such treatments, monitorings, follow-ups, advice, etc. can be based, for example, directly on identifications, a record of such identifications, or a combination. Such treatments, monitorings, follow-ups, advice, etc. can be performed, for example, by the same individual or entity as, by a different individual or entity than, or a combination of the same individual or entity as and a different individual or entity than, the individual or entity that made the identifications and/or record of the identifications. The disclosed methods of treating, monitoring, following-up with, advising, etc. can be combined with any one or more other methods disclosed herein, and in particular, with any one or more steps of the disclosed methods of identification.

Examples

Example 1: Correlation Analysis of Risk of Local Recurrence of Breast Cancer Risk Telomere Length Variation and Relative Telomere Length

This example describes a telomere length association study to examine the associations between the risk of local recurrence of breast cancer and lengths of telomeres in tumor cells, related cells, and normal cells and breast cancer risk. The correlations discovered indicate that normal cells can indicate risk of local recurrence of breast cancer and provide the foundation of the disclosed methods. Telomere length and telomere length variation was examined in various types of cells surrounding breast tumor in search for potential biomarkers to predict the risk of local recurrence.

I. Methods

1. Patient Population

A total of 2,025 breast cancer patients who had complete follow-up data were recorded in the cancer registry database of the Lombardi Comprehensive Cancer Center

(LCCC), Georgetown University Medical Centers. Of these, 1,654 (81.7%) had no disease recurrence at the last contact, 74 (3.7%) had local recurrence, 200 (9.9%) had distant recurrence, 45 (2.2%) were never disease free and 50 (2.5%) had unknown type of recurrence. Breast cancer patients who had local recurrence (N=74) were considered cases in this study. Breast cancer patients who had no disease recurrence were considered controls. 148 controls (2 controls per case) were randomly selected, matched to cases on year of surgery (5-year interval), type of surgery (total mastectomy, partial mastectomy/ segmental mastectomy, lumpectomy), and age at diagnosis (5 -year interval) to include in this study.

2. Tumor tissue retrieval

The list of selected patients ( =222) was sent to the Histopathology and Tissue

Shared Resources of Lombardi Comprehensive Cancer Center to retrieval paraffin-embedded tissue blocks. Two blocks (a tumor and a separate benign tissue blocks) were retrieved for each of the 75 (33.8%) patients, tumor blocks were retrieved for 37 (16.7%) patients, and benign blocks were retrieved for 44 (19.8%) patients. In 66 (30%) patients, no tissue blocks were found. Ten serial 5-micron sections were cut from each block and one section (first section) was H&E stained. The second sections were used for telomere fluorescent in situ hybridization. The study pathologist examined all the H&E slides and circled cell types, i.e., cancer cell, normal epithelial cell, and infiltrative lymphocytes, as the guide for cell type identification. All the tissue sections were only labeled with a unique study ID number.

3. Clinical data

The Clinical Molecular Epidemiology Shared Resources (CMESR) of the LCCC provided de-identified clinical and treatment data, including age at diagnosis, date of birth, date of diagnosis, race, type of surgery, date of surgery, disease stage, tumor size, radiotherapy and type, radiotherapy date, chemotherapy and type, chemotherapy date, tumor ER/PR status, recurrence type, recurrence date, date of first contact, date of last contact, vital status, and date of death. The data were downloaded from the Cancer Registry of the LCCC and a unique study ID was assigned to each patient. All patient identifiable information was removed before the data were sent out to the study team for data analysis.

4. Telomere quantitative fluorescent in situ hybridization (TQ-FISH)

TQ-FISH was performed following published protocol with modifications (Meeker et al. Telomere length assessment in human archival tissues: combined telomere fluorescence in situ hybridization and immunostaining. Am J Pathol 2002; 160: 1259-68). Tissue sections were deparaffined in Citrisol and hydrated through a graded ethanol series and distilled water. The slides were then incubated in 10 mM Sodium Citrate buffer (pH 6.5) at 85 °C for 15 min, neutralized in PBS and dehydrated using ethanol series. 15 μΐ of hybridization buffer containing 1 μΜ Cy3 -labelled telomere-specific peptide nucleic acid (PNA) probe, 50% formamide, lOmM Tris (pH 7.5), 5% blocking agent and 1 x Denhardt's solution was added to the slides. Hybridization was carried out at 30°C over night following denaturation at 75 °C for 5 min. The slides were subsequently washed with occasional shaking for 10 min each in 2xSSC, l xSSC, 0.5xSSC and O. l xSSC at 45°C, and immediately mounted with anti-fade mounting medium containing DAPI.

The cells were imaged using a Leica DM4000B fluorescent microscope (Leica Microsystems, Bannockburn, IL) coupled with a PixelFly charge-coupled device camera, both controlled by IPlabs software (Scanalytics, Inc). An oil lens with magnification of 100x was used. Both Cy3 and DAPI images were captured. The exposure time was held constant at

150 ms for all Cy3 images to keep the signals within the linear range of the camera and enable comparison of telomere signal. Telomere length/length variations were measured in five cell types: cancer cells, normal epithelial cells adjacent to tumor, distant normal epithelial cells, carcinoma-associated fibroblast cells and infiltrative lymphocytes.

Identification of five cell types was assisted with the H&E slides cut from the same tissue block with tumor and benign areas marked out by the study pathologist. Quantification of the digitized fluorescent telomere signals was accomplished using ImageJ supplemented with a semi-automated script TeloMeter (website bui2.win.ad.jhu.edu/telometer/). For each patient, at least 30 cells were analyzed for each cell type to estimate average telomere length.

Telomere length variation (TLV) was defined as the coefficient of variation (CV) of telomere lengths among 30 analyzed cells. Relative telomere lengths were calculated as telomere fluorescent intensity unites (FIU) of cell type of interest divided by the telomere FIU of the infiltrative lymphocytes. A total number of 231 slides (112 tumor sections and 119 benign sections) were assayed in 26 batches in this study. A control slide containing cells with known telomere length was included in each batch of TQ-FISH experiment to monitor the hybridization efficiency. The CV of the mean telomere length among the 26 control slides was 12.8%. The TQ-FISH assay success rate was 100% (18 samples were repeated to capture infiltrative lymphocytes that were missed in the first attempt). The laboratory personnel were blinded to the case-controls status of the specimen.

5. Statistical analysis

Wilcoxon rank-sum tests and Fisher's exact tests were used to examine the case- control differences in continuous and categorical variables, respectively. Unconditional logistic regression was used to estimate the odd ratios for the association between telomere length variation and the risk of breast cancer local recurrence while controlling for age at diagnosis, type of surgery, year of surgery, disease stage and estrogen receptor status.

Kaplan-Meier analysis for recurrence-free survival was estimated for patients with small and large telomere length variation in normal epithelial cells adjacent to the tumor and compared using Log-rank test. TLV was dichotomized as small/large using the median value in control patients as the cut point. Paired- Student t-test was used to examine the differences in telomere length or length variation between cell types among all subjects. Spearman correlation was used to examine the correlations of telomere length variation between cell types among all subjects. P-values were 2-sided and considered significant if p < 0.05. All analyses were performed using SAS software, version 9.1 (SAS Institute, Inc., Cary, NC).

J. Results

1. Characteristics of study population

The characteristics of the study subjects are presented in Table 1. There were no significant case-control differences in the distributions of race, histological type, and type of surgery. The mean age at diagnosis was 50.2 years for cases and 51.5 years for controls and the average tumor size was 2.70 cm for cases and 1.71 cm for controls. The median follow-up time was slightly higher in cases (78 months) than in controls (65 months). Cases had significantly higher percentage of advanced stage (III - IV) disease compared with controls (22% vs. 2%, p< 0.001). The percent of patients who had ER negative tumors was significantly higher in cases (34.8%) than in controls (1 1.3%, p = 0.004). Cases were significantly more likely to receive radiation therapy or chemotherapy or both, partly reflecting the factor that higher proportion of the cases had more advanced disease.

Table 1. Clinicopahtologic characteristics of study population

Cases Controls

Variables N=46 N=106 P value†

Age at diagnosis, mean (SD) 50.2 (11.7) 51.5 (10.9) 0.374

Tumor size in cm, mean (SD) 2.49 (2.70) 1.71 (1.26) 0.097

Months of follow-up, mean (SD) 96.5 (65.6) 76.5 (57.0) 0.067

Race, N (%)

White 27 (58.7) 71 (66.4)

Black 10 (21.7) 20 (18.7)

Others 9 (19.6) 16 (15.0) 0.544

Histological type

Duct carcinoma 36 (78.3) 88 (82.2)

Duct & lobular carcinoma 1 (2.2) 8 (7.5)

Lobular carcinoma 5 (10.9) 6 (5.6)

Others 4 (8.1) 5 (4.7) 0.231

Stage, N (%)

0 - 1 15 (36.6) 47 (45.6)

II 17 (41.5) 54 (52.4)

III - IV 9 (22.0) 2 (1.9) < 0.001

Type of surgery, N (%)

Lumpectomy 18 (39.1) 42 (39.6)

Partial Mastectomy 14 (30.4) 16 (15.1)

Total mastectomy 11 (23.9) 35 (33.0)

Others 3 (6.5) 13 (12.3) 0.151

Year of Surgery, N (%)

Before 1995 11 (25.6) 13 (12.3)

1995 - 1999 18 (41.9) 39 (36.8)

2000 - 2004 13 (30.2) 38 (35.9)

After 2004 1 (2.3) 16 (15.1) 0.036

Systemic therapy, N (%)

None 8 (17.4) 47 (44.3)

Radiation therapy only 11 (23.9) 11 (10.4)

Chemotherapy only 13 (28.3) 21 (19.8)

Both 14 (30.4) 27 (25.5) 0.006

ER^A status, N (%) Positive 14 (30.4) 47 (44.3)

Negative 16 (34.8) 12 (11.3)

Unknown 16 (34.8) 47 (44.3) 0.004

†p-values were based on Wilcoxon rank sum test (continuous variables) or Fisher's exact test (categorical variables)

^Aestrogen receptor

2. Telomere length variation in normal epithelial cells and breast cancer local recurrence

Telomere length variation, defined as the coefficient of variation of the telomere lengths among 30 analyzed cells, was examined to determine if it is associated with breast cancer local recurrence. It was found that telomere length variation in normal epithelial cells adjacent to the tumor was significantly lower in cases (mean + SD = 60.2 + 16.3) than in controls (72.9 + 21.0, p = 0.008, Table 2). Using the median value in controls as a cut point, patients who had smaller telomere length variation in normal epithelial cells adjacent to the tumor had a significantly increased risk of breast cancer local recurrence, with an adjusted odds ratio [OR] of 5.13 (95% confidence interval [CI] =1.2- 22.2, Table 3). ORs were adjusted for year of surgery, type of surgery, age at diagnosis, disease stage and estrogen receptor status. When the TLV was categorized into quartiles based on the value in controls, a significant dose response relationship was observed between TLV in normal epithelial cells adjacent to the tumor and breast cancer local recurrence, with the lowest-vs-highest quartile OR of 15.3 (P_trend = 0.012, Table 3). Kaplan-Meier survival analysis indicated that patients with larger TLV (> 69.3) had 80% recurrence-free survival at the 10-year follow-up, significantly better than the 33% recurrence-free survival rate in patients who had smaller TLV (<69.3, p = 0.018, Figure 1).

Table 2. Case-control comparison of telomere length and telomere length variation.

Cases Controls

N mean (SD) N mean (SD) P value

Relative telomere length*

Tumor cells 35 0.772 (0.74) 66 0.726 (0.61) 0.95

CAFs^A 36 0.887 (0.56) 68 0.741 (0.35) 0.23

Adjacent epithelia cells $ 28 0.699 (0.35) 59 0.615 (0.31) 0.30

Distant epithelia cells § 23 0.651 (0.30) 52 0.613 (0.37) 0.40

Telomere length variation†

Tumor cells 36 95.3 (52.3) 69 85.6 (45.1) 0.32

CAFs 37 70.6 (16.4) 71 78.8 (31.8) 0.43

Adjacent epithelia cells 29 60.2 (16.3) 59 72.9 (21.0) 0.008

Distant epithelia cells 30 67.9 (29.8) 84 74.1 (21.7) 0.09

Lymphocytes 37 57.1 (19.7) 71 56.5 (13.8) 0.82 *relative telomere length (RTL) was defined as the telomere FIU of the cell type of interest divided by the telomere FIU of the infiltrative lymphocytes

†Telomere length variation is the coefficient of variation (CV%) of telomere length in 30 cells

ACAF= carcinoma-associated fibroblasts

|normal appearing epithelial cells on the same blocks as the tumor cells

§normal appearing epithelial cells on the separate blocks from the tumor cells

P- values were based on Wilcoxon rank sum test

Table 3. Association between TLV and risk of breast cancer local recurrence.

Case/control

Cell type N OR* (95% CI) P value

Adjacent normal epithelial cells^A

By median

> 69.3 7/29 ref

< 69.3 22/30 5.13 (1.19 - 22.2) 0.029

By quartiles

> 88.4 2/15 ref

69.3 - 88.4 5/14 2.68 (0.30 - 24.3)

55.5 - 69.3 10/15 6.13 (0.74 - 50.9)

< 55.5 12/15 15.31 (1.64 - 143) 0.012§

Distant normal epithelial cellsj

By median

> 70.4 12/42 ref

< 70.4 18/42 1.67 (0.59 - 4.71) 0.33

By quartiles

> 91.6 3/22 ref

70.4 - 91.6 9/20 1.53 (0.29 - 8.14)

57.3 - 70.4 5/22 1.05 (0.17 - 6.40)

< 57.3 13/20 3.41 (0.70 - 16.7) 0.13§

*odds ratios were adjusted for age at diagnosis, year of surgery, type of surgery, stage and estrogen receptor status (positive, negative or unknown)

Anormal appearing epithelial cells on the same block as the tumor cells

|normal appearing epithelial cells on the separate block from the tumor cells

§p-for-trend

Telomere length variation in normal epithelial cells distant to the tumor (epithelial cells were identified from the blocks without tumor cells) was non-significantly smaller in cases (mean + SD = 67.9 + 29.8) than in controls (74.1 + 21.7, p = 0.09, Table 2). Using the median value in controls as a cut point, patients with smaller telomere length variation in normal epithelial cells distant to the tumor had an non-significantly increased risk of breast cancer local recurrence, with an adjusted odds ratio [OR] of 1.67 (95% confidence interval [CI] =0.6 - 4.7, Table 3). When the TLV was categorized into quartiles based on the value in controls, a trend of increasing risk of LR was observed with decreasing TLV in normal epithelial cells distant to the tumor, with the lowest-vs-highest quartile OR of 3.4 (P_trend = 0.13, Table 3). These results are somewhat consistent with the results from normal epithelial cells adjacent to the tumor. However, it should be noted that the exact distances between the normal epithelial cells and the tumor were unknown.

No significant associations between telomere length variation in cancer cells were observed in CAFs or in infiltrative lymphocytes and breast cancer local recurrence (Table 2).

3. Telomere length variation in normal epithelial cells and clinical factors

The relationship between telomere length variation in normal epithelial cells adjacent to tumor and selected clinical and host factors was also examined. TLV in normal epithelial cells adjacent to tumor was found to be significantly smaller in patients with large tumors (> 1.5 cM) than in patients with small tumors (< 1.5 cM, Table 4). No significant association between TLV and patients' race, age at diagnosis, disease stage or tumor histological type was observed. It was found that telomere length variation is lower in ER negative tumors than in ER positive tumors, but this difference wan not statistically significant (Table 4).

Table 4. Distribution of telomere length variation (TLV) in adjacent normal epithelial cells by clinical characteristics in all subjects.

TLV in ANEC^A TLV in DNEC†

N mean (SD) N mean (SD)

Race

Whites 55 71.7 (21.6) 70 76.0 (27.0)

Blacks 14 65.1 (12.8) 21 62.5 (15.2)

Others 19 62.9 (20.2) 23 70.7 (18.9)

P value 0.28 0.13

Age at diagnosis

<= 40 19 61.6 (15.3) 20 74.2 (30.1)

41 - 50 29 72.3 (22.2) 39 69.8 (17.3)

51 - 60 25 66.2 (19.9) 30 68.3 (19.4)

>= 61 15 75.0 (21.6) 25 80.0 (31.6)

P value 0.12 0.48

tage

0 -1 31 71.9 (22.8) 48 76.6 (26.3)

II 47 67.8 (19.7) 55 70.3 (22.7)

III - IV 7 66.9 (16.5) 5 62.8 (29.1)

P value 0.80 0.39

umor size

< 1.5 cM 21 81.9 (22.4) 28 82.1 (31.5)

> 1.5 cM 43 66.2 (20.0) 45 71.1 (21.3)

P value 0.003 0.12

ER status Negative 21 60.5 (19.4) 21 64.0 (18.6) Positive 33 69.5 (20.8) 43 72.8 (23.8) P value 0.12 0.21

Histological type

Ductal 72 69.1 (21.3) 94 71.0 (21.9) Lobular 5 61.8 (21.0) 6 88.5 (53.3)

Ductal & lobular 5 72.0 (11.7) 6 85.3 (23.2)

Others 6 67.8 (15.1) 8 67.5 (14.5) P value 0.69 0.49

^Anormal appearing epithelial cells on the same blocks as the tumor cells

†normal appearing epithelial cells on the separate blocks from the tumor cells

p-values were based on Kruskal-Wallis test

4. Characteristics of telomere length variation in cancer and stromal cells

Telomere length/length variations were measured in five cell types: cancer cells, normal epithelial cells adjacent to tumor, distant normal epithelial cells, carcinoma-associated fibroblast cells and lymphocytic infiltrates. The average telomere length variation was significantly different between cell types (one-way ANOVA, p <0.001), such as average TLV in lymphocytes (56.7%) < normal epithelial cells adjacent to tumor (68.7%) < distant normal epithelial cells (72.4%) < CAFs (76.0%) < tumor cells (88.9%). The differences in TLV between lymphocytes and other four cell types, and between cancer cells and other four cell types were highly significant at p < 0.001 level. The differences in mean TLV between normal epithelial cells adjacent to tumor and distant normal epithelial cells, and between distant normal epithelial cells and CAFs were not statistically significant with a p-value of 0.26 and 0.15, respectively.

Correlations in TLV were also examined between cell types. Significant correlation in TLV was seen between normal epithelial cells adjacent to tumor and infiltrative lymphocytes (r = 0.42, p < 0.001), between normal epithelial cells adjacent to tumor and distant normal epithelial cells (r = 0.24, P = 0.026), between normal epithelial cells adjacent to tumor and CAFs (r = 0.23, p = 0.012), and between CAFs and infiltrative lymphocytes (r = 0.24, p = 0.006). No significant correlation in TLV was seen between cancer cells and any other four cell types, between CAFs and distant normal epithelial cells (r = -0.01, p = 0.99), and between infiltrative lymphocytes and distant normal epithelial cells (r = 0.08, p = 0.40).

5. Characteristics of telomere length in cancer and stromal cells

The mean telomere length, expressed as fluorescent intensity units (FIU), in infiltrative lymphocytes (mean FIU = 208, 935) were significantly longer than in tumor cells (mean FIU = 143,422, p < 0.001), in normal epithelial cells adjacent to tumor (mean FIU = 145,401, p < 0.001), in distant normal epithelial cells (mean FIU = 140,423, p < 0.001), and in carcinoma-associated fibroblast (CAF) cells (mean FIU = 152,348, p <0.001). In 17 cases (15.3%), however, longer telomeres were found in tumor cells than in either infiltrative lymphocytes or normal epithelial cells adjacent to tumor. Relative telomere length (RTL), defined as telomere FIU in cells of interest divided by telomere FIU in infiltrative lymphocytes, was significantly shorter in normal epithelial cells adjacent to tumor (mean = 0.670) than in CAFs (mean = 0.871, p = 0.013, Table 2). There are no significant differences in RTL between normal epithelial cells adjacent to tumor and distance epithelial cells (p = 0.522), between normal epithelial cells adjacent to tumor and tumor cells (p = 0.230), between CAFs and tumor cells (p = 0.324). The observed telomere length differences between different cell types were consistent with previous reports (Meeker et al. Telomere shortening occurs in subsets of normal breast epithelium as well as in situ and invasive carcinoma. Am J Pathol 2004; 164:925-35; Kurabayashi et al. Luminal and cancer cells in the breast show more rapid telomere shortening than myoepithelial cells and fibroblasts. Hum Pathol 2008; 39: 1647-55).

6. Telomere length and breast cancer local recurrence

No significant case-control differences were observed in relative telomere length in tumor cells, in normal epithelial cells adjacent to tumor, in distant epithelial cells, or in CAFs (Table 2). Logistic regression analysis indicated that RTL in any of the four cell types were not associated with risk of breast cancer local recurrence.

K. Discussion

In this example, it was demonstrated that telomere length variation among normal appearing epithelial cells adjacent to the tumor was significantly associated with breast cancer local recurrence. Patients who had large telomere length variation had significantly better 10-year recurrence free survival. The results indicate that early molecular changes in the morphologically normal epithelial cells adjacent to the tumor are predictive of breast cancer local recurrence. This study is the first to report that telomere length variation in normal epithelial cells adjacent to tumor is a molecular marker to predict breast cancer local recurrence.

One of the most important predictors of LR is the pathological margin status after breast conserving surgery (Solin et al. The significance of the pathology margins of the tumor excision on the outcome of patients treated with definitive irradiation for early stage breast cancer. Int J Radiat Oncol Biol Phys 1991 ; 21 :279-87; Smitt et al. The importance of the lumpectomy surgical margin status in long-term results of breast conservation. Cancer 1995; 76:259-67; Schnitt et al. The relationship between microscopic margins of resection and the risk of local recurrence in patients with breast cancer treated with breast-conserving surgery and radiation therapy. Cancer 1994; 74: 1746-51; Pittinger et al. Importance of margin status in outcome of breast-conserving surgery for carcinoma. Surgery 1994; 1 16:605-8). Surgically excised tumors are routinely subject to margin examination by histology to make sure all tumor tissues has been removed; otherwise, additional surgery will be performed (Silverstein et al. Ductal carcinoma in situ (DCIS) of the breast: diagnostic and therapeutic controversies. J Am Coll Surg 2001; 192: 196-214). However, histological examination based on morphology may not identify "cancerous" cells that carry early malignant molecular changes but show "normal" morphology. Thus a negative margin classification based on current standard may not be truly negative. After breast-conserving surgery, microscopically normal- appearing but genetically altered epithelium may remain in situ. These epithelial cells can acquire additional mutations or epigenetic alterations that initiate the development of a second tumor of the same or a different histological type, representing a local recurrence. This is probably why the vast majority of local recurrences occur at the site of excision

(Idvall et al. Histopathological and cell biological characteristics of ductal carcinoma in situ (DCIS) of the breast-a comparison between the primary DCIS and subsequent ipsilateral and contralateral tumours. Breast 2005; 14:290-7; Fisher et al. Pathologic findings from the National Surgical Adjuvant Breast Project (protocol 6)). I. Intraductal carcinoma (DCIS). Cancer 1986; 57: 197-208). This concept is consistent with the phenomenon of field cancerization. Field cancerization describes the presence of occult but clinically important preneoplastic lesions of the epithelium within an anatomic region exposed to the same carcinogens (Slaughter et al. Field cancerization in oral stratified squamous epithelium; clinical implications of multicentric origin. Cancer 1953; 6:963-8) and has been described for many types of cancers including breast cancer (Garcia et al. Field cancerization, clonality, and epithelial stem cells: the spread of mutated clones in epithelial sheets. J Pathol 1999; 187:61-81; Braakhuis et al. A genetic explanation of Slaughter's concept of field

cancerization: evidence and clinical implications. Cancer Res 2003; 63 : 1727-30).

In the present study, it was discovered that telomere length variation in normal appearing epithelial cells was significantly associated with breast cancer local recurrence.

Telomere length variations in tumor cells, carcinoma-associated fibroblast cells or lymphocytic infiltrates were not associated with local recurrence. These data indicate that local recurrence of breast cancer after breast conserving surgery is partly due to the failure to completely remove the morphologically normal "cancerous" cells in the remaining breast tissue, further highlighting the importance of better defining the surgical margin by using molecular biomarkers.

Telomeres are specialized structures that protect chromosome integrity and are essential for maintaining genome stability (McEachern et al. Telomeres and their control. Annu Rev Genet 2000; 34:331-58). Cell proliferation leads to telomere shortening due to the end replication problem and very short telomeres are a frequent genetic alteration in pre- malignant lesions, indicating that telomere dysfunction is often an early event in

carcinogenesis (Engelhardt et al. Telomerase and telomere length in the development and progression of premalignant lesions to colorectal cancer. Clin Cancer Res 1997; 3 : 1931-41 ; Kinouchi et al. Telomere shortening in the colonic mucosa of patients with ulcerative colitis. J Gastroenterol 1998; 33 :343-8; O'Sullivan JN, et al. Chromosomal instability in ulcerative colitis is related to telomere shortening. Nat Genet 2002; 32:280-4; van Heek et al. Telomere shortening is nearly universal in pancreatic intraepithelial neoplasia. Am J Pathol 2002; 161 : 1541-7; Meeker et al. Telomere shortening is an early somatic DNA alteration in human prostate tumorigenesis. Cancer Res 2002; 62:6405-9; Meeker et al. Telomere length abnormalities occur early in the initiation of epithelial carcinogenesis. Clin Cancer Res 2004; 10:3317-26). Previous studies have shown that telomere shortening occurs in breast cancer pre-malignant lesions during the transition from ductal hyperplasia to ductal carcinoma in situ (Meeker et al. Telomere shortening occurs in subsets of normal breast epithelium as well as in situ and invasive carcinoma. Am J Pathol 2004; 164:925-35; Chin et al. In situ analyses of genome instability in breast cancer. Nat Genet 2004; 36:984-8), indicating that short telomere is one of the earliest molecular changes during breast cancer development. However, it was determined that telomere length in normal appearing epithelial cells adjacent to the tumor was not associated with breast cancer local recurrence. Nor is the telomere length in tumor cells or carcinoma-associated fibroblast cells associated with LR (Table 2).

In this study set, it was observed that normal epithelial cells adjacent to tumor showed typical terminal duct lobular units (TDLU) structure and also had shorter average telomere length compared to carcinoma-associated fibroblast cells or tumor cells (Table 2). This observation is consistent with previous reports suggesting that TDLU of normal breast tissue typically have shorter telomeres than myoepithelial cells or normal large lactiferous ducts (Meeker et al. Telomere shortening occurs in subsets of normal breast epithelium as well as in situ and invasive carcinoma. Am J Pathol 2004; 164:925-35; Kurabayashi et al. Luminal and cancer cells in the breast show more rapid telomere shortening than myoepithelial cells and fibroblasts. Hum Pathol 2008; 39: 1647-55). In a separate study, 40 samples of normal breast tissue from women who underwent breast reduction surgery were examined. Telomere length in TDLU was significantly shorter than in large ducts. These observations indicate that telomere lengths in breast epithelial cells are heterogeneous and likely reflect the complex biology of breast development and differentiation during puberty, menstrual cycle, pregnancy and lactation. Importantly, small telomere length variation among normal epithelial cells adjacent to tumor was found to be significantly associated with an increased risk of local recurrence. Further, telomere length variation in normal epithelial cells adjacent to tumor was not associated with known recurrent risk factors, such as patient age at diagnosis, race, disease stage, and tumor histological type, indicating it is an independent risk marker. The biology underlying this observation is unknown and remains to be elucidated.

It was realized that telomere length variation, like telomere length, may reflect the recent history of cell proliferation in a given cell type. For example, a uniform telomere length (small telomere length variation) among the cells can indicate a recent clonal expansion. Clonal expansion has been reported to be a common step in cancer development, in which certain mutations transform cells into super-competitors that expand at the expense of the surrounding cells without inducing histological changes (Rhiner and Moreno Super competition as a possible mechanism to pioneer precancerous fields. Carcinogenesis 2009; 30:723-8). The normal epithelial cells adjacent to tumor, as part of the field giving rise to the primary tumor, could be the colonies of expanding super-competitors originated from the same progenitor cell. One would expect that these colonies of expanding super-competitors will have similar telomere length and high risk of developing a tumor. To shed light on this idea, immunochemical staining was performed with anti-Ki-67 antibody in the available samples (N=87). Normal epithelial cells adjacent to tumor that showed positive Ki-67 staining (high proliferation marker) had significantly smaller telomere length variation (mean ± SD = 67.1% ± 20.3%, N=67) than in Ki-67 negative stained cells (mean ± SD = 78.5% ± 26.1%, N=20, p = 0.047). These observations indicate an important biological basis of breast cancer local recurrence.

The present study tested a novel idea of developing non-tumor cell-related molecular markers for better defining surgical margins and for understanding the risk of local recurrence based on normal breast tissues surrounding the tumor. By using quantitative

FISH, telomere length was measured at the individual cell level and calculated telomere length variation (CV%) as a novel phenotype, in addition to traditionally used average telomere length. In this study, telomere length in infiltrative lymphocytes was used to normalize the hybridization variation and relative telomere length, defined as telomere length in cells of interest divided by telomere length of infiltrative lymphocytes, was used in case- control analysis. Telomere length variation was defined as the coefficient of variation of the mean (SD/mean) telomere length among the analyzed cells and this definition automatically corrects for hybridization variation. In addition, cases and controls were matched on year of surgery, which minimizes the bias of paraffin block aging on the TQ-FISH. Therefore, the observed case-control difference is not likely the result of technique artifact.

In summary, this study revealed that telomere length variation in normal epithelial cells adjacent to tumor is significantly associated with breast cancer local recurrence. Patients who had large telomere length variation had significantly better 10-year recurrence free survival rate (80%) than patients who had small telomere length variation (33%). Telomere length variation in normal epithelial cells adjacent to tumor is a useful non-tumor related biomarker for predicting breast cancer local recurrence after breast conserving surgery. Because effective treatment modalities exist for the locoregional control of breast cancer, robust biomarkers that can stratify patients into low/high risk group for local recurrence could profoundly affect the treatment of breast cancer.

Claims

1. A method of assessing a subject comprising:

measuring a length parameter of at least one chromosome telomere in at least one normal epithelial cell from a subject with cancer, thereby producing a telomere length parameter for the subject,

comparing the telomere length parameter with a reference telomere length parameter, wherein the comparison indicates the risk of local recurrence of cancer in the subject.

2. The method of claim 1, wherein the telomere length parameter is telomere length variation, wherein the reference telomere length parameter is reference telomere length variation, wherein the subject has an increased risk of local recurrence of cancer if the chromosome telomere length variation is less than the reference chromosome telomere length variation.

3. The method of claim 2, wherein the smaller the telomere length variation of the cell from the subject the higher the risk of local recurrence of cancer.

4. The method of claim 2 or 3, wherein the greater the telomere length variation of the cell from the subject the lower the risk of local recurrence of cancer.

5. The method of any one of claims 2-4, wherein if the subject has a chromosome telomere length variation less than the reference chromosome telomere length variation and has a large tumor, the subject has a greater risk of local recurrence of cancer than a subject with a chromosome telomere length variation less than the reference chromosome telomere length variation and a small tumor.

6. The method of any one of claims 2-5, herein if the subject has a chromosome telomere length variation less than the reference chromosome telomere length variation and has an estrogen receptor negative tumor, the subject has a greater risk of local recurrence of cancer than a subject with a chromosome telomere length variation less than the reference chromosome telomere length variation and an estrogen receptor positive tumor.

7. The method of any one of claims 1-6, wherein the normal epithelial cell is the same tissue type as the cancer.

8. The method of any one of claims 1-7, wherein the normal epithelial cell appears morphologically normal.

9. The method of any one of claims 1-8, wherein the normal epithelial cell is a normal epithelial cell adjacent to tumor.

10. The method of any one of claims 1-9, wherein the telomere length parameter of two or more telomeres in the cell is measured.

1 1. The method of any one of claims 1-10, wherein the telomere length parameter is measured in 20 or more normal epithelial cells adjacent to tumor from the subject.

12. The method of any one of claims 1-11, wherein the reference telomere length parameter is the telomere length parameter in at least one control cell from at least one control subject.

13. The method of any one of claims 1-12, wherein the reference telomere length parameter is the median telomere length parameter of three or more control subjects.

14. The method of claim 12 or 13, wherein the reference telomere length parameter is based on the telomere length parameter measured in 20 or more control cells from each control subject.

15. The method of any one of claims 12-14, wherein the control cells are the same tissue type as the normal epithelial cell.

16. The method of any one of claims 12-15, wherein the control subjects do not have local recurrence of cancer.

17. The method of any one of claims 1-16, wherein the subject has breast cancer.

18. The method of any one of claims 1-17, wherein measuring the length parameter of telomeres is accomplished by obtaining a sample from the subject, wherein the sample is a cancer sample; performing telomere analysis on at least one normal epithelial cell from the cancer sample; and quantitating the telomere length parameter.

19. The method of claim 18, wherein performing telomere analysis and quantitating the telomere length parameter are accomplished by telomere quantitative fluorescent in situ hybridization (QT-FISH).

20. The method of claim 19, wherein quantitating the telomere length parameter is accomplished by totaling the fluorescent signal from telomere probes from each of the telomeres being measured.

21. The method of any one of claims 1-20 further comprising selecting a treatment for the subject based on the indicated risk of local recurrence of cancer.

22. The method of any one of claims 1-21 further comprising treating the subject with a treatment selected based on the indicated risk of local recurrence of cancer.

23. The method of any one of claims 1-22 further comprising treating the subject with a more aggressive treatment if the subject has an increased risk of local recurrence of cancer.

24. The method of claim 23, wherein the more aggressive treatment is chemotherapy, radiation therapy, hormonal therapy, or a combination.

25. The method of any one of claims 1-22 further comprising treating the subject with a less aggressive treatment if the subject does not have an increased risk of local recurrence of cancer.

26. The method of claim 25, wherein the less aggressive therapy is surgery alone.

27. The method of any one of claims 21-23 or 25, wherein the treatment is lumpectomy alone or with any combination of chemotherapy, radiation therapy, and hormonal therapy; or mastectomy alone of with any combination of lymph node dissection, chemotherapy, radiation therapy, and hormonal therapy.