Skip to main content
Indian Journal of Human Genetics logoLink to Indian Journal of Human Genetics
. 2009 Jan-Apr;15(1):13–18. doi: 10.4103/0971-6866.50864

Chromosomal instability in the lymphocytes of breast cancer patients

Kaur Harsimran 1, Monga Gaganpreet Kaur 1, Setia Nitika 1, Sudan Meena 2, Uppal M S 2, Yamini 2, Batra A P S 3, Sambyal Vasudha 1,
PMCID: PMC2846563  PMID: 20407644

Abstract

Genomic instability in the tumor tissue has been correlated with tumor progression. In the present study, chromosomal aberrations (CAs) in peripheral blood lymphocytes (PBLs) of breast tumor patients were studied to assess whether chromosomal instability (CIN) in PBLs correlates with aggressiveness of breast tumor (i.e., disease stage) and has any prognostic utility. Cultured blood lymphocyte metaphases were scored for aberrations in 31 breast cancer patients and 20 healthy age and sex-matched controls. A variety of CAs, including aneuploidy, polyploidy, terminal deletions, acentric fragments, double minutes, chromatid separations, ring chromosome, marker chromosome, chromatid gaps, and breaks were seen in PBLs of the patients. The CAs in patients were higher than in controls. A comparison of the frequency of metaphases with aberrations by grouping the patients according to the stage of advancement of disease did not reveal any consistent pattern of variation in lymphocytic CIN. Neither was any specific chromosomal abnormality found to be associated with the stage of cancer. This might be indicative of the fact that cancer patients have constitutional CIN, which predisposes them to the disease, and this inherent difference in the level of genomic instability might play a role in disease progression and response to treatment.

Keywords: Breast cancer, chromosomal aberrations, genomic instability, lymphocytes

Introduction

Cancer is a complex disease in which cells with altered gene expression grow abnormally, invade other tissues, and disrupt their normal function. A crucial early event in carcinogenesis is the induction of the genomic instability phenotype, which enables an initiated cell to evolve into a cancer cell by achieving greater proliferative capacity and genetic plasticity to overcome host immunological resistance, localized toxic environment, and suboptimal micronutrient supply.

Genomic instability in cancer can be of two types: microsatellite instability (MIN) and chromosomal instability (CIN). MIN tumors exhibit an apparently normal karyotype and have mutations in DNA mismatch repair genes. But, a majority of the tumors exhibit abnormal karyotypes involving either chromosomal rearrangement and/or aneuploidy and are classified as CIN tumors.[13]

Various reports indicate a significant increase in the chromosomal aberrations (CAs) in peripheral blood lymphocytes (PBLs) of cancer patients with solid tumors.[47] PBLs of patients with breast cancer and other solid tumors show simple chromosomal lesions that may be stable markers in cancer cells.[8] Hence, it is proposed that lymphocytes may be used as a surrogate tissue model for studying genomic instability in case of solid tumors and the frequency of CAs in PBLs can be used as a predictor of cancer risk.[912]

Breast cancer is a major global health problem and the incidence of the disease continues to increase steadily. The frequency of sporadic breast cancer is higher in areas adjoining Amritsar city of Punjab, India (Unpublished data, Rotary Cancer Hospital, Amritsar; personal comunication). In the present study, CAs in PBLs of sporadic breast tumor patients were studied to assess whether CIN in PBLs correlates with aggressiveness of breast tumor, i.e. disease stage, and has any prognostic utility.

Materials and Methods

Five milliliters of blood sample from 31 cancer patients, 28 with sporadic malignant breast cancer and three with benign breast disease, were collected before surgery from the surgical wards of Sri Guru Ram Das Institute of Medical Sciences and Research, Amritsar (Punjab), after informed consent was obtained. Institutional ethical committee approval was obtained for the study. Relevant information regarding age, symptoms, duration and stage of the disease (TNM classification), habits, habitat, menstrual and reproductive history, occupation, and exposure of the patients to mutagens was recorded on a predesigned questionnaire. Age and sex-matched controls were randomly selected from the general population of Amritsar. Blood samples of 31 breast cancer patients and 20 healthy age and sex-matched controls were cultured in RPMI 1640 medium according to the standard culturing technique,[13] with some modifications. Slides were GTG banded according to the Benn and Perle[14] method. Banded slides were scanned for numerical and structural aberrations. For each subject, 100 clear metaphases were assessed for CAs. Of these, 10 metaphases were karyotyped as per ISCN 2005. The t-test was used to compare the frequency of aberrant metaphases among patients and controls.

Results

Among the patients, one patient had stage IV disease, 13 had stage III disease, eight were diagnosed at stage II, six had stage I, and three patients had benign disease. The cancer patients were in the age group of 28–65 years. None of the patients had history of early menarche (before the age of 12 years) or late menopause (after 55 years) in postmenopausal patients. 77.4% of the patients (n = 24) consumed vegetarian diet and only 22.5% (n = 7) consumed nonvegetarian food occasionally. All of them had first full-term pregnancy before the age of 30 years. 87.1% (n = 27) of the patients were housewives. Twelve patients (38.7%) belonged to urban area, six (19.3%) of them had suburban habitat, and 13 (42%) belonged to rural areas surrounding Amritsar [Table 1]. Control subjects were in the age group of 27–66 years. Fifty-five percent (n = 11) of the controls belonged to urban areas, 20% (n = 4) of them were from suburban areas, and 25% (n = 5) belonged to rural area. Most (90%) (n = 18) of them consumed vegetarian diet [Table 1].

Table 1.

Habits and habitat of the patients and control subjects

Stage Code Age Age at (years) Habitat Diet Occupation

Menarche Menopause
Benign P10 65 15 53 Rural Veg* Housewife
P11 45 16 - Rural Veg Housewife
P14 60 14 50 Suburban Veg Housewife
Stage I P1 65 15 53 Urban Veg Housewife
P4 45 14 50 Sub urban Veg Housemaid
P6 50 14 45 Urban Veg Housewife
P8 50 15 46 Urban Veg Housewife
P15 35 13 - Suburban Veg Housewife
P21 50 12 49 Rural Veg Housewife
Stage II P2 60 14 49 Urban Nonveg Housewife
P3 60 13 45 Urban Veg Teacher
P7 60 15 45 Urban Veg Housewife
P9 65 12 50 Urban Nonveg Housewife
P16 52 14 - Urban Nonveg Teacher
P18 57 13 50 Suburban Veg Housewife
P22 64 13 55 Rural Veg Housewife
P23 65 13 54 Rural Veg Housewife
Stage III P5 35 13 - Urban Veg Housewife
P13 42 15 - Urban Veg Housewife
P17 55 14 50 Suburban Veg Housewife
P19 45 - 45 Rural Nonveg Housewife
P20 48 13 43 Urban Veg Housewife
P24 35 14 - Rural Nonveg Housewife
P25 28 14 - Urban Veg Housewife
P26 50 13 - Rural Veg Housewife
P27 42 14 - Rural Veg Housewife
P28 65 14 53 Rural Veg Housewife
P29 55 12 53 Suburban Veg Housewife
P30 50 15 - Rural Nonveg Housewife
P31 47 16 - Rural Veg Housewife
Stage IV P12 33 14 - Rural Nonveg Laborer
Controls C1 30 12 - Urban Veg Housewife
C2 29 14 - Urban Nonveg Teacher
C3 50 13 45 Urban Veg Housewife
C4 45 12 44 Suburban Veg Housewife
C5 50 13 48 Urban Veg Housewife
C6 28 14 47 Suburban Veg Housewife
C7 60 15 48 Rural Veg Housewife
C8 65 14 46 Rural Veg Housewife
C9 32 12 - Urban Veg Housewife
C10 42 13 - Urban Veg Teacher
C11 45 12 44 Urban Veg Office job
C12 53 13 46 Urban Veg Office job
C13 40 12 - Urban Veg Office job
C14 55 12 47 Urban Veg Hostel attendant
C15 50 13 45 Rural Veg Sweeper
C16 63 14 46 Rural Veg Housewife
C17 53 12 47 Suburban Veg Housewife
C18 66 13 46 Rural Veg Farmer
C19 60 11 47 Suburban Veg Housewife
C20 27 13 - Urban Nonveg Student
*

Vegeterian

Nonvegeterian

The frequency of aberrant metaphases varied from 3.3 to 60.1% in cultured lymphocytes of patients and from 1.5 to 5.7% in controls [Table 2]. Stage I patients had aberrant metaphases ranging from 21.4 to 60%. The frequency of aberrant metaphases ranged from 20 to 50% in stage II patients and 3.3 to 60% in stage III and IV patients. Enormous variation was also seen for numerical and structural aberrations among patients with various stages of advancement of disease. A variety of CAs, including aneuploidy, polyploidy, terminal deletions, acentric fragments, double minutes, chromatid separations, ring chromosome and marker chromosome, chromatid gaps, and breaks were seen in PBLs of the patients. Specific CA correlated with stage of cancer was not observed, neither was any particular chromosome found to be involved in aberrations in all the patients. A high frequency of acrocentric associations (D-D, G-G, D-G) was seen in all the patients as compared to controls. The mean value of percent total aberrations in patients was 32.3% and in control subjects was 1.9%. A statistically significant difference in the percentage of aberrant metaphases was seen among patients and controls (t-value = 10.1, P < 0.001).

Table 2.

Comparison of frequency (%age) of aberrant metaphases in peripheral blood lymphocytes of breast cancer patients (grouped according to disease stage) and controls

Category Mean age (years) Mean age (years) at Mps with total aberrations (%) Mps with numerical aberration (%) Mps with structural aberration (%) Mps with acrocentric association (%)





Menarche Menopause Mean ± SD Range Mean± SD Range Mean ± SD Range Mean ± SD Range
Benign (n = 3) 56.7 15 51.5 20.2 15.7-23.3 16.7 7.9-23.3 4.4 5.2-8.11 28.6 27.02-28.9
Stage I (n = 6) 49.2 13.8 48.6 40.4 21.4-60 29.9 12.3-50 14.9 3.6-26 13.0 2.5-31.2
Stage II (n = 8) 60.4 13.4 49.7 33.7 20-50 25.9 16.6-24 14.4 0-27.8 9.4 2.5-25.2
Stage III (n = 13) 45.9 9.4 48.8 30.8 3.3-60.1 22.8 3.3-68 15.4 0-30.2 12.9 3.3-25.7
Stage IV (n = 1) 33 14 - 27.27 12.1 - 15.15 - 18.18 -
Statistical comparison of chromosomal aberrations using t-test
Patients (n = 31) 32.3±13.0 3.3-60.1 24.1±13.2 3.3-68.0 15.5±8.2 0-30.2 13.8±10.3 2.5-35.7
Controls (n = 20) 1.9±2.1 0-5.7 2.6±1.3 0-5.0 3.9±0.9 0-5.1 4.3±2.6 0-11.1
Statistical significance Significant difference (P < 0.0001) Significant difference (P < 0.0001) Significant difference (P < 0.005) Significant difference (P < 0.005)

Metaphases

Discussion

Genetic instability is a defining feature of human cancer. In the present study, breast cancer patients had a significantly higher percentage of aberrant metaphases as compared with controls. There was a high frequency of numerical as well as structural abnormalities in the cultured lymphocytes of patients, but enormous variation was seen in the level of lymphocytic CIN among the breast cancer patients. The mean of percentage of metaphases with aberrations was 20.2% in patients with benign disease, 40.4% in stage I patients, 33.9% in stage II patients, 30.8% in stage III patients, and 27.3% in stage IV patients. However, the percentage of aberrant metaphases ranged from 15.7 to 23.3% in patients with benign disease, 21.4 to 60% in stage I patients, 20.1 to 50.2% in stage II patients, and 3.3 to 60.1% in stage III patients, suggestive of variability in the underlying genomic composition of these patients. Grouping of patients according to the stage of advancement of disease did not reveal any consistent pattern of variation in lymphocytic CIN [Table 2], in contrast to tumor tissue where genomic instability has been correlated with tumor progression. Genomic instability has been found to be low in benign and hyperplastic tissues, but dramatically increased in ductal carcinoma and invasive cancer.[15] Frequency of allelic imbalance (or MIN) in tumor tissue has been shown to be significantly correlated with tumor progression in colorectal cancer.[16] In a fluorescent in situ hybridization study of numerical alterations of chromosomes 7, 8, 16, and 17 in 28 ductal carcinoma in situ (DCIS), it was shown that the patterns of aneuploidy in breast tumor tissue may differ according to the tumor grade.[17] This indicated that lymphocytic CIN was an index of inherent instability in the patient′s genome and was not influenced by the disease status, whereas genomic instability of the tumor could be influenced by the patient′s disease status or aggressiveness of tumor.

High frequency of aberrations in PBLs of breast cancer patients similar to that seen in tumor tissue has already been reported in several studies.[12,1820] Also, greater than expected infrared-induced genomic instability has been seen in lymphocytes of patients with breast cancer and other solid tumors.[2123] Thus, cancer patients probably have constitutional CIN, which participates in cancer predisposition.

Aberrations involving specific chromosomes (2, 7, 11, 12, 15, 19, 22, and X) in the lymphocytes of breast cancer patients have been reported in a previous study.[20] Various genes involved in genomic stability and breast tumorigenesis [EP300 (22q13.2), LKB1 (19p13.3), FGFR1 (8p11.2), CHEK2 (22q) and K-ras (12p12)] are located in these regions and might be involved in the variable CIN phenotype. The variable CIN phenotype is due to alterations at different CIN loci. CIN genes are involved in a variety of pathways, including chromosome condensation, sister chromatid cohesion, kinetochore structure and function, microtubule formation, and cell-cycle control.[24]

Another interesting observation from the analysis of epidemiological data of the patients was that many of the well-established epidemiological risk factors reported in previous studies on western data (i.e., late age of menopause, early age of menarche, nulliparity, older age at first birth, alcohol consumption, high meat intake, and high socioeconomic status[25,26]) did not account for the etiology of the disease in patients in the present study. Early age at menarche (less than 12 years of age) has been associated with a 10-20% increase in breast cancer risk and delayed menopause (after 54 years of age) maximizes the number of ovulatory cycles, leading to increased breast cancer risk.[2729] Nulliparity and late age at first birth also contribute toward an increased risk of developing breast cancer.[25] In the present study, most of the patients had a normal reproductive and menstrual history. The age at menarche of the patients varied from 12 to 16 years and age at menopause was between 43 and 55 years. Most of them consumed a vegetarian diet and none of them reported alcohol consumption. Thus, some genetic and environmental factors might be acting synergistically and are responsible for the high incidence of breast cancer in this area. Amritsar has many small-scale industries, such as textile processing, woolen, dyeing, electroplating, pharmaceutical, iron foundaries, pulp and paper mills, steel plants, dairy, and glass and plastic mills, and the area adjoining the city is mainly agricultural land, where the use of pesticides and agricultural chemicals is high. Heavy metal contamination has also been reported in agricultural products, soil, and water in and around Amritsar (www.punjabenvironment.com).

In the present study, the patients had much higher CIN than controls. Even patients with benign disease or at stage I had higher CIN than controls. But, the patients had variation in the level of CIN in PBLs with no apparent correlation with disease stage, as a stage I patient had up to 60% aberrant metaphases while a stage II patient had only 3.3% aberrant metaphases. The present study is in agreement with the previous reports on validity of cytogenetic assay for determination of frequency of CAs as a biomarker for cancer risk.[811] Such studies had been subject to criticism due to not accounting for the reverse causality bias, i.e. when the biomarker might be affected by the disease. But, the present study suggests an independence of this biomarker from disease stage. The inherent difference in the level of genomic instability might play a significant role in disease progression, patient tolerance for radiation and antineoplastic agents, and recurrence risk. Breast cancer (BRCA) proteins and their associated molecules (e.g., Fanconi anemia proteins, Ataxia telangiectasia mutated- Ras-associated diabetes (ATM- RAD complex) work in a network of connected biological complexes that encompass virtually all aspects of the cellular response to DNA damage during the S and G2 phases of the cell cycle.[30] Cells lacking these proteins fail to correct endogenous DNA damage during or after DNA synthesis. Individuals with mutation in BRCA or associated proteins show sensitivity to DNA cross-linking agents such as cisplatin and mitomycin C. Determination of the genomic instability level of individual patients before planning therapy may help avoid tissue and cellular damage by radiation and cancer chemotherapy drugs by permitting less-aggressive therapy of the sensitive patients.

Acknowledgments

Financial assistance in the form of grant from Council for Scientific and Industrial Research, India (grant no. 09/254(0162)/2006-EMR-1) to HK and Punjab State Council for Science and Technology (grant no. SSO/P08/80/1269) to GKM is highly acknowledged. We are grateful to Prof. Dr. Geeta Sharma, Principal SGRDIMSR, Amritsar for allowing access to the patients.

Footnotes

Source of Support: Nil

Conflict of Interest: None declared.

References

  • 1.Bardelli A, Cahill DP, Lederer G, Speicher MR, Kinzler KW, Vogelstein B, et al. Carcinogen-specific induction of genetic instability. Proc Natl Acad Sci USA. 2001;98:5770–5. doi: 10.1073/pnas.081082898. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Jallelapali PV, Lengauer C. Chromosome segregation and cancer: Cutting through the mystery. Nat Rev Cancer. 2001;1:109–17. doi: 10.1038/35101065. [DOI] [PubMed] [Google Scholar]
  • 3.Thompson SL, Crompton DA. Examining the link between chromosomal instability and aneuploidy in human cells. J Cell Biol. 2008;180:665–72. doi: 10.1083/jcb.200712029. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Barrios L, Caballin MR, Miro R, Fuster C, Guedea F, Subias A, et al. Chromosomal instability in breast cancer patients. Hum Genet. 1991;88:39–41. doi: 10.1007/BF00204926. [DOI] [PubMed] [Google Scholar]
  • 5.Gebhart E, Romahn R, Schneider A, Hoffmann R, Rau D, Tittelbach H. Cytogenetic studies in lymphocytes of patients with rectal cancer. Environ Health Perspect. 1993;101:169–75. doi: 10.1289/ehp.93101s3169. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Trivedi AH, Roy AK, Bhachech SH, Patel RK, Dalal AA, Bhatavedkar JM, et al. Cytogenetic evaluation of 20 sporadic breast cancer patients and their first degree relatives. Breast Cancer Res Treat. 1998;48:187–90. doi: 10.1023/a:1005951125574. [DOI] [PubMed] [Google Scholar]
  • 7.Doak SH. Aneuploidy in upper gastrointestinal tract cancers: A potential prognostic marker? Mutat Res. 2008;651:93–104. doi: 10.1016/j.mrgentox.2007.10.018. [DOI] [PubMed] [Google Scholar]
  • 8.Bonassi S, Znaor A, Norppa H, Hagmar L. Chromosomal aberrations and risk of cancer in humans: An epidemiologic perspective. Cytogenet Genome Res. 2004;104:376–82. doi: 10.1159/000077519. [DOI] [PubMed] [Google Scholar]
  • 9.Hagmar L, Stromberg U, Bonassi S, Hansteen IL, Knudsen LE, Lindholm C, et al. Impact of type of chromosomal aberrations on human cancer risk: Results from Nordic and Italian Cohorts. Cancer Res. 2004;64:2258–63. doi: 10.1158/0008-5472.can-03-3360. [DOI] [PubMed] [Google Scholar]
  • 10.Rossner P, Boffetta P, Ceppi M, Bonassi S, Smerhovsky Z, Landa K, et al. Chromosomal aberrations in lymphocytes of healthy subjects and risk of cancer. Environ Health Perspect. 2005;113:517–20. doi: 10.1289/ehp.6925. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 11.Boffetta P, van der Hel O, Norppa H, Fabianova E, Fucic A, Gundy S, et al. Chromosomal aberrations and cancer risk: Results of cohort study from central Europe. Am J Epidemiol. 2007;165:36–43. doi: 10.1093/aje/kwj367. [DOI] [PubMed] [Google Scholar]
  • 12.Pathak S, Hopwood VL, Hortobagyi GN, Jackson GL, Hughes JI, Mellilo D. Chromosomal anomalies in human breast cancer: Evidence for specific involvement of 1q region in lymphocyte cultures. Anticancer Res. 1991;11:1055–60. [PubMed] [Google Scholar]
  • 13.Moorhead PS, Nowell PC, Mellman WJ, Battips DM, Hungerford DA. Chromosome preparations of leucocytes cultured from human peripheral blood. Exp Cell Res. 1960;20:613–6. doi: 10.1016/0014-4827(60)90138-5. [DOI] [PubMed] [Google Scholar]
  • 14.Benn PA, Perle MA. Chromosome staining and banding techniques. In: Rooney DE, Czepulkowski BH, editors. Human cytogenetics: A practical approach. Oxford, England: IRL Press Ltd; 1986. p. 54. [Google Scholar]
  • 15.Chin K, de Solorzano CO, Knowles D, Jones A, Chou W, Rodriguez EG, et al. In situ analysis of genome instability in breast cancer. Nat Genet. 2004;36:384–8. doi: 10.1038/ng1409. [DOI] [PubMed] [Google Scholar]
  • 16.Weber JC, Schneider A, Rohr S, Nakano H, Bachelleir P, Mechine A, et al. Analysis of allelic imbalance in patients with colorectal cancer according to stage and presence of synchronous liver metastases. Ann Surg. 2001;234:795–802. doi: 10.1097/00000658-200112000-00011. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Visscher D, Jimenez RE, Grayson M, Mendelin J, Wallis T. Histopathologic analysis of chromosome aneuploidy in ductal carcinoma in situ. Hum Pathol. (3rd) 2000;31:201–7. doi: 10.1016/s0046-8177(00)80220-8. [DOI] [PubMed] [Google Scholar]
  • 18.Udayakumar AM, Bhargava MR. Chromosomal aberrations in peripheral blood lymphocytes of breast cancer patients prior to any therapy. Ann Genet. 1994;37:192–5. [PubMed] [Google Scholar]
  • 19.Bose T. Chromosomal instability in peripheral blood lymphocytes of patients with malignancy. Indian J Hum Genet. 2003;9:10–12. [Google Scholar]
  • 20.Guleria K, Singh HP, Singh J, Kaur H, Sambyal V. Non-random chromosomal aberrations in peripheral blood leucocytes of gastrointestinal tract and breast cancer patients. Int J Hum Genet. 2005;5:205–11. [Google Scholar]
  • 21.Zhang H, Buchholz TA, Hancock D, Spitz MR, Wu X. Gamma-radiation-induced single cell DNA damage as a measure of susceptibility to lung cancer: A preliminary report. Int J Oncol. 2000;17:399–404. doi: 10.3892/ijo.17.2.399. [DOI] [PubMed] [Google Scholar]
  • 22.Buchholz TA, Wu X. Radiation-induced chromatid breaks as a predictor of breast cancer risk. Int J Radiat Oncol Biol Phys. 2001;49:533–7. doi: 10.1016/s0360-3016(00)01502-9. [DOI] [PubMed] [Google Scholar]
  • 23.Colleu-Durel S, Guitton N, Nourgalieva K, Leveque J, Danic B, Chenal C. Genomic instability and breast cancer. Oncol Rep. 2001;8:1001–5. doi: 10.3892/or.8.5.1001. [DOI] [PubMed] [Google Scholar]
  • 24.Cahill DP, Kinzler KW, Vogelstein B, Lengauer C. Genetic instability and Darwinian selection in tumors. Trends Cell Biol. 1999;9:M57–60. [PubMed] [Google Scholar]
  • 25.McPherson K, Steel CM, Dixon JM. ABC of breast diseases: Breast cancer-epidemiology, risk factors and genetics. BMJ. 2000;321:624–8. doi: 10.1136/bmj.321.7261.624. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Robert SA, Strombom I, Trentham-Dietz A, Hampton JM, McElroy JA, Newcomb PA, et al. Socioeconomic risk factors for breast cancer: Distinguishing individual and community level effects. Epidemiology. 2004;15:442–50. doi: 10.1097/01.ede.0000129512.61698.03. [DOI] [PubMed] [Google Scholar]
  • 27.Kelsey JL, Gammon MD, John EM. Reproductive factors and breast cancer. Epidemiol Rev. 1993;15:36–47. doi: 10.1093/oxfordjournals.epirev.a036115. [DOI] [PubMed] [Google Scholar]
  • 28.Titus-Ernstoff L, Longnecker MP, Newcomb PA, Dain B, Greenberg ER, Mittendorf R, et al. Menstrual factors in relation to breast cancer risk. Cancer Epidemiol Biomarkers Prev. 1998;7:783–9. [PubMed] [Google Scholar]
  • 29.Berkey CS, Frazier AL, Gardner JD, Colditz GA. Adolescence and breast carcinoma risk. Cancer. 1999;85:2400–9. doi: 10.1002/(sici)1097-0142(19990601)85:11<2400::aid-cncr15>3.0.co;2-o. [DOI] [PubMed] [Google Scholar]
  • 30.Venkitaraman AR. Tracing the network connecting BRCA Fanconi anaemia proteins. Nat Rev Cancer. 2004;4:266–76. doi: 10.1038/nrc1321. [DOI] [PubMed] [Google Scholar]

Articles from Indian Journal of Human Genetics are provided here courtesy of Wolters Kluwer -- Medknow Publications

RESOURCES