| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
Molecular Oncology, Markers, Clinical Correlates |
1 The Breakthrough Toby Robins Breast Cancer Research Centre, Institute of Cancer Research, London, United Kingdom; 2 The Royal Marsden Hospital, London, United Kingdom; 3 Department of Cellular Pathology, John Radcliffe Hospital, Oxford, United Kingdom; 4 Centre Jean Perrin, Clermont-Ferrand, France; 5 Department of Pathology, Royal Free & University College, London, United Kingdom; 6 Service d’Anatomie Pathologique, Centre G-F Leclerc, Dijon, France; 7 Cancer Research U.K. Genetic Epidemiology Unit, Cambridge, United Kingdom; 8 Department of Experimental Oncology Istituto Nazionale Tumori, Milan, Italy; 9 Department of Pathology, Istituto Nazionale Tumori, Milan, Italy; 10 Department of Obstetrics and Gynaecology, General Hospital, University of Vienna, Vienna, Austria; 11 Department of Clinical Genetics, Oulu University Hospital/University of Oulu, Oulu, Finland; 12 Institute of Pathology and Molecular Immunology, University of Porto, R. Robert Frias, Porto, Portugal; 13 Laboratoire de Genetique, Lyon, France; 14 Mac-Delbruck-Centrum, Berlin, Germany; 15 Deutsches Krebsforschungszentrum, Divisions of Epidemiology and Molecular Genome Analysis, Heidelberg, Germany; 16Department of Genetics and Pathology, Leiden University, Leiden, the Netherlands; 17Department of Clinical Genetics and Medical Oncology, Daniel den Hoed Cancer Centre, Erasmus University Medical Centre Rotterdam, Rotterdam, the Netherlands; 18Department of Genetic Oncology and Cancer Control, Paoli-Calmettes Institute, Marseille, France; 19Cancer Research UK (CRUK) Genetic Epidemiology Laboratory and 20Department of Gynaecological Oncology, St. James University Hospital, Leeds, United Kingdom; 21CRUK Human Cancer Genetics Research Group, Cambridge, United Kingdom; 22Abramson Family Cancer Research Institute, University of Pennsylvania, Philadelphia, Pennsylvania; 23Unite de Genetique Oncologique, Institut Curie, Paris, France; 24Division Epidemiology, Department of Medicine, University of California Irvine, Irvine California; 25Department of Obstetrics and Gynaecology, Helsinki University Central Hospital, Helsinki, Finland; 26Department of Pathology, University of Helsinki, Helsinki, Finland; 27Laboratorio di Biologia Oncologica, Ospedale Infermi, Rimini, Italy
 |
ABSTRACT |
|---|
 Top ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Experimental Design: We performed a systematic review of ovarian tumors from 178 BRCA1 mutation carriers, 29 BRCA2 mutation carriers, and 235 controls with a similar age distribution. Tumors were evaluated by four pathologists blinded to mutation status. Both morphological features and immunochemical staining for p53 and HER2 were evaluated.
Results: Tumors in BRCA1 mutation carriers were more likely than tumors in age-matched controls to be invasive serous adenocarcinomas (odds ratio, 1.84; 95% confidence interval, 1.21–2.79) and unlikely to be borderline or mucinous tumors. Tumors in BRCA1 carriers were of higher grade (P < 0.0001), had a higher percentage solid component (P = 0.001), and were more likely to stain strongly for p53 (P = 0.018). The distribution of pathological features in BRCA2 carriers was similar to that in BRCA1 carriers.
Conclusions: Use of pathological features can substantially improve the targeting of predictive genetic testing. Results also suggest that BRCA1 and BRCA2 tumors are relatively aggressive and may be expected to have poor prognosis, although this may be treatment dependent.
|
INTRODUCTION |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
40% by age 70, with the corresponding risk in BRCA2 carriers being 10% (1)
. Mutations in these genes account for 5–13% of ovarian cancer cases in Western countries (2
, 3)
and for the majority of the familial aggregation of this disease (4)
. Ovarian neoplasms can be subdivided into three main groups: epithelial/stromal, germ cell, or sex cord/stromal. The vast majority (>90%) in the general population are epithelial in origin, and a large proportion of these are benign. All studies performed to date indicate that carcinoma (invasive epithelial malignancy) is the usual histological diagnosis in BRCA1- and BRCA2-associated ovarian cancer. The detailed pattern of histological characteristics in mutation carriers compared with ovarian cancer in noncarriers is less clear because most studies have been based on relatively small numbers of cases. Most of the available information relates to BRCA1-linked disease because BRCA1 germline mutations are approximately four times more common in ovarian cancer patients than BRCA2 mutations (4) . Most studies have reported that papillary serous adenocarcinoma is the predominant type to occur in BRCA1 or BRCA2 carriers. Rubin et al. (5) reported that 43 of 53 women with ovarian neoplasms who carried BRCA1 germline mutations had papillary serous adenocarcinoma. They also found that the tumors were of high grade. Stratton et al. (2) and Berchuck et al. (6) obtained similar results in 12 of 13 and 15 of 15 individuals studied, respectively. These data are further supported by results reported by Risch et al. (3) and more recently by Shaw et al. (7) . However, three larger investigations have reported that papillary serous carcinomas occurred with similar frequency in BRCA mutation carriers compared with control groups (8) .
Most studies have shown that malignant mucinous carcinoma is underrepresented in BRCA1 mutation carriers (2) , suggesting that mutations in this gene do not generally play a role in the development of this subtype of epithelial neoplasm. However, occasional invasive (5) and borderline (2) mucinous neoplasms have been described in BRCA1 mutation carriers.
In a large collaborative study carried out on behalf of the Breast Cancer Linkage Consortium (BCLC), we characterized the histopathological features of breast cancers arising in patients harboring germline mutations in the BRCA1 and BRCA2 genes (9, 10, 11) . The present study extends this approach to ovarian cancer, using cases ascertained through the BCLC resource together with cases identified from the United Kingdom Coordinating Committee on Cancer Research Familial Ovarian Cancer Study Group. It is a systematic blinded detailed review of >200 BRCA-associated ovarian cancers compared with population-based controls carried out by specialist gynecological pathologists. To our knowledge, this is the largest study on the morphology and immunophenotype of these tumors.
|
MATERIALS AND METHODS |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Controls were drawn from a population-based study covering West and North Yorkshire and Humberside over the calendar year 1993 (190 tumors) and from a consecutive series of patients from University College Hospital, London, over the period 1980–1995 (45 tumors). Stratified random sampling by age group (in decades) was used; a higher fraction of younger cases was selected to minimize the difference in the overall age distribution between the familial and unselected tumors.
We obtained specimens from case and control subjects in the form of blocks or unstained 3-µm-thick sections. All familial case and control samples were allocated randomly generated study numbers.
Morphological Analysis.
Samples were analyzed for morphological features by use of an agreed proforma similar to that used in previous BCLC studies (9, 10, 11)
. The forms recorded details of tumor subtype, histological grade (using the Silverberg system), presence or absence of psammoma bodies, percentage of solid component, presence of vascular invasion, presence of necrosis, and total mitotic count. Each slide was read independently by two pathologists (two of S. M., A. M. F., F. P-L., and L. A.). Because the slides were arranged and labeled only by their study number, the pathologists were not aware if the slide being read was from a case subject or a control subject. The numbers in Tables 2
and 4
refer to the number of observations of each histological category (counting the observations by each pathologists separately) rather than the numbers of tumors. No attempt was made to reconcile differences between pathologists because it was difficult to design such a process that would not introduce other biases.
|
|
Statistical Analysis.
Statistical analyses were performed in a manner similar to our previous analyses of breast tumors. We performed separate analyses comparing tumors in BRCA1 carriers and BRCA2 carriers with control tumors. The effects of each morphological feature on cancer status were summarized in terms of odds ratios (ORs). All analyses were adjusted for age in groups of <30, 30–39, 40–49, 50–59, and 60–69 years and by reviewing pathologist. These adjusted analyses were carried out with multiple logistic regression analysis, using the program Stata (version 7.0).
The main complication in the analysis is that the observations by different pathologists on the same slide cannot be considered independent. Use of standard logistic regression therefore leads to unbiased OR estimates but underestimates the SE and confidence intervals (CIs). To correct for this, we computed confidence limits, using the robust sandwich estimator for the variance-covariance matrix (12)
, with the "robust" option in Stata. This approach allows for variation in scoring individual samples between the pathologists without explicitly modeling the error distribution. Significance levels for each factor were derived from the parameter estimates and the covariance matrix (adjusted using the sandwich estimator). For those factors measured on an ordinal scale (e.g., grade) one-degree of freedom tests based on testing for linear trends in log (OR) with increasing category were derived. Heterogeneity 
2 statistics (based on k – 1 degrees of freedom for factors with k levels) are also presented.
To determine which factors were independently predictive of BRCA1 status, we also performed multiple regression analyses. In these analyses, all factors that were significant at the 5% level, together with pathologist and age of the patient, were initially included. Factors (other than age and pathologist) were then removed from the model on a stepwise basis until no further factors could be removed at the 5% level. (The corresponding analysis was not conducted for BRCA2 because the number of tumors was too small and none of the risk factor distributions were clearly different from controls.)
Concordance between pathologists was assessed using 
statistics. For characteristics on an ordinal scale, weighted s were used. Confidence limits were constructed by bootstrapping using 1000 bootstrap replicates.
The predicted prevalence of BRCA1 mutations in ovarian cancer cases with given pathological characteristics were calculated as in previous BCLC analyses of breast cancer (11)
. If there are n risk categories with frequencies p0, p1, ... pn – 1 and the OR for category j versus category 0 according the best model is 
j, then the mutation prevalence for cases in category j is given by:
 |
pjj; and K is the overall prevalence. For the purpose of this analysis we present age-specific prevalences for the age-groups 30–39, 40–49, and 50–69 years (the last of these based on the average of the prevalences in the 50–59 and 60–69 years age groups). The overall prevalence of BRCA1 mutations in ovarian cancer cases in these age groups were derived from the studies by Stratton et al. (2)
and Antoniou et al. (1)
. Stratton et al. (2)
found an overall prevalence of mutations in ovarian cancer cases without a previous breast cancer (and assuming 70% mutation sensitivity in that study) of 4.2%. On the basis of the penetrance estimates for breast and ovarian cancer from the meta-analysis of Antoniou et al. (1)
, the probability of a BRCA1 carrier being affected with ovarian cancer before breast cancer in each age group was as follows: <30 years, 0.015%; 30–39 years, 2.2%; 40–49 years, 8.3%; 50–59 years, 4.9%; 60–69 years, 6.9%. On the basis of these figures and the corresponding population risks for England and Wales, an overall prevalence of 4.2% corresponds to a BRCA1 carrier frequency of 0.3%, and the predicted age-specific prevalence of BRCA1 mutations in ovarian cancers in the age groups 30–39, 40–49, and 50–69 years are 6.6, 9.3 and 3.7%, respectively. Some studies, notably Risch et al. (3)
have reported a higher overall prevalence of ovarian cancer. However, because the pathology-specific prevalence estimates are simply proportional to the assumed overall prevalence, these estimates can be scaled as required. |
RESULTS |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
. Thirteen of the controls were under 30 years of age, whereas none of the tumors in carriers were diagnosed in this age-group. These controls were therefore excluded from all of the analyses. After this exclusion, women with BRCA1 tumors were, on average, younger than the controls, whereas women with BRCA2 tumors were, on average, older than the controls. The University College Hospital, London controls were (by deliberate selection), on average, younger than the Yorkshire controls.
|
Consistency between pathologists was assessed on the remaining 403 tumors. As expected, the statistic was highest for borderline/invasive (0.72) and lowest for vascular invasion (0.14). values for the remaining morphological features varied from 0.39 to 0.57. Agreement was good for p53 staining ( = 0.89) but weaker for HER2 ( = 0.14).
The distribution of morphological characteristics is shown in Table 2
, and the corresponding ORs and significance levels, adjusted for age and pathologist, are listed in Table 3
. The frequency of borderline tumors among BRCA1 carriers (1%) was markedly lower than in the control group (10%; OR, 0.044; P < 0.0001). The frequency of borderline tumors was also lower in the BRCA2 carriers than in the controls (OR, 0.57; 95% CI, 0.15–2.21), but the difference was less marked and not statistically significant.
|
Both BRCA1 and BRCA2 tumors were of higher grade on average than control tumors (P < 0.0001 and P = 0.028 respectively) and had a higher percentage solid component (P = 0.0004 and P = 0.056 respectively). The relationship with mitotic count was less clear. There was some evidence of a difference in the distribution of mitotic count between BRCA1 carriers and controls (heterogeneity P = 0.049), but this was mainly due to a higher frequency of the 20–29 mitoses/10hpf category in the BRCA1 tumors, with no evidence of an elevated frequency of tumors with 30 or more mitoses/10hpf. Mitotic count was higher on average in BRCA2 carriers than controls; again however the test for trend with increasing mitotic count was not significant and the effect was only significant when mitotic count was considered as an (unordered) categorical variable (P = 0.012). None of the other features considered (presence of psammoma bodies, vascular invasion and necrosis) differed significantly in frequency between BRCA1 or BRCA2 tumors and controls.
The results obtained by immunohistochemical examination of the tumors and controls with the antibodies to HER2 and p53 are shown in Table 4
; the corresponding ORs and significance levels are shown in Table 5
. No differences in HER2 expression were identified. There was some evidence for an increased frequency of p53 staining among BRCA1 tumors compared with control tumors. There was no apparent effect for mild staining, but the estimated OR for strong staining compared with no staining was 2.96 (95% CI, 1.18–7.44). A similar pattern was observed for the proportion of cells stained positive for p53. The estimated ORs for BRCA2 were consistent with an effect similar to BRCA1, but the numbers were too small to show a significant difference from controls.
|
. To test the adequacy of this model, we also fitted models that included interactions between histological type, grade, and p53 status and between any of these factors and age at diagnosis. We found no significant evidence of interaction (data not shown).
|
Predicted BRCA1 carrier probabilities for different subgroups based on age and pathology are given in Table 7
. On the basis of age, histological type, and grade, predicted carrier probabilities exceeded 10% for serous tumors that were undifferentiated or poorly differentiated in women 30–49 years of age at diagnosis and moderately differentiated in women 40–49 years of age at diagnosis. They also exceeded 10% for tumors diagnosed as "other histology" for undifferentiated tumors in women diagnosed at age 30–49 or poorly differentiated tumors in women 40–49. In contrast, carrier probabilities were <3% for all categories of mucinous or well-differentiated tumors. Table 7
also illustrates the additional predictive power of p53 staining. Thus, for poorly or undifferentiated serous tumors diagnosed below age 50 with strong p53 staining, the predicted carrier probability exceeded 20%.
|
|
DISCUSSION |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
Histopathological typing of tumors is commonly subject to significant interobserver variation. Ovarian carcinoma is no exception, and categorization is particularly difficult when a lesion is high grade (13)
. Furthermore, consensus criteria for grading ovarian carcinomas have not been agreed on and consequently differ among individuals (14
, 15)
, although a recently proposed system by Shimizu et al. (16)
and validated by Shaw et al. (7)
has helped provide uniformity among pathologists in this area. The difficulty in subtyping ovarian carcinomas is clearly shown in the publication by Pharoah et al. (8)
in which 59% (61 of 133 cases) of the BRCA1-associated neoplasms and 36% (8 of 26 cases) of the BRCA2-associated cancers were classified as unspecified carcinomas. The subjectivity of typing and grading is likely to account, at least in part, for the different results generated from studies undertaken to date. Systematic reviewing of the slides included in familial cancer studies by a group of histopathologists with a specialist interest in gynecological pathology has the benefit of reducing the interobserver diagnostic variation, but this has been performed only in studies by Zweener et al. (17)
, Shaw et al. (7)
and Werness et al. (18)
. We attempted to minimize the effects of interobserver variability in the present study by blinding the pathologists with respect to mutation status, by arranging for each slide to be scored by two different pathologists, and by adjusting for pathologist as a covariate in the analysis. The concordance as measured by values was reasonably high for most features.
Accepting the limitations of morphological analysis, the present results emphasize the greater frequency of serous carcinomas in BRCA1-associated tumors, consistent with previous studies by Rubin et al. (5) , Berchuck et al. (6) , and more recently by Shaw et al. (7) . Conversely, the frequency of mucinous tumors is much lower than among ovarian cancer patients in general. The frequencies of endometrioid and clear cell carcinomas were similar to, or slightly lower than, their frequencies in controls, in accordance with other reports (5) . These types therefore represent a significant fraction of tumors in BRCA1 carriers (36 and 18%, respectively). Although other tumor types, including transitional cell carcinomas, papillary and squamous carcinomas, and sarcomas, were observed, they were rare, accounting for <10% of all tumors. A dysgerminoma arising in a woman with a BRCA1 germline mutation has recently been reported (19) , but we found no examples of malignant germ cell tumors.
We found that borderline tumors are much rarer (as a proportion of all ovarian tumors) in BRCA1 carriers, in accordance with previous observations (20)
. The age-adjusted frequency of borderline tumors was 1/20th of the frequency in unselected cases, whereas the incidence rates for ovarian cancer in women older than age 30 are 50-fold greater than in noncarriers (1)
. Given the wide confidence limits on these estimates, it is thus possible that BRCA1 mutations confer little or no increased risk of borderline ovarian cancer.
Our data demonstrate that BRCA1-associated tumors are of higher grade, on average, than control tumors. This difference has been found in several other studies (5 , 7 , 8 , 21) . In contrast, Berchuck et al. (6) found that although the BRCA1 cases were all of advanced stage (III/IV), they were less likely to be poorly differentiated compared with cases without mutations, and Johannsson et al. (22) did not identify a difference in grade between the ovarian cancers in their BRCA mutation carriers and the control population-based cancer registry group. We have also found a greater proportion of solid tumor in BRCA1 tumors, indicating poor differentiation, an effect also seen by Shaw et al. (7) . The other morphological features, such as vascular invasion, necrosis, and mitotic count, were not significantly associated with BRCA1 positivity in this study.
The requirement that the mutation-positive cases be tested implies that cases with very poor survival may not have been included in our study. Because such cases are likely to be high grade, the effect of grade may, if anything, have been underestimated in this study.
Consistent with the association with grade, we found a higher frequency of strong p53 staining in BRCA1 and BRCA2 tumors. These results are consistent with those of Ramus et al. (23) , who analyzed both p53 immunohistochemistry and p53 mutations in 30 BRCA1, 18 BRCA2, and 33 sporadic ovarian cancers. The frequencies of p53 overexpression in the three groups were 70% for BRCA1, 67% for BRCA2, and 39% for sporadic ovarian carcinomas, whereas the corresponding mutation frequencies were 60, 50, and 30% respectively. In contrast, our study did not reveal any difference in HER2 expression between BRCA1 and BRCA2 ovarian cancers or controls. This contrasts with the pattern in breast cancer, in which HER2 overexpression is less frequent in BRCA-associated cancers than in controls (11) .
This study is the largest formal evaluation of ovarian cancers in BRCA2 carriers, although the number of tumors is still small. We found that the distribution of histology features in BRCA2 carriers was very similar to those in BRCA1 carriers, with a very low frequency of borderline and mucinous tumors, a higher than average frequency of serous tumors, and smaller but significant frequencies of endometrioid and giant-cell tumors. This pattern has been reflected in other, smaller studies (24) . We also found that BRCA2 tumors were of higher than average grade and solid component. This similarity in ovarian cancer pathology between BRCA1 and BRCA2 carriers contrasts with the breast cancer pathology, where there is a very marked contrast between BRCA1- and BRCA2-associated disease. The only notable differences between BRCA1- and BRCA2-related ovarian cancer are the much lower risk in BRCA2 carriers and the different age distributions, with BRCA2-associated disease occurring later in life (1) .
Although there is some disagreement regarding grade as a prognostic factor, the increased frequency of high grade and strong p53 staining, both of which have been shown in some studies to be adverse prognostic factors in tumors in BRCA1 carriers, raises the possibility that the disease may have a poor prognosis in these women. The direct evidence on the survival in carriers is conflicting. Rubin et al. (5) found better survival in carriers, but this effect may, at least in part, have been an artifact because carriers needed to be alive to be tested. Aida et al. (25) found it was twice as likely that women with BRCA-associated cancers had a negative second-look operation compared with their matched controls, whereas Boyd et al. (21) also found that post-chemotherapy disease-free survival was extended compared with that of the nonhereditary group. In contrast, Johannsson et al. (22) found an initial survival advantage in their BRCA1-associated ovarian cancer group that was lost over time. Pharoah et al.(8) found essentially no difference in survival between patients with BRCA1 or BRCA2 germline mutations and noncarriers. The apparent absence of a survival disadvantage in carriers might reflect an increased sensitivity to chemotherapy in carriers. The hypothesis might be particularly pertinent in BRCA2 carriers, given the role of BRCA2 in DNA cross-link repair (26) .
Morphological and immunohistochemical analysis provides a powerful predictor of BRCA1 mutation status that could aid genetic testing programs. Even in the absence of information on family history, the mutation prevalence in women with poorly differentiated and undifferentiated serous tumors exceeds 10% in most age groups, whereas the prevalence of mucinous and well-differentiated tumors is low. The addition of p53 staining further improves prediction. Because carrier distributions of tumor types are similar in BRCA1 and BRCA2 tumors, similar predictions can be made for BRCA2 tumors.
|
ACKNOWLEDGMENTS |
|---|
|
FOOTNOTES |
|---|
The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby marked advertisement in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.
Note: This work was a United Kingdom Coordinating Committee on Cancer Research (UKCCCR)/Breast Cancer Linkage Consortium (BCLC) collaborative study.
Requests for reprints: Sunil R. Lakhani, The Breakthrough Toby Robins Breast Cancer Research Centre, Institute of Cancer Research, Mary-Jean Mitchell Green Building, Chester Beatty Laboratories, Fulham Road, London SW3 6JB, United Kingdom. Phone: 44 020 7153 5525; Fax: 44 020 7153 5533; E-mail: Sunil.Lakhani{at}icr.ac.uk
Received 7/11/03; revised 12/16/03; accepted 12/29/03.
|
REFERENCES |
|---|
|
TopABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONREFERENCES |
|---|
This article has been cited by other articles:
|
|
 |
|
  D S P Tan, C Marchio, and J S Reis-Filho Hereditary breast cancer: from molecular pathology to tailored therapies J. Clin. Pathol., October 1, 2008; 61(10): 1073 - 1082. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 D. C. Allain Genetic Counseling and Testing for Common Hereditary Breast Cancer Syndromes: A Paper from the 2007 William Beaumont Hospital Symposium on Molecular Pathology J. Mol. Diagn., September 1, 2008; 10(5): 383 - 395. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 M. Soegaard, S. K. Kjaer, M. Cox, E. Wozniak, E. Hogdall, C. Hogdall, J. Blaakaer, I. J. Jacobs, S. A. Gayther, and S. J. Ramus BRCA1 and BRCA2 Mutation Prevalence and Clinical Characteristics of a Population-Based Series of Ovarian Cancer Cases from Denmark Clin. Cancer Res., June 15, 2008; 14(12): 3761 - 3767. [Abstract] [Full Text] [PDF]
|
|
|
|
|
|
R. A. Oldenburg, K. Kroeze-Jansema, H. Meijers-Heijboer, C. J. van Asperen, N. Hoogerbrugge, I. van Leeuwen, H. F.A. Vasen, A.-M. Cleton-Jansen, J. Kraan, J. J. Houwing-Duistermaat, et al. Characterization of Familial Non-BRCA1/2 Breast Tumors by Loss of Heterozygosity and Immunophenotyping. Clin. Cancer Res., March 15, 2006; 12(6): 1693 - 1700. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 H. M. Sowter and A. Ashworth BRCA1 and BRCA2 as ovarian cancer susceptibility genes Carcinogenesis, October 1, 2005; 26(10): 1651 - 1656. [Abstract] [Full Text] [PDF]
|
|
|
|
 |
|
 J. E. Garber and K. Offit Hereditary Cancer Predisposition Syndromes J. Clin. Oncol., January 10, 2005; 23(2): 276 - 292. [Abstract] [Full Text] [PDF]
|
|
| ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| HOME | HELP | FEEDBACK | SUBSCRIPTIONS | ARCHIVE | SEARCH | TABLE OF CONTENTS |
| Cancer Research | Clinical Cancer Research |
| Cancer Epidemiology Biomarkers & Prevention | Molecular Cancer Therapeutics |
| Molecular Cancer Research | Cancer Prevention Research |
| Cancer Prevention Journals Portal | Cancer Reviews Online |
| Annual Meeting Education Book | Meeting Abstracts Online |
