Abstract Background: Adjuvant chemotherapy (ACT) using anthracyclines and taxanes is a standard treatment for BC. Usual criteria as age, SBR grade, HER2 or hormonal status (HS), estrogen receptor (ER), triple negative BC, histological type, lymphovascular invasion (LVI), Ki67, tumor size and lymph node involvement are not yet sufficient for ACT decision. As SNPs located in genes involved in metabolism or transport of cytotoxic drugs may affect efficacy of ACT, we investigated the potential of 49 SNPs to predict response to ACT in BC. Methods: From 01/2008 to 01/2012, 418 patients (pts) with BC treated with ACT were included. 309 pts received FEC100-Docetaxel regimen (cohort 1), and 109 pts with HER2 overexpression FEC100-Docetaxel-Trastuzumab regimen (cohort 2). Genotyping of 49 SNPs was performed on germline DNA using real time PCR with SNPType (Fluidigm) or Taqman probes (Life technologies) on BioMark Platform (Fluidigm). PFS, MFS and overall survival (OS) were estimated by Kaplan-Meier method. Association of clinicopathologic features (CPF) with PFS/MFS was evaluated by log-Rank test. After ensuring Hardy-Weinberg equilibrium was respected, PFS/MFS were correlated to CPF and genotypes, using univariate and multivariate Cox logistic regression. A prognostic score was established. Results: PFS, MFS and OS rates were respectively 81.8%, 83.4% and 87.3% in cohort 1 (3.4 years of median follow up (FU)) and 90.1%, 90% and 93.8% in cohort 2 (4 years of FU). In cohort 1, univariate analysis revealed that 5 SNPs, SLCO1B3 (rs11045585), NOS3 (rs1799983), CYB2B6 (rs2279345), BRCA1 (rs799917) and CYP2D6 (rs3892097) were associated with MFS. Genotypes, HR, 95%CI and p value are as follows: SLCO1B3 GG 7.73 (1.83-32.7) p=0.001, NOS3 GT 0.32 (0.14-0.76) p=0.006, CYB2B6 TT 2.29 (1.02-5.13) p=0.04, BRCA1 CT 0.41 (0.19-0.89) p=0.02, and CYP2D6 AG 2.14 (1.05-4.36) p=0.03. Multivariate analysis revealed that 4 SNPs remained associated with metastatic risk: CYB2B6; TT 2.38 (1.05-5.41) p=0.038, NOS3; GG-TT 3.11 (1.33-7.27) p=0.009, BRCA1; CC-TT 2.21 (1.01-4.85) p=0.047, CYP2D6; AG 2.14(1.04-4.40) p=0.039. No CPF was associated with survival. Prognostic model revealed a metastatic risk of 10.25 (1.29-81.31) if these four adverse genotypes coexist. In cohort 2, subject to limited number of events, age (p=0.03), HS (p=0.06), ER (p=0.05), LVI (p=0.02) tumor size (p=0.003) and 2 SNPs were associated in univariate with PFS: CYB2B6 (rs2279345); CT 5.73 (1.22-27) p=0.01, MTHFR (rs1801133); CT 4.61 (0.98-21.7) p=0.03. Multivariate analysis showed unfavorable PFS for heterozygous patients for CYB2B6 or for MTHFR: 9.67 (1.82-51.28) p=0.008 and 5.62(1.19-26.59) p=0.03 respectively and if tumor size was ≥T2 10.78 (2.12-54.90) p=0.004. Conclusion: SNPs of genes involved in oxidative stress (NOS3 rs1799983; GG-TT), docetaxel transport (SLCO1B3 rs11045585; GG) cyclophosphamide (CYB2B6 rs2279345; TT in cohort 1 ou CT in cohort 2) and 5FU metabolism (MTHFR rs1801133; CT), or DNA repair (BRCA1rs799917; CC-TT) are associated with survival in pts treated with ACT. BRCA1, CYB2B6 and SLCO1B3 represent potential attractive tools for guiding ACT indication. Citation Format: Ducoulombier A, Dumont A, Revillion F, Bonneterre J, Peyrat J-P. Evaluation of single nucleotide polymorphisms (SNPs) as predictive factors of progression (PFS) and metastatic (MFS) free survival in adjuvant breast cancer (BC). [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P5-08-24.

Abstract The interest of rapid BRCA analysis, even before the initial treatment could modify the surgical indications (ie total mastectomy and immediate reconstruction even in case where tumorectomy would be suitable). The aim of this study was to evaluate the indications and consequences of this rapid determination of BRCA status in our institution. Patients Rapid BRCA analysis was conducted in 129 patients (pts) treated for breast cancer and addressed to the genetician at Oscar Lambret Center between 2009 and 2014: in 98 pts to discuss breast and axilla surgical modalities, in 4 cases to discuss oophorectomy, in 3 cases to have access to PARP inhibitors. In the other 24 pts, the reasons were debatable: patient leaving abroad, patient requiring reproductive assisted technology..... Results 38 deleterious mutations (29,4%) were identified (31 BRCA1, 7 BRCA2) in 38 pts. Cancer treatment was on going for 107 pts, programmed for 12 pts and finished for 10. The median time between cancer diagnosis and genetic counseling was 81 days (5-5160), between blood sample collection and BRCAs analysis 37 days (13-132), between availability of the laboratory results and the information to the patient: 39 days (1-234); 7 pts (5.4%) never came to obtain the laboratory results. Treatment was modified after genetic counselling for 8 pts out of 119 (7%). Six of them had BRCA1 deleterious mutations. Three decided subsequent radical mastectomy and adjuvant radiation was cancelled, another had a radical mastectomy before radiation, another treated for bilateral breast cancer had a bilateral radical mastectomy before radiation and the last treated for unilateral breast cancer had a bilateral radical mastectomy before radiation. Out of these 8 pts, two did not have a deleterious mutation. One had a bilateral radical mastectomy before laboratory result and one with BRCA variant of unknown significance had a homolateral radical mastectomy. Conclusion discussion Our experience shows that rapid BRCA analysis is feasible. In this selected population the mutation rate is very high. However, first, it appears that indications for rapid BRCA analysis were variable and not always relevant. Second, genetic result impacts on treatment only in 7% of pts. Indications could be justified by the use of PARP inhibitors. Up to now, the indications of rapid genetic analysis are rare. Citation Format: Mailliez A, Herin H, Revillion F, Adenis C, Peyrat J-P, Bonneterre J. Rapid BRCA analysis: Experience of a single institution. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-09-15.

Abstract Breast cancer is the most frequent female cancer with 48 800 new cases each year in France. A French national screening program in women without genetic risk factors has been initiated in 2004. Women with BRCA 1 or 2 mutations are included in surveillance programs. Women without such mutations can be assessed for breast cancer risk using risk prediction models. The aim of this study is to compare the performance of three breast cancer risk prediction models: GAIL2, BODICEA and IBIS in a population of patients (pts) who developed breast cancer. Patients and Methods: The GAIL1 model was performed to 188 pts at high risk of breast cancer according to their family history and who developed breast cancer. Personal and familial data was regenerated at the day before the diagnosis of breast cancer and the three models were applied. From this population, 60 pts were selected: for whom all information necessary to use the 3 models was available and for whom the GAIL1 model provided sufficient variability in the relative risk of breast cancer. The GAIL2 model takes into account individual risk factors: age, menarches, parity, age at first birth, history of breast biopsy, atypical hyperplasia or in situ lobular carcinoma. The BODICEA model considers age and familial risk factors: number of related affected by breast ovarian, prostate and pancreas cancer and age at diagnosis. Both personal and familial risk factors are used for the IBIS model. We estimated lifetime breast cancer risk for each patient with the three models from the available software packages. We assessed Pearson's correlation coefficient between the three models. Results Median (range) age was 45 years (25-74). Risk prediction could not be evalauted by the GAIL2 model for 14 pts since they were less than 35 years of age. Lifetime breast cancer risk was 16.1% (4.4-38.7) for GAIL2, 11.6% (2.2-39.5) for BODICEA and 16.5% (3.5-36.3) for IBIS. Pearson's correlation coefficient between BODICEA and GAIL2, IBIS and GAIL2 and between BODICEA and IBIS were 0.36, 0.38 and 0.69 respectively. In most cases, IBIS risk predictions were higher than GAIL2's which were higher than BODICEA's as soon as lifetime risk was at least 20%. When the three models were applicable (46pts), IBIS estimated a higher risk in 31 cases (67%) versus 10 for GAIL2 (21.74%) and 5 for BODICEA (10.86%). The median (range) time for use of the tools per patient was 30 seconds (16-80) for GAIL2, 588 (198-1804) for BODICEA and 86 (46-135) for IBIS. Discussion Results in this selected population of pts who developed breast cancer show that IBIS seems to be the better performer to predict breast cancer risk:. Results are obtained faster and the risk predictions provide higher estimates. The GAIL2 model is quick and easy to use but with a limited number of items. Conversely, BODICEA requires a very large number of items, not always available, and does not consider incomplete data. In conclusion, IBIS model seems to be the most suitable for practical use in the evaluation of breast cancer risk. Citation Format: Mailliez A, Kramar A, Peyrat J-P, Revillion F, Bonneterre J. Comparison of prediction models of breast cancer in high risk populations?. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-09-16.

Breast cancer is the most frequent female cancer with 48 800 new cases each year in France. A French national screening program in women without genetic risk factors has been initiated in 2004. Women with BRCA 1 or 2 mutations are included in surveillance programs. Women without such mutations can be assessed for breast cancer risk using risk prediction models. The aim of this study is to compare the performance of three breast cancer risk prediction models: GAIL2, BODICEA and IBIS in a population of patients (pts) who developed breast cancer. Patients and Methods: The GAIL1 model was performed to 188 pts at high risk of breast cancer according to their family history and who developed breast cancer. Personal and familial data was regenerated at the day before the diagnosis of breast cancer and the three models were applied. From this population, 60 pts were selected: for whom all information necessary to use the 3 models was available and for whom the GAIL1 model provided sufficient variability in the relative risk of breast cancer. The GAIL2 model takes into account individual risk factors: age, menarches, parity, age at first birth, history of breast biopsy, atypical hyperplasia or in situ lobular carcinoma. The BODICEA model considers age and familial risk factors: number of related affected by breast ovarian, prostate and pancreas cancer and age at diagnosis. Both personal and familial risk factors are used for the IBIS model. We estimated lifetime breast cancer risk for each patient with the three models from the available software packages. We assessed Pearson9s correlation coefficient between the three models. Results Median (range) age was 45 years (25-74). Risk prediction could not be evalauted by the GAIL2 model for 14 pts since they were less than 35 years of age. Lifetime breast cancer risk was 16.1% (4.4-38.7) for GAIL2, 11.6% (2.2-39.5) for BODICEA and 16.5% (3.5-36.3) for IBIS. Pearson9s correlation coefficient between BODICEA and GAIL2, IBIS and GAIL2 and between BODICEA and IBIS were 0.36, 0.38 and 0.69 respectively. In most cases, IBIS risk predictions were higher than GAIL29s which were higher than BODICEA9s as soon as lifetime risk was at least 20%. When the three models were applicable (46pts), IBIS estimated a higher risk in 31 cases (67%) versus 10 for GAIL2 (21.74%) and 5 for BODICEA (10.86%). The median (range) time for use of the tools per patient was 30 seconds (16-80) for GAIL2, 588 (198-1804) for BODICEA and 86 (46-135) for IBIS. Discussion Results in this selected population of pts who developed breast cancer show that IBIS seems to be the better performer to predict breast cancer risk:. Results are obtained faster and the risk predictions provide higher estimates. The GAIL2 model is quick and easy to use but with a limited number of items. Conversely, BODICEA requires a very large number of items, not always available, and does not consider incomplete data. In conclusion, IBIS model seems to be the most suitable for practical use in the evaluation of breast cancer risk. Citation Format: Mailliez A, Kramar A, Peyrat J-P, Revillion F, Bonneterre J. Comparison of prediction models of breast cancer in high risk populations?. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P2-09-16.

Dans le cancer du sein, le développement des marqueurs biologiques pronostiques ou prédictifs a pour objectif de mieux identifier les patientes pour lesquelles un traitement par chimiothérapie pourrait être évité ou a contrario indiqué. Dans ce contexte, en 2009, l’Institut national du cancer (INCa), agence sanitaire et scientifique de l’État chargée de coordonner les actions de lutte contre le cancer, avait publié en partenariat avec la Société française de sénologie et de pathologie mammaire un rapport sur l’état des connaissances relatives aux biomarqueurs uPA/PAI-1, Oncotype DX™ et MammaPrint® dans la prise en charge du cancer du sein. Ce rapport avait montré que seule la valeur pronostique d’uPA/PAI-1 atteignait le plus haut niveau de preuve (LOE I selon la grille de Hayes 1998). En 2012, devant la parution de nouvelles publications et la divergence des messages diffusés sur les signatures moléculaires, il a été décidé d’actualiser le rapport de 2009. Cet article présente les principales conclusions accompagnées de leurs niveaux de preuve.

Breast cancer prognosis and predictive biomarkers development would allow sparing some patients from chemotherapy or identifying patients for whom chemotherapy would be indicated. In this context, in 2009, the French National Cancer Institute, a National Health and Science Agency dedicated to cancer, in collaboration with the A << Soci,t, fran double dagger aise de s,nologie et de pathologie mammaire A >> published a report on the assessment of the prognostic and the predictive clinical validity of tissular biomarkers, uPA/PAI-1, Oncotype DX (TM) and MammaPrint A (R), in breast cancer management. They concluded that only the uPA/PAI-1 prognosis value reached the highest level of evidence (LOE I according to Hayes 1998 classification). In 2012, it was decided to update this report since new data have emerged and because information disparities among clinicians have been identified. This article aims to present the main conclusions together with the levels of evidence associated with those conclusions.The updating process was based on literature published since 2009 appraisal and on multidisciplinary and independent experts' opinion. The levels of evidence (LOE) used are those of the classification defined by Simon in 2009 (updated Hayes 1998 classification): LOE IA and LOE IB: high level of evidence; LOE IIB and LOE IIC: intermediate level of evidence; LOE IIIC and LOE IV-VD: low level of evidence.Among patients without lymph-node involvement, uPA/PAI-1, invasion process biomarkers, reach the highest level of evidence for 10 years recurrence free survival prognosis (LOE IA according to Simon). The predictive value to anthracyclins chemotherapy remains to be confirmed. No data were identified on uPA/PAI-1 medico-economic value. Oncotype DX (TM) and MammaPrintA (R) prognosis and predictive value do not reach the LOE I level. This updating' process confirms the 2009 levels of evidence for all the three biomarkers prognosis value. Besides, concerning Oncotype DX (TM) and MammaPrintA (R), new data do not allow to conclude neither to their complementary clinical information to other clinicopathological existing biomarkers nor to a favorable cost-efficiency ratio in therapeutic decision making and this because of the methodological weakness and uncertainty that are identified in the selected studies. Practically, beyond the prognosis and predictive biomarkers validity, the clinical utility of a new biomarker for chemotherapy indication depends on its clinical added information with regard to validated biomarkers (HR, HER2 and Ki67) and to clinicopathological parameters. Since they are the sole validated biomarkers of the invasion process, uPA/PAI-1 could complete clinical information of other clinicopathological factors and consequently could confer an added clinical value. However, data concerning the impact of this information on chemotherapy clinical indication are lacking.

A pathological complete response (pCR) after neoadjuvant chemotherapy is observed in approximately 20% of breast cancer patients. A proteomic analysis was performed on plasma and tumor tissue before treatment to evaluate its potential impact on the prediction of response. One hundred and forty-nine breast cancer patients eligible for neoadjuvant chemotherapy were included in the study between February 2004 and January 2009 at three centers. The proteomic analysis was performed using SELDI Technology (ProteinChip CM10 pH4, IMAC-Cu and H50). Three acquisition protocols were used according to the mass range. Plasma and tumor proteomic signatures were generated using generalized ROC criteria and cross-validation. Twenty-eight (18.8%) patients out of 149 experienced a pCR according to Sataloff criteria. In the cytosol analysis, respectively 4, 2 and 8 proteins had significantly different levels of expression in the responders and non-responders using IMAC-Cu, H50 and CM10 pH4. Among the 8 proteins of interest on CM10 pH4, 2 (C1 and C7) were selected and were validated in 95.0 and 85.6% of the models. In the plasma analysis, respectively 12, 6 and 2 proteins had different levels of expression using the same proteinchips. Among the 12 plasma proteins of interest on IMAC-Cu, 2 (P1 and P7) were selected and were validated in 94.8 and 97.6% of the models. A combined proteomic signature was generated, which remained statistically significant when adjusted for hormone receptor status and Ki-67. Our results show that proteomic analysis can differentiate complete pathological responders in breast cancer patients after neoadjuvant chemotherapy.

Hereditary breast cancers account for up to 5-10 % of breast cancers and a majority are related to the BRCA1 and BRCA2 genes. However, many families with breast cancer predisposition do not carry any known mutations for BRCA1 and BRCA2 genes. We explored the incidence of rare large rearrangements in the coding, noncoding and flanking regions of BRCA1/2 and in eight other candidate genes-CHEK2, BARD1, ATM, RAD50, RAD51, BRIP1, RAP80 and PALB2. A dedicated zoom-in CGH-array was applied to screen for rearrangements in 472 unrelated French individuals from breast-ovarian cancer families that were being followed in eight French oncogenetic laboratories. No new rearrangement was found neither in the genomic regions of BRCA1/2 nor in candidate genes, except for the CHEK2 and BARD1 genes. Three heterozygous deletions were detected in the 5' and 3' flanking regions of BRCA1. One large deletion introducing a frameshift was identified in the CHEK2 gene in two families and one heterozygous deletion was detected within an intron of BARD1. The study demonstrates the usefulness of CGH-array in routine genetic analysis and, aside from the CHEK2 rearrangements, indicates there is a very low incidence of large rearrangements in BRCA1/2 and in the other eight candidate genes in families already explored for BRCA1/2 mutations. Finally, next-generation sequencing should bring new information about point mutations in intronic and flanking regions and also medium size rearrangements.

The variable penetrance of breast cancer in BRCA1/2 mutation carriers suggests that other genetic or environmental factors modify breast cancer risk. Two genes of special interest are prohibitin (PHB) and methylene-tetrahydrofolate reductase (MTHFR), both of which are important either directly or indirectly in maintaining genomic integrity. To evaluate the potential role of genetic variants within PHB and MTHFR in breast and ovarian cancer risk, 4102 BRCA1 and 2093 BRCA2 mutation carriers, and 6211 BRCA1 and 2902 BRCA2 carriers from the Consortium of Investigators of Modifiers of BRCA1 and BRCA2 (CIMBA) were genotyped for the PHB 1630 C>T (rs6917) polymorphism and the MTHFR 677 C>T (rs1801133) polymorphism, respectively. There was no evidence of association between the PHB 1630 C>T and MTHFR 677 C>T polymorphisms with either disease for BRCA1 or BRCA2 mutation carriers when breast and ovarian cancer associations were evaluated separately. Analysis that evaluated associations for breast and ovarian cancer simultaneously showed some evidence that BRCA1 mutation carriers who had the rare homozygote genotype (TT) of the PHB 1630 C>T polymorphism were at increased risk of both breast and ovarian cancer (HR 1.50, 95%CI 1.10–2.04 and HR 2.16, 95%CI 1.24–3.76, respectively). However, there was no evidence of association under a multiplicative model for the effect of each minor allele. The PHB 1630TT genotype may modify breast and ovarian cancer risks in BRCA1 mutation carriers. This association need to be evaluated in larger series of BRCA1 mutation carriers.

10551 Background: A pathological complete response (PCR) after neoadjuvant chemotherapy is observed in about 20% of the patients. A proteomic analysis was performed on plasma and tumor before treatment to evaluate its potential interest in the prediction of response. Patients: One hundred and forty-nine patients eligible for neoadjuvant chemotherapy were included in the study. Methods: Before treatment plasma and tissues (fine needle aspirations) were collected and frozen at –80°C and in liquid nitrogen respectively. The proteomic analysis was performed using the SELDI Technology. One μl of plasma and 10 μg of cytosolic proteins were loaded on proteinchip CM10 pH4, Imac-Cu, H50 arrays. Three acquisition protocols were used according to the mass range. The differences between protein levels in the two populations (responder and non responder) were detected using Mann Withney tests. Then plasma and tumor proteomic signatures, in relation to tumor response, were determined. Results: 28 patients out of 149 experienced a PCR according to Sataloff criteria. In the cytosols, we observed 180 different proteins using CM10 pH4 arrays. For 8 proteins, the levels were statistically different between the 2 populations (responders vs non responders). In the plasma we observed 98 different proteins using Imac-Cu arrays. For 12 proteins, the levels were statistically different between the two populations (responders vs non responders). Using these conditions, proteomic signatures were established allowing the classification of samples. Considering the logistic regression, for a classification cut-off of 0.5, the specificities (number of classified non-responders according to the proteomic analysis / number of pathological non responders) were 92.9% in cytosols and 95.5% in plasma; the sensitivities (number of classified responders/number of PCR) were respectively 33.3% and 27.3%. Conclusions: Proteomic analyses allow the selection of the majority of non responder patients. We are now analyzing the results including clinical and biological parameters. This determination together with other predictive factors might be useful in the early prediction of treatment efficacy and avoid toxic chemotherapy regimens. No significant financial relationships to disclose.

Abstract Background: The effects of progesterone are mediated by two distinct nuclear receptors, called PR-A and PR-B, which are encoded by a single gene. In the normal human breast, these two isoforms are co-expressed at similar levels of expression whereas breast cancer seems to be characterized by an unbalanced expression of PR-A and PR-B, with a predominance of either one of these two isoforms. In the present study, we analyzed the relationships between the PR isoforms and the HER receptors and ligands network in primary breast cancer.Materials and Methods: This study involves 299 breast cancer samples from patients operated in our institute for locoregional disease between May 1989 and December 1991. Since PR-A has no specific sequence to distinguish it from PR-B, the mRNA expression of total PR-(A+B) isoforms as well as those of PR-B were assessed. They were quantified by real time quantitative RT-PCR using TaqMan probes, as previously described for HER receptors (Epidermal Growth Factor Receptor EGFR, HER2, HER3, and HER4) (Pawlowski et al, Clin Cancer Res 2000;6:4217-25) and HER ligands (EGF, Transforming Growth Factor alpha (TGFa), amphiregulin (AREG), betacellulin (BTC), Heparin-Binding EGF (HB-EGF), Epiregulin (EREG), and neuregulins 1-4 (NRG1-4)) (Révillion et al, Ann Oncol 2008;19:73-80).Results: PR-(A+B) and PR-B mRNA levels strongly correlated with PR and ER protein levels determined by radioligand assay. PR-(A+B) were found to correlate positively to IGF1 receptor, and both isoforms correlated negatively to histoprognostic grading. Considering the HER receptor and ligands network, PR-(A+B) were positively correlated with HER3, HER4, EGF, AREG, while they were negatively correlated with EGFR, TGFa, HB-EGF, EREG, and NRG2. Similarly, a positive correlation was found between PR-B and HER3, HER4, EGF and AREG while PR-B correlated negatively to EREG, NRG3 and NRG4. Finally, PR-(A+B) expression (higher than the lower quartile) was significantly associated with a longer overall survival (p= 0.02, Kaplan-Meier analysis).Conclusion: Our results, demonstrating strong correlations between PR isoforms and HER receptors and ligands network, reinforce the observations (Proietti et al, Mol Cell Biol 2009;29:1249-65) demonstrating that cross-talk between PR and the HER family appears to be a hallmark of breast cancer growth. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 4150.

In this study we aimed to evaluate the role of a SNP in intron 1 of the ERCC4 gene (rs744154), previously reported to be associated with a reduced risk of breast cancer in the general population, as a breast cancer risk modifier in BRCA1 and BRCA2 mutation carriers. We have genotyped rs744154 in 9408 BRCA1 and 5632 BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and assessed its association with breast cancer risk using a retrospective weighted cohort approach. We found no evidence of association with breast cancer risk for BRCA1 (per-allele HR: 0.98, 95% CI: 0.93–1.04, P=0.5) or BRCA2 (per-allele HR: 0.97, 95% CI: 0.89–1.06, P=0.5) mutation carriers. This SNP is not a significant modifier of breast cancer risk for mutation carriers, though weak associations cannot be ruled out.

Background:In this study we aimed to evaluate the role of a SNP in intron 1 of the ERCC4 gene (rs744154), previously reported to be associated with a reduced risk of breast cancer in the general population, as a breast cancer risk modifier in BRCA1 and BRCA2 mutation carriers.Methods:We have genotyped rs744154 in 9408 BRCA1 and 5632 BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and assessed its association with breast cancer risk using a retrospective weighted cohort approach.Results:We found no evidence of association with breast cancer risk for BRCA1 (per-allele HR: 0.98, 95% CI: 0.93–1.04, P= 0.5) or BRCA2 (per-allele HR: 0.97, 95% CI: 0.89–1.06, P= 0.5) mutation carriers.Conclusion:This SNP is not a significant modifier of breast cancer risk for mutation carriers, though weak associations cannot be ruled out.

Lymph node metastases are a major prognostic factor in cervical carcinomas. The aim of this study was to characterize the expression of 11 markers in cervical tumors and negative lymph nodes and to determine which ones could be helpful for improving the specificity of molecular diagnosis of nodal involvement. Using TaqMan RT-PCR, we studied the expression of CK19, MUC1, HER1-HER4, VEGF, VEGF-C, uPA, MMP9, and PRAD1 in uterine cervical tumors and in histologically nonmetastatic lymph nodes of 8 patients diagnosed with locally advanced cervical cancer. We observed that CK19, MUC1, HER1-HER3, uPA, and VEGF had a significantly higher expression in cervical tumors than in the negative nodes, whereas VEGF-C expression level was higher in the negative nodes than in the tumors. PRAD1 harbored similar expression levels in the tumors and in the negative nodes. Interestingly, 1 of the 4 patients who presented a clinical recurrence, showed elevated HER1, HER2, uPA, and VEGF in the histologically negative nodes. Our results suggest that CK19, MUC1, HER1-3, uPA, and VEGF are biomarkers that have a higher expression in tumoral cervical tissues compared with the negative lymph nodes and could be useful to diagnose nodal involvement in uterine cervical carcinoma. Our results should encourage us in continue to investigate a greater number of patients, including patients with histologically involved nodes.

Les liens entre obésité et cancer du sein pourraient résulter de l’action d’adipokines produites par les cellules adipeuses. Parmi ces adipokines, la leptine semble jouer un rôle important. La présence de ses récepteurs sur les cellules de cancers du sein montre qu’elle peut agir directement sur ces cellules: elle est de fait capable de stimuler leur prolifération. Les voies d’action empruntées sont endocrine, paracrine et autocrine. De plus, la leptine serait capable de s’opposer aux traitements anti-estrogéniques. Ces observations suggèrent que le blocage de la leptine aurait un intérêt thérapeutique dans les cancers du sein.

At the Centre Oscar Lambret, the anticancer centre of the North of France, sentinel lymph node (SLN) procedures are routinely performed for localized (T0–T1, N0, M0) breast carcinoma without any previous treatment, in order to prevent the deleterious effects of axillary lymph node dissection. The present study was undertaken to assess if the expression in the tumor of a panel of 19 genes would allow to predict histological SLN involvement. We looked at cytokeratin 19 (CK19), mucin-1 (MUC1), mammaglobin (MGB1), cyclin D1 (CCND1), the four members of the HER/ErbB growth factor receptor family (EGFR, HER2–4), insulin-like growth factor-1 receptor (IGF-1R), estradiol receptors (ERcx, ERβ), progesterone receptor (PR), vascular endothelial growth factors (VEGF, VEGF-C), urokinase-like plasminogen activator (uPA), matrix metalloproteinases 2 and 9 (MMP2, MMP9), ets-related transcription factor ERM, and E-cadherin (CDH1). Their expression was quantified by real-time RT-PCR in 134 breast cancer samples and the relationships with SLN metastases were analyzed. A slight increase (35–40%) in CK19 and HER3 expression was observed in the tumors of patients with SLN metastases compared to those of patients without metastases, even if neither CK19 expression nor HER3 expression allowed to distinguish patients with micrometastases from patients with macrometastases. We conclude that the tumoral expression of biological parameters involved in cell proliferation or playing a critical role in the metastatic process, including tumor invasion and angiogenesis, is not strongly associated with SLN metastases.