DNA methylation profiling reveals a predominant immune component in breast cancers.

Breast cancer is a molecularly, biologically and clinically heterogeneous group of disorders. Understanding this diversity is essential to improving diagnosis and optimizing treatment. Both genetic and acquired epigenetic abnormalities participate in cancer, but the involvement of the epigenome in breast cancer and its contribution to the complexity of the disease are still poorly understood. By means of DNA methylation profiling of 248 breast tissues, we have highlighted the existence of previously unrecognized breast cancer groups that go beyond the currently known 'expression subtypes'. Interestingly, we showed that DNA methylation profiling can reflect the cell type composition of the tumour microenvironment, and in particular a T lymphocyte infiltration of the tumours. Further, we highlighted a set of immune genes having high prognostic value in specific tumour categories. The immune component uncovered here by DNA methylation profiles provides a new perspective for the importance of the microenvironment in breast cancer, holding implications for better management of breast cancer patients.

Fine tuning of the Van Nuys prognostic index (VNPI) 2003 by integrating the genomic grade index (GGI): new tools for ductal carcinoma in situ (DCIS).

Ductal carcinoma in situ (DCIS) is considered a heterogeneous premalignant condition of the breast with a certain probability for progressing to malignancy. There is no standard of care. The updated Van Nuys Prognostic Index (VNPI) 2003 is a clinical tool in treatment decision making. This study assessed the prognostic value of the VNPI after integration of proliferative biomarkers (GGI and Ki-67). DCIS samples were divided into three VNPI subgroups (low risk [score 4-6], intermediate risk [score 7-9], high risk [score 10-12]) based on nuclear grade ± necrosis, tumor size, margin width, and age. Nuclear grade was substituted by the genomic grade index (GGI) to generate the VNPI-GGI and combined with the Ki-67 to generate the VNPI-Ki67. Disease-free survival was calculated by Kaplan-Meier survival plots with log-rank significance. Multiple regression analysis was carried out using Cox proportional hazard regression analysis. A total of 88 cases (median age 54 years) with representative tissue were identified out of 168 DCIS patients. Median follow-up was more than 5 years. Ten patients developed an ipsilateral recurrence of whom nine were invasive: six patients were classified in the VNPI subgroup 2 and three patients in the VNPI subgroup 3. One non-invasive recurrence (DCIS) was classified in the VNPI subgroup III. A statistical association was observed between a high VNPI score and a higher risk of recurrence (HR = 7.72 [95% CI 1.01-58.91], p = 0.049). Ki-67 did not improve the prognostic value of VNPI (HR = 6.5, [95% CI 0.80-53.33], p = 0.08). In contrast, the VNPI-GGI could identify more accurately high-risk DCIS patients with early relapses within 5 years (HR = 18.14 [95% CI 1.75-188], p = 0.015). GGI incorporated into the VNPI improved its prognostic value for DCIS, especially for identifying early relapses. This method should be validated and incorporated in future prospective clinical DCIS trials.

Low CD10 mRNA expression identifies high-risk ductal carcinoma in situ (DCIS).

PURPOSE: Optimal management of breast ductal carcinoma in situ (DCIS) is controversial, and many patients are still overtreated. The local death of myoepithelial cells (MECs) is believed to be a pre-requisite to tumor invasion. We thus hypothesized that loss of CD10 expression, a MEC surface peptidase, would signify basement membrane disruption and confer increased risk of relapse in DCIS. The aim of our study was to retrospectively evaluate the prognostic value of CD10 in DCIS. EXPERIMENTAL DESIGN: CD10 expression was evaluated by quantitative RT-PCR and immunohistochemistry using paraffin-embedded samples of normal breast tissue (n = 11); of morphologically normal ducts associated with DCIS (n = 10); and of DCIS without an invasive component (n = 154). RESULTS: CD10 immunostaining was only observed in MECs in normal tissue and in DCIS. Normal tissue showed high mRNA expression levels of CD10, whereas DCIS showed a variable range. After a median follow-up of 6 years, DCIS with CD10 expression below the levels observed in normal tissue (71%) demonstrated a higher risk of local relapse (HR = 1.88; [95CI:1.30-2.70], p = 0.001) in univariate analysis. No relapse was observed in patients expressing high CD10 mRNA levels (29%) similar to the ones observed in normal tissue. In multivariate analysis including known prognostic factors, low CD10 mRNA expression remained significant (HR = 2.25; [95%CI:1.24-4.09], p = 0.008), as did the recently revised Van Nuys Prognostic Index (VNPI) score (HR = 2.03; [95%CI:1.23-3.35], p = 0.006). CONCLUSION: The decrease of CD10 expression in MECs is associated with a higher risk of relapse in DCIS; this knowledge has the potential to improve DCIS management.

Improvement of the clinical applicability of the Genomic Grade Index through a qRT-PCR test performed on frozen and formalin-fixed paraffin-embedded tissues.

BACKGROUND: Proliferation and tumor differentiation captured by the genomic grade index (GGI) are important prognostic indicators in breast cancer (BC) especially for the estrogen receptor positive (ER+) disease. The aims of this study were to convert this microarray index to a qRT-PCR assay (PCR-GGI), which could be realized on formalin fixed paraffin embedded samples (FFPE), and to assess its prognostic performance and predictive value of clinical benefit in early and advanced ER+ BC patients treated with tamoxifen. METHODS: The accuracy and concordance of the PCR-GGI with the GGI was assessed using BC patients for which frozen and FFPE tissues as well as microarray data were available (n = 19). The evaluation of the prognostic value of the PCR-GGI was assessed on FFPE material using a consecutive series of 212 systemically treated early BC patients. The predictive performance for tamoxifen benefit was assessed using two ER+ BC populations treated either with adjuvant tamoxifen only (n = 77+139) or first-line tamoxifen for advanced disease (n = 270). RESULTS: The PCR-GGI is based on the expression of 8 genes (4 representative of the GGI and 4 reference genes). A significant correlation was observed between the microarray-derived GGI and the qRT-PCR assay using frozen (rho = 0.95, p < 10E-06) and FFPE material (rho = 0.89, p < 10E-06). The prognostic performance of the PCR-GGI was confirmed on FFPE samples (HRunivar. = 1.89; [95CI:1.01-3.54], p = 0.05). The PCR-GGI further identified two subgroups of patients with statistically different time to distant metastasis free survival (DMFS) across the two cohorts of ER+ BC patients treated with adjuvant tamoxifen. Additionally, the PCR-GGI was associated with response to tamoxifen in the advanced setting (HRunivar. = 1.98; [95CI:1.51-2.59], p = 6.9E-07). CONCLUSION: PCR-GGI recapitulates in an accurate and reproducible manner the performances of the GGI using frozen and FFPE samples.