Christine Desmedt

Signatures of mutational processes in human cancer

All cancers are caused by somatic mutations; however, understanding of the biological processes generating these mutations is limited. The catalogue of somatic mutations from a cancer genome bears the signatures of the mutational processes that have been operative. Here we analysed 4,938,362 mutations from 7,042 cancers and extracted more than 20 distinct mutational signatures. Some are present in many cancer types, notably a signature attributed to the APOBEC family of cytidine deaminases, whereas others are confined to a single cancer class. Certain signatures are associated with age of the patient at cancer diagnosis, known mutagenic exposures or defects in DNA maintenance, but many are of cryptic origin. In addition to these genome-wide mutational signatures, hypermutation localized to small genomic regions, ‘kataegis’, is found in many cancer types. The results reveal the diversity of mutational processes underlying the development of cancer, with potential implications for understanding of cancer aetiology, prevention and therapy.

The landscape of cancer genes and mutational processes in breast cancer

All cancers carry somatic mutations in their genomes. A subset, known as driver mutations, confer clonal selective advantage on cancer cells and are causally implicated in oncogenesis, and the remainder are passenger mutations. The driver mutations and mutational processes operative in breast cancer have not yet been comprehensively explored. Here we examine the genomes of 100 tumours for somatic copy number changes and mutations in the coding exons of protein-coding genes. The number of somatic mutations varied markedly between individual tumours. We found strong correlations between mutation number, age at which cancer was diagnosed and cancer histological grade, and observed multiple mutational signatures, including one present in about ten per cent of tumours characterized by numerous mutations of cytosine at TpC dinucleotides. Driver mutations were identified in several new cancer genes including AKT2, ARID1B, CASP8, CDKN1B, MAP3K1, MAP3K13, NCOR1, SMARCD1 and TBX3. Among the 100 tumours, we found driver mutations in at least 40 cancer genes and 73 different combinations of mutated cancer genes. The results highlight the substantial genetic diversity underlying this common disease.

Strong Time Dependence of the 76-Gene Prognostic Signature for Node-Negative Breast Cancer Patients in the TRANSBIG Multicenter Independent Validation Series

Purpose: Recently, a 76-gene prognostic signature able to predict distant metastases in lymph node–negative (N−) breast cancer patients was reported. The aims of this study conducted by TRANSBIG were to independently validate these results and to compare the outcome with clinical risk assessment. Experimental Design: Gene expression profiling of frozen samples from 198 N− systemically untreated patients was done at the Bordet Institute, blinded to clinical data and independent of Veridex. Genomic risk was defined by Veridex, blinded to clinical data. Survival analyses, done by an independent statistician, were done with the genomic risk and adjusted for the clinical risk, defined by Adjuvant! Online. Results: The actual 5- and 10-year time to distant metastasis were 98% (88-100%) and 94% (83-98%), respectively, for the good profile group and 76% (68-82%) and 73% (65-79%), respectively, for the poor profile group. The actual 5- and 10-year overall survival were 98% (88-100%) and 87% (73-94%), respectively, for the good profile group and 84% (77-89%) and 72% (63-78%), respectively, for the poor profile group. We observed a strong time dependence of this signature, leading to an adjusted hazard ratio of 13.58 (1.85-99.63) and 8.20 (1.10-60.90) at 5 years and 5.11 (1.57-16.67) and 2.55 (1.07-6.10) at 10 years for time to distant metastasis and overall survival, respectively. Conclusion: This independent validation confirmed the performance of the 76-gene signature and adds to the growing evidence that gene expression signatures are of clinical relevance, especially for identifying patients at high risk of early distant metastases.

Tumor infiltrating lymphocytes are prognostic in triple negative breast cancer and predictive for trastuzumab benefit in early breast cancer: results from the FinHER trial

BACKGROUND We have previously shown the prognostic importance of tumor-infiltrating lymphocytes (TILs) in newly diagnosed triple-negative breast cancer (TNBC) using tumor samples from a large clinical trial cohort. In this study, we aimed to validate these findings and also investigate associations with trastuzumab benefit in HER2-overexpressing disease (HER2+). PATIENTS AND METHODS A prospective-retrospective study was conducted using samples from the FinHER adjuvant, phase III trial that enrolled 1010 early-stage BC patients, 778 of whom were HER2-nonamplified. Those with HER2+ disease (n = 232) were randomized to 9 weeks of trastuzumab or no trastuzumab in addition to chemotherapy. Two pathologists independently quantified stromal TILs in 935 (92.6%) available slides. The primary end point of distant disease-free survival (DDFS) and interactions with trastuzumab were studied in Cox regression models. RESULTS Confirming our previous findings, in TNBC (n = 134) each 10% increase in TILs was significantly associated with decreased distant recurrence in TNBC; for DDFS the hazard ratio adjusted for clinicopathological factors: 0.77; 95% confidence interval (CI) 0.61-0.98, P = 0.02. In HER2+ BC (n = 209), each 10% increase in lymphocytic infiltration was significantly associated with decreased distant recurrence in patients randomized to the trastuzumab arm (DDFS P interaction = 0.025). CONCLUSIONS Higher levels of TILs present at diagnosis were significantly associated with decreased distant recurrence rates in primary TNBC. These results confirm our previous data and further support that TILs should be considered as a robust prognostic factor in this BC subtype. We also report for the first time an association between higher levels of TILs and increased trastuzumab benefit in HER2+ disease. Further research into why some TN and HER2+ BCs can or cannot generate a host antitumor immune response and how trastuzumab can favorably alter the immune microenvironment is warranted.

CD4+ follicular helper T cell infiltration predicts breast cancer survival

CD4⁺ T cells are critical regulators of immune responses, but their functional role in human breast cancer is relatively unknown. The goal of this study was to produce an image of CD4⁺ T cells infiltrating breast tumors using limited ex vivo manipulation to better understand the in vivo differences associated with patient prognosis. We performed comprehensive molecular profiling of infiltrating CD4⁺ T cells isolated from untreated invasive primary tumors and found that the infiltrating T cell subpopulations included follicular helper T (Tfh) cells, which have not previously been found in solid tumors, as well as Th1, Th2, and Th17 effector memory cells and Tregs. T cell signaling pathway alterations included a mixture of activation and suppression characterized by restricted cytokine/chemokine production, which inversely paralleled lymphoid infiltration levels and could be reproduced in activated donor CD4⁺ T cells treated with primary tumor supernatant. A comparison of extensively versus minimally infiltrated tumors showed that CXCL13-producing CD4⁺ Tfh cells distinguish extensive immune infiltrates, principally located in tertiary lymphoid structure germinal centers. An 8-gene Tfh signature, signifying organized antitumor immunity, robustly predicted survival or preoperative response to chemotherapy. Our identification of CD4⁺ Tfh cells in breast cancer suggests that they are an important immune element whose presence in the tumor is a prognostic factor.

Amplification of LAPTM4B and YWHAZ contributes to chemotherapy resistance and recurrence of breast cancer

Adjuvant chemotherapy for breast cancer after surgery has effectively lowered metastatic recurrence rates. However, a considerable proportion of women suffer recurrent cancer at distant metastatic sites despite adjuvant treatment. Identification of the genes crucial for tumor response to specific chemotherapy drugs is a challenge but is necessary to improve outcomes. By using integrated genomics, we identified a small number of overexpressed and amplified genes from chromosome 8q22 that were associated with early disease recurrence despite anthracycline-based adjuvant chemotherapy. We confirmed the association in an analysis of multiple independent cohorts. SiRNA-mediated knockdown of either of two of these genes, the antiapoptotic gene YWHAZ and a lysosomal gene LAPTM4B, sensitized tumor cells to anthracyclines, and overexpression of either of the genes induced anthracycline resistance. Overexpression of LAPTM4B resulted in sequestration of the anthracycline doxorubicin, delaying its appearance in the nucleus. Overexpression of these two genes was associated with poor tumor response to anthracycline treatment in a neoadjuvant chemotherapy trial in women with primary breast cancer. Our results suggest that 8q22 amplification and overexpression of LAPTM4B and YWHAZ contribute to de novo chemoresistance to anthracyclines and are permissive for metastatic recurrence. Overexpression of these two genes may predict anthracycline resistance and influence selection of chemotherapy.

Genomic Index of Sensitivity to Endocrine Therapy for Breast Cancer

PURPOSE We hypothesize that measurement of gene expression related to estrogen receptor α (ER; gene name ESR1) within a breast cancer sample represents intrinsic tumoral sensitivity to adjuvant endocrine therapy. METHODS A genomic index for sensitivity to endocrine therapy (SET) index was defined from genes coexpressed with ESR1 in 437 microarray profiles from newly diagnosed breast cancer, unrelated to treatment or outcome. The association of SET index and ESR1 levels with distant relapse risk was evaluated from microarrays of ER-positive breast cancer in two cohorts who received 5 years of tamoxifen alone as adjuvant endocrine therapy (n = 225 and 298, respectively), a cohort who received neoadjuvant chemotherapy followed by tamoxifen and/or aromatase inhibition (n = 122), and two cohorts who received no adjuvant systemic therapy (n = 208 and 133, respectively). RESULTS The SET index (165 genes) was significantly associated with distant relapse or death risk in both tamoxifen-treated cohorts (hazard ratio [HR] = 0.70, 95% CI, 0.56 to 0.88, P = .002; and HR = 0.76, 95% CI, 0.63 to 0.93, P = .007) and in the chemo-endocrine-treated cohort (HR = 0.19; 95% CI, 0.05 to 0.69, P = .011) independently from pathologic response to chemotherapy, but was not prognostic in two untreated cohorts. No distant relapse or death was observed after tamoxifen alone if node-negative and high SET or after chemo-endocrine therapy if intermediate or high SET. CONCLUSION The SET index of ER-related transcription predicted survival benefit from adjuvant endocrine therapy, not inherent prognosis. Prior chemotherapy seemed to enhance the efficacy of adjuvant endocrine therapy related to SET index.

Genomic Grade Index Is Associated With Response to Chemotherapy in Patients With Breast Cancer

PURPOSE The genomic grade index (GGI) is a 97-gene measure of histological tumor grade. High GGI is associated with decreased relapse-free survival in patients receiving either endocrine or no systemic adjuvant therapy. Herein we examined whether GGI predicts pathologic response to neoadjuvant chemotherapy in patients with HER-2-normal breast cancer. METHODS Gene expression data (gene chips) was generated from fine-needle aspiration biopsies (n = 229) prospectively collected before neoadjuvant paclitaxel, fluorouracil, doxorubicin, and cyclophosphamide chemotherapy. Pathologic response was quantified using the residual cancer burden (RCB) method. The association between the GGI and pathologic response was assessed in univariate and multivariate analyses. The performance of a response predictor combining clinical variables and GGI was evaluated under cross-validation. Results Eighty-five percent of grade 1 tumors had low GGI, 89% of grade 3 tumors had high GGI, and 63% of grade 2 tumors had low GGI. Among both estrogen receptor (ER)-positive and -negative cancers, high GGI score was associated with pathologic complete response (RCB-0) or minimal residual disease (RCB-1). A multivariate model combining GGI and clinical parameters had an overall accuracy of 71%, compared with 58% for the GGI alone, for prediction of pathologic response. However, high GGI score was also associated with significantly worse distant relapse-free survival in patients with ER-positive cancer (P = .005), and was not associated with survival in patients with ER-negative cancer. CONCLUSION High GGI is associated with increased sensitivity to neoadjuvant paclitaxel plus fluorouracil, adriamycin, and cyclophosphamide chemotherapy in both ER-negative and ER-positive patients, but it remains a predictor of worse survival in ER-positive patients.

Multifactorial Approach to Predicting Resistance to Anthracyclines

PURPOSE Validated biomarkers predictive of response/resistance to anthracyclines in breast cancer are currently lacking. The neoadjuvant Trial of Principle (TOP) study, in which patients with estrogen receptor (ER) -negative tumors were treated with anthracycline (epirubicin) monotherapy, was specifically designed to evaluate the predictive value of topoisomerase II-α (TOP2A) and develop a gene expression signature to identify those patients who do not benefit from anthracyclines. PATIENTS AND METHODS The TOP trial included 149 patients, 139 of whom were evaluable for response prediction analyses. The primary end point was pathologic complete response (pCR). TOP2A and gene expression profiles were evaluated using pre-epirubicin biopsies. Gene expression data from ER-negative samples of the EORTC (European Organisation for Research and Treatment of Cancer) 10994/BIG (Breast International Group) 00-01 and MDACC (MD Anderson Cancer Center) 2003-0321 neoadjuvant trials were used for validation purposes. RESULTS A pCR was obtained in 14% of the evaluable patients in the TOP trial. TOP2A amplification, but not protein overexpression, was significantly associated with pCR (P ≤ .001 v P ≤ .33). We developed an anthracycline-based score (A-Score) combining three signatures: a TOP2A gene signature and two previously published signatures related to tumor invasion and immune response. The A-Score was characterized by a high negative predictive value ([NPV]; NPV, 0.98; 95% CI, 0.90 to 1.00) overall and in the human epidermal growth factor receptor 2 (HER2) -negative and HER2-positive subpopulations. Its performance was independently confirmed in the anthracycline-based arms of the two validation trials (BIG 00-01: NPV, 0.83; 95% CI, 0.64 to 0.94 and MDACC 2003-0321: NPV, 1.00; 95% CI, 0.80 to 1.00). CONCLUSION Given its high NPV, the A-Score could become, if further validated, a useful clinical tool to identify those patients who do not benefit from anthracyclines and could therefore be spared the non-negligible adverse effects.

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.