Unravelling triple-negative breast cancer molecular heterogeneity using an integrative multiomic analysis

Background

Recent efforts of genome-wide gene expression profiling analyses have improved our understanding of the biological complexity and diversity of triple-negative breast cancers (TNBCs) reporting, at least six different molecular subtypes of TNBC namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). However, little is known regarding the potential driving molecular events within each subtype, their difference in survival and response to therapy. Further insight into the underlying genomic alterations is therefore needed.

Patients and methods

This study was carried out using copy-number aberrations, somatic mutations and gene expression data derived from the Molecular Taxonomy of Breast Cancer International Consortium (METABRIC) and The Cancer Genome Atlas. TNBC samples (n = 550) were classified according to Lehmann's molecular subtypes using the TNBCtype online subtyping tool (http://cbc.mc.vanderbilt.edu/tnbc/).

Results

Each subtype showed significant clinic-pathological characteristic differences. Using a multivariate model, IM subtype showed to be associated with a better prognosis (HR = 0.68; CI = 0.46-0.99; P = 0.043) whereas LAR subtype was associated with a worst prognosis (HR = 1.47; CI = 1.0-2.14; P = 0.046). BL1 subtype was found to be most genomically instable subtype with high TP53 mutation (92%) and copy-number deletion in genes involved in DNA repair mechanism (BRCA2, MDM2, PTEN, RB1 and TP53). LAR tumours were associated with higher mutational burden with significantly enriched mutations in PI3KCA (55%), AKT1 (13%) and CDH1 (13%) genes. M and MSL subtypes were associated with higher signature score for angiogenesis. Finally, IM showed high expression levels of immune signatures and check-point inhibitor genes such as PD1, PDL1 and CTLA4.

Conclusion

Our findings highlight for the first time the substantial genomic heterogeneity that characterize TNBC molecular subtypes, allowing for a better understanding of the disease biology as well as the identification of several candidate targets paving novel approaches for the development of anticancer therapeutics for TNBC.

Separation of samples into their constituents using gene expression data

Gene expression measurements are a powerful tool in molecular biology, but when applied to heterogeneous samples containing more than one cellular type the results are difficult to interpret. We present here a new approach to this problem allowing to deduce the gene expression profile of the various cellular types contained in a set of samples directly from the measurements taken on the whole sample.

Absence of a specific radiation signature in post-Chernobyl thyroid cancers

Thyroid cancers have been the main medical consequence of the Chernobyl accident. On the basis of their pathological features and of the fact that a large proportion of them demonstrate RET-PTC translocations, these cancers are considered as similar to classical sporadic papillary carcinomas, although molecular alterations differ between both tumours. We analysed gene expression in post-Chernobyl cancers, sporadic papillary carcinomas and compared to autonomous adenomas used as controls. Unsupervised clustering of these data did not distinguish between the cancers, but separates both cancers from adenomas. No gene signature separating sporadic from post-Chernobyl PTC (chPTC) could be found using supervised and unsupervised classification methods although such a signature is demonstrated for cancers and adenomas. Furthermore, we demonstrate that pooled RNA from sporadic and chPTC are as strongly correlated as two independent sporadic PTC pools, one from Europe, one from the US involving patients not exposed to Chernobyl radiations. This result relies on cDNA and Affymetrix microarrays. Thus, platform-specific artifacts are controlled for. Our findings suggest the absence of a radiation fingerprint in the chPTC and support the concept that post-Chernobyl cancer data, for which the cancer-causing event and its date are known, are a unique source of information to study naturally occurring papillary carcinomas.

Study of thyroid gene expression and regulation by DNA array technology: pitfalls and necessary controls in the use of commercial filters

In order to identify the genes differentially expressed by TSH stimulation in dog and human thyrocytes we have used the gene array technology. Some modifications of the standard procedure were introduced to improve the method. While the macroarray technology has been developed to identify genes differentially expressed between two tissues, we report here that certain widely publicized commercial nylon filters do not allow to achieve this result. Because each step is crucial to the method and because it relies on quantitative measurements, we report different pitfalls of the method when commercial nylon filters with spotted bacterial colonies are used. The list of the most expressed genes in dog and human thyrocytes, which constitutes the minimal transcriptome of these tissues, has nevertheless been drawn up. Control tests that should be applied before the experimental use of the very expensive arrays are proposed.

Abstract P4-06-03: Unravelling triple-negative breast cancer tumor microenvironment heterogeneity using an integrative multiomic analysis

Introduction: Triple negative breast cancer (TNBC) constitute 10-20% of all breast cancers and is associated with a worse prognosis and limited treatment options. Recent trials evaluating immune checkpoint blockade in TNBC demonstrated encouraging results for a subset of patients. TNBC is highly heterogeneous and its tumour microenvironment (TME) has been recognized as a critical determinant of its behavior and clinical outcome. Genome-wide gene expression profiling analyses have already improved our understanding of the complexity of this disease and have defined 6 different molecular subtypes namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR), exhibiting distinct biological and clinical characteristic.

In this study, we aim to dissect the molecular diversity of the TME and more specifically to assess the immune landscape according to TNBC molecular subtypes.

Methods: A cohort of 485 TNBC patient with publicly available data (RNA-Seq and Illumina HT-12 v3) from the METABRIC and the TCGA consortia were used in the gene expression analysis. Gene signatures reflecting different features or cellular components (immune, stromal, angiogenesis, lymphangiogenesis, hypoxia, metabolism) of the TME were used to evaluate multiple biological processes known to contribute to tumorogenesis. A compendium of 17 immune specific gene signatures and T cell localisation classification were used to evaluate the immune composition and spatial pattern of immune infiltrates. All parameters were compared using a logistic regression model to evaluate their relative contribution according to each molecular subtype.

Results: Our analyses demonstrated that each molecular subtype exhibits different TME profiles, as well as specific immune composition and localisation. IM tumors were associated with the highest expression of immune-related gene signatures, enriched with adaptive immune cells and with a fully inflamed spatial pattern. MSL tumors were mostly associated with the expression of Lymphangiogenesis and Stromal TME signatures. They also exhibited some immune activity through the expression of immune gene signatures capturing innate immune and adaptive immunosuppressive cells. This subtype was mainly associated with margin restricted and to some extent with fully inflamed spatial pattern. BL1 tumors were associated with the expression of Metabolism TME signatures, along with fully inflamed and stroma restricted spatial pattern. To a lesser extent, this subtype was also associated with activated DC and CD4 Tem cells. LAR and M tumors exhibited an immune cold phenotype. They were associated with Stromal and Metabolism TME signatures, enriched in margin restricted spatial pattern and negatively associated with every immune cells.

Conclusions: Our results demonstrate for the first time the huge heterogeneity that characterizes the TME of TNBCs. Identification of specific TME profiles could help to design more rationale and appropriate synergistic therapeutic combinations targeting TME elements in this high-risk disease.

Citation Format: Bareche Y, Buisseret L, Gruosso T, Girard E, Venet D, Dupont F, Desmedt C, Park M, Rothé F, Stagg J, Sotiriou C. Unravelling triple-negative breast cancer tumor microenvironment heterogeneity using an integrative multiomic analysis [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-06-03.

Abstract P2-07-02: Uncovering TNBC molecular heterogeneity by applying integrative “omics” analyses with potential clinical implications

Introduction: Triple-negative breast cancer (TNBC), representing about 10-20% of all breast cancers (BC), is a heterogeneous disease characterized by a clinically aggressive course, higher relapse rates and worse overall survival as compared to other BC subtypes. Recent efforts of genome-wide gene expression profiling have improved our understanding of the biological diversity of TNBCs reporting at least 6 different molecular subtypes namely Basal-like 1 (BL1), basal-like 2 (BL2), immunomodulatory (IM), mesenchymal (M), mesenchymal stem-like (MSL) and luminal androgen receptor (LAR). Little is known regarding the potential driving molecular events characterizing each subtype, their difference in survival and response to therapy. Moreover, limited progress has been made so far in the development of effective therapeutic strategies in TNBC partly due to the lack of obvious genetic targets. Further insight into the underlying genomic alterations is therefore needed.

Aims: Here, we aimed to study the genomic aberrations that drive each of the TNBC molecular subtypes as defined by Lehmann et al. by applying an integrative analysis combining somatic mutation, copy number aberrations and gene expression profiles of 272 TNBC derived from METABRIC consortium.

Methods: In silico analyses were performed using microarray, copy number aberrations profiles (CNA) and mutation profiles data retrieved from 272 TNBC patients from the METABRIC consortium. Somatic mutation profiles were derived from targeted sequencing of 173 cancer genes. CNAs at the gene level were computed using GISTIC 2.0.22. The relationship between TNBC molecular subtypes and genomic aberrations were analysed using Fisher test. Survival analyses were performed using Cox proportional hazard models adjust for standard clinical and pathologic variables.

Results: Using a multivariate model, IM and M subtypes were significantly associated with good (HR=0.53; FDR=0.01) and poor (HR=1.8; FDR=0.01) prognosis respectively. BL1 subtype was found to be the most genomically instable subtype with high frequency of TP53 mutations (93%) and copy-number deletions in genes involved in DNA repair mechanisms (BRCA2, MDM2, RB1 and TP53) and MYC overexpression. BL2 subtype was enriched with TP53 (95%) and PIK3CA mutations (52%), whereas LAR subtype was characterized by high frequency of PI3KCA mutations (44%). Of interest, for these two subtypes, mutations in genes in the PI3K signalling pathway were mutually exclusive. IM subtype was enriched in NCOR2 mutations (13%), a co-repressor of the Notch pathway, associated with lower gene expression (p=0.035). M and MSL subtypes were significantly associated with higher signature scores for angiogenesis. In addition, M subtype was associated with higher frequency of NOTCH1 mutations (M p=2.4E-2).

Conclusions: This integrative analysis combining somatic mutation, copy number and gene expression profiles shed new light on TNBC molecular heterogeneity, highlighting TNBC subtype-specific genomic aberrations which could potentially open new avenues for the development of effective targeted therapies in each TNBC molecular subtype such as DNA repair, Notch and angiogenesis.

Citation Format: Bareche Y, Venet D, Rothe F, Sotiriou C. Uncovering TNBC molecular heterogeneity by applying integrative “omics” analyses with potential clinical implications [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-07-02.

Abstract P1-01-10: Exome sequencing of circulating tumor cells in metastatic breast cancer

Aim: We interrogated whether Circulating Tumor Cells (CTCs) can complement metastatic biopsies for genomic analyses.

Patients and Methods: We compared single nucleotide variants (SNVs) and copy number aberrations (CNAs) identified using whole exome sequencing (WES) of DNA from frozen tumor tissue (primary/metastasis), amplified DNA from CTCs and normal DNA from 3 metastatic breast cancer (BC) patients (pts). All samples of the same patient were collected at the same timepoint. CTC isolation was performed using CellSearch and DEPArray systems followed by whole genome amplification (Ampli1 kit). WES was performed using the Illumina HiSeq2000 with 200X targeted coverage. Reads were aligned using bwa. SNVs had to be called by both Haplotype Caller (vs. reference genome) and Strelka (vs. paired normal). CNAs were determined by counting reads in 1MB windows and by comparing tumor/CTC samples with normal DNA. Pairwise concordance of CNAs profiles of different samples from the same patient was assessed using Spearman correlation (ρ). Significance of ρ differences between pts was obtained by Kruskal-Wallis test. Orthogonal validation for selected SNVs was performed.

Results: We studied 3 patients from the 3 major BC subtypes, patient (pt)1 with ER-/HER2+ BC (samples collected at diagnosis, initially metastatic disease), pt2 with triple-negative BC (samples collected 2 years from diagnosis) and pt3 with ER+/HER2- BC (samples collected 8 years from diagnosis).

We first compared tumor tissue and CTCs for SNVs. For pt1, of the 77 SNVs identified in the tumor, 51 were found on at least one of 12 CTCs samples. For pt2, of the 62 SNVs identified in the tumor, 19 were found on at least 1 of 11 CTCs samples. For pt3, of the 225 SNVs identified in the tumor, 48 were found on at least 1 of 3 CTCs samples. Interestingly, by increasing the number of CTCs analyzed, we increased the % of identified SNVs from synchronous tumor tissue. SNVs with high variant allele fraction (VAF) in tumor tissue were detected significantly more often in CTCs: 22% of the SNVs with VAFs <20% were found at least once, compared to 53% and 74% of SNVs with VAFs >20% and >40%, respectively (p=10-12, Fisher exact test).

Then, we compared tumor tissue and CTCs for CNAs. As time from diagnosis of metastatic disease to samples collection increased, we observed significantly higher heterogeneity within CTCs from the same patient (median ρ between CTCs was 86% for pt1, 84% for pt2 and 28% for pt3, p<0.01) and between CTCs and tumor tissue from the same patient (median ρ was 78% for pt1, 67% for pt2 and 21% for pt3, p<10-4). Interestingly, in pt3 one CTC was more similar to the metastasis than the other 2 (ρ of 53%, 21% and 21%). When a phylogenetic tree was constructed for pt3 by combining SNVs and CNAs data, three clones were identified: one clone with an AKT1 (E17K) and a TP53 (R248W) mutation and a 8p deletion, a second clone with the above profile plus an 8q amplification and a third clone with an AKT1 and an ESR1 (Y537N) mutation and 1p deletion. The metastasis was similar with the first clone.

Conclusions: These data suggest that tumor tissue and single CTC exome sequencing analyses provide complementary information to map tumor heterogeneity. Further validation for potential clinical applications is needed.

Citation Format: Ignatiadis M, Rothé F, Peeters D, Rouas G, Smeets D, Haan J, Lambrechts D, Campbell P, Piccart M, Voet T, Dirix L, Venet D, Sotiriou C. Exome sequencing of circulating tumor cells in metastatic breast cancer [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-01-10.

Abstract P2-05-04: Deregulation of A-to-I RNA editing is associated with poor prognosis in HER2+ breast cancers in the neoALTTO trial

Background

A-to-I RNA editing, a post-transcriptional modification of the RNA catalyzed by the ADAR family of enzymes, is emerging as a widespread phenomenon in breast cancer (BC). A-to-I RNA editing is more frequent in the highly repetitive Alu regions but can affect both coding and non-coding regions. It has been shown to greatly impact cell functionality. In a recent report, we have shown that A-to-I RNA editing is regulated both by ADAR copy number and type I interferon response (Fumagalli et al. Cell Rep 2015). The main aim of the current study was to investigate the extent and profile of A-to-I RNA editing in HER2+ BC patients (pts) treated in the NeoALTTO trial, and to explore its impact on pathologic complete response (pCR) and survival.

Methods

Aligned RNAseq reads of sufficient quality and quantity were obtained for 252 of the 455 pts enrolled in the study, as described previously (Fumagalli et al. JAMA Oncol 2016). Editing sites from the rediPortal database were assessed. The editing level at a given site was computed by counting the number of Gs and As. Sites with coverage more than 10 were considered for further analyses. Editing in normal tissues was obtained from the GTEx project of the rediPortal database. Tumor infiltrating lymphocytes (TILs) and copy number aberrations were previously reported. Correlations between different parameters were assessed using Spearman correlations (ρ). The Mann-Whitney test was used to relate binary and numerical features. Event-free survival (EFS) analysis was performed using the Cox proportional hazard model.

Results

There was a median of 71470 edited sites per sample. As expected, mean editing per sample correlated with ADAR expression (ρ=59%, p<10-16) and ADAR copy number (ρ=54%, p<10-16). It was also correlated with the IFN-gamma driven signature (ρ=22%, p=0.0005), as well as with ESR1 gene expression (ρ=24%, p=0.0002). Neither ADAR expression nor mean editing was correlated with TILs (ρ=-0.5% and ρ=3%). No relationship between mean editing and pCR or EFS was found. The correlations between editing in NeoALTTO tumor samples and GTEx normal tissues were computed, and the median editing per sample was taken. These median correlations, ranging from 32% to 56%, were not associated with ADAR expression (ρ=-25%, p=6x10-5) nor mean editing (ρ=8%, p=0.19). Of interest, patients whose tumors showed low correlation with editing in normal tissues were associated with poor EFS (p=0.028, HR=0.56 to 0.96) suggesting that deregulation of RNA editing may impact disease progression and outcome. Similar results were obtained when the correlations were assessed between tumor samples instead of between tumor and normal samples (ρ between the two median editing: 76%; p-value survival: 0.013). The median correlations were not predictive for pCR (p=0.44). There was no interaction between editing and treatment arm.

Conclusions

Our study shows for the first time that deregulated RNA editing, as compared to editing in normal tissues, is a widespread phenomenon in HER2+ BC patients treated in the NeoALTTO trial and is associated with poor outcome. These results may provide new perspectives for the treatment of HER2+ disease by developing therapies targeting RNA editing.

Citation Format: Venet D, Rothé F, Dupont F, Maetens M, Fumagalli D, Salgado R, Bradbury I, Pusztai L, Harbeck N, Izquierdo M, de la Pena L, Ignatiadis M, de Azambuja E, Huober J, Nuciforo P, Baselga J, Piccart M, Loi S, Sotiriou C. Deregulation of A-to-I RNA editing is associated with poor prognosis in HER2+ breast cancers in the neoALTTO trial [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-05-04.

Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in patients with HER2-positive early breast cancer (EBC)

BACKGROUND

In human epidermal growth factor receptor 2 (HER2)-positive early breast cancer (EBC), we investigated tumor and immune changes during neoadjuvant treatment and their impact on residual disease (RD) biology and prognostic implications across four neoadjuvant studies of trastuzumab with or without lapatinib, and with or without chemotherapy: CALGB 40601, PAMELA, NeoALTTO, and NSABP B-41.

PATIENTS AND METHODS

We compared tumor and immune gene expression changes during neoadjuvant treatment and their association with event-free survival (EFS) by uni- and multivariable Cox regression models in different cohorts and timepoints: 452 RD samples at baseline including 169 with a paired RD, and biomarker changes during neoadjuvant therapy, evaluating model performance via the c-index.

RESULTS

Analysis of 169 paired tumor samples revealed a shift in intrinsic subtype proportions from HER2-enriched at baseline (50.3%) to normal-like (49.1%) followed by luminal A (18.9%) in RD. This luminal phenotypic change was supported by decreased correlation to the HER2-enriched centroid, ERBB2, and HER2 amplicon genes and increased correlation to the luminal A centroid (Wilcoxon test P < 0.001). Additionally, RD showed relative immune activation marked by significant increases in B-cell, CD8 T-cell, and natural killer cell signatures (Wilcoxon test P < 0.05). In multivariable Cox models, intrinsic subtypes at baseline provided more prognostic information, while immune gene expression signatures provided more prognostic information in RD. Notably, the best multivariable EFS model (c-index = 0.77) integrated the immunoglobulin G signature from RD samples (adjusted hazard ratio 0.45, 95% confidence interval 0.30-0.67, adjusted P = 0.002).

CONCLUSIONS

In patients with HER2-positive EBC and RD, tumor biomarkers provide more prognostic information at baseline. In contrast, immune biomarkers perform better for EFS prognosis in RD.

Abstract PD5-06: The immunomodulatory potential of denosumab in breast cancer: results from D-BEYOND, a window of opportunity trial evaluating a RANK-ligand (RANKL) inhibitor and its biological effects in young pre-menopausal women diagnosed with early breast cancer

Background

Breast cancer (BC) in young women has unique biology and poor prognosis. Previous reports suggest that they often express RANKL, which was also shown to play a role in mammary tumorigenesis and various immune processes. Here, we present the primary results of D-BEYOND, a window study investigating the biological activity of the RANKL inhibitor; denosumab in pre-menopausal BC patients.

Methods

D-BEYOND is a prospective, phase Iia, single-arm, multicenter study assessing the effect of denosumab on BC biology in premenopausal women with early BC (NCT01864798). Patients received two subcutaneous injections of denosumab (120mg), one week apart, followed by breast surgery. The primary endpoint was geometric mean change in tumor Ki67 assessed by immunohistochemistry (IHC). Blood, tumor and normal adjacent breast tissue were collected pre- and post-treatment. Serum levels of RANKL, OPG and CTX were assessed by ELISA. RNA was extracted from fresh-frozen tissue and RNAseq was performed. DESeq2 was used for differential expression analysis, GAGE was used for pathway analysis and CIBERSORT was used to infer immune cell subsets between pre- and post-treatment. Ki67, CD4/Foxp3 and CD4/CD8 IHC were performed on FFPE tissue to further assess the immune microenvironment. The percentage of TILs was independently evaluated by two pathologists on H&E slides. Pre- and post-treatment values were compared using a paired t-test.

Results

A total of 27 patients were enrolled in the study between October 2013 and July 2016. The median age was 45 years (range 35-51 years). Tumors of 21 patients were hormone receptor positive (77.8%), 4 were HER2 positive (14.8%) and 2 were triple negative (7.4%). No serious adverse events were reported, the most frequent non-serious adverse event being arthralgia (14.8%). After treatment, serum levels of CTX and RANKL decreased in all patients (P &lt; 0.001) whereas OPG increased in 76.9% of patients (P = 0.009, 95% CI 0.56-0.91). There was no significant reduction of Ki67 values from baseline (geometric mean [GM] change after treatment; 0.98, 95% CI 0.76-1.26; P = 0.90). Twenty-four pre- and post-treatment tumor pairs were available for RNAseq, IHC and TILs evaluation. There was a significant increase in the percentage of stromal TILs after treatment (GM change of 1.75, 95% CI 1.28–2.39; P = 0.001). 1084 differentially expressed genes were identified and pathway analysis revealed enrichment of several immune processes. CIBERSORT revealed an enrichment of CD8+ T cells (GM change 1.72, 95% CI 1.19–2.48; P = 0.006) and a decrease of Treg cells (0.71, 95% CI 0.52–0.98, P = 0.040). These results were confirmed by IHC of CD8+ and CD4+/Foxp3+ cells (GM change 1.59, 95% CI 1.14–2.21; P = 0.008 and 0.63, 95% CI 0.49–0.83, P = 0.001, respectively).

Conclusion

Short course of denosumab did not reduce tumor proliferation rate. However, it induced a significant increase in TILs and CD8 cytotoxic T cells, while Treg infiltration decreased. These findings suggest an immunomodulatory role for denosumab in young breast cancer and that its use in combination could boost immunotherapy efficacy.

Citation Format: Nguyen B, Marion M, Salgado R, Venet D, Vuylsteke P, Polastro L, Wieldiers H, Simon P, Lindeman G, Larsimont D, Van den Eynden G, Velghe C, Rothe F, Garaud S, Michiels S, Willard-Gallo K, Azim Jr HA, Loi S, Piccart M, Sotiriou C. The immunomodulatory potential of denosumab in breast cancer: results from D-BEYOND, a window of opportunity trial evaluating a RANK-ligand (RANKL) inhibitor and its biological effects in young pre-menopausal women diagnosed with early breast cancer [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD5-06.

The long and winding road to biomarkers for immunotherapy: a retrospective analysis of samples from patients with triple-negative breast cancer treated with pembrolizumab

BACKGROUND

Immune checkpoint blockade (ICB) in combination with chemotherapy improves outcome of patients with triple-negative breast cancer (TNBC) in metastatic and early settings. The identification of predictive biomarkers able to guide treatment decisions is challenging and currently limited to programmed death-ligand 1 (PD-L1) expression and high tumor mutational burden (TMB) in the advanced setting, with several limitations.

MATERIALS AND METHODS

We carried out a retrospective analysis of clinical-pathological and molecular characteristics of tumor samples from 11 patients with advanced TNBC treated with single-agent pembrolizumab participating in two early-phase clinical trials: KEYNOTE-012 and KEYNOTE-086. Clinical, imaging, pathological [i.e. tumor-infiltrating lymphocytes (TILs), PD-L1 status], RNA sequencing, and whole-exome sequencing data were analyzed. We compared our results with publicly available transcriptomic data from TNBC cohorts from TCGA and METABRIC.

RESULTS

Response to pembrolizumab was heterogeneous: two patients experienced exceptional long-lasting responses, six rapid progressions, and three relatively slower disease progression. Neither PD-L1 nor stromal TILs were significantly associated with response to treatment. Increased TMB values were observed in tumor samples from exceptional responders compared to the rest of the cohort (P = 3.4 × 10-4). Tumors from exceptional responders were enriched in adaptive and innate immune cell signatures. Expression of regulatory T-cell markers (FOXP3, CCR4, CCR8, TIGIT) was mainly observed in tumors from responders except for glycoprotein-A repetitions predominant (GARP), which was overexpressed in tumors from rapid progressors. GARP RNA expression in primary breast tumors from the public dataset was significantly associated with a worse prognosis.

CONCLUSIONS

The wide spectrum of clinical responses to ICB supports that TNBC is a heterogeneous disease. Tumors with high TMB respond better to ICB. However, the optimal cut-off of 10 mutations (mut)/megabase (Mb) may not reflect the complexity of all tumor subtypes, despite its approval as a tumor-agnostic biomarker. Further studies are required to better elucidate the relevance of the tumor microenvironment and its components as potential predictive biomarkers in the context of ICB.

Abstract P2-05-01: Whole genome sequencing reveals enrichment of mutations in mucin gene family in breast cancer diagnosed during pregnancy

Background

Pregnancy is known to modulate breast cancer (BC) risk. Different reproductive behaviors have been shown to impact not only the risk of developing BC but also the phenotypes of these tumors. Breast cancer diagnosed during pregnancy (BCP) is a rare disease but could serve as a good model to understand how pregnancy modulates BC biology. In this project, we aim to interrogate the effect of pregnancy on the biology of BC by performing whole genome sequencing (WGS) using a unique series of BC patients diagnosed during pregnancy (BCP).

Method

Whole genome sequencing was performed for 35 BCP and 20 non-pregnant controls matched for age and stage with available clinic-pathological data. DNA extracted from primary tumor and matched adjacent normal FFPE tissues was assessed using WGS on Illumina HiSeqXTen platform targeting 60x and 30x coverage for tumor and normal DNA respectively. Briefly, 2x150bp paired end sequence data were generated, cleaned, trimmed and aligned to the reference genome (hg19) using bwa-mem. Somatic mutations were detected using Strelka and annotated using SnpEff. Mutational signatures were extracted using deconstructSigs. Differences on mutational profiles between BCP and case controls were assessed using Wilcoxon test for continuous variables and Fisher exact test for categorical variables.

Result

No difference in clinic-pathological features was observed between BCP and control patients. A median of 10084 and 13829 SNVs and of 26 and 21 indels were identified in the BCP and controls respectively, no significant difference between the two groups being observed (p = 0.703 and p = 0.851). Of interest, a significantly higher number of mutations was found in the BCP as compared to the control group when considering only mutations associated with a deleterious effect (median: 20 vs. 12, p = 0.027). As expected, TP53 and PIK3CA were the most frequently mutated genes both in BCP and control cases without any significant difference between the groups (34.3% vs. 22.2%, p = 0.53 and 20.0% vs. 16.7%, p = 1, respectively). Interestingly, there was a significant enrichment of non-silent mutations in the mucin genes family (MUC2, MUC4, MUC12, MUC16, MUC17, MUC20) in the BCP group: 45.7% of BCP vs. 11.1% of control cases had at least one such mutation (p = 0.015). A similar significant result (45.7% vs. 23.1%, p = 0.034) was found when comparing BCP with BC control cases from the TCGA dataset (selected to have similar age, ER and PR distribution, N = 56). When comparing the distribution of the twelve BC mutational signatures, a borderline significant enrichment with a signature depicting mismatch-repair deficiency (signature 20) was observed in the BCP patients (p = 0.059).

Conclusion

This is the first study reporting the mutational landscape of breast cancer diagnosed during pregnancy using WGS. We found that BCP are associated with a higher number of putative driver mutations including mutations in mucin genes, shown to be implicated in tumorigenesis. Furthermore, BCP were enriched with a mismatch-repair deficiency signature. These results could open new avenues for the development of targeted therapeutic approaches for patients diagnosed with breast cancer during pregnancy.

Citation Format: Nguyen B, Venet D, Desmedt C, Pruneri G, Peccatori F, Mardis ER, Azim HA, Rothé F, Sotiriou C. Whole genome sequencing reveals enrichment of mutations in mucin gene family in breast cancer diagnosed during pregnancy [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P2-05-01.