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.

Leveraging big data of immune checkpoint blockade response identifies novel potential targets.

BACKGROUND: The development of immune checkpoint blockade (ICB) has changed the way we treat various cancers. While ICB produces durable survival benefits in a number of malignancies, a large proportion of treated patients do not derive clinical benefit. Recent clinical profiling studies have shed light on molecular features and mechanisms that modulate response to ICB. Nevertheless, none of these identified molecular features were investigated in large enough cohorts to be of clinical value. MATERIALS AND METHODS: Literature review was carried out to identify relevant studies including clinical dataset of patients treated with ICB [anti-programmed cell death protein 1 (PD-1)/programmed death-ligand 1 (PD-L1), anti-cytotoxic T-lymphocyte antigen 4 (CTLA-4) or the combination] and available sequencing data. Tumor mutational burden (TMB) and 37 previously reported gene expression (GE) signatures were computed with respect to the original publication. Biomarker association with ICB response (IR) and survival (progression-free survival/overall survival) was investigated separately within each study and combined together for meta-analysis. RESULTS: We carried out a comparative meta-analysis of genomic and transcriptomic biomarkers of IRs in over 3600 patients across 12 tumor types and implemented an open-source web application (predictIO.ca) for exploration. TMB and 21/37 gene signatures were predictive of IRs across tumor types. We next developed a de novo GE signature (PredictIO) from our pan-cancer analysis and demonstrated its superior predictive value over other biomarkers. To identify novel targets, we computed the T-cell dysfunction score for each gene within PredictIO and their ability to predict dual PD-1/CTLA-4 blockade in mice. Two genes, F2RL1 (encoding protease-activated receptor-2) and RBFOX2 (encoding RNA-binding motif protein 9), were concurrently associated with worse ICB clinical outcomes, T-cell dysfunction in ICB-naive patients and resistance to dual PD-1/CTLA-4 blockade in preclinical models. CONCLUSION: Our study highlights the potential of large-scale meta-analyses in identifying novel biomarkers and potential therapeutic targets for cancer immunotherapy.

MicroRNA profiling and identification of let-7a as a target to prevent chemotherapy-induced primordial follicles apoptosis in mouse ovaries.

Cancer treatments as cyclophosphamide and its active metabolites are highly gonadotoxic leading to follicle apoptosis and depletion. Considering the risk of subsequent infertility, fertility preservation is recommended. Beside the germ cells and gametes cryopreservation options, ovarian pharmacological protection during treatment appears to be very attractive. Meanwhile, the advances in the field of oncology have brought microRNAs into spotlight as a potential feature of cancer treatment. Herein, we investigated miRNAs expressions in response to chemotherapy using postnatal-day-3 (PND3) mouse ovaries. Our results revealed that several miRNAs are differently expressed during chemotherapy exposure. Amongst them, let-7a was the most profoundly downregulated and targets genes involved in crucial cellular processes including apoptosis. Thus we developed a liposome-based system to deliver the let-7a mimic in whole PND3 ovaries in vitro. We showed that let-7a mimic prevented the upregulation of genes involved in cell death and reduced the chemotherapy-induced ovarian apoptosis, suggesting that it can be an interesting target to preserve ovarian function. However, its impact on subsequent follicular development has to be further elucidated in vivo using an appropriate delivery system. In this study, we demonstrated that miRNA replacement approaches can be a useful tool to reduce chemotherapy-induced ovarian damage in the future.

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.

Clinical significance of CD73 in triple-negative breast cancer: multiplex analysis of a phase III clinical trial.

Background: CD73 is an ecto-enzyme that promotes tumor immune escape through the production of immunosuppressive extracellular adenosine in the tumor microenvironment. Several CD73 inhibitors and adenosine receptor antagonists are being evaluated in phase I clinical trials. Patients and methods: Full-face sections from formalin-fixed paraffin-embedded primary breast tumors from 122 samples of triple-negative breast cancer (TNBC) from the BIG 02-98 adjuvant phase III clinical trial were included in our analysis. Using multiplex immunofluorescence and image analysis, we assessed CD73 protein expression on tumor cells, tumor-infiltrating leukocytes and stromal cells. We investigated the associations between CD73 protein expression with disease-free survival (DFS), overall survival (OS) and the extent of tumor immune infiltration. Results: Our results demonstrated that high levels of CD73 expression on epithelial tumor cells were significantly associated with reduced DFS, OS and negatively correlated with tumor immune infiltration (Spearman's R= -0.50, P < 0.0001). Patients with high levels of CD73 and low levels of tumor-infiltrating leukocytes had the worse clinical outcome. Conclusions: Taken together, our study provides further support that CD73 expression is associated with a poor prognosis and reduced anti-tumor immunity in human TNBC and that targeting CD73 could be a promising strategy to reprogram the tumor microenvironment in this BC subtype.

Pharmacological modulation of LMNA SRSF1-dependent splicing abrogates diet-induced obesity in mice.

Bakground/Objectives:Intense drug discovery efforts in the metabolic field highlight the need for novel strategies for the treatment of obesity. Alternative splicing (AS) and/or polyadenylation enable the LMNA gene to express distinct protein isoforms that exert opposing effects on energy metabolism and lifespan. Here we aimed to use the splicing factor SRSF1 that contribute to the production of these different isoforms as a target to uncover new anti-obesity drug. SUBJECTS/METHODS: Small molecules modulating SR protein activity and splicing were tested for their abilities to interact with SRSF1 and to modulate LMNA (AS). Using an LMNA luciferase reporter we selected molecules that were tested in diet-induced obese (DIO) mice. Transcriptomic analyses were performed in the white adipose tissues from untreated and treated DIO mice and mice fed a chow diet. RESULTS: We identified a small molecule that specifically interacted with the RS domain of SRSF1. ABX300 abolished DIO in mice, leading to restoration of adipose tissue homeostasis. In contrast, ABX300 had no effect on mice fed a standard chow diet. A global transcriptomic analysis revealed similar profiles of white adipose tissue from DIO mice treated with ABX300 and from untreated mice fed a chow diet. Mice treated with ABX300 exhibited an increase in O2 consumption and a switch in fuel preference toward lipids. CONCLUSIONS: Targeting SRSF1 with ABX300 compensates for changes in RNA biogenesis induced by fat accumulation and consequently represents a novel unexplored approach for the treatment of obesity.