DECOMICS, a shiny application for unsupervised cell type deconvolution and biological interpretation of bulk omic data.

Summary: Unsupervised deconvolution algorithms are often used to estimate cell composition from bulk tissue samples. However, applying cell-type deconvolution and interpreting the results remain a challenge, even more without prior training in bioinformatics. Here, we propose a tool for estimating and identifying cell type composition from bulk transcriptomes or methylomes. DECOMICS is a shiny-web application dedicated to unsupervised deconvolution approaches of bulk omic data. It provides (i) a variety of existing algorithms to perform deconvolution on the gene expression or methylation-level matrix, (ii) an enrichment analysis module to aid biological interpretation of the deconvolved components, based on enrichment analysis, and (iii) some visualization tools. Input data can be downloaded in csv format and preprocessed in the web application (normalization, transformation, and feature selection). The results of the deconvolution, enrichment, and visualization processes can be downloaded. Availability and implementation: DECOMICS is an R-shiny web application that can be launched (i) directly from a local R session using the R package available here: https://gitlab.in2p3.fr/Magali.Richard/decomics (either by installing it locally or via a virtual machine and a Docker image that we provide); or (ii) in the Biosphere-IFB Clouds Federation for Life Science, a multi-cloud environment scalable for high-performance computing: https://biosphere.france-bioinformatique.fr/catalogue/appliance/193/.

Cirscan: a shiny application to identify differentially active sponge mechanisms and visualize circRNA-miRNA-mRNA networks.

BACKGROUND: Non-coding RNAs represent a large part of the human transcriptome and have been shown to play an important role in disease such as cancer. However, their biological functions are still incompletely understood. Among non-coding RNAs, circular RNAs (circRNAs) have recently been identified for their microRNA (miRNA) sponge function which allows them to modulate the expression of miRNA target genes by taking on the role of competitive endogenous RNAs (ce-circRNAs). Today, most computational tools are not adapted to the search for ce-circRNAs or have not been developed for the search for ce-circRNAs from user's transcriptomic data. RESULTS: In this study, we present Cirscan (CIRcular RNA Sponge CANdidates), an interactive Shiny application that automatically infers circRNA-miRNA-mRNA networks from human multi-level transcript expression data from two biological conditions (e.g. tumor versus normal conditions in the case of cancer study) in order to identify on a large scale, potential sponge mechanisms active in a specific condition. Cirscan ranks each circRNA-miRNA-mRNA subnetwork according to a sponge score that integrates multiple criteria based on interaction reliability and expression level. Finally, the top ranked sponge mechanisms can be visualized as networks and an enrichment analysis is performed to help its biological interpretation. We showed on two real case studies that Cirscan is capable of retrieving sponge mechanisms previously described, as well as identifying potential novel circRNA sponge candidates. CONCLUSIONS: Cirscan can be considered as a companion tool for biologists, facilitating their ability to prioritize sponge mechanisms for experimental validations and identifying potential therapeutic targets. Cirscan is implemented in R, released under the license GPL-3 and accessible on GitLab ( https://gitlab.com/geobioinfo/cirscan_Rshiny ). The scripts used in this paper are also provided on Gitlab ( https://gitlab.com/geobioinfo/cirscan_paper ).

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma.

Two tumor (Classical/Basal) and stroma (Inactive/active) subtypes of Pancreatic adenocarcinoma (PDAC) with prognostic and theragnostic implications have been described. These molecular subtypes were defined by RNAseq, a costly technique sensitive to sample quality and cellularity, not used in routine practice. To allow rapid PDAC molecular subtyping and study PDAC heterogeneity, we develop PACpAInt, a multi-step deep learning model. PACpAInt is trained on a multicentric cohort (n = 202) and validated on 4 independent cohorts including biopsies (surgical cohorts n = 148; 97; 126 / biopsy cohort n = 25), all with transcriptomic data (n = 598) to predict tumor tissue, tumor cells from stroma, and their transcriptomic molecular subtypes, either at the whole slide or tile level (112 µm squares). PACpAInt correctly predicts tumor subtypes at the whole slide level on surgical and biopsies specimens and independently predicts survival. PACpAInt highlights the presence of a minor aggressive Basal contingent that negatively impacts survival in 39% of RNA-defined classical cases. Tile-level analysis ( > 6 millions) redefines PDAC microheterogeneity showing codependencies in the distribution of tumor and stroma subtypes, and demonstrates that, in addition to the Classical and Basal tumors, there are Hybrid tumors that combine the latter subtypes, and Intermediate tumors that may represent a transition state during PDAC evolution.

Priming therapy by targeting enhancer-initiated pathways in patient-derived pancreatic cancer cells.

BACKGROUND: Systems biology leveraging multi-OMICs technologies, is rapidly advancing development of precision therapies and matching patients to targeted therapies, leading to improved responses. A new pillar of precision oncology lies in the power of chemogenomics to discover drugs that sensitizes malignant cells to other therapies. Here, we test a chemogenomic approach using epigenomic inhibitors (epidrugs) to reset patterns of gene expression driving the malignant behavior of pancreatic tumors. METHODS: We tested a targeted library of ten epidrugs targeting regulators of enhancers and super-enhancers on reprogramming gene expression networks in seventeen patient-derived primary pancreatic cancer cell cultures (PDPCCs), of both basal and classical subtypes. We subsequently evaluated the ability of these epidrugs to sensitize pancreatic cancer cells to five chemotherapeutic drugs that are clinically used for this malignancy. FINDINGS: To comprehend the impact of epidrug priming at the molecular level, we evaluated the effect of each epidrugs at the transcriptomic level of PDPCCs. The activating epidrugs showed a higher number of upregulated genes than the repressive epidrugs (χ2 test p-value <0.01). Furthermore, we developed a classifier using the baseline transcriptome of epidrug-primed-chemosensitized PDPCCs to predict the best epidrug-priming regime to a given chemotherapy. Six signatures with a significant association with the chemosensitization centroid (R ≤ -0.80; p-value < 0.01) were identified and validated in a subset of PDPCCs. INTERPRETATION: We conclude that targeting enhancer-initiated pathways in patient-derived primary cells, represents a promising approach for developing new therapies for human pancreatic cancer. FUNDING: This work was supported by INCa (Grants number 2018-078 to ND and 2018- 079 to JI), Canceropole PACA (ND), Amidex Foundation (ND), and INSERM (JI).

Genomic Instability and Protumoral Inflammation Are Associated with Primary Resistance to Anti-PD-1 + Antiangiogenesis in Malignant Pleural Mesothelioma.

Cancer immunotherapy combinations have recently been shown to improve the overall survival of advanced mesotheliomas, especially for patients responding to those treatments. We aimed to characterize the biological correlates of malignant pleural mesotheliomas' primary resistance to immunotherapy and antiangiogenics by testing the combination of pembrolizumab, an anti-PD-1 antibody, and nintedanib, a pan-antiangiogenic tyrosine kinase inhibitor, in the multicenter PEMBIB trial (NCT02856425). Thirty patients with advanced malignant pleural mesothelioma were treated and explored. Unexpectedly, we found that refractory patients were actively recruiting CD3+CD8+ cytotoxic T cells in their tumors through CXCL9 tumor release upon treatment. However, these patients displayed high levels of somatic copy-number alterations in their tumors that correlated with high blood and tumor levels of IL6 and CXCL8. Those proinflammatory cytokines resulted in higher tumor secretion of VEGF and tumor enrichment in regulatory T cells. Advanced mesothelioma should further benefit from stratified combination therapies adapted to their tumor biology. SIGNIFICANCE: Sequential explorations of fresh tumor biopsies demonstrated that mesothelioma resistance to anti-PD-1 + antiangiogenics is not due to a lack of tumor T-cell infiltration but rather due to adaptive immunosuppressive pathways by tumors, involving molecules (e.g., IL6, CXCL8, VEGF, and CTLA4) that are amenable to targeted therapies. This article is highlighted in the In This Issue feature, p. 799.

Ephrin-B1 regulates the adult diastolic function through a late postnatal maturation of cardiomyocyte surface crests.

The rod-shaped adult cardiomyocyte (CM) harbors a unique architecture of its lateral surface with periodic crests, relying on the presence of subsarcolemmal mitochondria (SSM) with unknown role. Here, we investigated the development and functional role of CM crests during the postnatal period. We found in rodents that CM crest maturation occurs late between postnatal day 20 (P20) and P60 through both SSM biogenesis, swelling and crest-crest lateral interactions between adjacent CM, promoting tissue compaction. At the functional level, we showed that the P20-P60 period is dedicated to the improvement of relaxation. Interestingly, crest maturation specifically contributes to an atypical CM hypertrophy of its short axis, without myofibril addition, but relying on CM lateral stretching. Mechanistically, using constitutive and conditional CM-specific knock-out mice, we identified ephrin-B1, a lateral membrane stabilizer, as a molecular determinant of P20-P60 crest maturation, governing both the CM lateral stretch and the diastolic function, thus highly suggesting a link between crest maturity and diastole. Remarkably, while young adult CM-specific Efnb1 KO mice essentially exhibit an impairment of the ventricular diastole with preserved ejection fraction and exercise intolerance, they progressively switch toward systolic heart failure with 100% KO mice dying after 13 months, indicative of a critical role of CM-ephrin-B1 in the adult heart function. This study highlights the molecular determinants and the biological implication of a new late P20-P60 postnatal developmental stage of the heart in rodents during which, in part, ephrin-B1 specifically regulates the maturation of the CM surface crests and of the diastolic function.

Preclinical evaluation of CDK4 phosphorylation predicts high sensitivity of pleural mesotheliomas to CDK4/6 inhibition.

Malignant pleural mesothelioma (MPM) is an aggressive cancer with limited therapeutic options. We evaluated the impact of CDK4/6 inhibition by palbociclib in 28 MPM cell lines including 19 patient-derived ones, using various approaches including RNA-sequencing. Palbociclib strongly and durably inhibited the proliferation of 23 cell lines, indicating a unique sensitivity of MPM to CDK4/6 inhibition. When observed, insensitivity to palbociclib was mostly explained by the lack of active T172-phosphorylated CDK4. This was associated with high p16INK4A (CDKN2A) levels that accompany RB1 defects or inactivation, or (unexpectedly) CCNE1 overexpression in the presence of wild-type RB1. Prolonged palbociclib treatment irreversibly inhibited proliferation despite re-induction of cell cycle genes upon drug washout. A senescence-associated secretory phenotype including various potentially immunogenic components was irreversibly induced. Phosphorylated CDK4 was detected in 80% of 47 MPMs indicating their sensitivity to CDK4/6 inhibitors. Its absence in some highly proliferative MPMs was linked to very high p16 (CDKN2A) expression, which was also observed in public datasets in tumours from short-survival patients. Our study supports the evaluation of CDK4/6 inhibitors for MPM treatment, in monotherapy or combination therapy.

Difference in Pap test uptake between women who have sex with women and other women in France: A comparative survey of 2032 women.

The elimination of cervical cancer has been a priority of the World Health Organization since 2018. The number of these cancers induced by the human papillomavirus (HPV) could be drastically reduced through vaccination and regularly screening by Pap tests. Guidelines for cervical cancer screening apply to all women, including those who have sexual relations with women (WSW), as HPV can be transmitted during sex between two women. As far as we know, our study is the first that compare the Pap test rate between WSW and other women in France. We developed an 18-item questionnaire available on the internet for 15 days and finally analyzed the responses of 2032 women. Based on their responses about their self-definition of their sexual orientation and their sexual behavior, we classified them into three groups of women: exclusive WSW, mixed WSW, and non-WSW. For each question, we tested the statistical differences in responses between these three groups. Our study shows in a large sample representative of the French population that exclusive WSW undergo Pap tests significantly less often than either mixed WSW or non-WSW. Among the exclusive WSW, 28.9 % had never had a Pap test, compared with 9 % of the mixed WSW and 3.1 % of non-WSW (p < 0,001). The responses to our questionnaire contribute to an understanding of this disparity and thus help to envision solutions for better care of all women, regardless of their sexual orientation; this point is crucial for prevention of cervical cancer.

Integrative study of diet-induced mouse models of NAFLD identifies PPARα as a sexually dimorphic drug target.

OBJECTIVE: We evaluated the influence of sex on the pathophysiology of non-alcoholic fatty liver disease (NAFLD). We investigated diet-induced phenotypic responses to define sex-specific regulation between healthy liver and NAFLD to identify influential pathways in different preclinical murine models and their relevance in humans. DESIGN: Different models of diet-induced NAFLD (high-fat diet, choline-deficient high-fat diet, Western diet or Western diet supplemented with fructose and glucose in drinking water) were compared with a control diet in male and female mice. We performed metabolic phenotyping, including plasma biochemistry and liver histology, untargeted large-scale approaches (liver metabolome, lipidome and transcriptome), gene expression profiling and network analysis to identify sex-specific pathways in the mouse liver. RESULTS: The different diets induced sex-specific responses that illustrated an increased susceptibility to NAFLD in male mice. The most severe lipid accumulation and inflammation/fibrosis occurred in males receiving the high-fat diet and Western diet, respectively. Sex-biased hepatic gene signatures were identified for these different dietary challenges. The peroxisome proliferator-activated receptor α (PPARα) co-expression network was identified as sexually dimorphic, and in vivo experiments in mice demonstrated that hepatocyte PPARα determines a sex-specific response to fasting and treatment with pemafibrate, a selective PPARα agonist. Liver molecular signatures in humans also provided evidence of sexually dimorphic gene expression profiles and the sex-specific co-expression network for PPARα. CONCLUSIONS: These findings underscore the sex specificity of NAFLD pathophysiology in preclinical studies and identify PPARα as a pivotal, sexually dimorphic, pharmacological target. TRIAL REGISTRATION NUMBER: NCT02390232.

DECONbench: a benchmarking platform dedicated to deconvolution methods for tumor heterogeneity quantification.

BACKGROUND: Quantification of tumor heterogeneity is essential to better understand cancer progression and to adapt therapeutic treatments to patient specificities. Bioinformatic tools to assess the different cell populations from single-omic datasets as bulk transcriptome or methylome samples have been recently developed, including reference-based and reference-free methods. Improved methods using multi-omic datasets are yet to be developed in the future and the community would need systematic tools to perform a comparative evaluation of these algorithms on controlled data. RESULTS: We present DECONbench, a standardized unbiased benchmarking resource, applied to the evaluation of computational methods quantifying cell-type heterogeneity in cancer. DECONbench includes gold standard simulated benchmark datasets, consisting of transcriptome and methylome profiles mimicking pancreatic adenocarcinoma molecular heterogeneity, and a set of baseline deconvolution methods (reference-free algorithms inferring cell-type proportions). DECONbench performs a systematic performance evaluation of each new methodological contribution and provides the possibility to publicly share source code and scoring. CONCLUSION: DECONbench allows continuous submission of new methods in a user-friendly fashion, each novel contribution being automatically compared to the reference baseline methods, which enables crowdsourced benchmarking. DECONbench is designed to serve as a reference platform for the benchmarking of deconvolution methods in the evaluation of cancer heterogeneity. We believe it will contribute to leverage the benchmarking practices in the biomedical and life science communities. DECONbench is hosted on the open source Codalab competition platform. It is freely available at: https://competitions.codalab.org/competitions/27453 .

Multi-site tumor sampling highlights molecular intra-tumor heterogeneity in malignant pleural mesothelioma.

BACKGROUND: Malignant pleural mesothelioma (MPM) is a heterogeneous cancer. Better knowledge of molecular and cellular intra-tumor heterogeneity throughout the thoracic cavity is required to develop efficient therapies. This study focuses on molecular intra-tumor heterogeneity using the largest series to date in MPM and is the first to report on the multi-omics profiling of a substantial series of multi-site tumor samples. METHODS: Intra-tumor heterogeneity was investigated in 16 patients from whom biopsies were taken at distinct anatomical sites. The paired biopsies collected from apex, side wall, costo-diaphragmatic, or highest metabolic sites as well as 5 derived cell lines were screened using targeted sequencing. Whole exome sequencing, RNA sequencing, and DNA methylation were performed on a subset of the cohort for deep characterization. Molecular classification, recently defined histo-molecular gradients, and cell populations of the tumor microenvironment were assessed. RESULTS: Sequencing analysis identified heterogeneous variants notably in NF2, a key tumor suppressor gene of mesothelial carcinogenesis. Subclonal tumor populations were shared among paired biopsies, suggesting a polyclonal dissemination of the tumor. Transcriptome analysis highlighted dysregulation of cell adhesion and extracellular matrix pathways, linked to changes in histo-molecular gradient proportions between anatomic sites. Methylome analysis revealed the contribution of epigenetic mechanisms in two patients. Finally, significant changes in the expression of immune mediators and genes related to immunological synapse, as well as differential infiltration of immune populations in the tumor environment, were observed and led to a switch from a hot to a cold immune profile in three patients. CONCLUSIONS: This comprehensive analysis reveals patient-dependent spatial intra-tumor heterogeneity at the genetic, transcriptomic, and epigenetic levels and in the immune landscape of the tumor microenvironment. Results support the need for multi-sampling for the implementation of molecular-based precision medicine.

Intratumor CMS Heterogeneity Impacts Patient Prognosis in Localized Colon Cancer.

PURPOSE: The consensus molecular subtypes (CMS) represent a significant advance in the understanding of intertumor heterogeneity in colon cancer. Intratumor heterogeneity (ITH) is the new frontier for refining prognostication and understanding treatment resistance. This study aims at deciphering the transcriptomic ITH of colon cancer and understanding its potential prognostic implications. EXPERIMENTAL DESIGN: We deconvoluted the transcriptomic profiles of 1,779 tumors from the PETACC8 trial and 155 colon cancer cell lines as weighted sums of the four CMSs, using the Weighted In Silico Pathology (WISP) algorithm. We assigned to each tumor and cell line a combination of up to three CMS subtypes with a threshold above 20%. RESULTS: Over 55% of tumors corresponded to mixtures of at least two CMSs, demonstrating pervasive ITH in colon cancer. Of note, ITH was associated with shorter disease-free survival (DFS) and overall survival, [HR, 1.34; 95% confidence interval (CI; 1.12-1.59), 1.40, 95% CI (1.14-1.71), respectively]. Moreover, we uncovered specific combinations of CMS associated with dismal prognosis. In multivariate analysis, ITH represents the third parameter explaining DFS variance, after T and N stages. At a cellular level, combined WISP and single-cell transcriptomic analysis revealed that most colon cancer cell lines are a mixture of cells falling into different CMSs, indicating that ITH may correspond to distinct functional statuses of colon cancer cells. CONCLUSIONS: This study shows that CMS-based transcriptomic ITH is frequent in colon cancer and impacts its prognosis. CMS-based transcriptomic ITH may correspond to distinct functional statuses of colon cancer cells, suggesting plasticity between CMS-related cell populations. Transcriptomic ITH deserves further assessment in the context of personalized medicine.

Pancreatic Ductal Adenocarcinoma Arising in Young and Old Patients Displays Similar Molecular Features.

Pancreatic ducal adenocarcinoma is classically diagnosed in the 7th decade, but approximately 10% of patients are diagnosed under 55 years (y.o.). While the genomic and transcriptomic landscapes of late-onset tumors (LOT) have been described, little is known about early-onset tumors (EOT). Ageing is known to impact DNA methylation and proteome integrity through carbonylation-related oxidative damages. We therefore aimed to assess the global molecular features of EOT. We compared 176 EOT (≤55 y.o.) and 316 LOT (≥70 y.o.) from three distinct surgical cohorts at the clinical/genomic/epigenomic/transcriptomic level. Furthermore, we assessed oxidative stress responses and oxidative proteome damages using 2D gel electrophoresis followed by mass spectrometry protein identification. There was no consistent clinical difference between EOT and LOT across the three cohorts. The mutational landscape of key driver genes and the global methylation profile were similar in the two groups. LOT did display age-related features such as enriched DNA repair gene signatures and upregulation of oxidative stress defenses together with increased proteome carbonylation. However, these age-related differences were more preeminent in non-tumor tissues while tumor proteome and proteome damages were fairly comparable. In conclusion, this multi-omics comparison showed that EOT harbor a comparable molecular profile to that of LOT.

Establishment of a pancreatic adenocarcinoma molecular gradient (PAMG) that predicts the clinical outcome of pancreatic cancer.

BACKGROUND: A significant gap in pancreatic ductal adenocarcinoma (PDAC) patient's care is the lack of molecular parameters characterizing tumours and allowing a personalized treatment. METHODS: Patient-derived xenografts (PDX) were obtained from 76 consecutive PDAC and classified according to their histology into five groups. A PDAC molecular gradient (PAMG) was constructed from PDX transcriptomes recapitulating the five histological groups along a continuous gradient. The prognostic and predictive value for PMAG was evaluated in: i/ two independent series (n = 598) of resected tumours; ii/ 60 advanced tumours obtained by diagnostic EUS-guided biopsy needle flushing and iii/ on 28 biopsies from mFOLFIRINOX treated metastatic tumours. FINDINGS: A unique transcriptomic signature (PAGM) was generated with significant and independent prognostic value. PAMG significantly improves the characterization of PDAC heterogeneity compared to non-overlapping classifications as validated in 4 independent series of tumours (e.g. 308 consecutive resected PDAC, uHR=0.321 95% CI [0.207-0.5] and 60 locally-advanced or metastatic PDAC, uHR=0.308 95% CI [0.113-0.836]). The PAMG signature is also associated with progression under mFOLFIRINOX treatment (Pearson correlation to tumour response: -0.67, p-value < 0.001). INTERPRETATION: PAMG unify all PDAC pre-existing classifications inducing a shift in the actual paradigm of binary classifications towards a better characterization in a gradient. FUNDING: Project funding was provided by INCa (Grants number 2018-078 and 2018-079, BACAP BCB INCa_6294), Canceropole PACA, DGOS (labellisation SIRIC), Amidex Foundation, Fondation de France, INSERM and Ligue Contre le Cancer.

Genetic alterations of malignant pleural mesothelioma: association with tumor heterogeneity and overall survival.

Development of precision medicine for malignant pleural mesothelioma (MPM) requires a deep knowledge of tumor heterogeneity. Histologic and molecular classifications and histo-molecular gradients have been proposed to describe heterogeneity, but a deeper understanding of gene mutations in the context of MPM heterogeneity is required and the associations between mutations and clinical data need to be refined. We characterized genetic alterations on one of the largest MPM series (266 tumor samples), well annotated with histologic, molecular and clinical data of patients. Targeted next-generation sequencing was performed focusing on the major MPM mutated genes and the TERT promoter. Molecular heterogeneity was characterized using predictors allowing classification of each tumor into the previously described molecular subtypes and the determination of the proportion of epithelioid-like and sarcomatoid-like components (E/S.scores). The mutation frequencies are consistent with literature data, but this study emphasized that TERT promoter, not considered by previous large sequencing studies, was the third locus most affected by mutations in MPM. Mutations in TERT promoter, NF2, and LATS2 were more frequent in nonepithelioid MPM and positively associated with the S.score. BAP1, NF2, TERT promoter, TP53, and SETD2 mutations were enriched in some molecular subtypes. NF2 mutation rate was higher in asbestos unexposed patient. TERT promoter, NF2, and TP53 mutations were associated with a poorer overall survival. Our findings lead to a better characterization of MPM heterogeneity by identifying new significant associations between mutational status and histologic and molecular heterogeneity. Strikingly, we highlight the strong association between new mutations and overall survival.

Combined MEK and PI3K/p110ß Inhibition as a Novel Targeted Therapy for Malignant Mesothelioma Displaying Sarcomatoid Features.

Among malignant mesotheliomas (MM), the sarcomatoid subtype is associated with higher chemoresistance and worst survival. Due to its low incidence, there has been little progress in the knowledge of the molecular mechanisms associated with sarcomatoid MM, which might help to define novel therapeutic targets. In this work, we show that loss of PTEN expression is frequent in human sarcomatoid MM and PTEN expression levels are lower in sarcomatoid MM than in the biphasic and epithelioid subtypes. Combined Pten and Trp53 deletion in mouse mesothelium led to nonepithelioid MM development. In Pten;Trp53-null mice developing MM, the Gαi2-coupled receptor subunit activated MEK/ERK and PI3K, resulting in aggressive, immune-suppressed tumors. Combined inhibition of MEK and p110ß/PI3K reduced mouse tumor cell growth in vitro. Therapeutic inhibition of MEK and p110ß/PI3K using selumetinib (AZD6244, ARRY-142886) and AZD8186, two drugs that are currently in clinical trials, increased the survival of Pten;Trp53-null mice without major toxicity. This drug combination effectively reduced the proliferation of primary cultures of human pleural (Pl) MM, implicating nonepithelioid histology and high vimentin, AKT1/2, and Gαi2 expression levels as predictive markers of response to combined MEK and p110ß/PI3K inhibition. Our findings provide a rationale for the use of selumetinib and AZD8186 in patients with MM with sarcomatoid features. This constitutes a novel targeted therapy for a poor prognosis and frequently chemoresistant group of patients with MM, for whom therapeutic options are currently lacking. SIGNIFICANCE: Mesothelioma is highly aggressive; its sarcomatoid variants have worse prognosis. Building on a genetic mouse model, a novel combination therapy is uncovered that is relevant to human tumors.

Depicting the genetic architecture of pediatric cancers through an integrative gene network approach.

The genetic etiology of childhood cancers still remains largely unknown. It is therefore essential to develop novel strategies to unravel the spectrum of pediatric cancer genes. Statistical network modeling techniques have emerged as powerful methodologies for enabling the inference of gene-disease relationship and have been performed on adult but not pediatric cancers. We performed a deep multi-layer understanding of pan-cancer transcriptome data selected from the Treehouse Childhood Cancer Initiative through a co-expression network analysis. We identified six modules strongly associated with pediatric tumor histotypes that were functionally linked to developmental processes. Topological analyses highlighted that pediatric cancer predisposition genes and potential therapeutic targets were central regulators of cancer-histotype specific modules. A module was related to multiple pediatric malignancies with functions involved in DNA repair and cell cycle regulation. This canonical oncogenic module gathered most of the childhood cancer predisposition genes and clinically actionable genes. In pediatric acute leukemias, the driver genes were co-expressed in a module related to epigenetic and post-transcriptional processes, suggesting a critical role of these pathways in the progression of hematologic malignancies. This integrative pan-cancer study provides a thorough characterization of pediatric tumor-associated modules and paves the way for investigating novel candidate genes involved in childhood tumorigenesis.

Unraveling the cellular heterogeneity of malignant pleural mesothelioma through a deconvolution approach.

We determined the proportions of epithelioid-like and sarcomatoid-like cellular entities within malignant pleural mesothelioma samples, by deconvolution of their transcriptomes. These proportions are associated with prognosis and may guide therapeutic strategies. This novel approach describes both intra- and inter-tumor heterogeneity and provides a new way of thinking about cancer pathology.

Dissecting heterogeneity in malignant pleural mesothelioma through histo-molecular gradients for clinical applications.

Malignant pleural mesothelioma (MPM) is recognized as heterogeneous based both on histology and molecular profiling. Histology addresses inter-tumor and intra-tumor heterogeneity in MPM and describes three major types: epithelioid, sarcomatoid and biphasic, a combination of the former two types. Molecular profiling studies have not addressed intra-tumor heterogeneity in MPM to date. Here, we use a deconvolution approach and show that molecular gradients shed new light on the intra-tumor heterogeneity of MPM, leading to a reconsideration of MPM molecular classifications. We show that each tumor can be decomposed as a combination of epithelioid-like and sarcomatoid-like components whose proportions are highly associated with the prognosis. Moreover, we show that this more subtle way of characterizing MPM heterogeneity provides a better understanding of the underlying oncogenic pathways and the related epigenetic regulation and immune and stromal contexts. We discuss the implications of these findings for guiding therapeutic strategies, particularly immunotherapies and targeted therapies.

Prognostic Biomarkers in Pancreatic Cancer: Avoiding Errata When Using the TCGA Dataset.

Data from the Cancer Genome Atlas (TCGA) are now easily accessible through web-based platforms with tools to assess the prognostic value of molecular alterations. Pancreatic tumors have heterogeneous biology and aggressiveness ranging from the deadly adenocarcinoma (PDAC) to the better prognosis, neuroendocrine tumors. We assessed the availability of the pancreatic cancer TCGA data (TCGA_PAAD) from several repositories and investigated the nature of each sample and how non-PDAC samples impact prognostic biomarker studies. While the clinical and genomic data (n = 185) were fairly consistent across all repositories, RNAseq profiles varied from 176 to 185. As a result, 35 RNAseq profiles (18.9%) corresponded to a normal, inflamed pancreas or non-PDAC neoplasms. This information was difficult to obtain. By considering gene expression data as continuous values, the expression of the 5312 and 4221 genes were significantly associated with the progression-free and overall survival respectively. Considering the cohort was not curated, only 4 and 14, respectively, had prognostic value in the PDAC-only cohort. Similarly, mutations in key genes or well-described miRNA lost their prognostic significance in the PDAC-only cohort. Therefore, we propose a web-based application to assess biomarkers in the curated TCGA_PAAD dataset. In conclusion, TCGA_PAAD curation is critical to avoid important biological and clinical biases from non-PDAC samples.