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Abstract Background Microsatellite instability (MSI) due to mismatch repair deficiency (dMMR) is common in colorectal cancer (CRC). These cancers are associated with somatic coding events, but the noncoding pathophysiological impact of this genomic instability is yet poorly understood. Here, we perform an analysis of coding and noncoding MSI events at the different steps of colorectal tumorigenesis using whole exome sequencing and search for associated splicing events via RNA sequencing at the bulk-tumor and single-cell levels. Results Our results demonstrate that MSI leads to hundreds of noncoding DNA mutations, notably at polypyrimidine U2AF RNA-binding sites which are endowed with cis-activity in splicing, while higher frequency of exon skipping events are observed in the mRNAs of MSI compared to non-MSI CRC. At the DNA level, these noncoding MSI mutations occur very early prior to cell transformation in the dMMR colonic crypt, accounting for only a fraction of the exon skipping in MSI CRC. At the RNA level, the aberrant exon skipping signature is likely to impair colonic cell differentiation in MSI CRC affecting the expression of alternative exons encoding protein isoforms governing cell fate, while also targeting constitutive exons, making dMMR cells immunogenic in early stage before the onset of coding mutations. This signature is characterized by its similarity to the oncogenic U2AF1-S34F splicing mutation observed in several other non-MSI cancer. Conclusions Overall, these findings provide evidence that a very early RNA splicing signature partly driven by MSI impairs cell differentiation and promotes MSI CRC initiation, far before coding mutations which accumulate later during MSI tumorigenesis.

Abstract We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression of tumor samples, through a community-wide DREAM Challenge. We assess six published and 22 community-contributed methods using in vitro and in silico transcriptional profiles of admixed cancer and healthy immune cells. Several published methods predict most cell types well, though they either were not trained to evaluate all functional CD8+ T cell states or do so with low accuracy. Several community-contributed methods address this gap, including a deep learning-based approach, whose strong performance establishes the applicability of this paradigm to deconvolution. Despite being developed largely using immune cells from healthy tissues, deconvolution methods predict levels of tumor-derived immune cells well. Our admixed and purified transcriptional profiles will be a valuable resource for developing deconvolution methods, including in response to common challenges we observe across methods, such as sensitive identification of functional CD4+ T cell states.

Abstract Background The mesenchymal subtype of colorectal cancer (CRC), associated with poor prognosis, is characterized by abundant expression of the cellular prion protein PrPC, which represents a candidate therapeutic target. How PrPC is induced in CRC remains elusive. This study aims to elucidate the signaling pathways governing PrPC expression and to shed light on the gene regulatory networks linked to PrPC. Methods We performed in silico analyses on diverse datasets of in vitro, ex vivo and in vivo models of mouse CRC and patient cohorts. We mined ChIPseq studies and performed promoter analysis. CRC cell lines were manipulated through genetic and pharmacological approaches. We created mice combining conditional inactivation of Apc in intestinal epithelial cells and overexpression of the human prion protein gene PRNP. Bio-informatic analyses were carried out in two randomized control trials totalizing over 3000 CRC patients. Results In silico analyses combined with cell-based assays identified the Wnt-β-catenin and glucocorticoid pathways as upstream regulators of PRNP expression, with subtle differences between mouse and human. We uncover multiple feedback loops between PrPC and these two pathways, which translate into an aggravation of CRC pathogenesis in mouse. In stage III CRC patients, the signature defined by PRNP-CTNNB1-NR3C1, encoding PrPC, β-catenin and the glucocorticoid receptor respectively, is overrepresented in the poor-prognosis, mesenchymal subtype and associates with reduced time to recurrence. Conclusions An unleashed PrPC-dependent vicious circle is pathognomonic of poor prognosis, mesenchymal CRC. Patients from this aggressive subtype of CRC may benefit from therapies targeting the PRNP-CTNNB1-NR3C1 axis.

Abstract Checkpoint immunotherapy (CPI) has increased survival for some patients with advanced-stage bladder cancer (BCa). However, most patients do not respond. Here, we characterized the tumor and immune microenvironment in pre- and post-treatment tumors from the PURE01 neoadjuvant pembrolizumab immunotherapy trial, using a consolidative approach that combined transcriptional and genetic profiling with digital spatial profiling. We identify five distinctive genetic and transcriptomic programs and validate these in an independent neoadjuvant CPI trial to identify the features of response or resistance to CPI. By modeling the regulatory network, we identify the histone demethylase KDM5B as a repressor of tumor immune signaling pathways in one resistant subtype (S1, Luminal-excluded) and demonstrate that inhibition of KDM5B enhances immunogenicity in FGFR3-mutated BCa cells. Our study identifies signatures associated with response to CPI that can be used to molecularly stratify patients and suggests therapeutic alternatives for subtypes with poor response to neoadjuvant immunotherapy.

Abstract 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 .

Retinoblastoma is the most frequent intraocular paediatric malignancy whose molecular basis remains poorly understood. Here, the authors perform multi-omic analysis and identify two subtypes; one in a cone differentiated state and one more aggressive showing cone dedifferentiation and expressing neuronal markers.

Multiple molecular profiling methods are required to study urothelial non-muscle-invasive bladder cancer (NMIBC) due to its heterogeneity. Here the authors integrate multi-omics data of 834 NMIBC patients, identifying a molecular subgroup associated with multiple alterations and worse outcomes.

Abstract Quantifying tissue-infiltrating immune and stromal cells provides clinically relevant information for various diseases. While numerous methods can quantify immune or stromal cells in human tissue samples from transcriptomic data, few are available for mouse studies. We introduce murine Microenvironment Cell Population counter (mMCP-counter), a method based on highly specific transcriptomic markers that accurately quantify 16 immune and stromal murine cell populations. We validated mMCP-counter with flow cytometry data and showed that mMCP-counter outperforms existing methods. We showed that mMCP-counter scores are predictive of response to immune checkpoint blockade in cancer mouse models and identify early immune impacts of Alzheimer’s disease.

Chondrosarcomas are heterogenous tumours of the bone cartilage and have highly variable prognoses. Here, the authors perform a multi-omics analysis, revealing molecular features that can stratify clinical outcomes.

Context: The number of prognostic markers for clear cell renal cell carcinoma (ccRCC) has been increasing regularly over the last 15 years, without being integrated and compared.Objective: Our goal was to perform a review of prognostic markers for ccRCC to lay the ground for their use in the clinics.Evidence Acquisition: PubMed database was searched to identify RNA and protein markers whose expression level was reported as associated with survival of ccRCC patients. Relevant studies were selected through cross-reading by two readers.Evidence Synthesis: We selected 249 studies reporting an association with prognostic of either single markers or multiple-marker models. Altogether, these studies were based on a total of 341 distinct markers and 13 multiple-marker models. Twenty percent of these markers were involved in four biological pathways altered in ccRCC: cell cycle, angiogenesis, hypoxia, and immune response. The main genes (VHL, PBRM1, BAP1, and SETD2) involved in ccRCC carcinogenesis are not the most relevant for assessing survival.Conclusion: Among single markers, the most validated markers were KI67, BIRC5, TP53, CXCR4, and CA9. Of the multiple-marker models, the most famous model, ClearCode34, has been highly validated on several independent datasets, but its clinical utility has not yet been investigated.Patient Summary: Over the years, the prognosis studies have evolved from single markers to multiple-marker models. Our review highlights the highly validated prognostic markers and multiple-marker models and discusses their clinical utility for better therapeutic care.

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.

Malignant pleural mesothelioma (MPM) is a rare and aggressive form of cancer. Here, the authors show MPM is heterogeneously composed of epithelioid and sarcomatoid components and their proportions associate with prognosis and could inform therapeutic strategies.

Tumor cells constantly interact with their microenvironment, which comprises a variety of immune cells together with endothelial cells and fibroblasts. The composition of the tumor microenvironment (TME) has been shown to influence response to immune checkpoint blockade (ICB). ICB takes advantage of immune cell infiltration in the tumor to reinvigorate an efficacious antitumoral immune response. In addition to tumor cell intrinsic biomarkers, increasing data pinpoint the importance of the TME in guiding patient selection and combination therapies. Here, we review recent efforts in determining how various components of the TME can influence response and resistance to ICB. Although a large body of evidence points to the extent and functional orientation of the T cell infiltrate as important in therapy response, recent studies also confirm a role for other components of the TME, such as B cells, myeloid lineage cells, cancer-associated fibroblasts, and vasculature. If the ultimate goal of curative cancer therapies is to induce a long-term memory T cell response, the other components of the TME may positively or negatively modulate the induction of efficient antitumor immunity. The emergence of novel high-throughput methods for analyzing the TME, including transcriptomics, has allowed tremendous developments in the field, with the expansion of patient cohorts, and the identification of TME-based markers of therapy response. Together, these studies open the possibility of including TME-based markers for selecting patients that are likely to respond to specific therapies, and pave the way to personalized medicine in oncology.

Activation of the PPARγ/RXRα pathway in luminal bladder cancers has mainly been linked to PPARG gene amplifications and activating point mutations in RXRα. Here, the authors identify recurrent PPARγ mutations with similar effects and elucidate the structural basis for this mutational PPARγ activation.

Pancreatic ductal adenocarcinoma (PDAC) is a complex disease and its underlying epigenomic heterogeneity is not fully understood. Here, the authors utilize patient-derived PDAC xenografts to define the epigenomic landscape of PDAC, highlighting chromatin states linked to differing disease aggressiveness and survival.

Background & Aims: Recent studies have shown that cancers arise as a result of the positive selection of driver somatic events in tumor DNA, with negative selection playing only a minor role, if any. However, these investigations were concerned with alterations at nonrepetitive sequences and did not take into account mutations in repetitive sequences that have very high pathophysiological relevance in the tumors showing microsatellite instability (MSI) resulting from mismatch repair deficiency investigated in the present study. Methods: We performed whole-exome sequencing of 47 MSI colorectal cancers (CRCs) and confirmed results in an independent cohort of 53 MSI CRCs. We used a probabilistic model of mutational events within microsatellites, while adapting pre-existing models to analyze nonrepetitive DNA sequences. Negatively selected coding alterations in MSI CRCs were investigated for their functional and clinical impact in CRC cell lines and in a third cohort of 164 MSI CRC patients. Results: Both positive and negative selection of somatic mutations in DNA repeats was observed, leading us to identify the expected true driver genes associated with the MSI-driven tumorigenic process. Several coding negatively selected MSI-related mutational events (n = 5) were shown to have deleterious effects on tumor cells. In the tumors in which deleterious MSI mutations were observed despite the negative selection, they were associated with worse survival in MSI CRC patients (hazard ratio, 3; 95% CI, 1.1–7.9; P = .03), suggesting their anticancer impact should be offset by other as yet unknown oncogenic processes that contribute to a poor prognosis. Conclusions: The present results identify the positive and negative driver somatic mutations acting in MSI-driven tumorigenesis, suggesting that genomic instability in MSI CRC plays a dual role in achieving tumor cell transformation. Exome sequencing data have been deposited in the European genome–phenome archive (accession: EGAS00001002477). Keywords: Colorectal Cancer, Microsatellite Instability, Tumorigenic Process, Driver Gene Mutations, Positive and Negative Selection

Preclinical models based on patient-derived xenografts have remarkable specificity in distinguishing transformed human tumor cells from non-transformed murine stromal cells computationally. We obtained 29 pancreatic ductal adenocarcinoma (PDAC) xenografts from either resectable or non-resectable patients (surgery and endoscopic ultrasound-guided fine-needle aspirate, respectively). Extensive multiomic profiling revealed two subtypes with distinct clinical outcomes. These subtypes uncovered specific alterations in DNA methylation and transcription as well as in signaling pathways involved in tumor-stromal cross-talk. The analysis of these pathways indicates therapeutic opportunities for targeting both compartments and their interactions. In particular, we show that inhibiting NPC1L1 with Ezetimibe, a clinically available drug, might be an efficient approach for treating pancreatic cancers. These findings uncover the complex and diverse interplay between PDAC tumors and the stroma and demonstrate the pivotal role of xenografts for drug discovery and relevance to PDAC.

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.

Oligodendroglial tumours are characterized into three different molecular subtypes. Here, the authors use genomic data to identify a further three subgroups of 1p/19q co-deleted tumours and demonstrate an association with an aggressive phenotype.

Tumors are formed by aggregates of cells of various origins including malignant, stromal and immune cells. The number of therapies targeting the microenvironment is increasing as the tumor microenvironment is more and more recognized as playing an essential role in tumor control. In the era of precision medicine, it is essential to precisely estimate the composition, organization and functionality of the individual patient tumor microenvironment and to find ways to therapeutically modulate it. To quantify the cell populations present in the tumor microenvironment, many tools are now available and the most recent approaches will be reviewed herein. We provide an overview of experimental and computational methodologies used to quantify tumor-associated cellular populations, including immunohistochemistry, flow and mass cytometry, bulk and single-cell transcriptomic approaches. We illustrate their respective contribution to characterize the microenvironment. We also discuss how these methods allow to guide therapeutic choices, in relation to the predictive value of some characteristics of the microenvironment.

Extracting relevant information from large-scale data offers unprecedented opportunities in cancerology. We applied independent component analysis (ICA) to bladder cancer transcriptome data sets and interpreted the components using gene enrichment analysis and tumor-associated molecular, clinicopathological, and processing information. We identified components associated with biological processes of tumor cells or the tumor microenvironment, and other components revealed technical biases. Applying ICA to nine cancer types identified cancer-shared and bladder-cancer-specific components. We characterized the luminal and basal-like subtypes of muscle-invasive bladder cancers according to the components identified. The study of the urothelial differentiation component, specific to the luminal subtypes, showed that a molecular urothelial differentiation program was maintained even in those luminal tumors that had lost morphological differentiation. Study of the genomic alterations associated with this component coupled with functional studies revealed a protumorigenic role for PPARG in luminal tumors. Our results support the inclusion of ICA in the exploitation of multiscale data sets.

Insulin-like growth factor 2 (IGF2) overexpression is an important molecular marker of adrenocortical carcinoma (ACC), which is a rare but devastating endocrine cancer. It is not clear whether IGF2 overexpression modifies the biology and growth of this cancer, thus more studies are required before IGF2 can be considered as a major therapeutic target. We compared the phenotypical, clinical, biological, and molecular characteristics of ACC with or without the overexpression of IGF2, to address these issues. We also carried out a similar analysis in an ACC cell line (H295R) in which IGF2 expression was knocked down with si- or shRNA. We found no significant differences in the clinical, biological and molecular (transcriptomic) traits between IGF2-high and IGF2-low ACC. The absence of IGF2 overexpression had little influence on the activation of tyrosine kinase pathways both in tumors and in H295 cells that express low levels of IGF2. In IGF2-low tumors, other growth factors (FGF9, PDGFA) are more expressed than in IGF2-high tumors, suggesting that they play a compensatory role in tumor progression. In addition, IGF2 knock-down in H295R cells substantially impaired growth (>50% inhibition), blocked cells in G1 phase, and promoted apoptosis (>2-fold). Finally, analysis of the 11p15 locus showed a paternal uniparental disomy in both IGF2-high and IGF2-low tumors, but low IGF2 expression could be explained in most IGF2-low ACC by an additional epigenetic modification at the 11p15 locus. Altogether, these observations confirm the active role of IGF2 in adrenocortical tumor growth, but also suggest that other growth promoting pathways may be involved in a subset of ACC with low IGF2 expression, which creates opportunities for the use of other targeted therapies.

Peripheral T-cell lymphoma, not otherwise specified is a heterogeneous group of aggressive neoplasms with indistinct borders. By gene expression profiling we previously reported unsupervised clusters of peripheral T-cell lymphomas, not otherwise specified correlating with CD30 expression. In this work we extended the analysis of peripheral T-cell lymphoma molecular profiles to prototypical CD30+ peripheral T-cell lymphomas (anaplastic large cell lymphomas), and validated mRNA expression profiles at the protein level. Existing transcriptomic datasets from peripheral T-cell lymphomas, not otherwise specified and anaplastic large cell lymphomas were reanalyzed. Twenty-one markers were selected for immunohistochemical validation on 80 peripheral T-cell lymphoma samples (not otherwise specified, CD30+ and CD30−; anaplastic large cell lymphomas, ALK+ and ALK−), and differences between subgroups were assessed. Clinical follow-up was recorded. Compared to CD30− tumors, CD30+ peripheral T-cell lymphomas, not otherwise specified were significantly enriched in ALK− anaplastic large cell lymphoma-related genes. By immunohistochemistry, CD30+ peripheral T-cell lymphomas, not otherwise specified differed significantly from CD30− samples [down-regulated expression of T-cell receptor-associated proximal tyrosine kinases (Lck, Fyn, Itk) and of proteins involved in T-cell differentiation/activation (CD69, ICOS, CD52, NFATc2); upregulation of JunB and MUM1], while overlapping with anaplastic large cell lymphomas. CD30− peripheral T-cell lymphomas, not otherwise specified tended to have an inferior clinical outcome compared to the CD30+ subgroups. In conclusion, we show molecular and phenotypic features common to CD30+ peripheral T-cell lymphomas, and significant differences between CD30− and CD30+ peripheral T-cell lymphomas, not otherwise specified, suggesting that CD30 expression might delineate two biologically distinct subgroups.

BackgroundColon cancer (CC) pathological staging fails to accurately predict recurrence, and to date, no gene expression signature has proven reliable for prognosis stratification in clinical practice, perhaps because CC is a heterogeneous disease. The aim of this study was to establish a comprehensive molecular classification of CC based on mRNA expression profile analyses.Methods and findingsFresh-frozen primary tumor samples from a large multicenter cohort of 750 patients with stage I to IV CC who underwent surgery between 1987 and 2007 in seven centers were characterized for common DNA alterations, including BRAF, KRAS, and TP53 mutations, CpG island methylator phenotype, mismatch repair status, and chromosomal instability status, and were screened with whole genome and transcriptome arrays. 566 samples fulfilled RNA quality requirements. Unsupervised consensus hierarchical clustering applied to gene expression data from a discovery subset of 443 CC samples identified six molecular subtypes. These subtypes were associated with distinct clinicopathological characteristics, molecular alterations, specific enrichments of supervised gene expression signatures (stem cell phenotype-like, normal-like, serrated CC phenotype-like), and deregulated signaling pathways. Based on their main biological characteristics, we distinguished a deficient mismatch repair subtype, a KRAS mutant subtype, a cancer stem cell subtype, and three chromosomal instability subtypes, including one associated with down-regulated immune pathways, one with up-regulation of the Wnt pathway, and one displaying a normal-like gene expression profile. The classification was validated in the remaining 123 samples plus an independent set of 1,058 CC samples, including eight public datasets. Furthermore, prognosis was analyzed in the subset of stage II-III CC samples. The subtypes C4 and C6, but not the subtypes C1, C2, C3, and C5, were independently associated with shorter relapse-free survival, even after adjusting for age, sex, stage, and the emerging prognostic classifier Oncotype DX Colon Cancer Assay recurrence score (hazard ratio 1.5, 95% CI 1.1-2.1, p = 0.0097). However, a limitation of this study is that information on tumor grade and number of nodes examined was not available.ConclusionsWe describe the first, to our knowledge, robust transcriptome-based classification of CC that improves the current disease stratification based on clinicopathological variables and common DNA markers. The biological relevance of these subtypes is illustrated by significant differences in prognosis. This analysis provides possibilities for improving prognostic models and therapeutic strategies. In conclusion, we report a new classification of CC into six molecular subtypes that arise through distinct biological pathways.

Dense genotype data can be used to detect chromosome fragments inherited from a common ancestor in apparently unrelated individuals. A disease-causing mutation inherited from a common founder may thus be detected by searching for a common haplotype signature in a sample population of patients. We present here FounderTracker, a computational method for the genome-wide detection of founder mutations in cancer using dense tumor SNP profiles. Our method is based on two assumptions. First, the wild-type allele frequently undergoes loss of heterozygosity (LOH) in the tumors of germline mutation carriers. Second, the overlap between the ancestral chromosome fragments inherited from a common founder will define a minimal haplotype conserved in each patient carrying the founder mutation. Our approach thus relies on the detection of haplotypes with significant identity by descent (IBD) sharing within recurrent regions of LOH to highlight genomic loci likely to harbor a founder mutation. We validated this approach by analyzing two real cancer data sets in which we successfully identified founder mutations of well-characterized tumor suppressor genes. We then used simulated data to evaluate the ability of our method to detect IBD tracts as a function of their size and frequency. We show that FounderTracker can detect haplotypes of low prevalence with high power and specificity, significantly outperforming existing methods. FounderTracker is thus a powerful tool for discovering unknown founder mutations that may explain part of the "missing" heritability in cancer. This method is freely available and can be used online at the FounderTracker website.

IntroductionGermline BRCA1 or BRCA2 mutations account for 20-30% of familial clustering of breast cancer. The main indication for BRCA2 screening is currently the family history but the yield of mutations identified in patients selected this way is low.MethodsTo develop more efficient approaches to screening we have compared the gene expression and genomic profiles of BRCA2-mutant breast tumors with those of breast tumors lacking BRCA1 or BRCA2 mutations.ResultsWe identified a group of 66 genes showing differential expression in our training set of 7 BRCA2-mutant tumors and in an independent validation set of 19 BRCA2-mutant tumors. The differentially expressed genes include a prominent cluster of genes from chromosomes 13 and 14 whose expression is reduced. Gene set enrichment analysis confirmed that genes in specific bands on 13q and 14q showed significantly reduced expression, suggesting that the affected bands may be preferentially deleted in BRCA2-mutant tumors. Genomic profiling showed that the BRCA2-mutant tumors indeed harbor deletions on chromosomes 13q and 14q. To exploit this information we have created a simple fluorescence in situ hybridization (FISH) test and shown that it detects tumors with deletions on chromosomes 13q and 14q.ConclusionTogether with previous reports, this establishes that deletions on chromosomes 13q and 14q are a hallmark of BRCA2-mutant tumors. We propose that FISH to detect these deletions would be an efficient and cost-effective first screening step to identify potential BRCA2-mutation carriers among breast cancer patients without a family history of breast cancer.

The Warburg effect describes how cancer cells down-regulate their aerobic respiration and preferentially use glycolysis to generate energy. To evaluate the link between hypoxia and Warburg effect, we studied mitochondrial electron transport, angiogenesis and glycolysis in pheochromocytomas induced by germ-line mutations in VHL, RET, NF1 and SDH genes. SDH and VHL gene mutations have been shown to lead to the activation of hypoxic response, even in normoxic conditions, a process now referred to as pseudohypoxia. We observed a decrease in electron transport protein expression and activity, associated with increased angiogenesis in SDH- and VHL-related, pseudohypoxic tumors, while stimulation of glycolysis was solely observed in VHL tumors. Moreover, microarray analyses revealed that expression of genes involved in these metabolic pathways is an efficient tool for classification of pheochromocytomas in accordance with the predisposition gene mutated. Our data suggest an unexpected association between pseudohypoxia and loss of p53, which leads to a distinct Warburg effect in VHL-related pheochromocytomas.

BackgroundIn breast cancers, only a minority of patients fully benefit from the different chemotherapy regimens currently in use. Identification of markers that could predict the response to a particular regimen would thus be critically important for patient care. In cell lines or animal models, tumor protein p53 (TP53) plays a critical role in modulating the response to genotoxic drugs. TP53 is activated in response to DNA damage and triggers either apoptosis or cell-cycle arrest, which have opposite effects on cell fate. Yet, studies linking TP53 status and chemotherapy response have so far failed to unambiguously establish this paradigm in patients. Breast cancers with a TP53 mutation were repeatedly shown to have a poor outcome, but whether this reflects poor response to treatment or greater intrinsic aggressiveness of the tumor is unknown.Methods and findingsIn this study we analyzed 80 noninflammatory breast cancers treated by frontline (neoadjuvant) chemotherapy. Tumor diagnoses were performed on pretreatment biopsies, and the patients then received six cycles of a dose-dense regimen of 75 mg/m(2) epirubicin and 1,200 mg/m(2) cyclophosphamide, given every 14 days. After completion of chemotherapy, all patients underwent mastectomies, thus allowing for a reliable assessment of chemotherapy response. The pretreatment biopsy samples were used to determine the TP53 status through a highly efficient yeast functional assay and to perform RNA profiling. All 15 complete responses occurred among the 28 TP53-mutant tumors. Furthermore, among the TP53-mutant tumors, nine out of ten of the highly aggressive basal subtypes (defined by basal cytokeratin [KRT] immunohistochemical staining) experienced complete pathological responses, and only TP53 status and basal subtype were independent predictors of a complete response. Expression analysis identified many mutant TP53-associated genes, including CDC20, TTK, CDKN2A, and the stem cell gene PROM1, but failed to identify a transcriptional profile associated with complete responses among TP53 mutant tumors. In patients with unresponsive tumors, mutant TP53 status predicted significantly shorter overall survival. The 15 patients with responsive TP53-mutant tumors, however, had a favorable outcome, suggesting that this chemotherapy regimen can overcome the poor prognosis generally associated with mutant TP53 status.ConclusionsThis study demonstrates that, in noninflammatory breast cancers, TP53 status is a key predictive factor for response to this dose-dense epirubicin-cyclophosphamide regimen and further suggests that the basal subtype is exquisitely sensitive to this association. Given the well-established predictive value of complete responses for long-term survival and the poor prognosis of basal and TP53-mutant tumors treated with other regimens, this chemotherapy could be particularly suited for breast cancer patients with a mutant TP53, particularly those with basal features.

BackgroundMuscle-invasive bladder cancer (MIBC) and upper urinary tract urothelial carcinoma (UTUC) are molecularly heterogeneous. Despite chemotherapies, immunotherapies, or anti-fibroblast growth factor receptor (FGFR) treatments, these tumors are still of a poor outcome. Our objective was to develop a bank of patient-derived xenografts (PDXs) recapitulating the molecular heterogeneity of MIBC and UTUC, to facilitate the preclinical identification of therapies.MethodsFresh tumors were obtained from patients and subcutaneously engrafted into immune-compromised mice. Patient tumors and matched PDXs were compared regarding histopathology, transcriptomic (microarrays), and genomic profiles [targeted Next-Generation Sequencing (NGS)]. Several PDXs were treated with chemotherapy (cisplatin/gemcitabine) or targeted therapies [FGFR and epidermal growth factor (EGFR) inhibitors].ResultsA total of 31 PDXs were established from 1 non-MIBC, 25 MIBC, and 5 upper urinary tract tumors, including 28 urothelial (UC) and 3 squamous cell carcinomas (SCCs). Integrated genomic and transcriptomic profiling identified the PDXs of three different consensus molecular subtypes [basal/squamous (Ba/Sq), luminal papillary, and luminal unstable] and included FGFR3-mutated PDXs. High histological and genomic concordance was found between matched patient tumor/PDX. Discordance in molecular subtypes, such as a Ba/Sq patient tumor giving rise to a luminal papillary PDX, was observed (n=5) at molecular and histological levels. Ten models were treated with cisplatin-based chemotherapy, and we did not observe any association between subtypes and the response. Of the three Ba/Sq models treated with anti-EGFR therapy, two models were sensitive, and one model, of the sarcomatoid variant, was resistant. The treatment of three FGFR3-mutant PDXs with combined FGFR/EGFR inhibitors was more efficient than anti-FGFR3 treatment alone.ConclusionsWe developed preclinical PDX models that recapitulate the molecular heterogeneity of MIBCs and UTUC, including actionable mutations, which will represent an essential tool in therapy development. The pharmacological characterization of the PDXs suggested that the upper urinary tract and MIBCs, not only UC but also SCC, with similar molecular characteristics could benefit from the same treatments including anti-FGFR for FGFR3-mutated tumors and anti-EGFR for basal ones and showed a benefit for combined FGFR/EGFR inhibition in FGFR3-mutant PDXs, compared to FGFR inhibition alone.

Background: Comprehensive transcriptomic analyses have shown that colorectal cancer (CRC) is heterogeneous and have led to the definition of molecular subtypes among which the stem-cell, mesenchymal-like group is associated with poor prognosis. The molecular pathways orchestrating the emergence of this subtype are incompletely understood. In line with the contribution of the cellular prion protein PrPC to stemness, we hypothesize that deregulation of this protein could lead to a stem-cell, mesenchymal-like phenotype in CRC. Methods: We assessed the distribution of the PrPC-encoding PRNP mRNA in two large CRC cohorts according to molecular classification and its association with patient survival. We developed cell-based assays to explore the impact of gain and loss of PrPC function on markers of the mesenchymal subtype and to delineate the signalling pathways recruited by PrPC. We measured soluble PrPC in the plasmas of 325 patients with metastatic CRC and probed associations with disease outcome. Findings: We found that PRNP gene expression is enriched in tumours of the mesenchymal subtype and is associated with poor survival. Our in vitro analyses revealed that PrPC controls the expression of genes that specify the mesenchymal subtype through the recruitment of the Hippo pathway effectors YAP and TAZ and the TGFß pathway. We showed that plasma levels of PrPC are elevated in metastatic CRC and are associated with poor disease control. Interpretation: Our findings define PrPC as a candidate driver of the poor-prognosis mesenchymal subtype of CRC. They suggest that PrPC may serve as a potential biomarker for patient stratification in CRC. Funding: Grant support was provided by the following: Cancéropôle Ile de France (grant number 2016-1-EMERG-36-UP 5-1), Association pour la Recherche sur le Cancer (grant number PJA 20171206220), SATT Ile de France Innov (grant number 415) as well as INSERM. Keywords: Colorectal cancer, Molecular classification, Prion protein, Hippo pathway, TGFß pathway

The CMS4 mesenchymal subtype of colorectal cancer (CRC) is associated with poor prognosis and resistance to treatment. The cellular prion protein PrPC is overexpressed in CMS4 tumors and controls the expression of a panel of CMS4-specific genes in CRC cell lines. Here, we sought to investigate PrPC downstream pathways that may underlie its role in CMS4 CRC. By combining gene set enrichment analyses and gain and loss of function approaches in CRC cell lines, we identify the integrin-linked kinase ILK as a proximal effector of PrPC that mediates its control on the CMS4 phenotype. We further leveraged three independent large CRC cohorts to assess correlations in gene expression pattern with patient outcomes and found that ILK is overexpressed in CMS4 mesenchymal tumors and confers a poor prognosis, especially when combined with high expression of the PrPC encoding gene PRNP. Of note, we discovered that the PrPC-ILK signaling axis controls the expression and activity of the tryptophan metabolizing enzyme indoleamine 2,3 dioxygenase IDO1, a key player in immune tolerance. In addition, we monitored alterations in the levels of tryptophan and its metabolites of the kynurenine pathway in the plasma of metastatic CRC patients (n = 325) and we highlight their prognostic value in combination with plasma PrPC levels. Thus, the PrPC-ILK-IDO1 axis plays a key role in the mesenchymal subtype of CRC. PrPC and IDO1-targeted strategies may represent new avenues for patient stratification and treatment in CRC.

The chromosome translocations generating PAX3-FOXO1 and PAX7-FOXO1 chimeric proteins are the primary hallmarks of the paediatric fusion-positive alveolar subtype of Rhabdomyosarcoma (FP-RMS). Despite the ability of these transcription factors to remodel chromatin landscapes and promote the expression of tumour driver genes, they only inefficiently promote malignant transformation in vivo. The reason for this is unclear. To address this, we developed an in ovo model to follow the response of spinal cord progenitors to PAX-FOXO1s. Our data demonstrate that PAX-FOXO1s, but not wild-type PAX3 or PAX7, trigger the trans-differentiation of neural cells into FP-RMS-like cells with myogenic characteristics. In parallel, PAX-FOXO1s remodel the neural pseudo-stratified epithelium into a cohesive mesenchyme capable of tissue invasion. Surprisingly, expression of PAX-FOXO1s, similar to wild-type PAX3/7, reduce the levels of CDK-CYCLIN activity and increase the fraction of cells in G1. Introduction of CYCLIN D1 or MYCN overcomes this PAX-FOXO1-mediated cell cycle inhibition and promotes tumour growth. Together, our findings reveal a mechanism that can explain the apparent limited oncogenicity of PAX-FOXO1 fusion transcription factors. They are also consistent with certain clinical reports indicative of a neural origin of FP-RMS.

The molecular nature of large-cell neuroendocrine lung carcinomas (LCNEC) has remained unclear. Here, the authors show LCNECs represent a distinct transcriptional subgroup among lung cancers and comprise two molecular subgroups, type I (TP53 and STK11/KEAP1 alterations) and type II (TP53 and RB1 inactivation).

Abstract Muscle‐invasive forms of urothelial carcinomas are responsible for most mortality in bladder cancer. Finding new treatments for invasive bladder tumours requires adequate animal models to decipher the mechanisms of progression, in particular the way tumours interact with their microenvironment. Herein, using the murine bladder tumour cell line MB49 and its more aggressive variant MB49‐I, we demonstrate that the adaptive immune system efficiently limits progression of MB49, whereas MB49‐I has lost tumour antigens and is insensitive to adaptive immune responses. Furthermore, we unravel a parallel mechanism developed by MB49‐I to subvert its environment: de novo secretion of the proteoglycan decorin. We show that decorin overexpression in the MB49/MB49‐I model is required for efficient progression, by promoting angiogenesis and tumour cell invasiveness. Finally, we show that these results are relevant to muscle‐invasive human bladder carcinomas, which overexpress decorin together with angiogenesis‐ and adhesion/migration‐related genes, and that decorin overexpression in the human bladder carcinoma cell line TCCSUP is required for efficient invasiveness in vitro. We thus propose decorin as a new therapeutic target for these aggressive tumours.

Sporadic early onset colorectal carcinoma (EOCRC) which has by definition no identified hereditary predisposition is a growing problem that remains poorly understood. Molecular analysis could improve identification of distinct sub-types of colorectal cancers (CRC) with therapeutic implications and thus can help establish that sporadic EOCRC is a distinct entity. From 954 patients resected for CRC at our institution, 98 patients were selected. Patients aged 45-60 years were excluded to help define "young" and "old" groups. Thirty-nine cases of sporadic EOCRC (patients ≤ 45 years with microsatellite stable tumors) were compared to both microsatellite stable tumors from older patients (36 cases, patients>60 years) and to groups of patients with microsatellite instability. Each group was tested for TP53, KRAS, BRAF, PIK3CA mutations and the presence of a methylator phenotype. Gene expression profiles were also used for pathway analysis. Compared to microsatellite stable CRC from old patients, sporadic EOCRC were characterized by distal location, frequent synchronous metastases and infrequent synchronous adenomas but did not have specific morphological characteristics. A familial history of CRC was more common in sporadic EOCRC patients despite a lack of identified hereditary conditions (p = 0.013). Genetic studies also showed the absence of BRAF mutations (p = 0.022) and the methylator phenotype (p = 0.005) in sporadic EOCRC compared to older patients. Gene expression analysis implicated key pathways such as Wnt/beta catenin, MAP Kinase, growth factor signaling (EGFR, HGF, PDGF) and the TNFR1 pathway in sporadic EOCRC. Wnt/beta catenin signaling activation was confirmed by aberrant nuclear beta catenin immunostaining (p = 0.01). This study strongly suggests that sporadic EOCRC is a distinct clinico-molecular entity presenting as a distal and aggressive disease associated with chromosome instability. Furthermore, several signaling pathways including the TNFR1 pathway have been identified as potential biomarkers for both the diagnosis and treatment of this disease.

Angioimmunoblastic T-cell Lymphoma (AITL) is one of the most frequent T-cell lymphoma entities. Follicular helper T lymphocytes (TFH) are recognized as the normal cellular counterpart of the neoplastic component. Despite a clonal T-cell feature and few described recurrent cytogenetic abnormalities, a driving oncogenic event has not been identified so far. It has been recently reported that in mice, heterozygous inactivation of Roquin/Rc3h1, a RING type E3 ubiquitine ligase, recapitulates many of the clinical, histological, and cellular features associated with human AITL. In this study we explored whether ROQUIN alterations could be an initial event in the human AITL oncogenic process. Using microarray and RT-PCR analyses, we investigated the levels of ROQUIN transcripts in TFH tumor cells purified from AITL (n = 8) and reactive tonsils (n = 12) and found similar levels of ROQUIN expression in both. Moreover, we also demonstrated that ROQUIN protein was expressed by AITL TFH (PD1+) cells. We then analysed ROQUIN coding sequence in 12 tumor cell-rich AITL samples and found no mutation in any of the samples. Finally, we analysed the expression of MiR101, a putative partner of ROQUIN involved in the modulation of ICOS expression and found similar levels of expression in tumor and reactive TFH. Altogether, this study shows that neither alteration of ROQUIN gene nor deregulation of miR101 expression is likely to be a frequent recurrent event in AITL.

High-throughput post-genomic studies are now routinely and promisingly investigated in biological and biomedical research. The main statistical approach to select genes differentially expressed between two groups is to apply a t-test, which is subject of criticism in the literature. Numerous alternatives have been developed based on different and innovative variance modeling strategies. However, a critical issue is that selecting a different test usually leads to a different gene list. In this context and given the current tendency to apply the t-test, identifying the most efficient approach in practice remains crucial. To provide elements to answer, we conduct a comparison of eight tests representative of variance modeling strategies in gene expression data: Welch's t-test, ANOVA [1], Wilcoxon's test, SAM [2], RVM [3], limma [4], VarMixt [5] and SMVar [6]. Our comparison process relies on four steps (gene list analysis, simulations, spike-in data and re-sampling) to formulate comprehensive and robust conclusions about test performance, in terms of statistical power, false-positive rate, execution time and ease of use. Our results raise concerns about the ability of some methods to control the expected number of false positives at a desirable level. Besides, two tests (limma and VarMixt) show significant improvement compared to the t-test, in particular to deal with small sample sizes. In addition limma presents several practical advantages, so we advocate its application to analyze gene expression data.