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Primary central nervous system lymphoma (PCNSL) is a rare and distinct entity within diffuse large B-cell lymphoma presenting with variable response rates probably to underlying molecular heterogeneity.To identify and characterize PCNSL heterogeneity and facilitate clinical translation, we carried out a comprehensive multi-omic analysis [whole-exome sequencing, RNA sequencing (RNA-seq), methylation sequencing, and clinical features] in a discovery cohort of 147 fresh-frozen (FF) immunocompetent PCNSLs and a validation cohort of formalin-fixed, paraffin-embedded (FFPE) 93 PCNSLs with RNA-seq and clinico-radiological data.Consensus clustering of multi-omic data uncovered concordant classification of four robust, non-overlapping, prognostically significant clusters (CS). The CS1 and CS2 groups presented an immune-cold hypermethylated profile but a distinct clinical behavior. The 'immune-hot' CS4 group, enriched with mutations increasing the Janus kinase (JAK)-signal transducer and activator of transcription (STAT) and nuclear factor-κB activity, had the most favorable clinical outcome, while the heterogeneous-immune CS3 group had the worse prognosis probably due to its association with meningeal infiltration and enriched HIST1H1E mutations. CS1 was characterized by high Polycomb repressive complex 2 activity and CDKN2A/B loss leading to higher proliferation activity. Integrated analysis on proposed targets suggests potential use of immune checkpoint inhibitors/JAK1 inhibitors for CS4, cyclin D-Cdk4,6 plus phosphoinositide 3-kinase (PI3K) inhibitors for CS1, lenalidomide/demethylating drugs for CS2, and enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) inhibitors for CS3. We developed an algorithm to identify the PCNSL subtypes using RNA-seq data from either FFPE or FF tissue.The integration of genome-wide data from multi-omic data revealed four molecular patterns in PCNSL with a distinctive prognostic impact that provides a basis for future clinical stratification and subtype-based targeted interventions.

In our study the Bladder Cancer Molecular Taxonomy Group collaborated to extend a first consensus report, addressing the need for a consensus molecular classification for muscle-invasive bladder cancer (MIBC) that would support basic research and clinical trials. We provide such a consensus classification and offer a single-sample classifier (http://cit.ligue-cancer.net:3838/apps/consensusMIBC_web).

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.

Background Clear-cell renal-cell carcinoma (ccRCC) is characterized by loss of a functional Von Hippel–Lindau (VHL) protein. We investigated the potential of 3 single nucleotide polymorphisms (SNPs) in VHL as biomarkers in metastatic ccRCC (m-ccRCC) patients treated with vascular endothelial growth factor receptor (VEGFR) tyrosine kinase inhibitors (TKIs). Patients and Methods We genotyped 3 VHL SNPs in 199 m-ccRCC patients: rs1642742 T > C, rs1642743 A > G, and rs1678607 C > A. Primary end points were response rate (RR), progression-free survival (PFS), and overall survival (OS) after start of first-line TKI. RR was compared with Fisher’s exact test, and PFS and OS with Kaplan-Meier analysis and multivariable Cox regression. Secondary end points were association with VHL promotor hypermethylation, VHL mutation status, VHL loss of heterozygosity, ≥ 25% sarcomatoid dedifferentiation, and expression of genes implicated in angiogenesis and immunoresponse (Fisher’s exact test and unpaired t tests). Results The minor alleles of rs1642742 and rs1642743, known to be in close linkage disequilibrium, were associated with poor outcome, following a recessive pattern. For the rs1642742 CC versus TT/TC genotype, OS was 11 versus 26 months (hazard ratio = 2.3; 95% confidence interval, 1.2-6.6; P = .015). For the rs1642743 GG versus AA/AG genotype, OS was 15 versus 28 months (hazard ratio = 2.6; 95% confidence interval, 1.4-5.0; P = .004). After multivariable analysis, both remained linked with poor OS (P = .018 and P = .009, respectively). There was a trend toward shorter PFS and poorer RR. Both SNPs were associated with ≥ 25% sarcomatoid dedifferentiation (P = .037 and .006, respectively). No significant results were found for rs1678607. Conclusion rs1642742 and rs1642743 are candidate biomarkers for poor OS in m-ccRCC patients receiving first-line VEGFR-TKI. They are associated with higher levels of sarcomatoid dedifferentiation.

International audience; Background: We previously described 4 molecular subtypes of metastatic clear cell renal cell carcinoma (mccRCC), named ccrcc1-4 (Beuselinck et al, 2015). These have both prognostic and predictive value for patients treated with first-line sunitinib, with distinctive objective response rate (ORR), progression-free survival (PFS), and overall survival (OS). The ccrcc2 and ccrcc3 tumors have the best outcomes, followed by ccrcc1 and then ccrcc4. We hypothesized that these molecular subtypes would show similar outcomes with first-line pazopanib treatment.Patients and methods: We classified 28 mccRCC tumors treated with pazopanib as first-line therapy, as described previously. The primary endpoints were PFS and OS from the start of pazopanib. A secondary endpoint was ORR. Because there were only 2 ccrcc3 tumors, they were pooled with the ccrcc2 tumors for outcome analysis.Results: PFS was 9 months for the ccrcc2 and ccrcc3 tumors, 5 months for ccrcc1 tumors, and 3 months for the ccrcc4 tumors (P = .011). The corresponding OS duration was 69, 19, and 5 months (P = .003). The corresponding ORR was 50%, 33%, and 0%. The corresponding mean tumor size decreased by 34%, 6%, and 2% (P = .032). The ccrcc1-4 classification was a stronger predictor of outcome than the International Metastatic Renal Cell Carcinoma Database Consortium score on univariate analysis (P = .011 vs. P = .094 for PFS and P = .003 vs. .013 for OS). Both remained independent on bivariate analysis.Conclusion: The molecular subtypes of mccRCC are associated with outcome on pazopanib as first-line therapy. The prognostic and predictive value of the ccrcc1-4 molecular classification requires validation in prospective trials.

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)., Graphical abstract

Background Tumor pathologists classify tumors according to cell-level and tissue-level criteria, using molecular markers in addition to morphological patterns, as reported in WHO tumor classifications. Their work describes to some extent both inter-tumor and intra-tumor heterogeneity, but it is a tedious task with potential reproducibility issues. The molecular subtyping of tumors represents a sometimes parallel and sometimes convergent effort to describe the heterogeneity of tumors. It is automated, which attenuates the limitations of pathological scoring mentioned above, but so far it is poorly adapted to describe intra-tumor heterogeneity. Methods We propose a novel method, WISP (Weighted In Silico Pathology), which finely measures intra-tumor heterogeneity by automatically estimating the proportions of cell types present in a bulk tumor sample, these cell types being predefined based on histological or high-throughput molecular criterions. Results We illustrate the relevance of our approach in several tumor types including lung cancer, glioblastoma and pancreatic cancer. We show that the cell types that describe tumors for a given cancer type can fairly well recapitulate existing molecular classifications and are very consistent with an independent pathological scoring. We show that our method offers a more standardized and finer-grained solution for describing tumor heterogeneity than either pathological scoring or molecular subtyping. More importantly, we show that the proportion of certain cell types is strongly associated to prognosis and drug response. Conclusions This study provides a framework for standardized molecular pathology and fully reshapes the way in which we think about pathology or molecular subtyping. We believe that our results are a proof of concept demonstrating the importance of considering cell types intra-tumor proportions for personalized clinical care. Legal entity responsible for the study The authors. Funding CIT Program - Ligue Contre le Cancer. Disclosure All authors have declared no conflicts of interest.

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. This work is part of the “Cartes d’Identité des Tumeurs” (CIT) program funded and developed by the “Ligue Nationale contre le Cancer” (LNCC) (http://cit.ligue-cancer.net). We thank E. Voirin, N. Servant, G. Lucotte, and P. Hupé for their help with bioinformatics data management and analysis. We thank members of the bladder cancer CIT consortium (P. Maillé and D. Vordos, Henri Mondor Hospital; M. Sibony, Cochin Hospital; A. Laplanche, IGR, INSERM; Y. Denoux and V. Molinié, Foch Hospital; E. Letouzé, LNCC) for their constant support. This work was supported by the LNCC (to “Oncologie Moléculaire” and “Computational Systems Biology of Cancer” accredited teams), the Institut Curie (to F.R., E.B., A.Z.), the “Centre National de la Recherche Scientifique” (CNRS) (to F.R.), the “Institut National de la Santé et de la Recherche Médicale” (INSERM) (to E.B., A.Z., S.B., and Y.A.), the INCa (INCa_2960 and 4382 to F.R. and Y.A.), ITMO cancer, systems biology program (to A.Z., E.B., and F.R.), the Labex (no. ANR-10-LBX-0038) part of the IDEX PSL (no. ANR-10-IDEX-0001-02 PSL) (to F.R.), and York Against Cancer (to J.S.). A.B. was supported by a grant from the INCa, from the LNCC, and by NIH grant 5U24 CA143799-04 as part of TCGA project, Y.L. by a grant from the “Fondation Franco-Chinoise pour la Science et ses Applications” (FFCSA), Y.N. by a grant from the “Fondation ARC pour la recherche sur le cancer,” and A.K. by a grant from the LNCC

Background Soft tissue sarcomas (STS) form a group of rare cancers which accounts for around 1% of tumours. Although up to 15% of patients respond in immunotherapy trials, there are no biomarkers predicting response of STS to checkpoint blockade therapies yet. Methods We analysed transcriptomic data of 4 publicly available cohorts, accounting for more than 600 STS. We used MCP-counter, a deconvolution method to estimate the tumour microenvironment (TME) composition Based on MCP-counter estimates, we established a robust immune classificationof STS tumors into 5 Sarcoma Immune Classes, labelled A, B, C, D and E. These classes exhibited different type and extents of TME. We validated the profiles of these 5 groups on a 72-patients cohort using immunohistochemichal (IHC) stainings for CD3, CD8, CD20 and CD34. Results One group (A: 23.3% of tumours) exhibits a very low to low immune infiltrate for all TME cell types. Another class (C: 14.5% of all tumours) displays moderate immune infiltrate and a strong presence of endothelial cells. Finally, another group (E: 15.6%) is highly infiltrated by all immune cell types. The two remaining groups (B: 27.4% and D: 19.4%) are heterogeneous, respectively rather highly and lowly infiltrated. The immune high group E is associated with an overexpression of several immune checkpoint genes: PDCD1 (PD-1), CD274 (PD-L1), PDCD1LG2 (PD-L2), LAG3, HAVCR2 (TIM-3), CTLA4. On 72 patients, we showed that the immune-high group could be identified by the IHC-visible presence of tertiary lymphoid structures (TLS), defined as T cell aggregates juxtaposing B cell aggregates. The immune-high group also exhibited prolonged overall survival as compared with other groups. Using data from a phase II clinical trial with pembrolizumab, we show that responders can be identified as class E tumours, therefore allowing patient selection. Conclusions We have defined a novel immune-based classification of STS into 5 classes, among which an immune-high group characterized by a strong infiltration by all immune cell and expression of immune checkpoints, presence of TLS and longer overall survival. This class groups responders to PD-1 blockade in a phase II clinical trial. Legal entity responsible for the study INSERM. Funding Institut National de la Sante et de la Recherche Medicale, the University of Paris, Sorbonne University, the Programme Cartes d’Identite des Tumeurs (CIT) from the Ligue Nationale Contre le Cancer, Institut National du Cancer (HTE-INSERM plan cancer, C16082DS), Association pour la Recherche sur le Cancer (ARC), Cancer Research for Personalized Medecine programme, “FONCER contre le cancer” programme, Labex Immuno-Oncology, the National Institute of Health, Moon Shot program at MD Anderson Cancer Center, Ministry of Education and Ministry of Science and Technology of Taiwan, National Taiwan University, Merck, Inc, SARC, Sarcoma Foundation of America, and the QuadW Foundation. Disclosure T.W. Chen: Advisory / Consultancy, Research grant / Funding (self): Eisai; Advisory / Consultancy: Lilly. M.A. Burgess: Advisory / Consultancy: EMD Serono; Advisory / Consultancy: Immune Design; Advisory / Consultancy: Eisai. J. Wargo: Advisory / Consultancy: Merck; Advisory / Consultancy: BMS; Advisory / Consultancy: Novartis; Advisory / Consultancy: AstraZeneca; Advisory / Consultancy: Roche; Advisory / Consultancy: Genentech; Advisory / Consultancy: Illumina. H.A. Tawbi: Advisory / Consultancy, Research grant / Funding (self): BMS; Advisory / Consultancy, Research grant / Funding (self): Merck; Advisory / Consultancy, Research grant / Funding (self): Genentech; Research grant / Funding (self): Celgene; Research grant / Funding (self): GSK. W.H. Fridman: Advisory / Consultancy: MedImmune; Advisory / Consultancy: Novartis; Advisory / Consultancy: Servier; Advisory / Consultancy: Pierre Fabre. All other authors have declared no conflicts of interest.

Due to the phenotypic and molecular diversity of hepatocellular carcinomas (HCC), it is a challenge to determine a patient's prognosis. We aimed to identify new prognostic markers of patients with HCC treated by liver resection.We collected 314 HCC samples from patients at Bordeaux (1998-2007) and Créteil (2003-2007) hospitals in France. We analyzed the gene expression patterns of the tumors and compared expression patterns with patient survival times. Using the coefficient and regression formula of the multivariate Cox model, we identified a "5-gene score" associated with survival times. This molecular score was then validated in 2 groups of patients from Europe and the United States (n = 213) and China (n = 221).The 5-gene score, based on combined expression level of HN1, RAN, RAMP3, KRT19, and TAF9, was associated with disease-specific survival times of 189 patients with resected HCC in Bordeaux (hazard ratio = 3.5; 95% confidence interval: 1.9-6.6; P.0001). The association between the 5-gene score and disease-specific survival was validated in an independent cohort of 125 patients in Créteil (hazard ratio = 2.3; 95% confidence interval: 1.1-4.9; P.0001). The 5-gene score more accurately predicted patient outcomes than gene expression signatures reported previously. In multivariate analyses, the 5-gene score was associated with disease-specific survival, independent of other clinical and pathology feature of HCC. Disease-specific survival was also predicted by combining data on microvascular invasion, the Barcelona Clinic Liver Cancer classification system, and the 5-gene score in a nomogram. The prognostic accuracy of the 5-gene score was further validated in European and US patients with hepatitis C, cirrhosis, and HCC (overall survival P = .002) and in Asian patients with HCC with hepatitis B (overall survival, P = .02). Combining the 5-gene score with the expression pattern of 186 genes in corresponding cirrhotic tissues increased its prognostic accuracy.The molecular 5-gene score is associated with outcomes of patients with HCC treated by resection in different clinical settings worldwide. This new biomarker should be tested in clinical trials to stratify patients in therapeutic decisions.

SummaryParagangliomas are neuroendocrine tumors frequently associated with mutations in RET, NF1, VHL, and succinate dehydrogenase (SDHx) genes. Methylome analysis of a large paraganglioma cohort identified three stable clusters, associated with distinct clinical features and mutational status. SDHx-related tumors displayed a hypermethylator phenotype, associated with downregulation of key genes involved in neuroendocrine differentiation. Succinate accumulation in SDH-deficient mouse chromaffin cells led to DNA hypermethylation by inhibition of 2-OG-dependent histone and DNA demethylases and established a migratory phenotype reversed by decitabine treatment. Epigenetic silencing was particularly severe in SDHB-mutated tumors, potentially explaining their malignancy. Finally, inactivating FH mutations were identified in the only hypermethylated tumor without SDHx mutations. These findings emphasize the interplay between the Krebs cycle, epigenomic changes, and cancer.

Les lesions corticosurrenaliennes benignes regroupent un large eventail de maladies avec des morphologies ainsi que des secretions de steroides distinctes. Contrairement au corticosurrenalome, aucune vision globale moleculaire des alterations moleculaires n’est disponible pour ces tumeurs. Objectifs Fournir une classification moleculaire des tumeurs corticosurrenaliennes benignes, en utilisant une serie de mesures non biaisees pan-genomiques dans une cohorte incluant tous les types de tumeurs corticosurrenaliennes benignes. Methodes L’etude effectuee rapporte l’analyse pan-genomique incluant transcriptome, miRNome, methylome, mutations et alterations chromosomiques de 146 lesions adrenocorticales benignes. Resultats Le transcriptome, le methylome, le miRNome et le statut mutationnel convergent en une seule classification avec quatre groupes principaux : (i) les tumeurs productrices de cortisol, regroupant differents types partageant une activation commune de la voie AMPc/PKA par des mecanismes distincts. Le transcriptome a permis d’identifier une signature steroidogene ; (ii) des adenomes corticosurrenaliens (ACA) sans ou avec une secretion legere de cortisol, associes a des mutations de la beta-catenine ; (iii) des hyperplasies macronodulaires primaires avec des mutations ARMC5, montrant une signature d’expression ovarienne ; (iv) des ACA produisant de l’aldosterone, en dehors d’autres tumeurs benignes. Les alterations epigenetiques et la steroidogenese semblent associees, incluant l’hypomethylation des ilots CpG dans les tumeurs sans ou avec une secretion legere de cortisol, les profils des miARN definissant des groupes moleculaires specifiques, et la regulation directe de l’expression des enzymes steroidogenes par la methylation. Conclusion Cette premiere caracterisation pan-genomique a grande echelle des lesions corticosurrenaliennes benignes represente une nouvelle ressource importante pour l’etude de la tumorigenese corticosurrenalienne et de la steroidogenese.