Tertiary lymphoid structures generate and propagate anti-tumor antibody-producing plasma cells in renal cell cancer.

The presence of intratumoral tertiary lymphoid structures (TLS) is associated with positive clinical outcomes and responses to immunotherapy in cancer. Here, we used spatial transcriptomics to examine the nature of B cell responses within TLS in renal cell carcinoma (RCC). B cells were enriched in TLS, and therein, we could identify all B cell maturation stages toward plasma cell (PC) formation. B cell repertoire analysis revealed clonal diversification, selection, expansion in TLS, and the presence of fully mature clonotypes at distance. In TLS+ tumors, IgG- and IgA-producing PCs disseminated into the tumor beds along fibroblastic tracks. TLS+ tumors exhibited high frequencies of IgG-producing PCs and IgG-stained and apoptotic malignant cells, suggestive of anti-tumor effector activity. Therapeutic responses and progression-free survival correlated with IgG-stained tumor cells in RCC patients treated with immune checkpoint inhibitors. Thus, intratumoral TLS sustains B cell maturation and antibody production that is associated with response to immunotherapy, potentially via direct anti-tumor effects.

B cells are associated with survival and immunotherapy response in sarcoma.

Soft-tissue sarcomas represent a heterogeneous group of cancer, with more than 50 histological subtypes1,2. The clinical presentation of patients with different subtypes is often atypical, and responses to therapies such as immune checkpoint blockade vary widely3,4. To explain this clinical variability, here we study gene expression profiles in 608 tumours across subtypes of soft-tissue sarcoma. We establish an immune-based classification on the basis of the composition of the tumour microenvironment and identify five distinct phenotypes: immune-low (A and B), immune-high (D and E), and highly vascularized (C) groups. In situ analysis of an independent validation cohort shows that class E was characterized by the presence of tertiary lymphoid structures that contain T cells and follicular dendritic cells and are particularly rich in B cells. B cells are the strongest prognostic factor even in the context of high or low CD8+ T cells and cytotoxic contents. The class-E group demonstrated improved survival and a high response rate to PD1 blockade with pembrolizumab in a phase 2 clinical trial. Together, this work confirms the immune subtypes in patients with soft-tissue sarcoma, and unravels the potential of B-cell-rich tertiary lymphoid structures to guide clinical decision-making and treatments, which could have broader applications in other diseases.

Wnt, glucocorticoid and cellular prion protein cooperate to drive a mesenchymal phenotype with poor prognosis in colon cancer.

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-ß-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, ß-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.

Multilayer spectrum of intratumoral heterogeneity in basal bladder cancer.

Basal/squamous (Ba/Sq) subtype represents an intrinsic and robust group in the consensus molecular classification of muscle-invasive bladder cancer (MIBC), with poor outcome and controversial chemosensitivity. We aimed to investigate the spectrum of intratumor heterogeneity (ITH) in the Ba/Sq subtype. First, we validated a 29-gene NanoString CodeSet to predict the Ba/Sq subtype for FFPE samples. We identified heterogeneous Ba/Sq tumors in a series of 331 MIBC FFPE samples using dual GATA3/KRT5/6 immunohistochemistry (IHC). Heterogeneous regions with distinct immunostaining patterns were studied separately for gene expression using the 29-gene CodeSet, for mutations by targeted next-generation sequencing, and for copy number alteration (CNA) by microarray hybridization. Among 83 Ba/Sq tumors identified by GATA3/KRT5/6 dual staining, 19 tumors showed heterogeneity at the IHC level. In one third of the 19 cases, regions from the same tumor were classified in different distinct molecular subtypes. The mutational and CNA profiles confirmed the same clonal origin for IHC heterogeneous regions with possible subclonal evolution. Overall, two patterns of intratumoral heterogeneity (ITH) were observed in Ba/Sq tumors: low ITH (regions with distinct immunostaining, but common molecular subtype and shared CNA) or high ITH (regions with distinct immunostaining, molecular subtype, and CNA). These results showed multilayer heterogeneity in Ba/Sq MIBC. In view of personalized medicine, this heterogeneity adds complexity and should be taken into account for sampling procedures used for diagnosis and treatment choice. © 2021 The Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

The PAX-FOXO1s trigger fast trans-differentiation of chick embryonic neural cells into alveolar rhabdomyosarcoma with tissue invasive properties limited by S phase entry inhibition.

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.

Prognostic value of circulating tumour DNA in metastatic pancreatic cancer patients: post-hoc analyses of two clinical trials.

OBJECTIVE: The prognostication of metastatic pancreatic adenocarcinoma (mPDAC) patients remains uncertain, mainly based on carbohydrate antigen 19-9 (CA19-9), with limited utility. Circulating tumour DNA (ctDNA) has been suggested as a prognostic factor, but its added value has been poorly explored. The objective was to determine whether ctDNA is an independent factor for the prognostication of mPDAC. DESIGN: Translational study based on two prospective collections of plasma samples of mPDAC patients naïve for chemotherapy. One used as a test series and the other as validation series coming from two randomised trials (Prodige 35 and Prodige 37). CtDNA was assessed by digital droplet PCR targeting two methylated markers (HOXD8 and POU4F1) according to a newly developed and validated method. Univariate and multivariate analyses were performed according to ctDNA status. RESULTS: Of 372 plasma samples available, 354 patients were analyzed for survival. In the validation series, 145 of 255 patients were found ctDNA positive (56.8%), Median PFS and OS were 5.3 and 8.2 months in ctDNA-positive and 6.2 and 12.6 months in ctDNA-negative patients, respectively. ctDNA positivity was more often associated with young age, high CA19-9 level and neutrophils lymphocytes ratio. In multivariate analysis including these previous markers, ctDNA was confirmed as an independent prognostic marker for PFS (adjusted hazard ratio (HR) 1.5, CI 95% [1.03-2.18], p = 0.034) and OS (HR 1.62, CI 95% [1.05-2.5], p = 0.029). CONCLUSIONS: In this first ctDNA assessment in a large series of mPDAC derived from clinical trials, ctDNA was detectable in 56.8% of patients and confirmed as an independent prognostic marker.

Performance of Next-Generation Sequencing for the Detection of Microsatellite Instability in Colorectal Cancer With Deficient DNA Mismatch Repair.

BACKGROUND & AIMS: Next-generation sequencing (NGS) was recently approved by the United States Food and Drug Administration to detect microsatellite instability (MSI) arising from defective mismatch repair (dMMR) in patients with metastatic colorectal cancer (mCRC) before treatment with immune checkpoint inhibitors (ICI). In this study, we aimed to evaluate and improve the performance of NGS to identify MSI in CRC, especially dMMR mCRC treated with ICI. METHODS: CRC samples used in this post hoc study were reassessed centrally for MSI and dMMR status using the reference methods of pentaplex polymerase chain reaction and immunohistochemistry. Whole-exome sequencing (WES) was used to evaluate MSISensor, the Food and Drug Administration-approved and NGS-based method for assessment of MSI. This was performed in (1) a prospective, multicenter cohort of 102 patients with mCRC (C1; 25 dMMR/MSI, 24 treated with ICI) from clinical trials NCT02840604 and NCT033501260, (2) an independent retrospective, multicenter cohort of 113 patients (C2; 25 mCRC, 88 non-mCRC, all dMMR/MSI untreated with ICI), and (3) a publicly available series of 118 patients with CRC from The Cancer Genome Atlas (C3; 51 dMMR/MSI). A new NGS-based algorithm, namely MSICare, was developed. Its performance for assessment of MSI was compared with MSISensor in C1, C2, and C3 at the exome level or after downsampling sequencing data to the MSK-IMPACT gene panel. MSICare was validated in an additional retrospective, multicenter cohort (C4) of 152 patients with new CRC (137 dMMR/MSI) enriched in tumors deficient in MSH6 (n = 35) and PMS2 (n = 9) after targeted sequencing of samples with an optimized set of microsatellite markers (MSIDIAG). RESULTS: At the exome level, MSISensor was highly specific but failed to diagnose MSI in 16% of MSI/dMMR mCRC from C1 (4 of 25; sensitivity, 84%; 95% confidence interval [CI], 63.9%-95.5%), 32% of mCRC (8 of 25; sensitivity, 68%; 95% CI, 46.5%-85.1%), and 9.1% of non-mCRC from C2 (8 of 88; sensitivity, 90.9%; 95% CI, 82.9%-96%), and 9.8% of CRC from C3 (5 of 51; sensitivity, 90.2%; 95% CI, 78.6%-96.7%). Misdiagnosis included 4 mCRCs treated with ICI, of which 3 showed an overall response rate without progression at this date. At the exome level, reevaluation of the MSI genomic signal using MSICare detected 100% of cases with true MSI status among C1 and C2. Further validation of MSICare was obtained in CRC tumors from C3, with 96.1% concordance for MSI status. Whereas misdiagnosis with MSISensor even increased when analyzing downsampled WES data from C1 and C2 with microsatellite markers restricted to the MSK-IMPACT gene panel (sensitivity, 72.5%; 95% CI, 64.2%-79.7%), particularly in the MSH6-deficient setting, MSICare sensitivity and specificity remained optimal (100%). Similar results were obtained with MSICare after targeted NGS of tumors from C4 with the optimized microsatellite panel MSIDIAG (sensitivity, 99.3%; 95% CI, 96%-100%; specificity, 100%). CONCLUSIONS: In contrast to MSISensor, the new MSICare test we propose performs at least as efficiently as the reference method, MSI polymerase chain reaction, to detect MSI in CRC regardless of the defective MMR protein under both WES and targeted NGS conditions. We suggest MSICare may rapidly become a reference method for NGS-based testing of MSI in CRC, especially in mCRC, where accurate MSI status is required before the prescription of ICI.

Cancer stemness, intratumoral heterogeneity, and immune response across cancers.

Regulatory programs that control the function of stem cells are active in cancer and confer properties that promote progression and therapy resistance. However, the impact of a stem cell-like tumor phenotype ("stemness") on the immunological properties of cancer has not been systematically explored. Using gene-expression-based metrics, we evaluated the association of stemness with immune cell infiltration and genomic, transcriptomic, and clinical parameters across 21 solid cancers. We found pervasive negative associations between cancer stemness and anticancer immunity. This occurred despite high stemness cancers exhibiting increased mutation load, cancer-testis antigen expression, and intratumoral heterogeneity. Stemness was also strongly associated with cell-intrinsic suppression of endogenous retroviruses and type I IFN signaling, and increased expression of multiple therapeutically accessible immunosuppressive pathways. Thus, stemness is not only a fundamental process in cancer progression but may provide a mechanistic link between antigenicity, intratumoral heterogeneity, and immune suppression across cancers.

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 .

Identification of Four Immune Subtypes Characterized by Distinct Composition and Functions of Tumor Microenvironment in Intrahepatic Cholangiocarcinoma.

BACKGROUND AND AIMS: Intrahepatic cholangiocarcinoma (ICC) is a severe malignant tumor in which the standard therapies are mostly ineffective. The biological significance of the desmoplastic tumor microenvironment (TME) of ICC has been stressed but was insufficiently taken into account in the search for classifications of ICC adapted to clinical trial design. We investigated the heterogeneous tumor stroma composition and built a TME-based classification of ICC tumors that detects potentially targetable ICC subtypes. APPROACH AND RESULTS: We established the bulk gene expression profiles of 78 ICCs. Epithelial and stromal compartments of 23 ICCs were laser microdissected. We quantified 14 gene expression signatures of the TME and those of 3 functional indicators (liver activity, inflammation, immune resistance). The cell population abundances were quantified using the microenvironment cell population-counter package and compared with immunohistochemistry. We performed an unsupervised TME-based classification of 198 ICCs (training set) and 368 ICCs (validation set). We determined immune response and signaling features of the different immune subtypes by functional annotations. We showed that a set of 198 ICCs could be classified into 4 TME-based subtypes related to distinct immune escape mechanisms and patient outcomes. The validity of these immune subtypes was confirmed over an independent set of 368 ICCs and by immunohistochemical analysis of 64 ICC tissue samples. About 45% of ICCs displayed an immune desert phenotype. The other subtypes differed in nature (lymphoid, myeloid, mesenchymal) and abundance of tumor-infiltrating cells. The inflamed subtype (11%) presented a massive T lymphocyte infiltration, an activation of inflammatory and immune checkpoint pathways, and was associated with the longest patient survival. CONCLUSION: We showed the existence of an inflamed ICC subtype, which is potentially treatable with checkpoint blockade immunotherapy.

Assessing reproducibility of matrix factorization methods in independent transcriptomes.

MOTIVATION: Matrix factorization (MF) methods are widely used in order to reduce dimensionality of transcriptomic datasets to the action of few hidden factors (metagenes). MF algorithms have never been compared based on the between-datasets reproducibility of their outputs in similar independent datasets. Lack of this knowledge might have a crucial impact when generalizing the predictions made in a study to others. RESULTS: We systematically test widely used MF methods on several transcriptomic datasets collected from the same cancer type (14 colorectal, 8 breast and 4 ovarian cancer transcriptomic datasets). Inspired by concepts of evolutionary bioinformatics, we design a novel framework based on Reciprocally Best Hit (RBH) graphs in order to benchmark the MF methods for their ability to produce generalizable components. We show that a particular protocol of application of independent component analysis (ICA), accompanied by a stabilization procedure, leads to a significant increase in the between-datasets reproducibility. Moreover, we show that the signals detected through this method are systematically more interpretable than those of other standard methods. We developed a user-friendly tool for performing the Stabilized ICA-based RBH meta-analysis. We apply this methodology to the study of colorectal cancer (CRC) for which 14 independent transcriptomic datasets can be collected. The resulting RBH graph maps the landscape of interconnected factors associated to biological processes or to technological artifacts. These factors can be used as clinical biomarkers or robust and tumor-type specific transcriptomic signatures of tumoral cells or tumoral microenvironment. Their intensities in different samples shed light on the mechanistic basis of CRC molecular subtyping. AVAILABILITY AND IMPLEMENTATION: The RBH construction tool is available from http://goo.gl/DzpwYp. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Stratification of Pancreatic Ductal Adenocarcinomas Based on Tumor and Microenvironment Features.

BACKGROUND & AIMS: Genomic studies have revealed subtypes of pancreatic ductal adenocarcinoma (PDA) based on their molecular features, but different studies have reported different classification systems. It is a challenge to obtain high-quality, freshly frozen tissue for clinical analysis and determination of PDA subtypes. We aimed to redefine subtypes of PDA using a large number of formalin-fixed and paraffin-embedded PDA samples, which are more amenable to routine clinical evaluation. METHODS: We collected PDA samples from 309 consecutive patients who underwent surgery from September 1996 through December 2010 at 4 academic hospitals in Europe; nontumor tissue samples were not included. Samples were formalin fixed and paraffin embedded. DNA and RNA were isolated; gene expression, targeted DNA sequencing, and immunohistochemical analyses were performed. We used independent component analysis to deconvolute normal, tumor, and microenvironment transcriptome patterns in samples. We devised classification systems from an unsupervised analysis using a consensus clustering approach of our data set after removing normal contamination components. We associated subtypes with overall survival and disease-free survival of patients using Cox proportional hazards regression with estimation of hazard ratios and 95% confidence interval. We used The Cancer Genome Consortium and International Cancer Genome Consortium PDA data sets as validation cohorts. RESULTS: We validated the previously reported basal-like and classical tumor-specific subtypes of PDAs. We identified features of the PDA, including microenvironment gene expression patterns, that allowed tumors to be categorized into 5 subtypes, called pure basal like, stroma activated, desmoplastic, pure classical, and immune classical. These PDA subtypes have features of cancer cells and immune cells that could be targeted by pharmacologic agents. Tumor subtypes were associated with patient outcomes, based on analysis of our data set and the International Cancer Genome Consortium and The Cancer Genome Consortium PDA data sets. We also observed an exocrine signal associated with acinar cell contamination (from pancreatic tissue). CONCLUSIONS: We identified a classification system based on gene expression analysis of formalin-fixed PDA samples. We identified 5 PDA subtypes, based on features of cancer cells and the tumor microenvironment. This system might be used to select therapies and predict patient outcomes. We found evidence that the previously reported exocrine-like (called ADEX) tumor subtype resulted from contamination with pancreatic acinar cells. ArrayExpress accession number: E-MTAB-6134.

Machine Learning for Better Prognostic Stratification and Driver Gene Identification Using Somatic Copy Number Variations in Anaplastic Oligodendroglioma.

BACKGROUND: 1p/19q-codeleted anaplastic gliomas have variable clinical behavior. We have recently shown that the common 9p21.3 allelic loss is an independent prognostic factor in this tumor type. The aim of this study is to identify less frequent genomic copy number variations (CNVs) with clinical importance that may shed light on molecular oncogenesis of this tumor type. MATERIALS AND METHODS: A cohort of 197 patients with anaplastic oligodendroglioma was collected as part of the French POLA network. Clinical, pathological, and molecular information was recorded. CNV analysis was performed using single-nucleotide polymorphism arrays. Computational biology and feature selection based on the random forests method were used to identify CNV events associated with overall survival and other clinical-pathological variables. RESULTS: Recurrent chromosomal events were identified in chromosomes 4, 9, and 11. Forty-six focal amplification events and 22 focal deletion events were identified. Twenty-four focal CNV areas were associated with survival, and five of them were significantly associated with survival after multivariable analysis. Nine out of 24 CNV events were validated using an external cohort of The Cancer Genome Atlas. Five of the validated events contain a cancer-related gene or microRNA: CDKN2A deletion, SS18L1 amplification, RHOA/MIR191 copy-neutral loss of heterozygosity, FGFR3 amplification, and ARNT amplification. The CNV profile contributes to better survival prediction compared with clinical-based risk assessment. CONCLUSION: Several recurrent CNV events, detected in anaplastic oligodendroglioma, enable better survival prediction. More importantly, they help in identifying potential genes for understanding oncogenesis and for personalized therapy. IMPLICATIONS FOR PRACTICE: Genomic analysis of 197 anaplastic oligodendroglioma tumors reveals recurrent somatic copy number variation areas that may help in understanding oncogenesis and target identification for precision medicine. A machine learning multivariable model built using this genomic information enables better survival prediction.

Transcriptomic analysis of the tumor microenvironment to guide prognosis and immunotherapies.

Tumors are highly heterogeneous tissues where malignant cells are surrounded by and interact with a complex tumor microenvironment (TME), notably composed of a wide variety of immune cells, as well as vessels and fibroblasts. As the dialectical influence between tumor cells and their TME is known to be clinically crucial, we need tools that allow us to study the cellular composition of the microenvironment. In this focused research review, we report MCP-counter, a methodology based on transcriptomic markers that assesses the proportion of several immune and stromal cell populations in the TME from transcriptomic data, and we highlight how it can provide a way to decipher the complex mechanisms at play in tumors. In several malignancies, MCP-counter scores have been used to show various prognostic impacts of the TME, which we also show to be linked with the mutational burden of tumors. We also compared established molecular classifications of colorectal cancer and clear-cell renal cell carcinoma with the output of MCP-counter, and show that molecular subgroups have different TME profiles, and that these profiles are consistent within a given subgroup. Finally, we provide insights as to how knowing the TME composition may shape patient care in the near future.

How Bad Is the Hedgehog? GLI-Dependent, Hedgehog-Independent Cancers on the Importance of Biomarkers for Proper Patients Selection.

Hedgehog (HH) signaling plays an important role both during embryonic development and adult life. It is involved in the regulation of cell differentiation, cell proliferation and tissue polarity, as well as in the maintenance of stem cells, tissue repair, and regeneration (Briscoe and Therond, 2013; Jiang and Hui, 2008). Three ligands, Indian, Sonic, and Desert HH, can activate this pathway. Binding of HH ligands to their receptor, PTCH1 (Figure 1) lift its inhibition on SMO, resulting in activation and nuclear translocation of GLI transcription factors (Javelaud et al., 2012). The vertebrate GLI gene family is composed of three distinct genes GLI1, GLI2, and GLI3, encoding Krüppel-like transcription factors. GLI proteins exhibit distinct regulations, biochemical properties, and target genes. GLI3 acts as the main repressor of the pathway in the absence of HH ligands, whereas, in their presence, GLI2 is the main HH effector that drives the expression of GLI1 (Briscoe and Therond, 2013).

Pro-angiogenic gene expression is associated with better outcome on sunitinib in metastatic clear-cell renal cell carcinoma.

OBJECTIVES: Clear-cell renal cell carcinomas (ccRCC) are characterized by hyper-vascularization and can respond to vascular endothelial growth factor receptor (VEGFR) inhibitors such as sunitinib. We aimed to study the predictive value of the expression of genes in the hypoxia induced factor (HIF) - vascular endothelial growth factor (VEGF) - VEGFR-pro-angiogenic pathway in metastatic ccRCC (m-ccRCC) patients treated with sunitinib and the correlation between the expression of these genes and the molecular ccrcc-classification, the expression of genes involved in the immune-suppressive microenvironment and Von Hippel-Lindau (VHL) - and Polybromo-1 (PBRM1) - mutational status. MATERIAL AND METHODS: m-ccRCC patients treated with sunitinib as first-line targeted therapy were included. Gene expression was studied in the primary nephrectomy sample by qRT-PCR, VHL- and PBRM1-mutational status by sequencing. Response rate by RECIST, progression-free survival (PFS) and overall survival (OS) were study endpoints. RESULTS: One hundred and four patients were included. On multivariate-analysis, HIF2A-, platelet derived growth factor receptor beta (PDGFRB)-, VEGFC-, VEGFR1- and VEGFR2-expression were correlated with PFS and HIF1A-, HIF2A-, VEGFR1- and VEGFR2-expression with OS. VEGFR2-expression showed the strongest association with outcome, being significantly correlated with all outcome parameters. HIF2A, VEGFA, VEGFR1, VEGFR2 and VEGFR3 were highly expressed in the transcriptomic ccrcc2-subtype of tumors, known to be highly sensitive to sunitinib. In the total tumor series, there was no correlation nor inverse correlation between the expression of genes involved in angiogenesis and in the immune-suppressive microenvironment. In tumors with a bi-allelic PBRM1-inactivation, HIF2A-, VEGFA-, VEGFR1- and VEGFR2-expression were higher, compared to tumors with one or two functional PBRM1-alleles. CONCLUSIONS: Intratumoral expression of genes involved in the HIF-VEGF-VEGFR-pro-angiogenic pathway, especially VEGFR2, is associated with favorable outcome on sunitinib in m-ccRCCs. Several genes involved in this pathway are upregulated in the molecular ccrcc2-subgroup, which usually responds well to sunitinib.

Combined tumor genomic profiling and exome sequencing in a breast cancer family implicates ATM in tumorigenesis: A proof of principle study.

Familial breast cancers (BCs) account for 10%-20% of all diagnosed BCs, yet only 20% of such tumors arise in the context of a germline mutation in known tumor suppressor genes such as BRCA1 or BRCA2. The vast genetic heterogeneity which characterizes non BRCA1 and non BRCA2 (or BRCAx) families makes grouped studies impossible to perform. Next generation sequencing techniques, however, allow individual families to be studied to identify rare and or private mutations but the high number of genetic variants identified need to be sorted using pathogenicity or recurrence criteria. An additional sorting criterion may be represented by the identification of candidate regions defined by tumor genomic rearrangements. Indeed, comparative genomic hybridization (CGH) using single nucleotide polymorphism (SNP) arrays allows the detection of conserved ancestral haplotypes within recurrent regions of loss of heterozygosity, common to several familial tumors, which can highlight genomic loci harboring a germline mutation in cancer predisposition genes. The combination of both exome sequencing and SNP array-CGH for a series of familial BC revealed a germline ATM mutation associated with a loss of the wild-type allele in two BC from a BRCAx family. The analysis of additional breast tumors from ten BC families in which a germline ATM mutation had been identified revealed a high frequency of wild-type allele loss. This result argues strongly in favor of the involvement of ATM in these tumors as a tumor suppressor gene and confirms that germline ATM mutations are involved in a subset of familial BC.

Clearance of PML/RARA-bound promoters suffice to initiate APL differentiation.

PML/RARA, a potent transcriptional inhibitor of nuclear receptor signaling, represses myeloid differentiation genes and drives acute promyelocytic leukemia (APL). Association of the retinoid X receptor-α (RXRA) coreceptor to PML/RARA is required for transformation, with RXRA promoting its efficient DNA binding. APL is exquisitely sensitive to retinoic acid (RA) and arsenic trioxide (arsenic), which both trigger cell differentiation in vivo. Whereas RA elicits transcriptional activation of PML/RARA targets, how arsenic triggers differentiation remains unclear. Here we demonstrate that extinction of PML/RARA triggers terminal differentiation in vivo. Similarly, ablation of retinoid X receptors loosens PML/RARA DNA binding, inducing terminal differentiation of APL cells ex vivo or in vivo. RXRA sumoylation directly contributes to PML/RARA-dependent transformation ex vivo, presumably by enhancing transcriptional repression. Thus, APL differentiation is a default program triggered by clearance of PML/RARA-bound promoters, rather than obligatory active transcriptional activation, explaining how arsenic elicits APL maturation through PML/RARA degradation.

Transcriptional profiling of pure fibrolamellar hepatocellular carcinoma reveals an endocrine signature.

UNLABELLED: Fibrolamellar hepatocellular carcinoma (FLC) is a rare subtype of liver cancer occurring mostly in children and young adults. We have shown that FLC comprises two separate entities: pure (p-FLC) and mixed-FLC (m-FLC), differing in clinical presentation and course. We show that p-FLCs have a distinct gene expression signature different from that of m-FLCs, which have a signature similar to that of classical hepatocellular carcinomas. We found p-FLC profiles to be unique among 263 profiles related to diverse tumoral and nontumoral liver samples. We identified two distinct molecular subgroups of p-FLCs with different outcomes. Pathway analysis of p-FLCs revealed ERBB2 overexpression and an up-regulation of glycolysis, possibly leading to compensatory mitochondrial hyperplasia and oncocytic differentiation. Four of the sixteen genes most significantly overexpressed in p-FLCs were neuroendocrine genes: prohormone convertase 1 (PCSK1); neurotensin; delta/notch-like EGF repeat containing; and calcitonin. PCSK1 overexpression was validated by immunohistochemistry, yielding specific, diffuse staining of the protein throughout the cytoplasm, possibly corresponding to a functional form of this convertase. CONCLUSION: p-FLCs have a unique transcriptomic signature characterized by the strong expression of specific neuroendocrine genes, suggesting that these tumors may have a cellular origin different from that of HCC. Our data have implications for the use of genomic profiling for diagnosis and selection of targeted therapies in patients with p-FLC.

A hepatocellular carcinoma 5-gene score associated with survival of patients after liver resection.

BACKGROUND & AIMS: 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. METHODS: 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). RESULTS: 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. CONCLUSIONS: 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.