Different Genetic Signatures of Small-Cell Lung Cancer Characterize Anti-GABAB R and Anti-Hu Paraneoplastic Neurological Syndromes.

OBJECTIVE: Small-cell lung cancer (SCLC) is the malignancy most frequently associated with paraneoplastic neurological syndromes (PNS) and can trigger different antibody responses against intracellular (Hu) or neuronal surface (GABAB R) antigens. Our aim was to clarify whether the genomic and transcriptomic features of SCLC are different in patients with anti-GABAB R or anti-Hu PNS compared with SCLC without PNS. METHODS: A total of 76 SCLC tumor samples were collected: 34 anti-Hu, 14 anti-GABAB R, and 28 SCLC without PNS. The study consisted of 4 steps: (1) pathological confirmation; (2) next generation sequencing using a panel of 98 genes, including those encoding the autoantibodies targets ELAVL1-4, GABBR1-2, and KCTD16; (3) genome-wide copy number variation (CNV); and (4) whole-transcriptome RNA sequencing. RESULTS: CNV analysis revealed that patients with anti-GABAB R PNS commonly have a gain in chromosome 5q, which contains KCTD16, whereas anti-Hu and control patients often harbor a loss. No significantly different number of mutations regarding any onconeural genes was observed. Conversely, the transcriptomic profile of SCLC was different, and the differentially expressed genes allowed effective clustering of the samples into 3 groups, reflecting the antibody-based classification, with an overexpression of KCTD16 specific to anti-GABAB R PNS. Pathway analysis revealed that tumors of patients with anti-GABAB R encephalitis were enriched in B-cell signatures, as opposed to those of patients with anti-Hu, in which T-cell- and interferon-γ-related signatures were overexpressed. INTERPRETATION: SCLC genetic and transcriptomic features differentiate anti-GABAB R, anti-Hu, and non-PNS tumors. The role of KCTD16 appears to be pivotal in the tumor immune tolerance breakdown of anti-GABAB R PNS. ANN NEUROL 2023;94:1102-1115.

Somatic mutations reveal asymmetric cellular dynamics in the early human embryo.

Somatic cells acquire mutations throughout the course of an individual's life. Mutations occurring early in embryogenesis are often present in a substantial proportion of, but not all, cells in postnatal humans and thus have particular characteristics and effects. Depending on their location in the genome and the proportion of cells they are present in, these mosaic mutations can cause a wide range of genetic disease syndromes and predispose carriers to cancer. They have a high chance of being transmitted to offspring as de novo germline mutations and, in principle, can provide insights into early human embryonic cell lineages and their contributions to adult tissues. Although it is known that gross chromosomal abnormalities are remarkably common in early human embryos, our understanding of early embryonic somatic mutations is very limited. Here we use whole-genome sequences of normal blood from 241 adults to identify 163 early embryonic mutations. We estimate that approximately three base substitution mutations occur per cell per cell-doubling event in early human embryogenesis and these are mainly attributable to two known mutational signatures. We used the mutations to reconstruct developmental lineages of adult cells and demonstrate that the two daughter cells of many early embryonic cell-doubling events contribute asymmetrically to adult blood at an approximately 2:1 ratio. This study therefore provides insights into the mutation rates, mutational processes and developmental outcomes of cell dynamics that operate during early human embryogenesis.

Gene signature of circulating platelet-bound neutrophils is associated with poor prognosis in cancer patients.

Beyond their critical role in hemostasis, platelets physically interact with neutrophils to form neutrophil-platelet aggregates (NPAs), enhancing neutrophil effector functions during inflammation. NPAs may also promote disease worsening in various inflammatory diseases. However, characterization of NPAs in cancer remains totally unexplored. Using ImageStreamX (ISX) imaging flow cytometer, we were not only allowed able to detect CD15+ CD14- CD36+ ITGA2B+ NPAs in both healthy donors' (HDs) and cancer patients' bloods, but we also showed that NPAs result from the binding of platelets preferentially to low-density neutrophils (LDNs) as opposed to normal-density neutrophils (NDNs). By reanalyzing two independent public scRNAseq data of whole blood leukocytes from cancer patients and HDs, we could identify a subset of neutrophils with high platelet gene expression that may correspond to NPAs. Moreover, we showed that cancer patients' derived NPAs possessed a distinct molecular signature compared to the other neutrophil subsets, independently of platelet genes. Gene ontology (GO) term enrichment analysis of this NPAs-associated neutrophil transcriptomic signature revealed a significant enrichment of neutrophil degranulation, chemotaxis and trans-endothelial migration GO terms. Lastly, using The Cancer Genome Atlas (TCGA), we could show by multivariate Cox analysis that the NPAs-associated neutrophil transcriptomic signature was associated with a worse patient prognosis in several cancer types. These results suggest that neutrophils from NPAs are systemically primed by platelets empowering them with cancer progression capacities once at tumor site. NPAs may therefore hold clinical utility as novel noninvasive blood prognostic biomarker in cancer patients with solid tumors.

The circular RNome of primary breast cancer.

Circular RNAs (circRNAs) are a class of RNAs that is under increasing scrutiny, although their functional roles are debated. We analyzed RNA-seq data of 348 primary breast cancers and developed a method to identify circRNAs that does not rely on unmapped reads or known splice junctions. We identified 95,843 circRNAs, of which 20,441 were found recurrently. Of the circRNAs that match exon boundaries of the same gene, 668 showed a poor or even negative (R < 0.2) correlation with the expression level of the linear gene. In silico analysis showed only a minority (8.5%) of circRNAs could be explained by known splicing events. Both these observations suggest that specific regulatory processes for circRNAs exist. We confirmed the presence of circRNAs of CNOT2, CREBBP, and RERE in an independent pool of primary breast cancers. We identified circRNA profiles associated with subgroups of breast cancers and with biological and clinical features, such as amount of tumor lymphocytic infiltrate and proliferation index. siRNA-mediated knockdown of circCNOT2 was shown to significantly reduce viability of the breast cancer cell lines MCF-7 and BT-474, further underlining the biological relevance of circRNAs. Furthermore, we found that circular, and not linear, CNOT2 levels are predictive for progression-free survival time to aromatase inhibitor (AI) therapy in advanced breast cancer patients, and found that circCNOT2 is detectable in cell-free RNA from plasma. We showed that circRNAs are abundantly present, show characteristics of being specifically regulated, are associated with clinical and biological properties, and thus are relevant in breast cancer.

HERVs characterize normal and leukemia stem cells and represent a source of shared epitopes for cancer immunotherapy.

Human endogenous retroviruses (HERVs) represent 8% of the human genome. The expression of HERVs and their immune impact have not been extensively studied in Acute Myeloid Leukemia (AML). In this study, we used a reference of 14 968 HERV functional units to provide a thorough analysis of HERV expression in normal and AML bone marrow cells. We show that the HERV retrotranscriptome accurately characterizes normal and leukemic cell subpopulations, including leukemia stem cells, in line with different epigenetic profiles. We then show that HERV expression delineates AML subtypes with different prognoses. We finally propose a method to select and prioritize CD8+ T cell epitopes derived from AML-specific HERVs and we show that lymphocytes infiltrating patient bone marrow at diagnosis contain naturally occurring CD8+ T cells against these HERV epitopes. We also provide in vitro data supporting the functionality of HERV-specific CD8+ T-cells against AML cells. These results show that HERVs represent an important source of genetic information that can help enhancing disease stratification or biomarker identification and an important reservoir of alternative tumor-specific T cell epitopes relevant for cancer immunotherapy.

Peptimapper: proteogenomics workflow for the expert annotation of eukaryotic genomes.

BACKGROUND: Accurate structural annotation of genomes is still a challenge, despite the progress made over the past decade. The prediction of gene structure remains difficult, especially for eukaryotic species, and is often erroneous and incomplete. We used a proteogenomics strategy, taking advantage of the combination of proteomics datasets and bioinformatics tools, to identify novel protein coding-genes and splice isoforms, assign correct start sites, and validate predicted exons and genes. RESULTS: Our proteogenomics workflow, Peptimapper, was applied to the genome annotation of Ectocarpus sp., a key reference genome for both the brown algal lineage and stramenopiles. We generated proteomics data from various life cycle stages of Ectocarpus sp. strains and sub-cellular fractions using a shotgun approach. First, we directly generated peptide sequence tags (PSTs) from the proteomics data. Second, we mapped PSTs onto the translated genomic sequence. Closely located hits (i.e., PSTs locations on the genome) were then clustered to detect potential coding regions based on parameters optimized for the organism. Third, we evaluated each cluster and compared it to gene predictions from existing conventional genome annotation approaches. Finally, we integrated cluster locations into GFF files to use a genome viewer. We identified two potential novel genes, a ribosomal protein L22 and an aryl sulfotransferase and corrected the gene structure of a dihydrolipoamide acetyltransferase. We experimentally validated the results by RT-PCR and using transcriptomics data. CONCLUSIONS: Peptimapper is a complementary tool for the expert annotation of genomes. It is suitable for any organism and is distributed through a Docker image available on two public bioinformatics docker repositories: Docker Hub and BioShaDock. This workflow is also accessible through the Galaxy framework and for use by non-computer scientists at https://galaxy.protim.eu . Data are available via ProteomeXchange under identifier PXD010618.

Toll-like receptor 3 downregulation is an escape mechanism from apoptosis during hepatocarcinogenesis.

BACKGROUND & AIMS: Low levels of toll-like receptor 3 (TLR3) in patients with hepatocellular carcinoma (HCC) are associated with poor prognosis, primarily owing to the loss of inflammatory signaling and subsequent lack of immune cell recruitment to the liver. Herein, we explore the role of TLR3-triggered apoptosis in HCC cells. METHODS: Quantitative reverse transcription PCR, western blotting, immunohistochemistry and comparative genomic hybridization were used to analyze human and mouse HCC cell lines, as well as surgically resected primary human HCCs, and to study the impact of TLR3 expression on patient outcomes. Functional analyses were performed in HCC cells, following the restoration of TLR3 by lentiviral transduction. The role of TLR3-triggered apoptosis in HCC was analyzed in vivo in a transgenic mouse model of HCC. RESULTS: Lower expression of TLR3 in tumor compared to non-tumor matched tissue was observed at both mRNA and protein levels in primary HCC, and was predictive of shorter recurrence-free survival after surgical resection in both univariate (hazard ratio [HR] 1.79; 95% CI 1.04-3.06; p = 0.03) and multivariate analyses (HR 1.73; CI 1.01-2.97; p = 0.04). Immunohistochemistry confirmed frequent downregulation of TLR3 in human and mouse primary HCC cells. None of the 6 human HCC cell lines analyzed expressed TLR3, and ectopic expression of TLR3 following lentiviral transduction not only restored the inflammatory response but also sensitized cells to TLR3-triggered apoptosis. Lastly, in the transgenic mouse model of HCC, absence of TLR3 expression was accompanied by a lower rate of preneoplastic hepatocyte apoptosis and accelerated hepatocarcinogenesis without altering the tumor immune infiltrate. CONCLUSION: Downregulation of TLR3 protects transforming hepatocytes from direct TLR3-triggered apoptosis, thereby contributing to hepatocarcinogenesis and poor patient outcome. LAY SUMMARY: Hepatocellular carcinoma (HCC) is a heterogeneous disease associated with a poor prognosis. In patients with HCC, TLR3 downregulation is associated with reduced survival. Herein, we show that the absence of TLR3 is associated with a lower rate of apoptosis, and subsequently more rapid hepatocarcinogenesis, without any change to the immune infiltrate in the liver. Therefore, the poor prognosis associated with low TLR3 expression in HCC is likely linked to tumors ability to escape apoptosis. TLR3 may become a promising therapeutic target in TLR3-positive HCC.

A gene-expression profiling score for prediction of outcome in patients with follicular lymphoma: a retrospective training and validation analysis in three international cohorts.

BACKGROUND: Patients with follicular lymphoma have heterogeneous outcomes. Predictor models to distinguish, at diagnosis, between patients at high and low risk of progression are needed. The objective of this study was to use gene-expression profiling data to build and validate a predictive model of outcome for patients treated in the rituximab era. METHODS: A training set of fresh-frozen tumour biopsies was prospectively obtained from 160 untreated patients with high-tumour-burden follicular lymphoma enrolled in the phase 3 randomised PRIMA trial, in which rituximab maintenance was evaluated after rituximab plus chemotherapy induction (median follow-up 6·6 years [IQR 6·0-7·0]). RNA of sufficient quality was obtained for 149 of 160 cases, and Affymetrix U133 Plus 2.0 microarrays were used for gene-expression profiling. We did a multivariate Cox regression analysis to identify genes with expression levels associated with progression-free survival independently of maintenance treatment in a subgroup of 134 randomised patients. Expression levels from 95 curated genes were then determined by digital expression profiling (NanoString technology) in 53 formalin-fixed paraffin-embedded samples of the training set to compare the technical reproducibility of expression levels for each gene between technologies. Genes with high correlation (>0·75) were included in an L2-penalised Cox model adjusted on rituximab maintenance to build a predictive score for progression-free survival. The model was validated using NanoString technology to digitally quantify gene expression in 488 formalin-fixed, paraffin-embedded samples from three independent international patient cohorts from the PRIMA trial (n=178; distinct from the training cohort), the University of Iowa/Mayo Clinic Lymphoma SPORE project (n=201), and the Barcelona Hospital Clinic (n=109). All tissue samples consisted of pretreatment diagnostic biopsies and were confirmed as follicular lymphoma grade 1-3a. The patients were all treated with regimens containing rituximab and chemotherapy, possibly followed by either rituximab maintenance or ibritumomab-tiuxetan consolidation. We determined an optimum threshold on the score to predict patients at low risk and high risk of progression. The model, including the multigene score and the threshold, was initially evaluated in the three validation cohorts separately. The sensitivity and specificity of the score for the prediction of the risk of lymphoma progression at 2 years were assessed on the combined validation cohorts. FINDINGS: In the training cohort, the expression levels of 395 genes were associated with a risk of progression. 23 genes reflecting both B-cell biology and tumour microenvironment with correlation coefficients greater than 0·75 between the two technologies and sample types were retained to build a predictive model that identified a population at an increased risk of progression (p<0·0001). In a multivariate Cox model for progression-free survival adjusted on rituximab maintenance treatment and Follicular Lymphoma International Prognostic Index 1 (FLIPI-1) score, this predictor independently predicted progression (adjusted hazard ratio [aHR] of the high-risk group compared with the low-risk group 3·68, 95% CI 2·19-6·17 [p<0·0001]). The 5-year progression-free survival was 26% (95% CI 16-43) in the high-risk group and 73% (64-83) in the low-risk group. The predictor performances were confirmed in each of the individual validation cohorts (aHR comparing high-risk to low-risk groups 2·57 [95% CI 1·65-4·01] in cohort 1; 2·12 [1·32-3·39] in cohort 2; and 2·11 [1·01-4·41] in cohort 3). In the combined validation cohort, the median progression-free survival was 3·1 years (95% CI 2·4-4·8) in the high-risk group and 10·8 years (10·1-not reached) in the low-risk group (p<0·0001). The risk of lymphoma progression at 2 years was 38% (95% CI 29-46) in the high-risk group and 19% (15-24) in the low-risk group. In a multivariate analysis, the score predicted progression-free survival independently of anti-CD20 maintenance treatment and of the FLIPI score (aHR for the combined cohort 2·30, 95% CI 1·72-3·07). INTERPRETATION: We developed and validated a robust 23-gene expression-based predictor of progression-free survival that is applicable to routinely available formalin-fixed, paraffin-embedded tumour biopsies from patients with follicular lymphoma at time of diagnosis. Applying this score could allow individualised therapy for patients according to their risk category. FUNDING: Roche, SIRIC Lyric, LYSARC, National Institutes of Health, the Henry J Predolin Foundation, and the Spanish Plan Nacional de Investigacion.

A 13-gene expression-based radioresistance score highlights the heterogeneity in the response to radiation therapy across HPV-negative HNSCC molecular subtypes.

BACKGROUND: Radiotherapy for head and neck squamous cell carcinomas (HNSCC) is associated with a substantial morbidity and inconsistent efficacy. Human papillomavirus (HPV)-positive status is recognized as a marker of increased radiosensitivity. Our goal was to identify molecular markers associated with benefit to radiotherapy in patients with HPV-negative disease. METHODS: Gene expression profiles from public repositories were downloaded for data mining. Training sets included 421 HPV-negative HNSCC tumors from The Cancer Genome Atlas (TCGA) and 32 HNSCC cell lines with available radiosensitivity data (GSE79368). A radioresistance (RadR) score was computed using the single sample Gene Set Enrichment Analysis tool. The validation sets included two panels of cell lines (NCI-60 and GSE21644) and HPV-negative HNSCC tumor datasets, including 44 (GSE6631), 82 (GSE39366), and 179 (GSE65858) patients, respectively. We finally performed an integrated analysis of the RadR score with known recurrent genomic alterations in HNSCC, patterns of protein expression, biological hallmarks, and patterns of drug sensitivity using TCGA and the E-MTAB-3610 dataset (659 pancancer cell lines, 140 drugs). RESULTS: We identified 13 genes differentially expressed between tumor and normal head and neck mucosa that were associated with radioresistance in vitro and in patients. The 13-gene expression-based RadR score was associated with recurrence in patients treated with surgery and adjuvant radiotherapy but not with surgery alone. It was significantly different among different molecular subtypes of HPV-negative HNSCC and was significantly lower in the "atypical" molecular subtype. An integrated analysis of RadR score with genomic alterations, protein expression, biological hallmarks and patterns of drug sensitivity showed a significant association with CCND1 amplification, fibronectin expression, seven hallmarks (including epithelial-to-mesenchymal transition and unfolded protein response), and increased sensitivity to elesclomol, an HSP90 inhibitor. CONCLUSIONS: Our study highlights the clinical relevance of the molecular classification of HNSCC and the RadR score to refine radiation strategies in HPV-negative disease.

BCL2 mutations do not confer adverse prognosis in follicular lymphoma patients treated with rituximab.

BCL2 mutations have been suggested to confer an adverse prognosis to follicular lymphoma (FL) patients, but their prognostic value has not been assessed in patients treated with a rituximab-containing regimen. Here we evaluated the prognostic value of BCL2 mutations in a large prospective cohort of 252 patients with FL treated with immunochemotherapy in the PRIMA randomized trial. Using a DNA-targeted sequencing approach, we detected amino acid altering mutations in 135 patients (54%) and showed that these mutations were probably mediated by the over-activation of AICDA (activation-induced cytidine deaminase) in the context of the t(14;18) translocation. The BCL2 variants identified in PRIMA patients affected the BH1, BH2, and BH3 functional motifs at a lower frequency than the N-terminus and flexible loop domain, with mostly conservative aminoacid changes. With a median follow-up of 6.7 years, we did not observe any impact of BCL2 mutations either on overall survival or progression-free survival.

Chemical and biological insecticides select distinct gene expression patterns in Aedes aegypti mosquito.

Worldwide evolution of mosquito resistance to chemical insecticides represents a major challenge for public health, and the future of vector control largely relies on the development of biological insecticides that can be used in combination with chemicals (integrated management), with the expectation that populations already resistant to chemicals will not become readily resistant to biological insecticides. However, little is known about the metabolic pathways affected by selection with chemical or biological insecticides. Here we show that Aedes aegypti, a laboratory mosquito strain selected with a biological insecticide (Bacillus thuringiensis israelensis, Bti) evolved increased transcription of many genes coding for endopeptidases while most genes coding for detoxification enzymes were under-expressed. By contrast, in strains selected with chemicals, genes encoding detoxification enzymes were mostly over-expressed. In all the resistant strains, genes involved in immune response were under-transcribed, suggesting that basal immunity might be a general adjustment variable to compensate metabolic costs caused by insecticide selection. Bioassays generally showed no evidence for an increased susceptibility of selected strains towards the other insecticide type, and all chemical-resistant strains were as susceptible to Bti as the unselected parent strain, which is a good premise for sustainable integrated management of mosquito populations resistant to chemicals.

UniPathway: a resource for the exploration and annotation of metabolic pathways.

UniPathway (http://www.unipathway.org) is a fully manually curated resource for the representation and annotation of metabolic pathways. UniPathway provides explicit representations of enzyme-catalyzed and spontaneous chemical reactions, as well as a hierarchical representation of metabolic pathways. This hierarchy uses linear subpathways as the basic building block for the assembly of larger and more complex pathways, including species-specific pathway variants. All of the pathway data in UniPathway has been extensively cross-linked to existing pathway resources such as KEGG and MetaCyc, as well as sequence resources such as the UniProt KnowledgeBase (UniProtKB), for which UniPathway provides a controlled vocabulary for pathway annotation. We introduce here the basic concepts underlying the UniPathway resource, with the aim of allowing users to fully exploit the information provided by UniPathway.

Added value of whole-exome and RNA sequencing in advanced and refractory cancer patients with no molecular-based treatment recommendation based on a 90-gene panel.

INTRODUCTION: The objective was to determine the added value of comprehensive molecular profile by whole-exome and RNA sequencing (WES/RNA-Seq) in advanced and refractory cancer patients who had no molecular-based treatment recommendation (MBTR) based on a more limited targeted gene panel (TGP) plus array-based comparative genomic hybridization (aCGH). MATERIALS AND METHODS: In this retrospective analysis, we selected 50 patients previously included in the PROFILER trial (NCT01774409) for which no MBT could be recommended based on a targeted 90-gene panel and aCGH. For each patient, the frozen tumor sample mirroring the FFPE sample used for TGP/aCGH analysis were processed for WES and RNA-Seq. Data from TGP/aCGH were reanalyzed, and together with WES/RNA-Seq, findings were simultaneously discussed at a new molecular tumor board (MTB). RESULTS: After exclusion of variants of unknown significance, a total of 167 somatic molecular alterations were identified in 50 patients (median: 3 [1-10]). Out of these 167 relevant molecular alterations, 51 (31%) were common to both TGP/aCGH and WES/RNA-Seq, 19 (11%) were identified by the TGP/aCGH only and 97 (58%) were identified by WES/RNA-Seq only, including two fusion transcripts in two patients. A MBTR was provided in 4/50 (8%) patients using the information from TGP/aCGH versus 9/50 (18%) patients using WES/RNA-Seq findings. Three patients had similar recommendations based on TGP/aCGH and WES/RNA-Seq. CONCLUSIONS: In advanced and refractory cancer patients in whom no MBTR was recommended from TGP/aCGH, WES/RNA-Seq allowed to identify more alterations which may in turn, in a limited fraction of patients, lead to new MBTR.

NF-κB subunits RelA and c-Rel selectively control CD4+ T cell function in multiple sclerosis and cancer.

The outcome of cancer and autoimmunity is often dictated by the effector functions of CD4+ conventional T cells (Tconv). Although activation of the NF-κB signaling pathway has long been implicated in Tconv biology, the cell-autonomous roles of the separate NF-κB transcription-factor subunits are unknown. Here, we dissected the contributions of the canonical NF-κB subunits RelA and c-Rel to Tconv function. RelA, rather than c-Rel, regulated Tconv activation and cytokine production at steady-state and was required for polarization toward the TH17 lineage in vitro. Accordingly, RelA-deficient mice were fully protected against neuroinflammation in a model of multiple sclerosis due to defective transition to a pathogenic TH17 gene-expression program. Conversely, Tconv-restricted ablation of c-Rel impaired their function in the microenvironment of transplanted tumors, resulting in enhanced cancer burden. Moreover, Tconv required c-Rel for the response to PD-1-blockade therapy. Our data reveal distinct roles for canonical NF-κB subunits in different disease contexts, paving the way for subunit-targeted immunotherapies.

The CanOE strategy: integrating genomic and metabolic contexts across multiple prokaryote genomes to find candidate genes for orphan enzymes.

Of all biochemically characterized metabolic reactions formalized by the IUBMB, over one out of four have yet to be associated with a nucleic or protein sequence, i.e. are sequence-orphan enzymatic activities. Few bioinformatics annotation tools are able to propose candidate genes for such activities by exploiting context-dependent rather than sequence-dependent data, and none are readily accessible and propose result integration across multiple genomes. Here, we present CanOE (Candidate genes for Orphan Enzymes), a four-step bioinformatics strategy that proposes ranked candidate genes for sequence-orphan enzymatic activities (or orphan enzymes for short). The first step locates "genomic metabolons", i.e. groups of co-localized genes coding proteins catalyzing reactions linked by shared metabolites, in one genome at a time. These metabolons can be particularly helpful for aiding bioanalysts to visualize relevant metabolic data. In the second step, they are used to generate candidate associations between un-annotated genes and gene-less reactions. The third step integrates these gene-reaction associations over several genomes using gene families, and summarizes the strength of family-reaction associations by several scores. In the final step, these scores are used to rank members of gene families which are proposed for metabolic reactions. These associations are of particular interest when the metabolic reaction is a sequence-orphan enzymatic activity. Our strategy found over 60,000 genomic metabolons in more than 1,000 prokaryote organisms from the MicroScope platform, generating candidate genes for many metabolic reactions, of which more than 70 distinct orphan reactions. A computational validation of the approach is discussed. Finally, we present a case study on the anaerobic allantoin degradation pathway in Escherichia coli K-12.

ecoPrimers: inference of new DNA barcode markers from whole genome sequence analysis.

Using non-conventional markers, DNA metabarcoding allows biodiversity assessment from complex substrates. In this article, we present ecoPrimers, a software for identifying new barcode markers and their associated PCR primers. ecoPrimers scans whole genomes to find such markers without a priori knowledge. ecoPrimers optimizes two quality indices measuring taxonomical range and discrimination to select the most efficient markers from a set of reference sequences, according to specific experimental constraints such as marker length or specifically targeted taxa. The key step of the algorithm is the identification of conserved regions among reference sequences for anchoring primers. We propose an efficient algorithm based on data mining, that allows the analysis of huge sets of sequences. We evaluate the efficiency of ecoPrimers by running it on three different sequence sets: mitochondrial, chloroplast and bacterial genomes. Identified barcode markers correspond either to barcode regions already in use for plants or animals, or to new potential barcodes. Results from empirical experiments carried out on a promising new barcode for analyzing vertebrate diversity fully agree with expectations based on bioinformatics analysis. These tests demonstrate the efficiency of ecoPrimers for inferring new barcodes fitting with diverse experimental contexts. ecoPrimers is available as an open source project at: http://www.grenoble.prabi.fr/trac/ecoPrimers.

An Early Neoplasia Index (ENI10), Based on Molecular Identity of CD10 Cells and Associated Stemness Biomarkers, is a Predictor of Patient Outcome in Many Cancers.

An accurate estimate of patient survival at diagnosis is critical to plan efficient therapeutic options. A simple and multiapplication tool is needed to move forward the precision medicine era. Taking advantage of the broad and high CD10 expression in stem and cancers cells, we evaluated the molecular identity of aggressive cancer cells. We used epithelial primary cells and developed a breast cancer stem cell­based progressive model. The superiority of the early-transformed isolated molecular index was evaluated by large-scale analysis in solid cancers. BMP2-driven cell transformation increases CD10 expression which preserves stemness properties. Our model identified a unique set of 159 genes enriched in G2­M cell-cycle phases and spindle assembly complex. Using samples predisposed to transformation, we confirmed the value of an early neoplasia index associated to CD10 (ENI10) to discriminate premalignant status of a human tissue. Using a stratified Cox model, a large-scale analysis (>10,000 samples, The Cancer Genome Atlas Pan-Cancer) validated a strong risk gradient (HRs reaching HR = 5.15; 95% confidence interval: 4.00­6.64) for high ENI10 levels. Through different databases, Cox regression model analyses highlighted an association between ENI10 and poor progression-free intervals for more than 50% of cancer subtypes tested, and the potential of ENI10 to predict drug efficacy. The ENI10 index constitutes a robust tool to detect pretransformed tissues and identify high-risk patients at diagnosis. Owing to its biological link with refractory cancer stem cells, the ENI10 index constitutes a unique way of identifying effective treatments to improve clinical care. SIGNIFICANCE: We identified a molecular signature called ENI10 which, owing to its biological link with stem cell properties, predicts patient outcome and drugs efficiency in breast and several other cancers. ENI10 should allow early and optimized clinical management of a broad number of cancers, regardless of the stage of tumor progression.

Sorafenib in Molecularly Selected Cancer Patients: Final Analysis of the MOST-Plus Sorafenib Cohort.

BACKGROUND: MOST-plus is a multicenter, randomized, open-label, adaptive Phase II trial evaluating the clinical benefit of targeted treatments matched to molecular alteration in advanced/metastatic solid tumors. Sorafenib was tested on patients with tumors harboring sorafenib-targeted genes. METHODS: The MOST-plus trial used a randomized discontinuation design. After 12 weeks of sorafenib (400 mg, po BID), patients with progressive disease discontinued study, patients with objective response were proposed to continue sorafenib, whereas patients with stable disease (SD) were randomly assigned (1:1) to the maintenance or interruption of treatment. The primary endpoint was RECIST version 1.1 progression-free rate at 16 weeks after randomization (PFR-16w). Secondary endpoints included progression-free survival (PFS), overall survival (OS), and toxicity. Statistical analyses used a sequential Bayesian approach with interim efficacy analyses. The enrolment could be stopped in the case of a 95% probability for the estimated PFR-16w to be higher in the maintenance than in the interruption arm (NCT02029001). RESULTS: 151 patients were included, of whom 35 had SD at 12 weeks of Sorafenib. For the 35 patients with SD on sorafenib, the PFR-16w was 65% [95% credibility interval 43.4-83.7] in the continuation arm and 25% [7.8-48.1] in the interruption arm. Median PFS and OS were improved in the maintenance versus the interruption arm (mPFS: 5.6 [95%CI 1.97-6.77] months versus 2.0 [95%CI 1.61-3.91] months (p = 0.0231) and mOS: 14.3 [95%CI 8.9-23.8] versus 8.0 months [95%CI 3.5-15.2] (p = 0.0857)). CONCLUSION: Sorafenib showed activity in progressive patients with solid tumors harboring somatic genomic alterations in sorafenib-targeted genes. Continuing sorafenib when SD is achieved improves PFR compared to interruption.

Dissecting the Origin of Heterogeneity in Uterine and Ovarian Carcinosarcomas.

Gynecologic carcinosarcomas (CS) are biphasic neoplasms composed of carcinomatous (C) and sarcomatous (S) malignant components. Because of their rarity and histologic complexity, genetic and functional studies on CS are scarce and the mechanisms of initiation and development remain largely unknown. Whole-genome analysis of the C and S components reveals shared genomic alterations, thus emphasizing the clonal evolution of CS. Reconstructions of the evolutionary history of each tumor further reveal that C and S samples are composed of both ancestral cell populations and component-specific subclones, supporting a common origin followed by distinct evolutionary trajectories. However, while we do not find any recurrent genomic features associated with phenotypic divergence, transcriptomic and methylome analyses identify a common mechanism across the cohort, the epithelial-to-mesenchymal transition (EMT), suggesting a role for nongenetic factors in inflicting changes to cellular fate. Altogether, these data accredit the hypothesis that CS tumors are driven by both clonal evolution and transcriptomic reprogramming, essential for susceptibility to transdifferentiation upon encountering environmental cues, thus linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences. Significance: We have provided a detailed characterization of the genomic landscape of CS and identified EMT as a common mechanism associated with phenotypic divergence, linking CS heterogeneity to genetic, transcriptomic, and epigenetic influences.