Inferring ligand-receptor cellular networks from bulk and spatial transcriptomic datasets with BulkSignalR.

The study of cellular networks mediated by ligand-receptor interactions has attracted much attention recently owing to single-cell omics. However, rich collections of bulk data accompanied with clinical information exists and continue to be generated with no equivalent in single-cell so far. In parallel, spatial transcriptomic (ST) analyses represent a revolutionary tool in biology. A large number of ST projects rely on multicellular resolution, for instance the Visium™ platform, where several cells are analyzed at each location, thus producing localized bulk data. Here, we describe BulkSignalR, a R package to infer ligand-receptor networks from bulk data. BulkSignalR integrates ligand-receptor interactions with downstream pathways to estimate statistical significance. A range of visualization methods complement the statistics, including functions dedicated to spatial data. We demonstrate BulkSignalR relevance using different datasets, including new Visium liver metastasis ST data, with experimental validation of protein colocalization. A comparison with other ST packages shows the significantly higher quality of BulkSignalR inferences. BulkSignalR can be applied to any species thanks to its built-in generic ortholog mapping functionality.

Frequency of pathogenic germline variants in cancer susceptibility genes in 1336 renal cell carcinoma cases.

Renal cell carcinoma (RCC) occurs in a number of cancer predisposition syndromes, but the genetic architecture of susceptibility to RCC is not well defined. We investigated the frequency of pathogenic and likely pathogenic (P/LP) germline variants in cancer susceptibility genes (CSGs) within a large series of unselected RCC participants. Whole-genome sequencing data on 1336 RCC participants and 5834 controls recruited to the UK 100 000 Genomes Project, a nationwide multicentre study, was analyzed to identify rare P/LP short variants (single nucleotide variants and insertions/deletions ranging from 1 to 50 base pairs) and structural variants in 121 CSGs. Among 1336 RCC participants [mean: 61.3 years (±12 SD), range: 13-88 years; 64% male], 85 participants [6.4%; 95% CI (5.1, 7.8)] had one or more P/LP germline variant in a wider range of CSGs than previously recognized. A further 64 intragenic variants in CSGs previously associated with RCC were classified as a variant of uncertain significance (VUS) (24 'hot VUSs') and were considered to be of potential clinical relevance as further evaluation might results in their reclassification. Most patients with P variants in well-established CSGs known to predispose to renal cell carcinoma (RCC-CSGs) were aged <50 years. Burden test analysis for filtered variants in CSGs demonstrated a significant excess of CHEK2 variants in European RCC participants compared with the healthy European controls (P = 0.0019). Approximately, 6% of the patients with RCC unselected for family history have a germline variant requiring additional follow-up analysis. To improve diagnostic yield, we suggest expanding the panel of RCC-CSGs tested to include CHEK2 and all SDHx subunits and raising the eligibility criteria for age-based testing.

Elongin C (ELOC/TCEB1)-associated von Hippel-Lindau disease.

Around 95% of patients with clinical features that meet the diagnostic criteria for von Hippel-Lindau disease (VHL) have a detectable inactivating germline variant in VHL. The VHL protein (pVHL) functions as part of the E3 ubiquitin ligase complex comprising pVHL, elongin C, elongin B, cullin 2 and ring box 1 (VCB-CR complex), which plays a key role in oxygen sensing and degradation of hypoxia-inducible factors. To date, only variants in VHL have been shown to cause VHL disease. We undertook trio analysis by whole-exome sequencing in a proband with VHL disease but without a detectable VHL mutation. Molecular studies were also performed on paired DNA extracted from the proband's kidney tumour and blood and bioinformatics analysis of sporadic renal cell carcinoma (RCC) dataset was undertaken. A de novo pathogenic variant in ELOC NM_005648.4(ELOC):c.236A>G (p.Tyr79Cys) gene was identified in the proband. ELOC encodes elongin C, a key component [C] of the VCB-CR complex. The p.Tyr79Cys substitution is a mutational hotspot in sporadic VHL-competent RCC and has previously been shown to mimic the effects of pVHL deficiency on hypoxic signalling. Analysis of an RCC from the proband showed similar findings to that in somatically ELOC-mutated RCC (expression of hypoxia-responsive proteins, no somatic VHL variants and chromosome 8 loss). These findings are consistent with pathogenic ELOC variants being a novel cause for VHL disease and suggest that genetic testing for ELOC variants should be performed in individuals with suspected VHL disease with no detectable VHL variant.

PCIG: a web-based application to explore immune-genomics interactions across cancer types.

MOTIVATION: Genomic alterations can modulate the tumor immunophenotype depending on their nature and tissue of origin. Although this immune-genomic interaction may shape disease progression and response to immunotherapy, the factors governing such dynamics and the influence of each tissue-specific context remain poorly understood. RESULTS: Here, we have developed the PanCancer ImmunoGenomics (PCIG) tool, a web-based resource that provides researchers with the opportunity to mine immunome-genome relationships across several cancer types using data from the Pan-Cancer Analysis of Whole-Genomes (PCAWG) study, which comprises >2,600 samples spanning across 20 different cancer primary sites. PCIG yields an integrative analysis of the crosstalk between somatic genomic alterations and different immune features, thus helping to understand immune response-related processes. AVAILABILITY AND IMPLEMENTATION: PCIG is freely available at https://pcig.vhio.net and is supported by all major web browsers. PCIG was developed with Django, which is a Python-based free and open-source framework, and it uses SQL Server as a relational database management system. The code is freely available for download at GitHub https://github.com/AnnaPG/PCIG and in its online supplementary material. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Integrated multi-omics profiling of high-grade estrogen receptor-positive, HER2-negative breast cancer.

Estrogen receptor-positive and human epidermal growth factor receptor 2-negative (ER+ HER2- ) breast cancer accounts for ~ 60-70% of all cases of invasive breast carcinoma. High-grade ER+ HER2- tumors respond poorly to endocrine therapy. In this study, we systematically analyzed clinical and multi-omics data to find potential strategies for personalized therapy of patients with high-grade ER+ HER2- disease. Six different cohorts were analyzed, for which multi-omics data were available. Grade III ER+ HER2- cases harbored higher proportions of large tumor size (> 5 cm), lymph node metastasis, chemotherapy use, and luminal B subtypes defined by PAM50, as compared with grade I/II tumors. DNA methylation (HM450) data and methylation-specific PCR indicated that the cg18629132 locus in the MKI67 promoter was hypermethylated in grade I/II cases and normal tissue, but hypomethylated in grade III cases or triple-negative breast cancer, resulting in higher expression of MKI67. Mutations in ESR1 and TP53 were detected in post-endocrine treatment metastatic samples at a higher rate than in treatment-naive tumors in grade III cases. We identified 42 and 20 focal copy number events in nonmetastatic and metastatic high-grade ER+ HER2- cases, respectively, with either MYC or MDM2 amplification representing an independent prognostic event in grade III cases. Transcriptional profiling within grade III tumors highlighted ER signaling downregulation and upregulation of immune-related pathways in non-luminal-like tumors defined by PAM50. Recursive partitioning analysis was employed to construct a decision tree of an endocrine-resistant subgroup (GATA3-negative and AGR-negative) of two genes that was validated by immunohistochemistry in a Chinese cohort. All together, these data suggest that grade III ER+ HER2- tumors have distinct clinical and molecular characteristics compared with low-grade tumors, particularly in cases with non-luminal-like biology. Due to the dismal prognosis in this group, clinical trials are warranted to test the efficacy of potential novel therapies.

Copy-Number Alteration Burden Differentially Impacts Immune Profiles and Molecular Features of Hepatocellular Carcinoma.

PURPOSE: Chromosomal instability is a hallmark of cancer that results in broad and focal copy-number alterations (CNAs), two events associated with distinct molecular, immunologic, and clinical features. In hepatocellular carcinoma (HCC), the role of CNAs has not been thoroughly assessed. Thus, we dissected the impact of CNA burdens on HCC molecular and immune features. EXPERIMENTAL DESIGN: We analyzed SNP array data from 452 paired tumor/adjacent resected HCCs and 25 dysplastic nodules. For each sample, broad and focal CNA burdens were quantified using CNApp, and the resulting broad scores (BS) and focal scores (FS) were correlated with transcriptomic, mutational, and methylation profiles, tumor immune composition, and clinicopathologic data. RESULTS: HCCs with low broad CNA burdens (defined as BS ≤ 4; 17%) presented high inflammation, active infiltrate signaling, high cytolytic activity, and enrichment of the "HCC immune class" and gene signatures related to antigen presentation. Conversely, tumors with chromosomal instability (high broad CNA loads, BS ≥ 11; 40%), displayed immune-excluded traits and were linked to proliferation, TP53 dysfunction, and DNA repair. Candidate determinants of the low cytotoxicity and immune exclusion features of high-BS tumors included alterations in antigen-presenting machinery (i.e., HLA), widespread hypomethylation, and decreased rates of observed/expected neoantigenic mutations. High FSs were independent of tumor immune features, but were related to proliferation, TP53 dysfunction, and progenitor cell traits. CONCLUSIONS: HCCs with high chromosomal instability exhibit features of immune exclusion, whereas tumors displaying low burdens of broad CNAs present an immune active profile. These CNA scores can be tested to predict response to immunotherapies.

The role of exome sequencing in newborn screening for inborn errors of metabolism.

Public health newborn screening (NBS) programs provide population-scale ascertainment of rare, treatable conditions that require urgent intervention. Tandem mass spectrometry (MS/MS) is currently used to screen newborns for a panel of rare inborn errors of metabolism (IEMs)1-4. The NBSeq project evaluated whole-exome sequencing (WES) as an innovative methodology for NBS. We obtained archived residual dried blood spots and data for nearly all IEM cases from the 4.5 million infants born in California between mid-2005 and 2013 and from some infants who screened positive by MS/MS, but were unaffected upon follow-up testing. WES had an overall sensitivity of 88% and specificity of 98.4%, compared to 99.0% and 99.8%, respectively for MS/MS, although effectiveness varied among individual IEMs. Thus, WES alone was insufficiently sensitive or specific to be a primary screen for most NBS IEMs. However, as a secondary test for infants with abnormal MS/MS screens, WES could reduce false-positive results, facilitate timely case resolution and in some instances even suggest more appropriate or specific diagnosis than that initially obtained. This study represents the largest, to date, sequencing effort of an entire population of IEM-affected cases, allowing unbiased assessment of current capabilities of WES as a tool for population screening.

A Mitochondrial tRNA Mutation Causes Axonal CMT in a Large Venezuelan Family.

OBJECTIVE: The objective of this study was to identify the genetic cause for progressive peripheral nerve disease in a Venezuelan family. Despite the growing list of genes associated with Charcot-Marie-Tooth disease, many patients with axonal forms lack a genetic diagnosis. METHODS: A pedigree was constructed, based on family clinical data. Next-generation sequencing of mitochondrial DNA (mtDNA) was performed for 6 affected family members. Muscle biopsies from 4 family members were used for analysis of muscle histology and ultrastructure, mtDNA sequencing, and RNA quantification. Ultrastructural studies were performed on sensory nerve biopsies from 2 affected family members. RESULTS: Electrodiagnostic testing showed a motor and sensory axonal polyneuropathy. Pedigree analysis revealed inheritance only through the maternal line, consistent with mitochondrial transmission. Sequencing of mtDNA identified a mutation in the mitochondrial tRNAVal (mt-tRNAVal ) gene, m.1661A>G, present at nearly 100% heteroplasmy, which disrupts a Watson-Crick base pair in the T-stem-loop. Muscle biopsies showed chronic denervation/reinnervation changes, whereas biochemical analysis of electron transport chain (ETC) enzyme activities showed reduction in multiple ETC complexes. Northern blots from skeletal muscle total RNA showed severe reduction in abundance of mt-tRNAVal , and mildly increased mt-tRNAPhe , in subjects compared with unrelated age- and sex-matched controls. Nerve biopsies from 2 affected family members demonstrated ultrastructural mitochondrial abnormalities (hyperplasia, hypertrophy, and crystalline arrays) consistent with a mitochondrial neuropathy. CONCLUSION: We identify a previously unreported cause of Charcot-Marie-Tooth (CMT) disease, a mutation in the mt-tRNAVal , in a Venezuelan family. This work expands the list of CMT-associated genes from protein-coding genes to a mitochondrial tRNA gene. ANN NEUROL 2020;88:830-842.

Molecular classification and therapeutic targets in extrahepatic cholangiocarcinoma.

BACKGROUND & AIMS: Cholangiocarcinoma (CCA), a deadly malignancy of the bile ducts, can be classified based on its anatomical location into either intrahepatic (iCCA) or extrahepatic (eCCA), each with different pathogenesis and clinical management. There is limited understanding of the molecular landscape of eCCA and no targeted therapy with clinical efficacy has been approved. We aimed to provide a molecular classification of eCCA and identify potential targets for molecular therapies. METHODS: An integrative genomic analysis of an international multicenter cohort of 189 eCCA cases was conducted. Genomic analysis included whole-genome expression, targeted DNA-sequencing and immunohistochemistry. Molecular findings were validated in an external set of 181 biliary tract tumors from the ICGC. RESULTS: KRAS (36.7%), TP53 (34.7%), ARID1A (14%) and SMAD4 (10.7%) were the most prevalent mutations, with ∼25% of tumors having a putative actionable genomic alteration according to OncoKB. Transcriptome-based unsupervised clustering helped us define 4 molecular classes of eCCA. Tumors classified within the Metabolic class (19%) showed a hepatocyte-like phenotype with activation of the transcription factor HNF4A and enrichment in gene signatures related to bile acid metabolism. The Proliferation class (23%), more common in patients with distal CCA, was characterized by enrichment of MYC targets, ERBB2 mutations/amplifications and activation of mTOR signaling. The Mesenchymal class (47%) was defined by signatures of epithelial-mesenchymal transition, aberrant TGFß signaling and poor overall survival. Finally, tumors in the Immune class (11%) had a higher lymphocyte infiltration, overexpression of PD-1/PD-L1 and molecular features associated with a better response to immune checkpoint inhibitors. CONCLUSION: An integrative molecular characterization identified distinct subclasses of eCCA. Genomic traits of each class provide the rationale for exploring patient stratification and novel therapeutic approaches. LAY SUMMARY: Targeted therapies have not been approved for the treatment of extrahepatic cholangiocarcinoma. We performed a multi-platform molecular characterization of this tumor in a cohort of 189 patients. These analyses revealed 4 novel transcriptome-based molecular classes of extrahepatic cholangiocarcinoma and identified ∼25% of tumors with actionable genomic alterations, which has potential prognostic and therapeutic implications.

CNApp, a tool for the quantification of copy number alterations and integrative analysis revealing clinical implications.

Somatic copy number alterations (CNAs) are a hallmark of cancer, but their role in tumorigenesis and clinical relevance remain largely unclear. Here, we developed CNApp, a web-based tool that allows a comprehensive exploration of CNAs by using purity-corrected segmented data from multiple genomic platforms. CNApp generates genome-wide profiles, computes CNA scores for broad, focal and global CNA burdens, and uses machine learning-based predictions to classify samples. We applied CNApp to the TCGA pan-cancer dataset of 10,635 genomes showing that CNAs classify cancer types according to their tissue-of-origin, and that each cancer type shows specific ranges of broad and focal CNA scores. Moreover, CNApp reproduces recurrent CNAs in hepatocellular carcinoma and predicts colon cancer molecular subtypes and microsatellite instability based on broad CNA scores and discrete genomic imbalances. In summary, CNApp facilitates CNA-driven research by providing a unique framework to identify relevant clinical implications. CNApp is hosted at https://tools.idibaps.org/CNApp/.

In most cases, human cells contain two copies of each of their genes, yet sometimes this can change, an effect called copy number alteration (CNA). Cancer is a genetic disease and thus, studying the DNA from tumor samples is crucial to improving diagnosis and choosing the right treatment. Most tumors contain cells with CNAs; however, the impact of CNAs in cancer progression is poorly understood. CNAs can be studied by examining the genome of tumor cells and finding which regions display an unusual number of copies. It may also be possible to gather information about different cancer types by analyzing the CNAs in a tumor, but this approach requires the analysis of large amounts of data. To aid the analysis of CNAs in cancer cells, Franch-Expósito, Bassaganyas et al. have created an online tool called CNApp, which is able to identify and count CNAs in genomic data and link them to features associated with different cancers. The hope is that a better understanding of the effect of CNAs in cancer could help better diagnose cancers, and improve outcomes for patients. Potentially, this could also predict what type of treatment would work better for a specific tumor. Besides, by using a machine-learning approach, the tool can also make predictions about specific cancer subtypes in order to facilitate clinical decisions. Franch-Expósito, Bassaganyas et al. tested CNApp using previously existing cancer data from 33 different cancer types to show how CNApp can help the interpretation of CNAs in cancer. Moreover, CNApp can also use CNAs to identify different types of bowel (colorectal) cancer in a way that could help doctors to make decisions about treatment. Together these findings show that CNApp provides an adaptable and accessible research tool for the study of cancer genomics, which could provide opportunities to inform medical procedures.

New factors for protein transport identified by a genome-wide CRISPRi screen in mammalian cells.

Protein and membrane trafficking pathways are critical for cell and tissue homeostasis. Traditional genetic and biochemical approaches have shed light on basic principles underlying these processes. However, the list of factors required for secretory pathway function remains incomplete, and mechanisms involved in their adaptation poorly understood. Here, we present a powerful strategy based on a pooled genome-wide CRISPRi screen that allowed the identification of new factors involved in protein transport. Two newly identified factors, TTC17 and CCDC157, localized along the secretory pathway and were found to interact with resident proteins of ER-Golgi membranes. In addition, we uncovered that upon TTC17 knockdown, the polarized organization of Golgi cisternae was altered, creating glycosylation defects, and that CCDC157 is an important factor for the fusion of transport carriers to Golgi membranes. In conclusion, our work identified and characterized new actors in the mechanisms of protein transport and secretion and opens stimulating perspectives for the use of our platform in physiological and pathological contexts.

Molecular portrait of high alpha-fetoprotein in hepatocellular carcinoma: implications for biomarker-driven clinical trials.

The clinical utility of serum alpha-fetoprotein (AFP) in patients with hepatocellular carcinoma (HCC) is widely recognised. However, a clear understanding of the mechanisms of AFP overexpression and the molecular traits of patients with AFP-high tumours are not known. We assessed transcriptome data, whole-exome sequencing data and DNA methylome profiling of 520 HCC patients from two independent cohorts to identify distinct molecular traits of patients with AFP-high tumours (serum concentration > 400 ng/ml), which represents an accepted prognostic cut-off and a predictor of response to ramucirumab. Those AFP-high tumours (18% of resected cases) were characterised by significantly lower AFP promoter methylation (p < 0.001), significant enrichment of progenitor-cell features (CK19, EPCAM), higher incidence of BAP1 oncogene mutations (8.5% vs 1.6%) and lower mutational rates of CTNNB1 (14% vs 30%). Specifically, AFP-high tumours displayed significant activation of VEGF signalling (p < 0.001), which might provide the rationale for the reported benefit of ramucirumab in this subgroup of patients.

Molecular predictors of prevention of recurrence in HCC with sorafenib as adjuvant treatment and prognostic factors in the phase 3 STORM trial.

OBJECTIVE: Sorafenib is the standard systemic therapy for advanced hepatocellular carcinoma (HCC). Survival benefits of resection/local ablation for early HCC are compromised by 70% 5-year recurrence rates. The phase 3 STORM trial comparing sorafenib with placebo as adjuvant treatment did not achieve its primary endpoint of improving recurrence-free survival (RFS). The biomarker companion study BIOSTORM aims to define (A) predictors of recurrence prevention with sorafenib and (B) prognostic factors with B level of evidence. DESIGN: Tumour tissue from 188 patients randomised to receive sorafenib (83) or placebo (105) in the STORM trial was collected. Analyses included gene expression profiling, targeted exome sequencing (19 known oncodrivers), immunohistochemistry (pERK, pVEGFR2, Ki67), fluorescence in situ hybridisation (VEGFA) and immunome. A gene signature capturing improved RFS in sorafenib-treated patients was generated. All 70 RFS events were recurrences, thus time to recurrence equalled RFS. Predictive and prognostic value was assessed using Cox regression models and interaction test. RESULTS: BIOSTORM recapitulates clinicopathological characteristics of STORM. None of the biomarkers tested (related to angiogenesis and proliferation) or previously proposed gene signatures, or mutations predicted sorafenib benefit or recurrence. A newly generated 146-gene signature identifying 30% of patients captured benefit to sorafenib in terms of RFS (p of interaction=0.04). These sorafenib RFS responders were significantly enriched in CD4+ T, B and cytolytic natural killer cells, and lacked activated adaptive immune components. Hepatocytic pERK (HR=2.41; p=0.012) and microvascular invasion (HR=2.09; p=0.017) were independent prognostic factors. CONCLUSION: In BIOSTORM, only hepatocytic pERK and microvascular invasion predicted poor RFS. No mutation, gene amplification or previously proposed gene signatures predicted sorafenib benefit. A newly generated multigene signature associated with improved RFS on sorafenib warrants further validation. TRIAL REGISTRATION NUMBER: NCT00692770.

Whole exome and whole genome sequencing with dried blood spot DNA without whole genome amplification.

Newborn screening (NBS) for rare conditions is performed in all 50 states in the USA. We have partnered with the California Department of Public Health Genetic Disease Laboratory to determine whether sufficient DNA can be extracted from archived dried blood spots (DBS) for next-generation sequencing in the hopes that next-generation sequencing can play a role in NBS. We optimized the DNA extraction and sequencing library preparation protocols for residual infant DBS archived over 20 years ago and successfully obtained acceptable whole exome and whole genome sequencing data. This sequencing study using DBS DNA without whole genome amplification prior to sequencing library preparation provides evidence that properly stored residual newborn DBS are a satisfactory source of DNA for genetic studies.

Unconventional secretion of FABP4 by endosomes and secretory lysosomes.

An appreciation of the functional properties of the cytoplasmic fatty acid binding protein 4 (FABP4) has advanced with the recent demonstration that an extracellular form secreted by adipocytes regulates a wide range of physiological functions. Little, however, is known about the mechanisms that mediate the unconventional secretion of FABP4. Here, we demonstrate that FABP4 secretion is mediated by a membrane-bounded compartment, independent of the conventional endoplasmic reticulum-Golgi secretory pathway. We show that FABP4 secretion is also independent of GRASP proteins, autophagy, and multivesicular bodies but involves enclosure within endosomes and secretory lysosomes. We highlight the physiological significance of this pathway with the demonstration that an increase in plasma levels of FABP4 is inhibited by chloroquine treatment of mice. These findings chart the pathway of FABP4 secretion and provide a potential therapeutic means to control metabolic disorders associated with its dysregulated secretion.

A Role for CD154, the CD40 Ligand, in Granulomatous Inflammation.

Granulomatous inflammation is a distinctive form of chronic inflammation in which predominant cells include macrophages, epithelioid cells, and multinucleated giant cells. Mechanisms regulating granulomatous inflammation remain ill-understood. CD154, the ligand of CD40, is a key mediator of inflammation. CD154 confers a proinflammatory phenotype to macrophages and controls several macrophagic functions. Here, we studied the contribution of CD154 in a mouse model of toxic liver injury with carbon tetrachloride and a model of absorbable suture graft. In both models, granulomas are triggered in response to endogenous persistent liver calcified necrotic lesions or by grafted sutures. CD154-deficient mice showed delayed clearance of carbon tetrachloride-induced liver calcified necrotic lesions and impaired progression of suture-induced granuloma. In vitro, CD154 stimulated phagocytosis of opsonized erythrocytes by macrophages, suggesting a potential mechanism for the altered granulomatous inflammation in CD154KO mice. These results suggest that CD154 may contribute to the natural history of granulomatous inflammation.

Trunk mutational events present minimal intra- and inter-tumoral heterogeneity in hepatocellular carcinoma.

BACKGROUND & AIMS: According to the clonal model of tumor evolution, trunk alterations arise at early stages and are ubiquitous. Through the characterization of early stages of hepatocarcinogenesis, we aimed to identify trunk alterations in hepatocellular carcinoma (HCC) and study their intra- and inter-tumor distribution in advanced lesions. METHODS: A total of 151 samples representing the multistep process of hepatocarcinogenesis were analyzed by targeted-sequencing and a single nucleotide polymorphism array. Genes altered in early lesions (31 dysplastic nodules [DNs] and 38 small HCCs [sHCC]) were defined as trunk. Their distribution was explored in: a) different regions of large tumors (43 regions, 21 tumors), and b) different nodules of the same patient (39 tumors, 17 patients). Multinodular lesions were classified as intrahepatic metastases (IMs) or synchronous tumors based on chromosomal aberrations. RESULTS: TERT promoter mutations (10.5%) and broad copy-number aberrations in chromosomes 1 and 8 (3-7%) were identified as trunk gatekeepers in DNs and were maintained in sHCCs. Trunk drivers identified in sHCCs included TP53 (23%) and CTNNB1 (11%) mutations, and focal amplifications or deletions in known drivers (6%). Overall, TERT, TP53 and CTNNB1 mutations were the most frequent trunk events and at least one was present in 51% of sHCCs. Around 90% of mutations in these genes were ubiquitous among different regions of large tumors. In multinodular HCCs, 35% of patients harbored IMs; 85% of mutations in TERT, TP53 and/or CTNNB1 were retained in primary and metastatic tumors. CONCLUSIONS: Trunk events in early stages (TERT, TP53, CTNNB1 mutations) were ubiquitous across different regions of the same tumor and between primary and metastatic nodules in >85% of cases. This concept supports the knowledge that single biopsies would suffice to capture trunk mutations in HCC. LAY SUMMARY: Trunk alterations arise at early stages of cancer and are shared among all malignant cells of the tumor. In order to identify trunk alterations in HCC, we characterized early stages of hepatocarcinogenesis represented by dysplastic nodules and small lesions. Mutations in TERT, TP53 and CTNNB1 genes were the most frequent. Analyses in more advanced lesions showed that mutations in these same genes were shared between different regions of the same tumor and between primary and metastatic tumors, suggesting their trunk role in this disease.

Identification of an Immune-specific Class of Hepatocellular Carcinoma, Based on Molecular Features.

BACKGROUND & AIMS: Agents that induce an immune response against tumors by altering T-cell regulation have increased survival times of patients with advanced-stage tumors, such as melanoma or lung cancer. We aimed to characterize molecular features of immune cells that infiltrate hepatocellular carcinomas (HCCs) to determine whether these types of agents might be effective against liver tumors. METHODS: We analyzed HCC samples from 956 patients. We separated gene expression profiles from tumor, stromal, and immune cells using a non-negative matrix factorization algorithm. We then analyzed the gene expression pattern of inflammatory cells in HCC tumor samples. We correlated expression patterns with the presence of immune cell infiltrates and immune regulatory molecules, determined by pathology and immunohistochemical analyses, in a training set of 228 HCC samples. We validated the correlation in a validation set of 728 tumor samples. Using data from 190 tumors in the Cancer Genome Atlas, we correlated immune cell gene expression profiles with numbers of chromosomal aberrations (based on single-nucleotide polymorphism array) and mutations (exome sequence data). RESULTS: We found approximately 25% of HCCs to have markers of an inflammatory response, with high expression levels of the CD274 molecule (programmed death-ligand 1) and programmed cell death 1, markers of cytolytic activity, and fewer chromosomal aberrations. We called this group of tumors the Immune class. It contained 2 subtypes, characterized by markers of an adaptive T-cell response or exhausted immune response. The exhausted immune response subclass expressed many genes regulated by transforming growth factor beta 1 that mediate immunosuppression. We did not observe any differences in numbers of mutations or expression of tumor antigens between the immune-specific class and other HCCs. CONCLUSIONS: In an analysis of HCC samples from 956 patients, we found almost 25% to express markers of an inflammatory response. We identified 2 subclasses, characterized by adaptive or exhausted immune responses. These findings indicate that some HCCs might be susceptible to therapeutic agents designed to block the regulatory pathways in T cells, such as programmed death-ligand 1, programmed cell death 1, or transforming growth factor beta 1 inhibitors.

Golgi enzymes do not cycle through the endoplasmic reticulum during protein secretion or mitosis.

Golgi-specific sialyltransferase (ST) expressed as a chimera with the rapamycin-binding domain of mTOR, FRB, relocates to the endoplasmic reticulum (ER) in cells exposed to rapamycin that also express invariant chain (Ii)-FKBP in the ER. This result has been taken to indicate that Golgi-resident enzymes cycle to the ER constitutively. We show that ST-FRB is trapped in the ER even without Ii-FKBP upon rapamycin addition. This is because ER-Golgi-cycling FKBP proteins contain a C-terminal KDEL-like sequence, bind ST-FRB in the Golgi, and are transported together back to the ER by KDEL receptor-mediated retrograde transport. Moreover, depletion of KDEL receptor prevents trapping of ST-FRB in the ER by rapamycin. Thus ST-FRB cycles artificially by binding to FKBP domain-containing proteins. In addition, Golgi-specific O-linked glycosylation of a resident ER protein occurs only upon artificial fusion of Golgi membranes with ER. Together these findings support the consensus view that there is no appreciable mixing of Golgi-resident enzymes with ER under normal conditions.

PeSV-Fisher: identification of somatic and non-somatic structural variants using next generation sequencing data.

UNLABELLED: Next-generation sequencing technologies expedited research to develop efficient computational tools for the identification of structural variants (SVs) and their use to study human diseases. As deeper data is obtained, the existence of higher complexity SVs in some genomes becomes more evident, but the detection and definition of most of these complex rearrangements is still in its infancy. The full characterization of SVs is a key aspect for discovering their biological implications. Here we present a pipeline (PeSV-Fisher) for the detection of deletions, gains, intra- and inter-chromosomal translocations, and inversions, at very reasonable computational costs. We further provide comprehensive information on co-localization of SVs in the genome, a crucial aspect for studying their biological consequences. The algorithm uses a combination of methods based on paired-reads and read-depth strategies. PeSV-Fisher has been designed with the aim to facilitate identification of somatic variation, and, as such, it is capable of analysing two or more samples simultaneously, producing a list of non-shared variants between samples. We tested PeSV-Fisher on available sequencing data, and compared its behaviour to that of frequently deployed tools (BreakDancer and VariationHunter). We have also tested this algorithm on our own sequencing data, obtained from a tumour and a normal blood sample of a patient with chronic lymphocytic leukaemia, on which we have also validated the results by targeted re-sequencing of different kinds of predictions. This allowed us to determine confidence parameters that influence the reliability of breakpoint predictions. AVAILABILITY: PeSV-Fisher is available at http://gd.crg.eu/tools.