Search

Background & Aims: Hepatocellular carcinoma (HCC) is a model of a diverse spectrum of cancers because it is induced by well-known etiologies, mainly hepatitis C virus (HCV) and hepatitis B virus. Here, we aimed to identify HCV-specific mutational signatures and explored the link between the HCV-related regional variation in mutations rates and HCV-induced alterations in genome-wide chromatin organization., Methods: To identify an HCV-specific mutational signature in HCC, we performed high-resolution targeted sequencing to detect passenger mutations on 64 HCC samples from 3 etiology groups: hepatitis B virus, HCV, or other. To explore the link between the genomic signature and genome-wide chromatin organization we performed chromatin immunoprecipitation sequencing for the transcriptionally permissive H3K4Me3, H3K9Ac, and suppressive H3K9Me3 modifications after HCV infection., Results: Regional variation in mutation rate analysis showed significant etiology-dependent regional mutation rates in 12 genes: LRP2, KRT84, TMEM132B, DOCK2, DMD, INADL, JAK2, DNAH6, MTMR9, ATM, SLX4, and ARSD. We found an enrichment of C->T transversion mutations in the HCV-associated HCC cases. Furthermore, these cases showed regional variation in mutation rates associated with genomic intervals in which HCV infection dictated epigenetic alterations. This signature may be related to the HCV-induced decreased expression of genes encoding key enzymes in the base excision repair pathway., Conclusions: We identified novel distinct HCV etiology-dependent mutation signatures in HCC associated with HCV-induced alterations in histone modification. This study presents a link between cancer-causing mutagenesis and the increased predisposition to liver cancer in chronic HCV-infected individuals, and unveils novel etiology-specific mechanisms leading to HCC and cancer in general., (Copyright © 2023 The Authors. Published by Elsevier Inc. All rights reserved.)

Inference of germline polymorphisms in immunoglobulin genes from B cell receptor repertoires is complicated by somatic hypermutations, sequencing/PCR errors, and by varying length of reference alleles. The light chain inference is particularly challenging owing to large gene duplications and absence of D genes. We analyzed the light chain cDNA sequences from naïve B cell receptor repertoires from 100 individuals. We optimized light chain allele inference by tweaking parameters of the TIgGER functions, extending the germline reference sequences, and establishing mismatch frequency patterns at polymorphic positions to filter out false-positive candidates. We identified 48 previously unreported variants of light chain variable genes. We selected 14 variants for validation and successfully validated 11 by Sanger sequencing. Clustering of light chain 5'UTR, L-PART1, and L-PART2 revealed partial intron retention in 11 kappa and 9 lambda V alleles. Our results provide insight into germline variation in human light chain immunoglobulin loci., Competing Interests: V.G. declares advisory board positions in aiNET GmbH and Enpicom B.V. V.G. is also a consultant for Roche/Genentech. All remaining authors declare no conflict of interests., (© 2021 The Authors.)

The partial success of tumor immunotherapy induced by checkpoint blockade, which is not antigen-specific, suggests that the immune system of some patients contain antigen receptors able to specifically identify tumor cells. Here we focused on T-cell receptor (TCR) repertoires associated with spontaneous breast cancer. We studied the alpha and beta chain CDR3 domains of TCR repertoires of CD4 T cells using deep sequencing of cell populations in mice and applied the results to published TCR sequence data obtained from human patients. We screened peripheral blood T cells obtained monthly from individual mice spontaneously developing breast tumors by 5 months. We then looked at identical TCR sequences in published human studies; we used TCGA data from tumors and healthy tissues of 1,256 breast cancer resections and from 4 focused studies including sequences from tumors, lymph nodes, blood and healthy tissues, and from single cell dataset of 3 breast cancer subjects. We now report that mice spontaneously developing breast cancer manifest shared, Public CDR3 regions in both their alpha and beta and that a significant number of women with early breast cancer manifest identical CDR3 sequences. These findings suggest that the development of breast cancer is associated, across species, with biomarker, exclusive TCR repertoires., Competing Interests: The authors have declared that no competing interests exist.

Germline variations in immunoglobulin genes influence the repertoire of B cell receptors and antibodies, and such polymorphisms may impact disease susceptibility. However, the knowledge of the genomic variation of the immunoglobulin loci is scarce. Here, we report 25 potential novel germline IGHV alleles as inferred from rearranged naïve B cell cDNA repertoires of 98 individuals. Thirteen novel alleles were selected for validation, out of which ten were successfully confirmed by targeted amplification and Sanger sequencing of non-B cell DNA. Moreover, we detected a high degree of variability upstream of the V-REGION in the 5'UTR, L-PART1 and L-PART2 sequences, and found that identical V-REGION alleles can differ in upstream sequences. Thus, we have identified a large genetic variation not only in the V-REGION but also in the upstream sequences of IGHV genes. Our findings provide a new perspective for annotating immunoglobulin repertoire sequencing data., (© The Author(s) 2020. Published by Oxford University Press on behalf of Nucleic Acids Research.)

Summary: Antibody haplotype inference (chromosomal phasing) may have clinical implications for the identification of genetic predispositions to diseases. Yet, our knowledge of the genomic loci encoding for the variable regions of the antibody is only partial, mostly due to the challenge of aligning short reads from genome sequencing to these highly repetitive loci. A powerful approach to infer the content of these loci relies on analyzing repertoires of rearranged V(D)J sequences. We present here RAbHIT, an R Haplotype Antibody Inference Tool, that implements a novel algorithm to infer V(D)J haplotypes by adapting a Bayesian framework. RAbHIT offers inference of haplotype and gene deletions. It may be applied to sequences from naïve and non-naïve B-cells, sequenced by different library preparation protocols., Availability and Implementation: RAbHIT is freely available for academic use from comprehensive R archive network (CRAN) (https://cran.r-project.org/web/packages/rabhit/) under CC BY-SA 4.0 license., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

The adaptive immune receptor repertoire (AIRR) contains information on an individuals' immune past, present and potential in the form of the evolving sequences that encode the B cell receptor (BCR) repertoire. AIRR sequencing (AIRR-seq) studies rely on databases of known BCR germline variable (V), diversity (D), and joining (J) genes to detect somatic mutations in AIRR-seq data via comparison to the best-aligning database alleles. However, it has been shown that these databases are far from complete, leading to systematic misidentification of mutated positions in subsets of sample sequences. We previously presented TIgGER, a computational method to identify subject-specific V gene genotypes, including the presence of novel V gene alleles, directly from AIRR-seq data. However, the original algorithm was unable to detect alleles that differed by more than 5 single nucleotide polymorphisms (SNPs) from a database allele. Here we present and apply an improved version of the TIgGER algorithm which can detect alleles that differ by any number of SNPs from the nearest database allele, and can construct subject-specific genotypes with minimal prior information. TIgGER predictions are validated both computationally (using a leave-one-out strategy) and experimentally (using genomic sequencing), resulting in the addition of three new immunoglobulin heavy chain V (IGHV) gene alleles to the IMGT repertoire. Finally, we develop a Bayesian strategy to provide a confidence estimate associated with genotype calls. All together, these methods allow for much higher accuracy in germline allele assignment, an essential step in AIRR-seq studies.

Analysis of antibody repertoires by high-throughput sequencing is of major importance in understanding adaptive immune responses. Our knowledge of variations in the genomic loci encoding immunoglobulin genes is incomplete, resulting in conflicting VDJ gene assignments and biased genotype and haplotype inference. Haplotypes can be inferred using IGHJ6 heterozygosity, observed in one third of the people. Here, we propose a robust novel method for determining VDJ haplotypes by adapting a Bayesian framework. Our method extends haplotype inference to IGHD- and IGHV-based analysis, enabling inference of deletions and copy number variations in the entire population. To test this method, we generated a multi-individual data set of naive B-cell repertoires, and found allele usage bias, as well as a mosaic, tiled pattern of deleted IGHD and IGHV genes. The inferred haplotypes may have clinical implications for genetic disease predispositions. Our findings expand the knowledge that can be extracted from antibody repertoire sequencing data.

The role of B cells and posttranslational modifications in pathogenesis of organ-specific immune diseases is increasingly envisioned but remains poorly understood, particularly in human disorders. In celiac disease, transglutaminase 2-modified (TG2-modified; deamidated) gluten peptides drive disease-specific T cell and B cell responses, and antibodies to deamidated gluten peptides are excellent diagnostic markers. Here, we substantiate by high-throughput sequencing of IGHV genes that antibodies to a disease-specific, deamidated, and immunodominant B cell epitope of gluten (PLQPEQPFP) have biased and stereotyped usage of IGHV3-23 and IGHV3-15 gene segments with modest somatic mutations. X-ray crystal structures of 2 prototype IGHV3-15/IGKV4-1 and IGHV3-23/IGLV4-69 antibodies reveal peptide interaction mainly via germline-encoded residues. In-depth mutational analysis showed restricted selection and substitution patterns at positions involved in antigen binding. While the IGHV3-15/IGKV4-1 antibody interacts with Glu5 and Gln6, the IGHV3-23/IGLV4-69 antibody interacts with Gln3, Pro4, Pro7, and Phe8 - residues involved in substrate recognition by TG2. Hence, both antibodies, despite different interaction with the epitope, recognize signatures of TG2 processing that facilitates B cell presentation of deamidated gluten peptides to T cells, thereby providing a molecular framework for the generation of these clinically important antibodies. The study provides essential insight into the pathogenic mechanism of celiac disease.

Long noncoding RNAs (lncRNAs) are major regulators of many cellular processes including cell cycle progression and tumorigenesis. In this study, we identify a novel lncRNA, MA-linc1, and reveal its effects on cell cycle progression and cancer growth. Inhibition of MA-linc1 expression alters cell cycle distribution, leading to a decrease in the number of G1 cells and a concomitant increase in all other stages of the cell cycle, and in particular G2/M, suggesting its involvement in the regulation of M phase. Accordingly, knock down of MA-linc1 inhibits M phase exit upon release from a mitotic block. We further demonstrate that MA-linc1 predominantly functions in cis to repress expression of its neighboring gene, Purα, which is often deleted in human cancers and whose ectopic expression inhibits cell cycle progression. Knock down of Purα partially rescues the MA-linc1 dependent inhibition of M phase exit. In agreement with its suggested role in M phase, inhibition of MA-linc1 enhances apoptotic cell death induced by the antimitotic drug, Paclitaxel and this enhancement of apoptosis is rescued by Purα knockdown. Furthermore, high levels of MA-linc1 are associated with reduced survival in human breast and lung cancer patients.Taken together, our data identify MA-linc1 as a novel lncRNA regulator of cell cycle and demonstrate its potential role in cancer progression and treatment.

Autoreactive IgA plasma cells (PCs) specific for the enzyme transglutaminase 2 (TG2) are abundant in the small intestine of patients with active celiac disease (CD), and their number drops in patients treated by dietary gluten elimination. Little is known about their characteristics and their role in the disease. In this study, using high-throughput sequencing of the IgH V region (IGHV) genes, we have studied features of TG2-specific PCs and their related B cell clones in peripheral blood. We found that TG2-specific PCs from both untreated and treated patients have acquired lower number of somatic hypermutation and used focused IGHV repertoire with overrepresentation of the IGHV3-48, IGHV4-59, IGHV5-10-1, and IGHV5-51 gene segments. Furthermore, these PCs were clonally expanded and showed signs of affinity maturation. Lineage trees demonstrated shared clones between gut PCs and blood memory B cells, primarily IgAs. Some trees also involved IgG cells, suggesting that anti-TG2 IgA and IgG responses are related. Similarly to TG2-specific PCs, clonally related memory IgA B cells of blood showed lower mutation rates with biased usage of IGHV3-48 and IGHV5-51. Such memory cells were rare in peripheral blood, yet detectable in most patients assessed by production of anti-TG2 Abs in vitro following stimulation of cells from patients who had been on a long-term gluten-free diet. Thus, the Ab response to TG2 in CD, while maintaining its IGHV gene usage, is dynamically regulated in response to gluten exposure with a low degree of maintenance at both PC and memory B cell levels in patients in remission., (Copyright © 2015 by The American Association of Immunologists, Inc.)

Background: The mechanistic target of rapamycin, (mTOR) kinase plays a pivotal role in controlling critical cellular growth and survival pathways, and its aberrant induction is implicated in cancer pathogenesis. Therefore, suppression of active mTOR signaling has been of great interest to researchers; several mTOR inhibitors have been discovered to date. Ethanol (EtOH), similar to pharmacologic mTOR inhibitors, has been shown to suppress the mTOR signaling pathway, though in a non-catalytic manner. Despite population studies showing that the consumption of EtOH has a protective effect against hematological malignancies, the mechanisms behind EtOH's modulation of mTOR activity in cells and its downstream consequences are largely unknown. Here we evaluated the effects of EtOH on the mTOR pathway, in comparison to the active-site mTOR inhibitor INK128, and compared translatome analysis of their downstream effects in diffuse large B-cell lymphoma (DLBCL)., Results: Treatment of DLBCL cells with EtOH suppressed mTORC1 complex formation while increasing AKT phosphorylation and mTORC2 complex assembly. INK128 completely abrogated AKT phosphorylation without affecting the structure of mTORC1/2 complexes. Accordingly, EtOH less profoundly suppressed cap-dependent translation and global protein synthesis, compared to a remarkable inhibitory effect of INK128 treatment. Importantly, EtOH treatment induced the formation of stress granules, while INK128 suppressed their formation. Microarray analysis of polysomal RNA revealed that although both agents primarily affected cell growth and survival, EtOH and INK128 regulated the synthesis of mostly distinct genes involved in these processes. Though both EtOH and INK128 inhibited cell cycle, proliferation and autophagy, EtOH, in contrast to INK128, did not induce cell apoptosis., Conclusion: Given that EtOH, similar to pharmacologic mTOR inhibitors, inhibits mTOR signaling, we systematically explored the effect of EtOH and INK128 on mTOR signal transduction, components of the mTORC1/2 interaction and their downstream effectors in DLBCL malignancy. We found that EtOH partially inhibits mTOR signaling and protein translation, compared to INK128's complete mTOR inhibition. Translatome analysis of mTOR downstream target genes established that differential inhibition of mTOR by EtOH and INK128 distinctly modulates translation of specific subsets of mRNAs involved in cell growth and survival, leading to differential cellular response and survival.

Introduction: GATA binding protein 3 (GATA3) is a regulator of mammary luminal cell differentiation, and an estrogen receptor (ER) associated marker in breast cancer. Tumor suppressor functions of GATA3 have been demonstrated primarily in basal-like breast cancers. Here, we focused on its function in luminal breast cancer, where GATA3 is frequently mutated, and its levels are significantly elevated., Methods: GATA3 target genes were identified in normal- and luminal cancer- mammary cells by ChIP-seq, followed by examination of the effects of GATA3 expressions and mutations on tumorigenesis-associated genes and processes. Additionally, mutations and expression data of luminal breast cancer patients from The Cancer Genome Atlas were analyzed to characterize genetic signatures associated with GATA3 mutations., Results: We show that some GATA3 effects shift from tumor suppressing to tumor promoting during tumorigenesis, with deregulation of three genes, BCL2, DACH1, THSD4, representing major GATA3-controlled processes in cancer progression. In addition, we identify an altered activity of mutant GATA3, and distinct associated genetic signatures. These signatures depend on the functional domain mutated; and, for a specific subgroup, are shared with basal-like breast cancer patients, who are a clinical group with regard to considerations of mode of treatment., Conclusions: The GATA3 dependent mechanisms may call for special considerations for proper prognosis and treatment of patients.

Motivation: At the core of transcriptome analyses of cancer is a challenge to detect molecular differences affiliated with disease phenotypes. This approach has led to remarkable progress in identifying molecular signatures and in stratifying patients into clinical groups. Yet, despite this progress, many of the identified signatures are not robust enough to be clinically used and not consistent enough to provide a follow-up on molecular mechanisms., Results: To address these issues, we introduce PhenoNet, a novel algorithm for the identification of pathways and networks associated with different phenotypes. PhenoNet uses two types of input data: gene expression data (RMA, RPKM, FPKM, etc.) and phenotypic information, and integrates these data with curated pathways and protein-protein interaction information. Comprehensive iterations across all possible pathways and subnetworks result in the identification of key pathways or subnetworks that distinguish between the two phenotypes., Availability and Implementation: Matlab code is available upon request., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)