Biology subjects

Hosseini, N.

Publications and source records attributed to Hosseini, N..

4 recordsLinked to original sources

bioRxiv2024

Targeting of SUMOylation leads to cBAF complex stabilization and disruption of the SS18::SSX transcriptome in Synovial Sarcoma

Synovial Sarcoma (SS) is driven by the SS18::SSX fusion oncoprotein. and is ultimately refractory to therapeutic approaches. SS18::SSX alters ATP-dependent chromatin remodeling BAF (mammalian SWI/SNF) complexes, leading to the degradation of canonical (cBAF) complex and amplified presence of an SS18::SSX-containing non-canonical BAF (ncBAF or GBAF) that drives an SS-specific transcription program and tumorigenesis. We demonstrate that SS18::SSX activates the SUMOylation program and SSs are sensitive to the small molecule SAE1/2 inhibitor, TAK-981. Mechanistically, TAK-981 de-SUMOylates the cBAF subunit SMARCE1, stabilizing and restoring cBAF on chromatin, shifting away from SS18::SSX-ncBAF-driven transcription, associated with DNA damage and cell death and resulting in tumor inhibition across both human and mouse SS tumor models. TAK-981 synergized with cytotoxic chemotherapy through increased DNA damage, leading to tumor regression. Targeting the SUMOylation pathway in SS restores cBAF complexes and blocks the SS18::SSX-ncBAF transcriptome, identifying a therapeutic vulnerability in SS, positioning the in-clinic TAK-981 to treat SS.

cancer biology↗

bioRxiv2023

MHCnvex: Likelihood-based model for calling the copy number variations and loss of heterozygosity in MHC class I and II locus

MotivationAccurate detection of copy number variation (CNV) and loss of heterozygosity (LOH) in the major histocompatibility complex (MHC) locus is of great significance to both clinicians and researchers since it has the potential to inform treatment decisions, particularly in the context of immunotherapy. However, due to the high level of polymorphism in this region, calling copy number variations is a challenging task and requires special methodology. To address this challenge, we have developed a tool with a wide range of applicability to call CNV and LOH in the MHC region. ResultsTo address the challenge mentioned above, we have developed MHCnvex, an algorithm that accurately calls haplotype level CNVs for the genes in the MHC class I and II locus. MHCnvex presents a novel approach based on likelihood models for detecting CNVs at haplotype level. Additionally, this method integrates the MHC locus with other adjacent loci from the short arm of chromosome 6 to enhance the accuracy of the calls. The incorporation of a statistical approach and the examination of the broader chromosome 6 region, rather than just the MHC locus alone, make MHCnvex less vulnerable to local coverage biases (commonly associated with MHC locus). The performance of MHCnvex has been evaluated according to different measures including concordance with MHC flanking regions and changes in the allelic expression of MHC genes due to alteration. MHCnvex has also shown to significantly reduce the variability of calculated coverage for CNV analysis. AvailabilityImplementation of MHCnvex algorithm is available as an R package at: https://github.com/NoshadHo/MHCnvex

bioinformatics↗

bioRxiv2023

HLAProphet: Personalized allele-level quantification of the HLA proteins

Loss of HLA expression in tumor cells is a commonly observed phenotype that is known to be associated with T-cell evasion. Proteogenomic characterizations of the molecular mechanisms underpinning this loss of HLA expression are hindered by the polymorphic nature of the HLA proteins, with most individuals having germline HLA sequences that are highly divergent from the sequences found in standard reference databases. To address this issue, we have developed HLAProphet, an algorithm that utilizes HLA types from paired DNA sequencing data to provide personalized allele-level quantification of the HLA proteins from TMT mass spectrometry data. We show that HLAProphet triples the number of tryptic peptide identifications made by standard reference based approaches, and produces protein expression values that have high concordance with RNA expression and known loss of heterozygosity events.

bioinformatics↗

bioRxiv2023

Distinct mutational processes shape selection of MHC class I and class II mutations across primary and metastatic tumors

Disruption of antigen presentation via loss of MHC expression is a strategy whereby cancer cells escape immune surveillance and develop resistance to immunotherapy. We developed the personalized genomics algorithm Hapster and accurately called somatic mutations within the MHC genes of 10,001 primary and 2,199 metastatic tumors, creating a catalog of 1663 nonsynonymous mutations that provide key insights into MHC mutagenesis. We found that MHC-I genes are among the most frequently mutated genes in both primary and metastatic tumors, while MHC-II mutations are more restricted. Recurrent deleterious mutations are found within haplotype and cancer-type specific hotspots associated with distinct mutational processes. Functional classification of MHC residues revealed significant positive selection for mutations disruptive to the B2M, peptide, and T-cell binding interfaces, as well as MHC chaperones. At the cohort level, all cancers with positive selection for MHC mutations are responsive to immune checkpoint inhibitors, underscoring the translational relevance of our findings.

cancer biology↗