An accurate quantification of HLA class I gene expression is important in understanding the interplay with the tumor microenvironment of antitumor cytotoxic T cell activities. Because HLA-I sequences ...are highly variable, standard RNAseq and mass spectrometry-based quantification workflows using common genome and protein sequence references do not provide HLA-I allele specific quantifications. Here, we used personalized HLA-I nucleotide and protein reference sequences based on the subjects’ HLA-I genotypes and surveyed tumor and adjacent normal samples from patients across nine cancer types. Mass spectrometry using data dependent acquisition data was validated to be sufficient to estimate HLA-A protein expression at the allele level. We found that HLA-I proteins were present in significantly higher levels in tumors compared to adjacent normal tissues from 41 to 63% of head and neck squamous cell carcinoma, uterine corpus endometrial carcinoma, and clear cell renal cell carcinoma patients, and this was driven by increased levels of HLA-I gene transcripts. Most immune cell types are universally enriched in HLA-I high tumors, while endothelial and neuronal cells showed divergent relationships with HLA-I. Pathway analysis revealed that tumor senescence and autophagy activity influence the level of HLA-I proteins in glioblastoma. Genes correlated to HLA-I protein expression are mostly the ones directly involved in HLA-I function in immune response and cell death, while glycosylation genes are exclusively co-expressed with HLA-I at the protein level.
Abstract
Motivation
LINE-1 elements are retrotransposons that are capable of copying their sequence to new genomic loci. LINE-1 derepression is associated with a number of disease states, and has the ...potential to cause significant cellular damage. Because LINE-1 elements are repetitive, it is difficult to quantify LINE-1 RNA at specific loci and to separate transcripts with protein coding capability from other sources of LINE-1 RNA.
Results
We provide a tool, L1EM that uses the expectation maximization algorithm to quantify LINE-1 RNA at each genomic locus, separating transcripts that are capable of generating retrotransposition from those that are not. We show the accuracy of L1EM on simulated data and against long read sequencing from HEK cells.
Availability and implementation
L1EM is written in python. The source code along with the necessary annotations are available at https://github.com/FenyoLab/L1EM and distributed under GPLv3.
Supplementary information
Supplementary data are available at Bioinformatics online.
The determination of endometrial carcinoma histological subtypes, molecular subtypes, and mutation status is critical for the diagnostic process, and directly affects patients’ prognosis and ...treatment. Sequencing, albeit slower and more expensive, can provide additional information on molecular subtypes and mutations that can be used to better select treatments. Here, we implement a customized multi-resolution deep convolutional neural network, Panoptes, that predicts not only the histological subtypes but also the molecular subtypes and 18 common gene mutations based on digitized H&E-stained pathological images. The model achieves high accuracy and generalizes well on independent datasets. Our results suggest that Panoptes, with further refinement, has the potential for clinical application to help pathologists determine molecular subtypes and mutations of endometrial carcinoma without sequencing.
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CNN models predict subtypes and mutations in endometrial cancer based on H&E imagesMulti-resolution CNN models perform better on H&E images than single-resolution onesFeature extraction suggests CNN models use human interpretable tumor featuresTumor grade distinguishes CNV-H molecular subtype from endometrioid histology samples
Hong et al. develop and implement a customized multi-resolution deep convolutional neural network that predict molecular subtypes and 18 common gene mutations in endometrial cancer based on digitized H&E-stained pathological images. The models learn human interpretable and generalizable features, indicating potential clinical application without sequencing analysis.
Recent studies have revealed diverse amino acid, post-translational, and noncanonical modifications of proteins in diverse organisms and tissues. However, their unbiased detection and analysis remain ...hindered by technical limitations. Here, we present a spectral alignment method for the identification of protein modifications using high-resolution mass spectrometry proteomics. Termed SAMPEI for spectral alignment-based modified peptide identification, this open-source algorithm is designed for the discovery of functional protein and peptide signaling modifications, without prior knowledge of their identities. Using synthetic standards and controlled chemical labeling experiments, we demonstrate its high specificity and sensitivity for the discovery of substoichiometric protein modifications in complex cellular extracts. SAMPEI mapping of mouse macrophage differentiation revealed diverse post-translational protein modifications, including distinct forms of cysteine itaconatylation. SAMPEI’s robust parametrization and versatility are expected to facilitate the discovery of biological modifications of diverse macromolecules. SAMPEI is implemented as a Python package and is available open-source from BioConda and GitHub (https://github.com/FenyoLab/SAMPEI).
Unbiased assays such as shotgun proteomics and RNA-seq provide high-resolution molecular characterization of tumors. These assays measure molecules with highly varied distributions, making ...interpretation and hypothesis testing challenging. Samples with the most extreme measurements for a molecule can reveal the most interesting biological insights yet are often excluded from analysis. Furthermore, rare disease subtypes are, by definition, underrepresented in cancer cohorts. To provide a strategy for identifying molecules aberrantly enriched in small sample cohorts, we present BlackSheep, a package for nonparametric description and differential analysis of genome-wide data, available from Bioconductor (https://www.bioconductor.org/packages/release/bioc/html/blacksheepr.html) and Bioconda (https://bioconda.github.io/recipes/blksheep/README.html). BlackSheep is a complementary tool to other differential expression analysis methods, which is particularly useful when analyzing small subgroups in a larger cohort.
Abstract
Motivation
Retrotransposition is an important force in shaping the human genome and is involved in prenatal development, disease and aging. Current genome browsers are not optimized for ...visualizing the experimental evidence for retrotransposon insertions.
Results
We have developed a specialized browser to visualize the evidence for retrotransposon insertions for both targeted and whole-genome sequencing data.
Availability and implementation
TranspoScope’s source code, as well as installation instructions, are available at https://github.com/FenyoLab/transposcope.
The GPMDB REST interface Fenyö, David; Beavis, Ronald C
Bioinformatics (Oxford, England),
06/2015, Letnik:
31, Številka:
12
Journal Article
Recenzirano
Odprti dostop
The Global Proteome Machine and Database (GPMDB) representational state transfer (REST) service was designed to provide simplified access to the proteomics information in GPMDB using a stable set of ...methods and parameters. Version 1 of this interface gives access to 25 methods for retrieving experimental information about protein post-translational modifications, amino acid variants, alternate splicing variants and protein cleavage patterns.
GPMDB data and database tables are freely available for commercial and non-commercial use. All software is also freely available, under the Artistic License. http://rest.thegpm.org/1 (GPMDB REST Service), http://wiki.thegpm.org/wiki/GPMDB_REST (Service description and help), and http://www.thegpm.org (GPM main project description and documentation). The code for the interface and an example REST client is available at ftp://ftp.thegpm.org/repos/gpmdb_rest
A recent study by Saldanha et al. demonstrates that blockchain-based models outcompeted local models and performed similarly with merged models to predict molecular features from cancer ...histopathology images. The results reveal the capability of decentralized models in molecular diagnosis of cancer.
A recent study by Saldanha et al. demonstrates that blockchain-based models outcompeted local models and performed similarly with merged models to predict molecular features from cancer histopathology images. The results reveal the capability of decentralized models in molecular diagnosis of cancer.
MED19, a component of the mediator complex and a co-regulator of the androgen receptor (AR), is pivotal in prostate cancer cell proliferation. MED19 has two isoforms: a full-length "canonical" and a ...shorter "alternative" variant. Specific antibodies were developed to investigate these isoforms. Both exhibit similar expression in normal prostate development and adult prostate tissue, but the canonical isoform is elevated in prostate adenocarcinomas. Overexpression of canonical MED19 in LNCaP cells promotes growth under conditions of androgen deprivation in vitro and in vivo, mirroring earlier findings with alternative MED19-overexpressing LNCaP cells. Interestingly, alternative MED19 cells displayed strong colony formation in clonogenic assays under conditions of androgen deprivation, while canonical MED19 cells did not, suggesting distinct functional roles. These isoforms also modulated gene expression differently. Canonical MED19 triggered genes related to extracellular matrix remodeling while suppressing those involved in androgen-inactivating glucuronidation. In contrast, alternative MED19 elevated genes tied to cell movement and reduced those associated with cell adhesion and differentiation. The ratio of MED19 isoform expression in prostate cancers shifts with the disease stage. Early-stage cancers exhibit higher canonical MED19 expression than alternative MED19, consistent with canonical MED19's ability to promote cell proliferation under androgen deprivation. Conversely, alternative MED19 levels were higher in later-stage metastatic prostate cancer than in canonical MED19, reflecting alternative MED19's capability to enhance cell migration and autonomous cell growth. Our findings suggest that MED19 isoforms play unique roles in prostate cancer progression and highlights MED19 as a potential therapeutic target for both early and late-stage prostate cancer.
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