Proteogenomics connects somatic mutations to signalling in breast cancer
Somatic mutations have been extensively characterized in breast cancer, but the effects of these genetic alterations on the proteomic landscape remain poorly understood. Here we describe quantitative mass-spectrometry-based proteomic and phosphoproteomic analyses of 105 genomically annotated breast cancers, of which 77 provided high-quality data. Integrated analyses provided insights into the somatic cancer genome including the consequences of chromosomal loss, such as the 5q deletion characteristic of basal-like breast cancer. Interrogation of the 5q trans-effects against the Library of Integrated Network-based Cellular Signatures, connected loss of CETN3 and SKP1 to elevated expression of epidermal growth factor receptor (EGFR), and SKP1 loss also to increased SRC tyrosine kinase. Global proteomic data confirmed a stromal-enriched group of proteins in addition to basal and luminal clusters, and pathway analysis of the phosphoproteome identified a G-protein-coupled receptor cluster that was not readily identified at the mRNA level. In addition to ERBB2, other amplicon-associated highly phosphorylated kinases were identified, including CDK12, PAK1, PTK2, RIPK2 and TLK2. We demonstrate that proteogenomic analysis of breast cancer elucidates the functional consequences of somatic mutations, narrows candidate nominations for driver genes within large deletions and amplified regions, and identifies therapeutic targets.
BlackSheep: A Bioconductor and Bioconda Package for Differential Extreme Value Analysis
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.
Distinct Features of Human Myeloid Cell Cytokine Response Profiles Identify Neutrophil Activation by Cytokines as a Prognostic Feature during Tuberculosis and Cancer
Myeloid cells are a vital component of innate immunity and comprise monocytes, macrophages, dendritic cells, and granulocytes. How myeloid cell lineage affects activation states in response to cytokines remains poorly understood. The cytokine environment and cellular infiltrate during an inflammatory response may contain prognostic features that predict disease outcome. In this study, we analyzed the transcriptional responses of human monocytes, macrophages, dendritic cells, and neutrophils in response to stimulation by IFN-Î³, IFN-Î², IFN-Î», IL-4, IL-13, and IL-10 cytokines to better understand the heterogeneity of activation states in inflammatory conditions. This generated a myeloid cell-cytokine-specific response matrix that can infer representation of myeloid cells and the cytokine environment they encounter during infection, in tumors and in whole blood. Neutrophils were highly responsive to type 1 and type 2 cytokine stimulation but did not respond to IL-10. We identified transcripts specific to IFN-Î² stimulation, whereas other IFN signature genes were upregulated by both IFN-Î³ and IFN-Î². When we used our matrix to deconvolute blood profiles from tuberculosis patients, the IFN-Î²-specific neutrophil signature was reduced in tuberculosis patients with active disease, whereas the shared response to IFN-Î³ and IFN-Î² in neutrophils was increased. When applied to glioma patients, transcripts of neutrophils exposed to IL-4/IL-13 and monocyte responses to IFN-Î³ or IFN-Î² emerged as opposing predictors of patient survival. Hence, by dissecting how different myeloid cells respond to cytokine activation, we can delineate biological roles for myeloid cells in different cytokine environments during disease processes, especially during infection and tumor progression.
Gene Expression Signature in Patients With Symptomatic Peripheral Artery Disease
OBJECTIVE:<0.05, |log2foldchange| >0.5) and analyzed using weighted gene co-expression network analysis. Weighted gene co-expression network analysis revealed blood modules enriched for immune activation, secretory granules, and coagulation in patients with PAD. Of these 127 differentially expressed transcripts, 40 were significantly associated with MACLE (log-rank false discovery rate <0.1). MicroRNA-4477b was significantly increased in patients with PAD with subsequent MACLE and in a mouse hindlimb ischemia model. CONCLUSIONS:A whole blood transcript signature identified patients with symptomatic PAD and PAD patients at increased risk of MACLE. A previously uncharacterized transcript microRNA-4477b was overexpressed in prevalent PAD, incident MACLE, and in a mouse hindlimb ischemia model. Our novel transcriptomic signature provides insight into potential mechanisms of patients with severe symptomatic PAD.
Platelets amplify endotheliopathy in COVID-19
[Figure: see text].
Proteogenomic Characterization of Endometrial Carcinoma
We undertook a comprehensive proteogenomic characterization of 95 prospectively collected endometrial carcinomas, comprising 83 endometrioid and 12 serous tumors. This analysis revealed possible new consequences of perturbations to the p53 and Wnt/Î²-catenin pathways, identified a potential role for circRNAs in the epithelial-mesenchymal transition, and provided new information about proteomic markers of clinical and genomic tumor subgroups, including relationships to known druggable pathways. An extensive genome-wide acetylation survey yielded insights into regulatory mechanisms linking Wnt signaling and histone acetylation. We also characterized aspects of the tumor immune landscape, including immunogenic alterations, neoantigens, common cancer/testis antigens, and the immune microenvironment, all of which can inform immunotherapy decisions. Collectively, our multi-omic analyses provide a valuable resource for researchers and clinicians, identify new molecular associations of potential mechanistic significance in the development of endometrial cancers, and suggest novel approaches for identifying potential therapeutic targets.
An analysis of the sensitivity of proteogenomic mapping of somatic mutations and novel splicing events in cancer
Improvements in mass spectrometry (MS)-based peptide sequencing provide a new opportunity to determine whether polymorphisms, mutations and splice variants identified in cancer cells are translated. Herein we apply a proteogenomic data integration tool (QUILTS) to illustrate protein variant discovery using whole genome, whole transcriptome and global proteome datasets generated from a pair of luminal and basal-like breast cancer patient derived xenografts (PDX). The sensitivity of proteogenomic analysis for singe nucleotide variant (SNV) expression and novel splice junction (NSJ) detection was probed using multiple MS/MS sample process replicates defined here as an independent tandem MS experiment using identical sample material. Despite analysis of over thirty sample process replicates, only about 10% of SNVs (somatic and germline) detected by both DNA and RNA sequencing were observed as peptides. An even smaller proportion of peptides corresponding to NSJ observed by RNA sequencing were detected (<0.1%). Peptides mapping to DNA-detected SNVs without a detectable mRNA transcript were also observed, suggesting that transcriptome coverage was incomplete (~80%). In contrast to germline variants, somatic variants were less likely to be detected at the peptide level in the basal-like tumor than in the luminal tumor raising the possibility of differential translation or protein degradation effects. In conclusion, this large-scale proteogenomic integration allowed us to determine the degree to which mutations are translated and identified gaps in sequence coverage, thereby benchmarking current technology and progress towards whole cancer proteome and transcriptome analysis.
A proteogenomic portrait of lung squamous cell carcinoma
Lung squamous cell carcinoma (LSCC) remains a leading cause of cancer death with few therapeutic options. We characterized the proteogenomic landscape of LSCC, providing a deeper exposition of LSCC biology with potential therapeutic implications. We identify NSD3 as an alternative driver in FGFR1-amplified tumors and low-p63 tumors overexpressing the therapeutic target survivin. SOX2 is considered undruggable, but our analyses provide rationale for exploring chromatin modifiers such as LSD1 and EZH2 to target SOX2-overexpressing tumors. Our data support complex regulation of metabolic pathways by crosstalk between post-translational modifications including ubiquitylation. Numerous immune-related proteogenomic observations suggest directions for further investigation. Proteogenomic dissection of CDKN2A mutations argue for more nuanced assessment of RB1 protein expression and phosphorylation before declaring CDK4/6 inhibition unsuccessful. Finally, triangulation between LSCC, LUAD, and HNSCC identified both unique and common therapeutic vulnerabilities. These observations and proteogenomics data resources may guide research into the biology and treatment of LSCC.
Staphylococcus aureus induces a muted host response in human blood that blunts the recruitment of neutrophils
Translational regulation of TFH cell differentiation and autoimmune pathogenesis
Little is known regarding T cell translational regulation. We demonstrate that T follicular helper (TFH) cells use a previously unknown mechanism of selective messenger RNA (mRNA) translation for their differentiation, role in B cell maturation, and in autoimmune pathogenesis. We show that TFH cells have much higher levels of translation factor eIF4E than non-TFH CD4+ T cells, which is essential for translation of TFH cell fate-specification mRNAs. Genome-wide translation studies indicate that modest down-regulation of eIF4E activity by a small-molecule inhibitor or short hairpin RN impairs TFH cell development and function. In mice, down-regulation of eIF4E activity specifically reduces TFH cells among T helper subtypes, germinal centers, B cell recruitment, and antibody production. In experimental autoimmune encephalomyelitis, eIF4E activity down-regulation blocks TFH cell participation in disease pathogenesis while promoting rapid remission and spinal cord remyelination. TFH cell development and its role in autoimmune pathogenesis involve selective mRNA translation that is highly druggable.