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Cell Aug 2023Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our...
Cancer driver events refer to key genetic aberrations that drive oncogenesis; however, their exact molecular mechanisms remain insufficiently understood. Here, our multi-omics pan-cancer analysis uncovers insights into the impacts of cancer drivers by identifying their significant cis-effects and distal trans-effects quantified at the RNA, protein, and phosphoprotein levels. Salient observations include the association of point mutations and copy-number alterations with the rewiring of protein interaction networks, and notably, most cancer genes converge toward similar molecular states denoted by sequence-based kinase activity profiles. A correlation between predicted neoantigen burden and measured T cell infiltration suggests potential vulnerabilities for immunotherapies. Patterns of cancer hallmarks vary by polygenic protein abundance ranging from uniform to heterogeneous. Overall, our work demonstrates the value of comprehensive proteogenomics in understanding the functional states of oncogenic drivers and their links to cancer development, surpassing the limitations of studying individual cancer types.
Topics: Humans; Proteogenomics; Neoplasms; Oncogenes; Cell Transformation, Neoplastic; DNA Copy Number Variations
PubMed: 37582357
DOI: 10.1016/j.cell.2023.07.014 -
Cell Aug 2023To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and...
To improve the understanding of chemo-refractory high-grade serous ovarian cancers (HGSOCs), we characterized the proteogenomic landscape of 242 (refractory and sensitive) HGSOCs, representing one discovery and two validation cohorts across two biospecimen types (formalin-fixed paraffin-embedded and frozen). We identified a 64-protein signature that predicts with high specificity a subset of HGSOCs refractory to initial platinum-based therapy and is validated in two independent patient cohorts. We detected significant association between lack of Ch17 loss of heterozygosity (LOH) and chemo-refractoriness. Based on pathway protein expression, we identified 5 clusters of HGSOC, which validated across two independent patient cohorts and patient-derived xenograft (PDX) models. These clusters may represent different mechanisms of refractoriness and implicate putative therapeutic vulnerabilities.
Topics: Female; Humans; Cystadenocarcinoma, Serous; Ovarian Neoplasms; Proteogenomics
PubMed: 37541199
DOI: 10.1016/j.cell.2023.07.004 -
Cancer Cell Aug 2023The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics... (Review)
Review
The National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium (CPTAC) investigates tumors from a proteogenomic perspective, creating rich multi-omics datasets connecting genomic aberrations to cancer phenotypes. To facilitate pan-cancer investigations, we have generated harmonized genomic, transcriptomic, proteomic, and clinical data for >1000 tumors in 10 cohorts to create a cohesive and powerful dataset for scientific discovery. We outline efforts by the CPTAC pan-cancer working group in data harmonization, data dissemination, and computational resources for aiding biological discoveries. We also discuss challenges for multi-omics data integration and analysis, specifically the unique challenges of working with both nucleotide sequencing and mass spectrometry proteomics data.
Topics: Humans; Proteogenomics; Proteomics; Genomics; Neoplasms; Gene Expression Profiling
PubMed: 37582339
DOI: 10.1016/j.ccell.2023.06.009 -
Cell Aug 2023Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable...
Post-translational modifications (PTMs) play key roles in regulating cell signaling and physiology in both normal and cancer cells. Advances in mass spectrometry enable high-throughput, accurate, and sensitive measurement of PTM levels to better understand their role, prevalence, and crosstalk. Here, we analyze the largest collection of proteogenomics data from 1,110 patients with PTM profiles across 11 cancer types (10 from the National Cancer Institute's Clinical Proteomic Tumor Analysis Consortium [CPTAC]). Our study reveals pan-cancer patterns of changes in protein acetylation and phosphorylation involved in hallmark cancer processes. These patterns revealed subsets of tumors, from different cancer types, including those with dysregulated DNA repair driven by phosphorylation, altered metabolic regulation associated with immune response driven by acetylation, affected kinase specificity by crosstalk between acetylation and phosphorylation, and modified histone regulation. Overall, this resource highlights the rich biology governed by PTMs and exposes potential new therapeutic avenues.
Topics: Humans; Acetylation; Histones; Neoplasms; Phosphorylation; Protein Processing, Post-Translational; Proteomics
PubMed: 37582358
DOI: 10.1016/j.cell.2023.07.013 -
Science Translational Medicine Jul 2023Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics...
Organoid models have the potential to recapitulate the biological and pharmacotypic features of parental tumors. Nevertheless, integrative pharmaco-proteogenomics analysis for drug response features and biomarker investigation for precision therapy of patients with liver cancer are still lacking. We established a patient-derived liver cancer organoid biobank (LICOB) that comprehensively represents the histological and molecular characteristics of various liver cancer types as determined by multiomics profiling, including genomic, epigenomic, transcriptomic, and proteomic analysis. Proteogenomic profiling of LICOB identified proliferative and metabolic organoid subtypes linked to patient prognosis. High-throughput drug screening revealed distinct response patterns of each subtype that were associated with specific multiomics signatures. Through integrative analyses of LICOB pharmaco-proteogenomics data, we identified the molecular features associated with drug responses and predicted potential drug combinations for personalized patient treatment. The synergistic inhibition effect of mTOR inhibitor temsirolimus and the multitargeted tyrosine kinase inhibitor lenvatinib was validated in organoids and patient-derived xenografts models. We also provide a user-friendly web portal to help serve the biomedical research community. Our study is a rich resource for investigation of liver cancer biology and pharmacological dependencies and may help enable functional precision medicine.
Topics: Humans; Proteogenomics; Proteomics; Precision Medicine; Liver Neoplasms; Organoids
PubMed: 37494474
DOI: 10.1126/scitranslmed.adg3358 -
Nature Oct 2023The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we...
The Pharma Proteomics Project is a precompetitive biopharmaceutical consortium characterizing the plasma proteomic profiles of 54,219 UK Biobank participants. Here we provide a detailed summary of this initiative, including technical and biological validations, insights into proteomic disease signatures, and prediction modelling for various demographic and health indicators. We present comprehensive protein quantitative trait locus (pQTL) mapping of 2,923 proteins that identifies 14,287 primary genetic associations, of which 81% are previously undescribed, alongside ancestry-specific pQTL mapping in non-European individuals. The study provides an updated characterization of the genetic architecture of the plasma proteome, contextualized with projected pQTL discovery rates as sample sizes and proteomic assay coverages increase over time. We offer extensive insights into trans pQTLs across multiple biological domains, highlight genetic influences on ligand-receptor interactions and pathway perturbations across a diverse collection of cytokines and complement networks, and illustrate long-range epistatic effects of ABO blood group and FUT2 secretor status on proteins with gastrointestinal tissue-enriched expression. We demonstrate the utility of these data for drug discovery by extending the genetic proxied effects of protein targets, such as PCSK9, on additional endpoints, and disentangle specific genes and proteins perturbed at loci associated with COVID-19 susceptibility. This public-private partnership provides the scientific community with an open-access proteomics resource of considerable breadth and depth to help to elucidate the biological mechanisms underlying proteo-genomic discoveries and accelerate the development of biomarkers, predictive models and therapeutics.
Topics: Humans; ABO Blood-Group System; Biological Specimen Banks; Blood Proteins; COVID-19; Databases, Factual; Drug Discovery; Epistasis, Genetic; Fucosyltransferases; Genetic Predisposition to Disease; Genomics; Health; Plasma; Proprotein Convertase 9; Proteome; Proteomics; Public-Private Sector Partnerships; Quantitative Trait Loci; United Kingdom; Galactoside 2-alpha-L-fucosyltransferase
PubMed: 37794186
DOI: 10.1038/s41586-023-06592-6 -
Blood Cancer Discovery Jul 2023The safety and efficacy of combining the isocitrate dehydrogenase-1 (IDH1) inhibitor ivosidenib (IVO) with the BCL2 inhibitor venetoclax (VEN; IVO + VEN) ± azacitidine...
UNLABELLED
The safety and efficacy of combining the isocitrate dehydrogenase-1 (IDH1) inhibitor ivosidenib (IVO) with the BCL2 inhibitor venetoclax (VEN; IVO + VEN) ± azacitidine (AZA; IVO + VEN + AZA) were evaluated in four cohorts of patients with IDH1-mutated myeloid malignancies (n = 31). Most (91%) adverse events were grade 1 or 2. The maximal tolerated dose was not reached. Composite complete remission with IVO + VEN + AZA versus IVO + VEN was 90% versus 83%. Among measurable residual disease (MRD)-evaluable patients (N = 16), 63% attained MRD--negative remissions; IDH1 mutation clearance occurred in 64% of patients receiving ≥5 treatment cycles (N = 14). Median event-free survival and overall survival were 36 [94% CI, 23-not reached (NR)] and 42 (95% CI, 42-NR) months. Patients with signaling gene mutations appeared to particularly benefit from the triplet regimen. Longitudinal single-cell proteogenomic analyses linked cooccurring mutations, antiapoptotic protein expression, and cell maturation to therapeutic sensitivity of IDH1-mutated clones. No IDH isoform switching or second-site IDH1 mutations were observed, indicating combination therapy may overcome established resistance pathways to single-agent IVO.
SIGNIFICANCE
IVO + VEN + AZA is safe and active in patients with IDH1-mutated myeloid malignancies. Combination therapy appears to overcome resistance mechanisms observed with single-agent IDH-inhibitor use, with high MRD-negative remission rates. Single-cell DNA ± protein and time-of-flight mass-cytometry analysis revealed complex resistance mechanisms at relapse, highlighting key pathways for future therapeutic intervention. This article is highlighted in the In This Issue feature, p. 247.
Topics: Humans; Neoplasm Recurrence, Local; Antineoplastic Agents; Azacitidine; Isocitrate Dehydrogenase
PubMed: 37102976
DOI: 10.1158/2643-3230.BCD-22-0205 -
Cell Feb 2024Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune...
Despite the successes of immunotherapy in cancer treatment over recent decades, less than <10%-20% cancer cases have demonstrated durable responses from immune checkpoint blockade. To enhance the efficacy of immunotherapies, combination therapies suppressing multiple immune evasion mechanisms are increasingly contemplated. To better understand immune cell surveillance and diverse immune evasion responses in tumor tissues, we comprehensively characterized the immune landscape of more than 1,000 tumors across ten different cancers using CPTAC pan-cancer proteogenomic data. We identified seven distinct immune subtypes based on integrative learning of cell type compositions and pathway activities. We then thoroughly categorized unique genomic, epigenetic, transcriptomic, and proteomic changes associated with each subtype. Further leveraging the deep phosphoproteomic data, we studied kinase activities in different immune subtypes, which revealed potential subtype-specific therapeutic targets. Insights from this work will facilitate the development of future immunotherapy strategies and enhance precision targeting with existing agents.
Topics: Humans; Combined Modality Therapy; Genomics; Neoplasms; Proteogenomics; Proteomics; Tumor Escape
PubMed: 38359819
DOI: 10.1016/j.cell.2024.01.027 -
Cancer Cell Sep 2023We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted...
We characterized a prospective endometrial carcinoma (EC) cohort containing 138 tumors and 20 enriched normal tissues using 10 different omics platforms. Targeted quantitation of two peptides can predict antigen processing and presentation machinery activity, and may inform patient selection for immunotherapy. Association analysis between MYC activity and metformin treatment in both patients and cell lines suggests a potential role for metformin treatment in non-diabetic patients with elevated MYC activity. PIK3R1 in-frame indels are associated with elevated AKT phosphorylation and increased sensitivity to AKT inhibitors. CTNNB1 hotspot mutations are concentrated near phosphorylation sites mediating pS45-induced degradation of β-catenin, which may render Wnt-FZD antagonists ineffective. Deep learning accurately predicts EC subtypes and mutations from histopathology images, which may be useful for rapid diagnosis. Overall, this study identified molecular and imaging markers that can be further investigated to guide patient stratification for more precise treatment of EC.
Topics: Female; Humans; Proto-Oncogene Proteins c-akt; Prospective Studies; Proteogenomics; Endometrial Neoplasms; beta Catenin; Metformin
PubMed: 37567170
DOI: 10.1016/j.ccell.2023.07.007 -
Cell Reports. Medicine Sep 2023We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with...
We introduce a pioneering approach that integrates pathology imaging with transcriptomics and proteomics to identify predictive histology features associated with critical clinical outcomes in cancer. We utilize 2,755 H&E-stained histopathological slides from 657 patients across 6 cancer types from CPTAC. Our models effectively recapitulate distinctions readily made by human pathologists: tumor vs. normal (AUROC = 0.995) and tissue-of-origin (AUROC = 0.979). We further investigate predictive power on tasks not normally performed from H&E alone, including TP53 prediction and pathologic stage. Importantly, we describe predictive morphologies not previously utilized in a clinical setting. The incorporation of transcriptomics and proteomics identifies pathway-level signatures and cellular processes driving predictive histology features. Model generalizability and interpretability is confirmed using TCGA. We propose a classification system for these tasks, and suggest potential clinical applications for this integrated human and machine learning approach. A publicly available web-based platform implements these models.
Topics: Humans; Proteogenomics; Deep Learning; Neoplasms; Proteomics; Machine Learning
PubMed: 37582371
DOI: 10.1016/j.xcrm.2023.101173