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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 -
Nature Oct 2023Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets. Because previous proteogenomic...
Integrating human genomics and proteomics can help elucidate disease mechanisms, identify clinical biomarkers and discover drug targets. Because previous proteogenomic studies have focused on common variation via genome-wide association studies, the contribution of rare variants to the plasma proteome remains largely unknown. Here we identify associations between rare protein-coding variants and 2,923 plasma protein abundances measured in 49,736 UK Biobank individuals. Our variant-level exome-wide association study identified 5,433 rare genotype-protein associations, of which 81% were undetected in a previous genome-wide association study of the same cohort. We then looked at aggregate signals using gene-level collapsing analysis, which revealed 1,962 gene-protein associations. Of the 691 gene-level signals from protein-truncating variants, 99.4% were associated with decreased protein levels. STAB1 and STAB2, encoding scavenger receptors involved in plasma protein clearance, emerged as pleiotropic loci, with 77 and 41 protein associations, respectively. We demonstrate the utility of our publicly accessible resource through several applications. These include detailing an allelic series in NLRC4, identifying potential biomarkers for a fatty liver disease-associated variant in HSD17B13 and bolstering phenome-wide association studies by integrating protein quantitative trait loci with protein-truncating variants in collapsing analyses. Finally, we uncover distinct proteomic consequences of clonal haematopoiesis (CH), including an association between TET2-CH and increased FLT3 levels. Our results highlight a considerable role for rare variation in plasma protein abundance and the value of proteogenomics in therapeutic discovery.
Topics: Humans; Alleles; Biological Specimen Banks; Biomarkers; Blood Proteins; Databases, Factual; Exome; Genetic Association Studies; Genomics; Hematopoiesis; Mutation; Plasma; Proteomics; United Kingdom
PubMed: 37794183
DOI: 10.1038/s41586-023-06547-x -
Cell Reports Oct 2023Understanding the mechanisms underlying cancer gene expression is critical for precision oncology. Posttranscriptional regulation is a key determinant of protein...
Understanding the mechanisms underlying cancer gene expression is critical for precision oncology. Posttranscriptional regulation is a key determinant of protein abundance and cancer cell behavior. However, to what extent posttranscriptional regulatory mechanisms impact protein levels and cancer progression is an ongoing question. Here, we exploit cancer proteogenomics data to systematically compare mRNA-protein correlations across 14 different human cancer types. We identify two clusters of genes with particularly low mRNA-protein correlations across all cancer types, shed light on the role of posttranscriptional regulation of cancer driver genes and drug targets, and unveil a cohort of 55 mutations that alter systems-wide posttranscriptional regulation. Surprisingly, we find that decreased levels of posttranscriptional control in patients correlate with shorter overall survival across multiple cancer types, prompting further mechanistic studies into how posttranscriptional regulation affects patient outcomes. Our findings underscore the importance of a comprehensive understanding of the posttranscriptional regulatory landscape for predicting cancer progression.
Topics: Humans; Neoplasms; Precision Medicine; Gene Expression Regulation; RNA, Messenger
PubMed: 37742190
DOI: 10.1016/j.celrep.2023.113172 -
Annual Review of Pharmacology and... Jan 2024Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding... (Review)
Review
Proteogenomics refers to the integration of comprehensive genomic, transcriptomic, and proteomic measurements from the same samples with the goal of fully understanding the regulatory processes converting genotypes to phenotypes, often with an emphasis on gaining a deeper understanding of disease processes. Although specific genetic mutations have long been known to drive the development of multiple cancers, gene mutations alone do not always predict prognosis or response to targeted therapy. The benefit of proteogenomics research is that information obtained from proteins and their corresponding pathways provides insight into therapeutic targets that can complement genomic information by providing an additional dimension regarding the underlying mechanisms and pathophysiology of tumors. This review describes the novel insights into tumor biology and drug resistance derived from proteogenomic analysis while highlighting the clinical potential of proteogenomic observations and advances in technique and analysis tools.
Topics: Humans; Precision Medicine; Proteogenomics; Proteomics; Genomics; Mass Spectrometry
PubMed: 37738504
DOI: 10.1146/annurev-pharmtox-022723-113921 -
Scientific Data Sep 2023Proteogenomic methodologies have enabled the identification of protein sequences in wild species without annotated genomes, shedding light on molecular mechanisms...
Proteogenomic methodologies have enabled the identification of protein sequences in wild species without annotated genomes, shedding light on molecular mechanisms affected by pollution. However, proteomic resources for sentinel species are limited, and organ-level investigations are necessary to expand our understanding of their molecular biology. This study presents proteomic resources obtained from proteogenomic analyses of key organs (hepatopancreas, gills, hemolymph) from three established aquatic sentinel invertebrate species of interest in ecotoxicological/ecological research and environmental monitoring: Gammarus fossarum, Dreissena polymorpha, and Palaemon serratus. Proteogenomic analyses identified thousands of proteins for each species, with over 90% of them being annotated to putative function. Functional analysis validated the relevance of the proteomic atlases by revealing similarities in functional annotation of catalogues of proteins across analogous organs in the three species, while deep contrasts between functional profiles are delimited across different organs in the same organism. These organ-level proteomic atlases are crucial for future research on these sentinel animals, aiding in the evaluation of aquatic environmental risks and providing a valuable resource for ecotoxicological studies.
Topics: Animals; Amino Acid Sequence; Invertebrates; Proteogenomics; Proteomics; Sentinel Species
PubMed: 37735452
DOI: 10.1038/s41597-023-02545-w -
NPJ Precision Oncology Sep 2023Immune checkpoint inhibitor (ICI) therapy has had limited success (<30%) in treating metastatic recurrent Head and Neck Oropharyngeal Squamous Cell Carcinomas (OPSCCs)....
Immune checkpoint inhibitor (ICI) therapy has had limited success (<30%) in treating metastatic recurrent Head and Neck Oropharyngeal Squamous Cell Carcinomas (OPSCCs). We postulate that spatial determinants in the tumor play a critical role in cancer therapy outcomes. Here, we describe the case of a male patient diagnosed with p16 OPSCC and extensive lung metastatic disease who failed Nivolumab and Pembrolizumab/Lenvatinib therapies. Using advanced integrative spatial proteogenomic analysis on the patient's recurrent OPSCC tumors we demonstrate that: (i) unbiased tissue clustering based on spatial transcriptomics (ST) successfully detected tumor cells and enabled the investigation of phenotypic traits such as proliferation or drug-resistance genes in the tumor's leading-edge and core; (ii) spatial proteomic imagining used in conjunction with ST (SpiCi, Spatial Proteomics inferred Cell identification) can resolve the profiling of tumor infiltrating immune cells, (iii) ST data allows for the discovery and ranking of clinically relevant alternative medicines based on their interaction with their matching ligand-receptor. Importantly, when the spatial profiles of ICI pre- and post-failure OPSCC tumors were compared, they exhibited highly similar PD-1/PD-L1 and VEGFA expression, suggesting that these new tumors were not the product of ICI resistance but rather of Lenvatinib dose reduction due to complications. Our work establishes a path for incorporating spatial-omics in clinical settings to facilitate treatment personalization.
PubMed: 37704757
DOI: 10.1038/s41698-023-00444-2 -
Nature Communications Sep 2023The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC...
The progression of urothelial bladder cancer (UC) is a complicated multi-step process. We perform a comprehensive multi-omics analysis of 448 samples from 190 UC patients, covering the whole spectrum of disease stages and grades. Proteogenomic integration analysis indicates the mutations of HRAS regulated mTOR signaling to form urothelial papilloma rather than papillary urothelial cancer (PUC). DNA damage is a key signaling pathway in the progression of carcinoma in situ (CIS) and related to APOBEC signature. Glucolipid metabolism increase and lower immune cell infiltration are associated with PUC compared to CIS. Proteomic analysis distinguishes the origins of invasive tumors (PUC-derived and CIS-derived), related to distinct clinical prognosis and molecular features. Additionally, loss of RBPMS, associated with CIS-derived tumors, is validated to increase the activity of AP-1 and promote metastasis. This study reveals the characteristics of two distinct branches (PUC and CIS) of UC progression and may eventually benefit clinical practice.
Topics: Humans; Proteogenomics; Proteomics; Urinary Bladder Neoplasms; Carcinoma, Transitional Cell; Carcinoma in Situ; Carcinoma, Papillary
PubMed: 37704624
DOI: 10.1038/s41467-023-41139-3 -
Nature Communications Sep 2023Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data...
Both proteome and transcriptome data can help assess the relevance of non-coding somatic mutations in cancer. Here, we combine mass spectrometry-based proteomics data with whole genome sequencing data across 1307 human tumors spanning various tissues to determine the extent somatic structural variant (SV) breakpoint patterns impact protein expression of nearby genes. We find that about 25% of the hundreds of genes with SV-associated cis-regulatory alterations at the mRNA level are similarly associated at the protein level. SVs associated with enhancer hijacking, retrotransposon translocation, altered DNA methylation, or fusion transcripts are implicated in protein over-expression. SVs combined with altered protein levels considerably extend the numbers of patients with tumors somatically altered for critical pathways. We catalog both SV breakpoint patterns involving patient survival and genes with nearby SV breakpoints associated with increased cell dependency in cancer cell lines. Pan-cancer proteogenomics identifies targetable non-coding alterations, by virtue of the associated deregulated genes.
Topics: Humans; Proteome; Neoplasms; Cell Line; DNA Methylation; Mass Spectrometry
PubMed: 37704602
DOI: 10.1038/s41467-023-41374-8 -
Medical Research Archives Aug 2023Obesity and old age are commonly assumed to be risk factors for COVID-19 mortality. On a worldwide basis, we examine quantitative measures of obesity and elderly in the...
OBJECTIVES
Obesity and old age are commonly assumed to be risk factors for COVID-19 mortality. On a worldwide basis, we examine quantitative measures of obesity and elderly in the populations of individual countries and territories, and investigate whether these measures are predictive of COVID-19 mortality in those countries. In particular, we highlight regional differences relative to obesity and elderly metrics, and how these relate to COVID-19 mortality.
METHODS
In this retrospective, population-based study, we obtained data relating to percentages of obese or elderly individuals in 199 countries, as well as COVID-19 mortality rates in these countries. We used negative binomial regression analyses to assess associations between COVID-19 mortality rates and the putative risk factors, in six regions - Africa, Asia, Europe, North America, Oceania, and South America.
RESULTS
We found significant differences between regions relative to COVID-19 mortality, as well as obesity and elderly population proportions. There were also substantial differences between countries within regions relative to proportions of obesity and elderly individuals, and COVID-19 mortality.
CONCLUSIONS
There are significant differences both between regions and within regions relative to COVID-19 mortality rates, as well as proportions of obese or elderly individuals. A global pronouncement that obesity and elderly constitute definitive risk factors for COVID-19 mortality masks the subtleties engendered by these intra- and inter-regional differences.
PubMed: 37674672
DOI: 10.18103/mra.v11i8.4248 -
Journal of Proteome Research Oct 2023Precision medicine focuses on adapting care to the individual profile of patients, for example, accounting for their unique genetic makeup. Being able to account for the...
Precision medicine focuses on adapting care to the individual profile of patients, for example, accounting for their unique genetic makeup. Being able to account for the effect of genetic variation on the proteome holds great promise toward this goal. However, identifying the protein products of genetic variation using mass spectrometry has proven very challenging. Here we show that the identification of variant peptides can be improved by the integration of retention time and fragmentation predictors into a unified proteogenomic pipeline. By combining these intrinsic peptide characteristics using the search-engine post-processor Percolator, we demonstrate improved discrimination power between correct and incorrect peptide-spectrum matches. Our results demonstrate that the drop in performance that is induced when expanding a protein sequence database can be compensated, hence enabling efficient identification of genetic variation products in proteomics data. We anticipate that this enhancement of proteogenomic pipelines can provide a more refined picture of the unique proteome of patients and thereby contribute to improving patient care.
PubMed: 37656829
DOI: 10.1021/acs.jproteome.3c00243