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Cell Jan 2022The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human...
The liver is the largest solid organ in the body, yet it remains incompletely characterized. Here we present a spatial proteogenomic atlas of the healthy and obese human and murine liver combining single-cell CITE-seq, single-nuclei sequencing, spatial transcriptomics, and spatial proteomics. By integrating these multi-omic datasets, we provide validated strategies to reliably discriminate and localize all hepatic cells, including a population of lipid-associated macrophages (LAMs) at the bile ducts. We then align this atlas across seven species, revealing the conserved program of bona fide Kupffer cells and LAMs. We also uncover the respective spatially resolved cellular niches of these macrophages and the microenvironmental circuits driving their unique transcriptomic identities. We demonstrate that LAMs are induced by local lipid exposure, leading to their induction in steatotic regions of the murine and human liver, while Kupffer cell development crucially depends on their cross-talk with hepatic stellate cells via the evolutionarily conserved ALK1-BMP9/10 axis.
Topics: Animals; Biological Evolution; Cell Nucleus; Fatty Liver; Hepatocytes; Homeostasis; Humans; Kupffer Cells; Leukocyte Common Antigens; Lipids; Liver; Lymphocytes; Macrophages; Mice, Inbred C57BL; Models, Biological; Myeloid Cells; Obesity; Proteogenomics; Proteome; Signal Transduction; Transcriptome; Mice
PubMed: 35021063
DOI: 10.1016/j.cell.2021.12.018 -
Nature Reviews. Cancer May 2022Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of... (Review)
Review
Genomic analyses in cancer have been enormously impactful, leading to the identification of driver mutations and development of targeted therapies. But the functions of the vast majority of somatic mutations and copy number variants in tumours remain unknown, and the causes of resistance to targeted therapies and methods to overcome them are poorly defined. Recent improvements in mass spectrometry-based proteomics now enable direct examination of the consequences of genomic aberrations, providing deep and quantitative characterization of tumour tissues. Integration of proteins and their post-translational modifications with genomic, epigenomic and transcriptomic data constitutes the new field of proteogenomics, and is already leading to new biological and diagnostic knowledge with the potential to improve our understanding of malignant transformation and therapeutic outcomes. In this Review we describe recent developments in proteogenomics and key findings from the proteogenomic analysis of a wide range of cancers. Considerations relevant to the selection and use of samples for proteogenomics and the current technologies used to generate, analyse and integrate proteomic with genomic data are described. Applications of proteogenomics in translational studies and immuno-oncology are rapidly emerging, and the prospect for their full integration into therapeutic trials and clinical care seems bright.
Topics: DNA Copy Number Variations; Genomics; Humans; Neoplasms; Proteogenomics; Proteomics
PubMed: 35236940
DOI: 10.1038/s41568-022-00446-5 -
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 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 -
Cell Jul 2020Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of...
Lung cancer in East Asia is characterized by a high percentage of never-smokers, early onset and predominant EGFR mutations. To illuminate the molecular phenotype of this demographically distinct disease, we performed a deep comprehensive proteogenomic study on a prospectively collected cohort in Taiwan, representing early stage, predominantly female, non-smoking lung adenocarcinoma. Integrated genomic, proteomic, and phosphoproteomic analysis delineated the demographically distinct molecular attributes and hallmarks of tumor progression. Mutational signature analysis revealed age- and gender-related mutagenesis mechanisms, characterized by high prevalence of APOBEC mutational signature in younger females and over-representation of environmental carcinogen-like mutational signatures in older females. A proteomics-informed classification distinguished the clinical characteristics of early stage patients with EGFR mutations. Furthermore, integrated protein network analysis revealed the cellular remodeling underpinning clinical trajectories and nominated candidate biomarkers for patient stratification and therapeutic intervention. This multi-omic molecular architecture may help develop strategies for management of early stage never-smoker lung adenocarcinoma.
Topics: Adenocarcinoma of Lung; Biomarkers, Tumor; Carcinogens; Cohort Studies; Cytosine Deaminase; Disease Progression; Asia, Eastern; Gene Expression Regulation, Neoplastic; Gene Regulatory Networks; Genome, Human; Humans; Lung Neoplasms; Matrix Metalloproteinases; Mutation; Principal Component Analysis; Proteogenomics; Smoking
PubMed: 32649875
DOI: 10.1016/j.cell.2020.06.012 -
Protein and Peptide Letters 2021
Topics: Computational Biology; Proteogenomics; Proteome
PubMed: 34525913
DOI: 10.2174/092986652808210810142049 -
Immunological Medicine Jun 2019T cells recognize antigen peptides displayed by HLA molecules and specifically eliminate their target cells. Identification of responsible antigens as well as... (Review)
Review
T cells recognize antigen peptides displayed by HLA molecules and specifically eliminate their target cells. Identification of responsible antigens as well as understanding the mechanism by which antigens are produced inside cells are equally crucial for cancer immunology. In this review, we introduce proteogenomics and its applications in cancer antigen research, which leverages mass spectrometry and next-generation sequencing. The approach comprehensively captures immunopeptidome displayed by HLA, revealing new classes of antigens, such as mutation-derived neoantigens, spliced peptides, and non-coding region derived peptides. These antigens may serve as therapeutic targets or biomarkers. Thus, proteogenomics is a promising approach for cancer antigen research and contributes to immunotherapy development.
Topics: Antigens, Neoplasm; HLA Antigens; Humans; Immunotherapy; Mass Spectrometry; Mutation; Neoplasms; Proteogenomics
PubMed: 31318319
DOI: 10.1080/25785826.2019.1640500 -
Cell Reports Jun 2022We analyze transposable elements (TEs) in glioblastoma (GBM) patients using a proteogenomic pipeline that combines single-cell transcriptomics, bulk RNA sequencing...
We analyze transposable elements (TEs) in glioblastoma (GBM) patients using a proteogenomic pipeline that combines single-cell transcriptomics, bulk RNA sequencing (RNA-seq) samples from tumors and healthy-tissue cohorts, and immunopeptidomic samples. We thus identify 370 human leukocyte antigen (HLA)-I-bound peptides encoded by TEs differentially expressed in GBM. Some of the peptides are encoded by repeat sequences from intact open reading frames (ORFs) present in up to several hundred TEs from recent long interspersed nuclear element (LINE)-1, long terminal repeat (LTR), and SVA subfamilies. Other HLA-I-bound peptides are encoded by single copies of TEs from old subfamilies that are expressed recurrently in GBM tumors and not expressed, or very infrequently and at low levels, in healthy tissues (including brain). These peptide-coding, GBM-specific, highly recurrent TEs represent potential tumor-specific targets for cancer immunotherapies.
Topics: DNA Transposable Elements; Glioblastoma; Histocompatibility Antigens Class I; Humans; Peptides; Proteogenomics; RNA-Seq
PubMed: 35675780
DOI: 10.1016/j.celrep.2022.110916 -
Sheng Wu Gong Cheng Xue Bao = Chinese... Oct 2022Cancer is a heterogeneous disease with complex mechanisms that requires targeted precision medicine strategies. The growth of precision medicine is indispensable from... (Review)
Review
Cancer is a heterogeneous disease with complex mechanisms that requires targeted precision medicine strategies. The growth of precision medicine is indispensable from the rapid development of genomics. However, genomics has certain limitations in molecular phenotype analysis, proteogenomics thus arose at the right time. Proteogenomics is the merging of proteomics and genomics. This review describes the limitations of genomic analysis and highlights the importance of proteogenomics to re-understand precision oncology from a proteogenomic perspective. In addition, the application of proteogenomics in precision oncology is briefly introduced, the related public data projects are described, and finally, the challenges that need to be addressed at this stage are proposed.
Topics: Humans; Proteogenomics; Precision Medicine; Neoplasms; Proteomics; Genomics
PubMed: 36305397
DOI: 10.13345/j.cjb.220528 -
Clinica Chimica Acta; International... Nov 2019One of the best-established area within multi-omics is proteogenomics, whereby the underpinning technologies are next-generation sequencing (NGS) and mass spectrometry... (Review)
Review
One of the best-established area within multi-omics is proteogenomics, whereby the underpinning technologies are next-generation sequencing (NGS) and mass spectrometry (MS). Proteogenomics has contributed significantly to genome (re)-annotation, whereby novel coding sequences (CDS) are identified and confirmed. By incorporating in-silico translated genome variants in protein database, single amino acid variants (SAAV) and splice proteoforms can be identified and quantified at peptide level. The application of proteogenomics in cancer research potentially enables the identification of patient-specific proteoforms, as well as the association of the efficacy or resistance of cancer therapy to different mutations. Here, we discuss how NGS/TGS data are analyzed and incorporated into the proteogenomic framework. These sequence data mainly originate from whole genome sequencing (WGS), whole exome sequencing (WES) and RNA-Seq. We explain two major strategies for sequence analysis i.e., de novo assembly and reads mapping, followed by construction of customized protein databases using such data. Besides, we also elaborate on the procedures of spectrum to peptide sequence matching in proteogenomics, and the relationship between database size on the false discovery rate (FDR). Finally, we discuss the latest development in proteogenomics-assisted precision oncology and also challenges and opportunities in proteogenomics research.
Topics: Animals; High-Throughput Nucleotide Sequencing; Humans; Mass Spectrometry; Precision Medicine; Proteogenomics; Proteomics
PubMed: 31421119
DOI: 10.1016/j.cca.2019.08.010