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Molecular & Cellular Proteomics : MCP Apr 2024Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as noncanonical major...
Discovering noncanonical peptides has been a common application of proteogenomics. Recent studies suggest that certain noncanonical peptides, known as noncanonical major histocompatibility complex-I (MHC-I)-associated peptides (ncMAPs), that bind to MHC-I may make good immunotherapeutic targets. De novo peptide sequencing is a great way to find ncMAPs since it can detect peptide sequences from their tandem mass spectra without using any sequence databases. However, this strategy has not been widely applied for ncMAP identification because there is not a good way to estimate its false-positive rates. In order to completely and accurately identify immunopeptides using de novo peptide sequencing, we describe a unique pipeline called proteomics X genomics. In contrast to current pipelines, it makes use of genomic data, RNA-Seq abundance and sequencing quality, in addition to proteomic features to increase the sensitivity and specificity of peptide identification. We show that the peptide-spectrum match quality and genetic traits have a clear relationship, showing that they can be utilized to evaluate peptide-spectrum matches. From 10 samples, we found 24,449 canonical MHC-I-associated peptides and 956 ncMAPs by using a target-decoy competition. Three hundred eighty-seven ncMAPs and 1611 canonical MHC-I-associated peptides were new identifications that had not yet been published. We discovered 11 ncMAPs produced from a squirrel monkey retrovirus in human cell lines in addition to the two ncMAPs originating from a complementarity determining region 3 in an antibody thanks to the unrestricted search space assumed by de novo sequencing. These entirely new identifications show that proteomics X genomics can make the most of de novo peptide sequencing's advantages and its potential use in the search for new immunotherapeutic targets.
Topics: Peptides; Histocompatibility Antigens Class I; Humans; Proteomics; RNA-Seq; Animals
PubMed: 38403075
DOI: 10.1016/j.mcpro.2024.100743 -
Journal of Proteomics Apr 2024Seed germination, a key initial event in the plant life cycle, directly affects cotton yield and quality. Gossypium barbadense and Gossypium hirsutum gradually evolved...
Seed germination, a key initial event in the plant life cycle, directly affects cotton yield and quality. Gossypium barbadense and Gossypium hirsutum gradually evolved through polyploidization, resulting in different characteristics, and this interspecific variation lacks genetic and molecular explanation. This work aimed to compare the proteomes between G. barbadense and G. hirsutum during seed germination. Here, we identified 2740 proteins for G. barbadense and 3758 for G. hirsutum. In the initial state, proteins in two cotton involved similar bioprocess, such as sugar metabolism, DNA repairing, and ABA signaling pathway. However, in the post-germination stage, G. hirsutum expressed more protein related to redox homeostasis, peroxidase activity, and pathogen interactions. Analyzing the different expression patterns of 915 single-copy orthogroups between the two kinds of cotton indicated that most of the differentially expressed proteins in G. barbadense were related to carbon metabolism. In contrast, most proteins in G. hirsutum were associated with stress response. Besides that, by proteogenomic analysis, we found 349 putative non-canonical peptides, which may be involved in plant development. These results will help to understand the different characteristics of these two kinds of cotton, such as fiber quality, yield, and adaptability. SIGNIFICANCE STATEMENT: Cotton is the predominant natural fiber crop worldwide; Gossypium barbadense and Gossypium hirsutum have evolved through polyploidization to produce differing traits. However, given their specific features, the divergence of mechanisms underlying seed germination between G. hirsutum and G. barbadense has not been discussed. Here, we explore what protein contributes to interspecific differences between G. barbadense and G. hirsutum during the seed germination period. This study helps to elucidate the evolution and domestication history of cotton polyploids and may allow breeders to understand their domestication history better and improve fiber quality and adaptability.
Topics: Gossypium; Germination; Proteomics; Seeds; Phenotype; Cotton Fiber
PubMed: 38401592
DOI: 10.1016/j.jprot.2024.105130 -
Cell Reports Feb 2024Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we...
Metastatic progression of colorectal adenocarcinoma (CRC) remains poorly understood and poses significant challenges for treatment. To overcome these challenges, we performed multiomics analyses of primary CRC and liver metastases. Genomic alterations, such as structural variants or copy number alterations, were enriched in oncogenes and tumor suppressor genes and increased in metastases. Unsupervised mass spectrometry-based proteomics of 135 primary and 123 metastatic CRCs uncovered distinct proteomic subtypes, three each for primary and metastatic CRCs, respectively. Integrated analyses revealed that hypoxia, stemness, and immune signatures characterize these 6 subtypes. Hypoxic CRC harbors high epithelial-to-mesenchymal transition features and metabolic adaptation. CRC with a stemness signature shows high oncogenic pathway activation and alternative telomere lengthening (ALT) phenotype, especially in metastatic lesions. Tumor microenvironment analysis shows immune evasion via modulation of major histocompatibility complex (MHC) class I/II and antigen processing pathways. This study characterizes both primary and metastatic CRCs and provides a large proteogenomics dataset of metastatic progression.
Topics: Humans; Proteogenomics; Proteome; Proteomics; Genomics; Colorectal Neoplasms; Histocompatibility Antigens Class II; Hypoxia; Tumor Microenvironment
PubMed: 38377004
DOI: 10.1016/j.celrep.2024.113810 -
Cell Feb 2024
PubMed: 38364782
DOI: 10.1016/j.cell.2024.01.016 -
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 -
International Journal of Cancer Jun 2024Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer...
Neoadjuvant chemo- or chemo-radiation-therapy of pancreatic ductal adenocarcinoma differentially shift ECM composition, complement activation, energy metabolism and ribosomal proteins of the residual tumor mass.
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, often diagnosed at stages that dis-qualify for surgical resection. Neoadjuvant therapies offer potential tumor regression and improved resectability. Although features of the tumor biology (e.g., molecular markers) may guide adjuvant therapy, biological alterations after neoadjuvant therapy remain largely unexplored. We performed mass spectrometry to characterize the proteomes of 67 PDAC resection specimens of patients who received either neoadjuvant chemo (NCT) or chemo-radiation (NCRT) therapy. We employed data-independent acquisition (DIA), yielding a proteome coverage in excess of 3500 proteins. Moreover, we successfully integrated two publicly available proteome datasets of treatment-naïve PDAC to unravel proteome alterations in response to neoadjuvant therapy, highlighting the feasibility of this approach. We found highly distinguishable proteome profiles. Treatment-naïve PDAC was characterized by enrichment of immunoglobulins, complement and extracellular matrix (ECM) proteins. Post-NCT and post-NCRT PDAC presented high abundance of ribosomal and metabolic proteins as compared to treatment-naïve PDAC. Further analyses on patient survival and protein expression identified treatment-specific prognostic candidates. We present the first proteomic characterization of the residual PDAC mass after NCT and NCRT, and potential protein candidate markers associated with overall survival. We conclude that residual PDAC exhibits fundamentally different proteome profiles as compared to treatment-naïve PDAC, influenced by the type of neoadjuvant treatment. These findings may impact adjuvant or targeted therapy options.
Topics: Humans; Neoadjuvant Therapy; Ribosomal Proteins; Proteome; Neoplasm, Residual; Proteomics; Pancreatic Neoplasms; Carcinoma, Pancreatic Ductal; Complement Activation; Energy Metabolism
PubMed: 38353498
DOI: 10.1002/ijc.34867 -
Proteomics Feb 2024Immunotherapy harnesses neoantigens encoded within the human genome, but their therapeutic potential is hampered by low expression, which may be controlled by the...
Immunotherapy harnesses neoantigens encoded within the human genome, but their therapeutic potential is hampered by low expression, which may be controlled by the nonsense-mediated mRNA decay (NMD) pathway. This study investigates the impact of UPF1-knockdown on the expression of non-canonical/mutant proteins, employing proteogenomic to explore UPF1 role within the NMD pathway. Additionally, we conducted a comprehensive pan-cancer analysis of UPF1 expression and evaluated UPF1 expression in Triple-Negative Breast Cancer (TNBC) tissue in-vivo. Our findings reveal that UPF1-knockdown leads to increased translation of non-canonical/mutant proteins, particularly those originating from retained-introns, pseudogenes, long non-coding RNAs, and unannotated transcript biotypes. Moreover, our analysis demonstrates elevated UPF1 expression in various cancer types, with notably heightened protein levels in patient-derived TNBC tumors compared to adjacent tissues. This study elucidates UPF1 role in mitigating transcriptional noise by degrading transcripts encoding non-canonical/mutant proteins. Targeting this mechanism may reveal a new spectrum of neoantigens accessible to the antigen presentation pathway. Our novel findings provide a strong foundation for the development of therapeutic strategies aimed at targeting UPF1 or modulating the NMD pathway.
PubMed: 38350726
DOI: 10.1002/pmic.202300361 -
Diabetologia May 2024Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its... (Review)
Review
Precision diabetes medicine (PDM) aims to reduce errors in prevention programmes, diagnosis thresholds, prognosis prediction and treatment strategies. However, its advancement and implementation are difficult due to the heterogeneity of complex molecular processes and environmental exposures that influence an individual's disease trajectory. To address this challenge, it is imperative to develop robust screening methods for all areas of PDM. Innovative proteomic technologies, alongside genomics, have proven effective in precision cancer medicine and are showing promise in diabetes research for potential translation. This narrative review highlights how proteomics is well-positioned to help improve PDM. Specifically, a critical assessment of widely adopted affinity-based proteomic technologies in large-scale clinical studies and evidence of the benefits and feasibility of using MS-based plasma proteomics is presented. We also present a case for the use of proteomics to identify predictive protein panels for type 2 diabetes subtyping and the development of clinical prediction models for prevention, diagnosis, prognosis and treatment strategies. Lastly, we discuss the importance of plasma and tissue proteomics and its integration with genomics (proteogenomics) for identifying unique type 2 diabetes intra- and inter-subtype aetiology. We conclude with a call for action formed on advancing proteomics technologies, benchmarking their performance and standardisation across sites, with an emphasis on data sharing and the inclusion of diverse ancestries in large cohort studies. These efforts should foster collaboration with key stakeholders and align with ongoing academic programmes such as the Precision Medicine in Diabetes Initiative consortium.
Topics: Humans; Proteomics; Diabetes Mellitus, Type 2; Precision Medicine; Genomics; Prognosis
PubMed: 38345659
DOI: 10.1007/s00125-024-06097-5 -
Cancers Jan 2024Triple-negative breast cancer (TNBC) is characterized by an aggressive clinical presentation and a paucity of clinically actionable genomic alterations. Here, we...
Triple-negative breast cancer (TNBC) is characterized by an aggressive clinical presentation and a paucity of clinically actionable genomic alterations. Here, we utilized the Cancer Genome Atlas (TCGA) to explore the proteogenomic landscape of TNBC subtypes to see whether genomic alterations can be inferred from proteomic data. We found only 4% of the protein level changes are explained by mutations, while 21% of the protein and 35% of the transcriptomics changes were determined by copy number alterations (CNAs). We found tighter coupling between proteome and genome in some genes that are predicted to be the targets of drug inhibitors, including CDKs, PI3K, tyrosine kinase (TKI), and mTOR. The validation of our proteogenomic workflow using mass spectrometry Clinical Proteomic Tumor Analysis Consortium (MS-CPTAC) data also demonstrated the highest correlation between protein-RNA-CNA. The integrated proteogenomic approach helps to prioritize potentially actionable targets and may enable the acceleration of personalized cancer treatment.
PubMed: 38339267
DOI: 10.3390/cancers16030516 -
Journal of Translational Medicine Feb 2024Neoantigens have emerged as a promising area of focus in tumor immunotherapy, with several established strategies aiming to enhance their identification. Human leukocyte...
BACKGROUND
Neoantigens have emerged as a promising area of focus in tumor immunotherapy, with several established strategies aiming to enhance their identification. Human leukocyte antigen class I molecules (HLA-I), which present intracellular immunopeptides to T cells, provide an ideal source for identifying neoantigens. However, solely relying on a mutation database generated through commonly used whole exome sequencing (WES) for the identification of HLA-I immunopeptides, may result in potential neoantigens being missed due to limitations in sequencing depth and sample quality.
METHOD
In this study, we constructed and evaluated an extended database for neoantigen identification, based on COSMIC mutation database. This study utilized mass spectrometry-based proteogenomic profiling to identify the HLA-I immunopeptidome enriched from HepG2 cell. HepG2 WES-based and the COSMIC-based mutation database were generated and utilized to identify HepG2-specific mutant immunopeptides.
RESULT
The results demonstrated that COSMIC-based database identified 5 immunopeptides compared to only 1 mutant peptide identified by HepG2 WES-based database, indicating its effectiveness in identifying mutant immunopeptides. Furthermore, HLA-I affinity of the mutant immunopeptides was evaluated through NetMHCpan and peptide-docking modeling to validate their binding to HLA-I molecules, demonstrating the potential of mutant peptides identified by the COSMIC-based database as neoantigens.
CONCLUSION
Utilizing the COSMIC-based mutation database is a more efficient strategy for identifying mutant peptides from HLA-I immunopeptidome without significantly increasing the false positive rate. HepG2 specific WES-based database may exclude certain mutant peptides due to WES sequencing depth or sample heterogeneity. The COSMIC-based database can effectively uncover potential neoantigens within the HLA-I immunopeptidomes.
Topics: Humans; Antigens, Neoplasm; Histocompatibility Antigens Class I; Mutation; Peptides; T-Lymphocytes; Databases, Genetic
PubMed: 38336780
DOI: 10.1186/s12967-023-04821-0