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Nature Cancer Jun 2024Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new...
Multiple myeloma (MM) is a plasma cell malignancy of the bone marrow. Despite therapeutic advances, MM remains incurable, and better risk stratification as well as new therapies are therefore highly needed. The proteome of MM has not been systematically assessed before and holds the potential to uncover insight into disease biology and improved prognostication in addition to genetic and transcriptomic studies. Here we provide a comprehensive multiomics analysis including deep tandem mass tag-based quantitative global (phospho)proteomics, RNA sequencing, and nanopore DNA sequencing of 138 primary patient-derived plasma cell malignancies encompassing treatment-naive MM, plasma cell leukemia and the premalignancy monoclonal gammopathy of undetermined significance, as well as healthy controls. We found that the (phospho)proteome of malignant plasma cells are highly deregulated as compared with healthy plasma cells and is both defined by chromosomal alterations as well as posttranscriptional regulation. A prognostic protein signature was identified that is associated with aggressive disease independent of established risk factors in MM. Integration with functional genetics and single-cell RNA sequencing revealed general and genetic subtype-specific deregulated proteins and pathways in plasma cell malignancies that include potential targets for (immuno)therapies. Our study demonstrates the potential of proteogenomics in cancer and provides an easily accessible resource for investigating protein regulation and new therapeutic approaches in MM.
PubMed: 38942927
DOI: 10.1038/s43018-024-00784-3 -
Oncology Letters Aug 2024Lung metastasis is the second most common type of metastasis in colorectal cancer. Specific treatments for lung metastasis have not been developed since the underlying...
Lung metastasis is the second most common type of metastasis in colorectal cancer. Specific treatments for lung metastasis have not been developed since the underlying mechanisms are poorly understood. The present study aimed to elucidate the molecular basis of lung metastasis in colorectal cancer. In a mouse model, cell lines that were highly metastatic to the lungs were established by injecting colorectal cancer cells through the tail vein and removing them from the lungs. Differential gene expression comparing the transfected cells with their parental cells was investigated using DNA microarrays. The results were functionally interpreted using gene enrichment analysis and validated using reverse transcription-quantitative PCR (RT-qPCR). The isoforms of the identified genes were examined by melting curve analysis. The present study established colorectal cancer cell lines that were highly metastatic to the lungs. DNA microarray experiments revealed that genes (N-cadherin, VE-cadherin, , Akt and VCAM1) involved in motility, proliferation and adhesion were upregulated, and genes ( and ) with tumor-suppressive functions were downregulated in metastatic cells. () expression was upregulated in multiple metastatic cell lines using RT-qPCR. Two isoforms were overexpressed in metastatic cells. and models were established and genes associated with lung metastasis were identified to overcome the heterogeneity of the disease. Overall, aberrant expression is unreported in lung metastasis in colorectal cancer. In the present study, two isoforms with differential tissue distribution were upregulated in metastatic cells, suggesting that they promote lung metastasis in colorectal cancer.
PubMed: 38939626
DOI: 10.3892/ol.2024.14514 -
Genes Jun 2024The high-throughput proteomics data generated by increasingly more sensible mass spectrometers greatly contribute to our better understanding of molecular and cellular...
The high-throughput proteomics data generated by increasingly more sensible mass spectrometers greatly contribute to our better understanding of molecular and cellular mechanisms operating in live beings. Nevertheless, proteomics analyses are based on accurate genomic and protein annotations, and some information may be lost if these resources are incomplete. Here, we show that most proteomics data may be recovered by interconnecting genomics and proteomics approaches (i.e., following a proteogenomic strategy), resulting, in turn, in an improvement of gene/protein models. In this study, we generated proteomics data from (HU3 strain) promastigotes that allowed us to detect 1908 proteins in this developmental stage on the basis of the currently annotated proteins available in public databases. However, when the proteomics data were searched against all possible open reading frames existing in the genome, twenty new protein-coding genes could be annotated. Additionally, 43 previously annotated proteins were extended at their N-terminal ends to accommodate peptides detected in the proteomics data. Also, different post-translational modifications (phosphorylation, acetylation, methylation, among others) were found to occur in a large number of proteins. Finally, a detailed comparative analysis of the and experimental proteomes served to illustrate how inaccurate conclusions can be raised if proteomes are compared solely on the basis of the listed proteins identified in each proteome. Finally, we have created data entries (based on freely available repositories) to provide and maintain updated gene/protein models. Raw data are available via ProteomeXchange with the identifier PXD051920.
Topics: Leishmania donovani; Proteogenomics; Protozoan Proteins; Genome, Protozoan; Protein Processing, Post-Translational; Proteomics; Proteome; Molecular Sequence Annotation
PubMed: 38927711
DOI: 10.3390/genes15060775 -
Biomolecules Jun 2024As an essential component of modern drug discovery, the role of drug-target identification is growing increasingly prominent. Additionally, single-omics technologies... (Review)
Review
As an essential component of modern drug discovery, the role of drug-target identification is growing increasingly prominent. Additionally, single-omics technologies have been widely utilized in the process of discovering drug targets. However, it is difficult for any single-omics level to clearly expound the causal connection between drugs and how they give rise to the emergence of complex phenotypes. With the progress of large-scale sequencing and the development of high-throughput technologies, the tendency in drug-target identification has shifted towards integrated multi-omics techniques, gradually replacing traditional single-omics techniques. Herein, this review centers on the recent advancements in the domain of integrated multi-omics techniques for target identification, highlights the common multi-omics analysis strategies, briefly summarizes the selection of multi-omics analysis tools, and explores the challenges of existing multi-omics analyses, as well as the applications of multi-omics technology in drug-target identification.
Topics: Humans; Genomics; Drug Discovery; Proteomics; Metabolomics; Computational Biology; Multiomics
PubMed: 38927095
DOI: 10.3390/biom14060692 -
Current Oncology (Toronto, Ont.) May 2024Epithelial ovarian cancer (EOC) has not significantly benefited from advances in immunotherapy, mainly because of the lack of well-defined actionable antigen targets....
Epithelial ovarian cancer (EOC) has not significantly benefited from advances in immunotherapy, mainly because of the lack of well-defined actionable antigen targets. Using proteogenomic analyses of primary EOC tumors, we previously identified 91 aberrantly expressed tumor-specific antigens (TSAs) originating from unmutated genomic sequences. Most of these TSAs derive from non-exonic regions, and their expression results from cancer-specific epigenetic changes. The present study aimed to evaluate the immunogenicity of 48 TSAs selected according to two criteria: presentation by highly prevalent HLA allotypes and expression in a significant fraction of EOC tumors. Using targeted mass spectrometry analyses, we found that pulsing with synthetic TSA peptides leads to a high-level presentation on dendritic cells. TSA abundance correlated with the predicted binding affinity to the HLA allotype. We stimulated naïve CD8 T cells from healthy blood donors with TSA-pulsed dendritic cells and assessed their expansion with two assays: MHC-peptide tetramer staining and TCR Vβ CDR3 sequencing. We report that these TSAs can expand sizeable populations of CD8 T cells and, therefore, represent attractive targets for EOC immunotherapy.
Topics: Humans; Female; Antigens, Neoplasm; Ovarian Neoplasms; Dendritic Cells; Carcinoma, Ovarian Epithelial; CD8-Positive T-Lymphocytes; Immunotherapy
PubMed: 38920720
DOI: 10.3390/curroncol31060236 -
Cell Jun 2024Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium...
Fewer than 200 proteins are targeted by cancer drugs approved by the Food and Drug Administration (FDA). We integrate Clinical Proteomic Tumor Analysis Consortium (CPTAC) proteogenomics data from 1,043 patients across 10 cancer types with additional public datasets to identify potential therapeutic targets. Pan-cancer analysis of 2,863 druggable proteins reveals a wide abundance range and identifies biological factors that affect mRNA-protein correlation. Integration of proteomic data from tumors and genetic screen data from cell lines identifies protein overexpression- or hyperactivation-driven druggable dependencies, enabling accurate predictions of effective drug targets. Proteogenomic identification of synthetic lethality provides a strategy to target tumor suppressor gene loss. Combining proteogenomic analysis and MHC binding prediction prioritizes mutant KRAS peptides as promising public neoantigens. Computational identification of shared tumor-associated antigens followed by experimental confirmation nominates peptides as immunotherapy targets. These analyses, summarized at https://targets.linkedomics.org, form a comprehensive landscape of protein and peptide targets for companion diagnostics, drug repurposing, and therapy development.
PubMed: 38917788
DOI: 10.1016/j.cell.2024.05.039 -
BioRxiv : the Preprint Server For... Jun 2024PARP1 (ARTD1) and Tankyrases (TNKS1/TNKS2; PARP5a/5b) are poly-ADP-ribose polymerases (PARPs) with catalytic and non-catalytic functions that regulate both the genome...
PARP1 (ARTD1) and Tankyrases (TNKS1/TNKS2; PARP5a/5b) are poly-ADP-ribose polymerases (PARPs) with catalytic and non-catalytic functions that regulate both the genome and proteome during zygotic genome activation (ZGA), totipotent, and pluripotent embryonic stages. Here, we show that primed, conventional human pluripotent stem cells (hPSC) cultured continuously under non-specific TNKS1/TNKS2/PARP1-inhibited chemical naive reversion conditions underwent epigenetic reprogramming to clonal blastomere-like stem cells. TIRN stem cells concurrently expressed hundreds of gene targets of the ZGA-priming pioneer factor DUX4, as well as a panoply of four-cell (4C)-specific (e.g., TPRXL, HOX clusters), eight-cell (8C)-specific (e.g., DUXA, GSC, GATA6), primitive endoderm-specific (e.g., GATA4, SOX17), trophectoderm-specific (e.g., CDX2, TFAP2C), and naive epiblast-specific (e.g., DNMT3L, NANOG, POU5F1(OCT4)) factors; all in a hybrid, combinatorial single-cell manner. Mapping of proteomic and single-cell expressions of TIRN cells against human preimplantation embryo references identified them as relatively homogenous 4C-8C stage populations. Injection of TIRN cells into murine 8C-16C-staged embryos resulted in efficient totipotent-like single cell contributions of human cells to both extra-embryonic (trophectoderm, placenta) and embryonic (neural, fetal liver, hematopoietic) lineages in human-murine blastocyst and fetal chimeras. Pairing of proteome with ubiquitinome analyses of TIRN cells revealed a global shutdown of ADP-ribosylation, and a perturbed TNKS/PARP1 equilibrium which not only impacted the protein levels of hundreds of TNKS/PARP1 substrates via a rewiring of the ubiquitin-proteosome system (UPS), but also de-repressed expression of hundreds of developmental genes associated with PARP1 suppression. ChIP-Seq analysis of core NANOG-SOX2-OCT4 (NSO) pluripotency factors in TIRN cells identified reprogrammed DUX4-accessible distal and cis-regulatory enhancer regions that were co-bound by PARP1 (NSOP). These NSOP enhancer regions possessed co-binding motifs for hundreds of the same ZGA-associated, embryonic, and extraembryonic lineage-specifying pioneer factors (e.g., HOX, FOX, GATA, SOX, TBX, CDX families) that were concurrently co-expressed in TIRN cells; suggesting that PARP1 and DUX4 cooperate with NSO pluripotency core factors to regulate the epigenetic plasticity of a human totipotency program. These findings provide the first demonstration that global, proteome-wide perturbations of post-translational modifications (i.e., ADP-ribosylation, ubiquitination) can regulate epigenetic reprogramming during human embryogenesis. Totipotent TIRN stem cells will provide a valuable cell culture model for studying the proteogenomic regulation of lineage specification from human blastomere stages and may facilitate the efficient generation of human organs in interspecies chimeras.
PubMed: 38915486
DOI: 10.1101/2024.06.14.598510 -
The Journal of Pain Jun 2024Numerous genome-wide association studies have identified risk genes for chronic pain, yet the mechanisms by which genetic variants modify susceptibility have remained...
Numerous genome-wide association studies have identified risk genes for chronic pain, yet the mechanisms by which genetic variants modify susceptibility have remained elusive. We sought to identify key genes modulating chronic pain risk by regulating brain protein expression. We integrated brain proteomic data with the largest genome-wide dataset for multisite chronic pain (N=387,649) in a proteome-wide association study (PWAS) using discovery and confirmatory proteomic datasets (N=376 and 152) from the dorsolateral prefrontal cortex (dPFC). Leveraging summary data-based Mendelian randomization (SMR) and Bayesian colocalization analysis (COLOC), we pinpointed potential causal genes, while a transcriptome-wide association study (TWAS) integrating 452 human brain transcriptomes investigated whether cis-effects on protein abundance extended to the transcriptome. Single-cell RNA sequencing data and single-nucleus transcriptomic data revealed cell-type specific expression patterns for identified causal genes in the dPFC and dorsal root ganglia (DRG), complemented by RNA microarray analysis of expression profiles in other pain-related brain regions. Of the 22 genes cis-regulating protein abundance identified by the discovery PWAS, 18 (82%) were deemed causal by SMR or COLOC analyses, with 7 of these 18 genes (39%) replicating in the confirmatory PWAS, including GMPPB, which also associated at the transcriptome level. Several causal genes exhibited selective expression in excitatory neurons, inhibitory neurons, oligodendrocytes, and astrocytes, while most identified genes were expressed across additional pain-related brain regions. This integrative proteogenomic approach identified 18 high-confidence causal genes for chronic pain, regulated by cis-effects on brain protein levels, suggesting promising avenues for treatment research and indicating a contributory role for the DRG. PERSPECTIVE: The current post-GWAS analyses identified 18 high-confidence causal genes regulating chronic pain risk via cis-modulation of brain protein abundance, suggesting promising avenues for future chronic pain therapies. Additionally, the significant expression of these genes in the DRG indicated a potential contributory role, warranting further investigation.
PubMed: 38909833
DOI: 10.1016/j.jpain.2024.104610 -
Cancer Cell Jun 2024Multiple myeloma (MM) is an incurable plasma cell malignancy that exploits transcriptional networks driven by IRF4. We employ a multi-omics approach to discover IRF4...
Multiple myeloma (MM) is an incurable plasma cell malignancy that exploits transcriptional networks driven by IRF4. We employ a multi-omics approach to discover IRF4 vulnerabilities, integrating functional genomics screening, spatial proteomics, and global chromatin mapping. ARID1A, a member of the SWI/SNF chromatin remodeling complex, is required for IRF4 expression and functionally associates with IRF4 protein on chromatin. Deleting Arid1a in activated murine B cells disrupts IRF4-dependent transcriptional networks and blocks plasma cell differentiation. Targeting SWI/SNF activity leads to rapid loss of IRF4-target gene expression and quenches global amplification of oncogenic gene expression by MYC, resulting in profound toxicity to MM cells. Notably, MM patients with aggressive disease bear the signature of SWI/SNF activity, and SMARCA2/4 inhibitors remain effective in immunomodulatory drug (IMiD)-resistant MM cells. Moreover, combinations of SWI/SNF and MEK inhibitors demonstrate synergistic toxicity to MM cells, providing a promising strategy for relapsed/refractory disease.
PubMed: 38906156
DOI: 10.1016/j.ccell.2024.05.026 -
Molecular & Cellular Proteomics : MCP Jun 2024Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide...
Rescoring of peptide spectrum matches originating from database search engines enabled by peptide property predictors is exceeding the performance of peptide identification from traditional database search engines. In contrast to the peptide spectrum match scores calculated by traditional database search engines, rescoring peptide spectrum matches generates scores based on comparing observed and predicted peptide properties, such as fragment ion intensities and retention times. These newly generated scores enable a more efficient discrimination between correct and incorrect peptide spectrum matches. This approach was shown to lead to substantial improvements in the number of confidently identified peptides, facilitating the analysis of challenging datasets in various fields such as immunopeptidomics, metaproteomics, proteogenomics, and single-cell proteomics. In this review, we summarize the key elements leading up to the recent introduction of multiple data-driven rescoring pipelines. We provide an overview of relevant post-processing rescoring tools, introduce prominent data-driven rescoring pipelines for various applications, and highlight limitations, opportunities and future perspectives of this approach and its impact on mass spectrometry-based proteomics.
PubMed: 38871251
DOI: 10.1016/j.mcpro.2024.100798