ProteomicsPub Date : 2026-10-18DOI: 10.1002/pmic.70199
{"title":"Meet the Editorial Team. An Interview With Garry Corthals, Editor-in-Chief, Proteomics and Proteomics Clinical Applications, University of Amsterdam, Amsterdam, Netherlands.","authors":"","doi":"10.1002/pmic.70199","DOIUrl":"10.1002/pmic.70199","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70199"},"PeriodicalIF":4.1,"publicationDate":"2026-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149214773","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-16DOI: 10.1002/pmic.70197
Qinxin Zhang, Fan Chen, Yong Dai, Wei Zhang
{"title":"Integrated Multiomics Profiling Reveals Membrane-Associated Signaling Alterations Associated With Disease Activity in Systemic Lupus Erythematosus.","authors":"Qinxin Zhang, Fan Chen, Yong Dai, Wei Zhang","doi":"10.1002/pmic.70197","DOIUrl":"https://doi.org/10.1002/pmic.70197","url":null,"abstract":"<p><p>Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by pervasive immune dysregulation, yet membrane-associated molecular alterations in immune cells remain incompletely defined. Here, we performed integrated proteomic and phosphoproteomic profiling of peripheral blood mononuclear cells (PBMCs) from a self-established cohort of 130 SLE patients across disease stages and 90 healthy controls, with individual samples pooled into 36 samples for LC-MS/MS analysis, complemented by publicly available transcriptomic data from 1461 SLE patients. Focusing on membrane-associated proteins, we identified alterations in protein abundance and phosphorylation involving cytoskeletal organization, cell adhesion, and membrane trafficking, with the RHO GTPase cycle consistently enriched in both omic layers. Dynamic multisite phosphorylation of FLNA and increased abundance of FLNB and FNBP1 were observed. Clustering revealed distinct disease-stage-associated patterns involving integrin proteins in SLE in remission (SLE_R) and cytoskeletal and mechanotransduction components in active SLE (SLE_A). OAS3 and IFIT5 showed concordant transcript-protein changes, while interferon- and NF-κB-related transcriptional programs were implicated. Computational kinase analysis identified disease-stage-associated predicted activity patterns involving PKC, MAPKs, CDKs, and CaM-Ks. Together, these findings provide a multiomics view of membrane-associated molecular alterations associated with disease activity in SLE.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70197"},"PeriodicalIF":4.1,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149190448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Advancing Cancer Biomarker Discovery Through Multi-Omics, Bioinformatics, and Artificial Intelligence: A Systematic Review.","authors":"Pendy Tok, Vijayan Manickam-Achari, Siow-Wee Chang","doi":"10.1002/pmic.70196","DOIUrl":"https://doi.org/10.1002/pmic.70196","url":null,"abstract":"<p><p>The rapid accumulation of multi-omics data provides increasing opportunities for cancer biomarker discovery, but the heterogeneity and high dimensionality of these datasets remain major challenges for data integration and analysis. This review examines the application of bioinformatics and artificial intelligence for multi-omics integration in cancer biomarker research. Common multi-omics data paradigms and integration strategies are discussed, followed by a review of the bioinformatics, machine learning and deep learning approaches applied across 84 included studies. Cross-study comparison showed limited recurrence among the reported biomarkers, with only 15 biomarkers identified in at least four studies. Further assessment of the 13 recurrent protein-coding biomarkers showed significant protein-protein interaction enrichment and functional convergence in cancer-related processes, particularly PI3K/AKT and ERBB2-related signaling. This review also highlights current challenges, including missing data, heterogeneity across datasets, limited independent validation and the interpretability of artificial intelligence models. Future research may benefit from integrating multi-omics data with clinical information, pathological imaging, electronic health records, single-cell multi-omics and radiomics, together with broader datasets and greater use of independent validation to support the translation of multi-omics biomarker findings into clinical applications.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70196"},"PeriodicalIF":4.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149190435","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-15DOI: 10.1002/pmic.70193
{"title":"Meet the Editorial Team. An Interview With Laura Elo, Associate Editor, Proteomics and Proteomics Clinical Applications, University of Turku, Turku, Finland.","authors":"","doi":"10.1002/pmic.70193","DOIUrl":"https://doi.org/10.1002/pmic.70193","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70193"},"PeriodicalIF":4.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149190481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-15DOI: 10.1002/pmic.70194
{"title":"Meet the Editorial Team. An Interview With Eva Cuypers, Associate Editor, Proteomics and Proteomics Clinical Applications, Maastricht University, Maastricht, Netherlands.","authors":"","doi":"10.1002/pmic.70194","DOIUrl":"https://doi.org/10.1002/pmic.70194","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70194"},"PeriodicalIF":4.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149190471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-15DOI: 10.1002/pmic.70195
Lang Ding, Hanfeng Lin, Cuizhen Huang, Viruthika Vallanadu, Kelly Ashley, Scarlett Rose Pitts, Ayse Sena Mutlu, Yue Zhou, Xing Ma, Jong Min Choi, Feng Jin, Jin Wang, Meng C Wang
{"title":"Comparative Proteomic Quantification Reveals Novel Longevity Regulators.","authors":"Lang Ding, Hanfeng Lin, Cuizhen Huang, Viruthika Vallanadu, Kelly Ashley, Scarlett Rose Pitts, Ayse Sena Mutlu, Yue Zhou, Xing Ma, Jong Min Choi, Feng Jin, Jin Wang, Meng C Wang","doi":"10.1002/pmic.70195","DOIUrl":"https://doi.org/10.1002/pmic.70195","url":null,"abstract":"<p><p>Proteomics is a powerful tool for profiling the protein landscape underlying cellular and physiological processes. Advances in mass spectrometry-based methods, such as tandem mass tags (TMT) isobaric labeling-based proteomics at both MS2 and MS3, label-free quantification (LFQ) with data-dependent acquisition (DDA) or data-independent acquisition (DIA)-based proteomics, and stable isotope labeling with amino acid (SILAC) spike-in-assisted proteomics, enable quantitative proteome comparisons across biological conditions. These five quantitative proteomic methods offer distinct advantages in coverage, throughput, and quantitative reproducibility. Here, we treated them as orthogonal approaches, retaining protein candidates with significant, consistent-direction changes supported across multiple independently instrumented methods to identify high-confidence protein-level changes associated with longevity. Insulin/insulin-like growth factor signaling (IIS) is a highly conserved longevity regulatory pathway from Caenorhabditis elegans to humans. By quantitatively profiling IIS mutants in C. elegans and performing genetic screening, we obtained a systems-view of proteomic changes linked to longevity and identified new longevity regulators. This systematic cross-method comparison also serves as a valuable resource for guiding the selection of quantitative proteomics approaches.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70195"},"PeriodicalIF":4.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149190468","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-15DOI: 10.1002/pmic.70192
{"title":"Meet the Editorial Team. An Interview with Aleksandra Nita-Lazar, Associate Editor, Proteomics and Proteomics Clinical Applications, NIH, Bethesda, MD, USA.","authors":"","doi":"10.1002/pmic.70192","DOIUrl":"https://doi.org/10.1002/pmic.70192","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70192"},"PeriodicalIF":4.1,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149190418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-14DOI: 10.1002/pmic.70191
{"title":"Meet the Editorial Team. An Interview With Prof David Greening, Associate Editor, Proteomics, Baker Heart and Diabetes Institute, Melbourne, Australia.","authors":"","doi":"10.1002/pmic.70191","DOIUrl":"https://doi.org/10.1002/pmic.70191","url":null,"abstract":"","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70191"},"PeriodicalIF":4.1,"publicationDate":"2026-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149178415","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-12DOI: 10.1002/pmic.70189
Claudia Sissely Chaviano-Montes de Oca, Violeta Larios-Serrato, María Luisa Labra-Barrios, Emmanuel Ríos-Castro, Carlos Alberto Castañón-Sánchez, Rodolfo Moreno-Castillo, Erika Beatriz Ángeles-Morales, Juan Pedro Luna-Arias
{"title":"Proteomic Analysis of Mixed Cell Membrane Extracts From Triple-Negative Breast Cancer Cell Lines Revealed Broad Metabolic Reprogramming Associated With Tumor Progression.","authors":"Claudia Sissely Chaviano-Montes de Oca, Violeta Larios-Serrato, María Luisa Labra-Barrios, Emmanuel Ríos-Castro, Carlos Alberto Castañón-Sánchez, Rodolfo Moreno-Castillo, Erika Beatriz Ángeles-Morales, Juan Pedro Luna-Arias","doi":"10.1002/pmic.70189","DOIUrl":"https://doi.org/10.1002/pmic.70189","url":null,"abstract":"<p><p>Triple-negative breast cancer (TNBC) represents the most aggressive subtype with limited therapeutic options and the poorest clinical outcomes. Using high-resolution nUPLC-QTOF-MS/MS, we performed comprehensive proteomic profiling of TNBC cell lines representing disease progression stages: HCC-1937 (stage IIB), HCC-1599 (stage IIIA), and MDA-MB-231 (stage IV), benchmarked against nontumorigenic MCF-12F cells. From 11,864 initially detected proteins, 5623 high-confidence proteins were retained after quality filtering, spanning a dynamic range of six orders of magnitude. Differential abundance protein analysis identified distinct stage-associated proteomics profiles, finding 381, 490, and 550 differentially abundant proteins (DAPs) in HCC-1937, HCC-1599, and MDA-MB-231, respectively, with no shared DAPs among the three TNBC cell lines. Sparse PLS-DA and k-means clustering analyses showed distinct clustering patterns among TNBC cell lines. STRING network topology analysis uncovered dysregulated hubs in oxidative phosphorylation, mitochondrial electron transport chain complexes, including multiple subunits of Complex I (NDUFB3, NDUFB9, NDUFB10, NDUFB11), Complex III (UQCRC1, UQCRC2, UQCRB, UQCRFS1), and Complex IV (COX4I1, MT-CO2) in HCC-1937 and MDA-MB-231 cells, glycolytic enzymes, and cytoskeletal remodeling proteins. Functional enrichment analysis revealed significant alterations in metabolic pathways, including coordinated upregulation of glycolysis-associated proteins and downregulation of oxidative phosphorylation-related proteins. Cancer hallmark analysis identified enrichment in tissue invasion/metastasis (FDR < 0.001), immune evasion, genomic instability, and inflammatory signaling across all TNBC stages. The mitochondrial ribosomal proteins MRPL24, MRPL49, MRPL58, MRPS18B, and MRPS34 were found downregulated, which likely impairs assembly of functional respiratory chain complexes across multiple TNBC lines, which provides mechanistic insight into the observed OXPHOS suppression. In addition, the coordinated downregulation of PMPCA, the mitochondrial processing peptidase and TOMM22 and TIMM10, which are members of the mitochondrial import machinery, also contributes to the impaired mitochondrial function. These stage-resolved proteomics landscapes provide mechanistic insights into TNBC progression and identify potential therapeutic vulnerabilities and prognostic biomarker candidates for precision oncology. Data are available via ProteomeXchange with identifier PXD071351.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70189"},"PeriodicalIF":4.1,"publicationDate":"2026-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149164366","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
ProteomicsPub Date : 2026-10-08DOI: 10.1002/pmic.70190
Barbara Kracher, Giada Marino, Thomas Wild, Yannick Cogne, Till Kindel, Marion Tondeur, Marie Guillemot, Andreas Tebbe, François Autelitano, Carleen Kluger, Samira Vautrin
{"title":"Bead-Based Enrichment Methods for Unbiased Secretome Profiling Enable Unprecedented Protein Coverage in an Immune Cell Model.","authors":"Barbara Kracher, Giada Marino, Thomas Wild, Yannick Cogne, Till Kindel, Marion Tondeur, Marie Guillemot, Andreas Tebbe, François Autelitano, Carleen Kluger, Samira Vautrin","doi":"10.1002/pmic.70190","DOIUrl":"https://doi.org/10.1002/pmic.70190","url":null,"abstract":"<p><p>Bead-based enrichment strategies for low-abundance proteins in biofluids, followed by LC-MS/MS analysis, have dramatically increased the coverage of the serum and plasma proteome. These technologies effectively mitigate the dynamic range limitations imposed by high-abundance proteins like albumin, thereby facilitating the detection of low-abundance proteins. Here, we demonstrate that bead-based enrichment strategies are also disrupting the field of secretomics by enabling easy access to thousands of proteins released into the cell-conditioned media, even in the presence of physiologically relevant growth supplements, such as fetal bovine serum. Using lipopolysaccharide-stimulated THP-1 human acute monocytic leukemia cells as a model of inflammatory activation, we demonstrate that two independent bead-based enrichment platforms, ENRICH-iST and Proteograph, enable comprehensive characterization of secreted proteins in the conditioned media. Application of these approaches provided novel insights into the regulation of cytokine and chemokine signaling pathways that remained inaccessible without enrichment, even when employing labor-intensive and time-consuming deep fractionation workflows. Taken together, these findings underscore the potential of bead-based enrichment methods to overcome long-standing limitations in secretome analysis, offering a scalable and efficient route to uncover complex signaling networks with direct relevance to both fundamental biology and translational research.</p>","PeriodicalId":224,"journal":{"name":"Proteomics","volume":" ","pages":"e70190"},"PeriodicalIF":4.1,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149134369","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}