Molecular & Cellular Proteomics最新文献

{"title":"The soluble HLA repertoire captures neoantigenic, cryptic, and tumour-associated peptides in melanoma.","authors":"Gabriel Goncalves, Jordan W Conway, Tima Shamekhi, Joel R Steele, Jayden Beckwith, Scott A Blundell, Erwin Tanuwidjaya, Ralf B Schittenhelm, Georgina V Long, Ines Pires da Silva, Pouya Faridi","doi":"10.1016/j.mcpro.2026.101684","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101684","url":null,"abstract":"<p><p>Melanoma is a highly immunogenic malignancy in which T cell recognition of HLA-presented peptides plays a central role in tumour control. While immunopeptidomics has enabled detailed characterisation of melanoma antigen repertoires, its clinical application is limited by restricted access to tumour tissue. Soluble HLA (sHLA) complexes in circulation present a potential minimally invasive alternative. However, the extent to which circulating HLA repertoires reflect tumour-derived antigen presentation remains unclear. Here, we applied an optimised SAPrIm workflow coupled with Orbitrap Astral mass spectrometry to analyse the immunopeptidome of matched tumour tissue and plasma samples from five melanoma patients collected at the time of tumour resection. We identified 6,590-17,690 non-redundant HLA-I peptides from tumour tissue (5-25 mg input) and 5,213-10,089 non-redundant HLA peptides from plasma-derived sHLA complexes (200-571 μL input within the volume of a routine biobank aliquot). Plasma-derived sHLA ligandomes retained key features of membrane-bound tumour HLA-I presentation, including dominant 9-mer peptide length distributions and conserved HLA-binding characteristics. Peptide recovery was strongly concordant between compartments following normalisation (Pearson r = 0.92), indicating that ligandome depth and recovery were primarily driven by intrinsic biological variation rather than sample input. Tumour-associated antigens were consistently detected in circulating sHLA peptides. Cryptic peptides derived from \"peptideins\" were preserved in circulation and comprised approximately 1% of the total repertoire. Somatic patient-specific variant calling revealed a candidate neo-peptide is also preserved and presented in sHLA. To assess tumour specificity and biomarker potential, identified HLA peptides were mapped to their corresponding source proteins and compared against healthy sHLA and benign tissue reference datasets. This analysis identified 247 candidate melanoma-associated source proteins not detected in healthy plasma or benign tissue reference datasets. Among these, 9 source proteins were recurrently detected across at least 4 of 5 patients, representing priority candidates for further biomarker validation. In this proof-of-concept study of five matched patients, these findings indicate that circulating sHLA ligandomes preserve core features of tumour antigen presentation and provide proof-of-concept support for plasma immunopeptidomics as a minimally invasive approach for antigen discovery and biomarker hypothesis generation.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101684"},"PeriodicalIF":6.3,"publicationDate":"2026-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149228298","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Two-Dimensional Size-Exclusion Chromatography-Based Isolation and Characterization of Plasma-Derived Extracellular Vesicle Subpopulations from Prostate Cancer Patients.","authors":"Alan J Zimmerman, Getulio Pereira de Oliveira, Jacqueline Wood, Maya Bowden, Mandy E Turner, Elena Aikawa, Jennifer C Jones, Ionita Ghiran, Alexander R Ivanov","doi":"10.1016/j.mcpro.2026.101682","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101682","url":null,"abstract":"<p><p>Extracellular vesicles (EVs) collectively include nanosized vesicles and particles (condensates) that are released by cells and tissues and are circulated in blood and other physiological fluids. Their biomolecular cargo modulates key molecular and cellular pathways, rendering them a critical biological medium for advancing both diagnostic clinical applications and fundamental biology research. However, it is challenging to isolate highly heterogeneous EVs from complex biological matrices and fractionate EVs into subpopulations. A novel and straightforward two-dimensional size-exclusion chromatography (2D-SEC) approach for plasma-derived EV isolation and fractionation was developed as an alternative to existing low-purity EV isolation methods. The technique presented here enabled the isolation of EV subpopulation-enriched fractions while further depleting high-abundance plasma contaminants, resulting in improved detection of low-abundance EV-associated proteins. Furthermore, plasma-derived EV subpopulation-enriched fractions were isolated from prostate cancer (PCa) and healthy donors. The EV subpopulation-enriched fractions were subjected to mass spectrometry-based quantitative proteomic analysis to assess the presence of PCa- and tumor-associated proteins. Results show that deeper proteomic profiling of 2D-SEC EV isolates was achieved, compared to the 1D-SEC, identifying proteins involved in the PAM, MAPK, and NF-κB pathways, indicating that the developed 2D-SEC approach could be beneficial for enabling minimally invasive clinical applications and broader studies of EV biology.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101682"},"PeriodicalIF":6.3,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Variability of sodium channel toxins in Mesobuthus thersites Advised toolkit for comprehensive venomics.","authors":"Mikhail A Chernykh, Rustam H Ziganshin, Maria I Toropygina, Vladislav V Babenko, Ilya Y Toropygin, Alexander A Vassilevski","doi":"10.1016/j.mcpro.2026.101681","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101681","url":null,"abstract":"<p><p>Natural venoms constitute vast combinatorial libraries of ion channel ligands with unprecedented properties including high affinity and selectivity. Scorpion venoms in particular are abundant in sodium and potassium channel ligands representing small proteins or peptides, which are traditionally studied by transcriptomics and proteomics approaches. However, a universal algorithm to pursue the examination of multicomponent peptide-rich mixtures such as venoms is lacking. Here we present a general scheme to the analysis of scorpion toxin arsenal with focus on sodium channel ligands. We explored the venom of the Central Asian scorpion Mesobuthus thersites using venom gland transcriptomics and three proteomic methods. We compared traditional automated annotation by Blast2GO with our custom approach based on regular expressions. We found that the traditional annotation is compromised yielding a considerable percentage of false annotations, whereas our approach is rigorous. As a result, we predicted 120 unique toxin-like peptides from transcriptomic data, 30 of which were omitted by Blast2GO. Using a combination of MALDI and LC-MS proteomic techniques, we detected the presence of 358 peptides in the venom. Our results demonstrate the limitations of the currently used methods in venomics and suggest a preferred framework for the investigation of toxin variability. Implementation of this framework will aid toxinologists to uncover previously elusive or undetected venom components.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101681"},"PeriodicalIF":6.3,"publicationDate":"2026-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149207232","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Proteomic and β-hydroxybutyrylation Landscapes Reveal AMPKα2-Associated Modulation in HUCMSC-Derived Exosome-Mediated Amelioration of Cardiac Aging.","authors":"Xuehui Li, Wenjing Ding, Xuechun Yang, Congmin Tang, Wenzhuo Yu, Xu Jia, Zhen Zhang, Yiping Song, Mingying Ling, Guixiang Yao, Yanqiu Xing","doi":"10.1016/j.mcpro.2026.101680","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101680","url":null,"abstract":"<p><p>Cardiac aging is characterized by progressive functional decline and metabolic remodeling. We previously found that lysine β-hydroxybutyrylation (Kbhb) is altered in wild-type (WT) aged and AMP-activated protein kinase alpha 2 (AMPKα2)-knockout (AK) young hearts, but whether this landscape can be reversed therapeutically remains unknown. We evaluated the therapeutic potential of human umbilical cord mesenchymal stromal cell-derived exosomes (hUCMSC-exos) in WT and AK aged mice, using young and aged untreated cohorts as controls. Quantitative proteomics across six experimental groups identified 1,755 Kbhb sites on 652 proteins, mapping the dynamic cardiac Kbhb landscape under aging, AMPKα2 deficiency, and exosome intervention. In wild-type aged (WTA) mice, hUCMSC-exos improved systolic and diastolic function, enhanced grip strength, reduced fibrosis, and restored ATP levels, accompanied by predominant downregulation of Kbhb on enzymes of glycolysis/gluconeogenesis, fatty acid oxidation, the tricarboxylic acid cycle, and oxidative phosphorylation. In AMPKα2-knockout aged (AKA) mice, exosomes partially improved mitochondrial ultrastructure and diastolic indices but did not rescue systolic function or fibrosis. Site-level analysis revealed that exosomes selectively normalized Kbhb sites elevated during aging, whereas AMPKα2 deficiency caused nonselective global depletion. The candidate AMPKα2-SIRT3 pathway, supported by SIRT5, may underlie this Kbhb reprogramming. We validated carnitine acetyltransferase (CRAT) K141bhb as an age-accumulated modification reversed by exosomes in an AMPKα2- associated manner. Molecular modeling indicated that K141bhb neutralizes the positive charge of K141, disrupting the local salt bridge between K141 and E144 and destabilizing the α-helical structure, suggesting that K141bhb may serve as a metabolic brake on CRAT activity. These findings map the cardiac Kbhb landscape and show that hUCMSC-exos ameliorate cardiac aging through AMPKα2- associated Kbhb modulation.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101680"},"PeriodicalIF":6.3,"publicationDate":"2026-10-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149195377","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"ProCAS: Multi-Lysine Post-Translational Modification Site Prediction Based on the SPUS Algorithm and the ProCAS Architecture.","authors":"Yun Zuo, Li Zhou, Xingze Fang, Zhaohong Deng, Anjing Zhao, Hongwei Yin","doi":"10.1016/j.mcpro.2026.101650","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101650","url":null,"abstract":"<p><p>Among PTMs, multiple chemical modifications on lysine residues have received extensive attention due to their dynamic and reversible properties. Although mass spectrometry can accurately identify modification sites, its high technical requirements and limited throughput restrict large scale application. In recent years, advances in deep learning have provided new strategies for high throughput prediction of lysine modifications. However, most existing methods still face limitations in simultaneous prediction of multiple lysine modification types, protein-level contextual representation, and prediction bias caused by imbalanced data distributions. To address these challenges, we developed an intelligent prediction system termed ProCAS. This system integrates multi-dimensional feature engineering, including: (1) an MLPSTAAP feature matrix derived from sequence information; (2) CTD descriptors that represent physicochemical properties of protein sequences; and (3) deep representations generated by ESM-2. A specially designed SPUS algorithm performs dynamic balancing optimization at the data distribution level, thereby increasing the modelling contribution of rare modification samples. The ProCAS neural architecture combines four core components, including bidirectional LSTM, a Self-Highway gating module, channel attention, and multi-head self-attention mechanisms. This design enables effective capture of both local and global sequence context and their complex associations with modification related functions. A bilinear mapping classifier is further applied to jointly output the probability distributions of four lysine modification types. Detailed ablation analysis demonstrated that the SPUS module plays a decisive role in alleviating data imbalance, while the ProCAS architecture effectively establishes deep associations between sequence features and modification types. In addition, SHAP based interpretability analysis was conducted to systematically examine the decision mechanisms of multi-label prediction. The results showed that ESM-2 features provided clear label-specific contributions across different modification types, while CTD features captured global physicochemical property patterns, together explaining both local sequence signals and broader physicochemical determinants of lysine modifications. Code and datasets are available at https://github.com/Lilyjoys/ProCAS, and a free web platform is provided at http://www.mlysprocas.com.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101650"},"PeriodicalIF":6.3,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the nano Liquid Chromatography coupled with Zeno TOF 7600 Mass Spectrometer for Cell Type-Resolved Spatial Proteomics.","authors":"Keren Zhang, Xi Wang, Wan He, Jiani Wang, An He, Binbin Zheng, Yangqiu Li, Ruilian Xu, Weina Gao, Henry Lam, Ruijun Tian","doi":"10.1016/j.mcpro.2026.101599","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101599","url":null,"abstract":"<p><p>In this study, we systematically evaluated the nanoLC-Zeno TOF platform using data-independent acquisition (DIA) and identified 3,142 to 7,059 protein groups from 1 to 200 ng of standard K562 digest. Additionally, a targeted acquisition strategy detected 184 peptides with enhanced signals using Zeno activation. To achieve cell type-resolved spatial proteomics, we developed a workflow integrating image-guided laser capture microdissection for the analysis of gastric cancer tissue. A 30-minute nanoLC gradient facilitated the quantification of 2,514 proteins from 0.2 mm² regions representing cancer cells, cancer-associated fibroblasts (CAFs), and immune cells, as defined by multiplex immunohistochemistry (mIHC). This spatial proteomics approach revealed cellular heterogeneity within the tumor microenvironment of a clinical gastric cancer sample, and targeted validation identified the differential expression of 12 cancer-associated proteins comprising 103 peptides between cancer cell-enriched and CAF-enriched regions. This workflow offers a practical strategy for spatial proteomic analysis of clinical tissue samples.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101599"},"PeriodicalIF":6.3,"publicationDate":"2026-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149183214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evolution and adaptations of the seminal proteome in an insect with traumatic insemination.","authors":"Martin D Garlovsky, Oliver Otti, Klaus Reinhardt, Timothy L Karr","doi":"10.1016/j.mcpro.2026.101679","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101679","url":null,"abstract":"<p><p>The protein composition of sperm and seminal fluid are key to male fitness. However, we currently lack an understanding of the factors that shape seminal proteome composition. The common bedbug (Cimex lectularius) mates by traumatic insemination, subjecting the ejaculate to a unique selective environment as sperm traverse the female genital and paragenital system. We provide the first high-throughput proteomic characterisation of the sperm and seminal fluid proteome in a hemimetabolous insect and the first in-depth proteomic characterisation of the male bedbug reproductive system. Our analysis revealed conserved and unique features of the bedbug sperm and seminal fluid proteome possibly linked to traumatic insemination. The sperm proteome showed elevated rates of molecular evolution, unlike most other studied insect species, yet also contained many conserved proteins. Notably, we found that bedbugs and other hemimetabolous insects share an expansion of Sperm-leucylaminopeptidases (S-Laps). Using in silico protein-ligand binding predictions, we show that S-Laps have likely retained catalytic activity in bedbugs. Our results provide a foundation for future studies of this expanding global pest.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101679"},"PeriodicalIF":6.3,"publicationDate":"2026-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149137504","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermal proteome profiling identifies new drug targets in Plasmodium falciparum parasites.","authors":"Samuel Pazicky, Jerzy M Dziekan, Seth Tjia, Selina Bopp, Dyann Wirth, Peter R Preiser, Zbynek Bozdech","doi":"10.1016/j.mcpro.2026.101678","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101678","url":null,"abstract":"<p><p>Spreading resistance to clinically used antimalarial drugs increases the need for identification of new drug targets. Here, we screened 25 antimalarials with known and unknown mode of action to validate old and find new drug targets in P. falciparum. Combining experimental approach by proteome-wide cellular thermal shift assay and computational filtering by molecular docking, we found the drugs to bind to previously known drug targets, validated ACS10 as the target of MMV665915 and discovered new drug targets. Furthermore, we updated the experimental and analytical MS-CETSA pipeline with the inclusion of membrane solubilization step, validated the targets of atovaquone and cipargamin on cell lysates and in intact cells and mapped the parasite response to these antimalarials.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101678"},"PeriodicalIF":6.3,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128065","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Empirical-Bayes and Bayesian Hierarchical Modelling for Missingness and Differential Expression in Proteomics.","authors":"Mengchun Li, Venkatesh Mallikarjun, Andrew Frey, Emmanuel O Ogundimu, Matthias Trost","doi":"10.1016/j.mcpro.2026.101677","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101677","url":null,"abstract":"<p><p>Mass spectrometry-based label-free proteomics data often suffer from missing values, especially for low-abundance proteins or when a protein is completely absent in one condition. This makes it challenging to estimate fold changes reliably and perform downstream analyses. Traditional imputation methods often show inconsistent performance across datasets and they typically treat imputed values as fixed rather than uncertain. This can lead to an underestimation of variability in downstream analyses. To address those problems, we present a hierarchical model that accounts for both observed protein intensities and patterns of missing data. Missing values are modelled as left-censored observations below protein-specific detection limits, reflecting the limited sensitivity of the instrument, or as missing with a probability that depends on the latent intensity (intensity-dependent missingness). Our proposed model captures structure at multiple levels: intensity-level measurements, group-level effects (e.g., experimental conditions), and protein-level variation. To estimate model parameters, we employ an empirical Bayes (EB) framework to infer hyperparameters across proteins and use Markov Chain Monte Carlo (MCMC) methods to sample parameters from the posterior distribution. Our pipeline avoids the need for imputing missing values and is designed to produce more reliable fold-change estimates and uncertainty measures. We benchmark our method against existing approaches and demonstrate that it provides accurate, stable, and robust estimates for differential expression analysis.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101677"},"PeriodicalIF":6.3,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128060","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pretrained spectrum representations for diverse tandem mass spectrometry proteomics tasks.","authors":"Justin Sanders, Melih Yilmaz, Jacob H Russell, Wout Bittremieux, William E Fondrie, Nicholas M Riley, Sewoong Oh, William S Noble","doi":"10.1016/j.mcpro.2026.101673","DOIUrl":"https://doi.org/10.1016/j.mcpro.2026.101673","url":null,"abstract":"<p><p>Mass spectrometry is the dominant technology in the field of proteomics, enabling high-throughput analysis of the protein content of complex biological samples. Due to the complexity of the instrumentation and resulting data, sophisticated computational methods are required for the processing and interpretation of acquired mass spectra. Machine learning has shown great promise to improve the analysis of mass spectrometry data, with numerous purpose-built methods for improving specific steps in the data acquisition and analysis pipeline reaching widespread adoption. Each of these tasks rely on a shared fundamental understanding of the information present in a mass spectrum. Here, we propose a transfer learning framework, CasanovoTL, which utilizes pretrained spectrum representations, derived from a de novo sequencing model trained on a massive proteomics dataset, rather than training a spectrum encoder from scratch for each task. We show that using these pre-trained spectrum representations significantly improves our performance on the four downstream tasks of spectrum quality prediction, chimericity prediction, phosphorylation prediction, and glycosylation status prediction. Finally, we perform end-to-end finetuning, as well as multi-task training, and find that finetuned spectrum representations further improve performance on each individual task. Overall, our work demonstrates that a pretrained spectrum encoder for tandem mass spectrometry proteomics trained on de novo sequencing learns generalizable representations of spectra, improves performance on downstream tasks where training data is limited, and can ultimately enhance data acquisition and analysis in proteomics experiments.</p>","PeriodicalId":18712,"journal":{"name":"Molecular & Cellular Proteomics","volume":" ","pages":"101673"},"PeriodicalIF":6.3,"publicationDate":"2026-10-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"149128093","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}