Journal of Proteome Research最新文献

Detecting Human Contaminant Genetically Variant Peptides in Nonhuman Samples.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-20 DOI: 10.1021/acs.jproteome.4c00718

Fanny Chu, Andy Lin

{"title":"Detecting Human Contaminant Genetically Variant Peptides in Nonhuman Samples.","authors":"Fanny Chu, Andy Lin","doi":"10.1021/acs.jproteome.4c00718","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00718","url":null,"abstract":"During proteomics data analysis, experimental spectra are searched against a user-defined protein database consisting of proteins that are reasonably expected to be present in the sample. Typically, this database contains the proteome of the organism under study concatenated with expected contaminants, such as trypsin and human keratins. However, there are additional contaminants that are not commonly added to the database. In this study, we describe a new set of protein contaminants and provide evidence that they can be detected in mass spectrometry-based proteomics data. Specifically, we provide evidence that human genetically variant peptides (GVPs) can be detected in nonhuman samples. GVPs are peptides that contain single amino acid polymorphisms that result from nonsynonymous single nucleotide polymorphisms in protein-coding regions of DNA. We reanalyzed previously collected nonhuman data-dependent acquisition (DDA) and data-independent acquisition (DIA) data sets and detected between 0 and 135 GVPs per data set. In addition, we show that GVPs are unlikely to originate from nonhuman sources and that a subset of eight GVPs are commonly detected across data sets.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142869274","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}

引用次数: 0

Multiomics Approach Identifies Key Proteins and Regulatory Pathways in Colorectal Cancer.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-19 DOI: 10.1021/acs.jproteome.4c00902

Jun Rao, Xing Wang, Xianghui Wan, Chao Chen, Xiaopeng Xiong, Aihua Xiong, Zhiqing Yang, Lanyu Chen, Ting Wang, Lihua Mao, Chunling Jiang, Jiquan Zeng, Zhi Zheng

{"title":"Multiomics Approach Identifies Key Proteins and Regulatory Pathways in Colorectal Cancer.","authors":"Jun Rao, Xing Wang, Xianghui Wan, Chao Chen, Xiaopeng Xiong, Aihua Xiong, Zhiqing Yang, Lanyu Chen, Ting Wang, Lihua Mao, Chunling Jiang, Jiquan Zeng, Zhi Zheng","doi":"10.1021/acs.jproteome.4c00902","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00902","url":null,"abstract":"The prevalence rate of colorectal cancer (CRC) has dramatically increased in recent decades. However, robust CRC biomarkers with therapeutic value for early diagnosis are still lacking. To comprehensively reveal the molecular characteristics of CRC development, we employed a multiomics strategy to investigate eight different types of CRC samples. Proteomic analysis revealed 2022 and 599 differentially expressed tissue proteins between CRC and control groups in CRC patients and CRC mice, respectively. In patients with colorectal precancerous lesions, 25 and 34 significantly changed proteins were found between patients and healthy controls in plasma and white blood cells, respectively. Notably, vesicle-associated membrane protein-associated protein A (VAPA) was found to be consistently and significantly decreased in most types of CRC samples, and its level was also significantly correlated with increased overall survival of CRC patients. Furthermore, 37 significantly enriched pathways in CRC were further validated via metabolomics analysis. Ten VAPA-related pathways were found to be significantly enriched in CRC samples, among which PI3K-Akt signaling, central carbon metabolism in cancer, cholesterol metabolism, and ABC transporter pathways were also enriched in the premalignant stage. Our study identified VAPA and its associated pathways as key regulators, suggesting their potential applications in the early diagnosis and prognosis of CRC.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851636","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}

引用次数: 0

Biomarker Discovery for Early Detection of Pancreatic Ductal Adenocarcinoma (PDAC) Using Multiplex Proteomics Technology.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-19 DOI: 10.1021/acs.jproteome.4c00752

Alcibiade Athanasiou, Natasha Kureshi, Anja Wittig, Maria Sterner, Ramy Huber, Norma A Palma, Thomas King, Ralph Schiess

{"title":"Biomarker Discovery for Early Detection of Pancreatic Ductal Adenocarcinoma (PDAC) Using Multiplex Proteomics Technology.","authors":"Alcibiade Athanasiou, Natasha Kureshi, Anja Wittig, Maria Sterner, Ramy Huber, Norma A Palma, Thomas King, Ralph Schiess","doi":"10.1021/acs.jproteome.4c00752","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00752","url":null,"abstract":"Early detection of pancreatic ductal adenocarcinoma (PDAC) can improve survival but is hampered by the absence of early disease symptoms. Imaging remains key for surveillance but is cumbersome and may lack sensitivity to detect small tumors. CA19-9, the only FDA-approved blood biomarker for PDAC, is insufficiently sensitive and specific to be recommended for surveillance. We aimed to discover a blood-based protein signature to improve PDAC detection in our main target population consisting of stage I or II PDAC patients (n = 75) and various controls including healthy controls (n = 50), individuals at high risk (genetic and familial) for PDAC (n = 47), or those under surveillance for an intraductal papillary mucinous neoplasm (n = 36). Roughly 3000 proteins were measured using Olink multiplex technology and conventional immunoassays. Machine learning combined biomarker candidates into 4- to 6-plex signatures. These signatures significantly (p < 0.001) outperformed CA19-9 with 84% sensitivity at 95% specificity, compared to CA19-9's sensitivity of 53% in the target population. Exploratory analysis was performed in new-onset diabetes (n = 81) and chronic pancreatitis (n = 50) patients. In conclusion, 41 promising biomarker candidates across multiple signatures were identified using proteomics technology and will be further tested in an independent cohort.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851634","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}

引用次数: 0

Proteomics for Biomarker Discovery in Gynecological Cancers: A Systematic Review.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-19 DOI: 10.1021/acs.jproteome.4c00675

Dong-Hui Huang, Yi-Zi Li, He-Li Xu, Fang-Hua Liu, Xiao-Ying Li, Qian Xiao, Xing Chen, Ke-Xin Liu, Dong-Dong Wang, Yi-Xuan Men, Yi-Ning Cao, Song Gao, Yu-Hong Zhao, Ting-Ting Gong, Qi-Jun Wu

{"title":"Proteomics for Biomarker Discovery in Gynecological Cancers: A Systematic Review.","authors":"Dong-Hui Huang, Yi-Zi Li, He-Li Xu, Fang-Hua Liu, Xiao-Ying Li, Qian Xiao, Xing Chen, Ke-Xin Liu, Dong-Dong Wang, Yi-Xuan Men, Yi-Ning Cao, Song Gao, Yu-Hong Zhao, Ting-Ting Gong, Qi-Jun Wu","doi":"10.1021/acs.jproteome.4c00675","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00675","url":null,"abstract":"The present study aims to summarize the current biomarker landscape in gynecological cancers (GCs) and incorporate bioinformatics analysis to highlight specific biological processes. The literature was retrieved from PubMed, Web of Science, Embase, Scopus, Ovid Medline, and Cochrane Library. The final search was conducted on December 7, 2022. Prospective registration was completed with the PROSPERO with registration number CRD42023477145. This systematic review covered proteomic research on biomarkers for cervical, endometrial, and ovarian cancers. The PANTHER classification system was used to classify the shortlisted candidate biomarkers (CBs), and the STRING database was utilized to visualize protein-protein interaction networks. A total of 23 articles were included in this systematic review. Consistently regulated CBs in the GCs include collagen alpha-2(I) chain, collagen alpha-1(III) chain, collagen alpha-2(V) chain, calreticulin, protein disulfide-isomerase A3, heat shock protein family A (Hsp70) member 5, prolyl 4-hydroxylase, beta polypeptide, fibrinogen alpha chain, fibrinogen gamma chain, apolipoprotein B-100, apolipoprotein C-IV, and apolipoprotein M. In conclusion, collagens, fibrinogens, chaperones, and apolipoproteins were revealed to be replicated in GCs and to be regulated consistently. These CBs contribute to GC etiology and physiology by participating in collagen fibril organization, blood coagulation, protein folding in endoplasmic reticulum, and lipid transporter activity.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142851638","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}

引用次数: 0

Use and Comparison of Machine Learning Techniques to Discern the Protein Patterns of Autoantibodies Present in Women with and without Breast Pathology.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-19 DOI: 10.1021/acs.jproteome.4c00759

José-Luis Llaguno-Roque, Rocio-Erandi Barrientos-Martínez, Héctor-Gabriel Acosta-Mesa, Antonia Barranca-Enríquez, Efrén Mezura-Montes, Tania Romo-González

{"title":"Use and Comparison of Machine Learning Techniques to Discern the Protein Patterns of Autoantibodies Present in Women with and without Breast Pathology.","authors":"José-Luis Llaguno-Roque, Rocio-Erandi Barrientos-Martínez, Héctor-Gabriel Acosta-Mesa, Antonia Barranca-Enríquez, Efrén Mezura-Montes, Tania Romo-González","doi":"10.1021/acs.jproteome.4c00759","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00759","url":null,"abstract":"Breast cancer (BC) has become a global health problem, ranking first in incidence and fifth in mortality in women around the world. Although there are some diagnostic methods for the disease, these are not sufficiently effective and are invasive. In this work, we discriminated between patients without breast pathology (BP), with benign BP, and with BC based on the band patterns obtained from Western blot strip images of the autoantibody response to antigens of the T47D tumor line using and comparing supervised machine learning techniques to have a sensitive and accurate method. When comparing the aforementioned machine learning techniques, it was found that by obtaining a convolutional neural network architecture from a neuroevolution algorithm, it is possible to automatically discriminate with a classification accuracy of 90.67% between patients with cancer and with/without BP. In the case of discrimination between patients with cancer and without BP, a classification accuracy of 96.67% was obtained with the K-NN algorithm and 95.13% with the convolutional neural network obtained using a neuroevolution algorithm, although these results are not statistically significant. It is concluded that the convolutional neural network obtained by neuroevolution is the method with the best performance with respect to those evaluated in this work.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862533","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}

引用次数: 0

Development of an Optimized LC-MS Workflow for Host Cell Protein Characterization to Support Upstream Process Development.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-19 DOI: 10.1021/acs.jproteome.4c00637

Janik D Seidel, Mark R Condina, Manuela Klingler-Hoffmann, Clifford Young, Leigh Donnellan, Craig Kyngdon, Peter Hoffmann

{"title":"Development of an Optimized LC-MS Workflow for Host Cell Protein Characterization to Support Upstream Process Development.","authors":"Janik D Seidel, Mark R Condina, Manuela Klingler-Hoffmann, Clifford Young, Leigh Donnellan, Craig Kyngdon, Peter Hoffmann","doi":"10.1021/acs.jproteome.4c00637","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00637","url":null,"abstract":"Host cell proteins (HCPs) coexpressed during the production of biotherapeutics can affect the safety, efficacy, and stability of the final product. As such, monitoring HCP populations and amounts throughout the production and purification process is an essential part of the overall quality control framework. Mass spectrometry (MS) is used as an orthogonal method to enzyme-linked immunosorbent assays (ELISA) for the simultaneous identification and quantification of HCPs, particularly for the analysis of downstream processes. In this study, we present an MS-based analytical protocol with improvements in both speed and identification performance that can be implemented for routine analysis to support upstream process development. The protocol adopts a streamlined sample preparation strategy, combined with a high-throughput MS analysis pipeline. The developed method identifies and quantifies over 1000 HCPs, including 20 proteins listed as high risk in the literature, in a clarified cell culture sample with repeatability and precision shown for digest replicates. In addition, we explore the effects of varying standard spike-ins and changes to the data processing pipeline on absolute quantification estimates of the HCPs, which highlight the importance of standardization for wider use in the industry. Data are available via ProteomeXchange with the identifier PXD053035.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142862532","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}

引用次数: 0

The Exoproteome and Surfaceome of Toxigenic Corynebacterium diphtheriae 1737 and Its Response to Iron Restriction and Growth on Human Hemoglobin.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-18 DOI: 10.1021/acs.jproteome.4c00443

Andrew K Goring, Scott Hale, Poojita Dasika, Yu Chen, Robert T Clubb, Joseph A Loo

{"title":"The Exoproteome and Surfaceome of Toxigenic Corynebacterium diphtheriae 1737 and Its Response to Iron Restriction and Growth on Human Hemoglobin.","authors":"Andrew K Goring, Scott Hale, Poojita Dasika, Yu Chen, Robert T Clubb, Joseph A Loo","doi":"10.1021/acs.jproteome.4c00443","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00443","url":null,"abstract":"Toxin-producing Corynebacterium diphtheriae strains are the etiological agents of the severe upper respiratory disease, diphtheria. A global phylogenetic analysis revealed that biotype gravis is particularly lethal as it produces diphtheria toxin and a range of other virulence factors, particularly when it encounters low levels of iron at sites of infection. To gain insight into how it colonizes its host, we have identified iron-dependent changes in the exoproteome and surfaceome of C. diphtheriae strain 1737 using a combination of whole-cell fractionation, intact cell surface proteolysis, and quantitative proteomics. In total, we identified 1414 of the predicted 2265 proteins (62%) encoded by its reference genome. For each protein, we quantified its degree of secretion and surface exposure, revealing that exoproteases and hydrolases predominate in the exoproteome, while the surfaceome is enriched with adhesins, particularly DIP2093. Our analysis provides insight into how components in the heme-acquisition system are positioned, showing pronounced surface exposure of the strain-specific ChtA/ChtC paralogues and high secretion of the species-conserved heme-binding HtaA protein, suggesting it functions as a hemophore. Profiling the response of the exoproteome and surfaceome after microbial exposure to human hemoglobin and iron limitation reveals potential virulence factors that may be expressed at sites of infection. Data are available via ProteomeXchange with identifier PXD051674.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142845312","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}

引用次数: 0

Deep Saliva Proteomics Elucidating the Pathogenesis of Early Childhood Caries and Identifying Biomarkers for Early Prediction. 深度唾液蛋白质组学阐明儿童早期龋病的发病机制并确定早期预测的生物标志物。

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-16 DOI: 10.1021/acs.jproteome.4c00831

Shiyan Huang, Wenmin Tian, Jing Tian, Haohao Tang, Man Qin, Bingqian Zhao, Jingyan Wang, Yang Chen, He Xu

{"title":"Deep Saliva Proteomics Elucidating the Pathogenesis of Early Childhood Caries and Identifying Biomarkers for Early Prediction.","authors":"Shiyan Huang, Wenmin Tian, Jing Tian, Haohao Tang, Man Qin, Bingqian Zhao, Jingyan Wang, Yang Chen, He Xu","doi":"10.1021/acs.jproteome.4c00831","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00831","url":null,"abstract":"Early childhood caries (ECC) significantly impacts the physical and mental health of children. Saliva stands as a critical model for investigating the pathogenesis of caries disease since it reflects both host and microbial dynamics. However, the specific contributions of salivary host factors to ECC have not been fully understood. In this study, we monitored a prospective cohort of 3-4 year-old healthy children for 12 months, who either stayed caries-free or developed caries. Deep quantitative proteomics analysis of saliva was conducted at both recruitment and end point of the cohort to investigate the molecular mechanisms underlying ECC etiology and identify potential biomarkers for caries prediction. Proteomics analysis identified a total of 2873 proteins and revealed involvement of immune response, dental structure repair, and regeneration, as well as interactions with microorganisms during caries pathogenesis. Characteristic salivary proteins were identified in caries-susceptible children prior to caries development. An ECC prediction panel of proteins keratin 3 (KRT3) and mucin 21 (MUC21) was established and further validated through another independent cohort. This study illuminated the role of the complex salivary microenvironment in caries etiology and offered a prognostic tool for early ECC prediction, thus facilitating the precise prevention and control of ECC to ultimately reduce its incidence.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142833110","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}

引用次数: 0

Tear Fluid-Based Metabolomics Profiling in Chronic Dacryocystitis Patients. 基于泪液的慢性泪囊炎患者代谢组学分析

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-13 DOI: 10.1021/acs.jproteome.4c00592

Shuai Ben, Qun Zheng, Ya Zhao, Jiao Xia, Wan Mu, Mudi Yao, Biao Yan, Qin Jiang

{"title":"Tear Fluid-Based Metabolomics Profiling in Chronic Dacryocystitis Patients.","authors":"Shuai Ben, Qun Zheng, Ya Zhao, Jiao Xia, Wan Mu, Mudi Yao, Biao Yan, Qin Jiang","doi":"10.1021/acs.jproteome.4c00592","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00592","url":null,"abstract":"Chronic dacryocystitis (CD) can result in severe complications and vision impairment due to ongoing microbial infections and persistent tearing. Tear fluid, which contains essential components vital for maintaining ocular surface health, has been investigated for its potential in the noninvasive identification of ocular biomarkers through metabolomics analysis. In this study, we employed UHPLC-MS/MS to analyze the tear metabolome of CD patients. UHPLC-MS/MS analysis of tear samples from CD patients revealed significant metabolic alterations. Compared with the control group, 298 metabolites were elevated, while 142 were decreased. KEGG pathway analysis suggested that these changes primarily affected arginine and proline metabolism, biosynthesis of amino acids, and phenylalanine biosynthesis in CD. Notably, 3-dehydroquinic acid, anthranilic acid, citric acid, and l-isoleucine emerged as potential biomarker candidates of CD with high diagnostic accuracy (AUC = 0.94). These findings suggest that tear fluid metabolism, particularly amino acid biosynthesis, plays a significant role in the pathogenesis of CD. Uncovering these metabolic products and pathways provides valuable insights into the mechanisms underlying CD and paves the way for the development of diagnostic tools and targeted therapies.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816785","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}

引用次数: 0

TBK1 Reprograms Metabolism in Breast Cancer: An Integrated Omics Approach.

IF 3.8 2区生物学

Journal of Proteome Research Pub Date : 2024-12-13 DOI: 10.1021/acs.jproteome.4c00530

Meenu Maan, Neha Jaiswal, Min Liu, Harold I Saavedra, Srikumar P Chellappan, Mainak Dutta

{"title":"TBK1 Reprograms Metabolism in Breast Cancer: An Integrated Omics Approach.","authors":"Meenu Maan, Neha Jaiswal, Min Liu, Harold I Saavedra, Srikumar P Chellappan, Mainak Dutta","doi":"10.1021/acs.jproteome.4c00530","DOIUrl":"https://doi.org/10.1021/acs.jproteome.4c00530","url":null,"abstract":"Metabolic rewiring is required for cancer cells to survive in harsh microenvironments and is considered to be a hallmark of cancer. Specific metabolic adaptations are required for a tumor to become invasive and metastatic. Cell division and metabolism are inherently interconnected, and several cell cycle modulators directly regulate metabolism. Here, we report that TBK1, which is a noncanonical IKK kinase with known roles in cell cycle regulation and TLR signaling, affects cellular metabolism in cancer cells. While TBK1 is reported to be overexpressed in several cancers and its enhanced protein level correlates with poor prognosis, the underlying molecular mechanism involved in the tumor-promoting role of TBK1 is not fully understood. In this study, we show a novel role of TBK1 in regulating cancer cell metabolism using combined metabolomics, transcriptomics, and pharmacological approaches. We find that TBK1 mediates the regulation of nucleotide and energy metabolism through aldo-keto reductase B10 (AKRB10) and thymidine phosphorylase (TYMP) genes, suggesting that this TBK1-mediated metabolic rewiring contributes to its oncogenic function. In addition, we find that TBK1 inhibitors can act synergistically with AKRB10 and TYMP inhibitors to reduce cell viability. These findings raise the possibility that combining these inhibitors might be beneficial in combating cancers that show elevated levels of TBK1.","PeriodicalId":48,"journal":{"name":"Journal of Proteome Research","volume":" ","pages":""},"PeriodicalIF":3.8,"publicationDate":"2024-12-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142816782","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}

引用次数: 0