RT Journal Article
SR Electronic
T1 Pan-cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2023.01.23.525265
DO 10.1101/2023.01.23.525265
A1 Wang, Jixin
A1 Yu, Wen
A1 D’Anna, Rachel
A1 Przybyla, Anna
A1 Wilson, Matt
A1 Sung, Matthew
A1 Bullen, John
A1 Hurt, Elaine
A1 DAngelo, Gina
A1 Sidders, Ben
A1 Lai, Zhongwu
A1 Zhong, Wenyan
YR 2023
UL http://biorxiv.org/content/early/2023/01/23/2023.01.23.525265.abstract
AB The National Cancer Institute’s Clinical Proteomic Tumor Analysis Consortium (CPTAC) provides unique opportunities for cancer target discovery using protein expression. Proteomics data from CPTAC tumor types have been primarily generated using a multiplex tandem mass tag (TMT) approach, which is designed to provide protein quantification relative to reference samples. However, relative protein expression data is suboptimal for prioritization of targets within a tissue type, which requires additional reprocessing of the original proteomics data to derive absolute quantitation estimation. We evaluated the feasibility of using differential protein analysis coupled with intensity-based absolution quantification (iBAQ) to identify tumor-enriched and highly expressed cell surface antigens, employing tandem mass tag (TMT) proteomics data from CPTAC. Absolute quantification derived from TMT proteomics data was highly correlated with that of label-free proteomics data from the CPTAC colon adenocarcinoma cohort, which contains proteomics data measured by both approaches. We validated the TMT-iBAQ approach by comparing the iBAQ value to the receptor density value of HER2 and TROP2 measured by flow cytometry in about 30 selected breast and lung cancer cell lines from the Cancer Cell Line Encyclopedia. Collections of these tumor-enriched and highly expressed cell surface antigens could serve as a valuable resource for the development of cancer therapeutics, including antibody-drug conjugates and immunotherapeutic agents.Competing Interest StatementThe authors have declared no competing interest.APEXabsolute protein expressionBRCAbreast cancerCCLECancer Cell Line EncyclopediaccRCCclear-cell renal cell carcinomaCOADcolon adenocarcinomaCPTACClinical Proteomic Tumor Analysis ConsortiumDEPdifferential protein analysisDIAdata-independent acquisitionFDRfalse discovery rateGBMglioblastoma multiformeHNSCChead and neck squamous-cell carcinomaiBAQintensity-based absolute quantificationIgGimmunoglobulin GKNNk–nearest neighbor;LFQlabel-free protein quantificationLSCClung squamous-cell carcinomaLU ADlung adenocarcinomaNATnormal adjacent tissueOVovarian cancerPBSphosphate-buffered salinePDApancreatic ductal adenocarcinomaSPCsurface prediction consensusT-DXdtrastuzumab deruxtecanTMTtandem mass tagTPAtotal protein approachUCECuterine corpus endometrial carcinoma