Pan-Cancer Proteomics Analysis to Identify Tumor-Enriched and Highly Expressed Cell Surface Antigens as Potential Targets for Cancer Therapeutics

Abstract

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 are 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 absolute 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.

Keywords: CPTAC; iBAQ; pan-cancer; proteomics; therapeutic target; tumor surface antigen.

Graphical abstract

Figure 1

Workflow for identification of tumor-enriched and highly expressed cell surface antigens. CPTAC, Clinical Proteomic Tumor Analysis Consortium; iBAQ, intensity-based absolute quantification; KNN, k–nearest neighbor; TMT, tandem mass tag; TPA, total protein approach.

Figure 2

Estimation of absolute protein abundance of iBAQ derived from TMT and label-free proteomics data, respectively, in the CPTAC COAD data set.A, LFQ-TPA and LFQ-iBAQ, as well as TMT-TPA and TMT-iBAQ, were highly correlated by Pearson correlation. B, for overlap sample and proteins, the TPA and iBAQ methods showed relatively good correlation between LFQ and TMT data. iBAQ, intensity-based absolute quantification; LFQ, label-free quantification; TMT, tandem mass tag; TPA, total protein approach.

Figure 3

Validation of absolute protein abundance by the iBAQ method with CCLE cell line receptor density data. iBAQ quantity and receptor density for HER2 (A) and TROP2 (B) were highly correlated by Pearson correlation. iBAQ, intensity-based absolute quantification.