Abstract 3607: Tissue-based proteome-wide association study identifies novel risk proteins and candidate drug targets for colorectal cancer

Abstract Background Colorectal cancer (CRC) is the second leading cause of cancer-related death worldwide. To date, ∼250 genetic risk loci have been identified through genome-wide association studies (GWAS), and transcriptome-wide association studies (TWAS) has implicated ∼500 putative CRC risk genes. However, proteins, the primary effectors of cellular function and drug response, remain underexplored. Thus, proteome-wide association studies (PWAS) linking genetic variation to protein abundance in colorectal tissue are essential for identifying causal proteins, clarifying disease mechanisms, and discovering therapeutic targets. Methods We performed unbiased data-independent acquisition mass spectrometry on 323 normal colon tissues from the Tennessee Colorectal Polyp Study and BarcUVa-seq studies, quantifying >9,000 proteins, and generated matched blood genotypes. Protein preprocessing included low-abundance filtering, log2 transformation, and PEER adjustment. We conducted PWAS using our previously developed approach which integrates susceptible TF occupied cis-regulatory elements (PMID: 36402776) to build genetically predicted protein expression models and applied to two CRC GWAS datasets separately: (1) European ancestry (80,774 cases, 105,298 controls) and (2) a trans-ancestry meta-analysis (104,346 cases, 153,998 controls). Risk proteins were identified by combining results from both datasets. We performed pQTL analyses of known CRC lead variants (PMID: 38670944), followed by Bayesian colocalization, and evaluated therapeutic relevance by mapping CRC-associated proteins to drug-target interactions using DrugBank, ChEMBL, TTD, and Open Targets. Results At a Bonferroni-corrected threshold of P < 0.05, our PWAS identified 41 proteins significantly associated with CRC risk, including 12 not previously linked to CRC. pQTL analyses identified 14 risk proteins, five with strong colocalization (PP.H4 > 0.8). We also found support for 76 previously reported CRC risk genes based on PWAS or pQTL signals at nominal P < 0.05. Among all risk proteins, 13 were potentially druggable, linked to 235 candidate therapeutic compounds. We provided the genetic evidence supporting multiple potential therapeutic drug targets for CRC prevention, with drug-protein interactions mapped to key CRC-relevant pathways such as PGE2-EP4 signaling (e.g., PTGER4 protein inhibitor E7046, Phase I/II), redox homeostasis (TXN protein inhibitor PX-12, Phase II; ALDH2 approved inhibitor Disulfiram), and BET signaling (BD2-selective inhibitor ABBV-744, Phase I). Conclusion This study provides the first large-scale tissue-based PWAS in CRC, identifying novel risk proteins and multiple potential druggable targets. These findings advance our understanding of CRC etiology and highlight new opportunities for therapeutic development and CRC prevention. Citation Format: Qing Li, Timothy Su, Chao Li, Quanhu Sheng, Shuai Xu, Wanqing Wen, Qi Dai, Martha J. Shrubsole, Jirong Long, Qiuyin Cai, Bing Zhang, Xioa-Ou Shu, Bhuminder Singh, Ken S. Lau, You Chen, Yuankai Huo, Zhijun Yin, Stephen B. Gruber, Riki (Ulrike) Peters, Victor R. Moreno, Wei Zheng, Xingyi Guo. Tissue-based proteome-wide association study identifies novel risk proteins and candidate drug targets for colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3607.

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Cancer Research
Published
2026-04-03
DOI
https://doi.org/10.1158/1538-7445.am2026-3607
Primary Topic
Genetic Associations and Epidemiology
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article
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article

Abstract 3607: Tissue-based proteome-wide association study identifies novel risk proteins and candidate drug targets for colorectal cancer

Shuai Xu, Riki Peters, Vı́ctor Moreno, Martha J. Shrubsole et al.
Cancer Research
Genetic Associations and Epidemiology
article

Abstract 3607: Tissue-based proteome-wide association study identifies novel risk proteins and candidate drug targets for colorectal cancer

Shuai Xu, Riki Peters, Vı́ctor Moreno, Martha J. Shrubsole, Yuankai Huo, Wanqing Wen, Timothy Su, Bhuminder Singh, Qi Dai, Quanhu Sheng, You Chen, Ken S. Lau, Stephen B. Gruber, Bing Zhang, Zhijun Yin, Wei Zheng, Jirong Long, Qiuyin Cai, Xingyi Guo, Xioa-Ou Shu, Chao Li, Qing Li
article en

Abstract

Abstract Background Colorectal cancer (CRC) is the second leading cause of cancer-related death worldwide. To date, ∼250 genetic risk loci have been identified through genome-wide association studies (GWAS), and transcriptome-wide association studies (TWAS) has implicated ∼500 putative CRC risk genes. However, proteins, the primary effectors of cellular function and drug response, remain underexplored. Thus, proteome-wide association studies (PWAS) linking genetic variation to protein abundance in colorectal tissue are essential for identifying causal proteins, clarifying disease mechanisms, and discovering therapeutic targets. Methods We performed unbiased data-independent acquisition mass spectrometry on 323 normal colon tissues from the Tennessee Colorectal Polyp Study and BarcUVa-seq studies, quantifying >9,000 proteins, and generated matched blood genotypes. Protein preprocessing included low-abundance filtering, log2 transformation, and PEER adjustment. We conducted PWAS using our previously developed approach which integrates susceptible TF occupied cis-regulatory elements (PMID: 36402776) to build genetically predicted protein expression models and applied to two CRC GWAS datasets separately: (1) European ancestry (80,774 cases, 105,298 controls) and (2) a trans-ancestry meta-analysis (104,346 cases, 153,998 controls). Risk proteins were identified by combining results from both datasets. We performed pQTL analyses of known CRC lead variants (PMID: 38670944), followed by Bayesian colocalization, and evaluated therapeutic relevance by mapping CRC-associated proteins to drug-target interactions using DrugBank, ChEMBL, TTD, and Open Targets. Results At a Bonferroni-corrected threshold of P < 0.05, our PWAS identified 41 proteins significantly associated with CRC risk, including 12 not previously linked to CRC. pQTL analyses identified 14 risk proteins, five with strong colocalization (PP.H4 > 0.8). We also found support for 76 previously reported CRC risk genes based on PWAS or pQTL signals at nominal P < 0.05. Among all risk proteins, 13 were potentially druggable, linked to 235 candidate therapeutic compounds. We provided the genetic evidence supporting multiple potential therapeutic drug targets for CRC prevention, with drug-protein interactions mapped to key CRC-relevant pathways such as PGE2-EP4 signaling (e.g., PTGER4 protein inhibitor E7046, Phase I/II), redox homeostasis (TXN protein inhibitor PX-12, Phase II; ALDH2 approved inhibitor Disulfiram), and BET signaling (BD2-selective inhibitor ABBV-744, Phase I). Conclusion This study provides the first large-scale tissue-based PWAS in CRC, identifying novel risk proteins and multiple potential druggable targets. These findings advance our understanding of CRC etiology and highlight new opportunities for therapeutic development and CRC prevention. Citation Format: Qing Li, Timothy Su, Chao Li, Quanhu Sheng, Shuai Xu, Wanqing Wen, Qi Dai, Martha J. Shrubsole, Jirong Long, Qiuyin Cai, Bing Zhang, Xioa-Ou Shu, Bhuminder Singh, Ken S. Lau, You Chen, Yuankai Huo, Zhijun Yin, Stephen B. Gruber, Riki (Ulrike) Peters, Victor R. Moreno, Wei Zheng, Xingyi Guo. Tissue-based proteome-wide association study identifies novel risk proteins and candidate drug targets for colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 1 (Regular Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(7 Suppl):Abstract nr 3607.

Cancer ResearchVol. 86(7_Supplement)
City Of Hope National Medical Center (US), Baylor College of Medicine (US), Vanderbilt University (US), Fred Hutch Cancer Center (US), Ajuntament de L’Hospitalet (ES), Vanderbilt University Medical Center (US)
Good health and well-being
Openalex Percentile: Top 30%
Genetic Associations and Epidemiology
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