PO.PS01.07 · 人群科学
基于组织的全蛋白质组关联研究鉴定结直肠癌的新型风险蛋白和候选药物靶点
Tissue-based proteome-wide association study identifies novel risk proteins and candidate drug targets for colorectal cancer
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摘要 Abstract
中文摘要
背景:结直肠癌(CRC)是全球癌症相关死亡的第二大原因。迄今为止,全基因组关联研究(GWAS)已鉴定出约250个遗传风险位点,全转录组关联研究(TWAS)已提示约500个假定的CRC风险基因。然而,作为细胞功能和药物反应主要效应器的蛋白质仍未被充分研究。因此,将遗传变异与结直肠组织中蛋白质丰度相联系的全蛋白质组关联研究(PWAS)对于鉴定因果蛋白、阐明疾病机制和发现治疗靶点至关重要。
方法:我们对来自Tennessee Colorectal Polyp Study和BarcUVa-seq研究的323例正常结肠组织进行了无偏数据非依赖采集质谱分析,定量了超过9,000种蛋白质,并生成了配对的血液基因型。蛋白质预处理包括低丰度过滤、log₂转换和PEER校正。我们采用先前开发的方法进行PWAS,该方法整合易感转录因子占据的顺式调控元件(PMID: 36402776)以构建遗传预测的蛋白质表达模型,并分别应用于两个CRC GWAS数据集:(1)欧洲血统(80,774例病例,105,298例对照)和(2)跨血统荟萃分析(104,346例病例,153,998例对照)。通过合并两个数据集的结果鉴定风险蛋白。我们对已知CRC主导变异(PMID: 38670944)进行了pQTL分析,随后进行贝叶斯共定位,并通过将CRC相关蛋白映射到药物-靶点相互作用(使用DrugBank、ChEMBL、TTD和Open Targets)评估治疗相关性。
结果:在Bonferroni校正阈值P<0.05下,我们的PWAS鉴定出41种与CRC风险显著相关的蛋白,包括12种此前未与CRC相关联的蛋白。pQTL分析鉴定出14种风险蛋白,其中5种具有强共定位(PP.H4>0.8)。我们还发现基于PWAS或pQTL信号在名义P<0.05下支持76个此前报道的CRC风险基因。在所有风险蛋白中,13种具有潜在成药性,与235种候选治疗化合物相关联。我们提供了支持CRC预防多个潜在治疗药物靶点的遗传学证据,药物-蛋白相互作用映射到关键的CRC相关通路,如PGE₂-EP4信号(例如PTGER4蛋白抑制剂E7046,I/II期)、氧化还原稳态(TXN蛋白抑制剂PX-12,II期;ALDH2获批抑制剂双硫仑)和BET信号(BD2选择性抑制剂ABBV-744,I期)。
结论:本研究提供了首个大规模的基于组织的CRC PWAS,鉴定出新型风险蛋白和多个潜在可成药靶点。这些发现推进了我们对CRC病因的理解,并凸显了治疗开发和CRC预防的新机遇。
查看英文原文 English 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.
利益披露 Disclosure
Q. Li, None..
T. Su, None..
Q. Sheng, None..
W. Wen, None..
Q. Dai, None..
M. J. Shrubsole, None..
J. Long, None..
Q. Cai, None..
X. Shu, None..
Y. Chen, None..
Y. Huo, None..
Z. Yin, None..
W. Zheng, None..
X. Guo, None.