Integrating Single‐Cell Transcriptome‐Wide Mendelian Randomization and Differentially Expressed Gene Analyses to Prioritize Dynamic Immune‐Related Drug Targets for Cancers
Single-cell expression quantitative trait loci data offer promising opportunities to inform immune-related drug development in cancer. However, pleiotropy can complicate causal inference. We introduce MR-DEG, a framework that integrates Mendelian randomization (MR) and differential expressed gene (DEG) to strengthen causal inference. Using eight conventional MR and colocalization methods, we estimated effects of 11 021 dynamic gene expression profiles during CD4+ T cell activation on the risk of six cancer types. This identified 1000 gene-cancer pairs with putative effects (https://www.omicsharbour.com/sc-eqtl-mr). Of these 1000 pairs, 517 involved 205 unique genes that were differentially expressed in relevant cancer tissues based on single-cell RNA-sequencing data. Of these 517 pairs, 265 were classified as likely causal using the conventional MR methods. After applying MR-DEG to the remaining 252 potentially pleiotropic pairs, an additional 89 were classified as likely causal. Sixty-four and 391 of the 1000 original pairs exhibited time- and non-time dependent effects on cancer risk, respectively. Integrating the 1000 gene-cancer pairs of MR findings and clinical trial evidence, we identified 200 pairs corresponding to 33 unique genes that encode drug targets under clinical investigation. These results demonstrate how combining genetic, transcriptomic and clinical trial evidence can reduce pleiotropic bias, and prioritize immune-related drug targets for cancer prevention.
Authors
- Guang Ning
- Jieli Lu (ORCID: https://orcid.org/0000-0003-1317-0896)
- George Davey Smith (ORCID: https://orcid.org/0000-0002-1407-8314)
- Zhongshang Yuan (ORCID: https://orcid.org/0000-0002-3527-4488)
- Tom R. Gaunt (ORCID: https://orcid.org/0000-0003-0924-3247)
- Xueyan Wu (ORCID: https://orcid.org/0000-0001-9127-7854)
- Philip Haycock (ORCID: https://orcid.org/0000-0001-5001-3350)
- Yi Duan (ORCID: https://orcid.org/0000-0002-6229-9461)
- Ruizhi Zheng (ORCID: https://orcid.org/0000-0002-2068-7597)
- Richard Michael Martin (ORCID: https://orcid.org/0000-0002-7992-7719)
- Tiange Wang (ORCID: https://orcid.org/0000-0003-0723-489X)
- Jie Zheng (ORCID: https://orcid.org/0000-0002-6623-6839)
- Xi Huang (ORCID: https://orcid.org/0000-0002-7177-7525)
- Yifan Ye (ORCID: https://orcid.org/0000-0002-5173-5117)
- Qian Yang (ORCID: https://orcid.org/0000-0001-8778-4132)
- Lei Ye (ORCID: https://orcid.org/0000-0001-5195-1867)
- Yi Liu (ORCID: https://orcid.org/0000-0002-2051-440X)
- Weiqing Wang (ORCID: https://orcid.org/0000-0001-6027-3084)
- Haoyu Liu
- Min Xu (ORCID: https://orcid.org/0000-0001-5135-6507)
- Mian Li (ORCID: https://orcid.org/0000-0001-6514-2729)
- Hui Ying
- Zhiyun Zhao
- Hao Guo (ORCID: https://orcid.org/0000-0002-9289-9775)
- Fang Hu (ORCID: https://orcid.org/0000-0001-9378-0699)
- Huiling Zhao
- Yufang Bi
- Yilan Ding
- Shuangyuan Wang (ORCID: https://orcid.org/0000-0002-1060-492X)
- Hong Lin (ORCID: https://orcid.org/0000-0002-4766-095X)
Institutions
- University of Science and Technology of China (CN)
- Central South University (CN)
- Shandong University (CN)
- Shanghai Jiao Tong University (CN)
- University of Toronto (CA)
- Xiamen University (CN)
- University Hospitals Bristol NHS Foundation Trust (GB)
- Hospital for Sick Children (CA)
- Ruijin Hospital (CN)
- University of Bristol (GB)
- First Affiliated Hospital of Xiamen University (CN)
- Brain Tumour Research (GB)
- State Key Laboratory of Oncogene and Related Genes (CN)
- SickKids Foundation (CA)
- Second Xiangya Hospital of Central South University (CN)
Publication Details
- Journal
- Advanced Science
- Published
- 2025-11-11
- DOI
- https://doi.org/10.1002/advs.202507451
- Citations
- 1
- Primary Topic
- Single-cell and spatial transcriptomics
- Type
- article
- Field-Weighted Citation Impact
- 0.81