Causal relationship between immune cell signatures and colorectal cancer: a bi-directional, two-sample mendelian...

Prior studies have demonstrated the association between immune cells and colorectal cancer (CRC). However, the causal link to specific immunophenotypes is limited. This study intends to elucidate the causal relationship of immune cell signatures on CRC.

We performed a bi-directional and two-sample mendelian randomization (MR) study, utilizing GWAS summary data of 731 immune cell traits (n = 3,757) and CRC statistics (n = 470,002). The primary MR methodology was inverse-variance weighted (IVW) method. Furthermore, heterogeneity was evaluated by Cochran's Q test. MR-PRESSO and MR-Egger were employed to assess horizontal and vertical pleiotropy respectively. Sensitivity analysis and FDR correction were conducted in our results. These results were validated in both the UK Biobank and FinnGen cohorts. We also extracted transcriptomic data of CRC and adjacent non-tumor tissues from TCGA, and used CIBERSORT to compare the infiltration patterns of 22 immune cell panels between normal tissues and the tumor microenvironment (TME).

Our study indicated nine immune cell signatures had significant causality with the risk of CRC after sensitivity analysis and FDR correction. The positive results covered four panels: B cell, CD8 + T cell, Treg, and monocyte. IgD- CD38br and IgD + CD38br B cell, CD8dim and CD28 + CD45RA- CD8dim T cell, and CD14 on CD14 + CD16- monocyte were the protective factors of CRC. However, CD39 + resting Treg, CX3CR1 on CD14- CD16 + monocyte, FSC-A on HLA DR + T cell, and BAFF-R on B cell increased the risk of CRC. The results were validated in the UK Biobank data and FinnGen cohorts. The data from the TCGA database also confirmed the infiltration of B cell, CD8 + T cell, Treg, and monocyte panels in the TME.

This study highlights the causal link between specific immune cell phenotypes and CRC, providing valuable insights into the immune microenvironment's role in CRC. The validation of our findings using large-scale datasets (UK Biobank, FinnGen) and TCGA underscores the robustness of our results, offering new potential therapeutic targets for CRC treatment.