Background: We aimed to assess the differences in gene expression and systemic inflammatory markers in colorectal cancer (CRC) patients with different mismatch repair (MMR) statuses.
Methods: Bioinformatics analysis was used to identify the different expression genes in patients with CRC at different MMR statuses. A total of 208 patients with resectable colorectal cancer, including 104 deficient mismatch repair (dMMR) patients and 104 matched proficient mismatch repair (pMMR) patients, were retrospectively analyzed.
Results: Bioinformatics analysis showed that chemokine-mediated signaling pathway and inflammatory responses were the main differences in gene expression between dMMR and pMMR CRC patients. In all 208 patients with CRC, those with dMMR frequently had it located on the right side, with more mucinous adenocarcinoma and grade 3 tumors. Patients with dMMR had an earlier American Joint Committee on Cancer (AJCC) stage than pMMR patients. Meanwhile, lymph nodes (LNs) metastasis was more frequently negative in dMMR patients than pMMR patients. Interestingly, patients with CRC with dMMR had more regional lymph nodes removed during surgery, although with less metastatic cancer. Patients with resectable CRC with dMMR were more likely to have higher levels of neutrophil, monocyte, platelet, neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), C-reactive protein to albumin ratio (CAR), Glasgow prognostic score (GPS) and C-reactive protein (CRP). In patients with dMMR, those with higher levels of PLR, MLR, CAR, and co-effect present had shorter overall survival (OS) significantly. It was noteworthy that the prognosis of high levels of systemic inflammatory markers did not predict prolonged OS in patients with pMMR CRC.
Conclusion: dMMR CRC has presented a comprehensively distinct systemic inflammatory microenvironment. The systemic inflammatory response can predict oncological outcomes in patients with CRC with dMMR.
Keywords: gene expression, systemic inflammatory markers, colorectal cancer, bioinformatics analysis, lymph nodes