Using single cell sequencing to investigate tumor microenvironment differences in left and right colon cancer and prognosis-related core genes

Colon cancer is a common intestinal malignancy and previous studies reported many differences between left (LCC) and right colon cancer (RCC). Traditional research methods are unable to compare differences within tumors at the single-cell level. We downloaded single-cell RNA sequencing (scRNA seq) data from GEO database. After quality control we conducted cell clustering, annotation and pseudotime analysis to identify the differentially expressed genes (DEGs) in RCC compared to LCC. Gene set enrichment analysis (GSEA) was undertaken to explore the pathways these DEGs involved. Based on the expression of these DEGs, we divided patients from TCGA (The Cancer Genome Atlas) database. The differences of tumor microenvironment and immune infiltration in different clusters were also analyzed. WGCNA was performed to select the survival-related genes. Survival-related DEGs were selected and univariate Cox regression analysis was conducted to further identify independent prognostic genes. A nomogram model was established for risk prediction and its accuracy was verified by calibration curve and immunohistochemistry (IHC) analysis. We found significant differences of tumor microenvironment and immune infiltration among three patient clusters. The patients with high infiltration of memory B cells were associated with poorer survival. We eventually obtained seven prognosis-related genes: S100P, LGALS4, TIMP1, DNASE1L3, BGN, TPM2 and LY6E, based on which a risk model was constructed, which was an accurate independent predictor for CRC patients. IHC stanning confirmed that the expression levels of these prognostic genes in tumor versus adjacent non-tumor tissues were consistent with our risk model. Our prognosis-related risk model based on DEGs between RCC and LCC may provide better prediction of clinical outcomes for patients with colon cancer.