Effects of SMC1A on immune microenvironment and cancer stem cells in colon adenocarcinoma.

BACKGROUND

Our previous study suggested that SMC1 has significant functions in colorectal cancer (CRC). However, few reports have shown the effects of structural maintenance of chromosomes 1 (SMC1A) on the immune microenvironment and tumor stem cells.

METHODS

The Cancer Genome Atlas (TCGA) database, CPTAC database, Human Protein Atlas (HPA) database, the Cancer Cell Line Encyclopedia (CCLE) and Tumor Immune Single-cell Hub were used. Flow cytometry and immunohistochemical analysis were checked for immune infiltration on MC38 mice model. Human CRC tissues were tested with RT-qPCR.

RESULTS

The mRNA and protein levels of SMC1A were increased in colon adenocarcinoma (COAD) samples. SMC1A was associated with DNA activity. Interestingly, SMC1A was highly expressed in many types of immune cells at single-cell levels. Moreover, the high expression of SMC1A was positively correlated with immune infiltration, and immunohistochemical analysis showed that SMC1A was positively associated with CD45 expression in MC38 mice model. Also, the percentage of IL4 CD4 T cells (Th2) and FoxP3 CD4 T cells (Tregs) was significantly higher in the SMC1A overexpression group than in control by flow cytometry assay in vivo. SMC1A expression could affect the proliferation of T cells in the mice model. The mutation and somatic cell copy number variation (SCNV) of SMC1A were also associated with immune cell infiltration. In addition to SMC1A in the "hot" T-cell inflammatory microenvironment of colon cancer, SMC1A also positively correlates with the immune checkpoint genes CD274, CTLA4, and PDCD1 in colon adenocarcinoma (COAD) samples. Furthermore, we also found that SMC1A plays a positive correlation with the induction of cancer stem cells (CSCs). Our results also showed that miR-23b-3p binds SMC1A.

CONCLUSION

SMC1A may be a bidirectional target switch that simultaneously regulates the immune microenvironment and tumor stem cells. Moreover, SMC1A may be a biomarker for the prediction of immune checkpoint inhibitor (ICI) therapy.