T‐cell exhaustion prediction algorithm in tumor microenvironment for evaluating prognostic stratification and immunotherapy effect of esophageal cancer

Abstract

AbstractEsophageal cancer (EC) is a common digestive malignancy that ranks sixth in cancer deaths, with a 5‐year survival rate of 15%–25%. As a result, reliable prognostic biomarkers are required to accurately predict the prognosis of EC. T‐cell exhaustion (TEX) is associated with poorer prognosis and immune infiltration in EC. In this study, nine risk genes were finally screened to constitute the prognostic model using least absolute shrinkage and selection operator analysis. Patients were divided into two groups based on the expression of the TEX‐related genes: high‐risk group and low‐risk group. The expression of TEX‐related genes differed significantly between the two groups. The findings revealed that the risk model developed was highly related to the clinical prognosis and amount of immune cell infiltration in EC patients. It was also significantly correlated with the therapeutic sensitivity of multiple chemotherapeutic agents in EC patients. Subsequently, we successfully constructed drug‐resistant cell lines KYSE480/CDDP‐R and KYSE180/CDDP‐R to verify the correlation between PD‐1 and drug resistance in EC. Then, we examined the mRNA and protein expression levels of PD‐1 in parental and drug‐resistant cells using qPCR and WB. It was found that the expression level of PD‐1 was significantly increased in the plasma red of drug‐resistant cells. Next, we knocked down PD‐1 in drug‐resistant cells and found that the resistance of EC cells to CDDP was significantly reduced. And the proportion of apoptotic cells in cells treated with 6 μM CDDP for 24 h was significantly in increase. The TEX‐based risk model achieved good prediction results for prognosis prediction in EC patients. And it was also significantly associated with the level of immune cell infiltration and drug therapy sensitivity of EC patients. Additionally, the downregulation of PD‐1 may be associated with increased drug sensitivity in EC and enhanced T‐cell infiltration. The high‐risk group had lower TIDE scores, indicating that the high‐risk group benefits more after receiving immunotherapy. Thus, the TEX‐based risk model can be used as a novel tumor prognostic biomarker.