BACKGROUND

Immune checkpoint inhibitors (ICIs) are emerging promising agents for the treatment of patients with esophageal squamous cell carcinoma (ESCC), however, there are only a small proportion respond to ICI therapy. Therefore, selecting candidate patients who will benefit the most from these drugs is critical. However, validated biomarkers for predicting immunotherapy response and overall survival are lacking. As the fundamental principle of ICI therapy is T cell-mediated tumor killing (TTK), we aimed to develop a unique TTK-related gene prognostic index (TTKPI) for predicting survival outcomes and responses to immune-based therapy in ESCC patients.

METHODS

Transcriptomic and clinical information of ESCC patients were from the GSE53625, GSE53624, GSE47404 and TCGA datasets. TTK-related genes were from the TISIDB database. The LASSO Cox regression model was employed to create the TTKPI. The prediction potential of the TTKPI was evaluated using the KM curve and time-dependent ROC curve analysis. Finally, the relationship between TTKPI and immunotherapy efficacy was investigated in clinical trials of ICIs (GSE91061, GSE135222, IMvigor210 cohort). The role of KIF11 in accelerating tumor progression was validated via a variety of functional experiments, including western blot, CCK-8, colony formation, wound healing scratch, and xenograft tumor model. The KIF11 expression was detected by multiplex fluorescent immunohistochemistry on tissue microarray from ESCC patients.

RESULTS

We constructed the TTKPI based on 8 TTK-related genes. The TTKPI low-risk patients exhibited better overall survival. TTKPI was significantly and positively correlated with the main immune checkpoint molecules levels. Furthermore, the low-risk patients were more prone to reap the benefits of immunotherapy in the cohort undergoing anti-PD-L1 therapy. Moreover, we performed functional experiments on KIF11, which ranked as the most significant prognostic risk gene among the 8 TTK-related genes. Our findings identified that KIF11 knockdown significantly hindered cell proliferation and mobility in ESCC cells. The KIF11 expression was negatively related with CD8 T cell infiltration in ESCC patient samples.

CONCLUSIONS

The TTKPI is a promising biomarker for accurately determining survival and predicting the effectiveness of immunotherapy in ESCC patients. This risk indicator can help patients receive timely and precise early intervention, thereby advancing personalized medicine and facilitating precise immuno-oncology research. KIF11 plays a crucial role in driving tumor proliferation and migration and may act as a potential tumor biomarker of ESCC.