The TTK-related gene prognostic index () is based on 8 genes and is associated with patient survival in esophageal squamous cell carcinoma.
Patients classified as low-risk by the TTKPI showed better overall survival outcomes.
The TTKPI positively correlates with levels of key immune checkpoint molecules.
Low-risk patients demonstrated a greater likelihood of benefiting from anti-PD-L1 immunotherapy.
was identified as the most significant prognostic risk gene among the TTK-related genes.
Knockdown of KIF11 significantly reduced cell proliferation and mobility in esophageal squamous cell carcinoma cells.
KIF11 expression in patient samples was negatively correlated with the presence of CD8T cell infiltration.
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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 () 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 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 CD8T 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.
Key numbers
14% vs. 31%
Risk Group Comparison
Response rates in high-risk vs. low-risk ESCC patients undergoing immunotherapy.
179
Overall Survival Improvement
Total number of ESCC patients analyzed for effectiveness.
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