Risk model based on genes regulating the response of tumor cells to T-cell-mediated killing in esophageal squamous cell carcinoma

Feb 2, 2024Aging

Risk model based on genes controlling tumor cell response to T-cell killing in esophageal squamous cell cancer

AI simplified

Circadian Biology on OpenScience ↗PubMed ↗DOI ↗

Abstract

A prognostic risk scoring model based on eight genes regulating tumor cell killing by T cells may predict overall survival in patients with esophageal squamous cell carcinoma (ESCC).

Patients with ESCC were categorized into high- and low-risk groups according to the model derived from gene data.
The high-risk group showed significant immune cell infiltration and higher expression of immune checkpoints and inflammation-related genes.
Responses to immunotherapy and neoadjuvant chemotherapy were greater in the high-risk group compared to the low-risk group.
Drug sensitivity analysis indicated lower resistance to certain drugs in high-risk patients, while low-risk patients showed lower resistance to other agents.
Differential expression of genes related to tumor cell killing was confirmed in ESCC tissues compared to adjacent non-cancerous tissues.

AI simplified

Immune checkpoint inhibitors (ICIs) represent a promising therapeutic approach for esophageal squamous cell carcinoma (ESCC). However, the subpopulations of ESCC patients expected to benefit from ICIs have not been clearly defined. The anti-tumor cytotoxic activity of T cells is an important pharmacological mechanism of ICIs. In this study, the prognostic value of the genes regulating tumor cells to T cell-mediated killing (referred to as GRTTKs) in ESCC was explored by using a comprehensive bioinformatics approach. Training and validation datasets were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO), respectively. A prognostic risk scoring model was developed by integrating prognostic GRTTKs from TCGA and GEO datasets using a ridge regression algorithm. Patients with ESCC were divided into high- and low-risk groups based on eight GRTTKs (,,,,,,, and) to predict overall survival in the TCGA cohort. Using Kaplan-Meier curves, receiver operating characteristic curves, and C-index analysis, the high reliability of the prognostic risk-scoring model was certified. The model scores served as independent prognostic factors, and combining clinical staging with risk scoring improved the predictive value. Patients in the high-risk group exhibited abundant immune cell infiltration, including immune checkpoint expression, antigen presentation capability, immune cycle gene expression, and high tumor inflammation signature scores. The high-risk group exhibited a greater response to immunotherapy and neoadjuvant chemotherapy than the low-risk group. Drug sensitivity analysis demonstrated lower IC50 for AZD6244 and PD.0332991 in high-risk groups and lower IC50 for cisplatin, ATRA, QS11, and vinorelbine in the low-risk group. Furthermore, the differential expression of GRTTK-related signatures including CDK2, TCEA1, and TMEM209 were verified in ESCC tissues and paracancerous tissues. Overall, the novel GRTTK-based prognostic model can serve as indicators to predict the survival status and immunotherapy response of patients with ESCC, thereby providing guidance for the development of personalized treatment strategies. EIF4H CDK2TCEA1SPTLC2TMEM209RGP1EIF3D CAPZA3

Full Text

We can’t show the full text here under this license. Use the link below to read it at the source.

View full text ↗

Risk model based on genes regulating the response of tumor cells to T-cell-mediated killing in esophageal squamous cell carcinoma

Abstract

Full Text

You found one interesting study. We’ll send the next 7.

what lands in your inbox each week:

Recent issues from the circadian biology brief

Abstract

Full Text

Related papers

You found one interesting study. We’ll send the next 7.

what lands in your inbox each week:

Recent issues from the circadian biology brief