Comprehensive Analysis on Prognostic Signature Based on T Cell-Mediated Tumor Killing Related Genes in Gastric Cancer

Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes...

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Bibliographic Details
Published in:Biochemical genetics 2024-02, Vol.62 (1), p.504-529
Main Authors: Zhai, Jiabao, Nie, Chuang, Wang, Wanyu, Liu, Chang, Liu, Tianyu, Sun, Lishuang, Li, Wei, Wang, Wentong, Ren, Xiyun, Han, Xu, Zhou, Haibo, Li, Xin, Tian, Wenjing
Format: Article
Language:English
Subjects:
Biochemistry
Biomedical and Life Sciences
Biomedicine
Cancer
Cluster Analysis
Clustering
DNA microarrays
Drug delivery
drug therapy
Gastric cancer
Gene expression
Genes
Human Genetics
Humans
Immune checkpoint
Immune system
Immunomodulation
Immunomodulators
Immunosuppressive agents
Immunotherapy
Lymphocytes
Lymphocytes T
Medical Microbiology
Medical prognosis
microarray technology
nomogram
Nomograms
Original Article
Patients
Polymerase chain reaction
Prognosis
quantitative polymerase chain reaction
risk
Risk groups
RNA-Seq
sequence analysis
stomach neoplasms
Stomach Neoplasms - genetics
Stomach Neoplasms - therapy
T-Lymphocytes
Tumor-infiltrating lymphocytes
Tumors
Zoology
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Summary:Although immunotherapy is a valuable treatment for gastric cancer (GC), identifying the patients who would benefit most from this approach presents a challenge. In this study, GC patients were divided into two subtypes by consensus clustering according to T cell-mediated tumor killing related genes (TTKRGs), and there were significant differences in tumor-infiltrating immune cells, signaling pathways, and gene expression of immunomodulators and inhibitory immune checkpoints between the two subtypes. Then, we developed an individualized signature based on TTKRGs, and its clinical and predictive value in GC patients for chemotherapeutic and immunotherapeutic responses was assessed. We confirmed the expression levels of signature genes in GC tumor tissue using quantitative real-time polymerase chain reaction (qRT-PCR). Additionally, to improve the accuracy of GC prognosis predictions, we established a nomogram. We further identified some compounds as sensitive drugs targeting GC risk groups. The signature showed significant predictive ability across RNA-seq, microarray, and qRT-PCR cohorts, which could assist in predicting survival, immunotherapeutic and chemotherapeutic outcomes in GC patients.
ISSN:0006-2928
1573-4927
DOI:10.1007/s10528-023-10436-3