Circadian rhythm genes contribute to the prognosis prediction and potential therapeutic target in gastric cancer

The role of circadian rhythm genes (CRGs) in gastric cancer (GC) is poorly understood. This study aimed to develop a CRG signature to improve understanding of prognosis and immunotherapy responses in GC patients. We integrated the The Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) dataset with CRGs to develop a prognostic signature for GC. The signature's predictive ability was validated using Kaplan-Meier and ROC curves. The CIBERSORT algorithm evaluated immune cell proportions, and tumor immune dysfunction and exclusion score, as well as immune phenotype score, determined the response to immunotherapy for STAD patients. Finally, we assessed signature genes expression using real-time quantitative polymerase chain reaction. We developed a 4-CRG signature for STAD, demonstrating accurate prognostic ability. The low-risk group showed increased B cell memory and CD8 + T cells, and decreased M2 Macrophages compared to the high-risk group. Patients in the low-risk group had a higher likelihood of benefiting from immunotherapy. Additionally, gastric cancer tissues exhibited elevated expression of OPN3 and decreased expression of TP53 compared to adjacent tissue. This study successfully established a prognostic signature for CRGs, accurately predicting prognosis and immunotherapeutic response among STAD patients, providing insights for the development of personalized therapeutic strategies for these patients.

Authors

Institutions

Publication Details

Journal
Scientific Reports
Published
2024-10-25
DOI
https://doi.org/10.1038/s41598-024-76565-w
Citations
3
Primary Topic
Circadian rhythm and melatonin
Type
article
Field-Weighted Citation Impact
0.82

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Circadian rhythm genes contribute to the prognosis prediction and potential therapeutic target in gastric cancer

Mingming Deng, Li‐Jun Xiao, Muhan Lü, Gang Luo et al.
3 citations
Scientific Reports
Circadian rhythm and melatonin
0.82
article

Circadian rhythm genes contribute to the prognosis prediction and potential therapeutic target in gastric cancer

Mingming Deng, Li‐Jun Xiao, Muhan Lü, Gang Luo, Sha Liu, Chao Zhang, Jing Yu, Wanmeng Xiao, Wen Yin, Liping Yuan
article en
3 citations

Abstract

The role of circadian rhythm genes (CRGs) in gastric cancer (GC) is poorly understood. This study aimed to develop a CRG signature to improve understanding of prognosis and immunotherapy responses in GC patients. We integrated the The Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) dataset with CRGs to develop a prognostic signature for GC. The signature's predictive ability was validated using Kaplan-Meier and ROC curves. The CIBERSORT algorithm evaluated immune cell proportions, and tumor immune dysfunction and exclusion score, as well as immune phenotype score, determined the response to immunotherapy for STAD patients. Finally, we assessed signature genes expression using real-time quantitative polymerase chain reaction. We developed a 4-CRG signature for STAD, demonstrating accurate prognostic ability. The low-risk group showed increased B cell memory and CD8 + T cells, and decreased M2 Macrophages compared to the high-risk group. Patients in the low-risk group had a higher likelihood of benefiting from immunotherapy. Additionally, gastric cancer tissues exhibited elevated expression of OPN3 and decreased expression of TP53 compared to adjacent tissue. This study successfully established a prognostic signature for CRGs, accurately predicting prognosis and immunotherapeutic response among STAD patients, providing insights for the development of personalized therapeutic strategies for these patients.

Scientific ReportsVol. 14(1)
Southwest Medical University (CN), Affiliated Hospital of Southwest Medical University (CN), Binzhou People's Hospital (CN)
Southwest Medical University
Good health and well-being
Openalex Percentile: Top 29%
Circadian rhythm and melatonin
0.82
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.