Cargando…
Exploring the Relationship Between Senescence and Colorectal Cancer in Prognosis, Immunity, and Treatment
Background: Senescence, as an effective barrier against tumorigenesis, plays a critical role in cancer therapy. However, the role of senescence in colorectal cancer (CRC) has not yet been reported. This study aimed to build a prognostic signature for the prognosis of patients with CRC based on senes...
Autores principales: | , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9240351/ https://www.ncbi.nlm.nih.gov/pubmed/35783270 http://dx.doi.org/10.3389/fgene.2022.930248 |
Sumario: | Background: Senescence, as an effective barrier against tumorigenesis, plays a critical role in cancer therapy. However, the role of senescence in colorectal cancer (CRC) has not yet been reported. This study aimed to build a prognostic signature for the prognosis of patients with CRC based on senescence-related genes. Methods: A prognostic signature was built from TCGA based on differentially expressed senescence-related genes by the least absolute shrinkage and selection operator (LASSO) and Cox regression analyses, which were further validated using two Gene Expression Omnibus (GEO) cohorts. The CIBERSORT and ssGSEA algorithms were utilized to analyze the infiltrating abundance of immune cells. The relationship of signature with the immune therapy and the sensitivity of different therapies was explored. Results: We found 93 genes associated with senescence that were differentially expressed. Based on expression and clinical parameters, we developed a senescence-related prognostic signature and its effectiveness was verified using two external validation cohorts. Overall survival was predicted using a prognostic nomogram that incorporated the predictive values of the risk score and clinical traits. Additionally, the risk score was significantly correlated with immune cells infiltration, tumor immune microenvironment (TME) score, immune checkpoints, immunotherapeutic efficacy, and chemotherapy sensitivity. Conclusion: The senescence-related prognostic model can well predict the prognosis, immunotherapeutic response, and identify potential drug targets, which can help guide individualized treatment. |
---|