Identification of cellular senescence-associated genes as new biomarkers for predicting the prognosis and...

Area of Science:

• Oncology
• Molecular Biology
• Genomics

Background:

• Lung carcinoma is a leading cause of cancer death globally, with limited treatment advancements.
• Cellular senescence, a state of cell cycle arrest, plays a critical role in tumor development and progression.
• Understanding senescence-related molecular markers is crucial for improving non-small cell lung cancer (NSCLC) outcomes.

Purpose of the Study:

• To identify and analyze cell senescence-related messenger RNAs (mRNAs) associated with NSCLC prognosis.
• To develop a predictive risk model and nomogram for NSCLC based on these senescence-related mRNAs.
• To investigate the relationship between the risk model, immune infiltration, and immunotherapy response in NSCLC.

Main Methods:

• Acquired NSCLC expression data from The Cancer Genome Atlas (TCGA).
• Employed univariate and multivariate Cox proportional hazard models to identify prognostic senescence-related mRNAs.
• Integrated identified mRNAs with clinical-pathological features to construct a prognostic nomogram and assess immune infiltration.

Main Results:

• A risk model comprising 12 senescence-related mRNAs (IGFBP1, TLR3, WT1, ID1, PTTG1, ERRFI1, HEPACAM, MAP2K3, RAD21, NANOG, PRKCD, SOX5) was developed.
• The risk score derived from these mRNAs was a significant independent predictor of NSCLC prognosis (HR > 1, p < 0.001).
• The risk model demonstrated significant differences in immune infiltration and predicted immunotherapy response between high- and low-risk groups.

Conclusions:

• Cellular senescence-related mRNAs are reliable predictors of prognosis in non-small cell lung cancer (NSCLC).
• The developed risk model and nomogram can aid in predicting NSCLC patient outcomes.
• These senescence-related markers are associated with immune infiltration and may predict immunotherapy response in NSCLC.