An Apoptosis-Related Gene Prognostic Index for Colon Cancer

Abstract

Purpose: To construct an apoptosis-related gene prognostic index (ARGPI) for colon cancer, and clarify the molecular and immune characteristics of the risk subgroup as defined by the prognostic index and the benefits of adjuvant chemotherapy. Integrating the prognostic index and clinicopathological risk factors to better evaluate the prognosis of patients with colon cancer.Methods: Based on the colon adenocarcinoma data in the TCGA database, 20 apoptosis-related hub genes were screened by weighted gene co-expression network analysis (WGCNA). Five genes constituting the prognosis model were determined by Cox regression and verified by the Gene Expression Omnibus (GEO) dataset. Then the molecular and immune characteristics of risk subgroups defined by the prognostic index and the benefits of adjuvant chemotherapy were analyzed. Finally, nomograms integrating ARGPI and four clinicopathological risk factors were used to evaluate the prognosis of patients with colon cancer.Results: The ARGPI was constructed based on the FAS, VWA5A, SPTBN2, PCK1, and TIMP1 genes. In the TCGA cohort, patients in the low-risk subgroup had a longer progression-free interval (PFI) than patients in the high-risk subgroup, which coincided with the results of the GEO cohort. The comprehensive results showed that the high-risk score was related to the enrichment of the cell cycle pathway, high mutation rate of TP53 and KRAS, high infiltration of T regulatory cells (Tregs), immunosuppressive state, and less chemotherapeutic benefit. However, low-risk scores are related to drug metabolism-related pathways, low TP53 and KRAS mutation rates, high infiltration of plasma cells, more resting CD4 memory cells and eosinophils, active immune function, and better chemotherapeutic benefits. Receiver operating characteristic curve of two-year progress prediction evaluation showed that the ARGPI had higher prognostic accuracy than TNM staging. Nomograms integrating ARGPI and clinicopathological risk factors can better evaluate the prognosis of patients with colon cancer.Conclusions: The ARGPI is a promising biomarker for determining risk of colon cancer progression, molecular and immune characteristics, and chemotherapeutic benefit. This is a reliable method to predict the prognosis of colon cancer patients. It also can assist doctors in formulating more effective treatment strategies.

Pancancer transcriptomic profiling identifies key PANoptosis markers as therapeutic targets for oncology

“…However, since several of the PANoptosis genes had correlated expression profiles ( Supplementary Figures S1A–C ), the GLMnet model can result in a diverse set of genes with non-zero coefficients (either beneficial or detrimental to survival) for different initial random seeds ( 63 ). This was an important caveat that has not been accounted for by several previously published techniques using GLMnet models for cox regression analysis ( 5–13 ). To overcome this limitation, we ran our GLMnet model 100 times with 100 random seeds and 5-fold cross-validation to obtain the optimal model (in terms of cross-validation CI) during each run ( Supplementary Figures S7A and B ).…”

“…Though the induction of inflammatory cell death can inhibit the occurrence and development of tumors, pyroptosis and necroptosis can also propagate tumorigenesis ( 81 ). While previous studies have evaluated the roles of pyroptosis, apoptosis and necroptosis independently in cancers ( 5–8 ), increasing evidence suggests there is also a critical role for PANoptosis in cancers ( 17 , 18 , 28 ). Thus, understanding the role of PANoptosis in cancer is of paramount importance for developing more efficient patient stratification systems to guide tumor-specific therapeutic strategies ( 82 ).…”

“…Several distinct innate immune-mediated PCD pathways have been identified ( 4 ), with pyroptosis, apoptosis and necroptosis being the best-characterized. Understanding the clinical impact of PCD in cancer prognosis is important for patient stratification and identifying the molecular mechanisms of cancer pathogenesis, making this an active area of research ( 5–13 ). However, much remains unknown.…”

Adoption of Artificial Intelligence (AI)-Based Computerized Tomography (CT) Evaluation of Comprehensive Nursing in the Operation Room in Laparoscopy-Guided Radical Surgery of Colon Cancer

“…erefore, exponential decay function is used to improve the effect of the difference between the gradient directions of two neighborhoods on weight. Eventually, the improved weight function is expressed by equations ( 13)- (16).…”

“…As a result, the resolution of Z axis and temporal resolution are greatly enhanced. The enhancement provides more comprehensive and visual tutorial information for the stipulation of preoperative staging plan and treatment plan of stomach cancer and colon cancer, and the incision of stomach cancer and colon cancer under laparoscope [ 16 ]. Since multiple factors affect CT images, such as noise and some details being photographed, which make fine particles block the details of images, physicians misdiagnose patients' diseases.…”