AI Article Synopsis

  • Recent research discovered a new cell death mechanism called disulfidptosis, which is triggered by disulfide stress in conditions like glucose starvation, particularly in cells with increased SLC7A11 expression.
  • This study employed bioinformatics to analyze disulfidptosis-related genes in colorectal cancer (COAD), identifying two distinct molecular subtypes and creating a prognosis risk model based on seven key genes.
  • The study ultimately revealed that patient outcomes could be predicted by classifying them into high-risk and low-risk groups based on the expression of these genes, with further analyses providing insights into immune response and treatment options.

Article Abstract

Background: Recent research has found a new way of cell death: disulfidptosis. Under glucose starvation, abnormal accumulation of disulfide molecules such as Cystine in Solute Carrier Family 7 Member 11 (SLC7A11) overexpression cells induced disulfide stress to trigger cell death. The research on disulfidptosis is still in its early stages, and its role in the occurrence and development of colorectal malignancies is still unclear.

Method: In this study, we employed bioinformatics methods to analyze the expression and mutation characteristics of disulfidptosis-related genes (DRGs) in colorectal cancer. Consensus clustering analysis was used to identify molecular subtypes of Colorectal Adenocarcinoma (COAD) associated with disulfidptosis. The biological behaviors between subtypes were analyzed to explore the impact of disulfidptosis on the tumor microenvironment. Constructing and validating a prognostic risk model for COAD using diverse data. The influence of key genes on prognosis was evaluated through SHapley Additive exPlanations (SHAP) analysis, and the predictive capability of the model was assessed using Overall Survival analysis, Area Under Curve and risk curves. The immunological status of different patients and the prediction of drug treatment response were determined through immune cell infiltration, TMB, MSI status, and drug sensitivity analysis. Single-cell analysis was employed to explore the expression of genes at the cellular level, and finally validated the expression of key genes in clinical samples.

Result: By integrating the public data from two platforms, we identified 2 colorectal cancer subtypes related to DRGs. Ultimately, we established a prognosis risk model for COAD using 7 genes (FABA4+GIPC2+EGR3+HOXC6+CCL11+CXCL10+ITLN1). SHAP analysis can further explained the positive or negative impact of gene expression on prognosis. By dividing patients into high-risk and low-risk groups, we found that patients in the high-risk group had poorer prognosis, higher TMB, and a higher proportion of MSI-H and MSI-L statuses. We also predicted that drugs such as 5-Fluorouracil, Oxaliplatin, Gefitinib, and Sorafenib would be more effective in low-risk patients, while drugs like Luminesib and Staurosporine would be more effective in high-risk patients. Single-cell analysis revealed that these 7 genes not only differ at the level of immune cells but also in epithelial cells, fibroblasts, and myofibroblasts, among other cell types. Finally, the expression of these key genes was verified in clinical samples, with consistent results.

Conclusions: Our research findings provide evidence for the role of disulfidptosis in COAD and offer new insights for personalized and precise treatment of COAD.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11466812PMC
http://dx.doi.org/10.3389/fimmu.2024.1409149DOI Listing

Publication Analysis

Top Keywords

key genes
12
role disulfidptosis
8
colorectal adenocarcinoma
8
cell death
8
death disulfidptosis
8
colorectal cancer
8
risk model
8
model coad
8
shap analysis
8
single-cell analysis
8

Similar Publications

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!