Discussion
endometrial cancer, tumor, cancer, UCEC, cholangiocarcinoma
CANCER, ENDOMETRIAL CANCER, CHOLANGIOCARCINOMA, TUMOR
The prevalence of endometrial cancer is on the rise, and although surgery usually leads to positive outcomes for early-stage casesUsing 14 DALPMs, we constructed a prognostic model to forecast the patients' prognosis in this research. By conducting co-expression analysis, a set of 1,136 lncRNAs linked to 10 disulfide death genes were extracted to acquire DALPM suitable for prognostic modeling. We obtained the 14 DALPMs for building our prognostic risk model through LASSO, univariate Cox, and multivariate Cox analyses. After examining these 14 DALPMs, we identified U91328.1, AC244517.7, AC009779.2, AC090617.5, AC093382.1, and BOLA3-AS1 as potential prognostic indicators for specific types of cancerTo assess the necessity and accuracy of our model, we categorized patients into high and low risk groups by calculating the risk score using DALPMs. The KM curves for OS and PFS demonstrated a clear distinction in survival rates between patients, which implies that it is important to consider the treatment and prognosis of patients classified as high risk. We also conducted univariate and multivariate Cox analyses, revealing that the risk score independently predicts the prognosis of UCEC and generated ROC curves to compare the risk scores with other clinical factors currently in use. According to the ROC curves, the risk score exhibited the highest AUC value, indicating that utilizing the risk score as a predictor may provide a relatively more precise assessment of the prognosis for patients with UCEC. By combining risk scores with other clinical factors, the nomogram and calibration curve were created to estimate the 1-, 3-, and 5-year survival rates for patients. Furthermore, the risk scores can be used to differentiate the survival outcomes of patients with varying clinical stages. The precision examinations for our model produced extremely pleasing outcomes, suggesting its capability to precisely forecast the prognosis of patients diagnosed with UCEC.The concept of TME, the existence of benign cells and constituents within tumor cellsDespite the absence of a general disparity in immune cell scores, a closer examination revealed discrepancies in particular immune cell populations, including memory B cells and activated CD4 memory T cells, among the high and low risk groups. The immune cells that are expressed differently in the TME could serve as potential targets for therapeutic interventions in UCEC. Immune cells with the ability to adapt, like B cells and T cells, have a significant impact on the TMEWe examined the immune pathways that exhibited variations among patients in the two groups and observed variations in aDCs, APC-co-inhibition, macrophages, parainflammation, and Type-I-IFN-Reponse. Type-I-IFN encompasses a broad class of inflammatory cytokines released when the immune system is weakenedTumor mutational burden reflects the genetic mutation in patients. The examination of tumor mutation adherence indicated that the low-risk group exhibited a greater TMB compared with the high risk group, signifying a disparity in TMB between the two groups. PTEN, which plays a significant role in the advancement and therapy of cancer, exhibited the highest mutation rate among both groups. The inhibition of PTEN can enhance the release of exosomes and the spread of cholangiocarcinoma by impeding TFEB-mediated formation of lysosomesThe analysis of TIDE, which investigates the possibility of tumor evasion during immunotherapy, uncovered variations in TIDE scores among the groups at high and low risk. The group at increased risk demonstrated elevated TIDE scores, suggesting a higher probability of immune evasion during immunotherapy. This aligns with our earlier TME analysis. In addition, we performed drug susceptibility analysis to compare the effectiveness of medications among patients categorized as high and low risk groups. The findings from the drug sensitivity analysis revealed variances in the IC50 values of a total of 19 drugs among patients in both groups. Better treatment effects were observed in patients in the high-risk group when using drugs with lower IC50 values, such as Cisplatin, Foretinib, NG-25, TG101348, and WH-4-023, among the screened medications; therefore, these drugs deserve further attention. Our results indicate that our model can predict the prognosis and response to immunotherapy in patients with UCEC, potentially assisting in clinical decision-making.In conclusion, disulfidptosis is a recently discovered form of cellular demise that is linked to cancer. lncRNAs affect cellular biological processes, consequently influencing the treatment of cancer. At present, there is still a lack of research on the disulfidptosis related lncRNAs in UCEC. By utilizing experimental and validation cohorts, our bioinformatics research allows for the investigation of prognostic biomarkers associated with disulfidptosis in UCEC while ensuring the model's reliability. We believe that our research provides a new perspective for the study of UCEC, and we believe that as the research continues to deepen, the prognostic markers we have identified will provide some guidance for clinical practice. We also believe that with the improvement of relevant experiments, this model has sufficient potential to be transformed into clinical tools to serve more patients. For example, we can quantify the expression of LncRNA within the model in the patient's body to comprehensively assess the patient's risk, estimate the patient's prognosis, and provide targeted guidance for treatment. However, our research may have the following limitations to some extent. We searched for UCEC-related datasets in the GEO database and found no dataset that met our analysis criteria. Therefore, we randomly organized the datasets from the TCGA repository to validate the precision of our findings. Furthermore, additional preclinical investigations are required to enhance the model's reliability prior to its implementation in clinical settings.