MATERIAL AND METHODS: Differential gene expression was identified using the "limma" package in R. Prognosis-related LncRNAs were identified via univariate Cox regression analysis, while a prognostic model was crafted using multivariate Cox regression analysis. Survival analysis was conducted using Kaplan-Meier curves. The precision of the prognostic model was assessed through ROC analysis. Subsequently, the Tumor Immune Dysfunction and Exclusion (TIDE) algorithm were executed on the TCGA dataset via the TIDE database. Fractions of 24 types of immune cell infiltration were obtained from NCI Cancer Research Data Commons using deconvolution techniques. The protein expression levels encoded by specific genes were obtained through the TPCA database.
RESULTS: In this research, we have identified 85 LncRNAs associated with TP53 mutations and developed a corresponding signature referred to as TP53MLncSig. Kaplan-Meier analysis revealed a lower 3-year survival rate in high-risk patients (46.9%) compared to low-risk patients (74.2%). The accuracy of the prognostic TP53MLncSig was further evaluated by calculating the area under the ROC curve. The analysis yielded a 5-year ROC score of 0.793, confirming its effectiveness. Furthermore, a higher score for TP53MLncSig was found to be associated with an increased response rate to immune checkpoint blocker (ICB) therapy (p = .005). Patients possessing high-risk classification exhibited lower levels of P53 protein expression and higher levels of genomic instability.
CONCLUSION: The present study aimed to identify and validate LncRNAs associated with TP53 mutations. We constructed a prognostic model that can predict chemosensitivity and response to ICB therapy in HCC patients. This novel approach sheds light on the role of LncRNAs in TP53 mutation and provides valuable resources for analyzing patient prognosis and treatment selection.
CONCLUSION: The progress of developing a cancer treatment that may successfully and efficiently target mutant p53 is on the verge of development. Mutant p53 proteins not only initiate oncogenesis but also cause resistance in cancer cells to certain chemo or radiotherapies, further endorse cancer cell survival and promote migration as well as metastasis of cancerous cells. With this regard, many mutant p53 inhibitors have been developed, some of which are currently being evaluated at the pre-clinical level and have been identified and discussed. To date, APR-246 is the most prominent one that has progressed to the Phase III clinical trial.
METHODS: Surgical samples from seven patients with a total of 17 sequential biopsies were retrieved for the study of p53 gene expression using immunohistochemical stain, and gene status by PCR-SSCP for exons 5-8. The tumours were graded according to the WHO classification criteria. P53 was distinctly over-expressed in five transformed higher grade biopsies, and all except one showed electrophoretic mobility shift in PCR-SSCP analysis. Sequencing analysis revealed single nucleotide substitutions in three of four of these high-grade transformed cases with band shift (75%), whereas some other studies reported a lower frequency of 25-30%, and mobility shift result was found to correlate with P53 expression. Lower grade tumours without P53 over-expression did not demonstrate band shift, and sequencing analysis did not reveal mutations.
CONCLUSIONS: We demonstrated the feasibility of adopting PCR-SSCP for screening of p53 mutations in archival tissue samples in this study, and there is a strong correlation of p53 gene over-expression and mutation events in high-grade transformed tumours.