Lili Yin

Significance of TP53 Mutational Status‐Associated Signature in the Progression and Prognosis of Endometrial Carcinoma

Background. TP53 mutations are associated with poor outcome for patients with endometrial carcinoma (EC). However, to date, there have been no studies focused on the construction of TP53 mutational status‐associated signature in EC. In this study, we aim to conduct a TP53 mutation‐associated prognostic gene signature for EC. Methods. Hence, we explored the mutational landscape of TP53 in patients with EC based on the simple nucleotide variation data downloaded from The Cancer Genome Atlas (TCGA) database. Differential expression analysis and least absolute shrinkage and selection operator (LASSO)–Cox analysis was used to establish TP53 mutation‐associated prognostic gene signature. The overall survival rate between the high‐risk and low‐risk groups was compared by the Kaplan–Meier (K‐M) method. Results. We found that the TP53 mutation was associated with poor outcome, older age, lower BMI, and higher grade and stage of EC in patients. A TP53 mutational status‐associated signature was established based on transcriptome profiling data. Moreover, the patients in TCGA database were categorized into high‐ and low‐risk groups. Kaplan–Meier (K‐M) analysis indicated that the patients in the high‐risk group have poor survival outcome. Furthermore, receiver operating characteristic (ROC) curves confirmed the robust prognostic prediction efficiency of the TP53 mutational status‐associated signature. Finally, the prognostic ability was successfully verified in the other two datasets from cBioPortal database as well as in 60 clinical specimens. Univariate (hazard ratio (HR) = 1.041, 95%CI = 1.031–1.051, p < 0.001) and multivariate (hazard ratio (HR) = 1.029, 95%CI = 1.018–1.040, p < 0.001) Cox regression analyses indicated that the TP53 mutational status‐associated signature could be used as an independent prognostic factor for EC patients. Conclusion. In summary, our research constructed a powerful TP53 mutational status‐associated signature that could be a potential novel prognostic biomarker and therapeutic target for EC.

DNA methylation subtypes for ovarian cancer prognosis

Ovarian cancer is one of three major malignancies of the female reproductive system. DNA methylation (MET) is closely related to ovarian cancer occurrence and development, and as such, elucidation of effective MET subtype markers may guide individualized treatment and improve ovarian cancer prognosis. To identify potential markers, we downloaded a total of 571 ovarian cancer MET samples from The Cancer Genome Atlas (TCGA), and established a Cox proportional hazards model using the MET spectrum and clinical pathological parameters. A total of 250 prognosis‐related MET loci were obtained by Cox regression, and six molecular subtypes were screened by consensus clustering of CpG loci with a significant difference in both univariate and multivariate analyses. There was a remarkable MET difference between most subtypes. Cluster 2 had the highest MET level and demonstrated the best prognosis, while Clusters 4 and 5 had MET levels significantly lower than those of the other subtypes and demonstrated very poor prognosis. All Cluster 5 samples were at a high grade, while the percentage of stage IV samples in Cluster 4 was greater than in the other subtypes. We obtained five CpG loci using a coexpression network: cg27625732, cg00431050, cg22197830, cg03152385, and cg22809047. Our cluster analysis showed that prognosis in patients with hypomethylation was significantly worse than in patients with hypermethylation. These MET molecular subtypes can be used not only to evaluate ovarian cancer prognosis, but also to fully distinguish the tumor stage and histological grade in patients with ovarian cancer.