Xue Pan

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.

Independent predictive value of blood inflammatory composite markers in ovarian cancer: recent clinical evidence and perspective focusing on NLR and PLR

AbstractOvarian cancer (OC) is one of the deadliest malignant tumors affecting women worldwide. The predictive value of some blood inflammatory composite markers in OC has been extensively reported. They can be used for early detection and differential diagnosis of OC and can be used for predicting survival, treatment response, and recurrence in the affected patients. Here, we reviewed the predictive values of composite inflammatory markers based on complete blood count, namely neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio, and systemic inflammation index and markers based on blood protein, namely C-reactive protein-to-albumin ratio and prognostic nutritional index in OC, with a focus on NLR and PLR. We referred to the clinical studies on these six markers, reviewed the patient population, and summarized the marker cut-off values, significance, and limitations of these studies. All these studies were retrospective and most of them were single-center clinical studies with small sample sizes. We found that the cut-off values of these markers have not been unified, and methods used to determine these values varied among studies. The predictive value of these markers on survival was mainly reflected in the postoperative patients of multiple subtypes of ovarian cancer including epithelial OC, high-grade serous ovarian carcinoma, and ovarian clear cell carcinoma. We focused on NLR and PLR and calculated their pooled hazard ratios. NLR and PLR were reliable in predicting overall and progression-free survivals in patients with OC. Therefore, it is necessary to adjust important confounding factors and conduct a long-term follow-up prospective cohort study to further clarify the cut-off values of NLR and PLR and their clinical applications.