Li H, et al. J Gynecol Oncol. 2016 Apr;27(4):e43. https://doi.org/10.3802/jgo.2016.27.e43

The purpose of this study was to analyze the impact of surgery of primary sites on stage IVB cervical cancer patients from a population-based database, the Surveillance, Epidemiology and End Results (SEER). Propensity score matching was performed to minimize heterogeneity in patient between with-surgery group and without-surgery group. Clinicopathological characteristics were compared using the χ² or Fisher's exact test. Survival analysis included the Kaplan-Meier method, log-rank test, and Cox proportional hazards model. Between 2010-2015, a total of 1,139 International Federation of Gynecology and Obstetrics (FIGO) stage IVB cervical cancer patients receiving chemoradiotherapy (CRT) were included in this retrospective study. Within post-matching cohort, the median duration of overall survival (OS) in stage IVB cervical cancer patients receiving CRT was 22 months. The overall 5-year survival rate was 25.7%. The increasing American Joint Committee on Cancer T stage (T1 vs. T2, p=0.033, hazard ratio [HR]=1.79, 95% confidence interval [CI]=1.05-3.05; T1 vs. T3, p=0.003, HR=2.20, 95% CI=1.31-3.67; T1 vs. T4, p=0.037, HR=2.75, 95% CI=1.06-7.12) and visceral metastasis (with vs. without, p=0.038, HR=1.60, 95% CI=1.03-2.49) was reported as independent risk factors of OS. Surgery of primary sites combined with CRT tended to prolong the survival of stage IVB cervical cancer patients (p<0.001, HR=0.36, 95% CI=0.21-0.61) compared with CRT, especially for patients without visceral metastasis (p=0.005, HR=0.31, 95% CI=0.14-0.70). In conclusion, patients with stage IVB cervical cancer may achieve their best outcomes through CRT combined with surgery of primary sites. However, it deserves large scale prospective clinical trials to confirm.

Background: Endometrial cancer was the commonest gynecological malignancy in developed countries. Despite striking advances in multimodality management, however, for patients in advanced stage, targeted therapy still remained a challenge. Our study aimed to investigate new biomarkers for endometrial cancer and establish a novel risk score system of immune genes in endometrial cancer. Methods: The clinicopathological characteristics and gene expression data were downloaded from The Cancer Genome Atlas (TCGA) database. Differentially expressed genes (DEGs) of immune genes between tumors and normal tissues were identified. Protein–protein interaction (PPI) network of immune genes and transcriptional factors was integrated and visualized in Cytoscape. Univariate and multivariate analysis were employed for key genes to establish a new risk score system. Receiver operating characteristic (ROC) curve and survival analysis were performed to investigate the prognostic value of the model. Association between clinical characteristics and the model was analyzed by logistic regression. For validation, we identified 34 patients with endometrial cancer from Fudan University Shanghai Cancer Center (FUSCC). We detected 14-genes mRNA expression and calculated the risk scores of each patients and we performed survival analysis between the high-risk group and the low-risk group. Results: 23 normal tissues and 552 tumor tissues were obtained from TCGA database. 410 immune-related DEGs was identified by difference analysis and correlation analysis. KEGG and GO analysis revealed these DEGs were enriched in cell adhesion, chemotaxis, MAPK pathways and PI3K-Akt signaling pathway, which might regulate tumor progression and migration. All genes were screened for risk model construction and 14 hub immune-related genes (HTR3E, CBLC, TNF, PSMC4, TRAV30, PDIA3, FGF8, PDGFRA, ESRRA, SBDS, CRHR1, LTA, NR2F1, TNFRSF18) were prognostic in endometrial cancer. The area under the curve (AUC) was 0.787 and the high-risk group estimated by the model possessed worse outcome (P < 0.001). Multivariate analysis suggested that the model was indeed an independent prognostic factor (high-risk vs. low-risk, HR = 1.14, P < 0.001). Meanwhile, the high-risk group was prone to have higher grade (P = 0.002) and advanced clinical stage (P = 0.018). In FUSCC validation set, the high-risk group had worse survival than the low-risk group (P < 0.001). Conclusions: In conclusion, the novel risk model of immune genes had some merits in predicting the prognosis of endometrial cancer and had strong correlation with clinical outcomes. Furthermore, it might provide new biomarkers for targeted therapy in endometrial cancer.

Xu Y, et al. J Gynecol Oncol. 2018 Aug;30:e21. https://doi.org/10.3802/jgo.2019.30.e21

Li H, et al. J Gynecol Oncol. 2024 Oct;36:e42. https://doi.org/10.3802/jgo.2025.36.e42

Small cell carcinoma of cervix (SCCC) was a highly aggressive tumor with dismal prognosis. Current treatment strategies manifested poor survival outcomes and novel treatment options were needed exploration. We aimed to investigate several prognostic biomarkers for SCCC and conducted a novel risk-score system to predict cancer specific survival (CSS) in early-stage SCCC. Seven cell-cycle proteins were detected by immunohistochemistry in 88 SCCCs. Univariate and multivariate analysis were performed to identify prognostic proteins and establish a predicting model. Total patients were divided into two groups by the median risk-score: the high-risk group and the low-risk group. Logistic regression and Wilcoxon test were used to investigate the association between clinical variables and the risk-score system. Seven cell cycle proteins were overexpressed in SCCC. The expression of CDC20, MAD2L1, MCM2 and BUBR1 were correlated to survival outcomes with P < 0.05. A novel risk-score system consisting of CDC20, MAD2L1 and BUBR1 was significantly an independent prognostic factor for CSS and the high-risk group possessed worse survival (P < 0.001). The c-indexes for clinical model, risk-score system and the combined model were 0.668, 0.718 and 0.727, respectively. The AUCs for these three models were 0.730, 0.775 and 0.823, respectively. Furthermore, we discovered that patients with high-risk scores were inclined to possessing older age, parametrial invasion and higher FIGO stage (IIA vs IA/IB) with P < 0.05. This risk-score system consisting of CDC20, MAD2L1 and BUBR1 presented good discrimination and predictability for SCCC. Novel biomarkers in this study might have some merits in providing guidance of novel treatment strategies for SCCC.