Cervical cancer (CC) is one of the most common malignancies encountered in gynecology practice. However, there is a paucity of information about specific biomarkers that assist in the diagnosis and prognosis of CC. Pyroptosis is a form of programmed cell death whose different elements are related to the occurrence, invasion, and metastasis of tumors. However, the role of pyroptosis phenomena in the progression of CC has not yet been elucidated. This study focuses on the development of a pyroptosis-associated prognostic signature for CC using integrated bioinformatics to delineate the relationships among the signature, tumor microenvironment, and immune response of the patients. In this respect, we identified a prognostic signature that depends on eight pyroptosis-related genes (PRGs) that designate with better prognostic survival in the low-risk group (P<0.05) and where AUC values were greater than 0.7. A multi-factor Cox regression analysis indicated that such a signature could be used as an independent prognostic factor, and both the DCA and the Nomogram suggested that the proposed prognostic signature had good predictive capabilities. Interestingly, this prognostic signature can be applied to multiple tumors and thus, is versatile from a clinical point of view. In addition, there were significant differences in the tumor microenvironment and immune infiltration status between the high- and low-risk groups (P<0. 05). The core gene granzyme B (GZMB) was screened and the CC-associated regulatory axis, GZMB/ miR-378a/TRIM52-AS1, was constructed, which may promote CC progression, and further experimentation is needed to validate these results.

Background To evaluate the clinical significance of low-frequency electrical stimulation in preventing urinary retention after radical hysterectomy. Methods A total of 91 women with stage IA2–IB2 cervical cancer, who were treated with radical hysterectomy and lymphadenectomy from January 2009 to December 2012, were enrolled into this study and were randomly divided into two groups: trail group (48 cases) and control group (43 cases). Traditional bladder function training and low-frequency electrical stimulation were conducted in the trail group, while patients in the control group were only treated by traditional bladder training. The general condition, rate of urinary retention, and muscle strength grades of pelvic floor muscle in the perioperative period were compared between these two groups. Results The incidence of postoperative urinary retention in the electrical stimulation group was 10.41%, significantly lower than that in the control group (44.18%), and the difference was statistically significant ( P < 0.01). The duration of postoperative fever and use of antibiotics were almost the same between these two groups. Eleven days after surgery, the difference in grades of the pelvic floor muscle between these two groups was not statistically significant. However, 14 days after the operation, grades of the pelvic floor muscle were significantly higher in the trail group than in the control group, and the difference was statistically significant ( P < 0.01). In addition, although there was no significant difference between the two groups with different parameters ( P = 0.782), the incidence of urinary retention was lower in the endorphins analgesia program group than in the neuromuscular repair program group (9.09% < 11.54%). Conclusion Low-frequency electrical stimulation is more effective than conventional intervention in preventing urinary retention after radical hysterectomy. It also intensifies the recovery of pelvic muscle strength.

Background Uterine corpus endometrial carcinoma (UCEC) is a frequent gynecological malignancy with a poor prognosis particularly at an advanced stage. Herein, this study aims to construct prognostic markers of UCEC based on immune-related genes to predict the prognosis of UCEC. Methods We analyzed expression data of 575 UCEC patients from The Cancer Genome Atlas database and immune genes from the ImmPort database, which were used for generation and validation of the signature. We constructed a transcription factor regulatory network based on Cistrome databases, and also performed functional enrichment and pathway analyses for the differentially expressed immune genes. Moreover, the prognostic value of 410 immune genes was determined using the Cox regression analysis. We then constructed and verified a prognostic signature. Finally, we performed immune infiltration analysis using TIMER-generating immune cell content. Results The immune cell microenvironment as well as the PI3K-Akt, and MARK signaling pathways were involved in UCEC development. The established prognostic signature revealed a ten-gene prognostic signature, comprising of PDIA3, LTA, PSMC4, TNF, SBDS, HDGF, HTR3E, NR3C1, PGR, and CBLC. This signature showed a strong prognostic ability in both the training and testing sets and thus can be used as an independent tool to predict the prognosis of UCEC. In addition, levels of B cells and neutrophils were significantly correlated with the patient’s risk score, while the expression of ten genes was associated with immune cell infiltrates. Conclusions In summary, the ten-gene prognostic signature may guide the selection of the immunotherapy for UCEC.