Aiqin He

Construction of artificial neural network (ANN) based on predictive value of prognostic nutritional index (PNI) and neutrophil-to-lymphocyte ratio (NLR) in patients with cervical squamous cell carcinoma

To explore the analytical worth of prognostic nutritional index (PNI) and neutrophil-to-lymphocyte ratio (NLR) in patients with cervical squamous cell carcinoma. The clinical data of 539 patients with cervical cancer in the Affiliated Tumor Hospital of Nantong University from December 2007 to October 2016 were analyzed retrospectively. The ROC is used to select the best cutoff values of PNI and NLR, which are 48.95 and 2.4046. Cox regression analysis was used for univariate and multivariate analysis. Survival differences were assessed by Kaplan–Meier (KM) survival method. Finally, a 3-layer artificial neural network (ANN) model is established. In cervical squamous cell carcinoma, the KM survival curve showed that the overall survival (OS) rate of high-level PNI group was significantly higher than that of low-level PNI group (P < .001), while the OS rate of low-level NLR group was significantly higher than that of high-level NLR group (P = .002). In non-squamous cell carcinoma, there was no significant difference in OS between the 2 groups (P > .005). According to Cox multivariate analysis, preliminary diagnosed PNI and NLR were independent prognostic factors of cervical squamous cell carcinoma (P < .001, P = .008), and pathological type and International Federation of Gynecology and Obstetrics (FIGO) stage also had a certain impact on tumor progression (P = .042, P = .048). The increase of PNI and the decrease of NLR will help patients with cervical squamous cell carcinoma live longer. ANN showed that PNI and NLR were of great importance in predicting survival. Preoperative PNI and NLR are independent predictors of cervical squamous cell carcinoma patients related to clinicopathological features, and have particular value in judging prognosis.

High expression of PYK2 is associated with poor prognosis and cancer progression in early-stage cervical carcinoma

Proline-rich tyrosine kinase-2 (PYK2), also known as calcium dependent tyrosine kinase, regulates different signal transduction cascades that control cell proliferation, migration, and invasion. However, the role of PYK2 in cervical cancer remains to be elucidated. The current study retrospectively included 134 patients with cervical cancer from December 2007 to September 2014. PYK2 expression was detected in tissue microarray and cervical cancer cell lines. Statistical analysis was performed to evaluate its clinicopathological significance. Small interfering RNA (siRNA) was employed to suppress endogenous PYK2 expression in cervical cancer cells to observe the biological function. PYK2 expression was up-regulated in cervical cancer specimens compared with paired adjacent normal cervical tissue samples. Statistical analyses indicated that PYK2 expression might be an independent prognostic indicator for patients with early-stage cervical cancer. A nomogram model was constructed based on PYK2 expression and other clinicopathological risk factors, and it performed well in predicting patients survival. In cellular studies, down-regulation of PYK2 remarkably inhibited cellular proliferation, migration and invasion. PYK2 expression possessed the potential to serve as a novel prognostic marker in cervical cancer patients.

A histone acetylation-based predictive model for immunotherapy response and combinatorial targeting in cervical cancer

Histone acetylation, a fundamental component of epigenetic modification, plays a pivotal role in the progression, treatment, and prognosis of numerous cancers. In this study, we systematically investigated, for the first time, the clinical value of histone acetylation (HAT) modification in the prognostic assessment of cervical cancer. Utilizing the GSE44001 and The Cancer Genome Atlas-CESC databases, a HAT-associated prognostic model comprising 7 pivotal genes was formulated through Lasso-Cox regression analysis. The integration of multiple bioinformatics algorithms (including Cibersort, ESTIMATE, ssGSEA, and TIDE) has enabled the profound delineation of immune microenvironmental characteristics among disparate risk groups. Utilizing molecular docking technology, we conducted a screening process that identified 2 potential target drugs. The prognostic model’s predictive efficacy was successfully validated in an independent cohort. The analysis has revealed that the high-risk group exhibits a pronounced immunosuppressive phenotype. The study identified 2 additional factors that contribute to the prognosis of cervical cancer: CPE and PGK1. These factors have been shown to be significantly associated with poor clinical outcomes. In addition, we have identified 2 drugs that may target CPE and PGK1, namely Z-LLNle-CHO and OSU-03-012. The discovery of these drugs has opened up a new potential pathway for overcoming resistance to immunotherapy. This study addresses a significant research gap concerning HAT in the prognostic assessment of cervical cancer. Furthermore, it offers a crucial molecular basis for clinical decisions regarding individualized therapeutic interventions.

First-line bevacizumab plus chemotherapy in Chinese patients with stage III/IV epithelial ovarian cancer, fallopian tube cancer or primary peritoneal cancer: a phase III randomized controlled trial

First-line bevacizumab plus carboplatin and paclitaxel (CP) is approved for stage III/IV ovarian cancer treatment following initial surgical resection, based on global phase III GOG-0218 and ICON7 trials. This study evaluated the efficacy and safety of bevacizumab + CP as first-line ovarian cancer therapy in Chinese patients. Patients with newly diagnosed, International Federation of Gynecology and Obstetrics (FIGO) stage III/IV epithelial ovarian, fallopian tube, or primary peritoneal cancer post-primary surgery were randomized 1:1 to receive 6 cycles of CP with bevacizumab/placebo, followed by bevacizumab/placebo maintenance until unacceptable toxicity or disease progression. Primary endpoint was investigator-assessed progression-free survival (PFS). Stratification factors were FIGO stage and debulking status (stage III optimally debulked vs stage III suboptimally debulked vs stage IV) and Eastern Cooperative Oncology Group performance status (0 vs 1 or 2). Of randomized patients, 51 received bevacizumab + CP and 49 received placebo + CP. Median PFS was 22.6 months with bevacizumab + CP (95% confidence interval [CI]=18.6, not estimable) and 12.3 months (95% CI=9.5, 15.0) with placebo + CP (stratified hazard ratio=0.30; 95% CI=0.17, 0.53). Treatment-related grade 3/4 adverse events occurred in 46 of 49 (94%) patients receiving bevacizumab + CP, and 34 of 50 (68%) receiving placebo + CP. Bevacizumab + CP showed clinically meaningful improvement in PFS vs placebo + CP, consistent with GOG-0218 results. Safety data were aligned with the known bevacizumab safety profile. These results support first-line bevacizumab + CP therapy in Chinese patients with ovarian cancer. ClinicalTrials.gov Identifier: NCT03635489.