Ovarian cancer remains the leading cause of death among all gynaecological cancers, illustrating the urgent need to understand the molecular mechanisms involved in this disease. Eukaryotic initiation factor 3c (EIF3c) plays an important role in protein translation and cancer cell growth and proliferation, but its role in human ovarian cancer is unclear. Our results showed that EIF3c silencing significantly up-regulated 217 and down-regulated 340 genes. Ingenuity Pathway Analysis (IPA) indicated that the top differentially expressed genes are involved in ‘Classical Pathways’, ‘Diseases and Functions’ and ‘Networks’, especially those involved in signalling and cellular growth and proliferation. In addition, eIF3c silencing inhibited cellular proliferation, enhanced apoptosis and regulated the expression of apoptosis-associated proteins. In conclusion, these results indicate that by dysregulating translational initiation, eIF3c plays an important role in the proliferation and survival of human ovarian cancer cells. These results should provide experimental directions for further in-depth studies on important human ovarian cancer cell pathways.

Cervical cancer is one of the most common gynecological malignancies. Due to the high heterogeneity of cervical cancer accelerating cancer progression, it is necessary to identify new prognostic markers and treatment regimens for cervical cancer to improve patients’ survival rates. We purpose to construct and verify a risk prediction model for cervical cancer patients. Based on the analysis of data from the Gene Expression Omnibus database (GEO) and The Cancer Genome Atlas (TCGA), differences of genes in normal and cancer samples were analyzed and then used analysis of WGCNA along with consistent clustering to construct single-factor + multi-factor risk models. After regression analysis, the target genes were obtained as prognostic genes and prognostic risk models were constructed, and the validity of the risk model was confirmed using the receiver operating characteristic curve (ROC) and Kaplan–Meier curve. Subsequently, the above model was verified on the GSE44001 data validation followed by independent prognostic analysis. Enrichment analysis was conducted by grouping the high and low risks of the model. In addition, differences in immune analysis (immune infiltration, immunotherapy), drug sensitivity, and other levels were counted by the high and low risks groups. In our study, three prognostic genes including APOD, APOC1, and SQLE were obtained, and a risk model was constructed along with validation based on the above-mentioned analysis. According to the model, immune correlation and immunotherapy analyses were carried out, which will provide a theoretical basis and reference value for the exploration and treatment of cervical cancer.

ObjectiveTo investigate the clinicopathological characteristics and overall survival in high-risk human papillomavirus (HPV)-independent and HPV-associated cervical cancer.MethodsPatients with cervical cancer hospitalized between September 2015 and December 2019 from the Affiliated Cancer Hospital of Guizhou Medical University were enrolled. First, patients with negative results by HPV primary screening were excluded. Second, the paraffin-embedded tumor tissues from patients with negative results were used for extraction of deoxyribonucleic acid (DNA). The Hybribio K-37 test (PCR and flow-through hybridization for 37 types of HPV) was used to further identify HPV-negative infection status. Finally, 1:4 propensity score matching between high-risk HPV-independent and HPV-associated groups was performed, and the clinicopathological characteristics and overall survival were compared between the two groups.ResultsForty cervical HPV primary screening negative patients were screened of 729 patients (5.5%). Among them, 13 (1.8%) patients who were identified with high-risk HPV-independent cervical cancer after the K-37 test were selected as the study group. There were significant intergroup differences in the distribution of International Federation of Gynecology and Obstetrics (FIGO, 2018) stage (χ2=5.825, p=0.016), pathological types (χ2=6.910, p=0.009), lymph node metastasis (χ2=6.168, p=0.013), and tumor size (χ2=5.319, p=0.021). After propensity score matching, 52 patients from the HPV-associated group were selected as the control group. Patients with high-risk HPV-independent cervical cancer had poorer prognosis than those with HPV-associated cervical cancer (median overall survival: 27 vs 29 months, p=0.03; median disease-free survival: 27 vs 29 months, p=0.021).ConclusionPatients with high-risk HPV-independent cervical cancer more frequently had advanced stage disease, nodal metastasis, larger tumor, and a higher proportion of adenocarcinoma. The prognosis of patients with high-risk HPV-independent cervical cancer was poorer than those with HPV-associated cervical cancer.