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The chronic inflammation operates as one of the critical causes of cervical cancer. Activation of HMGB1/RAGE axis could induce the inflammation and lead to multiple types of cancer. However, whether the HMGB1/RAGE axis could affect the development of cervical cancer by regulating the inflammation is unclear. Here, we stimulated normal cervical epithelial cells with lipopolysaccharide (LPS). Next, the expression of RAGE in these cells was suppressed by the RAGE inhibitor. CCK-8 and wound healing assays were performed to detect the proliferation and invasion. To determine how inflammatory factors (IL-1β, IL-6 and TNF-α) expressed in supernatant of these cells, ELISA was conducted. Western blotting was used for the detection of the expression of pyroptosis-related proteins (NLRP3 and caspase4). It was found that stimulation of LPS enhanced the proliferation and invasion of normal cervical epithelial cells. The expression of inflammatory factors (IL-1β, IL-6 and TNF-α) in these cells was promoted as well. Application of RAGE inhibitor abolished the efficacy of LPS on these cells. Furthermore, LPS promoted the expression of NLRP3 and caspase4 in these cells while RAGE inhibitor exerted suppressive effects on the expression of these proteins. In summary, LPS-induced inflammation of normal cervical epithelial cells resulted in the malignant transformation of these cells by activating HMGB1/RAGE axis.

Cervical cancer (CC) is the third most common carcinoma and the fourth leading cause of cancer-associated mortality in women. The deregulation of fatty acid metabolism plays a crucial role in the progression of various tumors. This study is aimed at exploring the prognostic values of fatty acid metabolism- (FAM-) related long noncoding RNAs (lncRNAs) in CC. FAM-related differentially expressed genes (DEGs) and lncRNAs were screened in CC specimens based on TCGA datasets. Univariate analysis was carried out on differentially expressed lncRNAs to screen the survival-related lncRNAs. Multivariate assays were performed on the resulting lncRNAs to create a novel risk model. Survival assays were applied to examine the prognostic abilities of our model. Receiver operating characteristic (ROC) analysis was used to evaluate the accuracy of the new model. The association between risk model and immune responses was analyzed. In this study, we screened 9 differently expressed lncRNAs associated with the clinical outcome of CC patients. A nine-lncRNA signature comprising SCAT1, AC119427.1, AC009097.2, MIR100HG, AC010996.1, AL583856.2, MIAT, AP003774.2, and AC004540.2 was established to predict overall survival of CC. Survival assays revealed that patients’ high risk score showed a shorter overall survival than those with low risk score. Multivariate assays demonstrated that the nine-gene signature was an independent prognostic factor in CC. In addition, we observed that APC_co_stimulation, CCR, and parainflammation were distinctly different between low-risk and high-risk groups. Our group observed a distinct difference in the expressions of CD44, TNFRSF8, CD276, LAG3, TNFRSF14, TMIGD2, VTCN1, TNFRSF25, CD80, NRP1, TNFRSF18, CD70, TNFSF9, and LGALS9 between the two groups of patients. Overall, our findings indicated that the 9 FAM-related lncRNA signature might be a promising prognostic factor for CC and can promote the management of FAM-related therapy in clinical practice.

Ovarian cancer (OC) is the main cause of deaths worldwide in female reproductive system malignancies. Growing studies have indicated that eRNAs could regulate cellular activities in various tumors. Yet the potential roles of eRNAs in OC progression have not been elucidated. Thus, comprehensive assays were needed to screen the critical eRNAs and to explore their possible function in OC. We used Kaplan–Meier methods to identify survival-associated eRNAs in OC based on TCGA datasets. The levels of ZFHX4-AS1 were examined using TCGA datasets. Further exploration was carried out based on the following assays: clinical and survival assays, GO terms, and KEGG assays. TIMER was applied to delve into the relationships between ZFHX4-AS1 and tumor immune infiltration. In this research, we observed 71 survival-related eRNAs in OC patients. ZFHX4-AS1 was highly expressed in OC specimens and predicted a poor prognosis of OC patients. In addition, high ZFHX4-AS1 expression was positively related to the advanced stages of OC specimens. Multivariate assays revealed that ZFHX4-AS1 was an independent prognostic factor for overall survival of OC patients. KEGG analysis indicated that ZFHX4-AS1 may play a regulatory effect on TGF-beta signaling, PI3K-Akt signaling, and proteoglycans in cancer. The pan-cancer validation indicated that ZFHX4-AS1 was related to survival in eight tumors, namely, UCEC, STAD, SARC, OV, ACC, KICH, KIRC, and BLCA. The expression of ZFHX4-AS1 was correlated with the levels of B cells, T cell CD8+, neutrophil, macrophage, and myeloid dendritic cells. Simultaneously, ZFHX4-AS1 may be a prognostic biomarker and a distinctly immunotherapy-related eRNA in OC.