Search

Ya Gao,1,* Hongyang Liu,1,* Junhu Wan,2 Fenghua Chang,1 Lindong Zhang,1 Wenjuan Wang,1 Qinshan Zhang,1 Quanling Feng1 1Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China; 2Department of Clinical Laboratory, Key Clinical Laboratory of Henan Province, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China*These authors contributed equally to this workCorrespondence: Quanling Feng, Department of Obstetrics and Gynecology, The Third Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan, People’s Republic of China, Tel +86-18638963361, Email zzufql@126.comPurpose: Cervical cancer (CC) has the fourth highest incidence and mortality rate among female cancers. Lactate is a key regulator promoting tumor progression. Long non-coding RNAs (lncRNAs) are closely associated with cervical cancer (CC). The study was aimed to develop a prognostic risk model for cervical cancer based on lactate metabolism-associated lncRNAs and to determine their clinical prognostic value.Patients and Methods: In this study, CESC transcriptome data were obtained from the TCGA database. 262 lactate metabolism-associated genes were extracted from MsigDB (Molecular Characterization Database). Then, correlation analysis was used to identify LRLs. Univariate Cox regression analysis was performed afterwards, followed by least absolute shrinkage and selection operator (LASSO) regression analysis and multiple Cox regression analysis. 10 lncRNAs were finally identified to construct a risk score model. They were divided into two groups of high risk and low risk according to the median of risk scores. The predictive performance of the models was assessed by Kaplan-Meier (K-M) analysis, subject work characteristics (ROC) analysis, and univariate and multivariate Cox analyses. To assess the clinical utility of the prognostic model, we performed functional enrichment analysis, immune microenvironment analysis, mutation analysis, and column line graph generation.Results: We constructed a prognostic model consisting of 10 LRLs at CC. We observed that high-risk populations were strongly associated with poor survival outcomes. Risk score was an independent risk factor for CC prognosis and was strongly associated with immune microenvironment analysis and tumor mutational load.Conclusion: We developed a risk model of lncRNAs associated with lactate metabolism and used it to predict prognosis of CC, which could guide and facilitate the progress of new treatment strategies and disease monitoring in CC patients.Keywords: cervical cancer, lactate metabolism, long non-coding RNA, bioinformatics, prognostic model

Additional file 1: Figure S1. High expression of circRUNX1 is related to advanced TNM stage and differentiation grade. Figure S2. CircRUNX1 overexpression promotes ESCC progression. Figure S3. FOXP3 is a downstream target of circRUNX1. Figure S4. FOXP3 knocking down inhibites ESCC cell proliferation and metastasis. Figure S5. CircRUNX1 facilitates ESCC cell progression by regulating FOXP3 in vitro. Figure S6. CircRUNX1 functions as a miR-449b-5p sponge in ESCC cells. Figure S7. The cancer-inhibiting effect of miR-449b-5p in ESCC cells can be reversed by FOXP3. Figure S8. Relative expression of seven candidate circRUNX1 binding proteins in ESCC tissues was predicted from GEPIA. Figure S9. Depletion of circRUNX1 rescues the promotive effect of IGF2BP2 overexpression on malignant behaviors in ESCC cells. Table S1. Sequences of siRNA and shRNA used in this study. Table S2. Primers used in this study. Table S3. Information of top 8 circRNAs in ESCC tissues. Table S4. The correlation between circRUNX1 and ESCC clinicopathological features. Table S5. The correlation between IGF2BP2 and ESCC clinicopathological features.

Background: Long noncoding RNAs (lncRNAs), a class of noncoding RNA nucleotides >200 bp, has been demonstrated to play vital role in the development of cancer. FEZ family zinc finger 1 antisense RNA 1 (FEZF1-AS1) has been reported as an lncRNA which acts as a tumor-promoting effect in some cancers. However, the role of it in esophageal squamous cell carcinoma (ESCC) and its potential regulatory mechanism was unclear now. Methods: qRT-PCR was used to detect the levels of FEZF1-AS1 and mRNA CTNNB1 (β-catenin) in ESCC tissues and cells. Cell transfection experiments were used to knock down or overexpress the level of FEZF1-AS1 in EC1 and EC9706 cell lines. WST-1 assays, cell cycle assays, scratch wound assays, migration, and invasion assays were used to evaluate the function of FEZF1-AS1 in ESCC progression. Results: FEZF1-AS1 was remarkably upregulated in ESCC tissues and cell lines. Silencing of FEZF1-AS1 significantly inhibited the migration and invasion of ESCC cells, while overexpression of FEZF1-AS1 notably accelerated ESCC migration and invasion. Meanwhile, the levels of FEZF1-AS1 had no effect on ESCC cell proliferation and cell cycle. We also found that β-catenin was upregulated in ESCC tissues, and the level of it was positively correlated with the expression of FEZF1-AS1. Silencing of FEZF1-AS1 could decrease the mRNA and protein level of β-catenin, while overexpression FEZF1-AS1 could lead to the contrary. Conclusion: Our results suggested that the expression of lncRNA FEZF1-AS1 played an important role in ESCC progression, especially the motility of the tumor. FEZF1-AS1 may provide us with a new sight for ESCC treatment.

Additional file 3. Table S3.

Additional file 1. Table S1.

Additional file 7. Figure S3.

Additional file 4. Table S4.

Additional file 5. Figure S1.

Additional file 8. Figure S4.

Additional file 2. Table S2.

Additional file 6. Figure S2.