Identification And Functional Study Of Potentially Coding LncRNA In Esophageal Cancer

Objective:Non-coding RNAs(LncRNAs)play a role at multiple levels,forming a complex molecular network,directly or indirectly regulating a variety of biological processes,and its abnormal expression is also closely related to tumor proliferation,invasion and migration.Recently,studies had shown that LncRNA not only functions in the form of RNA,but some LncRNAs can encode functional peptides(hidden polypeptides or micro-peptides),participating in the formation of clones and EMT transformation of tumor cells.However,the current research results based on Ribo-seq,RNC-seq and mass spectrometry still have significant deficiencies in answering which RNAs can be encoded and their detailed features.Methods:Analyzing the transcriptome sequencing data of matched esophageal cancer tissues and normal esophageal epithelial tissues in the TCGA database to screen for differentially expressed LncRNAs related to esophageal cancer.Integrated analysis of eIF3b-CLIP-seq and iTRAQ mass spectrometry data using Trans-Proteomic Pipeline to enrich and screen for coding-potential LncRNA.Performing Peak-calling and Motif-finding to summarize the characteristics of eIF3b enriched coding-LncRNA and compare the mass spectral coverage and abundance difference of the proteins encoded by coding-LncRNA and known coding protein genes.By constructing expression vectors and customized antibodies to detect the exogenous and endogenous expression of peptide encoded by LncRNA.Knockdown and exogenous expression experiments to detect the effect of LncRNA-encoded short peptides on malignant phenotypes of esophageal cancer cell such as proliferation,clonal formation,and scratch healing ability,combined with esophageal cancer patient data in the TCGA database to analyze the relationship between coding LncRNA and esophagus cancer patients’ survival,tumor stage and immune cell infiltration.Results:eIF3b has binding peaks on both mRNA and LnRNA,but mainly binds to mRNA.The length of the peak that eIF3b binds to LncRNA is generally shorter than the length of the peak that binds to mRNA.eIF3b has a higher abundance in transcription initiation sites of mRNA and LnRNA and translation initiation sites of mRNA.eIF3b has obvious binding peaks in the CDS region(37.63±1.01%VS 10.51±1.89%,P=0.006)and 5’UTR region(9.43 ±0.08%VS 2.375±0.225%,P=0.0011).Through iTRAQ mass spectrometry experiments,we detected a total of 58,984 peptides in esophageal cancer KYSE410,whose length is mainly distributed between 7-16 amino acids.We screened 186 potentially coding LncRNAs by integrated analysis of eIF3b-CLIP-seq and iTRAQ mass spectrometry data using Trans-Proteomic Pipeline.Compared with known proteins,the coverage and expression abundance of short peptides encoded by LncRNA is lower.Through the construction of expression-vectors and customized antibodies,we verified the coding ability of eIF3b-bounded LncRNA AC027682.1,which can encode a 15KD functional short peptide CTCF-AS.CTCF-AS is expressed in normal esophageal epithelial cells and various esophageal cancer cell lines.Analysis of the TCGA database revealed that the expression of CTCF-AS in esophageal cancer tissues was significantly higher than that of normal esophageal tissues(P<0.05),and the survival time of patients with higher expression of CTCF-AS was significantly lower than that of lower(1.781 vs 3.841,HR1.93[95%CI:1.085-3.431];P=0.039).After exogenous expression of CTCF-AS,proliferation,clone formation and scratch healing ability of esophageal cancer cell were enhanced;knockdown of CTCF-AS significantly inhibits the proliferation of esophageal cancer cell.The CTCF-AS expression level was positively correlated with the infiltration score of immunosuppressive cells such as iTreg and TAM.Conclusions:There are many potentially coding LncRNAs in esophageal cancer.eIF3b can effectively enrich potentially coding LncRNAs in a sequence-specific manner.Compared to known proteins,short peptides encoded by LncRNAs have low coverage and low abundance.LncRNA AC027682.1 can encode a peptide,a 15KD short peptide CTCF-AS,which can promote the proliferation of esophageal cancer cells and enhance the clonal formation and scratch healing ability of esophageal cancer cells.CTCF-AS is highly expressed in various cancer tissues including esophageal cancer,and esophageal cancer patients with high expression of CTCF-AS have poor survival.Objective:To construct a multi-LncRNA prognostic model for breast cancer(BRCA)patients based on the TCGA database transcriptome sequencing data and clinical characteristics of 1081 BRCA samples.Methods:1081 breast cancer patients were randomly divided into two groups:training set(541)and validation set(540).Performing differential expression analysis and univariate analysis on 112 paired breast cancer and normal breast tissues’ transcriptome sequencing data in the TCGA database,and screened for differentially expressed LncRNAs(DELncRNAs)that significantly correlated with the prognosis of BRCA(To reduce batch effects,sequencing data has been normalized using the DESeq function).Performing Cox proportional hazard regression using DELncRNAs and establishing a multi-LncRNA prognosis model in the training set,followed by Proportional Hazards Assumption test.Patients were divided into high-risk and low-risk groups based on calculated risk score.Kaplan-Meier method was used for survival analysis,and validation set data was adopted for verification.Besides,the LncRNA-based prognostic model was also expended to lung adenocarcinoma(LUAD)and liver hepatocellular cancer(LIHC)patients in TCGA datasets.Gene Set Enrichment Analysis(GSEA)dissected potential mechanisms of LncRNAs affecting patient’ s overall survival.Results:Transcriptome sequencing data mining filter out 2815 differentially expressed genes including 91 DElncRNA.Cox proportional hazard regression was performed using the 91 DElncRNA of 541 breast cancer patients in the training set to construct a prognostic model,eventually,which is based on five DElncRNAs.They are AC004551.1,MTOR-AS1,KCNAB1-AS2,FAM230G and LINC01283(training set AUC=0.746,validation set AUC=0.650)and this model passed PH hypothesis test(P=0.388).Patients in the high-risk group have poor survival compared with low-risk patients,regardless of the training(MST:7.049 years VS 12.21 years,HR 0.369[95%CI 0.228-0.597];P<0.001)or validation sets(MST:7.57 years VS 10.85 years,HR 0.412[95%CI 0.214-0.793];P<0.001).Similar predictive results were obtained in other TCGA cancer types:LUAD(HR 0.604,95%CI 0.383-0.951,P=0.007)and LIHC(HR 0.551,95%CI 0.307-0.987,P=0.011).GSEA results suggested that the expression signature of five lncRNA is related to the cell cycle regulation of tumor cells.Conclusions:The prognostic model constructed based on expression profile of AC004551.1,MTOR-AS1,KCNAB1-AS2,FAM230G and LINC01283 can be used to predict the prognosis of breast cancer patients,which is helpful to further guide clinical treatment.