Molecular Analysis Of Hsa_circ₀000247 And Clinical Analyses Of TTN And GET4 In Non-small Cell Lung Cancer Based On Data Mining Of TCGA And GEO Database

Lung cancer is one of the most common cancers in China with the highest incidence and mortality.Non-small cell lung cancer?NSCLC?is the most common type of lung cancer.Lung adenocarcinoma and lung squamous cell carcinoma are the main pathological types of NSCLC.The occurrence and development of tumors is a complex process of multi-gene out of control and multi-omics regulation?including genome,transcriptome,proteome,etc.?.Traditional treatments including surgery and chemoradiotherapy have little benefit on advanced lung cancer patients.With the innovation of gene chip and high throughput sequencing technology and the rise of bioinformatics,gene-target inhibitors have effectively prolonged the overall survival of patients in clinical trials.Nevertheless,problems such as secondary drug resistance and limited beneficiaries have forced researchers to constantly search for new treatments.As a matter of urgency,research on new targets is still the main theme of cancer research.Meanwhile,data mining and analysis of genome and transcriptome provide a basis for it.This study utilized the high-throughput sequencing or chip data of genomes and transcripts downloaded from TCGA,GEO and other public databases based on bioinformatics analysis,related database prediction and literature screening to find out genes that would benefit more cancer patients.In this study,we focused on three research hotspots of genome and transcriptome studies?including genomic mutations,mRNA expression profiles,circRNA expression profiles?.Based on data mining of genomic mutations,mRNA expression profiles and circRNA expression profiles in non-small cell lung cancer,molecular and clinical studies of three candidate gene were performed.We firstly found that TTN has the highest mutation rate in non-small cell lung cancer patients through data mining of gene mutation.The mutation frequency in lung squamous cell carcinoma patients was significantly higher than that in lung adenocarcinoma patients;TTN missense mutation in lung squamous cell carcinoma patients would have a longer overall survival;Lung squamous cell carcinoma patients with TTN/TP53 co-mutation would have better overall survival and disease-free survival after initial treatment.The second part of of our research focusing on the data mining of mRNA expression profiles showed that GET4 had genomic or transcriptome changes in 27% of patients with lung adenocarcinoma;Combining with multiple chip data,GET4 mRNA was significantly up-regulated compared with normal lung tissues;High expression of GET4 mRNA was significantly correlated with poor overall survival of lung adenocarcinoma patients.Immunohistochemistry showed that the expression of GET4 protein in lung adenocarcinoma was higher than that in adjacent normal tissues.However,the correlation analysis of clinicopathological features showed that GET4 protein expression was not significantly correlated with tumor pathological stage.In the third part of our research screened Hsa_circ₀000247 as candidate gene based on GEO chip mining,circular RNA database and qRT-PCR;The bioinformatics prediction elaborated Hsa_circ₀000247 may functionally combined with HUR protein,but the final results of immunoprecipitation experiments could not support that there was a specific binding between Hsa_circ₀000247 and HUR protein.In this paper,through the data mining of genome and transcriptome in non-small cell lung cancer and clinical relevance/molecular analysis of candidate genes,the research value of TTN missense mutation in lung squamous cell carcinoma and the significance of GET4 transcriptional expression in lung adenocarcinoma are respectively explained.The basis for further verification and mechanism research has been laid.