Background:Lung adenocarcinoma is one of the most common cancer with high mortalities.Currently,surgery is the primary strategy in treatment of lung adenocarcinoma,chemotherapy often served as supplementary regimen.However,early-stage lung adenocarcinomas are usually ignored due to the light symptoms,a majority of patients are in advanced stage when diagnose.For patients who cannot undergo surgeries,chemotherapy or radiotherapy is the first choice in treatment.A number of drugs targeted on lung adenocarcinoma have been applied in clinical,they have mean efficacy in practice.Moreover,the prognosis of lung adenocarcinoma remains poor because of lack of biomarkers with high sensitivity and specificity.Cancer-related metabolism is one of the most popular hot spots in the field of cancer research.The metabolic pattern and profiles is quite different between tumor cells and normal tissue cells.Thus,drugs targeted on cancer-specific metabolic pathways are considered new direction of anti-cancer drug discovery.Bioinformatics is a novel cross subject of biology and information science.It has been widely applied in genetic screening and molecular diagnosis.In this study,we conducted bioinformatics analysis to screen out potent prognosis biomarkers,and validate bioinformatics results via cell and animal experiments.Methods:First,we used R statistic software to screen the differential expressed genes from The Cancer Genome Atlas(TCGA).Library(DESeq)was used to calibrate and analyze the different changes,survival analyses of differential expressed genes were performed by K-M curves and univariate COX regression.In addition,we selected 30 pairs of tissues samples from biobank of Shandong Provincial Hospital.Real-time PCR was used to validate the differential expressed genes from TCGA database.Hesperetin and siRNAs were used to inhibit or knockout UGT1A3 in vitro.Cell damage,IC50 and proliferation inhibition were detected by Sulforhodamine B.Wound healing assay and colony formation assay were used to investigate the inhibition of invasion and migration via Hesperetin or siRNAs.We performed flow cytometry to research cell cycles and apoptosis in condition of Hesperetin and siRNAs.Moreover,we investigate in vivo efficacy of Hesperetin using C57BL/6 mice.Results:UGT1A3 was significantly high expressed in tumor tissues,fold change>103(p<0.0001).The high-express state of UGT1A3 was significantly correlated with poor prognosis(HR=1.500,95%CI:1.053-2.138,p=0.0247).Gene Set Enrichment Analysis(GSEA)indicated that predicted function of UGT1A3 mainly enriched at drug metabolism.Knockout out UGT1A3 in vitro significantly inhibit proliferation of A549 cell line,and induced apoptosis(p<0.0001).Hesperetin exert cell killing function in A549 cell line with IC50:125.006±9.591 ?M,95%CI:121.425 ?M-128.588 pM,while in HBEC cell line,IC50 of Hesperetin was 189.157±11.354Mm,95%CI:184.918?M-193.397?M.Similarly,Hesperetin could also significantly inhibit proliferation of A549 cell line,and induced apoptosis in vitro(p<0.0001).Combination of Hesperetin and carboplatin significantly increased cell sensitivity to carboplatin.The IC50 of carboplatin in combination group was 26.110±1.797Mm,95%CI:25.439?M-26.781 ?M,which is one out of six dose of the single-carboplatin group.In contrast,in HBEC cell line,Hesperetin antagonize the cytotoxic effect of carboplatin.Furthermore,inhibition of proliferation,cell apoptosis and inhibition of invasion and migration were significantly enhanced in combination group than single-agent groups and control group.Tumor volumes of xenograft in combination group were much smaller than those in single-agent groups(p<0.0001).Conclusion:UGT1A3 is a potent prognosis biomarker in lung adenocarcinoma,its inhibitor,Hesperetin,can inhibit proliferation,invasion and migration and induce apoptosis in lung adenocarcinoma cells.Combination of Hesperetin and carboplatin make cancer cell more sensible to carboplatin as well as decrease the cytotoxic effect of carboplatin to normal bronchial epithelial cells. |