Abstract
BackgroundLung cancer has been the leading cause of tumor related death, and 80% ~ 85% of it is non-small cell lung cancer (NSCLC). Even with the rising molecular targeted therapies, for example EGFR, ROS1 and ALK, the treatment is still challenging. The study is to identify credible responsible genes during the development of NSCLC using bioinformatic analysis, developing new prognostic biomarkers and potential gene targets to the disease.MethodsFirstly, three genes expression profiles GSE44077, GSE18842 and GSE33532 were picked from Gene Expression Omnibus (GEO) to analyze the genes with different expression level (GDEs) between NSCLC and normal lung samples, and the cellular location, molecular function and the biology pathways the GDEs enriched in were analyzed. Then, gene function modules of GDEs were explored based on the protein-protein interaction network (PPI), and the top module which contains most genes was identified, followed by containing genes annotation and survival analysis. Moreover, multivariate cox regression analysis was performed in addition to the Kaplan meier survival to narrow down the key genes scale. Further, the clinical pathological features of the picked key genes were explored using TCGA data.ResultsThree GEO profiles shared a total of 664 GDEs, including 232 up-regulated and 432 down-regulated genes. Based on the GDEs PPI network, the top function module containing a total of 69 genes was identified, and 31 of 69 genes were mitotic cell cycle regulation related. And survival analysis of the 31 genes revealed that 17/31 genes statistical significantly related to NSCLC overall survival, including 4 spindle assembly checkpoints, namely NDC80, BUB1B, MAD2L1 and AURKA. Further, multivariate cox regression analysis identified NDC80 and MAD2L1 as independent prognostic indicators in lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) respectively. Interestingly, pearson correlation analysis indicated strong connection between the four genes NDC80, BUB1B, MAD2L1 and AURKA, and their clinical pathological features were addressed.ConclusionsUsing bioinformatic analysis of GEO combined with TCGA data, we revealed two independent prognostic indicators in LUAD and LUSC respectively and analyzed their clinical features. However, more detailed experiments and clinical trials are needed to verify their drug targets role in clinical medical use.
Highlights
Lung cancer has been the leading cause of tumor related death, and 80% ~ 85% of it is non-small cell lung cancer (NSCLC)
Using bioinformatic analysis of Gene Expression Omnibus (GEO) combined with TCGA data, we revealed two independent prognostic indicators in lung adenocarcinoma (LUAD) and Lung squamous cell carcinoma (LUSC) respectively and analyzed their clinical features
Unearth of the genes with different expression level (GDEs) in NSCLC from normal lung samples GEO2R tool [19] is provided pared with GEO data online, and in the study, it wad used to analyze the GDEs between NSCLC and normal lung samples
Summary
Lung cancer has been the leading cause of tumor related death, and 80% ~ 85% of it is non-small cell lung cancer (NSCLC). Chemotherapy and radiotherapy, targeted therapy is a newly developed clinical curative method in NSCLC involving tens genes, including EGFR, ALK, ROS1, BRAF, HER2, PIK3CA, RET and so on [5]. NDC80, which is short for nuclear division cycle 80, is one of the proteins of outer kinetochore It forms a heterotetramer complex with proteins SPC24, SPC25 and NUF2, and the complex has been known to involve in spindle assembly checkpoint signaling, detecting the unaligned chromosomes to assure the correct segregation of chromosomes. Aberrant expression of NDC80 has been reported in several other tumors [35,36,37,38,39], for instance osteosarcoma, hepatocellulcar carcinoma, colorectal cancer and breast cancer, indicating its potential as a newly bio target
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