Identification of Biomarker and Co-Regulatory Motifs in Lung Adenocarcinoma Based on Differential Interactions

Regulatory Effect of let-7f Transfection in Non-Small Cell Lung Cancer on its Candidate Target Genes

BACKGROUND

Let-7f has essential impacts on biological processes; however, its biological and molecular functions in lung cancer pathogenesis have yet been remained unclear. We aimed to investigate the expression level of let-7f and its candidate target genes both in lung cancer tissues and A549 cell line.

METHODS

Bioinformatics databases were first used to select candidate target genes of let-7f. Then the relative gene and protein expressions of let-7f and its target genes, including HMGA2, ARID3B, SMARCAD1, and FZD3, were measured in lung tissues of NSCLC patients and A549 cell line using qRT-PCR and Western blotting. The electroporation method was used to transfect A549 cells with let-7f mimic and microRNA inhibitor. The impact of let-7f transfection on the viability of A549 cells was assessed using MTT assay. The expression data of studied genes were analyzed statistically.

RESULTS

Results indicated significant downregulated expression level of let-7f-5p (p = 0.0013) and upregulated level of the HMGA2 and FZD3 in NSCLC cases (p < 0.05). In A549 cells, after transfection with let-7f mimic, the expression of both mRNA and protein levels of HMGA2, ARID3B, SMARCAD1, and FZD3 decreased. Also, the overexpression of let-7f significantly inhibited the A549 cell proliferation and viability (p = 0.017).

CONCLUSION

Our findings exhibited the high value of let-7f and HMGA2 as biomarkers for NSCLC. The let-7f, as a major tumor suppressor regulatory factor via direct targeting genes (e.g. HMGA2), inhibits lung cancer cell viability and proliferation and could serve as a marker for the early diagnostic of NSCLC.

Regulatory Effect of let-7f Transfection in Non-Small Cell Lung Cancer on its Candidate Target Genes

BACKGROUND

Let-7f has essential impacts on biological processes; however, its biological and molecular functions in lung cancer pathogenesis have yet been remained unclear. We aimed to investigate the expression level of let-7f and its candidate target genes both in lung cancer tissues and A549 cell line.

METHODS

Bioinformatics databases were first used to select candidate target genes of let-7f. Then the relative gene and protein expressions of let-7f and its target genes, including HMGA2, ARID3B, SMARCAD1, and FZD3, were measured in lung tissues of NSCLC patients and A549 cell line using qRT-PCR and Western blotting. The electroporation method was used to transfect A549 cells with let-7f mimic and microRNA inhibitor. The impact of let-7f transfection on the viability of A549 cells was assessed using MTT assay. The expression data of studied genes were analyzed statistically.

RESULTS

Results indicated significant downregulated expression level of let-7f-5p (p = 0.0013) and upregulated level of the HMGA2 and FZD3 in NSCLC cases (p < 0.05). In A549 cells, after transfection with let-7f mimic, the expression of both mRNA and protein levels of HMGA2, ARID3B, SMARCAD1, and FZD3 decreased. Also, the overexpression of let-7f significantly inhibited the A549 cell proliferation and viability (p = 0.017).

CONCLUSION

Our findings exhibited the high value of let-7f and HMGA2 as biomarkers for NSCLC. The let-7f, as a major tumor suppressor regulatory factor via direct targeting genes (e.g. HMGA2), inhibits lung cancer cell viability and proliferation and could serve as a marker for the early diagnostic of NSCLC.

The Functional Effects of Key Driver KRAS Mutations on Gene Expression in Lung Cancer

Lung cancer is a common malignant cancer. Kirsten rat sarcoma oncogene (KRAS) mutations have been considered as a key driver for lung cancers. KRAS p.G12C mutations were most predominant in NSCLC which was comprised about 11–16% of lung adenocarcinomas (p.G12C accounts for 45–50% of mutant KRAS). But it is still not clear how the KRAS mutation triggers lung cancers. To study the molecular mechanisms of KRAS mutation in lung cancer. We analyzed the gene expression profiles of 156 KRAS mutation samples and other negative samples with two stage feature selection approach: (1) minimal Redundancy Maximal Relevance (mRMR) and (2) Incremental Feature Selection (IFS). At last, 41 predictive genes for KRAS mutation were identified and a KRAS mutation predictor was constructed. Its leave one out cross validation MCC was 0.879. Our results were helpful for understanding the roles of KRAS mutation in lung cancer.

Integrated analysis reveals candidate genes and transcription factors in lung adenocarcinoma

Lung adenocarcinoma is the most common type of non‑small cell lung cancer in Asia. Therefore, it is important to improve understanding of the underlying transcriptional regulatory mechanisms involved. The present study aimed to identify potential candidate genes and transcription factors (TFs) associated with the disease. Four gene expression profiles were downloaded from the Gene Expression Omnibus database, which included 141 lung adenocarcinoma patients and 191 healthy controls. The differentially expressed genes (DEGs) were screened out and functional annotation was performed. In addition, TFs were identified and a global transcriptional regulatory network was constructed. Integrated analysis gave rise to a total of 1,238 DEGs in lung adenocarcinoma when compared with healthy tissues, including 970 upregulated and 268 downregulated DEGs. The six overexpressed outlier genes of ceruloplasmin, heparan sulfate 6‑O‑sulfotransferase 2, transmembrane protease serine 4, anillin actin binding protein, cellular retinoic acid binding protein 2 and cystatin SN may serve important roles in the development of lung adenocarcinoma. In addition, the downregulation of carbonic anhydrase 4 and S100 calcium binding protein A12 may render these effective diagnostic biomarkers. The results of the transcriptional regulatory network demonstrated that the hub nodes were sex determining region Y‑box 10, Spi‑B transcription factor and nuclear receptor subfamily 4 group A member 2. The four TFs, forkhead box D1, E74‑like ETS transcription factor 5, homeobox A5 and kruppel‑like factor 5, may warrant future investigations into their function in disease development. In conclusion, the present study provided for further studies a list of candidate genes and TFs for the detection and treatment of lung adenocarcinoma.