Collagen prolyl hydroxylase 3 has a tumor suppressive activity in human lung cancer

Li, Yong; Chen, Yuan; Ma, Yunsheng; Nenkov, Miljana; Haase, Daniela; Petersen, Iver

doi:10.1016/j.yexcr.2017.12.020

Cited by 17 publications

(14 citation statements)

References 35 publications

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“…P3H3, a member of the prolyl hydroxylase family exhibits tumor suppressor activity in lung cancer. P3H3 is silenced by the DNA methylation and the ectopic expression of P3H3 circumvented cell proliferation, colony formation, metastasis and invasion of lung cancer [35]. We found the decreased expression of LEPREL1 in A549 and PC9 cell lines as compared to the BEAS cell line and in cancer patients as compared to healthy person ( gure 6).…”

Section: Discussionmentioning

confidence: 74%

Integrated computational analysis revealed hub genes in lung adenocarcinoma

Jamal¹,

Khan²,

Bangash³

et al. 2021

Preprint

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Background Lung cancer (LUCA) is the leading cause of cancer-related morbidities and mortalities globally. Despite the recent advancements in lung cancer research, understanding of the molecular mechanism underlying LUCA tumorigenesis and prognosis remains suboptimal. This study aims to identify the candidate biomarkers and therapeutic genes in lung cancer. Methods In this study, gene expression profiles of GSE30219, GSE33532, GSE32863 and GSE43458 were downloaded from GEO. The differentially expressed genes (DEGs) in LUAD tissue and normal lung tissue with a p-value < 0.05 and a |log fold change (FC)| >1.0 were identified by GEO2R. For functional enrichment analysis of these DEGs, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were performed with KOBAS and DAVID tools. Next, the candidate hub genes were filtered out with Cytoscape using CytoHubba plugin. These hub genes were validated by (the Cancer Genome Atlas) TCGA-based gene expression analysis, protein-protein network interaction (PPI) analysis, survival analysis. Moreover, the expression of these genes in cancer and normal tissue was assessed in the Human Protein Atlas (HPA) database. In addition, miRNA network of the hub genes was constructed. Finally, DGIdb database was used to check the drug-targeting potentials of the hub genes. Results a total of 332 overlapping differentially expressed genes (DEGs) including 73 upregulated and 259 downregulated, respectively were identified. GO analysis revealed that the DEGs were principally regulating various cancer-associated functions and pathways. The module analysis revealed 55 hub genes in 4 modules. The survival analysis through Kaplan-Meier (KM) plotter indicated that the altered expression of these genes resulted in the poor overall survival (OS) of LUCA patients. Moreover, these genes show a differential expression on both protein and mRNA level in cancer patient compared to the normal. In addition, in addition, 6 potential microRNAs (miRNAs) interacting with hub genes were identified. Finally, a list of 117 therapeutic small molecules was tabulated that could facilitate LUCA treatment. Conclusions the findings of this study may help in the development of novel and reliable biomarkers for diagnosis, prognosis and therapeutic intervention for LUAD.

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Section: Discussionmentioning

confidence: 74%

Integrated computational analysis revealed hub genes in lung adenocarcinoma

Jamal¹,

Khan²,

Bangash³

et al. 2021

Preprint

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“…Numerous studies have shown that collagen levels play an essential role in the development of LC [ 20 , 21 ]. Naveen et al .…”

Section: Discussionmentioning

confidence: 99%

Impact of COL6A4P2 gene polymorphisms on the risk of lung cancer: A case-control study

Dang¹,

Zhao²,

Li³

et al. 2021

PLoS ONE

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Lung cancer (LC) is a malignant tumor that poses the greatest threat to human health and life. Most studies suggested that the occurrence of LC is associated with environmental and genetic factors. We aimed to explore the association between COL6A4P2 single nucleotide polymorphisms (SNPs) and CHD risk in the Chinese Southern Han population. Based on the ‘case-control’ experimental design (510 cases and 495 controls), we conducted an association study between five candidate COL6A4P2 SNPs and the corresponding LC risk. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated by logistic regression to analyze the LC susceptibility under different genetic models. The results showed that COL6A4P2 rs34445363 was significantly associated with LC risk under alleles model (OR = 1.26, 95%CI: 1.01–1.58, p = 0.038). In addition, rs34445363 was also significantly associated with LC risk under the log-additive model (OR = 1.26, 95%CI: 1.01–1.58, p = 0.041). The results of subgroup analysis showed that rs34445363 (OR = 1.42, 95%CI: 1.03–1.95, p = 0.033) and rs61733464 (OR = 0.72, 95%CI: 0.52–0.99, p = 0.048) were both significantly associated with LC risk in the log-additive model among participants who were ≤ 61 years old. We also found that the variation of rs34445363 (GA vs. GG, OR = 1.73, 95%CI: 1.04–2.86, p = 0.034) and rs77941834 (TA vs. TT, OR = 1.88, 95%CI: 1.06–3.34, p = 0.032) were associated with LC risk in the codominant model among female participants. Our study is the first to find that COL6A4P2 gene polymorphism is associated with LC risk in the Chinese Han population. Our study provides a basic reference for individualized LC prevention.

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“…Numerous studies have shown that collagen levels play an important role in the development of LC (19,20). Naveen et al (21) identified collagen VI as a potential biomarker for early diagnosis of LC by proteomic analysis, suggesting that LC is associated with collagen-encoding genes.…”

Section: Discussionmentioning

confidence: 99%

Impact of COL6A4P2 gene polymorphisms on the risk of lung cancer in a Chinese Han population

Duan

Liu

Niu³

et al. 2020

Preprint

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Background The aim of this study was to investigate the effects of COL6A4P2 polymorphisms on lung cancer (LC) in Chinese Han population.Methods To examine whether variants of COL6A4P2 contribute to LC, five single nucleotide polymorphisms (SNPs) of COL6A4P2 were genotyped by Agena MassARRAY in 510 LC patients and 495 controls. Odds ratio (OR) and 95% confidence intervals (CIs) were calculated by logistic regression.Results We found that COL6A4P2 rs34445363 significantly increased the risk of LC in the alleles model (OR = 1.26, 95%CI: 1.01 - 1.58, p = 0.038). And rs34445363 also increased the LC risk under the log-additive model (OR = 1.26, 95%CI: 1.01 - 1.58, p = 0.041) with the multigene model analysis. Further stratification analysis showed that rs34445363 increased the LC risk under the log-additive model (OR = 1.42, 95%CI: 1.03 - 1.95, p = 0.033) in people aged ≤ 61; and rs61733464 was associated with a decreased LC risk in the log-additive model (OR = 0.72, 95%CI: 0.52 - 0.99, p = 0.048) in people aged ≤ 61. We also found that the mutations of rs34445363 and rs77941834 were associated with increased LC risk in the codominant model (rs34445363, GA vs. GG, OR = 1.73, 95%CI: 1.04 - 2.86, p = 0.034; rs77941834, TA vs. TT, OR = 1.88, 95%CI: 1.06 - 3.34, p = 0.032) in females.Conclusions This study provided an evidence for polymorphisms of COL6A4P2 gene associated to the development of LC, also a new insight into etiology of LC.

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Collagen prolyl hydroxylase 3 has a tumor suppressive activity in human lung cancer

Cited by 17 publications

References 35 publications

Integrated computational analysis revealed hub genes in lung adenocarcinoma

Integrated computational analysis revealed hub genes in lung adenocarcinoma

Impact of COL6A4P2 gene polymorphisms on the risk of lung cancer: A case-control study

Impact of COL6A4P2 gene polymorphisms on the risk of lung cancer in a Chinese Han population

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