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Pubmed ID: 29250167
Publication Date: 2017/10/10

Associations between abnormal vitamin D metabolism pathway function and non-small cell lung cancer.


Lung cancer is a type of malignant tumor derived from the respiratory system, which is the leading cause of cancer-associated mortality worldwide, of which ~80% of cases are attributable to non-small cell lung cancer (NSCLC). A previous study demonstrated that 1α,25-Dihydroxyvitamin D (1α,25(OH)D), derived from the vitamin D metabolic pathway contributes an antitumor effect. Aberrant expression of the essential enzyme encoding genes, Cytochrome P450 Family 27 Subfamily A Member 1 (), Cytochrome P450 Family 27 Subfamily B Member 1 (), and Cytochrome P450 Family 24 Subfamily A Member 1 () may be associated with lung cancer. However, a lack of evidence exists concerning the association between , , expression and NSCLC. The aim of the present study was to investigate the functions of and expression in NSCLC. Lung cancer tissue and para-carcinoma control tissue were collected from patients with NSCLC. Reverse transcription-quantitative polymerase chain reaction was applied to analyze and mRNA expression in lung cancer tissues. An association analysis was performed between the aforementioned metabolic enzymes and patients with NSCLC age, gender, tumor node metastasis (TNM) stage, pathological type, differentiation and prognosis. and mRNA were upregulated in NSCLC compared with controls (P<0.05). However, no significant differences in expression were observed between NSCLC and control. In addition, expression was not associated with age, sex, smoking or TNM stage, but was associated with pathological type, differentiation and prognosis (P<0.05). expression was significantly associated with TNM stage, differentiation, and prognosis, but not age, sex, smoking or pathological type. In conclusion, and may be considered as independent prognostic factors of NSCLC and may be novel therapeutic targets to assist clinical diagnosis, treatment and prognosis of the disease.
Authors: Ge Nan , Chu Xiu-Mei , Xuan Yun-Peng , Ren Dun-Qiang , Wang Yongjie , Ma Kai , Gao Hui-Jiang , Jiao Wen-Jie ,

Reference:

  1. ncbi.nlm.nih.gov. [Last access 2017/10/10].

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