Genetic analysis identifies the role of HLF in renal cell carcinoma

CHAO YUAN HUANG, SHU PIN HUANG, YU MEI HSUEH, LIH CHYANG CHEN, TE LING LU, BO YING BAO

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)

Abstract

Background/Aim: Circadian rhythm is an internal clock that regulates the cycles of many biological functions. Epidemiological studies have linked aberrant circadian rhythm to an increased susceptibility to cancer and poor patient prognosis. However, there remains a gap in our understanding of genetic variants related to the circadian pathway in renal cell carcinoma (RCC) progression. Patients and Methods: We examined the associations of 150 single nucleotide polymorphisms (SNPs) in 12 core circadian pathway genes with RCC risk and survival in 630 patients with RCC and controls. Results: After adjusting for multiple comparisons and performing multivariate analyses, we found that the HLF rs6504958 polymorphism was significantly associated with RCC risk (q<0.05), whereas, no SNP association was significant for survival. Furthermore, the rs6504958 G allele was associated with reduced expression of HLF; consequently, a lower HLF expression was correlated with more advanced RCC. Moreover, a metaanalysis of six kidney cancer gene expression datasets demonstrated that an elevated HLF expression was associated with a favorable prognosis in patients with RCC (hazard ratio=0.70, 95% confidence interval=0.65-0.76, p<0.001). Conclusion: These findings implicate the potential protective role of HLF in the progression of RCC.

Original languageEnglish
Pages (from-to)827-833
Number of pages7
JournalCancer Genomics and Proteomics
Volume17
Issue number6
DOIs
Publication statusPublished - Dec 2020

Keywords

  • Circadian rhythm
  • Metastasis-free survival
  • Overall survival
  • Renal cell carcinoma
  • Single nucleotide polymorphism

ASJC Scopus subject areas

  • Biochemistry
  • Molecular Biology
  • Genetics
  • Cancer Research

Fingerprint

Dive into the research topics of 'Genetic analysis identifies the role of HLF in renal cell carcinoma'. Together they form a unique fingerprint.

Cite this