Genetic variation of clock genes and cancer risk: A field synopsis and meta-analysis

Clara Benna, Charlotte Helfrich-Förster, Senthilkumar Rajendran, Halenya Monticelli, Pierluigi Pilati, Donato Nitti, Simone Mocellin

Research output: Contribution to journalReview article

19 Citations (Scopus)

Abstract

BACKGROUND: The number of studies on the association between clock genes' polymorphisms and cancer susceptibility has increased over the last years but the results are often conflicting and no comprehensive overview and quantitative summary of the evidence in this field is available. RESULTS: Literature search identified 27 eligible studies comprising 96756 subjects (cases: 38231) and investigating 687 polymorphisms involving 14 clock genes. Overall, 1025 primary and subgroup meta-analyses on 366 gene variants were performed. Study distribution by tumor was as follows: breast cancer (n=15), prostate cancer (n=3), pancreatic cancer (n=2), non-Hodgkin's lymphoma (n=2), glioma (n=1), chronic lymphocytic leukemia (n=1), colorectal cancer (n=1), nonsmall cell lung cancer (n=1) and ovarian cancer (n=1). We identified 10 single nucleotide polymorphisms (SNPs) significantly associated with cancer risk: NPAS2 rs10165970 (mixed and breast cancer shiftworkers), rs895520 (mixed), rs17024869 (breast) and rs7581886 (breast); CLOCK rs3749474 (breast) and rs11943456 (breast); RORA rs7164773 (breast and breast cancer postmenopausal), rs10519097 (breast); RORB rs7867494 (breast cancer postmenopausal), PER3 rs1012477 (breast cancer subgroups) and assessed the level of quality evidence to be intermediate. We also identified polymorphisms with lower quality statistically significant associations (n=30). CONCLUSIONS: Our work supports the hypothesis that genetic variation of clock genes might affect cancer risk. These findings also highlight the need for more efforts in this research field in order to fully establish the contribution of clock gene variants to the risk of developing cancer. METHODS: We conducted a systematic review and meta-analysis of the evidence on the association between clock genes' germline variants and the risk of developing cancer. To assess result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Subgroup meta-analysis was also performed based on participant features and tumor type. The breast cancer subgroup was further stratified by work conditions, estrogen receptor/progesterone receptor status and menopausal status, conditions associated with the risk of breast cancer in different studies.

Original languageEnglish
Pages (from-to)23978-23995
Number of pages18
JournalOncotarget
Volume8
Issue number14
DOIs
Publication statusPublished - Jan 1 2017

Fingerprint

Neoplasm Genes
Meta-Analysis
Breast Neoplasms
Breast
Neoplasms
Genes
Progesterone Receptors
B-Cell Chronic Lymphocytic Leukemia
Pancreatic Neoplasms
Non-Small Cell Lung Carcinoma
Glioma
Estrogen Receptors
Ovarian Neoplasms
Non-Hodgkin's Lymphoma
Single Nucleotide Polymorphism
Colorectal Neoplasms
Prostatic Neoplasms
Research

Keywords

  • Cancer risk
  • Circadian rhythms
  • Clock genes
  • Meta-analysis
  • SNP

ASJC Scopus subject areas

  • Oncology

Cite this

Benna, C., Helfrich-Förster, C., Rajendran, S., Monticelli, H., Pilati, P., Nitti, D., & Mocellin, S. (2017). Genetic variation of clock genes and cancer risk: A field synopsis and meta-analysis. Oncotarget, 8(14), 23978-23995. https://doi.org/10.18632/oncotarget.15074

Genetic variation of clock genes and cancer risk : A field synopsis and meta-analysis. / Benna, Clara; Helfrich-Förster, Charlotte; Rajendran, Senthilkumar; Monticelli, Halenya; Pilati, Pierluigi; Nitti, Donato; Mocellin, Simone.

In: Oncotarget, Vol. 8, No. 14, 01.01.2017, p. 23978-23995.

Research output: Contribution to journalReview article

Benna, C, Helfrich-Förster, C, Rajendran, S, Monticelli, H, Pilati, P, Nitti, D & Mocellin, S 2017, 'Genetic variation of clock genes and cancer risk: A field synopsis and meta-analysis', Oncotarget, vol. 8, no. 14, pp. 23978-23995. https://doi.org/10.18632/oncotarget.15074
Benna C, Helfrich-Förster C, Rajendran S, Monticelli H, Pilati P, Nitti D et al. Genetic variation of clock genes and cancer risk: A field synopsis and meta-analysis. Oncotarget. 2017 Jan 1;8(14):23978-23995. https://doi.org/10.18632/oncotarget.15074
Benna, Clara ; Helfrich-Förster, Charlotte ; Rajendran, Senthilkumar ; Monticelli, Halenya ; Pilati, Pierluigi ; Nitti, Donato ; Mocellin, Simone. / Genetic variation of clock genes and cancer risk : A field synopsis and meta-analysis. In: Oncotarget. 2017 ; Vol. 8, No. 14. pp. 23978-23995.
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N2 - BACKGROUND: The number of studies on the association between clock genes' polymorphisms and cancer susceptibility has increased over the last years but the results are often conflicting and no comprehensive overview and quantitative summary of the evidence in this field is available. RESULTS: Literature search identified 27 eligible studies comprising 96756 subjects (cases: 38231) and investigating 687 polymorphisms involving 14 clock genes. Overall, 1025 primary and subgroup meta-analyses on 366 gene variants were performed. Study distribution by tumor was as follows: breast cancer (n=15), prostate cancer (n=3), pancreatic cancer (n=2), non-Hodgkin's lymphoma (n=2), glioma (n=1), chronic lymphocytic leukemia (n=1), colorectal cancer (n=1), nonsmall cell lung cancer (n=1) and ovarian cancer (n=1). We identified 10 single nucleotide polymorphisms (SNPs) significantly associated with cancer risk: NPAS2 rs10165970 (mixed and breast cancer shiftworkers), rs895520 (mixed), rs17024869 (breast) and rs7581886 (breast); CLOCK rs3749474 (breast) and rs11943456 (breast); RORA rs7164773 (breast and breast cancer postmenopausal), rs10519097 (breast); RORB rs7867494 (breast cancer postmenopausal), PER3 rs1012477 (breast cancer subgroups) and assessed the level of quality evidence to be intermediate. We also identified polymorphisms with lower quality statistically significant associations (n=30). CONCLUSIONS: Our work supports the hypothesis that genetic variation of clock genes might affect cancer risk. These findings also highlight the need for more efforts in this research field in order to fully establish the contribution of clock gene variants to the risk of developing cancer. METHODS: We conducted a systematic review and meta-analysis of the evidence on the association between clock genes' germline variants and the risk of developing cancer. To assess result credibility, summary evidence was graded according to the Venice criteria and false positive report probability (FPRP) was calculated to further validate result noteworthiness. Subgroup meta-analysis was also performed based on participant features and tumor type. The breast cancer subgroup was further stratified by work conditions, estrogen receptor/progesterone receptor status and menopausal status, conditions associated with the risk of breast cancer in different studies.

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