Table 1.
Summary for the association between PCA and circadian clock genes
| Author | Refs | Study design | Study size | Function | Main result |
|---|---|---|---|---|---|
| Wendeu-Foyet | [111, 112] | Case–control study | 732 cases and 783 controls | Genotyping prediction |
The core-circadian pathway (CLOCK, BMAL1, CRY1/2, PER1/2/3, CSNK1E, NPAS2) (p = 0.0006) was correlated to PCA, both for low (p = 0.002) and high (p = 0.01) grade tumors These pathway was also significant for nightshift workers with aggressive PCA (p = 0.004), and especially predominant for those working at night < 20 years (p = 0.0002) or receiving long nightshift > 10 h/night (p = 0.001) ARNTL, NPAS2, and RORA were significantly related to aggressive PCA for nightshift workers at gene level |
| Zhu | [113] | Case–control study | 1308 cases and 1266 controls | Genotyping prediction | One SNP in nine circadian genes (PER1/2/3, CSNK1E, CRY1/2, ARNTL, CLOCK, NPAS2) were significantly correlated to PCA (both for overall and aggressive risks), while four SNPs in three genes (PER1/3, CLOCK) were varied by disease aggressiveness |
| Chu | [114] | Case–control study | 187 cases and 242 controls | Genotyping prediction | CRY2-variant C allele indicated about 1.7-fold increased PCA risk (95% CI 1.1–2.7) than GG genotype |
| Chu | [115] | Case–control study | 450 cases and 422 controls | Genotyping prediction | NPAS2 variation was related to PCA risk, with one SNP remained statistically significant (rs746924) after Bonferroni correction |
| Yu | [116] | Case–control study | 458 localized and 324 advanced PCA | Genotyping prediction | A SNP of NPAS2 (rs6542993 A > T) was significantly connected to PCA progression, both for localized (p = 0.001) and advanced (p = 0.039) cases |
| Gu | [117] | Bioinformatics tool | 14,818 cases and 14,227 controls | Genotyping prediction | The top two significant genes related to PCA were NPAS2 (pgene < 0.0062) and AANAT (pgene < 0.00078) after Bonferroni correction |
| Mocellin | [118] | Consortium meta-analysis | 14,160 cases and 12,724 controls | Genotyping prediction |
Circadian pathway genetic variation was significantly correlated to PCA (p = 4.1*10–6; top gene ARNTL, gene p = 0.0002) Seven circadian pathway variation (PER1/2, TIMELESS, NPAS2, ARNTL, RORα/β) were significantly related to aggressive PCA |
| Markt | [119] | Kernel machine test | 24, 40, and 105 fatal cases respectively | Genotyping prediction |
None of the 96 SNPs in 12 circadian clocks was individually consistent involved to fatal PCA Even CRY1 variation was just nominally involved to fatal PCA (p = 0.01, 0.05, 0.01 for AGES-Reykjavik, PHS, and HPFS, respectively) |
| Cao | [120] | – | Animal and/or cells | Suppressor-Per1 |
Per1 could interact with AR to inhibit its transcriptional activity in LNCaP Overexpressed Per1 significantly reduced tumor growth and induced apoptosis for PCA cells |
| Jung-Hynes | [121] | – | Animal and/or cells |
Suppressor-Per2, Clock Promoter-Bmal1 |
Bmal1 was increased but Clock and Per2 were dramatically decreased in PCA cells Upregulated Per2 could inhibit tumor growth and viability Melatonin preserved Per2 and Clock while decreased Bmal1 to manage PCA |
| Li | [122] | – | Animal and/or cells |
Suppressor-Per3 Promoter-Bmal1 |
PER3 was downregulated both in human PCA tissue and ALDHhiCD44+ (DP) PCA cells, PER3 concentration was associated to better patient survival Low PER3 level induced expression of BMAL1 to lead phosphorylation of β-catenin and activate WNT/β-catenin pathway in TME |
| Cai | [123] | – | Animal and/or cells | Suppressor-Per3 |
PER3 in paclitaxel-resistant PCA tissue was significantly lower than nonresistant group, upregulation of PER3 induced paclitaxel-resistant PCA being sensitive to paclitaxel Overexpressed PER3 significantly reduced IC-50, arrested cell cycle, and increased apoptosis Overexpressed PER3 attenuated this paclitaxel-resistance by inhibiting Notch1 |