| Literature DB >> 29467929 |
Yong Mao1, Chengda Zou2,3, Fanyi Meng2, Jiehong Kong2, Weipeng Wang2, Dong Hua1.
Abstract
The single nucleotide polymorphisms (SNPs) in the microRNA precursor (pre-miRNA) may modulate the posttranscriptional regulation of gene expression and explain individual sensitivity to chemotherapy. Here we investigated the correlation between 23 SNPs in the pre-miRNA and the efficacy of capecitabine-based chemotherapy in 274 advanced colon cancer patients. Statistical analysis indicated that much more patients with rs744591 A/C(48.03%), C/C (53.45%) or C allele (49.73%) responded to the chemotherapy than those with the A/A genotype (33.71%). The response rates of rs745666 G/C heterozygous patients (35.25%) and C allele carriers (39.69%) were apparently less than that of the G/G homozygous patients (56.25%). Moreover, three SNPs rs2114358, rs35770269, and rs73239138 were significantly associated with the occurrence of side effects of chemotherapy. The patients with rs2114358 C allele (OR = 2.016) or rs35770269 T allele (OR = 2.299) were much more prone to endure adverse events. However, the incidence of side effect was lower in the patients carrying rs73239138 A allele than those with G/G genotype (OR = 0.500). Our findings demonstrate that genetic variations in pre-miRNA may influence the efficacy of capecitabine-based chemotherapy in advanced colon cancer patients.Entities:
Keywords: capecitabine; colon cancer; microRNA; polymorphism
Year: 2017 PMID: 29467929 PMCID: PMC5805515 DOI: 10.18632/oncotarget.23190
Source DB: PubMed Journal: Oncotarget ISSN: 1949-2553
The association of genotypes with the efficacy of chemotherapy
| SNP | Genotype | Efficacy (n)a | Response rate (%) | OR (95% CI)b | ||
|---|---|---|---|---|---|---|
| PD + SD | PR + CR | |||||
| rs744591 | A/A | 59 | 30 | 33.71 | Reference | 1.000 |
| A/C | 66 | 61 | 48.03 | 1.815 (1.044–3.155) | ||
| C/C | 27 | 31 | 53.45 | 2.342 (1.193–4.608) | ||
| A/C-C/C | 93 | 92 | 49.73 | 1.969 (1.171–3.300) | ||
| A/A-A/C | 125 | 91 | 42.13 | Reference | 1.000 | |
| C/C | 27 | 31 | 53.45 | 1.639 (0.912–2.941) | 0.109 | |
| A/A-C/C | 86 | 61 | 41.50 | Reference | 1.000 | |
| A/C | 66 | 61 | 48.03 | 1.280 (0.795–2.062) | 0.334 | |
| rs745666 | G/G | 35 | 45 | 56.25 | Reference | 1.000 |
| G/C | 90 | 49 | 35.25 | 0.421 (0.241–0.739) | ||
| C/C | 27 | 28 | 50.91 | 0.794 (0.399–1.580) | 0.598 | |
| G/C-C/C | 117 | 77 | 39.69 | 0.508 (0.300–0.861) | ||
| G/G-G/C | 125 | 94 | 42.92 | Reference | 1.000 | |
| C/C | 27 | 28 | 50.91 | 1.359 (0.754–2.451) | 0.369 | |
| G/G-C/C | 62 | 73 | 54.07 | Reference | 1.000 | |
| G/C | 90 | 49 | 35.25 | 0.463 (0.286–0.751) | ||
a PD, progressive disease; SD, stable disease; PR, partial response; CR, complete response. b OR, odds ratio; CI, confidence interval. c The P values < 0.05 were in bold.
The association of genotypes with the side effects of chemotherapy
| SNP | Genotype | Side effect (n) | Incidence (%) | OR (95% CI)a | ||
|---|---|---|---|---|---|---|
| No | Yes | |||||
| rs2114358 | T/T | 54 | 90 | 62.50 | Reference | 1.000 |
| T/C | 26 | 75 | 74.26 | 1.876 (1.115–3.165) | ||
| C/C | 6 | 23 | 79.31 | 2.639 (1.093–6.369) | ||
| T/C-C/C | 32 | 98 | 75.38 | 2.016 (1.238–3.289) | ||
| T/T-T/C | 80 | 165 | 67.35 | Reference | 1.000 | |
| C/C | 6 | 23 | 79.31 | 2.058 (0.872–4.854) | 0.110 | |
| T/T-C/C | 60 | 113 | 65.32 | Reference | 1.000 | |
| T/C | 26 | 75 | 74.26 | 1.621 (0.978–2.688) | 0.076 | |
| rs35770269 | A/A | 34 | 49 | 59.04 | Reference | 1.000 |
| A/T | 43 | 103 | 70.55 | 2.012 (1.164–3.484) | ||
| T/T | 9 | 36 | 80.00 | 3.759 (1.698–8.333) | ||
| A/T-T/T | 52 | 139 | 72.77 | 2.299 (1.359–3.906) | ||
| A/A-A/T | 77 | 152 | 66.38 | Reference | 1.000 | |
| T/T | 9 | 36 | 80.00 | 2.404 (1.178–4.902) | ||
| A/A-T/T | 43 | 85 | 66.41 | Reference | 1.000 | |
| A/T | 43 | 103 | 70.55 | 1.297 (0.803–2.092) | 0.329 | |
| rs73239138 | G/G | 32 | 91 | 73.98 | Reference | 1.000 |
| G/A | 35 | 65 | 65.00 | 0.523 (0.302–0.905) | ||
| A/A | 19 | 32 | 62.75 | 0.460 (0.239–0.883) | ||
| G/A-A/A | 54 | 97 | 64.24 | 0.500 (0.304–0.822) | ||
| G/G-G/A | 67 | 156 | 69.96 | Reference | 1.000 | |
| A/A | 19 | 32 | 62.75 | 0.630 (0.349–1.136) | 0.132 | |
| G/G-A/A | 51 | 123 | 70.69 | Reference | 1.000 | |
| G/A | 35 | 65 | 65.00 | 0.683 (0.417–1.119) | 0.133 | |
a OR, odds ratio; CI, confidence interval. bThe P values < 0.05 were in bold.
The predicted targets for the polymorphic miRNAs
| SNP | miRNA | Location of SNP | Predicted targets a |
|---|---|---|---|
| rs744591 | miR-3196 | terminal loop | CDA, DHFR, FPGS, SMUG1, UMPS, XRCC3 |
| rs745666 | miR-3615 | terminal loop | ERCC2, NT5C, TP53 |
| rs2114358 | miR-1206 | anti-sense | ABCG2, FPGS, NT5C1A, SLC28A1, TYMS, UCK2, XRCC3 |
| rs35770269 | miR-449c | mature | CDA, NT5C1A, NT5C3A, SLC22A7, UCK2, UMPS |
| rs73239138 | miR-1269a | mature | NME1, SHMT1, SLC29A1, TP53, UCK1 |
aThe target genes are obtained from the Fluoropyrimidine Pathway (PharmGKB: https://www.pharmgkb.org/pathway/PA150653776).