| Literature DB >> 30186165 |
Haixia Chen1, Jianming Wu1, Zhihong Zhang2, Yong Tang1, Xiaoxuan Li1, Shuangqing Liu2, Shousong Cao1, Xianzhu Li2.
Abstract
Triple-negative breast cancer (TNBC) is a subtype of aggressive breast cancer and characterized by a lack of the expression of estrogen receptor, progesterone receptor and human epidermal growth factor receptor 2. BRCA genes are tumor-suppressor genes that are involved in DNA damage repair and mutations of BRCA genes may increase the risk of developing breast cancer and/or ovarian cancer due to defective DNA repair mechanisms. However, the relationship between BRCA status and TNBC needs to be further investigated and validated. The aim of this meta-analysis was to evaluate the association between BRCA status and TNBC. We systematically searched the electronic databases of MEDLINE (PubMed), Embase, and Cochrane Library to identify relevant publications from April, 1959 to November, 2017. The data from the studies were examined by a meta-analysis using STATA software to calculate the odds ratio (OR) with 95% confidence interval (CI) by fixed-effect and random-effect models. We identified 16 qualified studies from 527 publications with 46,870 breast cancer patients including 868 BRCA1 mutations (BRCA1Mut ) carriers, 739 BRCA2 mutations (BRCA2Mut ) carriers, and 45,263 non-carriers. The results showed that breast cancer patients with BRCA1Mut carriers were more likely to have TNBC than those of BRCA2Mut carriers (OR: 3.292; 95% CI: 2.773-3.909) or non-carriers (OR: 8.889; 95% CI: 6.925-11.410). Furthermore, high expression of nuclear grade and large tumor burden (>2 cm) were significantly more common in breast cancer patients with BRCA1Mut carriers than those of BRCA2Mut carriers (OR: 2.663; 95% CI: 1.731-4.097; P = 0.211) or non-carriers (OR: 1.577; 95% CI: 1.067-2.331; P = 0.157). The data suggest that breast cancer patients with BRCA1Mut are more likely to have TNBC, high nuclear grade, and larger tumor burden.Entities:
Keywords: BRCA1; BRCA2; Triple-negative breast cancer (TNBC); meta-analysis; mutation
Year: 2018 PMID: 30186165 PMCID: PMC6111442 DOI: 10.3389/fphar.2018.00909
Source DB: PubMed Journal: Front Pharmacol ISSN: 1663-9812 Impact factor: 5.810
Figure 1Flow chart for study selection.
The main characteristics of patients included in the studies.
| Haffty | USA | 2006 | NA (NA) | 8 | 2 | 1 | 6 | 13 | 29 |
| Atchley | USA | 2008 | 43 (21–75) | 32 | 24 | 7 | 23 | 54 | 337 |
| Kwong | Hong Kong | 2009 | 42 (21–82) | 8 | 4 | 6 | 11 | 45 | 131 |
| Comen | USA | 2011 | 57.1(NA) | 19 | 6 | 6 | 15 | 39 | 364 |
| Arun | USA | 2011 | 40 (21–73) | 33 | 19 | 2 | 21 | NA | NA |
| Gonzalez-Angulo | USA | 2011 | 51 (27–83) | 12 | 62 | 3 | 62 | NA | NA |
| Xu | China | 2011 | 50.6 (29–76) | 28 | 24 | 8 | 20 | 40 | 232 |
| Noh | Korea | 2013 | 40 (28–52) | 16 | 9 | 6 | 16 | 30 | 143 |
| Yu | Korea | 2014 | NA (12–96) | 49 | 31 | 13 | 88 | 6,842 | 34,758 |
| Zugazagoitia | Spain | 2014 | 32 (NA) | 7 | 5 | 1 | 7 | NA | NA |
| Li | China | 2014 | 39.7 (24-64) | 18 | 78 | 7 | 78 | NA | NA |
| Aleskandarany | UK | 2015 | 42 (NA) | 31 | 15 | 2 | 25 | 297 | 1552 |
| Krammer | Germany | 2017 | 44.1(24–82) | 128 | 99 | 26 | 185 | NA | NA |
| Ha | Korea | 2017 | 39.7(25–72) | 52 | 47 | 27 | 76 | NA | NA |
| Ghouadni | France | 2017 | 52 (38–58) | 18 | 8 | 3 | 10 | NA | NA |
| Gabaldó Barrios | Spain | 2017 | NA | 25 | 13 | 8 | 32 | 43 | 252 |
n, number; NA: not applicable.
Figure 2The odds ratio (OR) of BRCA1 mutations vs. BRCA2 mutations in patients with TNBC by Forest Plot.
Figure 3The odds ratio (OR) of BRCA1 mutations vs. non-carriers in patients with TNBC by Forest Plot.
Figure 4The odds ratio of BRCA2 mutations vs. non-carriers in patients with TNBC by Forest Plot.
Associations between BRCA mutation status and tumor size or nuclear grade.
| Haffty | NA | NA | NA | NA | NA | NA | NA | NA | 8 |
| Atchley | NA | NA | NA | NA | NA | NA | NA | NA | 8 |
| Kwong | 6 | 18 | 7 | 2 | NA | NA | NA | NA | 7 |
| Comen | NA | NA | NA | NA | NA | NA | NA | NA | 7 |
| Arun | 6 | 51 | 5 | 18 | 10 | 45 | 11 | 10 | 8 |
| Gonzalez-Angulo | NA | NA | NA | NA | NA | NA | NA | NA | 7 |
| Xu | 11 | 41 | 8 | 20 | 20 | 32 | 14 | 14 | 7 |
| Noh | 15 | 10 | 25 | 7 | 6 | 19 | 20 | 12 | 7 |
| Yu | 37 | 38 | 54 | 38 | 20 | 30 | 33 | 29 | 7 |
| Zugazagoitia | 6 | 18 | 7 | 2 | NA | NA | NA | NA | 7 |
| Li | NA | NA | NA | NA | NA | NA | NA | NA | 7 |
| Aleskandarany | 24 | 24 | 11 | 16 | NA | NA | NA | NA | 8 |
| Krammer | NA | NA | NA | NA | 65 | 160 | 110 | 105 | 7 |
| Ha | 49 | 40 | 41 | 53 | 45 | 54 | 66 | 37 | 7 |
| Ghouadni | NA | NA | NA | NA | NA | NA | NA | NA | 7 |
| Gabaldó Barrios | NA | NA | NA | NA | NA | NA | NA | NA | 7 |
TS, tumor size; NG, nuclear grade; NOS, new castle-ottawa Scale; n, number; NA, not applicable.
Figure 5Indication of publication bias for the association between BRCA1 mutations and BRCA2 mutations by Begg's Funnel Plot with pseudo 95% confidence limits. The data indicate that there was no obvious indication of publication bias.
Figure 6Indication of publication bias for the association between BRCA1 mutations and non-carriers by Begg's Funnel Plot with pseudo 95% confidence limits. The data indicate that there was no obvious indication of publication bias.