scholarly journals The clinical feature of triple-negative breast cancer in Beijing, China

Author(s):  
Hui Zhao ◽  
Yueqing Feng ◽  
Junzheng Yang

Objective: To collect and analyze the clinical feature of triple-negative breast cancer (TNBC) in Beijing, to provide the information for the local oncologist to make sound treatment plans. Methods: The clinical data of 280 breast cancer patients with TNBC admitted to the oncology hospital of China Academy of Medical Sciences were collected and divided into (recurrence and metastasis) group and non-(recurrence and metastasis) group. Breast cancer patients with TNBC were classified according to age distribution, family history of breast cancer, pathological type, histological grade, clinical stage, tumor thrombus, tumor size and lymph node metastasis. and 15 BRCA1 gene SNP loci were also measured by a high throughput Mass ARRAY time-of-flight mass spectrometry biochip system and compared the expression of 15 BRCA1 gene SNP loci between (recurrence and metastasis) group and non-(recurrence and metastasis) group. χ2 test was used to analyze the difference between two groups, and P<0.05 considered statistically significant. Results: A total of 280 breast cancer patients with TNBC were enrolled in this study, median age 45 years old. There were 117 cases breast cancer patients with TNBC in (recurrence and metastasis) group, accounting for 41.79% in total breast cancer patients with TNBC and 163 cases breast cancer patients with TNBC in non-(recurrence and metastasis) group, accounting for 58.21% in total breast cancer patients with TNBC; There was no significant difference in age distribution, family history of breast cancer, pathological type and histological grade between non-(recurrence and metastasis) group and (recurrence and metastasis) group (P>0.05); but there were significant differences in clinical stage, vascular tumor thrombus, tumor size and lymph node metastasis between two groups (P<0.05); and then we compared the expression of 15 BRCA1 gene SNP loci in (recurrence and metastasis) group and non-(recurrence and metastasis) group, found that BRCA1gene rs 12516 CC loci (38.8% VS 44.4%), BRCA1gene rs 12516 TT loci (15.6% VS 10.4%), BRCA1 gene rs 16940 CC loci (15.1% VS 10.4%), BRCA1 gene rs 16940 TT loci (39.0% VS 44.8%), BRCA1 gene rs 16941 AA loci (38.1% VS 44%), BRCA1 gene rs 16941 GG loci (15.0% VS 10.3%), BRCA1 gene rs16942 AA loci (39.0% VS 44.8%), BRCA1 gene rs16942 GG loci (15.1% VS 10.4%), BRCA1gene rs799906 CC loci (15.9% VS 10.4%), BRCA1gene rs799906 TT loci (38.7% VS 44.8%), BRCA1gene rs799917 CC loci (38.7% VS 44.4%), BRCA1gene rs799917 TT loci (15.7% VS 10.4%), BRCA1gene rs1060915 CC loci (15.5% VS 10.4%), BRCA1gene rs1060915 TT loci (39.1%VS 44.8%), BRCA1gene rs1799966 AA loci (37.7% VS 44.4%), BRCA1gene rs1799966 GG loci (15.1% VS 10.4%), BRCA1 Gene rs2070833 AA loci (3.1% VS 7.0%), BRCA1 Gene rs2070833 CC loci (56.3% VS 51.3%), BRCA1gene rs3737559 GG loci(78.5% VS 84.5%), BRCA1gene rs3737559 GA loci(19.0% VS 14.6%), BRCA1gene rs8176199 AA loci (60.5% VS 64.6%), BRCA1gene rs8176318 GG loci (38.4% VS 43.4%), BRCA1gene rs8176318 TT loci (15.1% VS 10.6%), BRCA1gene rs8176323 CC loci (38.6% VS 43.9%), BRCA1gene rs8176323 GG loci (15.2% VS10.5%), BRCA1gene rs11655505 AA loci (14.9% VS 10.4%), BRCA1gene rs11655505 GG loci (39.1% VS 44.8%) had a difference at the accident rate between recurrence and metastasis group and non-(recurrence and metastasis) group, but the frequencies of genotypes in the (recurrence and metastasis) group and non-(recurrence and metastasis) group were similar, there was no statistical significant correlation between the SNP genotype of the BRCA1 gene and the recurrence and metastasis risk of TNBC (P>0.05). Conclusions: There were higher recurrence and metastasis (41.79%) in total 280 cases breast cancer patients with TNBC in Beijing area; breast cancer patients with TNBC in Beijing area had a unique clinical feature no matter at clinical stage, vascular tumor thrombus, tumor size and lymph node metastasis or the expression of 15 BRCA1 gene SNP loci, those data may provide some information for clinical staff for TBNC treatment.

2008 ◽  
Vol 134 (11) ◽  
pp. 1229-1235 ◽  
Author(s):  
Sebastian Mayer ◽  
Axel zur Hausen ◽  
Dirk Otto Watermann ◽  
Stefan Stamm ◽  
Markus Jäger ◽  
...  

2021 ◽  
Author(s):  
Jingjing Gu ◽  
Dandan Chen ◽  
Zhiqiang li ◽  
Yongliang Yang ◽  
Zhaoming Ma ◽  
...  

Abstract Purpose: This meta-analysis investigated the relationships between the CD44+/CD24- phenotype and tumor size, lymph node metastasis, distant metastasis, disease-free survival (DFS), and overall survival (OS) in 8036 postoperative breast cancer patients enrolled in 23 studies.Methods: A literature search of PubMed, Medline, Cochrane, Embase, and PMC was conducted to identify eligible studies. The combined odds ratios (ORs) and 95% confidence intervals (95%CIs) were analyzed to evaluate the relationships between the CD44+/CD24- phenotype and the pathological and biological characteristics of breast cancer patients, and the combined hazard ratios (HRs) and 95% CIs were calculated to evaluate the relationships between CD44+/CD24- and DFS and OS of breast cancer petients using Stata12.0 software.Results: The CD44+/CD24- phenotype were not related to the tumor size (tumor size > 2.0 cm vs ≤ 2.0 cm, combined OR = 0.98, 95%CI: 0.68–1.34, p = 0.792) and didn’t promote lymph node metastasis (lymph node metastasis vs. no lymph node metastasis, combined OR = 0.94, 95% CI: 0.71–1.26, p = 0.692) and distant metastasis (distant metastasis vs no distant metastasis, combined OR = 3.88, 95% CI: 0.93–16.24, p = 0.064). The CD44+/CD24- phenotype was negatively correlated with postoperative DFS (HR = 1.67, 95% CI: 1.35–2.07, p <0.00001) and OS (combined HR = 1.52, 95%CI: 1.21–1.91, p = 0.0004).Conclusion: These results suggested expression of the CD44+/CD24- phenotype can be used as a reliable indicator of clinical prognosis and a potential therapeutic targets in breastcancer patients.


2004 ◽  
Vol 87 (2) ◽  
pp. 75-79 ◽  
Author(s):  
Osamu Watanabe ◽  
Tadao Shimizu ◽  
Hiroshi Imamura ◽  
Jun Kinoshita ◽  
Yoshihito Utada ◽  
...  

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