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Genetic analysis of oligo-recurrence breast cancer: correlation with clinical outcomes.
- Source :
- BMC Cancer; 9/15/2023, Vol. 23 Issue 1, p1-10, 10p
- Publication Year :
- 2023
-
Abstract
- Background: We aimed to identify the relationship between the genomic characteristics and clinical outcomes of oligo-metastatic breast cancer. Methods: Oligo-metastatic breast cancer diagnosed by pathology from January 2001 and August 2019 were reviewed and we matched the poly-metastatic patients based on the clinicopathological features of patients included. Clinicopathological values and data of genomic alterations were collected. Oligo-recurrence (oligo-R) was defined as a situation where disease progression occurred in less than 5 anatomical sites and other anatomic areas still suppressed by the ongoing therapy. Results: A total of 26 breast cancer patients were enrolled in our study, including 14 patients with strict oligo-metastatic disease (oligo-R > 6 months) and 12 with simultaneous poly-metastatic disease. PIK3CA, TP53 and ERBB2 were the most common shared alterations identified in patients included. Based on the median time of oligo-R, we divided the patients with oligo-metastasis into longer oligo-R group (oligo-R > 31.04 months) and shorter oligo-R group (oligo-R ≤ 31.04 months). The analysis of PIK3CA mutation sites showed that H1047R mutation was closely associated with oligo-metastasis, rather than poly-metastasis. H1047R mutation also predicted a better prognosis (oligo-R > 31.04 months) in oligo-metastatic breast cancer. In addition, HER2 positive was more likely to be related to a good outcome in patients with oligo-metastasis. Conclusions: Through the genetic analysis of samples from oligo-metastasis, we found the prognostic values of PIK3CA H1047R and HER2 in oligo- and poly-metastasis. We improved the stratification of prognosis and provided new insights for biological behaviors of oligo-metastatic breast cancer. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14712407
- Volume :
- 23
- Issue :
- 1
- Database :
- Complementary Index
- Journal :
- BMC Cancer
- Publication Type :
- Academic Journal
- Accession number :
- 171993500
- Full Text :
- https://doi.org/10.1186/s12885-023-10833-2