Genomics of Breast Cancer Brain Metastases: A Meta-Analysis and Therapeutic Implications.
Thuy Thi NguyenDiaddin HamdanEurydice AngeliJean-Paul FeugeasQuang Van LeFrederic PamoukdjianGuilhem BousquetPublished in: Cancers (2023)
Breast cancer brain metastases are a challenging daily practice, and the biological link between gene mutations and metastatic spread to the brain remains to be determined. Here, we performed a meta-analysis on genomic data obtained from primary tumors, extracerebral metastases and brain metastases, to identify gene alterations associated with metastatic processes in the brain. Articles with relevant findings were selected using Medline via PubMed, from January 1999 up to February 2022. A critical review was conducted according to the Preferred Reporting Items for Systematic Review and Meta-analysis statement (PRISMA). Fifty-seven publications were selected for this meta-analysis, including 37,218 patients in all, 11,906 primary tumor samples, 5541 extracerebral metastasis samples, and 1485 brain metastasis samples. We report the overall and sub-group prevalence of gene mutations, including comparisons between primary tumors, extracerebral metastases and brain metastases. In particular, we identified six genes with a higher mutation prevalence in brain metastases than in extracerebral metastases, with a potential role in metastatic processes in the brain: ESR1, ERBB2, EGFR, PTEN, BRCA2 and NOTCH1 . We discuss here the therapeutic implications. Our results underline the added value of obtaining biopsies from brain metastases to fully explore their biology, in order to develop personalized treatments.
Keyphrases
- brain metastases
- small cell lung cancer
- resting state
- white matter
- systematic review
- functional connectivity
- squamous cell carcinoma
- end stage renal disease
- risk factors
- cerebral ischemia
- genome wide
- cell proliferation
- prognostic factors
- primary care
- copy number
- healthcare
- physical activity
- tyrosine kinase
- randomized controlled trial
- multiple sclerosis
- gene expression
- peritoneal dialysis
- signaling pathway
- electronic health record
- machine learning
- quality improvement
- estrogen receptor