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Clin Transl Oncol ; 20(6): 785-793, 2018 Jun.
Article in English | MEDLINE | ID: mdl-29159791

ABSTRACT

PURPOSE: The present study evaluates the massive study of gene expression in metastatic breast carcinoma (MBC) patients using microarray gene expression profiling (MAGE) complemented with conventional sequencing, immunohistochemistry (IHC) and fluorescent "in situ" hybridization (FISH), seeking to optimize the treatment in a subset of heavily pretreated patients and with limited life expectancy. PATIENTS, MATERIAL AND METHODS: MBC patients in hormone therapy progression with survival expectancy of at least 3 months (m) have been included. The MAGE contains gene probes representing genes known to potentially interact with available drugs as cited in the literature. RESULTS: Thirty-nine procedures were performed from October 2010 to April 2016. Within the 30 evaluable procedures, considering all hormonal manipulations as a single line, the patients had received a median of 4 treatment lines prior to MAGE (range 1-7). Progression was observed in 6 cases, stable disease (SD) in 7 cases and partial response (PR) in 16 cases, which implies a clinical benefit rate (SD + PR) of 76%. Actuarial median progression-free survival (PFS) was 6 m (95% CI 2.5-9.5) in patients with clinical benefit. The median overall survival (OS) for the entire series was 11 m (95% CI 2.2-19.8). CONCLUSION: Data presented here indicate that the use of MAGE provides relevant information to establish personalized treatment in frail patients with limited life expectancy in which therapeutic futility is a particularly difficult burden to assume.


Subject(s)
Antineoplastic Combined Chemotherapy Protocols/therapeutic use , Biomarkers, Tumor/genetics , Breast Neoplasms/genetics , Gene Expression Profiling , Gene Expression Regulation, Neoplastic/drug effects , Precision Medicine , Adult , Aged , Aged, 80 and over , Breast Neoplasms/drug therapy , Breast Neoplasms/secondary , Female , Follow-Up Studies , Humans , Middle Aged , Neoplasm Metastasis , Pilot Projects , Prognosis , Survival Rate
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