Genomic alterations at the basis of treatment resistance in metastatic breast cancer: clinical applications
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Angela Toss1, Federico Piacentini1, Laura Cortesi1, Lucia Artuso2,3, Isabella Bernardis2,3, Sandra Parenti2,3, Elena Tenedini2,3, Guido Ficarra4, Antonino Maiorana4, Anna Iannone5, Claudia Omarini1, Luca Moscetti1, Massimo Cristofanilli6, Massimo Federico2,3,* and Enrico Tagliafico5,*
1Department of Oncology and Haematology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy
2Center for Genome Research, University of Modena and Reggio Emilia, Modena, Italy
3Department of Medical and Surgical Sciences, University of Modena and Reggio Emilia, Modena, Italy
4Department of Pathology, Azienda Ospedaliero-Universitaria Policlinico di Modena, Modena, Italy
5Department of Diagnostics, Clinical and Public Health Medicine, University of Modena and Reggio Emilia, Modena, Italy
6Department of Medicine-Hematology and Oncology, Robert H Lurie Comprehensive Cancer Center, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA
*These authors contributed equally to this work
Angela Toss, email: firstname.lastname@example.org
Keywords: breast cancer; treatment resistance; molecular characterization; next-generation sequencing; somatic mutations
Received: February 08, 2018 Accepted: July 12, 2018 Published: August 03, 2018
The standard of care for breast cancer has gradually evolved from empirical treatments based on clinical-pathological characteristics to the use of targeted approaches based on the molecular profile of the tumor. Consequently, an increasing number of molecularly targeted drugs have been developed. These drugs target specific alterations, called driver mutations, which confer a survival advantage to cancer cells. To date, the main challenge remains the identification of predictive biomarkers for the selection of the optimal treatment. On this basis, we evaluated a panel of 25 genes involved in the mechanisms of targeted treatment resistance, in 16 primary breast cancers and their matched recurrences, developed during treatment. Overall, we found a detection rate of mutations higher than that described in the literature. In particular, the most frequently mutated genes were ERBB2 and those involved in the PI3K/AKT/mTOR and the MAPK signaling pathways. The study revealed substantial discordances between primary tumors and metastases, stressing the need for analysis of metastatic tissues at recurrence. We observed that 85.7% of patients with an early-stage or locally advanced primary tumor showed at least one mutation in the primary tumor. This finding could explain the subsequent relapse and might therefore justify more targeted adjuvant treatments. Finally, the mutations detected in 50% of relapsed tissues could have guided subsequent treatment choices in a different way. This study demonstrates that mutation events may be present at diagnosis or arise during cancer treatment. As a result, profiling primary and metastatic tumor tissues may be a major step in defining optimal treatments.
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