Naoko Matsuda1,2, Bora Lim1,2, Ying Wang3, Savitri Krishnamurthy4,2, Wendy Woodward5,2, Ricardo H Alvarez1,2, Anthony Lucci6,2, Vicente Valero1,2, James M Reuben7,2, Funda Meric-Bernstam8,9,10, Naoto T Ueno11,12. 1. Section of Translational Breast Cancer Research, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1354, Houston, TX, 77030, USA. 2. Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 3. Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 4. Department of Pathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 5. Department of Radiation Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 6. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 7. Department of Hematopathology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. 8. Department of Surgical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. fmeric@mdanderson.org. 9. Department of Investigational Cancer Therapeutics, The University of Texas MD Anderson Cancer Center, 1400 Holcombe Blvd., Unit 455, Houston, TX, 77030, USA. fmeric@mdanderson.org. 10. Department of Sheikh Khalifa Bin Zayed Al Nahyan Institute for Personalized Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. fmeric@mdanderson.org. 11. Section of Translational Breast Cancer Research, Department of Breast Medical Oncology, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd., Unit 1354, Houston, TX, 77030, USA. nueno@mdanderson.org. 12. Morgan Welch Inflammatory Breast Cancer Research Program and Clinic, The University of Texas MD Anderson Cancer Center, Houston, TX, 77030, USA. nueno@mdanderson.org.
Abstract
PURPOSE: Inflammatory breast cancer is an aggressive form of breast cancer that shows distinct clinical features from non-inflammatory breast cancer. Genomic understanding of inflammatory breast cancer will shed light on biological targets for this disease. Our objective was to identify targeted hotspot mutations using multiplex genome sequencing in inflammatory breast cancer and compare the findings with those for patients with non-inflammatory breast cancer to further recognize novel targets. METHODS: We studied 400 patients with metastatic breast cancer who had somatic hotspot mutation testing using a 46- or 50-gene multiplex platform from March 2012 to December 2014. Among this population, 24 patients had inflammatory breast cancer and 376 patients had non-inflammatory breast cancer. We tested a total of 26 samples from 24 patients with inflammatory breast cancer. RESULTS: The average number of mutations per patient was higher in inflammatory breast cancer than in non-inflammatory breast cancer (1.23 vs. 0.65, respectively). Identified somatic mutations in inflammatory breast cancer were TP53 (n = 18, 75%), PIK3CA (n = 10, 41.7%), and ERBB2 (n = 4, 16.7%). TP53 and ERBB2 mutations were significantly more prevalent in inflammatory breast cancer than in non-inflammatory breast cancer (P < 0.01). All patients with ERBB2 mutations had hormone receptor (HR)+ primary tumors. CONCLUSIONS: TP53, PIK3CA, and ERBB2 were detected as three major somatic mutations in metastatic inflammatory breast cancer patients. While the inflammatory breast cancer TP53 and PIK3CA mutations mirrored previously reported data for metastatic non-inflammatory breast cancer, this is the first report of higher frequency of ERBB2 mutation in inflammatory breast cancer, especially in the HR+ subtype. Once validated in a larger cohort of inflammatory breast cancer patients, this novel finding could lead to development of treatments for HR+ inflammatory breast cancer.
PURPOSE:Inflammatory breast cancer is an aggressive form of breast cancer that shows distinct clinical features from non-inflammatory breast cancer. Genomic understanding of inflammatory breast cancer will shed light on biological targets for this disease. Our objective was to identify targeted hotspot mutations using multiplex genome sequencing in inflammatory breast cancer and compare the findings with those for patients with non-inflammatory breast cancer to further recognize novel targets. METHODS: We studied 400 patients with metastatic breast cancer who had somatic hotspot mutation testing using a 46- or 50-gene multiplex platform from March 2012 to December 2014. Among this population, 24 patients had inflammatory breast cancer and 376 patients had non-inflammatory breast cancer. We tested a total of 26 samples from 24 patients with inflammatory breast cancer. RESULTS: The average number of mutations per patient was higher in inflammatory breast cancer than in non-inflammatory breast cancer (1.23 vs. 0.65, respectively). Identified somatic mutations in inflammatory breast cancer were TP53 (n = 18, 75%), PIK3CA (n = 10, 41.7%), and ERBB2 (n = 4, 16.7%). TP53 and ERBB2 mutations were significantly more prevalent in inflammatory breast cancer than in non-inflammatory breast cancer (P < 0.01). All patients with ERBB2 mutations had hormone receptor (HR)+ primary tumors. CONCLUSIONS:TP53, PIK3CA, and ERBB2 were detected as three major somatic mutations in metastatic inflammatory breast cancerpatients. While the inflammatory breast cancerTP53 and PIK3CA mutations mirrored previously reported data for metastatic non-inflammatory breast cancer, this is the first report of higher frequency of ERBB2 mutation in inflammatory breast cancer, especially in the HR+ subtype. Once validated in a larger cohort of inflammatory breast cancerpatients, this novel finding could lead to development of treatments for HR+ inflammatory breast cancer.
Entities:
Keywords:
ERBB2; Genomics; Inflammatory breast cancer; Next-generation sequencing; Somatic mutation
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