Parathyroid carcinoma (PC) is a rare endocrine malignancy. Complete surgical resection is the most effective method for the management of PC, however, more than half of PC patients would have recurrent or metastatic lesions. In inoperable disease, treatment options are still limited since chemotherapy and radiotherapy have been generally ineffective in the treatment of PC. Emerging evidence from clinical practice indicated that pre-therapeutic test of molecular biomarkers in tumors may predict the efficacy of the respective targeted drugs. Therefore, understanding the genetic landscape of PC can help in determining whether targeted therapy has potential to be a novel option to treat this refractory disease.
DNA was extracted from formalin-fixed, paraffin-embedded (FFPE) sections from 19 recurrent or metastatic PC samples. A panel of 560 genes was sequenced with next-generation sequencing (NGS) using Illumina HiSeq X platform to identify genomic alterations at an average sequencing depth of 581×.
A total of 190 genomic alterations were identified. Nine PC samples (47%) harbored at least one potentially actionable genomic alteration including: ROS1 (5/19; 26%), PTEN (3/19; 16%), TSC1 (2/19; 11%), PIK3CA (1/19; 5%), AKT1 (1/19; 5%), MTOR (1/19; 5%), ERBB2 (1/19; 5%), NTRK1 (1/19; 5%), IDH1 (1/19; 5%), and FGFR3 (1/19; 5%). CDC73 mutations were detected in 9/19 (47%) PC samples. Additional recurrent genomic alterations were identified in MSH2 (15/19; 79%), AR (9/19; 47%), BCR (8/19; 42%), SLC45A3 (6/19; 32%), MAGI1 (5/19; 26%), ZNF521 (4/19; 21%), KMT2C (4/19; 21%), and NOTCH4 (4/19; 21%).
The present study identified a considerable frequency of potentially actionable genomic alterations in PC patients for the first time. A series of recurrent mutant genes have been detected as well. The present study would contribute to both selection of novel targeted therapies for PC and further molecular understanding of this refractory malignancy.
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This work was supported by the Peking Union Medical College Innovative Team Development Program (2016) and the Chinese Academy of Medical Sciences (CAMS) Initiative for Innovative Medicine (CAMS-I2M) (2017-I2M-1-001).
All authors have declared no conflicts of interest.