期刊
JOURNAL OF TRANSLATIONAL MEDICINE
卷 18, 期 1, 页码 -出版社
BMC
DOI: 10.1186/s12967-020-02273-4
关键词
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资金
- Science Foundation Ireland [08-SRC-B1410]
- Health Research Board [HRA/POR2012/054]
- North East Cancer Research and Education Trust (NECRET)
- Fox Family
- Kerins Family
Background An increasing number of anti-cancer therapeutic agents target specific mutant proteins that are expressed by many different tumor types. Successful use of these therapies is dependent on the presence or absence of somatic mutations within the patient's tumor that can confer clinical efficacy or drug resistance. Methods The aim of our study was to determine the type, frequency, overlap and functional proteomic effects of potentially targetable recurrent somatic hotspot mutations in 47 cancer-related genes in multiple disease sites that could be potential therapeutic targets using currently available agents or agents in clinical development. Results Using MassArray technology, of the 1300 patient tumors analysed 571 (43.9%) had at least one somatic mutation. Mutations were identified in 30 different genes. KRAS (16.5%), PIK3CA (13.6%) and BRAF (3.8%) were the most frequently mutated genes. Prostate (10.8%) had the lowest number of somatic mutations identified, while no mutations were identified in sarcoma. Ocular melanoma (90.6%), endometrial (72.4%) and colorectal (66.4%) tumors had the highest number of mutations. We noted high concordance between mutations in different parts of the tumor (94%) and matched primary and metastatic samples (90%). KRAS and BRAF mutations were mutually exclusive. Mutation co-occurrence involved mainly PIK3CA and PTPN11, and PTPN11 and APC. Reverse Phase Protein Array (RPPA) analysis demonstrated that PI3K and MAPK signalling pathways were more altered in tumors with mutations compared to wild type tumors. Conclusions Hotspot mutational profiling is a sensitive, high-throughput approach for identifying mutations of clinical relevance to molecular based therapeutics for treatment of cancer, and could potentially be of use in identifying novel opportunities for genotype-driven clinical trials.
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