Translational Oncology (Jun 2016)

Genomic Alterations in Biliary Tract Cancer Using Targeted Sequencing

  • Kwai Han Yoo,
  • Nayoung K.D. Kim,
  • Woo Il Kwon,
  • Chung Lee,
  • Sun Young Kim,
  • Jiryeon Jang,
  • Jungmi Ahn,
  • Mihyun Kang,
  • Hyojin Jang,
  • Seung Tae Kim,
  • Soomin Ahn,
  • Kee-Taek Jang,
  • Young Suk Park,
  • Woong-Yang Park,
  • Jeeyun Lee,
  • Jin Seok Heo,
  • Joon Oh Park

DOI
https://doi.org/10.1016/j.tranon.2016.01.007
Journal volume & issue
Vol. 9, no. 3
pp. 173 – 178

Abstract

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Background: Biliary tract cancers (BTCs) are rare and heterogeneous group of tumors classified anatomically into intrahepatic and extrahepatic bile ducts and gallbladder adenocarcinomas. Patient-derived tumor cell (PDC) models with genome analysis can be a valuable platform to develop a method to overcome the clinical barrier on BTCs. Material and Methods: Between January 2012 and June 2015, 40 BTC patients’ samples were collected. PDCs were isolated and cultured from surgical specimens, biopsy tissues, or malignant effusions including ascites and pleural fluid. Genome analysis using targeted panel sequencing as well as digital multiplexed gene analysis was applied to PDCs as well as primary tumors. Results: Extrahepatic cholangiocarcinoma (N = 15, 37.5%), intrahepatic cholangiocarcinoma (N = 10, 25.0%), gallbladder cancer (N = 14, 35.0%), and ampulla of Vater cancer (N = 1, 2.5%) were included. We identified 15 mutations with diverse genetic alterations in 19 cases of BTC from primary tumor specimens. The most common molecular alterations were in TP53 (8/19, 42.1%), including missense mutations such as C242Y, E285K, G112S, P19T, R148T, R248Q, and R273L. We also detected two NRAS mutations (G12C and Q61L), two KRAS mutations (G12A and G12S), two ERBB2 mutations (V777L and pM774delinsMA) and amplification, and three PIK3CA mutations (N345K, E545K, and E521K). PDC models were successfully established in 27 of 40 samples (67.5%), including 22/24 from body fluids (91.7%) and 5/16 from tissue specimens (31.3%). Conclusions: PDC models are promising tools for uncovering driver mutations and identifying rational therapeutic strategies in BTC. Application of this model is expected to inform clinical trials of drugs for molecular-based targeted therapy.