Genome Biology (Nov 2019)

Pharmacogenomic analysis of patient-derived tumor cells in gynecologic cancers

  • Jason K. Sa,
  • Jae Ryoung Hwang,
  • Young-Jae Cho,
  • Ji-Yoon Ryu,
  • Jung-Joo Choi,
  • Soo Young Jeong,
  • Jihye Kim,
  • Myeong Seon Kim,
  • E. Sun Paik,
  • Yoo-Young Lee,
  • Chel Hun Choi,
  • Tae-Joong Kim,
  • Byoung-Gie Kim,
  • Duk-Soo Bae,
  • Yeri Lee,
  • Nam-Gu Her,
  • Yong Jae Shin,
  • Hee Jin Cho,
  • Ja Yeon Kim,
  • Yun Jee Seo,
  • Harim Koo,
  • Jeong-Woo Oh,
  • Taebum Lee,
  • Hyun-Soo Kim,
  • Sang Yong Song,
  • Joon Seol Bae,
  • Woong-Yang Park,
  • Hee Dong Han,
  • Hyung Jun Ahn,
  • Anil K. Sood,
  • Raul Rabadan,
  • Jin-Ku Lee,
  • Do-Hyun Nam,
  • Jeong-Won Lee

DOI
https://doi.org/10.1186/s13059-019-1848-3
Journal volume & issue
Vol. 20, no. 1
pp. 1 – 13

Abstract

Read online

Abstract Background Gynecologic malignancy is one of the leading causes of mortality in female adults worldwide. Comprehensive genomic analysis has revealed a list of molecular aberrations that are essential to tumorigenesis, progression, and metastasis of gynecologic tumors. However, targeting such alterations has frequently led to treatment failures due to underlying genomic complexity and simultaneous activation of various tumor cell survival pathway molecules. A compilation of molecular characterization of tumors with pharmacological drug response is the next step toward clinical application of patient-tailored treatment regimens. Results Toward this goal, we establish a library of 139 gynecologic tumors including epithelial ovarian cancers (EOCs), cervical, endometrial tumors, and uterine sarcomas that are genomically and/or pharmacologically annotated and explore dynamic pharmacogenomic associations against 37 molecularly targeted drugs. We discover lineage-specific drug sensitivities based on subcategorization of gynecologic tumors and identify TP53 mutation as a molecular determinant that elicits therapeutic response to poly (ADP-Ribose) polymerase (PARP) inhibitor. We further identify transcriptome expression of inhibitor of DNA biding 2 (ID2) as a potential predictive biomarker for treatment response to olaparib. Conclusions Together, our results demonstrate the potential utility of rapid drug screening combined with genomic profiling for precision treatment of gynecologic cancers.

Keywords