Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning

Xiangyu Li; Woonghee Kim; Kajetan Juszczak; Muhammad Arif; Yusuke Sato; Haruki Kume; Seishi Ogawa; Hasan Turkez; Jan Boren; Jens Nielsen; Mathias Uhlen; Cheng Zhang; Adil Mardinoglu

doi:10.1016/j.isci.2021.102722

Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning

iScience. 2021 Jun 12;24(7):102722. doi: 10.1016/j.isci.2021.102722. eCollection 2021 Jul 23.

Authors

Xiangyu Li^{1

2}, Woonghee Kim¹, Kajetan Juszczak¹, Muhammad Arif¹, Yusuke Sato^{3

4}, Haruki Kume⁴, Seishi Ogawa^{3

5}, Hasan Turkez⁶, Jan Boren⁷, Jens Nielsen^{8

9}, Mathias Uhlen¹, Cheng Zhang^{1

10}, Adil Mardinoglu^{1

11}

Affiliations

¹ Science for Life Laboratory, KTH-Royal Institute of Technology, Stockholm 17165, Sweden.
² Bash Biotech Inc, 600 West Broadway, Suite 700, San Diego, CA 92101, USA.
³ Department of Pathology and Tumor Biology, Institute for the Advanced Study of Human Biology (WPI-ASHBi), Kyoto University, Kyoto 606-8501, Japan.
⁴ Department of Urology, Graduate School of Medicine, The University of Tokyo, Tokyo 113-8654, Japan.
⁵ Centre for Hematology and Regenerative Medicine, Department of Medicine, Karolinska Institute, Stockholm 17177, Sweden.
⁶ Department of Medical Biology, Faculty of Medicine, Atatürk University, Erzurum 25240, Turkey.
⁷ Department of Molecular and Clinical Medicine, University of Gothenburg, Sahlgrenska University Hospital, Gothenburg 41345, Sweden.
⁸ Department of Biology and Biological Engineering, Chalmers University of Technology, Gothenburg 41296, Sweden.
⁹ BioInnovation Institute, Copenhagen N 2200, Denmark.
¹⁰ Key Laboratory of Advanced Drug Preparation Technologies, School of Pharmaceutical Sciences, Ministry of Education, Zhengzhou University, Zhengzhou 450001, China.
¹¹ Centre for Host-Microbiome Interactions, Faculty of Dentistry, Oral & Craniofacial Sciences, King's College London, London SE1 9RT, UK.

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common histological type of kidney cancer and has high heterogeneity. Stratification of ccRCC is important since distinct subtypes differ in prognosis and treatment. Here, we applied a systems biology approach to stratify ccRCC into three molecular subtypes with different mRNA expression patterns and prognosis of patients. Further, we developed a set of biomarkers that could robustly classify the patients into each of the three subtypes and predict the prognosis of patients. Then, we reconstructed subtype-specific metabolic models and performed essential gene analysis to identify the potential drug targets. We identified four drug targets, including SOAT1, CRLS1, and ACACB, essential in all the three subtypes and GPD2, exclusively essential to subtype 1. Finally, we repositioned mitotane, an FDA-approved SOAT1 inhibitor, to treat ccRCC and showed that it decreased tumor cell viability and inhibited tumor cell growth based on in vitro experiments.

Keywords: bioinformatics; cancer systems biology; omics; systems biology.