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

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

^*Corresponding author for this work

Centre for Host Microbiome Interactions

Research output: Contribution to journal › Article › peer-review

8 Citations (Scopus)

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.

Original language	English
Article number	102722
Journal	iScience
Volume	24
Issue number	7
DOIs	https://doi.org/10.1016/j.isci.2021.102722
Publication status	Published - 23 Jul 2021

Keywords

bioinformatics
cancer systems biology
omics
systems biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.isci.2021.102722

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title = "Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning",

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",

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

note = "Funding Information: This research was funded by Knut och Alice Wallenbergs Stiftelse grant number CJDB 72110 and Bash Biotech Inc, San Diego, CA, USA. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project SNIC 2019/3599. Conceptualization, X.L. and C.Z.; methodology, X.L. and J.K.; software, J.K. and M.A; validation, W.K.; formal analysis, X.L. W.K. and K.J.; investigation, X.L. W.K. and H.T.; resources, A.M. and S.O.; data curation, Y.S. and H.K.; writing?original draft preparation, X.L.; writing?review and editing, C.Z. A.M. J.B. J.N. H.T. and M.U.; visualization, X.L. J.K. and W.K.; supervision, A.M. and C.Z.; project administration, A.M.; funding acquisition, A.M. and M.U. All authors have read and agreed to the published version of the manuscript. A.M. J.B. and M.U. are the founder and shareholders of ScandiBio Therapeutics and ScandiEdge Therapeutics Inc. Funding Information: This research was funded by Knut och Alice Wallenbergs Stiftelse grant number CJDB 72110 and Bash Biotech Inc , San Diego, CA, USA. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project SNIC 2019/3599. Publisher Copyright: {\textcopyright} 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.",

year = "2021",

month = jul,

day = "23",

doi = "10.1016/j.isci.2021.102722",

language = "English",

volume = "24",

journal = "iScience",

issn = "2589-0042",

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}

TY - JOUR

T1 - Stratification of patients with clear cell renal cell carcinoma to facilitate drug repositioning

AU - Li, Xiangyu

AU - Kim, Woonghee

AU - Juszczak, Kajetan

AU - Arif, Muhammad

AU - Sato, Yusuke

AU - Kume, Haruki

AU - Ogawa, Seishi

AU - Turkez, Hasan

AU - Boren, Jan

AU - Nielsen, Jens

AU - Uhlen, Mathias

AU - Zhang, Cheng

AU - Mardinoglu, Adil

N1 - Funding Information: This research was funded by Knut och Alice Wallenbergs Stiftelse grant number CJDB 72110 and Bash Biotech Inc, San Diego, CA, USA. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project SNIC 2019/3599. Conceptualization, X.L. and C.Z.; methodology, X.L. and J.K.; software, J.K. and M.A; validation, W.K.; formal analysis, X.L. W.K. and K.J.; investigation, X.L. W.K. and H.T.; resources, A.M. and S.O.; data curation, Y.S. and H.K.; writing?original draft preparation, X.L.; writing?review and editing, C.Z. A.M. J.B. J.N. H.T. and M.U.; visualization, X.L. J.K. and W.K.; supervision, A.M. and C.Z.; project administration, A.M.; funding acquisition, A.M. and M.U. All authors have read and agreed to the published version of the manuscript. A.M. J.B. and M.U. are the founder and shareholders of ScandiBio Therapeutics and ScandiEdge Therapeutics Inc. Funding Information: This research was funded by Knut och Alice Wallenbergs Stiftelse grant number CJDB 72110 and Bash Biotech Inc , San Diego, CA, USA. The computations were performed on resources provided by SNIC through Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) under Project SNIC 2019/3599. Publisher Copyright: © 2021 The Author(s) Copyright: Copyright 2021 Elsevier B.V., All rights reserved.

PY - 2021/7/23

Y1 - 2021/7/23

N2 - 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.

AB - 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.

KW - bioinformatics

KW - cancer systems biology

KW - omics

KW - systems biology

UR - http://www.scopus.com/inward/record.url?scp=85108505207&partnerID=8YFLogxK

U2 - 10.1016/j.isci.2021.102722

DO - 10.1016/j.isci.2021.102722

M3 - Article

AN - SCOPUS:85108505207

SN - 2589-0042

VL - 24

JO - iScience

JF - iScience

IS - 7

M1 - 102722

ER -

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

Abstract

Keywords

UN SDGs

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