Prediction of drug candidates for clear cell renal cell carcinoma using a systems biology-based drug repositioning approach
Artikel i vetenskaplig tidskrift, 2022

Background: The response rates of the clinical chemotherapies are still low in clear cell renal cell carcinoma (ccRCC). Computational drug repositioning is a promising strategy to discover new uses for existing drugs to treat patients who cannot get benefits from clinical drugs. Methods: We proposed a systematic approach which included the target prediction based on the co-expression network analysis of transcriptomics profiles of ccRCC patients and drug repositioning for cancer treatment based on the analysis of shRNA- and drug-perturbed signature profiles of human kidney cell line. Findings: First, based on the gene co-expression network analysis, we identified two types of gene modules in ccRCC, which significantly enriched with unfavorable and favorable signatures indicating poor and good survival outcomes of patients, respectively. Then, we selected four genes, BUB1B, RRM2, ASF1B and CCNB2, as the potential drug targets based on the topology analysis of modules. Further, we repurposed three most effective drugs for each target by applying the proposed drug repositioning approach. Finally, we evaluated the effects of repurposed drugs using an in vitro model and observed that these drugs inhibited the protein levels of their corresponding target genes and cell viability. Interpretation: These findings proved the usefulness and efficiency of our approach to improve the drug repositioning researches for cancer treatment and precision medicine. Funding: This study was funded by Knut and Alice Wallenberg Foundation and Bash Biotech Inc., San Diego, CA, USA.

ccRCC

Systems biology

Drug repositioning

Co-expression network

Target chemotherapy

Författare

Xiangyu Li

Bash Biotech Inc.

Kungliga Tekniska Högskolan (KTH)

Koeun Shong

Kungliga Tekniska Högskolan (KTH)

Woonghee Kim

Kungliga Tekniska Högskolan (KTH)

Meng Yuan

Kungliga Tekniska Högskolan (KTH)

Hong Yang

Kungliga Tekniska Högskolan (KTH)

Yusuke Sato

Institute for the Advanced Study of Human Biology

University of Tokyo

Haruki Kume

University of Tokyo

Seishi Ogawa

Institute for the Advanced Study of Human Biology

Karolinska Institutet

Hasan Turkez

Atatürk Üniversitesi

Saeed Shoaie

King's College London

Kungliga Tekniska Högskolan (KTH)

Jan Borén

Sahlgrenska universitetssjukhuset

Jens B Nielsen

BioInnovation Institute

Chalmers, Biologi och bioteknik, Systembiologi

Mathias Uhlen

Kungliga Tekniska Högskolan (KTH)

C. Zhang

Kungliga Tekniska Högskolan (KTH)

Zhengzhou University

Adil Mardinoglu

Kungliga Tekniska Högskolan (KTH)

King's College London

EBioMedicine

2352-3964 (eISSN)

Vol. 78 103963

Ämneskategorier

Farmaceutisk vetenskap

Farmakologi och toxikologi

Cancer och onkologi

DOI

10.1016/j.ebiom.2022.103963

Mer information

Senast uppdaterat

2022-04-05