Identification of a drug-response gene in multiple myeloma through longitudinal single-cell transcriptome sequencing

  • iScience. 2022 Jul 19;25(8):104781. doi: 10.1016/j.isci.2022.104781.
Toru Masuda  1 ,  Shojiro Haji  1 ,  Yasuhiro Nakashima  1 ,  Mariko Tsuda  1 ,  Daisaku Kimura  1 ,  Akiko Takamatsu  1 ,  Norifusa Iwahashi  1 ,  Hironobu Umakoshi  1 ,  Motoaki Shiratsuchi  1  2 ,  Chie Kikutake  3 ,  Mikita Suyama  3 ,  Yasuyuki Ohkawa  4 ,  Yoshihiro Ogawa  1
Affiliations
  • 1. Department of Medicine and Bioregulatory Science, Graduate School of Medical Sciences, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka 812-8582, Japan.
  • 2. Department of Hematology, Iizuka Hospital, Iizuka 820-8505, Japan.
  • 3. Division of Bioinformatics, Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan.
  • 4. Division of Transcriptomics, Medical Institute of Bioregulation, Kyushu University, Fukuoka 812-8582, Japan.
PMID: 35992084 DOI: 10.1016/j.isci.2022.104781
Abstract

Despite recent therapeutic advances for multiple myeloma (MM), relapse is very common. Here, we conducted longitudinal single-cell transcriptome Sequencing (scRNA-seq) of MM cells from a patient with relapsed MM, treated with multiple anti-myeloma drugs. We observed five subclusters of MM cells, which appeared and/or disappeared in response to the therapeutic pressure, and identified cluster 3 which emerged during lenalidomide treatment and disappeared after Proteasome Inhibitor (PI) treatment. Among the differentially expressed genes in cluster 3, we found a candidate drug-response gene; pellino E3 ubiquitin-protein Ligase family member 2 (PELI2), which is responsible for PI-induced cell death in in vitro assay. Kaplan-Meier survival analysis of database revealed that higher expression of PELI2 is associated with a better prognosis. Our integrated strategy combining longitudinal scRNA-seq analysis, in vitro functional assay, and database analysis would facilitate the understanding of clonal dynamics of MM in response to anti-myeloma drugs and identification of drug-response genes.

Keywords
cancer; drugs; omics.
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