4.7 Article

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

期刊

ISCIENCE
卷 25, 期 8, 页码 -

出版社

CELL PRESS
DOI: 10.1016/j.isci.2022.104781

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资金

  1. Ministry of Education, Culture, Sports, Science and Technology of Japan
  2. Clinical Research Promotion Foundation
  3. Daiwa Securities Health Foundation
  4. QR Program of Kyushu University
  5. Fukuoka Public Health Promotion Organization Cancer Research Fund
  6. JSPS KAKENHI [JP 22K08506]
  7. Japan Agency for Medical Research and Development, Core Research for Evolutional Science and Technology (AMED-CREST)
  8. Grant of The Clinical Research Promotion Foundation

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In this study, longitudinal single-cell transcriptome sequencing was performed on multiple myeloma (MM) cells from a patient with relapsed MM. The researchers observed dynamic changes in MM cells in response to anti-myeloma drugs and identified a drug-response gene, PELI2. Their integrated strategy provided new insights into the clonal dynamics of MM and identification of drug-response genes.
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 merged 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.

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