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Exploiting gene dependency to inform drug development for multiple myeloma

Molly Went1, Phuc H Hoang2,3, Philip J Law2

  • 1Division of Genetics and Epidemiology, The Institute of Cancer Research, London, SW7 3RP, UK. molly.went@icr.ac.uk.

Scientific Reports
|July 26, 2022
PubMed

Insights

Identifying essential genes in multiple myeloma (MM) offers new therapeutic targets. Gene expression analysis revealed TCF3 and FLVCR1 are linked to patient survival, guiding future MM drug development.

Area of Science:

  • Oncology
  • Genetics
  • Pharmacology

Background:

  • Multiple myeloma (MM) remains an incurable cancer despite therapeutic advancements.
  • Targeting tumor-specific essential genes presents a strategy to overcome drug resistance in MM.
  • Identifying druggable dependencies is crucial for developing novel MM therapies.

Purpose of the Study:

  • To identify essential genes in multiple myeloma (MM) using large-scale genetic perturbation data.
  • To investigate the correlation between the expression of identified MM essential genes and patient outcomes.
  • To explore the potential for repurposing existing drugs and developing new therapeutic agents for MM.

Main Methods:

  • Analysis of DepMap project data to identify 23 essential genes in multiple myeloma.
  • Examination of gene expression data in three independent patient cohorts (totaling 1503 cases).
  • Statistical analysis to assess the association between gene expression and progression-free survival.

Main Results:

  • The expression of TCF3 and FLVCR1 was significantly associated with progression-free survival in MM patients.
  • IKBKB, an existing drug target, shows potential for MM repurposing.
  • PIM2 is currently under investigation for MM treatment.

Conclusions:

  • Large-scale genetic screens are valuable for identifying therapeutic targets in MM.
  • TCF3 and FLVCR1 expression levels can serve as prognostic markers for MM.
  • Targeting essential genes offers a promising avenue for overcoming MM drug resistance and improving patient outcomes.

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