Dataset Information

Exploiting gene dependency to inform drug development for multiple myeloma.

ABSTRACT: Despite recent advances in therapy, multiple myeloma essentially remains an incurable malignancy. Targeting tumour-specific essential genes, which constitute a druggable dependency, potentially offers a strategy for developing new therapeutic agents to treat MM and overcome drug resistance. To explore this possibility, we analysed DepMap project data identifying 23 MM essential genes and examined the relationship between their expression and patient outcome in three independent series totalling 1503 cases. The expression of TCF3 and FLVCR1 were both significantly associated with progression-free survival. IKBKB is already a drug target in other diseases, offering the prospect of repurposing to treat MM, while PIM2 is currently being investigated as a treatment for the disease. Our analysis supports the rationale of using large-scale genetic perturbation screens to guide the development of new therapeutic agents for MM.

SUBMITTER: Went M

PROVIDER: S-EPMC9325789 | biostudies-literature | 2022 Jul

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Exploiting gene dependency to inform drug development for multiple myeloma.

Went Molly M Hoang Phuc H PH Law Philip J PJ Kaiser Martin F MF Houlston Richard S RS

Scientific reports 20220726 1

Despite recent advances in therapy, multiple myeloma essentially remains an incurable malignancy. Targeting tumour-specific essential genes, which constitute a druggable dependency, potentially offers a strategy for developing new therapeutic agents to treat MM and overcome drug resistance. To explore this possibility, we analysed DepMap project data identifying 23 MM essential genes and examined the relationship between their expression and patient outcome in three independent series totalling ...[more]

PMID: 35882937

Similar Datasets

Project description:Genomic instability can be observed at both chromosomal and chromatin levels. Instability at the macro level includes centrosome abnormalities (CA) resulting in numerical as well as structural chromosomal changes, whereas instability at the micro level is characterized by defects in DNA repair pathways resulting in microsatellite instability (MIN) or mutations. Genomic instability occurs during carcinogenesis without impairing survival and growth, though the precise mechanisms remain unclear. Solid tumors arising from most cells of epithelial origin are characterized by genomic instability which renders them resistant to chemotherapy and radiotherapy. This instability is also observed in 25% of myeloma patients and has been shown to be highly prognostic, independently of the international staging system (ISS). However, a biomarker of aberrant DNA repair and loss of heterozygosity (LOH), was only observed at a frequency of 5% in newly diagnosed patients. Several new molecules targeting the pathways involved in genomic instability are under development and some have already entered clinical trials. Poly(ADP-ribose) polymerase-1 (PARP) inhibitors have been FDA-approved for the treatment of breast cancer type 1 susceptibility protein (BRCA1)-mutated metastatic breast cancer, as well as ovarian and lung cancer. Topoisomerase inhibitors and epigenetic histone modification-targeting inhibitors, such as HDAC (Histone Deacetylase) inhibitors which are novel agents that can target genomic instability. Several of the small molecule inhibitors targeting chromosomal level instability such as PARP, Akt, Aurora kinase, cyclin dependent kinase or spindle kinase inhibitors have been tested in mouse models and early phase I/II trials. ATM, ATR kinase inhibitors and DNA helicase inhibitors are also promising novel agents. However, most of these drugs are not effective as single agents but appear to act synergistically with DNA damaging agents such as radiotherapy, platinum derivatives, immunomodulators, and proteasome inhibitors. In this review, new drugs targeting genomic instability and their mechanisms of action will be discussed.

Dataset Information

Exploiting gene dependency to inform drug development for multiple myeloma.

Publications

Exploiting gene dependency to inform drug development for multiple myeloma.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets