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Published on: October 11, 2018
Lineage-Selective Dependencies in Pediatric Cancers
K Elaine Ritter1, Adam D Durbin2
1Division of Molecular Oncology, Department of Oncology, St. Jude Children's Research Hospital, Memphis, Tennessee 38015, USA.
Abstract:
The quest for effective cancer therapeutics has traditionally centered on targeting mutated or overexpressed oncogenic proteins. However, challenges arise in cancers with low mutational burden or when the mutated oncogene is not conventionally targetable, which are common situations in childhood cancers. This obstacle has sparked large-scale unbiased screens to identify collateral genetic dependencies crucial for cancer cell growth. These screens have revealed promising targets for therapeutic intervention in the form of lineage-selective dependency genes, which may have an expanded therapeutic window compared to pan-lethal dependencies. Many lineage-selective dependencies regulate gene expression and are closely tied to the developmental origins of pediatric tumors. Placing lineage-selective dependencies in a transcriptional network model is helpful for understanding their roles in driving malignant cell behaviors. Here, we discuss the identification of lineage-selective dependencies and how two transcriptional models, core regulatory circuits and gene regulatory networks, can serve as frameworks for understanding their individual and collective actions, particularly in cancers affecting children and young adults.
Insights
Researchers are identifying new cancer drug targets by looking at genetic dependencies, especially in pediatric cancers. These lineage-selective dependencies offer a promising therapeutic window for difficult-to-treat tumors.
Area of Science:
- Oncology
- Genetics
- Molecular Biology
Background:
- Traditional cancer therapeutics target mutated oncogenic proteins, facing challenges in low-mutation cancers like pediatric tumors.
- Unbiased genetic screens are crucial for identifying novel therapeutic targets when conventional approaches fail.
Purpose of the Study:
- To discuss the identification of lineage-selective dependency genes as potential therapeutic targets.
- To explore how transcriptional network models can elucidate the role of these dependencies in pediatric cancers.
Main Methods:
- Utilizing large-scale unbiased genetic screens to discover collateral dependencies in cancer cells.
- Analyzing lineage-selective dependencies within the context of transcriptional network models.
Main Results:
- Identification of lineage-selective dependency genes, offering a potential therapeutic window.
- Demonstration that these dependencies are often linked to gene expression and tumor developmental origins.
Conclusions:
- Lineage-selective dependencies represent promising targets for pediatric cancer therapeutics.
- Transcriptional network models, including core regulatory circuits and gene regulatory networks, provide frameworks for understanding these dependencies.
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