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Smarcd1 is a “Goldilocks” metastasis modifier gene [RNA-seq_on_plastic]

GSE260672 Mus musculus Expression profiling by high throughput sequencing 15 samples 2024/10/03 GPL24247
Summary
Breast cancer is the most highly diagnosed cancer worldwide, making up around 12% of all diagnosed cancers in 2020. Mortality caused by breast cancer is largely due to metastasis to distant essential organs, and a lack of metastasis-targeted therapies perpetuates incredibly poor outcomes for late-stage patients. Here we have identified a new class of “Goldilocks” genes for metastasis-targeted therapeutic development, through our focus on meiotic genetics and inherited transcriptional network regulation. Building on previous work identifying the CCR4-NOT RNA deadenylase complex in metastasis, we further demonstrate that RNA binding proteins NANOS1, PUM2, and CPSF4 also regulate metastatic potential. Using cell lines, 3D culture, mouse models, and clinical data, we have identified Smarcd1 mRNA, a key target of all three factors, for which high and low expression is associated with positive clinical outcome, but medium expression significantly reduces probability of survival. Applying the theory of “essential genes” from evolution, we have identified an additional 50 genes that span several cellular processes and must be maintained within a discrete window of expression for metastasis to occur. In the case of Smarcd1, small perturbations in expression level significantly reduced metastasis in laboratory mouse models and altered splicing programs of particular relevance to the ER+HER2 enriched patient subtype. Identification of subtype-specific “Golidlocks” metastasis modifier genes creates a new class of genes and catalogue of potential novel targets that when therapeutically “nudged” in either direction may significantly improve late-stage patient outcomes.
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NCBI GEO page ↗ Paper (PMID 39390150) ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more mouse RNA-seq datasets →
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