Ex vivo screen identifies CDK12 as a metastatic vulnerability in osteosarcoma
Ian Bayles, Malgorzata Krajewska, W. Dean Pontius, Alina Saiakhova, James J. Morrow, Cynthia Bartels, Jim Lu, Zachary J. Faber, Yuriy Fedorov, Ellen S. Hong, Jaret M. Karnuta, Brian Rubin, Drew J. Adams, Rani E. George, Peter C. Scacheri
Ian Bayles, Malgorzata Krajewska, W. Dean Pontius, Alina Saiakhova, James J. Morrow, Cynthia Bartels, Jim Lu, Zachary J. Faber, Yuriy Fedorov, Ellen S. Hong, Jaret M. Karnuta, Brian Rubin, Drew J. Adams, Rani E. George, Peter C. Scacheri
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Research Article Genetics Oncology

Ex vivo screen identifies CDK12 as a metastatic vulnerability in osteosarcoma

Abstract

Despite progress in intensification of therapy, outcomes for patients with metastatic osteosarcoma (OS) have not improved in thirty years. We developed a system that enabled preclinical screening of compounds against metastatic OS cells in the context of the native lung microenvironment. Using this strategy to screen a library of epigenetically targeted compounds, we identified inhibitors of CDK12 to be most effective, reducing OS cell outgrowth in the lung by more than 90% at submicromolar doses. We found that knockout of CDK12 in an in vivo model of lung metastasis significantly decreased the ability of OS to colonize the lung. CDK12 inhibition led to defects in transcription elongation in a gene length– and expression-dependent manner. These effects were accompanied by defects in RNA processing and altered the expression of genes involved in transcription regulation and the DNA damage response. We further identified OS models that differ in their sensitivity to CDK12 inhibition in the lung and provided evidence that upregulated MYC levels may mediate these differences. Our studies provided a framework for rapid preclinical testing of compounds with antimetastatic activity and highlighted CDK12 as a potential therapeutic target in OS.

Authors

Ian Bayles, Malgorzata Krajewska, W. Dean Pontius, Alina Saiakhova, James J. Morrow, Cynthia Bartels, Jim Lu, Zachary J. Faber, Yuriy Fedorov, Ellen S. Hong, Jaret M. Karnuta, Brian Rubin, Drew J. Adams, Rani E. George, Peter C. Scacheri

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Figure 5

E9 affects transcript levels in a gene-length– and expression-dependent manner.

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E9 affects transcript levels in a gene-length– and expression-dependent ...
(A) Left: volcano plot of RNA-Seq–based expression differences between E9 and DMSO control–treated 143B cells. 1275 Genes showed a decrease of more than 2 fold (q value < 0.05). RNA-Seq for the cell line and condition was performed in triplicate. Right: violin plot of gene sizes for the indicated gene categories in 143B cells. Mann-Whitney U test was used to determine significance. *P < 0.001. (B) GO scores and associated terms from of all genes downregulated more than 2-fold in 143B cells using EnrichR. Terms are ranked based on EnrichR combined scores. (C) Heatmaps of Ser2 ChIP-Seq signal across all expressed genes in DMSO- and E9-treated 143B cells, ranked by gene size. Aggregate plots are shown above. Plotted on the immediate right are corresponding fold changes in transcript levels upon E9 treatment. The line plot on the far right denotes baseline transcript levels and E9-treated transcript levels. All genes are ordered similarly in all plots. (D) Heatmap of Ser2 ChIP-Seq signal in MG63.3 cells in a metagene analysis ± 1 kb of all active genes of the indicated size, ranked by size. Aggregate plots are shown above. (E) Heatmap of Ser2 ChIP-Seq signal in DMSO- and E9-treated 143B cells. Ser2 signals –5 kb and +20 kb of TSSs are shown for all active genes up to 20 kb in length, sorted by increasing gene length. Dark blue signal that runs diagonally from the top to the bottom of the left heatmap corresponds to TESs. (F) Browser view of Ser2 ChIP-Seq and RNA-Seq reads of EGR1 (left) and SKI (right) in E9-and DMSO-treated cells.