Biology subjects

Richters, A.

Publications and source records attributed to Richters, A..

2 recordsLinked to original sources

bioRxiv2024

Targeted Degradation of CDK9 Potently Disrupts the MYC Transcriptional Network

Cyclin-dependent kinase 9 (CDK9) coordinates signaling events that regulate RNA polymerase II (Pol II) pause-release states. It is an important co-factor for transcription factors, such as MYC, that drive aberrant cell proliferation when their expression is deregulated. CDK9 modulation offers an approach for attenuating dysregulation in such transcriptional programs. As a result, numerous drug development campaigns to inhibit CDK9 kinase activity have been pursued. More recently, targeted degradation has emerged as an attractive approach. However, comprehensive evaluation of degradation versus inhibition is still critically needed to assess the biological contexts in which degradation might offer superior therapeutic benefits. We validated that CDK9 inhibition triggers a compensatory mechanism that dampens its effect on MYC expression and found that this feedback mechanism was absent when the kinase is degraded. Importantly, CDK9 degradation is more effective than its inhibition for disrupting MYC transcriptional regulatory circuitry likely through the abrogation of both enzymatic and scaffolding functions of CDK9. Highlights- KI-CDK9d-32 is a highly potent and selective CDK9 degrader. - KI-CDK9d-32 leads to rapid downregulation of MYC protein and mRNA transcripts levels. - KI-CDK9d-32 represses canonical MYC pathways and leads to a destabilization of nucleolar homeostasis. - Multidrug resistance ABCB1 gene emerged as the strongest resistance marker for the CDK9 PROTAC degrader.

cancer biology↗

bioRxiv2018

Discovery of cancer driver genes based on nucleotide context

Many cancer genomes contain large numbers of somatic mutations, but few of these mutations drive tumor development. Current approaches to identify cancer driver genes are largely based on mutational recurrence, i.e. they search for genes with an increased number of nonsynonymous mutations relative to the local background mutation rate. Multiple studies have noted that the sensitivity of recurrence-based methods is limited in tumors with high background mutation rates, because passenger mutations dilute their statistical power. Here, we observe that passenger mutations tend to occur in characteristic nucleotide sequence contexts, while driver mutations follow a different distribution pattern determined by the location of functionally relevant genomic positions along the protein-coding sequence. To discover new cancer genes, we searched for genes with an excess of mutations in unusual nucleotide contexts that deviate from the characteristic context around passenger mutations. By applying this statistical framework to whole-exome sequencing data from 12,004 tumors, we discovered a long tail of novel candidate cancer genes with mutation frequencies as low as 1% and functional supporting evidence. Our results show that considering both the number and the nucleotide context around mutations helps identify novel cancer driver genes, particularly in tumors with high background mutation rates.

genetics↗