We were grateful for the opportunity to attend and present at the AACR Annual Meeting last week, where our scientists highlighted some of the exciting work happening across our oncology portfolio.
Using our platform to map and navigate biology and chemistry across the genome and hundreds of thousands of chemical compounds, our teams are identifying novel relationships between genes and compounds that may translate to potential cancer therapies. In our poster presented at AACR, we shared updates on two of our advanced oncology programs, including:
These programs demonstrate how our platform is being used to discover both novel biology and novel chemistry.
On the biology side, we use our maps to search for genes that show up as highly similar to genes that are known to be associated with certain types of cancers. This has led us to identify multiple novel targets, including the gene RBM39. When inhibited, RBM39 mimics the loss of CDK12, which plays a critical role in regulating gene expression and cellular processes.
Importantly, RBM39 leads to a distinct mechanism of action separate from that involving CDK12, which allows it to potentially mitigate the toxicities associated with pan-CDK inhibitors.
On the chemistry side, once we identify tool compounds that validate the initial inference and hypothesis, we begin iterative cycles of structure-activity relationship, or SAR, to optimize and create new chemical entities (NCEs).
As we do this, we onboard NCEs back into our maps to evaluate the effect in cells against our desired target. This allows us to rapidly verify that our proprietary compounds harbor the phenotype we want, so we don’t waste time on compounds that do not have this phenotype or have undesired off-target effects.
It’s early days for both of these programs, but the preclinical data are compelling. Our compounds are showing statistically significant reduction of tumor growth, increased survival rates, and, in some cases, complete tumor regressions compared to current standard treatment options in animal models.
We are encouraged by what these results mean for the future of cancer treatments, and we are working hard to move them into IND-enabling studies as quickly as possible.
For more information about these programs, download our poster from our website.