Sophont launches Holon S1, an AI model that predicts where genes are active in tumors from routine pathology slides
Cancer patients with the same diagnosis often have very different tumor biology. Molecular testing can reveal underlying differences, but that's slow and expensive. Introducing Holon-S1, our platform to predict genes and biomarkers from routine pathology slides. • beats two other models at predicting spatial gene activity in a controlled comparison • has identified potentially novel biomarkers in breast cancer and colon cancer • evaluated across 16 organ types and more than 15 scanners, using slides from both formalin-fixed, paraffin-embedded and fresh-frozen tissue. We believe Holon-S1 has the potential to help researchers find new biomarkers in slides they already have, discover treatment targets, and bring more personalized cancer care within reach!
Context
If it holds up, researchers could find cancer biomarkers in slides they already have, without slow and costly molecular tests.
Tanishq Mathew Abraham is chief executive and cofounder of Sophont, a medical AI startup, so this is a first hand company announcement. Sophont says Holon S1 is for research and is not validated for clinical decisions.
Deep dive
On October 20, Tanishq Mathew Abraham introduced Holon S1, which he called a platform to predict genes and biomarkers from routine pathology slides. He said cancer patients with the same diagnosis often have very different tumor biology, and that molecular testing can reveal the differences but is slow and expensive.
He said Holon S1 beats two other models at predicting spatial gene activity in a controlled comparison, has identified potentially novel biomarkers in breast and colon cancer, and was evaluated across 16 organ types and more than 15 scanners, on both preserved and fresh frozen tissue.
Sophont's technical report names the two models as Path2Space and DeepSpot M. It says Holon S1 found that the spatial pattern of the gene EREG was associated with response to chemotherapy in triple negative breast cancer, a marker previously linked to chemotherapy sensitivity only in other cancers. In a colorectal cancer study, the arrangement of predicted gene programs was associated with survival.
In a case study using publicly shared slides from one osteosarcoma patient, Sophont says the model recovered findings that had taken months of molecular testing, including activity of FAP, the target of a therapy the patient responded to.
These are the company's own results from retrospective studies, and the biomarkers are candidates that would need confirmation in further studies.
What to expect next
Watch for independent validation of Holon S1's predictions against measured gene activity, and for peer review of the biomarker findings. Researchers applying it to their own slide archives will show how well it generalizes. Also watch whether Sophont pursues clinical validation, which would be needed before the model could inform treatment decisions. Partnerships with hospitals or drug developers would be another sign of uptake, as would publication of the technical report in a peer reviewed journal.