Excited to be at @aithyra.bsky.social #AIinLifeScience symposium in Vienna. What a gorgeous venue!
Will be presenting posters on my latest work on personalized gene expression prediction and gene regulatory network inference

12/ Beyond chromatin changes, MYT1L transformed GB cells into less aggressive neuronal-like cells with: • Enhanced neurite-like morphology • Reduced tumor microtube connectivity • Decreased proliferation • In vivo: slower growth, less invasion, longer survival!

11/ Our experimental validation was striking: • MYT1L overexpression closed >80% of differential chromatin regions • MYT1L knockout reopened access to plastic fates • MYT1L directly bound and repressed regulators of other GB states• 85% of scDORI's predicted TF targets confirmed!

10/ 🔥 Can we use these GRNs to manipulate tumor identity and push GB cells into less plastic states? YES! We predicted MYT1L as the key regulatory bottleneck—a master repressor that locks cells into neuronal-like states by directly binding and suppressing the regulators of plastic states.

9/ Remarkably, our regulatory roadmap explains tumor architecture! States with easy transitions exist in close spatial proximity, while states separated by regulatory barriers are spatially distant. The regulatory rules we've uncovered directly shape how tumors are organized!

8/ This roadmap revealed striking asymmetry in GB plasticity: • OPC/NPC-like and AC-like states can easily activate multiple alternate fates • Neuronal-like states are "locked" by strong repression barriers • Transitions follow preferred directions (OPC→Neuronal easier than Neuronal→OPC)

7/ 🔑 The big question: Which tumor states can easily transition to others? We developed metrics to quantify both activation potential (what enables transitions) and repression barriers (what prevents them), creating the first regulatory roadmap of GB plasticity.

6/ The power of multi-omics: We can distinguish what a cell IS versus what it COULD BECOME. While only 16% of Topic Regulators are expressed across different tumor states, over 54% are epigenetically accessible—revealing "primed drivers" ready for activation during transitions!

5/ Applied to GB, scDORI uncovered Topics that redefine tumor heterogeneity through regulatory logic. Each Topic links specific TFs, enhancers, and target genes that work together across tumor states. We identified key "Topic Regulators" (TRs)—master TFs for each Topic.

3/ To decode GB's regulatory logic, we developed scDORI—an autoencoder that decomposes multi-omic profiles into "regulatory Topics." Each Topic represents specific TF-target gene relationships, modeling cells without requiring predefined cell-types. Code: github.com/bioFAM/scDoRI

2/ Key finding: Malignant GB cells are dramatically more plastic than non-malignant cells, BUT neuronal-like tumor states show surprisingly LOW plasticity. This hints at regulatory constraints we could potentially exploit therapeutically!

1/ Glioblastoma is driven by cellular plasticity—tumor cells switching between states. With @bayraktarlab.bsky.social, we profiled >1 M nuclei with single-cell multi-ome (RNA+ATAC) from 12 GBs, capturing the full tumor heterogeneity. We asked: what regulatory mechanisms guide these transitions?

🧠 Excited to share my main PhD project! We mapped the regulatory rules governing Glioblastoma plasticity using single-cell multi-omics and deep learning. This work is part of a two-paper series with @bayraktarlab.bsky.social @oliverstegle.bsky.social and @moritzmall.bsky.social, Preprint at end🧵👇