Crucially, these second order features require high measurement sensitivity as ligands and receptors in neighboring cells need to be co-detected. Downsampling analysis showed the ability to detect predictive LR pairs drops with loss of sensitivity, but not imaging area. (6/7)
We found that LR+ cell pairs have a different gene expression program and these programs can predict glioma recurrence times in bulk RNAseq data. Thus, Cell-signaling specific gene expression programs rather than cell-type specific gene expression programs may be important. (5/7)
We found that second-order features (i.e pairwise interactions) at the DNA and RNA level are highly predictive of whether tumors will MT or reamin stable. These are either chromosomes structure alternations or ligand-receptor signaling across neighboring cells. (3/7)
We applied high sensitivity DNA and RNA seqFISH (~50% sensitivity) combined with a Cell Interaction Foundation model on biopsies from 18 IDH-mutant glioma patients who either malignant transformed (MT) at later date or remained stable. (2/7)
Quality of the data matters! at least for predicting glioma progression from a patient's initial biopsy before any progression has occurred. Excited to share our new pre-print, authored by Michal Polonsky, Jonathan Fox, Yunrui Lu and Sheel Shah. (1/7)
biorxiv.org/content/10.64898…
Using gene regulatory network inference we also identified a network of transcription factors with a cyclic topology and identify germ cell signals that interact with this network, illuminating how Sertoli cells can coordinate with germ-cell development. (9/10)
Among possible mechanisms underlying the cyclic transcriptional profile we identified an innate retinoic acid cycle. (8/10)
But are the Sertoli cells just frozen in time? By analyzing Sertoli cells near remnant elongated spermatids, we found their transcriptional profiles are independent of spermatids, suggesting they cycle even without differentiating germ cells. (7/10)












