Using birth-death processes to infer tumor subpopulation structure from live-cell imaging drug screening data.

Tumor heterogeneity is a complex and widely recognized trait that poses significant challenges in developing effective cancer therapies. In particular, many tumors harbor a variety of subpopulations with distinct therapeutic response characteristics. Characterizing this heterogeneity by determining the subpopulation structure within a tumor enables more precise and successful treatment strategies. In our prior work, we developed PhenoPop, a computational framework for unravelling the drug-response subpopulation structure within a tumor from bulk high-throughput drug screening data. However, the deterministic nature of the underlying models driving PhenoPop restricts the model fit and the information it can extract from the data. As an advancement, we propose a stochastic model based on the linear birth-death process to address this limitation. Our model can formulate a dynamic variance along the horizon of the experiment so that the model uses more information from the data to provide a more robust estimation. In addition, the newly proposed model can be readily adapted to situations where the experimental data exhibits a positive time correlation. We test our model on simulated data (in silico) and experimental data (in vitro), which supports our argument about its advantages.

Molecular characterization of celtix-1, a bromodomain protein interacting with the transcription factor interferon regulatory factor 2.

Transcriptional control at the G1/S-phase transition of the cell cycle requires functional interactions of multimeric promoter regulatory complexes that contain DNA binding proteins, transcriptional cofactors, and/or chromatin modifying enzymes. Transcriptional regulation of the human histone H4/n gene (FO108) is mediated by Interferon Regulatory Factor-2 (IRF-2), as well as other histone gene promoter factors. To identify proteins that interact with cell-cycle regulatory factors, we performed yeast two-hybrid analysis with IRF-2 and identified a novel human protein termed Celtix-1 which binds to IRF-2. Celtix-1 contains several phylogenetically conserved domains, including a bromodomain, which is found in a number of transcriptional cofactors. Using a panel of IRF-2 deletion mutants in yeast two-hybrid assays, we established that Celtix-1 contacts the C-terminus of IRF-2. Celtix-1 directly interacts with IRF-2 based on binding studies with glutathione S-transferase (GST)/IRF-2 fusion proteins, and immunofluorescence studies suggest that Celtix-1 and IRF-2 associate in situ. Celtix-1 is distributed throughout the nucleus in a heterodisperse pattern. A subset of Celtix-1 colocalizes with the hyperacetylated forms of histones H3 and H4, as well as with the hyperphosphorylated, transcriptionally active form of RNA polymerase II. We conclude that the bromodomain protein Celtix-1 is a novel IRF-2 interacting protein that associates with transcriptionally active chromatin in situ.