Identifying Prognostic Cell State Interactions in the TumorMicroenvironment of IDH-Mutant Gliomas Using CSI-TME
Singh, A.; Mehani, B.; Gopalan, V.; Aldape, K.; Hannenhalli, S.
Show abstract
Intercellular communication between distinct transcriptional states of various cell types in the tumor microenvironment (TME) influence the progression and clinical outcome of the tumors. Details of such clinically relevant cellular state interactions (CSIs) in IDH-mutant gliomas remain obscure. Here we developed CSI-TME, a computational pipeline that deconvolves cell type-specific gene expression from bulk transcriptomic data, identifies distinct cell states, and uncovers prognostic cell state interactions by modelling the clinical data based on the joint activity of cell state pairs. We found a significantly reproducible cell state interaction network (CSIN) that is (i) predominantly pro-tumor, (ii) likely mediated through the interaction between cell surface molecules, (iii) differentially activated in IDH-mut astrocytoma and oligodendroglioma, and (iv) significantly associated with response to immune checkpoint blockade therapy. The distinct malignant cell states involved in CSIs resembled neuronal lineages such as astrocyte-like and oligodendrocyte progenitor cells-like states and captured key interactions between glioma stem cells and immune cells. Integration of CSIN with somatic mutation data suggests the anti-tumor role of CSIs in the early stages that transitions towards pro-tumor role as glioma progresses. In summary, CSI-TME provides valuable insights into the physiology of the TME in IDH-mutant glioma and provides a framework to prioritize ligand-receptor interactions or patients stratification for therapeutic interventions.
Matching journals
The top 6 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Evolutionary states and trajectories characterized by distinct pathways stratify ovarian high-grade serous carcinoma patients 95%
- Mutant IDH Inhibitors Induce Lineage Differentiation in IDH-mutant Oligodendroglioma 95%
- Systematic Elucidation and Pharmacological Targeting of Tumor-Infiltrating Regulatory T Cell Master Regulators 95%
Similar papers in this journal
- Pericytes orchestrate a tumor-restraining microenvironment in glioblastoma 96%
- Single-cell ATAC and RNA sequencing reveal pre-existing and persistent subpopulations of cells associated with relapse of prostate cancer 95%
- Identification of Relevant Genetic Alterations in Cancer using Topological Data Analysis 95%
Similar papers in this journal
- Machine-learning analysis of factors that shape cancer aneuploidy landscapes reveals an important role for negative selection 96%
- Spatiotemporal modeling reveals high-resolution invasion states in glioblastoma 96%
- An integrated single-cell RNA-seq map of human neuroblastoma tumors and preclinical models uncovers divergent mesenchymal-like gene expression programs. 96%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.