Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal.
| Title: | Differential cell signaling testing for cell-cell communication inference from single-cell data by dominoSignal. |
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| Authors: | Mitchell JT; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Quantitative Sciences Division, Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA.; Department of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, USA.; Stapleton O; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Quantitative Sciences Division, Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA.; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Krishnan K; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, Maryland, USA.; Nagaraj S; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Quantitative Sciences Division, Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA.; Lvovs D; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Cherry C; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, Maryland, USA.; Poissonnier A; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, Oregon, USA.; Horton W; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, Oregon, USA.; Adey A; Department of Molecular & Medical Genetics, Oregon Health & Science University, Portland, Oregon, USA.; Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA.; Rao V; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Huff A; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Zimmerman JW; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Kagohara LT; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Zaidi N; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Coussens LM; Department of Cell, Developmental & Cancer Biology, Oregon Health & Science University, Portland, Oregon, USA.; Knight Cancer Institute, Oregon Health & Science University, Portland, Oregon, USA.; Jaffee EM; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Elisseeff JH; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Translational Tissue Engineering Center, Johns Hopkins University, Baltimore, Maryland, USA.; Department of Chemical and Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Fertig EJ; Department of Oncology, Sydney Kimmel Comprehensive Cancer Center, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Convergence Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Johns Hopkins Bloomberg Kimmel Institute, Johns Hopkins University, Baltimore, Maryland, USA.; Quantitative Sciences Division, Department of Oncology, Johns Hopkins University, Baltimore, Maryland, USA.; Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Institute for Genome Sciences, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Department of Medicine, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Department of Applied Mathematics & Statistics, Whiting School of Engineering, Johns Hopkins University, Baltimore, Maryland, USA.; Greenbaum Comprehensive Cancer Center, University of Maryland School of Medicine, Baltimore, Maryland, USA.; Institute for Health Computing, University of Maryland School of Medicine, Baltimore, Maryland, USA. |
| Source: | BioRxiv : the preprint server for biology [bioRxiv] 2025 May 03. Date of Electronic Publication: 2025 May 03. |
| Publication Type: | Journal Article; Preprint |
| Language: | English |
| Journal Info: | Country of Publication: United States NLM ID: 101680187 Publication Model: Electronic Cited Medium: Internet ISSN: 2692-8205 (Electronic) Linking ISSN: 26928205 NLM ISO Abbreviation: bioRxiv Subsets: PubMed not MEDLINE |
| Abstract: | Algorithms for ligand-receptor network inference have emerged as commonly used tools to estimate cell-cell communication from reference single-cell data. Many studies employ these algorithms to compare signaling between conditions and lack methods to statistically identify signals that are significantly different. We previously developed the cell communication inference algorithm Domino, which considers ligand and receptor gene expression in association with downstream transcription factor activity scoring. We developed the dominoSignal software to innovate upon Domino and extend its functionality to test statistically differential cellular signaling. This new functionality includes compilation of active signals as linkages from multiple subjects in a single-cell data set and testing condition-dependent signaling linkage. The software is applicable for analysis of single-cell data sets with multiple subjects as biological replicates as well as with bootstrapped replicates from data sets with few or pooled subjects. We use simulation studies to benchmark the number of subjects in compared groups and cells within an annotated cell type sufficient to accurately identify differential linkages. We demonstrate the application of the Differential Cell Signaling Test (DCST) in the dominoSignal software to investigate consequences of cancer cell phenotypes and immunotherapy on cell-cell communication in tumor microenvironments. These applications in cancer studies demonstrate the ability of differential cell signaling analysis to infer changes to cell communication networks from therapeutic or experimental perturbations, which is broadly applicable across biological systems. |
| Competing Interests: | Competing Interests NZ receives research support from Bristol Myers Squibb, is a consultant for Genentech and Adventris Pharmaceuticals, and receive other support from Adventris Pharmaceuticals. LMC has received reagent support from Cell Signaling Technologies, Syndax Pharmaceuticals, Inc., ZielBio, Inc., and Hibercell, Inc.; holds sponsored research agreements with Prospect Creek Foundation and previously from ZielBio, Inc, and Syndax Pharmaceuticals; is on the Advisory Board for Carisma Therapeutics, Inc., CytomX Therapeutics, Inc., Kineta, Inc., Hibercell, Inc., Cell Signaling Technologies, Inc., Alkermes, Inc., NextCure, Guardian Bio, Dispatch Biotherapeutics, AstraZeneca Partner of Choice Network (OHSU Site Leader), Genenta Sciences, Pio Therapeutics Pty Ltd., and Lustgarten Foundation for Pancreatic Cancer Research Therapeutics Working Group, Inc. |
| Comments: | Update in: Bioinformatics. 2026 Feb 28;42(3):btag089. doi: 10.1093/bioinformatics/btag089.. (PMID: 41746282) |
| Grant Information: | U01 CA224012 United States CA NCI NIH HHS; T32 GM007814 United States GM NIGMS NIH HHS; K08 CA248624 United States CA NCI NIH HHS; P01 CA247886 United States CA NCI NIH HHS; F31 CA284525 United States CA NCI NIH HHS; U24 CA284156 United States CA NCI NIH HHS; U54 AG079779 United States AG NIA NIH HHS; U01 CA253403 United States CA NCI NIH HHS; DP1 AR076959 United States AR NIAMS NIH HHS; P30 CA069533 United States CA NCI NIH HHS |
| Entry Date(s): | Date Created: 20250714 Date Completed: 20260303 Latest Revision: 20260318 |
| Update Code: | 20260319 |
| PubMed Central ID: | PMC12248116 |
| DOI: | 10.1101/2025.05.02.651747 |
| PMID: | 40654902 |
| Database: | MEDLINE |
Journal Article; Preprint