ArticleCancer discovery2022
Deconvolving Clinically Relevant Cellular Immune Cross-talk from Bulk Gene Expression Using CODEFACS and LIRICS Stratifies Patients with Melanoma to Anti-PD-1 Therapy.
Article in Cancer discovery, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 43 papers.
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Who cites it
43 citing papers in PubMed, 59 citations in OpenAlex.
- Identifying clinically relevant cell state interactions in the tumor microenvironment of IDH-mutant gliomas using CSI-TME.Molecular systems biology · 2026Article
- ICIsAtlas reveals a suppressive NK cell niche in pan-cancer immunotherapy profiles.Communications biology · 2026Article
- Deep learning inference of cell type-specific gene expression from breast tumor histopathology.NPJ precision oncology · 2026Article
- Interferon-gamma-inducible protein 30 prevents IFN-γ-receptor 1 degradation to maintain PD-L1 and MHC-II levels in metastatic melanoma.Cell communication and signaling : CCS · 2026Article
- Immune Niche Formation Reveals Mechanisms of Tumor Dormancy and Targeting Opportunities.Research square · 2026Article
- Cholesterol efflux protein, ABCA1, supports anticancer functions of myeloid immune cells.Science advances · 2026Article
- Article
- Ubiquitin E3 ligase KPC1 governs mesenchymal metastatic melanoma reprogramming via proteasomal degradation of ZEB1.Cell death & disease · 2025Article
- Unico: a unified model for cell-type resolution genomics from heterogeneous omics data.Genome biology · 2025Article
- Longitudinal liquid biopsy identifies an early predictive biomarker of immune checkpoint blockade response in head and neck squamous cell carcinoma.Nature communications · 2025Article
- IC2Bert: masked gene expression pretraining and supervised fine tuning for robust immune checkpoint blockade (ICB) response prediction.Scientific reports · 2025Article
- Enhanced prediction of breast cancer patient response to chemotherapy by integrating deconvolved expression patterns of immune, stromal and tumor cells.bioRxiv : the preprint server for biology · 2025Article
- Advances in molecular pathology and therapy of non-small cell lung cancer.Signal transduction and targeted therapy · 2025Review
- Immune Niche Formation in Engineered Mouse Models Reveals Mechanisms of Tumor Dormancy.bioRxiv : the preprint server for biology · 2025Article
- Immunological responses and clinical outcomes in dogs with osteosarcoma receiving standard therapy and a Listeria vaccine expressing HER2.Molecular therapy : the journal of the American Society of Gene Therapy · 2025Article
- Mathematically mapping the network of cells in the tumor microenvironment.Cell reports methods · 2025Article
- Large-Scale Comparative Analysis of Canine and Human Osteosarcomas Uncovers Conserved Clinically Relevant Tumor Microenvironment Subtypes.Clinical cancer research : an official journal of the American Association for Cancer Research · 2024Article
- Charting the transcriptomic landscape of primary and metastatic cancers in relation to their origin and target normal tissues.Science advances · 2024Article
- Temporal Genomic Analysis of Homogeneous Tumor Models Reveals Key Regulators of Immune Evasion in Melanoma.Cancer discovery · 2024Article
- Mechanisms of Resistance to Oncogenic KRAS Inhibition in Pancreatic Cancer.Cancer discovery · 2024Article
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Authors and funding
9 authors at 1 institution in 2 countries.
Funding
Abstract
The tumor microenvironment (TME) is a complex mixture of cell types whose interactions affect tumor growth and clinical outcome. To discover such interactions, we developed CODEFACS (COnfident DEconvolution For All Cell Subsets), a tool deconvolving cell type-specific gene expression in each sample from bulk expression, and LIRICS (Ligand-Receptor Interactions between Cell Subsets), a statistical framework prioritizing clinically relevant ligand-receptor interactions between cell types from the deconvolved data. We first demonstrate the superiority of CODEFACS versus the state-of-the-art deconvolution method CIBERSORTx. Second, analyzing The Cancer Genome Atlas, we uncover cell type-specific ligand-receptor interactions uniquely associated with mismatch-repair deficiency across different cancer types, providing additional insights into their enhanced sensitivity to anti-programmed cell death protein 1 (PD-1) therapy compared with other tumors with high neoantigen burden. Finally, we identify a subset of cell type-specific ligand-receptor interactions in the melanoma TME that stratify survival of patients receiving anti-PD-1 therapy better than some recently published bulk transcriptomics-based methods. SIGNIFICANCE: This work presents two new computational methods that can deconvolve a large collection of bulk tumor gene expression profiles into their respective cell type-specific gene expression profiles and identify cell type-specific ligand-receptor interactions predictive of response to immune-checkpoint blockade therapy. This article is highlighted in the In This Issue feature, p. 873.
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