ArticleBriefings in bioinformatics2021
Unveiling the immune infiltrate modulation in cancer and response to immunotherapy by MIXTURE-an enhanced deconvolution method.
Article in Briefings in bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed, 20 citations in OpenAlex.
- Deconformer: efficient cell-type composition profiling of cfRNA across diverse cell types.Briefings in bioinformatics · 2026Article
- DeOPUS: cellular deconvolution via optimized power-transformed unmixing with shrinkage.Briefings in bioinformatics · 2026Article
- A guide to transcriptomic deconvolution in cancer.Nature reviews. Cancer · 2026Review
- TMBclaw: tumor clone-aware graph learning improves immunotherapy response prediction across heterogeneous cohorts.Briefings in bioinformatics · 2025Article
- Bioinformatics Strategies in Breast Cancer Research.Biomolecules · 2025Review
- Bioinformatics Strategies in Breast Cancer Research.Biomolecules · 2025Review
- Evaluating Gene Fusions as Prognostic Biomarkers and Therapeutic Targets in Immune Checkpoint Blockade-Treated Advanced Melanoma: A Retrospective Analysis.Cancer research communications · 2025Article
- Fourteen years of cellular deconvolution: methodology, applications, technical evaluation and outstanding challenges.Nucleic acids research · 2024Review
- Informing immunotherapy with multi-omics driven machine learning.NPJ digital medicine · 2024Review
- Article
- Blocking soluble TNFα sensitizes HER2-positive breast cancer to trastuzumab through MUC4 downregulation and subverts immunosuppression.Journal for immunotherapy of cancer · 2023Article
- Comprehensive analysis of tumor immune microenvironment and prognosis of m6A-related lncRNAs in gastric cancer.BMC cancer · 2022Article
- Multimetric feature selection for analyzing multicategory outcomes of colorectal cancer: random forest and multinomial logistic regression models.Laboratory investigation; a journal of technical methods and pathology · 2022Article
- Identification of circadian clock genes as regulators of immune infiltration in Hepatocellular Carcinoma.Journal of Cancer · 2022Article
- Oral squamous cell carcinoma (OSCC) tumors from heavy alcohol consumers are associated with higher levels of TLR9 and a particular immunophenotype: Impact on patient survival.Frontiers in immunology · 2022Article
- Evaluating the impact of age on immune checkpoint therapy biomarkers.Cell reports · 2021Article
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Authors and funding
10 authors at 5 institutions in 2 countries.
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No grant is acknowledged in the PubMed record.
Abstract
The accurate quantification of tumor-infiltrating immune cells turns crucial to uncover their role in tumor immune escape, to determine patient prognosis and to predict response to immune checkpoint blockade. Current state-of-the-art methods that quantify immune cells from tumor biopsies using gene expression data apply computational deconvolution methods that present multicollinearity and estimation errors resulting in the overestimation or underestimation of the diversity of infiltrating immune cells and their quantity. To overcome such limitations, we developed MIXTURE, a new ν-support vector regression-based noise constrained recursive feature selection algorithm based on validated immune cell molecular signatures. MIXTURE provides increased robustness to cell type identification and proportion estimation, outperforms the current methods, and is available to the wider scientific community. We applied MIXTURE to transcriptomic data from tumor biopsies and found relevant novel associations between the components of the immune infiltrate and molecular subtypes, tumor driver biomarkers, tumor mutational burden, microsatellite instability, intratumor heterogeneity, cytolytic score, programmed cell death ligand 1 expression, patients' survival and response to anti-cytotoxic T-lymphocyte-associated antigen 4 and anti-programmed cell death protein 1 immunotherapy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.