ArticleInternational journal of molecular sciences2021
Dissecting Response to Cancer Immunotherapy by Applying Bayesian Network Analysis to Flow Cytometry Data.
Article in International journal of molecular sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
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Who cites it
15 citing papers in PubMed, 19 citations in OpenAlex.
- Heterogeneity-optimized method for predicting immune checkpoint blockade response.Scientific reports · 2025Article
- Bayesian networks for network inference in biology.Journal of the Royal Society, Interface · 2025Review
- Minimum uncertainty as Bayesian network model selection principle.BMC bioinformatics · 2025Article
- Changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease.Scientific reports · 2024Article
- Dynamic label-free analysis of SARS-CoV-2 infection reveals virus-induced subcellular remodeling.Nature communications · 2024Article
- Bayesian network models identify cooperative GPCR:G protein interactions that contribute to G protein coupling.The Journal of biological chemistry · 2024Article
- Informing immunotherapy with multi-omics driven machine learning.NPJ digital medicine · 2024Review
- The Human Brainome: changes in expression of VGF, SPECC1L, HLA-DRA and RANBP3L act with APOE E4 to alter risk for late onset Alzheimer's disease.Research square · 2023Article
- Bayesian network models identify co-operative GPCR:G protein interactions that contribute to G protein coupling.bioRxiv : the preprint server for biology · 2023Article
- Progress of the "Molecular Informatics" Section in 2022.International journal of molecular sciences · 2023Article
- Bow-tie architectures in biological and artificial neural networks: Implications for network evolution and assay design.iScience · 2023Article
- Editorial of Special Issue "Deep Learning and Machine Learning in Bioinformatics".International journal of molecular sciences · 2022Article
- Bayesian networks elucidate complex genomic landscapes in cancer.Communications biology · 2022Article
- Editorial: Systems Biology Methods in Computational Immuno-Oncology.Frontiers in genetics · 2022Article
- Synthetic data generation with probabilistic Bayesian Networks.Mathematical biosciences and engineering : MBE · 2021Article
Corrections and comments
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
Abstract
Cancer immunotherapy, specifically immune checkpoint blockade, has been found to be effective in the treatment of metastatic cancers. However, only a subset of patients achieve clinical responses. Elucidating pretreatment biomarkers predictive of sustained clinical response is a major research priority. Another research priority is evaluating changes in the immune system before and after treatment in responders vs. nonresponders. Our group has been studying immune networks as an accurate reflection of the global immune state. Flow cytometry (FACS, fluorescence-activated cell sorting) data characterizing immune cell panels in peripheral blood mononuclear cells (PBMC) from gastroesophageal adenocarcinoma (GEA) patients were used to analyze changes in immune networks in this setting. Here, we describe a novel computational pipeline to perform secondary analyses of FACS data using systems biology/machine learning techniques and concepts. The pipeline is centered around comparative Bayesian network analyses of immune networks and is capable of detecting strong signals that conventional methods (such as FlowJo manual gating) might miss. Future studies are planned to validate and follow up the immune biomarkers (and combinations/interactions thereof) associated with clinical responses identified with this computational pipeline.
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Registered trials
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.