ArticleiScience2020
An Unsupervised Strategy for Identifying Epithelial-Mesenchymal Transition State Metrics in Breast Cancer and Melanoma.
Article in iScience, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Cell Communication Network factor 4 promotes tumor-induced immunosuppression in breast cancer.bioRxiv : the preprint server for biology · 2026Article
- MRI-based radiomic models to predict surgical margin status and infer tumor immune microenvironment in breast cancer patients with breast-conserving surgery: a multicenter validation study.European radiology · 2024Article
- Single-Cell Transcription Mapping of Murine and Human Mammary Organoids Responses to Female Hormones.Journal of mammary gland biology and neoplasia · 2024Article
- Data-driven learning how oncogenic gene expression locally alters heterocellular networks.Nature communications · 2022Article
- Mapping phenotypic heterogeneity in melanoma onto the epithelial-hybrid-mesenchymal axis.Frontiers in oncology · 2022Article
- Cell type identification from single-cell transcriptomes in melanoma.BMC medical genomics · 2021Article
- A Targeted Bioinformatics Assessment of Adrenocortical Carcinoma Reveals Prognostic Implications of GABA System Gene Expression.International journal of molecular sciences · 2020Article
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2 authors.
Funding
Abstract
Digital cytometry aims to identify different cell types in the tumor microenvironment, with the current focus on immune cells. Yet, identifying how changes in tumor cell phenotype, such as the epithelial-mesenchymal transition, influence the immune contexture is emerging as an important question. To extend digital cytometry, we developed an unsupervised feature extraction and selection strategy to capture functional plasticity tailored to breast cancer and melanoma separately. Specifically, principal component analysis coupled with resampling helped develop gene expression-based state metrics that characterize differentiation within an epithelial to mesenchymal-like state space and independently correlate with metastatic potential. First developed using cell lines, the orthogonal state metrics were refined to exclude the contributions of normal fibroblasts and provide tissue-level state estimates using bulk tissue RNA-seq measures. The resulting metrics for differentiation state aim to inform a more holistic view of how the malignant cell phenotype influences the immune contexture within the tumor microenvironment.
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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.