ArticleBMC cancer2020
Rare osteosarcoma cell subpopulation protein array and profiling using imaging mass cytometry and bioinformatics analysis.
Article in BMC cancer, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
10 citing papers in PubMed, 13 citations in OpenAlex.
- A Needle in a Haystack: The Precision of Liquid Biopsy in Finding Bone Tumors.Anti-cancer agents in medicinal chemistry · 2026Review
- A comprehensive overview of liquid biopsy applications in pediatric solid tumors.NPJ precision oncology · 2024Review
- Investigating surface proteins and antibody combinations for detecting circulating tumor cells of various sarcomas.Scientific reports · 2024Article
- Single-cell technologies uncover intra-tumor heterogeneity in childhood cancers.Seminars in immunopathology · 2023Review
- The impact of similarity metrics on cell-type clustering in highly multiplexed in situ imaging cytometry data.Bioinformatics advances · 2023Article
- Enhancing clinical potential of liquid biopsy through a multi-omic approach: A systematic review.Frontiers in genetics · 2023Review
- Canine and murine models of osteosarcoma.Veterinary pathology · 2022Review
- Advances in mass cytometry and its applicability to digital pathology in clinical-translational cancer research.Advances in laboratory medicine · 2022Review
- Application of High-Throughput Imaging Mass Cytometry Hyperion in Cancer Research.Frontiers in immunology · 2022Review
- An overview of multiplexed analyses of CAR T-cell therapies: insights and potential.Expert review of proteomics · 2021Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundSingle rare cell characterization represents a new scientific front in personalized therapy. Imaging mass cytometry (IMC) may be able to address all these questions by combining the power of MS-CyTOF and microscopy.
methodsWe have investigated this IMC method using < 100 to up to 1000 cells from human sarcoma tumor cell lines by incorporating bioinformatics-based t-Distributed Stochastic Neighbor Embedding (t-SNE) analysis of highly multiplexed IMC imaging data. We tested this process on osteosarcoma cell lines TC71, OHS as well as osteosarcoma patient-derived xenograft (PDX) cell lines M31, M36, and M60. We also validated our analysis using sarcoma patient-derived CTCs.
resultsWe successfully identified heterogeneity within individual tumor cell lines, the same PDX cells, and the CTCs from the same patient by detecting multiple protein targets and protein localization. Overall, these data reveal that our t-SNE-based approach can not only identify rare cells within the same cell line or cell population, but also discriminate amongst varied groups to detect similarities and differences.
conclusionsThis method helps us make greater inroads towards generating patient-specific CTC fingerprinting that could provide an accurate tumor status from a minimally-invasive liquid biopsy.
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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.