Rare osteosarcoma cell subpopulation protein array and profiling using imaging mass cytometry and bioinformatics analysis

Autor: Shulin Li, Jing Wang, Qi Wang, Qing Meng, Izhar Singh Batth, Jared K. Burks, Keila E. Torres, Richard Gorlick
Rok vydání: 2020
Předmět:
0301 basic medicine
T-distributed stochastic neighbor embedding (t-SNE)
Cancer Research
Cell
Smooth muscle actin (SMA)
Tumor Status
0302 clinical medicine
Cell surface vimentin (CSV)
Cytometry time-of-flight (CyTOF)
Patient-derived xenograft (PDX)
Image Cytometry
Circulating tumor cells (CTCs)
Osteosarcoma
education.field_of_study
Neoplastic Cells
Circulating
lcsh:Neoplasms. Tumors. Oncology. Including cancer and carcinogens
Imaging mass cytometry (IMC)
medicine.anatomical_structure
Oncology
030220 oncology & carcinogenesis
Protein microarray
Sarcoma
Fine needle aspirates (FNA)
Research Article
DNA Copy Number Variations
Biopsy
Fine-Needle
Population
Protein Array Analysis
Bone Neoplasms
Biology
lcsh:RC254-282
03 medical and health sciences
Cell Line
Tumor
Genetics
medicine
Humans
Vimentin
Mass cytometry
Liquid biopsy
education
Liquid Biopsy
Computational Biology
medicine.disease
DNA Fingerprinting
Actins
Copy number variations (CNV)
030104 developmental biology
Cancer research
Fluorescence associated cell-sorting (FACS)
Zdroj: BMC Cancer, Vol 20, Iss 1, Pp 1-10 (2020)
BMC Cancer
ISSN: 1471-2407
DOI: 10.1186/s12885-020-07203-7
Popis: Background Single 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. Methods We have investigated this IMC method using Results We 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. Conclusions This 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.
Databáze: OpenAIRE
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