Raman spectroscopy reveals phenotype switches in breast cancer metastasis
Raman spectroscopy reveals phenotype switches in breast cancer metastasis
Abstract The accurate analytical characterization of metastatic phenotype at primary tumor diagnosis and its evolution with time are critical for controlling metastatic progression of cancer. Here, we report a label-free optical strategy using Raman spectroscopy and machine learning to identify distinct metastatic phenotypes observed in tumors formed by isogenic murine breast cancer cell lines of progressively increasing metastatic propensities. Our Raman spectra-based random forest analysis provided evidence that machine learning models built on spectral data can allow the accurate identification of metastatic phenotype of independent test tumors. By silencing genes critical for metastasis in highly metastatic cell lines, we showed that the random forest classifiers provided predictions consistent with the observed phenotypic switch of the resultant tumors towards lower metastatic potential. Furthermore, the spectral assessment of lipid and collagen content of these tumors was consistent with the observed phenotypic switch. Overall, our findings indicate that Raman spectroscopy may offer a novel strategy to evaluate metastatic risk during primary tumor biopsies in clinical patients.
Paidi Santosh Kumar、Harper Mason G.、Ravindranathan Sruthi、Ivers Jesse D.、Zaharoff David A.、Barman Ishan、Nguyen Khue G.、Liu Zhenhui、Rajaram Narasimhan、Troncoso Joel Rodriguez
Department of Mechanical Engineering, Johns Hopkins UniversityUniversity of Arkansas for Medical SciencesDepartment of Hematology and Oncology, Emory UniversityDepartment of Biomedical Engineering, University of ArkansasJoint Department of Biomedical Engineering, University of North Carolina and North Carolina State UniversityDepartment of Mechanical Engineering, Johns Hopkins University||The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine||Department of Oncology, Johns Hopkins UniversityJoint Department of Biomedical Engineering, University of North Carolina and North Carolina State UniversityDepartment of Mechanical Engineering, Johns Hopkins UniversityDepartment of Biomedical Engineering, University of Arkansas||Winthrop P. Rockefeller Cancer Institute, University of Arkansas for Medical SciencesDepartment of Biomedical Engineering, University of Arkansas
医学研究方法肿瘤学生物科学研究方法、生物科学研究技术
Paidi Santosh Kumar,Harper Mason G.,Ravindranathan Sruthi,Ivers Jesse D.,Zaharoff David A.,Barman Ishan,Nguyen Khue G.,Liu Zhenhui,Rajaram Narasimhan,Troncoso Joel Rodriguez.Raman spectroscopy reveals phenotype switches in breast cancer metastasis[EB/OL].(2025-03-28)[2025-08-09].https://www.biorxiv.org/content/10.1101/2021.06.02.446487.点此复制
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