Name: A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells (Video) | JoVE Journal
Uploaded: 2025-08-22T12:40:00.000+00:00
Duration: 10 min 37 s
Description: Learn multimodal imaging using confocal Raman microspectroscopy and tomographic phase microscopy for label-free phenotyping of living breast cancer cells. This method provides rapid morpho-chemical analysis without perturbation.

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5 minutes

This research was funded by the Progetto Rocca of the MIT-Italy foundation, NIH grants (P41EB015871, UH3CA275687, R01DC021326), Apollon (Seoul, South Korea), and the National Cancer Center, Korea (NCC-24H1170). Leonardo Bianchi acknowledges the award of a Progetto Rocca Post-doctoral Fellowship to conduct collaborative research at the Massachusetts Institute of Technology and Politecnico di Milano.

<ol><li>Gosnell, M. E., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantitative+non-invasive+cell+characterisation+and+discrimination+based+on+multispectral+autofluorescence+features%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Quantitative non-invasive cell characterisation and discrimination based on multispectral autofluorescence features.</a> Sci Rep. 6 (1), 23453(2016).</li>
<li>Bresci, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Label-free+morpho-molecular+phenotyping+of+living+cancer+cells+by+combined+Raman+spectroscopy+and+phase+tomography%5BTitle%5D)+AND+%22Commun+Biol%22%5BJournal%5D)">Label-free morpho-molecular phenotyping of living cancer cells by combined Raman spectroscopy and phase tomography.</a> Commun Biol. 7 (1), 1-13 (2024).</li>
<li>Rocha, R. A., Fox, J. M., Genever, P. G., Hancock, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Biomolecular+phenotyping+and+heterogeneity+assessment+of+mesenchymal+stromal+cells+using+label-free+Raman+spectroscopy%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Biomolecular phenotyping and heterogeneity assessment of mesenchymal stromal cells using label-free Raman spectroscopy.</a> Sci Rep. 11 (1), 4385(2021).</li>
<li>Vicar, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cell+segmentation+methods+for+label-free+contrast+microscopy%3A+review+and+comprehensive+comparison%5BTitle%5D)+AND+%22BMC+Bioinform%22%5BJournal%5D)">Cell segmentation methods for label-free contrast microscopy: review and comprehensive comparison.</a> BMC Bioinform. 20 (1), 360(2019).</li>
<li>Kang, J. W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Combined+confocal+Raman+and+quantitative+phase+microscopy+system+for+biomedical+diagnosis%5BTitle%5D)+AND+%22Biomed+Opt+Express%22%5BJournal%5D)">Combined confocal Raman and quantitative phase microscopy system for biomedical diagnosis.</a> Biomed Opt Express. 2 (9), 2484-2492 (2011).</li>
<li>Pandey, R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Integration+of+diffraction+phase+microscopy+and+Raman+imaging+for+label-free+morpho-molecular+assessment+of+live+cells%5BTitle%5D)+AND+%22J+Biophotonics%22%5BJournal%5D)">Integration of diffraction phase microscopy and Raman imaging for label-free morpho-molecular assessment of live cells.</a> J Biophotonics. 12 (4), e201800291(2019).</li>
<li>Zhao, W., Sun, D., Yue, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Label-free+multimodal+non-linear+optical+imaging+of+three-dimensional+cell+cultures%5BTitle%5D)+AND+%22Front+Phys%22%5BJournal%5D)">Label-free multimodal non-linear optical imaging of three-dimensional cell cultures.</a> Front Phys. 10, 1100090(2023).</li>
<li>Hanna, K., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+spectroscopy%3A+current+applications+in+breast+cancer+diagnosis%2C+challenges+and+future+prospects%5BTitle%5D)+AND+%22Br+J+Cancer%22%5BJournal%5D)">Raman spectroscopy: current applications in breast cancer diagnosis, challenges and future prospects.</a> Br J Cancer. 126 (8), 1125-1139 (2022).</li>
<li>Dodo, K., Fujita, K., Sodeoka, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+spectroscopy+for+chemical+biology+research%5BTitle%5D)+AND+%22J+Am+Chem+Soc%22%5BJournal%5D)">Raman spectroscopy for chemical biology research.</a> J Am Chem Soc. 144 (43), 19651-19667 (2022).</li>
<li>Puppels, G. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Studying+single+living+cells+and+chromosomes+by+confocal+Raman+microspectroscopy%5BTitle%5D)+AND+%22Nature%22%5BJournal%5D)">Studying single living cells and chromosomes by confocal Raman microspectroscopy.</a> Nature. 347 (6290), 301-303 (1990).</li>
<li>Elumalai, S., Managó, S., De Luca, A. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+microscopy%3A+progress+in+research+on+cancer+cell+sensing%5BTitle%5D)+AND+%22Sensors+%28Basel%29%22%5BJournal%5D)">Raman microscopy: progress in research on cancer cell sensing.</a> Sensors (Basel). 20 (19), 5525(2020).</li>
<li>Chandra, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Unveiling+the+molecular+secrets%3A+a+comprehensive+review+of+Raman+spectroscopy+in+biological+research%5BTitle%5D)+AND+%22ACS+Omega%22%5BJournal%5D)">Unveiling the molecular secrets: a comprehensive review of Raman spectroscopy in biological research.</a> ACS Omega. 9 (51), 50049-50063 (2024).</li>
<li>Cacace, T., Bianco, V., Ferraro, P. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantitative+phase+imaging+trends+in+biomedical+applications%5BTitle%5D)+AND+%22Opt+Laser+Eng%22%5BJournal%5D)">Quantitative phase imaging trends in biomedical applications.</a> Opt Laser Eng. 135, 106188(2020).</li>
<li>Nguyen, T. L., Pradeep, S., Judson-Torres, R. L., Reed, J., Teitell, M. A., Zangle, T. A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantitative+phase+imaging%3A+recent+advances+and+expanding+potential+in+biomedicine%5BTitle%5D)+AND+%22ACS+Nano%22%5BJournal%5D)">Quantitative phase imaging: recent advances and expanding potential in biomedicine.</a> ACS Nano. 16 (8), 11516-11544 (2022).</li>
<li>Kuś, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tomographic+phase+microscopy+of+living+three-dimensional+cell+cultures%5BTitle%5D)+AND+%22J+Biomed+Opt%22%5BJournal%5D)">Tomographic phase microscopy of living three-dimensional cell cultures.</a> J Biomed Opt. 19 (4), 046009(2014).</li>
<li>Memmolo, P., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Loss+minimized+data+reduction+in+single-cell+tomographic+phase+microscopy+using+3D+Zernike+descriptors%5BTitle%5D)+AND+%22Intell+Comput%22%5BJournal%5D)">Loss minimized data reduction in single-cell tomographic phase microscopy using 3D Zernike descriptors.</a> Intell Comput. 2, 0010(2023).</li>
<li>Jin, D., Zhou, R., Yaqoob, Z., So, P. T. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tomographic+phase+microscopy%3A+principles+and+applications+in+bioimaging+%5BInvited%5D%5BTitle%5D)+AND+%22JOSA+B%22%5BJournal%5D)">Tomographic phase microscopy: principles and applications in bioimaging [Invited].</a> JOSA B. 34 (5), B64-B77 (2017).</li>
<li>Pirone, D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Stain-free+identification+of+cell+nuclei+using+tomographic+phase+microscopy+in+flow+cytometry%5BTitle%5D)+AND+%22Nat+Photonics%22%5BJournal%5D)">Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry.</a> Nat Photonics. 16 (12), 851-857 (2022).</li>
<li>Bresci, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Non-invasive+morpho-molecular+imaging+reveals+early+therapy-induced+senescence+in+human+cancer+cells%5BTitle%5D)+AND+%22Sci+Adv%22%5BJournal%5D)">Non-invasive morpho-molecular imaging reveals early therapy-induced senescence in human cancer cells.</a> Sci Adv. 9 (37), eadg6231(2023).</li>
<li>Ghislanzoni, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optical+diffraction+tomography+and+Raman+confocal+microscopy+for+the+investigation+of+vacuoles+associated+with+cancer+senescent+engulfing+cells%5BTitle%5D)+AND+%22Biosensors%22%5BJournal%5D)">Optical diffraction tomography and Raman confocal microscopy for the investigation of vacuoles associated with cancer senescent engulfing cells.</a> Biosensors. 13 (11), 973(2023).</li>
<li>Bischof, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Multimodal+bioimaging+across+disciplines+and+scales%3A+challenges%2C+opportunities+and+breaking+down+barriers%5BTitle%5D)+AND+%22npj+Imageing%22%5BJournal%5D)">Multimodal bioimaging across disciplines and scales: challenges, opportunities and breaking down barriers.</a> npj Imageing. 2 (1), 1-6 (2024).</li>
<li>Kobayashi-Kirschvink, K. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Prediction+of+single-cell+RNA+expression+profiles+in+live+cells+by+Raman+microscopy+with+Raman2RNA%5BTitle%5D)+AND+%22Nat+Biotechnol%22%5BJournal%5D)">Prediction of single-cell RNA expression profiles in live cells by Raman microscopy with Raman2RNA.</a> Nat Biotechnol. 42 (11), 1726-1732 (2024).</li>
<li>Popescu, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Optical+imaging+of+cell+mass+and+growth+dynamics%5BTitle%5D)+AND+%22Am+J+Physiol+Cell+Physiol%22%5BJournal%5D)">Optical imaging of cell mass and growth dynamics.</a> Am J Physiol Cell Physiol. 295 (2), C538-C544 (2008).</li>
<li>Kim, K., Lee, S., Yoon, J., Heo, J., Choi, C., Park, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Three-dimensional+label-free+imaging+and+quantification+of+lipid+droplets+in+live+hepatocytes%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Three-dimensional label-free imaging and quantification of lipid droplets in live hepatocytes.</a> Sci Rep. 6 (1), 36815(2016).</li>
<li>Schindelin, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Fiji%3A+an+open-source+platform+for+biological-image+analysis%5BTitle%5D)+AND+%22Nat+Methods%22%5BJournal%5D)">Fiji: an open-source platform for biological-image analysis.</a> Nat Methods. 9 (7), 676-682 (2012).</li>
<li>Stringer, C., Pachitariu, M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Cellpose3%3A+one-click+image+restoration+for+improved+cellular+segmentation%5BTitle%5D)+AND+%22Nat+Methods%22%5BJournal%5D)">Cellpose3: one-click image restoration for improved cellular segmentation.</a> Nat Methods. 22 (3), 592-599 (2025).</li>
<li>Talari, A. C. S., Movasaghi, Z., Rehman, S., Umapathy, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+spectroscopy+of+biological+tissues%5BTitle%5D)+AND+%22Appl+Spectrosc+Rev%22%5BJournal%5D)">Raman spectroscopy of biological tissues.</a> Appl Spectrosc Rev. 50 (1), 46-111 (2015).</li>
<li>Hobro, A. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+and+Raman+optical+activity+%28ROA%29+analysis+of+RNA+structural+motifs+in+Domain+I+of+the+EMCV+IRES%5BTitle%5D)+AND+%22Nucleic+Acids+Res%22%5BJournal%5D)">Raman and Raman optical activity (ROA) analysis of RNA structural motifs in Domain I of the EMCV IRES.</a> Nucleic Acids Res. 35 (4), 1169-1177 (2007).</li>
<li>Samuel, A. Z., Sugiyama, K., Ando, M., Takeyama, H. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Direct+imaging+of+intracellular+RNA%2C+DNA%2C+and+liquid-liquid+phase+separated+membraneless+organelles+with+Raman+microspectroscopy%5BTitle%5D)+AND+%22Commun+Biol%22%5BJournal%5D)">Direct imaging of intracellular RNA, DNA, and liquid-liquid phase separated membraneless organelles with Raman microspectroscopy.</a> Commun Biol. 5 (1), 1-9 (2022).</li>
<li>Kuhar, N., Sil, S., Umapathy, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Potential+of+Raman+spectroscopic+techniques+to+study+proteins%5BTitle%5D)+AND+%22Spectrochim+Acta+A+Mol+Biomol+Spectrosc%22%5BJournal%5D)">Potential of Raman spectroscopic techniques to study proteins.</a> Spectrochim Acta A Mol Biomol Spectrosc. 258, 119712(2021).</li>
<li>Park, C., Shin, S., Park, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Generalized+quantification+of+three-dimensional+resolution+in+optical+diffraction+tomography+using+the+projection+of+maximal+spatial+bandwidths%5BTitle%5D)+AND+%22JOSA+A%22%5BJournal%5D)">Generalized quantification of three-dimensional resolution in optical diffraction tomography using the projection of maximal spatial bandwidths.</a> JOSA A. 35 (11), 1891-1898 (2018).</li>
<li>Bresci, A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Label-free+monitoring+of+embryonic+development+in+living+colonies+by+combining+Raman+spectroscopy+and+tomographic+phase+microscopy%5BTitle%5D)+AND+%22Multiscale+Imaging+Spectrosc+VI%22%5BJournal%5D)">Label-free monitoring of embryonic development in living colonies by combining Raman spectroscopy and tomographic phase microscopy.</a> Multiscale Imaging Spectrosc VI. PC13327, PC1332703(2025).</li>
<li>Baczewska, M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Refractive+index+changes+of+cells+and+cellular+compartments+upon+paraformaldehyde+fixation+acquired+by+tomographic+phase+microscopy%5BTitle%5D)+AND+%22Cytometry+A%22%5BJournal%5D)">Refractive index changes of cells and cellular compartments upon paraformaldehyde fixation acquired by tomographic phase microscopy.</a> Cytometry A. 99 (4), 388-398 (2021).</li>
<li>Movasaghi, Z., Rehman, S., Umapathy, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+spectroscopy+of+biological+tissues%5BTitle%5D)+AND+%22Appl+Spectrosc+Rev%22%5BJournal%5D)">Raman spectroscopy of biological tissues.</a> Appl Spectrosc Rev. 42 (5), 493-541 (2007).</li>
<li>Butler, H. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Using+Raman+spectroscopy+to+characterize+biological+materials%5BTitle%5D)+AND+%22Nat+Protoc%22%5BJournal%5D)">Using Raman spectroscopy to characterize biological materials.</a> Nat Protoc. 11 (4), 664-687 (2016).</li>
<li>Allakhverdiev, E. S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+spectroscopy+and+its+modifications+applied+to+biological+and+medical+research%5BTitle%5D)+AND+%22Cells%22%5BJournal%5D)">Raman spectroscopy and its modifications applied to biological and medical research.</a> Cells. 11 (3), 386(2022).</li>
<li>Xu, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Unveiling+cancer+metabolism+through+spontaneous+and+coherent+Raman+spectroscopy+and+stable+isotope+probing%5BTitle%5D)+AND+%22Cancers%22%5BJournal%5D)">Unveiling cancer metabolism through spontaneous and coherent Raman spectroscopy and stable isotope probing.</a> Cancers. 13 (7), 1718(2021).</li>
<li>Swain, R. J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Assessment+of+cell+line+models+of+primary+human+cells+by+Raman+spectral+phenotyping%5BTitle%5D)+AND+%22Biophys+J%22%5BJournal%5D)">Assessment of cell line models of primary human cells by Raman spectral phenotyping.</a> Biophys J. 98 (8), 1703-1711 (2010).</li>
<li>Smith, R., Wright, K., Ashton, L. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+spectroscopy%3A+an+evolving+technique+for+live+cell+studies%5BTitle%5D)+AND+%22Analyst%22%5BJournal%5D)">Raman spectroscopy: an evolving technique for live cell studies.</a> Analyst. 141 (12), 3590-3600 (2016).</li>
<li>Du, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman-guided+subcellular+pharmaco-metabolomics+for+metastatic+melanoma+cells%5BTitle%5D)+AND+%22Nat+Commun%22%5BJournal%5D)">Raman-guided subcellular pharmaco-metabolomics for metastatic melanoma cells.</a> Nat Commun. 11 (1), 4830(2020).</li>
<li>Jones, R. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Raman+techniques%3A+fundamentals+and+frontiers%5BTitle%5D)+AND+%22Nanoscale+Res+Lett%22%5BJournal%5D)">Raman techniques: fundamentals and frontiers.</a> Nanoscale Res Lett. 14, 231(2019).</li>
<li>Shirokova, O., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Possibilities+of+holotomographic+microscopy+for+studying+primary+cell+cultures+of+the+brain%5BTitle%5D)+AND+%22Proc+IEEE+CNN%22%5BJournal%5D)">Possibilities of holotomographic microscopy for studying primary cell cultures of the brain.</a> Proc IEEE CNN. 208 (211), 208-211 (2024).</li>
<li>Choi, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Tomographic+phase+microscopy%5BTitle%5D)+AND+%22Nat+Methods%22%5BJournal%5D)">Tomographic phase microscopy.</a> Nat Methods. 4 (9), 717-719 (2007).</li>
<li>Park, Y., Depeursinge, C., Popescu, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Quantitative+phase+imaging+in+biomedicine%5BTitle%5D)+AND+%22Nat+Photonics%22%5BJournal%5D)">Quantitative phase imaging in biomedicine.</a> Nat Photonics. 12 (10), 578-589 (2018).</li>
<li>Jung, J., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Label-free+non-invasive+quantitative+measurement+of+lipid+contents+in+individual+microalgal+cells+using+refractive+index+tomography%5BTitle%5D)+AND+%22Sci+Rep%22%5BJournal%5D)">Label-free non-invasive quantitative measurement of lipid contents in individual microalgal cells using refractive index tomography.</a> Sci Rep. 8 (1), 6524(2018).</li>
<li>Debnath, S. K., Park, Y. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Real-time+quantitative+phase+imaging+with+a+spatial+phase-shifting+algorithm%5BTitle%5D)+AND+%22Opt+Lett%22%5BJournal%5D)">Real-time quantitative phase imaging with a spatial phase-shifting algorithm.</a> Opt Lett. 36 (23), 4677-4679 (2011).</li>
</ol>

The authors declare no conflicts of interest.

We presented a multimodal approach and straightforward analysis pipeline integrating two advanced, label-free imaging techniques: RS and TPM. The described workflow enabled rapid, non-invasive morpho-chemical phenotyping of living human breast cancer single cells (MDA-MB-231) without the need for external labeling.
RS is a non-destructive technique that allows for the characterization of the biochemical composition of biological samples through the detection of the vibrational modes of molecul...

Cell characterization and phenotyping are pivotal aspects of biomedical research1. Being able to characterize cells at both the morphological and molecular levels is paramount to understanding cell function, differentiation, and pathology1,2,3. It is particularly of interest in the field of oncology, where accurate cell profiling is necessary for tumor diagnosis, determining disease stage, and ultimately identifying therapeutic targets2. Traditional cell characterization methods cannot provide temporal dynamics and are usually based on invasive techniques, such as staining or labeling, which may interfere with the native state of the cells and introduce potential biases within the data4. Therefore, non-invasive strategies to provide accurate and thorough phenotyping of living cells, in their native, unperturbed state, are increasingly in demand.
In this context, label-free multimodal imaging methods have revolutionized cell biology research by combining complementary modalities to capture both morphological and molecular information2,5. These approaches allow for the integrated and non-invasive characterization of the cells that individual traditional techniques may not always be able to provide2,5,6. For instance, though microscopy techniques such as fluorescence microscopy have been widely used in morphological and functional cell imaging, they possess inherent limitations. Fluorescence methods often suffer from photobleaching, phototoxicity, and low quantities of targetable molecules, which restrict the analytical potential4. In addition, these approaches often require the use of exogenous labels or dyes, which may disrupt the native cell state or lead to artifacts7.
Multimodal imaging platforms, which combine the strengths of multiple imaging modalities, surpass these limitations by enabling the acquisition of different types of data from living cells without the need for labeling. The integration of Raman spectroscopy (RS) with other imaging modalities like phase contrast microscopy or tomographic phase microscopy (TPM) has been a promising strategy to overcome the limitations of single techniques. Indeed, multimodal imaging provides a deeper understanding of cellular phenotypes, especially in complex biological conditions and pathologies like cancer, where molecular and structural properties are crucial for accurate characterization2,5.
Label-free RS is well-suited for chemical imaging of cells8. By detecting molecular vibrational modes, RS provides biochemical fingerprints that can reveal in-depth information about the molecular composition of cells9,10,11. Raman spectra acquired from biological samples contain information about a variety of biomolecules such as lipids, proteins, nucleic acids, and metabolites, which play essential roles in understanding the molecular nature of cells9,12. One of the main strengths of RS is that it is non-invasive, allowing for the characterization of living cells in their natural state without altering their physiological condition.
Despite its many advantages, RS also presents some limitations. Indeed, although RS provides detailed molecular information, it does not allow for quantitative information on the morphology or structure of cells2. This is where complementary imaging techniques like TPM play a crucial role.
TPM is a form of quantitative phase imaging (QPI)13,14, and it enables the visualization of high-resolution, label-free quantitative information about cell morphology15,16. TPM differs from traditional microscopy techniques in that it does not require contrast agents; instead, it operates by measuring phase shifts resulting from variations in the refractive index (RI) of the sample17. Phase shifts provide information about the structural properties of the cell, including its volume, surface area, shape, and internal structure2,18. TPM can achieve high spatial resolution, to the nanometer level, and hence is an ideal technique for recording high-resolution morphological details of living cells. Further, the ability to reconstruct 3D RI tomograms makes it possible to visualize subcellular structures in their vivo environment18, providing more accurate information compared to 2D projections. However, one of the main limitations of TPM is its lack of chemical specificity, as it primarily provides information on the cell&#39;s morphology and phase distribution, without being able to differentiate between distinct chemical components or identify biochemical features.
The combination of RS and TPM in a multimodal technique provides advantages in cell phenotyping. While RS allows for rich molecular information, TPM adds a structural aspect, allowing cellular morphology to be analyzed in considerable detail. Recently, the combination of RS with TPM has been successfully demonstrated in several studies focused on cancer research2,19,20. For instance, previous work has reported that co-registering Raman spectroscopy with holographic phase microscopy data can provide complementary molecular and morphological information, allowing distinguishing among different cell types and tumor development stages2. These investigations have highlighted the power of multimodal imaging to enhance the accuracy of cell phenotyping, particularly in the context of cancer, where the molecular and structural characteristics of cells are closely linked to their malignancy and behavior2,20.
Despite the recent progress in multimodal imaging, there are still challenges to be addressed, particularly in data processing and analysis21. The large amounts of data that multimodal imaging techniques yield can be cumbersome to analyze, and straightforward procedures must be employed to extract meaningful information. To counter this challenge, user-friendly data processing pipelines must be established to handle the complexity of the data and minimize human bias in the analysis. Such pipelines are critical for the achievement of accuracy and reproducibility of the results and the possible translation of these approaches into clinical and diagnostic applications.
The goal of the present work is to illustrate the potential of merging RS with TPM for label-free, high-speed, and non-perturbative phenotyping of live single cancer cells. By merging these two robust imaging approaches, we provide a comprehensive and quantitative characterization of the molecular and morphological properties of human breast cancer cells (MDA-MB-231). The work also emphasizes the importance of establishing human-bias-free data processing pipelines to ensure that the extracted information from the multimodal datasets is correct and reliable. Here, we seek to establish a robust platform for cancer cell phenotyping that can be generalized to other types of cells. The versatility and sensitivity of this approach make it a potential candidate for a wide range of biomedical applications, from fundamental cell biology studies to diagnostics.

<table><tbody><tr><td>CCD camera</td><td>Princeton Instruments</td><td>PIXIS 100BR eXcelon</td><td>Detector for Raman scattering signal.</td></tr><tr><td>CCD camera control software</td><td>Princeton Instruments</td><td>LightField</td><td></td></tr><tr><td>Continuous-wave Ti-Sapphire laser (wavelength: 785 nm)</td><td>Spectra-Physics</td><td>3900 S</td><td>It is used for Raman microscopy excitation.</td></tr><tr><td>Dichroic mirror</td><td>ThorLabs</td><td>DMSP750B</td><td>749-nm dichroic mirror, deflects 785-nm Raman excitation to sample, filters out fluorescence and brightfield signals.</td></tr><tr><td>Fetal Bovine Serum</td><td>Thermo Fisher Scientific</td><td>A5256701</td><td></td></tr><tr><td>Fluorescence microscope body</td><td>Olympus</td><td>IX83</td><td></td></tr><tr><td>Laser (wavelength: 532 nm)</td><td>Spectra-Physics</td><td>Millennia eV</td><td>Pump laser for 785-nm Ti-Sapphire laser system.</td></tr><tr><td>MATLAB software</td><td>MathWorks</td><td>2023a</td><td></td></tr><tr><td>MDA-MB-231 cell line</td><td>ATCC</td><td>HTB-26</td><td></td></tr><tr><td>NIR spectrograph</td><td>Andror</td><td>Holospec HS-HSG-785-LF</td><td>It is used for spectral analysis of backscattered light.</td></tr><tr><td>Objective lens (60&amp;times; 1.2 NA water-immersion)</td><td>Olympus</td><td>UPLSAPO60&amp;times;</td><td></td></tr><tr><td>Onstage incubation chamber</td><td>Tokai Hit</td><td>stxg-welsx-set</td><td></td></tr><tr><td>Open-source microscope control software</td><td>&amp;micro;Manager</td><td>Micro-Manager-2.0</td><td></td></tr><tr><td>Penicillin-Streptomycin (10,000 U/mL)</td><td>Thermo Fisher Scientific</td><td>15140122</td><td></td></tr><tr><td>Phenol free DMEM/F-12</td><td>Thermo Fisher Scientific</td><td>21041025</td><td></td></tr><tr><td>Phosphate buffered saline</td><td>Gibco</td><td>10-010-023</td><td></td></tr><tr><td>Quartz glass-bottom Petri dishes</td><td>Waken B Tech</td><td>SF-S-D12</td><td></td></tr><tr><td>Raman data analysis software</td><td>RamApp</td><td></td><td>Web-based tool for Raman hyperspectral data processing.</td></tr><tr><td>sCMOS camera</td><td>Hamamatsu Photonics</td><td>Orca Flash 4.0 v2</td><td></td></tr><tr><td>Syringe pump</td><td>Chemyx</td><td>Fusion 720</td><td></td></tr><tr><td>Tomographic phase microscope</td><td>Tomocube, Inc.</td><td>HT-2H</td><td>Commercial system for obtaining quantitative phase images.</td></tr><tr><td>TPM data analysis software</td><td>Tomocube, Inc.</td><td>TomoStudio</td><td>Software used for analyzing tomographic phase microscopy (TPM) data.</td></tr></tbody></table>

a multimodal imaging framework to advance phenotyping of living label-free breast cancer cells

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

We present multimodal confocal Raman micro-spectroscopy (RS) and tomographic phase microscopy (TPM) for quick morpho-chemical phenotyping of human breast cancer cells (MDA-MB-231). Leveraging the non-perturbative nature of these advanced microscopy techniques, we captured detailed morpho-molecular data from living, label-free cells in their native physiological environment. Human bias-free data processing pipelines were developed to analyze hyperspectral Raman images (spanning Raman modes from 600 cm-1 to 1800 cm-1, which uniquely characterize a wide range of molecular bonds and subcellular structures), as well as morphological data from three-dimensional refractive index tomograms (providing measurements of cell volume, surface area, footprint, and sphericity at nanometer resolution, alongside dry mass and density). By systematically breaking down the rich single-cell details that RS and TPM deliver, we demonstrate, in a quantitative manner, the advantage of such a multimodal microscopy method for phenotyping tumoral breast cancer cells. Our tools also provide further insight into the subcellular information without the use of any labels. Finally, we study and discuss any unique or correlated information that RS- and TPM-derived datasets feature. We believe our tools and quantitative data analysis pipelines can revolutionize phenotyping tasks in biomedical research when in need of a rapid and non-perturbative method on living cells in culture, with the potential for future translation into clinical and diagnostic applications.

We described a workflow for the label-free morpho-chemical characterization of living cells based on confocal RS and TPM. We tested the ability of the proposed workflow to attain the molecular composition and morphological parameters of the human breast cancer cell line MDA-MB-231 (Figure 1).
MDA-MB-231 cells were seeded onto quartz glass-bottom Petri dishes. A custom-built confocal Raman microscope (Figure 1A), operating at 785-nm co...

This protocol presents a multimodal approach combining Raman spectroscopy and tomographic phase microscopy for label-free, non-invasive phenotyping of living human breast cancer cells. It includes a user-friendly, human-bias-free analysis pipeline for rapid, quantitative morpho-chemical analysis, providing detailed molecular and structural insights with applications in cancer research and cell biology.

We present multimodal confocal Raman micro-spectroscopy (RS) and tomographic phase microscopy (TPM) for quick morpho-chemical phenotyping of human breast ...

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Learn multimodal imaging using confocal Raman microspectroscopy and tomographic phase microscopy for label-free phenotyping of living breast cancer cells. This method provides rapid morpho-chemical analysis without perturbation.

A Multimodal Imaging Framework to Advance Phenotyping of Living Label-free Breast Cancer Cells

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