Current methods for identifying neoplastic cells and discerning them from their normal counterparts are often nonspecific, slow, biologically perturbing, or a combination thereof. Here, we show that single-cell micro-Raman spectroscopy averts these shortcomings and can be used to discriminate between unfixed normal human lymphocytes and transformed Jurkat and Raji lymphocyte cell lines based on their biomolecular Raman signatures. We demonstrate that single-cell Raman spectra provide a highly reproducible biomolecular fingerprint of each cell type. Characteristic peaks, mostly due to different DNA and protein concentrations, allow for discerning normal lymphocytes from transformed lymphocytes with high confidence (p << 0.05). Spectra are also compared and analyzed by principal component analysis to demonstrate that normal and transformed cells form distinct clusters that can be defined using just two principal components. The method is shown to have a sensitivity of 98.3% for cancer detection, with 97.2% of the cells being correctly classified as belonging to the normal or transformed type. These results demonstrate the potential application of confocal micro-Raman spectroscopy as a clinical tool for single cancer cell detection based on intrinsic biomolecular signatures, therefore eliminating the need for exogenous fluorescent labeling.

Using in situ Raman scattering in a confocal microscopy setup, we have observed changes in the network structure of fused silica after modifying regions inside the glass with tightly focused 800-nm 130-fs laser pulses at fluences of 5-200 J cm(-2). The Raman spectra show a large increase in the peaks at 490 and 605cm(-1), owing to 4- and 3-membered ring structures in the silica network, indicating that densification occurs after exposure to the femtosecond laser pulses. The results are consistent with the formation of a localized plasma by the laser pulse and a subsequent microexplosion inside the glass.

Self-renewable, pluripotent human embryonic stem cells (hESCs) can be differentiated into cardiomyocytes (CMs), providing an unlimited source of cells for transplantation therapies. However, unlike certain cell lineages such as hematopoietic cells, CMs lack specific surface markers for convenient identification, physical separation, and enrichment. Identification by immunostaining of cardiac-specific proteins such as troponin requires permeabilization, which renders the cells unviable and non-recoverable. Ectopic expression of a reporter protein under the transcriptional control of a heart-specific promoter for identifying hESC-derived CMs (hESC-CMs) is useful for research but complicates potential clinical applications. The practical detection and removal of undifferentiated hESCs in a graft, which may lead to tumors, is also critical. Here, we demonstrate a non-destructive, label-free optical method based on Raman scattering to interrogate the intrinsic biochemical signatures of individual hESCs and their cardiac derivatives, allowing cells to be identified and classified. By combining the Raman spectroscopic data with multivariate statistical analysis, our results indicate that hESCs, human fetal left ventricular CMs, and hESC-CMs can be identified by their intrinsic biochemical characteristics with an accuracy of 96%, 98% and 66%, respectively. The present study lays the groundwork for developing a systematic and automated method for the non-invasive and label-free sorting of i) high-quality hESCs for expansion, and ii) ex vivo CMs (derived from embryonic or adult stem cells) for cell-based heart therapies.