Raman Imaging and Fluorescence Lifetime Imaging Microscopy for Diagnosis of Cancer State and Metabolic Monitoring

Abstract

Hurdles for effective tumor therapy are delayed detection and limited effectiveness of systemic drug therapies by patient-specific multidrug resistance. Non-invasive bioimaging tools such as fluorescence lifetime imaging microscopy (FLIM) and Raman-microspectroscopy have evolved over the last decade, providing the potential to be translated into clinics for early-stage disease detection, in vitro drug screening, and drug efficacy studies in personalized medicine. Accessing tissue- and cell-specific spectral signatures, Raman microspectroscopy has emerged as a diagnostic tool to identify precancerous lesions, cancer stages, or cell malignancy. In vivo Raman measurements have been enabled by recent technological advances in Raman endoscopy and signal-enhancing setups such as coherent anti-stokes Raman spectroscopy or surface-enhanced Raman spectroscopy. FLIM enables in situ investigations of metabolic processes such as glycolysis, oxidative stress, or mitochondrial activity by using the autofluorescence of co-enzymes NADH and FAD, which are associated with intrinsic proteins as a direct measure of tumor metabolism, cell death stages and drug efficacy. The combination of non-invasive and molecular-sensitive in situ techniques and advanced 3D tumor models such as patient-derived organoids or microtumors allows the recapitulation of tumor physiology and metabolism in vitro and facilitates the screening for patient-individualized drug treatment options.

Keywords: 3D in vitro models; Raman microspectroscopy; fluorescence lifetime imaging microscopy; in situ imaging; tissue diagnostics; tumor metabolism.

Figure 2

Application of Raman and FLIM imaging to discriminate tumor tissues. (a) Imaging of tissues from patients with low grade (A–D) and stage IIA (E–H) colorectal carcinoma. H&E staining (A, E), K-means clustering result of CARS spectra in the 2700–3000 cm⁻¹ region (B, F), combined images of second harmonic generation (SHG) intensities at 408 nm and CARS signals at 2850 cm⁻¹ (C, G) and overlay of k-means clustering with SHG and CARS (D, H) are shown. Reprinted with permission from [110]. (b) CARS (A–D) and H&E (E–H) imaging of mouse brain sections with an experimental human U87MG glioblastoma (A, B), breast cancer metastasis induced by MCF-7 cells (C) and melanoma induced by A375 cells (D). White matter of brain and normal tissue appears brighter in CARS images, while the tumor regions are darker. Reprinted with permission from [119]. (c) FLIM images of skin sections from actinic keratosis (AK), Bowen’s disease (BD), and basal cell carcinoma (BCC). The corresponding color-coding scheme ranges from red (0 ps) to blue (450 ps). For each patient and disease type, the mean fluorescence lifetimes (τm) of stratum corneum (SC, black line), epithelial cells (EC, red line), and dermal connective tissue (CT, blue line) were compared. Reprinted with permission from [124]. (d) 5-ALA fluorescence intensity (grey scale) and FLIM images (color) of brain tumor samples. Infiltrating tumor tissues characterized by increased lifetimes in green (2.1, 2.2), focal glial cell infiltration (2.3), strong 5-ALA positive fluorescence, according to increased lifetimes in red (3.1, 4.1) and glioblastoma with minimal infiltration of tumor cells are demonstrated (5.1). Areas in purple correspond to areas outside of the sample. Scale bars are equal to 2 mm. Reprinted with permissions from [125].

Figure 3

In vitro cancer models and Raman/FLIM imaging of 3D patient-derived tissue models. (a) Schematic illustration of 2D and different 3D in vitro tumor models. (b) Raman images of renal cell carcinoma (RCC) microtumors, colorectal cancer (CRC) organoids [218] and endometrium organoids. False color-coded intensity distribution heatmaps indicate DNA (blue), cytoplasm (green), lipids (pink), proteins (light blue) and mitochondria (orange/red). (c) Fluorescence lifetime imaging microscopy of CRC organoids. Displayed are the ratios of unbound to bound NADH (α1 [%]) of control organoids and organoids 24 h after cisplatin and regorafenib treatment. Patient-derived microtumor and organoid samples were provided by C. Schmees and A. Koch and retrieved in accordance with the Declaration of Helsinki; the protocol was approved by the Ethics Committee of the Medical Faculty at the University of Tübingen (150/2018BO2 and 379/2010BO2).

Figure 1

Schematic of Raman and FLIM instrumentation. The basic light pathway of both techniques is initiated at a laser source which is directed on the sample to induce photon–matter interactions. The emitted or scattered light is then directed through a beam splitter and a pinhole to the detector. (a) In Raman microspectroscopy, inelastic scattering results in energy transfer processes to higher (anti-Stokes) or lower (Stokes) energy levels than the excitation source. Raman spectroscopy requires a spectrograph e.g., with a charge-couple device (CCD) camera as a detector and Raman spectra are the typical readouts. By raster scanning, hyperspectral Raman images can be generated, where each pixel corresponds to one specific Raman spectrum. (b) Fluorescence lifetime decays are the targeted processes in fluorescence lifetime imaging (FLIM) microscopy. The average time that a fluorophore spends in the excited state can be detected by photomultiplier-tubes (PMT). The most common acquisition modes are frequency-domain or time-domain photon counting.