Fluorescence microscopy is a core biomedical imaging tool that provides high-resolution images of molecular contrast in living samples. Stokes coined the term “fluorescence” in 1852 for the “remarkable phenomena of light” observed in the materials that emitted light at a different color than the absorbed light.¹ At that time, refraction (or refrangibility), internal dispersion, circular dichroism, and other phenomena of light were well studied. Stokes examined flower petals, leaves, turmeric, calcium fluoride, and many other compounds. In the 20th century, fluorescence was redefined as a short-lived emission of photons caused by the incidence of higher energy photons and became a popular tool for studying molecular dynamics and characterizing compounds.

The fluorescence lifetime is the average time that a fluorophore remains in an excited state before returning to the ground state and emitting a photon. The fluorescence lifetime is sensitive to the environment of the fluorophore, including pH, temperature, viscosity, and binding state. Fluorescence lifetime imaging microscopy (FLIM) provides information on molecular interactions that are advantageous for biological and medical imaging. FLIM captures the decay time of fluorophores at each pixel of the image, and therefore, provides unique information compared to intensity (photon flux) or spectral (photon wavelength or energy) imaging of fluorescence. Unlike intensity-based measurements, lifetime is self-referenced and independent of the absolute number of photons. Therefore, FLIM is not corrupted by variations in intensity between pixels. Our previous review covered the fundamentals of FLIM instrumentation and analysis, along with applications to live cell and tissue imaging.¹ The goal of this perspective paper is to provide updates of innovations in FLIM which we, as experts in the field, found impactful within the last year. These new developments have been categorized into advances in instrumentation, new approaches to FLIM data analysis, and recent applications of FLIM in biology and medicine. The developments covered in this perspective are not exhaustive and innovations in FLIM instrumentation, analysis, and applications are ongoing. For a more comprehensive review on FLIM, readers are encouraged to refer to other publications.^{1 – 5}

Gastroenteropancreatic neuroendocrine tumors (GEP-NET) account for roughly 60% of all neuroendocrine tumors. Low/intermediate grade human GEP-NETs have relatively low proliferation rates that animal models and cell lines fail to recapitulate. Short-term patient-derived cancer organoids (PDCOs) are a 3D model system that holds great promise for recapitulating well-differentiated human GEP-NETs. However, traditional measurements of drug response (i.e., growth, proliferation) are not effective in GEP-NET PDCOs due to the small volume of tissue and low proliferation rates that are characteristic of the disease. Here, we test a label-free, non-destructive optical metabolic imaging (OMI) method to measure drug response in live GEP-NET PDCOs. OMI captures the fluorescence lifetime and intensity of endogenous metabolic cofactors NAD(P)H and FAD. OMI has previously provided accurate predictions of drug response on a single cell level in other cancer types, but this is the first study to apply OMI to GEP-NETs. OMI tested the response to novel drug combination on GEP-NET PDCOs, specifically ABT263 (navitoclax), a Bcl-2 family inhibitor, and everolimus, a standard GEP-NET treatment that inhibits mTOR. Treatment response to ABT263, everolimus, and the combination were tested in GEP-NET PDCO lines derived from seven patients, using two-photon OMI. OMI measured a response to the combination treatment in 5 PDCO lines, at 72 h post-treatment. In one of the non-responsive PDCO lines, heterogeneous response was identified with two distinct subpopulations of cell metabolism. Overall, this work shows that OMI provides single-cell metabolic measurements of drug response in PDCOs to guide drug development for GEP-NET patients.

SignificanceCellular metabolism plays a central role in health and disease, making its study critical for advancing diagnostics and therapies. Label-free optical metabolic imaging using endogenous fluorescence from reduced nicotinamide adenine dinucleotide (phosphate) [NAD(P)H] and flavin adenine dinucleotide (FAD) provides nondestructive, high-resolution insights into metabolic function and heterogeneity from the sub-cellular to the tissue level. Standardized approaches are essential to ensure reproducibility and comparability across studies.AimWe aim to establish a consensus framework for the acquisition, calibration, and reporting of microscopic imaging metabolic function assessments based on fluorescence intensity and lifetime measurements of NAD(P)H and FAD.ApproachWe present best practices for calibrating, analyzing, and reporting fluorescence intensity-based optical redox ratios and fluorescence lifetime data using multiexponential fitting and phasor analysis. Guidelines for validation experiments and cross-system standardization are provided to improve accuracy and reproducibility.ResultsWe demonstrate the importance of calibration procedures and normalization strategies for intensity-based optical redox measurements. We highlight needed calibration, signal-to-noise ratio considerations, and the impact of distinct analytical approaches on fluorescence lifetime-based metabolic function metrics.ConclusionWe recommend a consistent, practical framework for reproducible, label-free, optical metabolic imaging, facilitating robust comparisons across studies and supporting the broader adoption of optical metabolic imaging technologies for biomedical research and clinical translation.

The prostate tumor microenvironment (TME) is strongly immunosuppressive; it is largely driven by alteration in cell phenotypes (i.e. tumor-associated macrophages and exhausted cytotoxic T cells) that result in pro-tumorigenic conditions and tumor growth. A greater understanding into how these altered immune cell phenotypes are developed and could potentially be reversed would provide important insights into improved treatment efficacy for prostate cancer. Here, we report a microfluidic model of the prostate TME that mimics prostate ducts across various stages of prostate cancer progression, with associated stroma and immune cells. Using this platform, we exposed immune cells to a benign prostate TME or a metastatic prostate TME and investigated their metabolism, gene and cytokine expression. Immune cells exposed to the metastatic TME showed metabolic differences with a higher redox ratio indicating a switch to a more glycolytic metabolic profile. These cells also increased expression of pro-tumor response cytokines that have been shown to increase cell migration and angiogenesis such as Interleukin-1 (IL-1) a and Granulocyte-macrophage colony-stimulating factor (GM-CSF). Lastly, we observed decreased TLR, STAT signaling and TRAIL expression, suggesting that phenotypes derived from exposure to the metastatic TME could have an impaired anti-tumor response. This platform could provide a valuable tool for studying immune cell phenotypes in in vitro tumor microenvironments.

Patient-derived cancer organoids (PDCO) are a valuable model to recapitulate human disease in culture, with important implications for drug development. However, current methods for rapidly and reproducibly assessing PDCOs are limited. Label-free imaging methods are a promising tool to measure organoid-level heterogeneity and rapidly screen drug responses in PDCOs. This study aimed to assess and predict PDCO response to treatments based on mutational profiles using label-free wide-field optical redox imaging (WF ORI). WF ORI provided organoid-level measurements of treatment response without labels or additional reagents by measuring the autofluorescence intensity of the metabolic coenzymes NAD(P)H and FAD, and the optical redox ratio, defined as the fluorescence intensity of [NAD(P)H/NAD(P)H + FAD], was used to measure the oxidation–reduction state of PDCOs. Development of leading-edge analysis tools helped maximize the sensitivity and reproducibility of treatment response measurements using WF ORI in colorectal cancer PDCOs. Leading-edge analysis improved sensitivity to redox changes in treated PDCOs. Additionally, WF ORI resolved FOLFOX (5-fluorouracil + oxaliplatin) treatment effects across all PDCOs better than two-photon ORI, with an approximately threefold increase in effect size. WF ORI distinguished metabolic differences based on driver mutations in colorectal cancer PDCOs, differentiating between KRAS + PIK3CA double-mutant PDCOs and wild-type PDCOs with 80% accuracy and identified treatment-resistant mutations in mixed PDCO cultures. Overall, WF ORI enables rapid, sensitive, and reproducible measurements of treatment response and heterogeneity in colorectal PDCOs that will affect patient management, clinical trials, and preclinical drug development. Significance: Label-free wide-field optical redox imaging is an accessible tool for monitoring changes in metabolism in patient-derived cancer organoids to reproducibly assess treatment response and heterogeneity in clinically relevant treatment studies.