Human induced pluripotent stem cell-derived planar neural organoids assembled on synthetic hydrogels.

The tailorable properties of synthetic polyethylene glycol (PEG) hydrogels make them an attractive substrate for human organoid assembly. Here, we formed human neural organoids from iPSC-derived progenitor cells in two distinct formats: (i) cells seeded on a Matrigel surface; and (ii) cells seeded on a synthetic PEG hydrogel surface. Tissue assembly on synthetic PEG hydrogels resulted in three dimensional (3D) planar neural organoids with greater neuronal diversity, greater expression of neurovascular and neuroinflammatory genes, and reduced variability when compared with tissues assembled upon Matrigel. Further, our 3D human tissue assembly approach occurred in an open cell culture format and created a tissue that was sufficiently translucent to allow for continuous imaging. Planar neural organoids formed on PEG hydrogels also showed higher expression of neural, vascular, and neuroinflammatory genes when compared to traditional brain organoids grown in Matrigel suspensions. Further, planar neural organoids contained functional microglia that responded to pro-inflammatory stimuli, and were responsive to anti-inflammatory drugs. These results demonstrate that the PEG hydrogel neural organoids can be used as a physiologically relevant in vitro model of neuro-inflammation.

A bioengineered organotypic prostate model for the study of tumor microenvironment-induced immune cell activation.

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.

Label-free redox imaging of patient-derived organoids using selective plane illumination microscopy.

High-throughput drug screening of patient-derived organoids offers an attractive platform to determine cancer treatment efficacy. Here, selective plane illumination microscopy (SPIM) was used to determine treatment response in organoids with endogenous fluorescence from the metabolic coenzymes NAD(P)H and FAD. Rapid 3-D autofluorescence imaging of colorectal cancer organoids was achieved. A quantitative image analysis approach was developed to segment each organoid and quantify changes in endogenous fluorescence caused by treatment. Quantitative analysis of SPIM volumes confirmed the sensitivity of patient-derived organoids to standard therapies. This proof-of-principle study demonstrates that SPIM is a powerful tool for high-throughput screening of organoid treatment response.

Label-free spectroscopic tissue characterization using fluorescence excitation-scanning spectral imaging.

Spectral imaging approaches provide new possibilities for measuring and discriminating fluorescent molecules in living cells and tissues. These approaches often employ tunable filters and robust image processing algorithms to identify many fluorescent labels in a single image set. Here, we present results from a novel spectral imaging technology that scans the fluorescence excitation spectrum, demonstrating that excitation-scanning hyperspectral image data can discriminate among tissue types and estimate the molecular composition of tissues. This approach allows fast, accurate quantification of many fluorescent species from multivariate image data without the need of exogenous labels or dyes. We evaluated the ability of the excitation-scanning approach to identify endogenous fluorescence signatures in multiple unlabeled tissue types. Signatures were screened using multi-pass principal component analysis. Endmember extraction techniques revealed conserved autofluorescent signatures across multiple tissue types. We further examined the ability to detect known molecular signatures by constructing spectral libraries of common endogenous fluorophores and applying multiple spectral analysis techniques on test images from lung, liver and kidney. Spectral deconvolution revealed structure-specific morphologic contrast generated from pure molecule signatures. These results demonstrate that excitation-scanning spectral imaging, coupled with spectral imaging processing techniques, provides an approach for discriminating among tissue types and assessing the molecular composition of tissues. Additionally, excitation scanning offers the ability to rapidly screen molecular markers across a range of tissues without using fluorescent labels. This approach lays the groundwork for translation of excitation-scanning technologies to clinical imaging platforms.

Patient-Derived Cancer Organoid Cultures to Predict Sensitivity to Chemotherapy and Radiation.

PURPOSE: Cancer treatment is limited by inaccurate predictors of patient-specific therapeutic response. Therefore, some patients are exposed to unnecessary side effects and delays in starting effective therapy. A clinical tool that predicts treatment sensitivity for individual patients is needed. EXPERIMENTAL DESIGN: Patient-derived cancer organoids were derived across multiple histologies. The histologic characteristics, mutation profile, clonal structure, and response to chemotherapy and radiation were assessed using bright-field and optical metabolic imaging on spheroid and single-cell levels, respectively. RESULTS: We demonstrate that patient-derived cancer organoids represent the cancers from which they were derived, including key histologic and molecular features. These cultures were generated from numerous cancers, various biopsy sample types, and in different clinical settings. Next-generation sequencing reveals the presence of subclonal populations within the organoid cultures. These cultures allow for the detection of clonal heterogeneity with a greater sensitivity than bulk tumor sequencing. Optical metabolic imaging of these organoids provides cell-level quantification of treatment response and tumor heterogeneity allowing for resolution of therapeutic differences between patient samples. Using this technology, we prospectively predict treatment response for a patient with metastatic colorectal cancer. CONCLUSIONS: These studies add to the literature demonstrating feasibility to grow clinical patient-derived organotypic cultures for treatment effectiveness testing. Together, these culture methods and response assessment techniques hold great promise to predict treatment sensitivity for patients with cancer undergoing chemotherapy and/or radiation.

MTORC1/2 Inhibition as a Therapeutic Strategy for PIK3CA Mutant Cancers.

PIK3CA mutations are common in clinical molecular profiling, yet an effective means to target these cancers has yet to be developed. MTORC1 inhibitors are often used off-label for patients with PIK3CA mutant cancers with only limited data to support this approach. Here we describe a cohort of patients treated with cancers possessing mutations activating the PI3K signaling cascade with minimal benefit to treatment with the MTORC1 inhibitor everolimus. Previously, we demonstrated that dual PI3K/mTOR inhibition could decrease proliferation, induce differentiation, and result in a treatment response in APC and PIK3CA mutant colorectal cancer. However, reactivation of AKT was identified, indicating that the majority of the benefit may be secondary to MTORC1/2 inhibition. TAK-228, an MTORC1/2 inhibitor, was compared with dual PI3K/mTOR inhibition using BEZ235 in murine colorectal cancer spheroids. A reduction in spheroid size was observed with TAK-228 and BEZ235 (-13% and -14%, respectively) compared with an increase of >200% in control (P < 0.001). These spheroids were resistant to MTORC1 inhibition. In transgenic mice possessing Pik3ca and Apc mutations, BEZ235 and TAK-228 resulted in a median reduction in colon tumor size of 19% and 20%, respectively, with control tumors having a median increase of 18% (P = 0.02 and 0.004, respectively). This response correlated with a decrease in the phosphorylation of 4EBP1 and RPS6. MTORC1/2 inhibition is sufficient to overcome resistance to everolimus and induce a treatment response in PIK3CA mutant colorectal cancers and deserves investigation in clinical trials and in future combination regimens.

Protein-bound NAD(P)H Lifetime is Sensitive to Multiple Fates of Glucose Carbon.

While NAD(P)H fluorescence lifetime imaging (FLIM) can detect changes in flux through the TCA cycle and electron transport chain (ETC), it remains unclear whether NAD(P)H FLIM is sensitive to other potential fates of glucose. Glucose carbon can be diverted from mitochondria by the pentose phosphate pathway (via glucose 6-phosphate dehydrogenase, G6PDH), lactate production (via lactate dehydrogenase, LDH), and rejection of carbon from the TCA cycle (via pyruvate dehydrogenase kinase, PDK), all of which can be upregulated in cancer cells. Here, we demonstrate that multiphoton NAD(P)H FLIM can be used to quantify the relative concentrations of recombinant LDH and malate dehydrogenase (MDH) in solution. In multiple epithelial cell lines, NAD(P)H FLIM was also sensitive to inhibition of LDH and PDK, as well as the directionality of LDH in cells forced to use pyruvate versus lactate as fuel sources. Among the parameters measurable by FLIM, only the lifetime of protein-bound NAD(P)H (τ2) was sensitive to these changes, in contrast to the optical redox ratio, mean NAD(P)H lifetime, free NAD(P)H lifetime, or the relative amount of free and protein-bound NAD(P)H. NAD(P)H τ2 offers the ability to non-invasively quantify diversions of carbon away from the TCA cycle/ETC, which may support mechanisms of drug resistance.

Comparing Methods for Analysis of Biomedical Hyperspectral Image Data.

Over the past 2 decades, hyperspectral imaging technologies have been adapted to address the need for molecule-specific identification in the biomedical imaging field. Applications have ranged from single-cell microscopy to whole-animal in vivo imaging and from basic research to clinical systems. Enabling this growth has been the availability of faster, more effective hyperspectral filtering technologies and more sensitive detectors. Hence, the potential for growth of biomedical hyperspectral imaging is high, and many hyperspectral imaging options are already commercially available. However, despite the growth in hyperspectral technologies for biomedical imaging, little work has been done to aid users of hyperspectral imaging instmments in selecting appropriate analysis algorithms. Here, we present an approach for comparing the effectiveness of spectral analysis algorithms by combining experimental image data with a theoretical "what if' scenario. This approach allows us to quantify several key outcomes that characterize a hyperspectral imaging study: linearity of sensitivity, positive detection cut-off slope, dynamic range, and false positive events. We present results of using this approach for comparing the effectiveness of several common spectral analysis algorithms for detecting weak fluorescent protein emission in the midst of strong tissue autofluorescence. Results indicate that this approach should be applicable to a very wide range of applications, allowing a quantitative assessment of the effectiveness of the combined biology, hardware, and computational analysis for detecting a specific molecular signature.

Excitation-Scanning Hyperspectral Imaging as a Means to Discriminate Various Tissues Types.

Little is currently known about the fluorescence excitation spectra of disparate tissues and how these spectra change with pathological state. Current imaging diagnostic techniques have limited capacity to investigate fluorescence excitation spectral characteristics. This study utilized excitation-scanning hyperspectral imaging to perform a comprehensive assessment of fluorescence spectral signatures of various tissues. Immediately following tissue harvest, a custom inverted microscope (TE-2000, Nikon Instruments) with Xe arc lamp and thin film tunable filter array (VersaChrome, Semrock, Inc.) were used to acquire hyperspectral image data from each sample. Scans utilized excitation wavelengths from 340 nm to 550 nm in 5 nm increments. Hyperspectral images were analyzed with custom Matlab scripts including linear spectral unmixing (LSU), principal component analysis (PCA), and Gaussian mixture modeling (GMM). Spectra were examined for potential characteristic features such as consistent intensity peaks at specific wavelengths or intensity ratios among significant wavelengths. The resultant spectral features were conserved among tissues of similar molecular composition. Additionally, excitation spectra appear to be a mixture of pure endmembers with commonalities across tissues of varied molecular composition, potentially identifiable through GMM. These results suggest the presence of common autofluorescent molecules in most tissues and that excitation-scanning hyperspectral imaging may serve as an approach for characterizing tissue composition as well as pathologic state. Future work will test the feasibility of excitation-scanning hyperspectral imaging as a contrast mode for discriminating normal and pathological tissues.

Hyperspectral imaging fluorescence excitation scanning for colon cancer detection.

Optical spectroscopy and hyperspectral imaging have shown the potential to discriminate between cancerous and noncancerous tissue with high sensitivity and specificity. However, to date, these techniques have not been effectively translated to real-time endoscope platforms. Hyperspectral imaging of the fluorescence excitation spectrum represents new technology that may be well suited for endoscopic implementation. However, the feasibility of detecting differences between normal and cancerous mucosa using fluorescence excitation-scanning hyperspectral imaging has not been evaluated. The goal of this study was to evaluate the initial feasibility of using fluorescence excitation-scanning hyperspectral imaging for measuring changes in fluorescence excitation spectrum concurrent with colonic adenocarcinoma using a small pre-pilot-scale sample size. Ex vivo analysis was performed using resected pairs of colorectal adenocarcinoma and normal mucosa. Adenocarcinoma was confirmed by histologic evaluation of hematoxylin and eosin (H&E) permanent sections. Specimens were imaged using a custom hyperspectral imaging fluorescence excitation-scanning microscope system. Results demonstrated consistent spectral differences between normal and cancerous tissues over the fluorescence excitation range of 390 to 450 nm that could be the basis for wavelength-dependent detection of colorectal cancers. Hence, excitation-scanning hyperspectral imaging may offer an alternative approach for discriminating adenocarcinoma from surrounding normal colonic mucosa, but further studies will be required to evaluate the accuracy of this approach using a larger patient cohort.

Three dimensional measurement of cAMP gradients using hyperspectral confocal microscopy.

Cyclic AMP (cAMP) is a ubiquitous second messenger known to differentially regulate many cellular functions over a wide range of timescales. Several lines of evidence have suggested that the distribution of cAMP within cells is not uniform, and that cAMP compartmentalization is largely responsible for signaling specificity within the cAMP signaling pathway. However, to date, no studies have experimentally measured three dimensional (3D) cAMP distributions within cells. Here we use both 2D and 3D hyperspectral microscopy to visualize cAMP gradients in endothelial cells from the pulmonary microvasculature (PMVECs). cAMP levels were measured using a FRET-based cAMP sensor comprised of a cAMP binding domain from EPAC sandwiched between FRET donors and acceptors - Turquoise and Venus fluorescent proteins. Data were acquired using either a Nikon A1R spectral confocal microscope or custom spectral microscopy system. Analysis of hyperspectral image stacks from a single confocal slice or from summed images of all slices (2D analysis) indicated little or no cAMP gradients were formed within PMVECs under basal conditions or following agonist treatment. However, analysis of hyperspectral image stacks from 3D cellular geometries (z stacks) demonstrate marked cAMP gradients from the apical to basolateral membrane of PMVECs. These results strongly suggest that 2D imaging studies of cAMP compartmentalization - whether epifluorescence or confocal microscopy - may lead to erroneous conclusions about the existence of cAMP gradients, and that 3D studies are required to assess mechanisms of signaling specificity.

Feasibility for detection of autofluorescent signatures in rat organs using a novel excitation-scanning hyperspectral imaging system.

The natural fluorescence (autofluorescence) of tissues has been noted as a biomarker for cancer for several decades. Autofluorescence contrast between tumors and healthy tissues has been of significant interest in endoscopy, leading to development of autofluorescence endoscopes capable of visualizing 2-3 fluorescence emission wavelengths to achieve maximal contrast. However, tumor detection with autofluorescence endoscopes is hindered by low fluorescence signal and limited quantitative information, resulting in prolonged endoscopic procedures, prohibitive acquisition times, and reduced specificity of detection. Our lab has designed a novel excitation-scanning hyperspectral imaging system with high fluorescence signal detection, low acquisition time, and enhanced spectral discrimination. In this study, we surveyed a comprehensive set of excised tissues to assess the feasibility of detecting tissue-specific pathologies using excitation-scanning. Fresh, untreated tissue specimens were imaged from 360 to 550 nm on an inverted fluorescence microscope equipped with a set of thin-film tunable filters (Semrock, A Unit of IDEX). Images were subdivided into training and test sets. Automated endmember extraction (ENVI 5.1, Exelis) with PCA identified endmembers within training images of autofluorescence. A spectral library was created from 9 endmembers. The library was used for identification of endmembers in test images. Our results suggest (1) spectral differentiation of multiple tissue types is possible using excitation scanning; (2) shared spectra between tissue types; and (3) the ability to identify unique morphological features in disparate tissues from shared autofluorescent components. Future work will focus on isolating specific molecular signatures present in tissue spectra, and elucidating the contribution of these signatures in pathologies.

Hyperspectral Imaging Fluorescence Excitation Scanning for Detecting Colorectal Cancer: Pilot Study.

Optical spectroscopy and hyperspectral imaging have shown the theoretical potential to discriminate between cancerous and non-cancerous tissue with high sensitivity and specificity. To date, these techniques have not been able to be effectively translated to endoscope platforms. Hyperspectral imaging of the fluorescence excitation spectrum represents a new technology that may be well-suited for endoscopic implementation. However, the feasibility of detecting differences between normal and cancerous mucosa using fluorescence excitation-scanning hyperspectral imaging has not been evaluated. The objective of this pilot study was to evaluate the changes in the fluorescence excitation spectrum of resected specimen pairs of colorectal adenocarcinoma and normal colorectal mucosa. Patients being treated for colorectal adenocarcinoma were enrolled. Representative adenocarcinoma and normal colonic mucosa specimens were collected from each case. Specimens were flash frozen in liquid nitrogen. Adenocarcinoma was confirmed by histologic evaluation of H&E permanent sections. Hyperspectral image data of the fluorescence excitation of adenocarcinoma and surrounding normal tissue were acquired using a custom microscope configuration previously developed in our lab. Results demonstrated consistent spectral differences between normal and cancerous tissues over the fluorescence excitation spectral range of 390-450 nm. We conclude that fluorescence excitation-scanning hyperspectral imaging may offer an alternative approach for differentiating adenocarcinoma and surrounding normal mucosa of the colon. Future work will focus on expanding the number of specimen pairs analyzed and will utilize fresh tissues where possible, as flash freezing and reconstituting tissues may have altered the autofluorescence properties.

Excitation-scanning hyperspectral imaging microscope.

Hyperspectral imaging is a versatile tool that has recently been applied to a variety of biomedical applications, notably live-cell and whole-tissue signaling. Traditional hyperspectral imaging approaches filter the fluorescence emission over a broad wavelength range while exciting at a single band. However, these emission-scanning approaches have shown reduced sensitivity due to light attenuation from spectral filtering. Consequently, emission scanning has limited applicability for time-sensitive studies and photosensitive applications. In this work, we have developed an excitation-scanning hyperspectral imaging microscope that overcomes these limitations by providing high transmission with short acquisition times. This is achieved by filtering the fluorescence excitation rather than the emission. We tested the efficacy of the excitation-scanning microscope in a side-by-side comparison with emission scanning for detection of green fluorescent protein (GFP)-expressing endothelial cells in highly autofluorescent lung tissue. Excitation scanning provided higher signal-to-noise characteristics, as well as shorter acquisition times (300 ms/wavelength band with excitation scanning versus 3 s/wavelength band with emission scanning). Excitation scanning also provided higher delineation of nuclear and cell borders, and increased identification of GFP regions in highly autofluorescent tissue. These results demonstrate excitation scanning has utility in a wide range of time-dependent and photosensitive applications.

Tunable thin-film optical filters for hyperspectral microscopy.

Hyperspectral imaging was originally developed for use in remote sensing applications. More recently, it has been applied to biological imaging systems, such as fluorescence microscopes. The ability to distinguish molecules based on spectral differences has been especially advantageous for identifying fluorophores in highly autofluorescent tissues. A key component of hyperspectral imaging systems is wavelength filtering. Each filtering technology used for hyperspectral imaging has corresponding advantages and disadvantages. Recently, a new optical filtering technology has been developed that uses multi-layered thin-film optical filters that can be rotated, with respect to incident light, to control the center wavelength of the pass-band. Compared to the majority of tunable filter technologies, these filters have superior optical performance including greater than 90% transmission, steep spectral edges and high out-of-band blocking. Hence, tunable thin-film optical filters present optical characteristics that may make them well-suited for many biological spectral imaging applications. An array of tunable thin-film filters was implemented on an inverted fluorescence microscope (TE 2000, Nikon Instruments) to cover the full visible wavelength range. Images of a previously published model, GFP-expressing endothelial cells in the lung, were acquired using a charge-coupled device camera (Rolera EM-C2, Q-Imaging). This model sample presents fluorescently-labeled cells in a highly autofluorescent environment. Linear unmixing of hyperspectral images indicates that thin-film tunable filters provide equivalent spectral discrimination to our previous acousto-optic tunable filter-based approach, with increased signal-to-noise characteristics. Hence, tunable multi-layered thin film optical filters may provide greatly improved spectral filtering characteristics and therefore enable wider acceptance of hyperspectral widefield microscopy.