Click chemistry functionalization of self-assembling peptide hydrogels.

Self-assembling peptide (SAP) hydrogels provide a fibrous microenvironment to cells while also giving users control of biochemical and mechanical cues. Previously, biochemical cues were introduced by physically mixing them with SAPs prior to hydrogel assembly, or by incorporating them into the SAP sequence during peptide synthesis, which limited flexibility and increased costs. To circumvent these limitations, we developed "Click SAPs," a novel formulation that can be easily functionalized via click chemistry thiol-ene reaction. Due to its high cytocompatibility, the thiol-ene click reaction is currently used to crosslink and functionalize other types of polymeric hydrogels. In this study, we developed a click chemistry compatible SAP platform by addition of a modified lysine (lysine-alloc) to the SAP sequence, enabling effective coupling of thiol-containing molecules to the SAP hydrogel network. We demonstrate the flexibility of this approach by incorporating a fluorescent dye, a cellular adhesion peptide, and a matrix metalloproteinase-sensitive biosensor using the thiol-ene reaction in 3D Click SAPs. Using atomic force microscopy, we demonstrate that Click SAPs retain the ability to self-assemble into fibers, similar to previous systems. Additionally, a range of physiologically relevant stiffnesses can be achieved by adjusting SAP concentration. Encapsulated cells maintain high viability in Click SAPs and can interact with adhesion peptides and a matrix metalloproteinase biosensor, demonstrating that incorporated molecules retain their biological activity. The Click SAP platform supports easier functionalization with a wider array of bioactive molecules and enables new investigations with temporal and spatial control of the cellular microenvironment.

A miniaturized screening platform to identify novel regulators of extracellular matrix alignment.

Extracellular matrix alignment contributes to metastasis in a number of cancers and is a known prognostic stromal factor; however, the mechanisms controlling matrix organization remain unclear. Cancer-associated fibroblasts (CAF) play a critical role in this process, particularly via matrix production and modulation of key signaling pathways controlling cell adhesion and contractility. Stroma normalization, as opposed to elimination, is a highly sought strategy, and screening for drugs that effectively alter extracellular matrix (ECM) alignment is a practical way to identify novel CAF-normalizing targets that modulate ECM organization. To meet this need, we developed a novel high-throughput screening platform in which fibroblast-derived matrices were produced in 384-well plates, imaged with automated confocal microscopy, and analyzed using a customized MATLAB script. This platform is a technical advance because it miniaturizes the assay, eliminates costly and time-consuming experimental steps, and streamlines data acquisition and analysis to enable high-throughput screening applications. As a proof of concept, this platform was used to screen a kinase inhibitor library to identify modulators of matrix alignment. A number of novel potential regulators were identified, including several receptor tyrosine kinases (c-MET, tropomyosin receptor kinase 1 (NTRK1), HER2/ERBB2) and the serine/threonine kinases protein kinase A, C, and G (PKA, PKC, and PKG). The expression of these regulators was analyzed in publicly available patient datasets to examine the association between stromal gene expression and patient outcomes.

Pten regulates collagen fibrillogenesis by fibroblasts through SPARC.

Collagen deposition contributes to both high mammographic density and breast cancer progression. Low stromal PTEN expression has been observed in as many as half of breast tumors and is associated with increases in collagen deposition, however the mechanism connecting PTEN loss to increased collagen deposition remains unclear. Here, we demonstrate that Pten knockout in fibroblasts using an Fsp-Cre;PtenloxP/loxP mouse model increases collagen fiber number and fiber size within the mammary gland. Pten knockout additionally upregulated Sparc transcription in fibroblasts and promoted collagen shuttling out of the cell. Interestingly, SPARC mRNA expression was observed to be significantly elevated in the tumor stroma as compared to the normal breast in several patient cohorts. While SPARC knockdown via shRNA did not affect collagen shuttling, it notably decreased assembly of exogenous collagen. In addition, SPARC knockdown decreased fibronectin assembly and alignment of the extracellular matrix in an in vitro fibroblast-derived matrix model. Overall, these data indicate upregulation of SPARC is a mechanism by which PTEN regulates collagen deposition in the mammary gland stroma.

Sample preparation strategies for high-throughput mass spectrometry imaging of primary tumor organoids.

Patient-derived 3D organoids show great promise for understanding patient heterogeneity and chemotherapy response in human-derived tissue. The combination of organoid culture techniques with mass spectrometry imaging provides a label-free methodology for characterizing drug penetration, patient-specific response, and drug biotransformation. However, current methods used to grow tumor organoids employ extracellular matrices that can produce small molecule background signal during mass spectrometry imaging analysis. Here, we develop a method to isolate 3D human tumor organoids out of a Matrigel extracellular matrix into gelatin mass spectrometry compatible microarrays for high-throughput mass spectrometry imaging analysis. The alignment of multiple organoids in the same z-axis is essential for sectioning organoids together and for maintaining reproducible sample preparation on a single glass slide for up to hundreds of organoids. This method successfully removes organoids from extracellular matrix interference and provides an organized array for high-throughput imaging analysis to easily identify organoids by eye for area selection and further analysis. With this method, mass spectrometry imaging can be readily applied to organoid systems for preclinical drug development and personalized medicine research initiatives.

Fluorescence lifetime imaging microscopy: fundamentals and advances in instrumentation, analysis, and applications.

SIGNIFICANCE: Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique to distinguish the unique molecular environment of fluorophores. FLIM measures the time a fluorophore remains in an excited state before emitting a photon, and detects molecular variations of fluorophores that are not apparent with spectral techniques alone. FLIM is sensitive to multiple biomedical processes including disease progression and drug efficacy. AIM: We provide an overview of FLIM principles, instrumentation, and analysis while highlighting the latest developments and biological applications. APPROACH: This review covers FLIM principles and theory, including advantages over intensity-based fluorescence measurements. Fundamentals of FLIM instrumentation in time- and frequency-domains are summarized, along with recent developments. Image segmentation and analysis strategies that quantify spatial and molecular features of cellular heterogeneity are reviewed. Finally, representative applications are provided including high-resolution FLIM of cell- and organelle-level molecular changes, use of exogenous and endogenous fluorophores, and imaging protein-protein interactions with Förster resonance energy transfer (FRET). Advantages and limitations of FLIM are also discussed. CONCLUSIONS: FLIM is advantageous for probing molecular environments of fluorophores to inform on fluorophore behavior that cannot be elucidated with intensity measurements alone. Development of FLIM technologies, analysis, and applications will further advance biological research and clinical assessments.

MEK activation modulates glycolysis and supports suppressive myeloid cells in TNBC.

Triple-negative breast cancers (TNBCs) are heterogeneous and aggressive, with high mortality rates. TNBCs frequently respond to chemotherapy, yet many patients develop chemoresistance. The molecular basis and roles for tumor cell-stromal crosstalk in establishing chemoresistance are complex and largely unclear. Here we report molecular studies of paired TNBC patient-derived xenografts (PDXs) established before and after the development of chemoresistance. Interestingly, the chemoresistant model acquired a distinct KRASQ61R mutation that activates K-Ras. The chemoresistant KRAS-mutant model showed gene expression and proteomic changes indicative of altered tumor cell metabolism. Specifically, KRAS-mutant PDXs exhibited increased redox ratios and decreased activation of AMPK, a protein involved in responding to metabolic homeostasis. Additionally, the chemoresistant model exhibited increased immunosuppression, including expression of CXCL1 and CXCL2, cytokines responsible for recruiting immunosuppressive leukocytes to tumors. Notably, chemoresistant KRAS-mutant tumors harbored increased numbers of granulocytic myeloid-derived suppressor cells (gMDSCs). Interestingly, previously established Ras/MAPK-associated gene expression signatures correlated with myeloid/neutrophil-recruiting CXCL1/2 expression and negatively with T cell-recruiting chemokines (CXCL9/10/11) across patients with TNBC, even in the absence of KRAS mutations. MEK inhibition induced tumor suppression in mice while reversing metabolic and immunosuppressive phenotypes, including chemokine production and gMDSC tumor recruitment in the chemoresistant KRAS-mutant tumors. These results suggest that Ras/MAPK pathway inhibitors may be effective in some breast cancer patients to reverse Ras/MAPK-driven tumor metabolism and immunosuppression, particularly in the setting of chemoresistance.

Metabolic Heterogeneity in Patient Tumor-Derived Organoids by Primary Site and Drug Treatment.

New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer.

Redox imaging and optical coherence tomography of the respiratory ciliated epithelium.

Optical coherence tomography (OCT) is an emerging technology for in vivo airway and lung imaging. However, OCT lacks sensitivity to the metabolic changes caused by inflammation, which drives chronic respiratory diseases such as asthma and chronic obstructive pulmonary disorder. Redox imaging (RI) is a label-free technique that uses the autofluorescence of the metabolic coenzymes NAD(P)H and flavin adenine dinucleotide (FAD) to probe cellular metabolism and could provide complimentary information to OCT for airway and lung imaging. We demonstrate OCT and RI of respiratory ciliated epithelial function in ex vivo mouse tracheae. We applied RI to measure cellular metabolism via the redox ratio [intensity of NAD(P)H divided by FAD] and particle tracking velocimetry OCT to quantify cilia-driven fluid flow. To model mitochondrial dysfunction, a key aspect of the inflammatory process, cyanide was used to inhibit oxidative metabolism and reduce ciliary motility. Cyanide exposure over 20 min significantly increased the redox ratio and reversed cilia-driven fluid flow. We propose that RI provides complementary information to OCT to assess inflammation in the airway and lungs.

Cellular Metabolic Heterogeneity In Vivo Is Recapitulated in Tumor Organoids.

Heterogeneous populations within a tumor have varying metabolic profiles, which can muddle the interpretation of bulk tumor imaging studies of treatment response. Although methods to study tumor metabolism at the cellular level are emerging, these methods provide a single time point "snapshot" of tumor metabolism and require a significant time and animal burden while failing to capture the longitudinal metabolic response of a single tumor to treatment. Here, we investigated a novel method for longitudinal, single-cell tracking of metabolism across heterogeneous tumor cell populations using optical metabolic imaging (OMI), which measures autofluorescence of metabolic coenzymes as a report of metabolic activity. We also investigated whether in vivo cellular metabolic heterogeneity can be accurately captured using tumor-derived three-dimensional organoids in a genetically engineered mouse model of breast cancer. OMI measurements of response to paclitaxel and the phosphatidylinositol-3-kinase inhibitor XL147 in tumors and organoids taken at single cell resolution revealed parallel shifts in metaboltruic heterogeneity. Interestingly, these previously unappreciated heterogeneous metabolic responses in tumors and organoids could not be attributed to tumor cell fate or varying leukocyte content within the microenvironment, suggesting that heightened metabolic heterogeneity upon treatment is largely due to heterogeneous metabolic shifts within tumor cells. Together, these studies show that OMI revealed remarkable heterogeneity in response to treatment, which could provide a novel approach to predict the presence of potentially unresponsive tumor cell subpopulations lurking within a largely responsive bulk tumor population, which might otherwise be overlooked by traditional measurements.

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.

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.

Pharmacological blockade of ASCT2-dependent glutamine transport leads to antitumor efficacy in preclinical models.

The unique metabolic demands of cancer cells underscore potentially fruitful opportunities for drug discovery in the era of precision medicine. However, therapeutic targeting of cancer metabolism has led to surprisingly few new drugs to date. The neutral amino acid glutamine serves as a key intermediate in numerous metabolic processes leveraged by cancer cells, including biosynthesis, cell signaling, and oxidative protection. Herein we report the preclinical development of V-9302, a competitive small molecule antagonist of transmembrane glutamine flux that selectively and potently targets the amino acid transporter ASCT2. Pharmacological blockade of ASCT2 with V-9302 resulted in attenuated cancer cell growth and proliferation, increased cell death, and increased oxidative stress, which collectively contributed to antitumor responses in vitro and in vivo. This is the first study, to our knowledge, to demonstrate the utility of a pharmacological inhibitor of glutamine transport in oncology, representing a new class of targeted therapy and laying a framework for paradigm-shifting therapies targeting cancer cell metabolism.

Temporal binning of time-correlated single photon counting data improves exponential decay fits and imaging speed.

Time-correlated single photon counting (TCSPC) enables acquisition of fluorescence lifetime decays with high temporal resolution within the fluorescence decay. However, many thousands of photons per pixel are required for accurate lifetime decay curve representation, instrument response deconvolution, and lifetime estimation, particularly for two-component lifetimes. TCSPC imaging speed is inherently limited due to the single photon per laser pulse nature and low fluorescence event efficiencies (<10%) required to reduce bias towards short lifetimes. Here, simulated fluorescence lifetime decays are analyzed by SPCImage and SLIM Curve software to determine the limiting lifetime parameters and photon requirements of fluorescence lifetime decays that can be accurately fit. Data analysis techniques to improve fitting accuracy for low photon count data were evaluated. Temporal binning of the decays from 256 time bins to 42 time bins significantly (p<0.0001) improved fit accuracy in SPCImage and enabled accurate fits with low photon counts (as low as 700 photons/decay), a 6-fold reduction in required photons and therefore improvement in imaging speed. Additionally, reducing the number of free parameters in the fitting algorithm by fixing the lifetimes to known values significantly reduced the lifetime component error from 27.3% to 3.2% in SPCImage (p<0.0001) and from 50.6% to 4.2% in SLIM Curve (p<0.0001). Analysis of nicotinamide adenine dinucleotide-lactate dehydrogenase (NADH-LDH) solutions confirmed temporal binning of TCSPC data and a reduced number of free parameters improves exponential decay fit accuracy in SPCImage. Altogether, temporal binning (in SPCImage) and reduced free parameters are data analysis techniques that enable accurate lifetime estimation from low photon count data and enable TCSPC imaging speeds up to 6x and 300x faster, respectively, than traditional TCSPC analysis.