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Dive into the research topics where Joe T. Sharick is active.

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Featured researches published by Joe T. Sharick.


Nature Medicine | 2018

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

Michael L. Schulte; Allie Fu; Ping Zhao; Jun Li; Ling Geng; Shannon T Smith; Jumpei Kondo; Robert J. Coffey; Marc O. Johnson; Jeffrey C. Rathmell; Joe T. Sharick; Melissa C. Skala; Jarrod A. Smith; Jordan Berlin; M. Kay Washington; Michael L. Nickels; H. Charles Manning

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.


Biomedical Optics Express | 2016

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

Alex J. Walsh; Joe T. Sharick; Melissa C. Skala; Hope T. Beier

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.


Scientific Reports | 2018

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

Joe T. Sharick; Peter F. Favreau; Amani A. Gillette; Sophia M. Sdao; Matthew J. Merrins; Melissa C. Skala

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.


Archive | 2015

Fluorescence Lifetime Measurements of NAD(P)H in Live Cells and Tissue

Alex J. Walsh; Amy T. Shah; Joe T. Sharick; Melissa C. Skala

Autofluorescence intensity and lifetime imaging of NAD(P)H yields quantitative, non-invasive measurements of cellular metabolism. NAD(P)H is a coenzyme involved in cellular metabolism processes including glycolysis and oxidative phosphorylation. The NAD(P)H fluorescence lifetime includes a short and long lifetime component due to the two possible physiological conditions of NAD(P)H, free or protein-bound (to an enzyme and/or substrate). Fluorescence lifetimes of NAD(P)H have been imaged in cells, ex vivo tissues, and in vivo tissues to investigate cellular metabolism at basal conditions and with perturbations. In particular, NAD(P)H fluorescence lifetimes are altered in pre-malignant and malignant cells and tissues compared with non-malignant cells and tissues across several cancers including head and neck cancers, breast cancer, and skin cancer. Additionally, NAD(P)H fluorescence lifetimes decrease in cancer cells and tumors following drug treatment and therefore, these metabolic endpoints show potential for drug monitoring and screening.


Proceedings of SPIE | 2016

Optical metabolic imaging for monitoring tracheal health

Joe T. Sharick; Daniel A. Gil; Michael A. Choma; Melissa C. Skala

The health of the tracheal mucosa and submucosa is a vital yet poorly understood component of critical care medicine, and a minimally-invasive method is needed to monitor tracheal health in patients. Of particular interest are the ciliated cells of the tracheal epithelium that move mucus away from the lungs and prevent respiratory infection. Optical metabolic imaging (OMI) allows cellular-level measurement of metabolism, and is a compelling method for assessing tracheal health because ciliary motor proteins require ATP to function. In this pilot study, we apply multiphoton imaging of the fluorescence intensities and lifetimes of metabolic co-enzymes NAD(P)H and FAD to the mucosa and submucosa of ex vivo mouse trachea. We demonstrate the feasibility and potential diagnostic utility of these measurements for assessing tracheal health and pathophysiology at the single-cell level.


Endoscopic Microscopy XIII | 2018

Optical coherence tomography and autofluorescence microscopy of respiratory ciliated epithelia (Conference Presentation)

Daniel A. Gil; Joe T. Sharick; Ute A. Gamm; Michael A. Choma; Melissa C. Skala

Efficient mucociliary clearance is necessary to protect the respiratory tract from infection. Mucociliary dysfunction is common in respiratory diseases including asthma, chronic obstructive pulmonary disease, and cystic fibrosis. Rescuing mucociliary clearance by stimulating the metabolism of respiratory ciliated epithelia could offer new treatments for respiratory diseases. However, the coupling between cellular metabolism and mechanical output in respiratory ciliated epithelia is poorly understood. We propose to study this coupling with autofluorescence microscopy and optical coherence tomography (OCT), to measure cellular metabolism and ciliary motility, respectively. The autofluorescent metabolic co-enzymes NAD(P)H and FAD provide non-invasive measures of metabolism through the optical redox ratio (NAD(P)H intensity divided by FAD intensity), while OCT measures both the frequency of ciliary beating and cilia-driven fluid flow. Preliminary experiments were performed in ex vivo mouse trachea using an epifluorescence microscope and a spectral-domain OCT system. Cilia-driven fluid flow was quantified using 2D particle tracking velocimetry (PTV-OCT) and TrackMate, a particle-tracking tool. PTV-OCT was validated by manual particle tracking (within 4% agreement) and a calibrated flow phantom (r=0.998, p<0.001). Treatment of the trachea with cyanide, a complex IV inhibitor that reduces intracellular ATP levels, demonstrated that an increase in optical redox ratio (p<0.001) reflects a decrease in cilia-driven flow (p<0.05). Additional studies using human samples are underway to explore how pathologically altered metabolism affects ciliary motility. This optical imaging approach could provide a better understanding of respiratory disease pathogenesis, and new therapeutic targets. In the future, these technologies could also monitor intensive care patients through an endoscope.


Proceedings of SPIE | 2017

Functional optical imaging of tracheal health (Conference Presentation)

Daniel A. Gil; Joe T. Sharick; Ute A. Gamm; Michael A. Choma; Melissa C. Skala

The health of the tracheal mucosa is an important, but poorly understood, aspect of critical care medicine. Many critical care patients are mechanically ventilated through an endotracheal tube that can cause local inflammation and blunt damage to the ciliated epithelial cells lining the trachea. These cilia clear mucus and infectious agents from the respiratory tract, so impaired ciliary function may lead to increased susceptibility to respiratory infection. Therefore, a minimally-invasive method to monitor mucosal health and ciliary function in intubated patients would be valuable to critical care medicine. Optical metabolic imaging (OMI) can quantitatively assess the metabolic state of cells by measuring the fluorescence intensities of endogenous metabolic co-enzymes NAD(P)H and FAD. OMI is especially attractive for assessing tracheal health because OMI is label-free, and ciliary function is tightly linked to the levels of NAD(P)H and FAD. In this study, we apply widefield OMI to ex vivo mouse tracheae (n=6), and demonstrate that the optical redox ratio (fluorescence intensity of NAD(P)H divided by the intensity of FAD) is sensitive to changes in the cellular metabolism of the tracheal mucosa. We observed a 46% increase in the redox ratio 20 minutes after treatment with 10mM of sodium cyanide (p<0.001, 95% CI [40%, 52%]), an inhibitor of oxidative cellular respiration. In addition to being a proof-of-concept demonstration, Pseudomonas aeruginosa, an important cause of morbidity and mortality in CF patients and in the ICU, produces hydrogen cyanide. Our results support the development of minimally-invasive fiber-optic probes for in vivo monitoring of tracheal health.


Proceedings of SPIE | 2017

Optical metabolic imaging measures early drug response in an allograft murine breast cancer model (Conference Presentation)

Joe T. Sharick; Rebecca S. Cook; Melissa C. Skala

Previous work has shown that cellular-level Optical Metabolic Imaging (OMI) of organoids derived from human breast cancer cell-line xenografts accurately and rapidly predicts in vivo response to therapy. To validate OMI as a predictive measure of treatment response in an immune-competent model, we used the polyomavirus middle-T (PyVmT) transgenic mouse breast cancer model. The PyVmT model includes intra-tumoral heterogeneity and a complex tumor microenvironment that can influence treatment responses. Three-dimensional organoids generated from primary PyVmT tumor tissue were treated with a chemotherapy (paclitaxel) and a PI3K inhibitor (XL147), each alone or in combination. Cellular subpopulations of response were measured using the OMI Index, a composite endpoint of metabolic response comprised of the optical redox ratio (ratio of the fluorescence intensities of metabolic co-enzymes NAD(P)H to FAD) as well as the fluorescence lifetimes of NAD(P)H and FAD. Combination treatment significantly decreased the OMI Index of PyVmT tumor organoids (p<0.0001) and in vivo tumors (p<0.0001) versus controls. Subpopulation analyses revealed a homogeneous response to combined therapy in both cultured organoids and in vivo tumors, while single agent treatment with XL147 alone or paclitaxel alone elicited heterogeneous responses in organoids. Tumor volume decreased with combination treatment through treatment day 30. These results indicate that OMI of organoids generated from PyVmT tumors can accurately reflect drug response in heterogeneous allografts with both innate and adaptive immunity. Thus, this method is promising for use in humans to predict long-term treatment responses accurately and rapidly, and could aid in clinical treatment planning.


Cancer Research | 2016

Abstract 4241: Predicting clinical response in breast cancer using cellular-resolution optical metabolic imaging

Joe T. Sharick; Alex J. Walsh; Melinda E. Sanders; Ingrid M. Meszoely; Mary A. Hooks; Mark C. Kelley; Melissa C. Skala

While over 50 drugs have been approved by the FDA to treat breast cancer, there are no reliable methods for optimizing treatment regimens for individual patients. Currently, oncologists choose drug treatments based on expression levels of tumor cell signaling receptors (i.e. HER2, ER) and assess whether the treatment is effective after weeks or months of precious time have passed. Unfortunately, over one third of patients exhibit resistance to their initial treatment. The toxic side effects and morbidities resulting from suboptimal drug regimens could be eradicated by applying a personalized medicine approach to breast cancer treatment. This approach would allow clinicians to determine the optimal treatment plan for individual patients early on, at the time of diagnosis. While current methods track therapy response via changes in tumor size (i.e. MRI, mammography, ultrasound), changes in cell metabolism precede changes in tumor size and thus present an earlier marker of treatment response. Optical metabolic imaging (OMI) is sensitive to these early changes in metabolism by exploiting the intrinsic fluorescent properties of NAD(P)H and FAD, coenzymes of metabolic reactions. OMI endpoints include the optical redox ratio (the fluorescence intensity of NAD(P)H divided by the fluorescence intensity of FAD), as well as the fluorescence lifetimes of NAD(P)H and FAD. The redox ratio reflects the cellular redox state, and the fluorescence lifetimes of NAD(P)H and FAD report on the binding activity of these coenzymes. Additionally, OMI has the unique ability to measure these endpoints in individual cells, which allows for the detection of heterogeneous subpopulations of responsive or resistant cells within a tumor. OMI also allows for high-throughput screening of potential cancer drugs and drug combinations on patient biopsy samples cultured ex vivo. These samples are grown as “organoids” in a 3D matrix that mimics the natural tumor environment. We have demonstrated that OMI accurately predicts treatment response in organoids derived from breast cancer xenografts compared with gold standard tumor growth curves in vivo. We have also shown that OMI can measure drug response and detect heterogeneous cell populations in organoids derived from triple negative, ER+, and HER2+ human breast tumors. The ability of OMI to predict treatment response has also been demonstrated in the polyoma middle-T mouse model of breast cancer, which exhibits more cellular heterogeneity than cell line xenografts and also incorporates the influence of the immune system on cancer drug response. Preliminary data shows that OMI of organoids generated from biopsies of newly diagnosed breast cancer patients can accurately predict how the patient clinically responds to neoadjuvant treatment. This methodology could allow oncologists to determine the ideal treatment regimen for their patients at the time of diagnosis. Citation Format: Joe T. Sharick, Alex J. Walsh, Melinda E. Sanders, Ingrid Meszoely, Mary A. Hooks, Mark C. Kelley, Melissa C. Skala. Predicting clinical response in breast cancer using cellular-resolution optical metabolic imaging. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 4241.


Multiphoton Microscopy in the Biomedical Sciences XVIII | 2018

Single-cell metabolism predicts drug response in patient-derived pancreatic cancer organoids (Conference Presentation)

Alexander A. Parikh; Cheri A. Pasch; Dustin A. Deming; Joe T. Sharick; Melissa C. Skala; Jillian K. Johnson; Lingjun Li

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Melissa C. Skala

University of Wisconsin-Madison

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Alex J. Walsh

Air Force Research Laboratory

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Cheri A. Pasch

University of Wisconsin-Madison

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Dustin A. Deming

University of Wisconsin-Madison

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Lingjun Li

University of Wisconsin-Madison

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