Biology subjects

Deming, D. A.

Publications and source records attributed to Deming, D. A..

8 recordsLinked to original sources

bioRxiv2026

Provisional extracellular matrix signaling network regulates tumor lymphoneogenesis and response to immunotherapy

Tertiary lymphoid structures (TLS) predict response to checkpoint inhibition, and conventional dendritic cells (cDC) are required to build and maintain them. What renders a niche permissive for their assembly is unknown: chemokines recruit the cellular constituents but do not specify how they organize. Here we show that the organizing signal is a matrix fragment. Proteolysis of the proteoglycan versican (VCAN) releases the matrikine versikine, constitutively in germinal center light zones and inducibly in tumor stroma. Versikine activates CD11b+ cDC and expands cDC1 to assemble TLS-archetypal triads, apposed DC: CD4+ T: CD8+ T units. Versikine-conditioned DC engage progenitor-exhausted CD8+ T cells (Tpex) and Th1-polarized follicular helper CD4+ T cells. Excess unproteolyzed VCAN inverts this toward DC-Treg crosstalk and Tpex loss. Versikine supplied as mRNA or recombinant protein sensitizes refractory tumors to PD-L1 blockade. VCAN proteolysis prospectively predicted outcomes after PD-1 blockade in metastatic colorectal cancer. Matrikines organize chemokine-recruited cells into functional immune niches.

immunology↗

bioRxiv2025

An automated image analysis pipeline for wide-field optical redox imaging of patient-derived cancer organoids

Wide-field optical redox imaging provides a fast and accessible method to monitor metabolic changes in cells and has recently been developed for drug screening in patient-derived cancer organoids (PDCOs). However, manual analysis of wide-field optical redox images is inefficient and laborious for large-scale drug screens. Here, we developed an automated pipeline for PDCO segmentation, single-PDCO tracking, and background correction in autofluorescence images. This pipeline was tested on two imaging systems over a 3-day time-course with two drug doses to demonstrate generalizability across imaging systems. Segmentation was performed using a fine-tuned Cellpose model, which when compared to manual masks, achieved mean Dice scores >0.8 across systems, indicating high reproducibility. Automated single-PDCO tracking was compared to manual tracking and the accuracy of the tracking algorithm exceeded 94% by two metrics, recall and Jaccard index. For background correction, the automated pipeline uses the full field-of-view to reduce sampling bias. Compared to the manual analysis pipeline, the automated pipeline resolves single-PDCO responses with comparable sensitivity to drug treatment but with over 127x faster processing time. This novel automated image analysis pipeline improves throughput and robustness in PDCO image analysis, which increases the accessibility and scalability of wide-field optical redox imaging for PDCO drug screening.

bioengineering↗

bioRxiv2024

Wide-field optical redox imaging with leading-edge detection for assessment of patient-derived cancer organoids

Patient-derived cancer organoids (PDCOs) are a valuable model to recapitulate human disease in culture with important implications for drug development. However, current methods for assessing PDCOs are limited. Label-free imaging methods are a promising tool to measure organoid level heterogeneity and rapidly screen drug response in PDCOs. The aim of this study was to assess and predict PDCO response to treatments based on mutational profiles using label-free wide-field optical redox imaging (WF ORI). WF ORI provides organoid-level measurements of treatment response without labels or additional reagents by measuring the autofluorescence intensity of the metabolic co-enzymes NAD(P)H and FAD. The optical redox ratio is defined as the fluorescence intensity of [NAD(P)H / NAD(P)H +FAD] which measures the oxidation-reduction state of PDCOs. We have implemented WF ORI and developed novel leading-edge analysis tools to maximize the sensitivity and reproducibility of treatment response measurements in colorectal PDCOs. Leading-edge analysis improves sensitivity to redox changes in treated PDCOs (G{Delta} = 1.462 vs G{Delta} = 1.233). Additionally, WF ORI resolves FOLFOX treatment effects across all PDCOs better than two-photon ORI, with [~]7X increase in effect size (G{Delta} = 1.462 vs G{Delta} = 0.189). WF ORI distinguishes metabolic differences based on driver mutations in CRC PDCOs identifying KRAS+PIK3CA double mutant PDCOs vs wildtype PDCOs with 80% accuracy and can identify treatment resistant mutations in mixed PDCO cultures (G{Delta} = 1.39). Overall, WF ORI enables rapid, sensitive, and reproducible measurements of treatment response and heterogeneity in colorectal PDCOs that will impact patient management, clinical trials, and preclinical drug development. Statement of SignificanceLabel-free wide-field optical redox imaging of patient-derived cancer organoids enables rapid, sensitive, and reproducible measurements of treatment response and heterogeneity that will impact patient management, clinical trials, and preclinical drug development.

bioengineering↗

bioRxiv2024

Cellpose as a reliable method for single-cell segmentation of autofluorescence microscopy images

Autofluorescence microscopy uses intrinsic sources of molecular contrast to provide cellular-level information without extrinsic labels. However, traditional cell segmentation tools are often optimized for high signal-to-noise ratio (SNR) images, such as fluorescently labeled cells, and unsurprisingly perform poorly on low SNR autofluorescence images. Therefore, new cell segmentation tools are needed for autofluorescence microscopy. Cellpose is a deep learning network that is generalizable across diverse cell microscopy images and automatically segments single cells to improve throughput and reduce inter-human biases. This study aims to validate Cellpose for autofluorescence imaging, specifically from multiphoton intensity images of NAD(P)H. Manually segmented nuclear masks of NAD(P)H images were used to train new Cellpose models. These models were applied to PANC-1 cells treated with metabolic inhibitors and patient-derived cancer organoids (across 9 patients) treated with chemotherapies. These datasets include co-registered fluorescence lifetime imaging microscopy (FLIM) of NAD(P)H and FAD, so fluorescence decay parameters and the optical redox ratio (ORR) were compared between masks generated by the new Cellpose model and manual segmentation. The Dice score between repeated manually segmented masks was significantly lower than that of repeated Cellpose masks (p<0.0001) indicating greater reproducibility between Cellpose masks. There was also a high correlation (R2>0.9) between Cellpose and manually segmented masks for the ORR, mean NAD(P)H lifetime, and mean FAD lifetime across 2D and 3D cell culture treatment conditions. Masks generated from Cellpose and manual segmentation also maintain similar means, variances, and effect sizes between treatments for the ORR and FLIM parameters. Overall, Cellpose provides a fast, reliable, reproducible, and accurate method to segment single cells in autofluorescence microscopy images such that functional changes in cells are accurately captured in both 2D and 3D culture.

bioengineering↗

bioRxiv2021

Stromal remodeling regulates dendritic cell abundance and activity in the tumor microenvironment

Stimulatory dendritic cells (SDC), enriched within Batf3-DC (cDC1), engage in productive interactions with CD8+ effectors along tumor-stroma boundaries. The paradoxical accumulation of "poised" cross-presenting Batf3-DC within stromal sheets, distal to tumoral nests, is unlikely to simply reflect passive exclusion away from immunosuppressive tumor cores. Drawing parallels with embryonic morphogenesis, we hypothesized that invasive margin stromal remodeling may generate developmentally conserved cell-fate cues that regulate Batf3-DC behavior. We find that CD8+ T-cells massively infiltrate tumor matrices undergoing proteoglycan versican (VCAN) proteolysis, an essential organ-sculpting modification in development and adult tissue-plane forging. VCAN proteolysis releases a bioactive fragment (matrikine), versikine, that is necessary and sufficient for Batf3-DC accumulation. Versikine does not influence tumor-seeding pre-DC differentiation; rather, it orchestrates a distinctive activation program conferring exquisite sensitivity to DNA-sensing, coupled with survival support from atypical innate lymphoid cells. Thus, homeostatic signals from stroma invasion regulate SDC survival and activity to promote T- cell inflammation. HIGHLIGHTSO_LITumor stroma remodeling generates cross-presenting DC survival and activation cues. C_LIO_LIStromal-activated Batf3-DC are hypersensitive to dsDNA-sensing. C_LIO_LIStromal signals promote atypical innate lymphoid cells (GM-CSFhi/ IFN{gamma}lo). C_LIO_LIT-cell repriming by stroma-licensed Batf3-DC may overcome exclusion at tumor margins. C_LI

immunology↗

bioRxiv2021

Integrating Subclonal Response Heterogeneity to Define Cancer Organoid Therapeutic Sensitivity

Tumor heterogeneity is predicted to confer inferior clinical outcomes, however modeling heterogeneity in a manner that still represents the tumor of origin remains a formidable challenge. Sequencing technologies are limited in their ability to identify rare subclonal populations and predict response to the multitude of available treatments for patients. Patient-derived organotypic cultures have significantly improved the modeling of cancer biology by faithfully representing the molecular features of primary malignant tissues. Patient-derived cancer organoid (PCO) cultures contain numerous individual organoids with the potential to recapitulate heterogeneity, though PCOs are most commonly studied in bulk ignoring any diversity in the molecular profile or treatment response. Here we demonstrate the advantage of evaluating individual PCOs in conjunction with cellular level optical metabolic imaging to characterize the largely ignored heterogeneity within these cultures to predict clinical therapeutic response, identify subclonal populations, and determine patient specific mechanisms of resistance.

cancer biology↗

bioRxiv2021

Impact of baseline culture conditions of mouse-derived cancer organoids when determining therapeutic response and tumor heterogeneity

Representative models are needed to screen new therapies for patients with cancer. Cancer organoids are a leap forward as a culture model that faithfully represents the disease. Mouse-derived cancer organoids (MDCOs) are becoming increasingly popular, however there has yet to be a standardized method to assess therapeutic response and identify subpopulation heterogeneity. There are multiple factors unique to organoid culture that could affect how therapeutic response and MDCO heterogeneity are assessed. Here we describe an analysis of nearly 3,500 individual MDCOs where individual organoid morphologic tracking was performed. Change in MDCO diameter was assessed in the presence of control media or targeted therapies. Individual organoid tracking was identified to be more sensitive to treatment response than well-level assessment. The impact of different generations of mice of the same genotype, different regions of the colon, and organoid specific characteristics including baseline size, passage number, plating density, and location within the matrix were examined. Only the starting size of the MDCO altered the subsequent growth. Here we establish organoid culture parameters for individual organoid morphologic tracking to determine therapeutic response and growth/response heterogeneity for translational studies using murine colorectal cancer organoids.

cancer biology↗

bioRxiv2019

Optical Metabolic Imaging of Heterogeneous Drug Response in Pancreatic Cancer Patient Organoids

New tools are needed to match pancreatic 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 cannot be completed in a clinically relevant time frame, only evaluate response at one time point, and most importantly, overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response. Organoids were generated from fresh patient tissue samples acquired during surgery and treated with the same drugs as the patient's prescribed adjuvant treatment. OMI measurements of heterogeneity in response to this treatment were compared to later patient response, specifically to the time to recurrence following surgery. OMI was sensitive to patient-specific treatment response in as little as 24 hours. 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 pancreatic cancer patients, and to develop new effective therapies that address cellular heterogeneity in pancreatic cancer.

bioengineering↗