Biology subjects

Harrington, D.

Publications and source records attributed to Harrington, D..

3 recordsLinked to original sources

bioRxiv2026

Assessing Bioactivity and Biointegration of Engineered Salivary Tissue Constructs in a Preclinical Unilateral Fractionated Irradiated Rat Model

Human salivary stem/progenitor cell (hS/PC)-loaded hyaluronic acid (HA)-based hydrogels, termed 3D-salivary tissue constructs (3D-ST), hold great promise for restoring salivary gland function post-radiation injury. Here, we developed a next-generation 3D-ST using heparin-modified HA and bioactive peptide-modified hydrogels. This new formulation enables controlled pre-loading and localized presentation of heparin-binding growth factors prior to surgical implantation, providing opportunities to enhance in vivo hS/PC bioactivity. To model clinically relevant radiation injury, we established an athymic rat model subjected to computed tomography (CT)-guided fractionated radiation, resulting in hallmark features of radiation-induced salivary dysfunction. Over 60-days post-irradiation, glands exhibited progressive loss of acini, increased fibrosis, and disruption of endothelial, neuronal, and myoepithelial compartments. Within this injured environment, a surgical pocket was created to precisely implant 3D-STs to assess graft performance. Fluorescent labeling of the 3D-STs enabled longitudinal tracking post-implantation. Over 14 days, implanted 3D-STs remained structurally stable within irradiated glands, and hS/PCs remained viable without evidence of local inflammatory responses. Compared to non-injured glands, the irradiated microenvironment suppressed hS/PC proliferation and phenotype, indicating alterations in the irradiated local tissue negatively impact hS/PC bioactivity. In addition, host neurovascular migration into the 3D-ST was majorly restricted in irradiated glands, providing new opportunities to enhance biointegration. Overall, this work establishes a reproducible preclinical framework for assessing hydrogel biocompatibility and stability, cell bioactivity, and host-graft biointegration prior to scale up into preclinical large animal models. This study has successfully established a tractable approach for improving 3D-ST formulations to enhance hS/PC expansion, differentiation, and biointegration following implantation into radiation-injured beds.

bioengineering↗

bioRxiv2026

3D Droplet-Based Bioprinting of Customized In Vitro Head and Neck Cancer Tumor Microenvironment Models

In vitro models are increasingly critical for interrogating cancer biology and therapeutic response, however, accurately recapitulating the tumor microenvironment (TME) remains a persistent challenge, particularly in head and neck cancers (HNC) characterized by complex cell-matrix interactions and heterogeneity. Current models often lack independent tunability of biochemical and biophysical cues, limiting systematic investigation of microenvironmental cues in a high-throughput format. Here, we establish a 3D droplet-based bioprinting platform for the fabrication of customizable in vitro TME models using poly(ethylene glycol) (PEG) hydrogels. Human HNC cell lines (FaDu and 2A3) with differing HPV statuses were bioprinted into PEG matrices spanning physiologically relevant stiffnesses (0.7-4.8 kPa) and compositions, including non-functionalized PEG and peptide-functionalized PEG (PEGfnc: RGD, YIGSR, CNYYSNS) and cultured for 7 days. Cluster growth, cell viability, and cluster morphology were assessed across multiple time points, matrix compositions, and matrix stiffnesses. Proliferation and endpoint phenotype expression were visualized using confocal microscopy through immunofluorescence. Results indicated enhanced cell viability in PEGfnc matrices, compared to non-functionalized matrices, while effect of matrix stiffness was less prominent. Median cluster size reached 40-50 m by day 7, and linear mixed-effects modeling identified how changes in cluster surface area, volume, and tumoroid complexity varied with cell type, matrix, and stiffness. By decoupling and systematically varying key TME parameters, this approach provides a robust and scalable framework for dissecting tumor-matrix interactions and advancing physiologically relevant in vitro models for cancer research and therapeutic screening.

bioengineering↗

bioRxiv2018

The impact of stroma on the discovery of molecular subtypes and prognostic gene signatures in serous ovarian cancer

PurposeRecent efforts to improve outcomes for high-grade serous ovarian cancer, a leading cause of cancer death in women, have focused on identifying molecular subtypes and prognostic gene signatures, but existing subtypes have poor cross-study robustness. We tested the contribution of cell admixture in published ovarian cancer molecular subtypes and prognostic gene signatures.\n\nExperimental DesignPublic gene expression data, two molecular subtype classifications, and 61 published gene signatures of ovarian cancer were examined. Using microdissected data, we developed gene signatures of ovarian tumor and stroma. Computational simulations of increasing stromal cell proportion were performed by mixing gene expression profiles of paired microdissected ovarian tumor and stroma.\n\nResultsEstablished ovarian cancer molecular subtypes are strongly associated with the cell admixture. Tumors were classified as different molecular subtypes in simulations, when the percentage of stromal cells increased. Stromal gene expression in bulk tumor was weakly prognostic, and in one dataset, increased stroma was associated with anatomic sampling location. Five published prognostic gene signatures were no longer prognostic in a multivariate model that adjusted for stromal content alone.\n\nConclusionsThe discovery that molecular subtypes of high grade serous ovarian cancer is influenced by cell admixture, and stromal cell gene expression is crucial for interpretation and reproduction of ovarian cancer molecular subtypes and gene signatures derived from bulk tissue. Single cell analysis may be required to refine the molecular subtypes of high grade serous ovarian cancer. Because stroma proportion was weakly prognostic, elucidating the role of the tumor microenvironments components will be important.\n\nTranslational relevanceOvarian cancer is a leading cause of cancer death in women in the United States. Although the tumor responds to standard therapy for the majority of patients, it frequently recurs and becomes drug-resistant. Recent efforts have focused on identifying molecular subtypes and prognostic gene signatures of ovarian cancer in order to tailor therapy and improve outcomes. This study demonstrates that molecular subtype identification depends on the ratio of tumor to stroma within the specimen. We show that the specific anatomic location of the biopsy may influence the proportion of stromal involvement and potentially the resulting gene expression pattern. It will be crucial for these factors to be taken into consideration when interpreting and reproducing ovarian cancer molecular subtypes and gene signatures derived using bulk tissue and single cells. Furthermore, it will be important to define the relative proportions of stromal cells and model their prognostic importance in the tumor microenvironment.

bioinformatics↗