Biology subjects

Peyton, S. R.

Publications and source records attributed to Peyton, S. R..

6 recordsLinked to original sources

bioRxiv2026

In Vitro Detection of Breast Cancer Cell Types Using Machine Learning-Assisted Spectral Fingerprinting of SWCNTs

The early detection of breast cancer currently relies on expensive mammography, followed by pathology that uses biopsied, fixed, and immunohistochemically stained tissues. A live-cell detection approach could be highly beneficial as a supportive diagnostic and research tool to better understand and resolve the dynamic nature of breast cancer cells and their response to treatment in real time. Here, we present a single-walled carbon nanotube (SWCNT) near-infrared fluorescence spectral fingerprinting approach combined with machine learning to precisely detect the heterogeneity of breast cancer cells in live culture. We introduced DNA-functionalized SWCNTs to MCF-10A (a non-tumorigenic healthy control) and cancer cell lines spanning known extrinsic disease subtypes: MCF-7 (luminal A), HCC1954 (HER2+), MDA-MB-231, and MDA-MB-468 (both triple-negative). The NIR fluorescence spectra of DNA-SWCNTs across 600 individual cells within each type showed significant differences in emission peak intensities, center wavelengths, and peak intensity ratios, attributable to variations in cellular uptake and biomolecular interactions. These spectral changes likely arise from complex SWCNT-cellular interaction "fingerprint" that includes redox-mediated modulation of the local nanotube environment, rather than from a single biomarker response. The extracted spectral features were used to train an ensemble machine learning model. The model achieved 98% classification accuracy for breast cancer detection and 95% classification accuracy for breast cancer cell subtyping. Moreover, Raman microscopy further showed that MDA-MB-468 cells exhibited the highest SWCNT uptake, whereas MCF-10A cells showed greater SWCNT aggregation, consistent with their lower broadband NIR fluorescence intensity. These results demonstrate that SWCNT NIR fluorescence fingerprints can capture cell line-specific optical signatures. This platform provides a foundation for nanomaterial-enabled biosensing strategies aimed at real-time monitoring of cancer-associated cellular states.

bioengineering↗

bioRxiv2024

Acute and Chronic Neural and Glial Response to Mild Traumatic Brain Injury in the Hippocampus

Traumatic brain injury (TBI) is an established risk factor for developing neurodegenerative disease. However, how TBI leads from acute injury to chronic neurodegeneration is limited to post-mortem models. There is a lack of connections between in vitro and in vivo TBI models that can relate injury forces to both macroscale tissue damage and brain function at the cellular level. Needle-induced cavitation (NIC) is a technique that can produce small cavitation bubbles in soft tissues, which allows us to relate small strains and strain rates in living tissue to ensuing acute and chronic cell death, tissue damage, and tissue remodeling. Here, we applied NIC to mouse brain slices to create a new model of TBI with high spatial and temporal resolution. We specifically targeted the hippocampus, which is a brain region critical for learning and memory and an area in which injury causes cognitive pathologies in humans and rodent models. By combining NIC with patch-clamp electrophysiology, we demonstrate that NIC in the Cornu Ammonis (CA)3 region of the hippocampus dynamically alters synaptic release onto CA1 pyramidal neurons in a cannabinoid 1 receptor (CB1R)-dependent manner. Further, we show that NIC induces an increase in extracellular matrix proteins associated with neural repair that is mitigated by CB1R antagonism. Together, these data lay the groundwork for advanced approaches in understanding how TBI impacts neural function at the cellular level, and the development of treatments that promote neural repair in response to brain injury. SIGNIFICANCECurrent models of mild TBI (mTBI) cannot relate injury forces to both macroscale tissue damage and brain function at the cellular level. We combine a microscale injury model in ex vivo brain slices while simultaneously recording glutamatergic inputs onto CA1 hippocampal pyramidal neurons. Post-injury examination of chronic tissue regeneration by astrocytes allow us to connect acute neuronal signaling responses to chronic fibrosis after TBI. These studies provide a new tool for understanding the physiological and molecular responses to TBI and lay the groundwork for future experiments unraveling the synaptic mechanisms that mediate these responses seconds, minutes, and days following injury.

neuroscience↗

bioRxiv2023

Tenascin-C activation of lung fibroblasts in a 3D synthetic lung extracellular matrix mimic

The lung extracellular matrix (ECM) maintains the structural integrity of the tissue and regulates the phenotype and functions of resident fibroblasts. Lung-metastatic breast cancer alters these cell-ECM interactions, promoting fibroblast activation. There is a need for bio-instructive ECM models that contain the ECM composition and biomechanics of the lung to study these cell-matrix interactions in vitro. Here, we developed a synthetic, bioactive hydrogel that mimics the native lung modulus, and includes a representative distribution of the most abundant ECM peptide motifs responsible for integrin binding and matrix metalloproteinase (MMP)-mediated degradation in the lung, which promotes quiescence of human lung fibroblasts (HLFs). Stimulation with transforming growth factor {beta}1 (TGF-{beta}1), metastatic breast cancer conditioned media (CM), or tenascin-C activated these hydrogel-encapsulated HLFs in a manner reflective of their native in vivo responses. We propose this lung hydrogel platform as a tunable, synthetic approach to study the independent and combinatorial effects of ECM in regulating fibroblast quiescence and activation.

bioengineering↗

bioRxiv2022

Agent-based models help interpret patterns of clinical drug resistance by contextualizing competition between distinct drug failure modes.

Structured AbstractO_ST_ABSIntroductionC_ST_ABSModern targeted cancer therapies are carefully crafted small molecules. These exquisite technologies exhibit an astonishing diversity of failure modes (drug resistance mechanisms) in the clinic. This diversity is surprising because back of the envelope calculations and classic modeling results in evolutionary dynamics suggest that the diversity in the modes of clinical drug resistance should be considerably smaller than what is observed. These same calculations suggest that known microenvironmental resistance mechanisms should not be able to compete for outgrowth with genetic resistance within a tumor, and yet evidence of microenvironmental resistance is often observed in the clinic. Quantitatively understanding the underlying biological mechanisms of failure mode diversity may improve the next generation of targeted anticancer therapies. It also provides insights into how intratumoral heterogeneity might shape interpatient diversity during clinical relapse. Materials and MethodsWe employed spatial agent-based models to explore regimes where spatial constraints enable microenvironmental resistance to significantly compete with genetically resistant subclones. In order to parameterize a model of microenvironmental resistance, BT20 cells were cultured in the presence and absence of fibroblasts from 16 different tissues. The degree of resistance conferred by cancer associated fibroblasts (CAFs) in the tumor microenvironment was quantified by treating mono- and co-cultures with letrozole and then measuring the death rates. Results and DiscussionOur simulations indicate that, even when a mutation is more drug resistant, its outgrowth can be delayed by abundant, low magnitude microenvironmental resistance across large regions of a tumor. These observations hold for different modes of microenvironmental resistance, including juxtacrine signaling, soluble secreted factors, and remodeled ECM. This result helps to explain the remarkable diversity of resistance mechanisms observed in solid tumors, which subverts the presumption that the failure mode that causes the quantitatively fastest growth in the presence of drug should occur most often in the clinic. ConclusionOur model results demonstrate that spatial effects can interact with low magnitude of resistance microenvironmental effects to successfully compete against genetic resistance that is orders of magnitude larger. Clinical outcomes of solid tumors are intrinsically connected to their spatial structure, and the tractability of spatial agent-based models like the ones presented here enable us to understand this relationship more completely.

bioengineering↗

bioRxiv2017

Fibroblasts from metastatic sites induce broad-spectrum drug desensitization via modulation of mitochondrial priming

Due to tumor heterogeneity, most believe that effective treatments should be tailored to the features of an individual tumor or tumor subclass. It is still unclear what information should be considered for optimal disease stratification, and most prior work focuses on tumor genomics. Here, we focus on the tumor micro-environment. Using a large-scale co-culture assay optimized to measure drug-induced cell death, we identify tumor-stroma interactions that modulate drug sensitivity. Our data show that the chemo-insensitivity typically associated with aggressive subtypes of breast cancer is not cell intrinsic, but rather a product of tumor-fibroblast interactions. Additionally, we find that fibroblast cells influence tumor drug response in two distinct and divergent manners, which were predicable based on the anatomical origin from which the fibroblasts were harvested. These divergent phenotypes result from modulation of \"mitochondrial priming\" of tumor cells, caused by secretion of inflammatory cytokines, such as IL6 and IL8, from stromal cells.

cancer biology↗

bioRxiv2017

Mechanosensing of Integrin α6 and EGFR Converges atCalpain 2

Introduction Introduction Materials and Methods Results Discussion Conclusions Author Contributions Conflict of Interest References Carcinoma progression is associated with deposition of ECM that stiffens the local microenvironment [1, 2]. This tissue stiffening results in deposition of additional matrix proteins, initiating a positive feedback loop between cells and the evolving stroma [3]. Cells sense and respond to the stiffness of their environment via RhoA GTPase activation, which feeds back to increase cell contractility via activation of myosin light chain kinase [4]. These ECM-driven changes in cytoskeletal tension regulate motility in a cell-type specific manner [5]. In vi ...

bioengineering↗