Biology subjects

Parsons, M. J.

Publications and source records attributed to Parsons, M. J..

5 recordsLinked to original sources

bioRxiv2025

Concurrent genetic and non-genetic resistance mechanisms to KRAS inhibition in CRC

KRAS is mutationally activated in 45-50% of colorectal cancer (CRC) cases, and while KRAS-targeted therapies have shown some clinical promise, upfront and acquired resistance limit their efficacy. To explore the acute response and mechanisms underlying KRAS inhibitor resistance, we used targeted exome sequencing and single-cell spatial transcriptomics to analyze patient-matched pre-treatment, on-treatment, and progression biopsies from patients treated with combined KRASG12C and EGFR inhibition. Acquired genetic events were identified in most patients at progression but were often subclonal and coexisted with transcriptional adaptive states. Mesenchymal, YAP, and fetal-like transcriptional signatures predominated in resistant tumors, while tumor cell-intrinsic inflammatory programs were induced in the early treatment phase. Single-cell spatial analysis revealed significant intratumoral heterogeneity, with diverse adaptive states predominating in different zones of individual tumors. Using human and murine organoid models, we show that these drug-induced inflammatory programs are cancer-cell autonomous and precede the emergence of regenerative fetal-like programs associated with drug resistance. We uncover TBK1 as a promising target to abrogate the early inflammatory adaptive phase and enhance responses to KRAS inhibition.

cancer biology↗

bioRxiv2022

Generation of floxed alleles for cell-specific knockout in zebrafish

A benefit of the zebrafish as a model is its amenability to genetic approaches. However, a lack of conditional deletion alleles makes it a challenge to perform stage- or cell-specific knockout. Here, we initially applied an existing protocol to establish a floxed allele for gata2a and encountered several issues, including off-target integration and incomplete knock-in. To address these problems, we developed a protocol incorporating simultaneous co-targeting with Cas12a to insert loxP sites in cis, together with transgenic counter-screening to identify off-target insertions. We applied this protocol to establish a floxed allele of foxc1a in a single generation. We demonstrate the utility of our floxed alleles by verifying Cre-dependent deletion, which yielded expected phenotypes in each case. Finally, we used the floxed gata2a allele to demonstrate an endothelial autonomous requirement in lymphatic valve development. Together, our results provide a framework for straightforward generation and application of floxed alleles in zebrafish.

genetics↗

bioRxiv2019

Regulation of thymocyte β-selection, development and positive selection by glycogen synthase kinase-3

Glycogen synthase kinase-3 (GSK-3) is a ubiquitously expressed serine/threonine kinase, that exists as two isoforms in mammals, GSK-3 and GSK-3{beta}, that are key downstream mediators of the phosphatidylinositol 3 kinase, Wnt, Notch and other pathways. Here, we report that simultaneous inactivation of both GSK-3 and GSK-3{beta} during early thymocyte ontogeny has profound effects on both {beta}-selection and positive selection, key checkpoints essential to producing functionally mature {beta} T cells. Conditional GSK-3/{beta} knockout animals (LckCre+ GSK-3{beta}fl/fl) possessed pre-double positive (pre-DP) thymocytes (CD4-CD8-CD117-CD25-) with compromised TCR{beta} chain expression along with elevated levels of {beta}-catenin and reduced Notch activity. {beta}-selection was impaired allowing pre-DP thymocytes to differentiate to DP thymocytes (CD4+CD8+) while bypassing strict requirements for productive TCR{beta} chain rearrangements and functional expression. Also impaired was the requisite pre-TCR and Notch-mediated expansion that normally precedes differentiation to the DP stage. Consequently, LckCre+ GSK-3{beta}fl/fl mice initially generated fewer DP thymocytes that expressed significantly reduced levels of mature TCR. The aberrant DP thymocytes expressed high levels of the pro-survival Bcl-2 family member Mcl-1, failed positive selection and accumulated as CD4hiCD8lo positive selection intermediates resulting in loss of both mature CD4 and CD8 lineages. LckCre+ GSK-3{beta}fl/fl mice succumbed to oligoclonal peripheral lymphomas with high penetrance. These data reveal essential roles for GSK-3 in several checkpoints of early T cell development.

immunology↗

bioRxiv2019

Dissociable effects of visual crowding on the perception of colour and motion

Our ability to recognise objects in peripheral vision is fundamentally limited by crowding, the deleterious effect of clutter that disrupts the recognition of features ranging from orientation and colour to motion and depth. Prior research is equivocal on whether this reflects a singular process that disrupts all features simultaneously or multiple processes that affect each independently. We examined crowding for motion and colour, two features that allow a strong test of feature independence. Cowhide stimuli were presented 15 degrees in peripheral vision, either in isolation or surrounded by flankers to give crowding. Observers reported either the target direction (clockwise/counterclockwise from upwards) or its hue (blue/purple). We first established that both features show systematic crowded errors (predominantly biased towards the flanker identities) and selectivity for target-flanker similarity (with reduced crowding for dissimilar target/flanker elements). The multiplicity of crowding was then tested with observers identifying both features: a singular object-selective mechanism predicts that when crowding is weak for one feature and strong for the other that crowding should be all-or-none for both. In contrast, when crowding was weak for colour and strong for motion, errors were reduced for colour but remained for motion, and vice versa with weak motion and strong colour crowding. This double dissociation reveals that crowding disrupts certain combinations of visual features in a feature-specific manner, ruling out a singular object-selective mechanism. The ability to recognise one aspect of a cluttered scene, like colour, thus offers no guarantees for the correct recognition of other aspects, like motion. Significance statementOur peripheral vision is primarily limited by crowding, the disruption to object recognition that arises in clutter. Crowding is widely assumed to be a singular process, affecting all of the features (orientation, motion, colour, etc.) within an object simultaneously. In contrast, we observe a double dissociation whereby observers make errors regarding the colour of a crowded object whilst correctly judging its direction, and vice versa. This dissociation can be reproduced by a population-coding model where the direction and hue of target/flanker elements are pooled independently. The selective disruption of some object features independently of others rules out a singular crowding mechanism, posing problems for high-level crowding theories, and suggesting that the underlying mechanisms may be distributed throughout the visual system.

neuroscience↗

bioRxiv2018

Label-free assessment of red blood cell storage lesions by deep learning

Blood transfusion is a life-saving clinical procedure. With millions of units needed globally each year, it is a growing concern to improve product quality and recipient outcomes.\n\nStored red blood cells (RBCs) undergo continuous degradation, leading to structural and biochemical changes. To analyze RBC storage lesions, complex biochemical and biophysical assays are often employed.\n\nWe demonstrate that label-free imaging flow cytometry and deep learning can characterize RBC morphologies during 42-day storage, replacing the current practice of manually quantifying a blood smear from stored blood units. Based only on bright field and dark field images, our model achieved 90% accuracy in classifying six different RBC morphologies associated with storage lesions versus human-curated manual examination. A model fitted to the deep learning-extracted features revealed a pattern of morphological changes within the aging blood unit that allowed predicting the expiration date of stored blood using solely morphological assessment.\n\nDeep learning and label-free imaging flow cytometry could therefore be applied to reduce complex laboratory procedures and facilitate robust and objective characterization of blood samples.

bioinformatics↗