Biology subjects

Dickinson, J.

Publications and source records attributed to Dickinson, J..

4 recordsLinked to original sources

bioRxiv2024

Individual Patient Data Analysis of Liver Lesion Dynamics: A Pan Cancer Analysis

There are now several databases available that enable the exploration of individual patient data from past Oncology clinical trials. These databases provide researchers with the opportunity to investigate the dynamics of individual lesions across various tumour sites within a patient and compare them across different patients. In this report, we specifically focus on liver metastases and examine the dynamics of individual lesions across different treatment and tumour types. Our findings reveal that when a lesion progresses early on, the rate of growth is significantly higher for liver lesions compared to other types of lesions, regardless of the treatment modality (chemotherapy, targeted therapy, or combination of both). These results indicate the need for further basic research on tumours and their microenvironment specifically within liver metastases. This analysis demonstrates how analysing open trial data can uncover new research prospects at the fundamental science level, thereby bridging the gap between laboratory research and clinical applications.

cancer biology↗

bioRxiv2023

Comparisons of two receptor pathways in a single cell-type reveal features of signalling specificity.

To respond appropriately to diverse stimuli, cells harbour numerous receptor pathways yet share downstream signalling components. Mitogen-Activated Protein Kinase (MPK) cascades, present in all eukaryotes, act as central hubs shared amongst diverse signalling pathways. How signalling specificity is maintained within a single plant cell-type is not well understood. We engineered a genetic background for direct comparisons of a developmental and an immunity pathway in the Arabidopsis root endodermis. We show the two pathways maintain distinct outputs despite similar MPK phosphorylation patterns. Systematic activation of all individual MPK Kinases (MKKs) in the endodermis revealed that different MKK groups can drive distinct outputs. We propose that specificity is achieved through a balance of combinatorial activation and cross-pathway inhibition within the MPK cascade. Our findings demonstrate the ability of MPK cascades to generate diverse outputs in one plant cell-type, providing new insights into the mechanisms contributing to signalling specificity.

plant biology↗

bioRxiv2020

Mucin granules are degraded in the autophagosome-lysosome pathway as a means of resolving airway mucous cell metaplasia

Exacerbations of muco-obstructive airway diseases such as COPD and asthma are associated with epithelial changes termed mucous cell metaplasia (MCM). The molecular pathways triggering MCM have been identified; however, the factors that regulate resolution are less well understood. We hypothesized that the autophagosome-lysosome pathway is required for resolution of MCM by degrading cytoplasmic mucins. We found increased intracellular levels of Muc5ac and Muc5b in autophagy-deficient mice. This difference was not due to defective mucin secretion. Instead, we found that Lamp1-labeled lysosomes surrounded mucin granules of mucous cells indicating that granules were being degraded. Using a model of resolution of mucous cell metaplasia in mice, we found increased lysosomal proteolytic activity that peaked in the days after inflammation. Autophagy-deficient mice had persistent accumulation of mucin granules that failed to decline due to reduced mucin degradation. We applied these findings in vitro to human airway epithelial cells (AECs). Activation of autophagy by mTOR inhibition led to degradation of mucin granules in AECs. Our findings indicate that during peak and resolution phases of MCM, mucin granules can be degraded by autophagy. The addition of mucin degradation to the existing paradigm of production and secretion may more fully explain how the secretory cells handle excess amounts of cytoplasmic mucin and offers a therapeutic target to speed resolution of MCM in airway disease exacerbations. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=142 SRC="FIGDIR/small/130534v2_ufig1.gif" ALT="Figure 1"> View larger version (40K): org.highwire.dtl.DTLVardef@94239org.highwire.dtl.DTLVardef@1dac6dforg.highwire.dtl.DTLVardef@368161org.highwire.dtl.DTLVardef@680b7d_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2019

Analysis of patient derived xenograft studies in Oncology drug development: impact on design and interpretation of future studies

BackgroundPreclinical Oncology drug development is heavily reliant on xenograft studies to assess the anti-tumour effect of new compounds. Patient derived xenograft (PDX) have become popular as they may better represent the clinical disease, however variability is greater than in cell-line derived xenografts. The typical approach of analysing these studies involves performing an un-paired t-test on the mean tumour volumes between the treated and control group at the end of the study. This approach ignores the time-series and may result in false conclusions, especially when considering the increased variability of PDX studies.\n\nAimTo test the hypothesis that a model-based analysis provides increased power than analysis of final day volumes and to provide insights into more efficient PDX study designs.\n\nMethodsData was extracted from tumour xenograft time-series data from a large publicly available PDX drug treatment database released by Novartis. For all 2-arm studies the percent tumour growth inhibition (TGI) at two time-points, day 10 and day 14 was calculated. For each study, the effect of treatment was calculated using an un-paired t-test and also a model-based analysis using the likelihood ratio-test. In addition a simulation study was also performed to assess the difference in power between the two data-analysis approaches for different levels of TGI for PDX or standard cell-line derived xenografts (CDX).\n\nResultsThe model-based analysis had greater statistical power than the un-paired t-test approach within the PDX data-set. The model-based approach was able to detect TGI values as low as 25 percent whereas the un-paired t-test approach required at least 50 percent TGI. These findings were confirmed within the simulation study performed which also highlighted that CDX studies require less animals than PDX studies which show the equivalent level of TGI.\n\nConclusionThe analysis of 59 2-arm PDX studies highlighted that taking a model-based approach gave increased statistical power over simply performing an un-paired t-test on the final study day. Importantly the model-based approach was able to detect smaller size of effect compared to the un-paired t-test approach is which maybe common of such studies. These findings were confirmed within simulated studies which also highlighted the same sample size used for CDX studies would lead to inadequately powered PDX studies. Application of a model-based analysis should allow studies to use less animals and run experiments for a shorter period thus providing effective insight into compound anti-tumour activity

cancer biology↗