Biology subjects

Main, N.

Publications and source records attributed to Main, N..

4 recordsLinked to original sources

bioRxiv2026

Advancing Liver Cancer Precision Medicine with TARGET-SL

Background and AimsA major goal of personalised liver oncology is the ability to make targeted predictions about cancer-specific toxicity, however there are limited methods available. To address this, we validated the performance of our bioinformatics framework, TARGET-SL, through ex vivo drug screening. MethodsUsing TARGET-SL we predicted gain of function (GOF), loss of function (LOF) and synthetic lethal (SL) genetic events, and corresponding drug candidates. We validated drug predictions across hepatocellular carcinoma (HCC) cell lines, and a cohort of HCC and cholangiocarcinoma (CCA) patient-derived organoids (PDOs). ResultsFor HCC cells and PDOs we found 37.5% and 25% of the respective selected compounds induced unique target-specific growth inhibition based on genetic biomarkers, suggesting novel biomarker-driven drug sensitivities. ConclusionsOur analyses demonstrate TARGET-SLs potential to enhance personalized drug screening for liver cancer, by focusing on genetically informed targets. This will reduce experimental costs and accelerate the pace of therapeutic discovery. Impact and ImplicationsPrimary liver cancer (PLC) is a cancer with poor prognosis, and current therapies increase survival only for a minority of patients. Through the application of TARGET-SL we can predict, for each patient, the essential genes and corresponding small molecule inhibitors. These data support further investigation in larger patient cohorts and offer the possibility to specify new small molecule inhibitors and to repurpose current drugs for PLC treatment. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/725819v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@10cb252org.highwire.dtl.DTLVardef@8f3049org.highwire.dtl.DTLVardef@ab4467org.highwire.dtl.DTLVardef@17f9d3_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LITARGET-SL can predict gene and drug sensitivities for cell lines and patient-derived organoids C_LIO_LIThis may reduce drug screening costs and accelerate the pace of therapeutic discovery. C_LIO_LITARGET-SL may assist in the repurposing of current drugs and their rapid translation for primary liver cancer C_LIO_LITARGET-SL is tumour-type agnostic, and therefore may have application in other cancers with poor prognosis C_LI

cancer biology↗

bioRxiv2023

Quantitative Comparison of Presenilin Protein Expression Reveals Greater Activity of PS2-gamma-Secretase.

{gamma}-Secretase processing of APP has long been of interest in the pathological progression of Alzheimers disease (AD) due to its role in the generation of amyloid-{beta}. The catalytic component of the enzyme are the presenilins of which there are two homologues, Presenilin-1 (PS1) and Presenilin-2 (PS2). The field has focussed on the PS1 form of this enzyme, as it is typically considered the more active at APP processing. However, much of this work has been completed without appropriate consideration of the specific levels of protein expression of PS1 and PS2. We propose that expression is an important factor in PS1- and PS2-{gamma}-secretase activity, and that when this is considered, PS1 does not have greater activity than PS2. We developed and validated tools for quantitative assessment of PS1 and PS2 protein expression levels to enable direct comparison of PS protein in exogenous and endogenous expression systems, in HEK-293 PS1 and/or PS2 knockout cells. We show that exogenous expression of Myc-PS1-NTF is 5.5-times higher than and Myc-PS2-NTF. Quantitating endogenous PS protein levels using a novel PS1/2 fusion standard we developed showed similar results. When the marked difference in PS1 and PS2 protein levels is considered, we show that compared to PS1-{gamma}-secretase, PS2-{gamma}-secretase has equal or more activity on APP and Notch1. This study has implications for understanding the PS1 and PS2 specific contributions to substrate processing, and their potential influence in AD pathogenesis.

cell biology↗

bioRxiv2022

Single Nucleus RNA Sequencing of Pre-Malignant Liver Reveals Disease-Associated Hepatocyte State with HCC Prognostic Potential

Current approaches to stage chronic liver diseases have limited utility to directly predict liver cancer risk. Here, we employed single nucleus RNA sequencing (snRNA-seq) to characterize the cellular microenvironment of healthy and chronically injured pre-malignant livers using two distinct mouse models. Analysis of 40,748 hepatic nuclei unraveled a previously uncharacterized disease-associated hepatocyte transcriptional state (daHep). These cells were absent in healthy livers, but were increasingly prevalent as chronic liver disease progressed towards hepatocarcinogenesis. Gene expression deconvolution of 1,439 human liver transcriptomes from publicly available datasets revealed that daHep frequencies highly correlate with current histopathological liver disease staging systems. Importantly, we show that high daHep levels precede carcinogenesis in mice and humans and predict a higher risk of hepatocellular carcinoma (HCC) development. This novel transcriptional signature with diagnostic and, more importantly, prognostic significance has the potential to change the way chronic liver disease patients are staged, surveilled and risk-stratified.

cancer biology↗

bioRxiv2019

The Role of CD147 in Leukocyte Aggregation in Liver Injury

BackgroundChronic inflammation is the driver of liver injury resulting in progressive fibrosis and eventual cirrhosis. The consequences include both liver failure and liver cancer. We have previously described increased expression of the highly multifunctional glycoprotein CD147 in liver injury. This work describes a novel role of CD147 in liver inflammation and the importance of leukocyte aggregates in determining the extent of liver injury.\n\nMethodsNon-diseased, progressive injury and cirrhotic liver from humans and mice were examined using mAb targeting CD147. Inflammatory cell subsets were assessed by multicolor flow cytometry.\n\nResultsIn liver injury, we observe abundant intrahepatic leukocyte clusters defined as [≥]5 adjacent CD45+ cells which we have labelled \"leukocyte aggregates\". We have shown that these leukocyte aggregates are significant in determining the extent of liver injury. If CD147 is blocked in vivo, these leukocyte aggregates diminish in size and number together with a marked significant reduction in liver injury including fibrosis. This accompanied by no change in overall intrahepatic leukocyte numbers. Further, blocking aggregation formation occurs prior to an appreciable increase in inflammatory markers or fibrosis. Additionally, there were no observed, \"off-target\" or unpredicted effects in targeting CD147.\n\nConclusionCD147 mediates leukocyte aggregation which is associated with the development of liver injury. This is not a secondary effect, but a cause of injury as aggregate formation proceeds other markers of injury. Leukocyte aggregation has been previously described in inflammation dating back over many decades but till now been shown to determine the extent of injury.

immunology↗