Shirolkar, G. D. | Search bioRxiv

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↗

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↗