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Biology subjects

Jassim, A.

Publications and source records attributed to Jassim, A..

2 recordsLinked to original sources

Cross-species graph-embedding unmasks the ageing microenvironment as a key determinant of pancreatic cancer malignant cell biology and therapy response

Pancreatic ductal adenocarcinoma (PDAC) has a dismal prognosis and is characterised by an extensive pro-tumorigenic stroma. Although most PDAC cases occur in older patients, the impact of ageing on malignant-stromal interactions and therapy response remains poorly understood. Here, we established orthotopically-grafted organoid-derived PDAC models across three murine age groups to characterise changes in the PDAC stroma and malignant cells with ageing. Cross-species analyses of tumour transcriptomes using a graph-embedding approach showed that integrating mouse models of different ages better captures the diversity of human PDAC, and that aged models more faithfully recapitulate the biology of older patients with PDAC. We also demonstrated that aged PDAC models have a more inflammatory stroma than that of younger tumours, shaping the malignant cell transcriptome. Finally, graph-embedding identified IRAK4 as a candidate therapeutic vulnerability in aged, but not young, KRAS- and p53-mutant PDAC, which we validated in preclinical drug studies. These findings highlight how ageing is a critical determinant of PDAC biology and associated therapeutic vulnerabilities, which should be an important consideration when designing disease models for preclinical development of precision therapies.

cancer biology↗

Natural language processing charts transcriptome evolution to design combination cancer therapies

Combination treatment-the mainstay of cancer therapy-often fails because treatment interactions evoke complex resistance mechanisms that are hard to predict. Designing combination therapy to prevent treatment resistance is especially challenging for rare cancers. Here, we introduce REsistance through COntext DRift (RECODR): a computational pipeline that tracks how genes change their transcriptome context across cancer development and drug treatment conditions. By applying RECODR to a genetically modified mouse model of choroid plexus carcinoma-a rare brain tumour of young children-we identified patterns of transcriptome evolution, cellular heterogeneity and treatment targets that emerged as tumours were initiated and resisted combination treatment. This enabled the prediction of treatment resistance mechanisms and the design of highly effective therapeutic protocols that avoided treatment failure. RECODR can describe complex and dynamic changes in normal and diseased tissues that could be applied to multimodal data from a variety of settings, mitigating treatment resistance across cancers and other diseases.

cancer biology↗