Dataset Information

MAFLD: an optimal framework for understanding liver cancer phenotypes.

ABSTRACT: Hepatocellular carcinoma has a substantial global mortality burden which is rising despite advancements in tackling the traditional viral risk factors. Metabolic (dysfunction) associated fatty liver disease (MAFLD) is the most prevalent liver disease, increasing in parallel with the epidemics of obesity, diabetes and systemic metabolic dysregulation. MAFLD is a major factor behind this sustained rise in HCC incidence, both as a single disease entity and often via synergistic interactions with other liver diseases. Mechanisms behind MAFLD-related HCC are complex but is crucially underpinned by systemic metabolic dysregulation with variable contributions from interacting disease modifiers related to environment, genetics, dysbiosis and immune dysregulation. MAFLD-related HCC has a distinct clinical presentation, most notably its common occurrence in non-cirrhotic liver disease. This is just one of several major challenges to effective surveillance programmes. The response of MAFLD-related HCC to immune-checkpoint therapy is currently controversial, and is further complicated by the high prevalence of MAFLD in individuals with HCC from viral aetiologies. In this review, we highlight the current data on epidemiology, clinical characteristics, outcomes and screening controversies. In addition, concepts that have arisen because of the MAFLD paradigm such as HCC in MAFLD/NAFLD non-overlapping groups, dual aetiology tumours and MAFLD sub-phenotypes is reviewed.

SUBMITTER: Crane H

PROVIDER: S-EPMC10522746 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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MAFLD: an optimal framework for understanding liver cancer phenotypes.

Crane Harry H Gofton Cameron C Sharma Ankur A George Jacob J

Journal of gastroenterology 20230720 10

Hepatocellular carcinoma has a substantial global mortality burden which is rising despite advancements in tackling the traditional viral risk factors. Metabolic (dysfunction) associated fatty liver disease (MAFLD) is the most prevalent liver disease, increasing in parallel with the epidemics of obesity, diabetes and systemic metabolic dysregulation. MAFLD is a major factor behind this sustained rise in HCC incidence, both as a single disease entity and often via synergistic interactions with ot ...[more]

PMID: 37470858

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Project description:One of the key challenges in current cancer research is the development of computational strategies to support clinicians in the identification of successful personalized treatments. Control theory might be an effective approach to this end, as proven by the long-established application to therapy design and testing. In this respect, we here introduce the Control Theory for Therapy Design (CT4TD) framework, which employs optimal control theory on patient-specific pharmacokinetics (PK) and pharmacodynamics (PD) models, to deliver optimized therapeutic strategies. The definition of personalized PK/PD models allows to explicitly consider the physiological heterogeneity of individuals and to adapt the therapy accordingly, as opposed to standard clinical practices. CT4TD can be used in two distinct scenarios. At the time of the diagnosis, CT4TD allows to set optimized personalized administration strategies, aimed at reaching selected target drug concentrations, while minimizing the costs in terms of toxicity and adverse effects. Moreover, if longitudinal data on patients under treatment are available, our approach allows to adjust the ongoing therapy, by relying on simplified models of cancer population dynamics, with the goal of minimizing or controlling the tumor burden. CT4TD is highly scalable, as it employs the efficient dCRAB/RedCRAB optimization algorithm, and the results are robust, as proven by extensive tests on synthetic data. Furthermore, the theoretical framework is general, and it might be applied to any therapy for which a PK/PD model can be estimated, and for any kind of administration and cost. As a proof of principle, we present the application of CT4TD to Imatinib administration in Chronic Myeloid leukemia, in which we adopt a simplified model of cancer population dynamics. In particular, we show that the optimized therapeutic strategies are diversified among patients, and display improvements with respect to the current standard regime.

Dataset Information

MAFLD: an optimal framework for understanding liver cancer phenotypes.

Publications

MAFLD: an optimal framework for understanding liver cancer phenotypes.

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