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Human-correlated genetic HCC organoid models identify combination therapy for precision medicine

ABSTRACT: Hepatocellular carcinoma (HCC), the most common form of primary liver cancer, is a leading cause of cancer related mortality worldwide. HCC occurs typically from a background of chronic liver disease, caused by a spectrum of predisposing conditions. Tumour development is driven by the expansion of clones that accumulated progressive driver mutations, with hepatocytes the most likely cell of origin. However, the landscape of driver mutations in HCC is independent of the underlying aetiologies. Despite an increasing range of systemic treatment options for advanced HCC outcomes remain heterogeneous and typically poor. Emerging data suggest that drug efficacies depend on disease aetiology and genetic alterations. Exploring subtypes in preclinical models with human relevance will therefore be essential to advance precision medicine in HCC. We generated over twenty-five new genetically-driven in vivo and in vitro HCC models. Our models represent multiple features of human HCC, including clonal origin, histopathological appearance, and metastasis to distant organs. We integrated transcriptomic data from the mouse models with human HCC data and identified four common human-mouse subtype clusters. The subtype clusters had distinct transcriptomic characteristics that aligned with histopathology. In a proof-of-principle analysis, we verified response to standard of care treatment and used a linked in vitro-in vivo pipeline to identify a promising therapeutic candidate, cladribine, that has not been linked to HCC treatment before. Cladribine acts in a highly effective subtype-specific manner in combination with standard of care therapy.

ORGANISM(S): Mus musculus

PROVIDER: GSE275443 | GEO | 2024/12/02

REPOSITORIES: GEO

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Project description:Breast cancer is the second leading cause of cancer related death in American women. Patient care is complicated by inherent tumor heterogeneity that can be classified into at least six intrinsic subtypes. While targeted treatments are standard of care for most subtypes, there remains a clinical need for targeted therapies against basal-like tumors that are typically ‘triple negative breast cancers’. As such, the molecular mechanisms underlying basal-like tumors are under intense investigation to identify genetic drivers and possible drug targets of this subtype. Somatic p53 mutations are one of the most common genetic events in basal-like breast tumors. This genetic foundation primes cells to accumulate secondary genetic aberrations, a subset of which is predicted to promote tumorigenesis. To identify additional drivers of basal-like tumors, a comparative study between human and murine tumors was performed utilizing a p53null mammary transplant murine model. The p53null mammary transplant murine model produced a genomically diverse set of tumors, a subset of which we show resemble the human basal-like subtype. Microarray and sequencing technologies were used to interrogate the secondary genetic aberrations of these murine tumors which were then compared to human basal-like tumors to highlight conserved features. Of the ‘omic’ datasets analyzed, DNA copy number variation produced the largest number of conserved candidate driver genes. These candidate gene lists were further filtered using a DNA-RNA Pearson correlation cutoff of 0.5 and a requirement that the gene was deemed essential in at least one human basal-like cell line from a genome-wide RNA-mediated interference screen database. These steps highlighted seven potential driver genes that are at amplified loci in both murine and human basal-like tumors: Atp11a, Col4a2, Cul4a, Lamp1, Met, Pnpla6, and Tubgcp3. Inhibition of Met using Crizotinib caused Met amplified tumors to regress, confirming that this genetic event is a driver in a subset of p53null transplant mammary tumors. This study identifies MET as a driver of basal-like murine tumors, thus identifying a shared potential driver of human basal-like breast cancer. Our results also highlight the importance of comparative genomic studies for discovering drug targets and for providing models to study whether patient populations are likely to respond to selective targeted treatments.

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Human-correlated genetic HCC organoid models identify combination therapy for precision medicine

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