Human-correlated genetic HCC models identify combination therapy for precision medicine [Pre-print]

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

Patient-derived organoids identify tailored therapeutic options and determinants of plasticity in sarcomatoid urothelial bladder cancer

Abstract Sarcomatoid Urothelial Bladder Cancer (SARC) is a rare and aggressive histological subtype of bladder cancer for which therapeutic options are limited and experimental models are lacking. Here, we report the establishment of a long-term 3D organoid-like model derived from a SARC patient (SarBC-01). SarBC-01 emulates aggressive morphological, phenotypical, and transcriptional features of SARC and harbors somatic mutations in genes frequently altered in sarcomatoid tumors such as TP53 (p53) and RB1 (pRB). High-throughput drug screening, using a library comprising 1567 compounds in SarBC-01 and conventional urothelial carcinoma (UroCa) organoids, identified drug candidates active against SARC cells exclusively, or UroCa cells exclusively, or both. Among those, standard-of-care chemotherapeutic drugs inhibited both SARC and UroCa cells, while a subset of targeted drugs was specifically effective in SARC cells, including agents targeting the Glucocorticoid Receptor (GR) pathway. In two independent patient cohorts and in organoid models, GR and its encoding gene NR3C1 were found to be significantly more expressed in SARC as compared to UroCa, suggesting that high GR expression is a hallmark of SARC tumors. Further, glucocorticoid treatment impaired the mesenchymal morphology, abrogated the invasive ability of SARC cells, and led to transcriptomic changes associated with reversion of epithelial-to-mesenchymal transition, at single-cell level. Altogether, our study highlights the power of organoids for precision oncology and for providing key insights into factors driving rare tumor entities