Brain tumoroids: treatment prediction and drug development for brain tumors with fast, reproducible and easy-to-use personalized models.

BACKGROUND: generation of patient avatar is critically needed in neuro-oncology for treatment prediction and preclinical therapeutic development. Our objective was to develop a fast, reproducible, low-cost and easy-to-use method of tumoroids generation and analysis, efficient for all types of brain tumors, primary and metastatic. METHODS: tumoroids were generated from 89 patients: 81 primary tumors including 77 gliomas, and 8 brain metastases. Tumoroids morphology, cellular and molecular characteristics were compared with the ones of the parental tumor by using histology, methylome profiling, pTERT mutations and multiplexed spatial immunofluorescences. Their cellular stability overtime was validated by flow cytometry. Therapeutic sensitivity was evaluated and predictive factors of tumoroid generation were analyzed. RESULTS: All the tumoroids analyzed had similar histological (N=21) and molecular features (N=7) than the parental tumor. Median generation time was 5 days. Success rate was 65 %: it was higher for high grade gliomas and brain metastases versus IDH mutated low grade gliomas. For high-grade gliomas, neither other clinical, neuro-imaging, histological nor molecular factors were predictive of tumoroid generation success. The cellular organization inside tumoroids analyzed by MACSima revealed territories dedicated to specific cell subtypes. Finally, we showed the correlation between tumoroid and patient treatment responses to radio-chemotherapy and their ability to respond to immunotherapy thanks to a dedicated and reproducible 3D analysis workflow. CONCLUSION: patient-derived tumoroid model that we developed offers a robust, user-friendly, low-cost and reproducible preclinical model valuable for therapeutic development of all type of primary or metastatic brain tumors, allowing their integration into forthcoming early-phase clinical trials.

SMAC mimetic drives microglia phenotype and glioblastoma immune microenvironment.

Tumor-associated macrophages/microglia (TAMs) are highly plastic and heterogeneous immune cells that can be immune-supportive or tumor-supportive depending of the microenvironment. TAMs are the most abundant immune cells in glioblastoma (GB), and play a key role in immunosuppression. Therefore, TAMs reprogramming toward immune-supportive cells is a promising strategy to overcome immunosuppression. By leveraging scRNAseq human GB databases, we identified that Inhibitor of Apoptosis Proteins (IAP) were expressed by TAMs. To investigate their role in TAMs-related immunosuppression, we antagonized IAP using the central nervous system permeant SMAC mimetic GDC-0152 (SMg). On explants and cultured immune cells isolated from human GB samples, SMg modified TAMs activity. We showed that SMg treatment promoted microglia pro-apoptotic and anti-tumoral function via caspase-3 pro-inflammatory cleavage and the inhibition of tumoroids growth. Then we designed a relevant immunogenic mouse GB model to decipher the spatio-temporal densities, distribution, phenotypes and function of TAMs with or without SMg treatment. We used 3D imaging techniques, a transgenic mouse with fluorescent TAM subsets and mass cytometry. We confirmed that SMg promoted microglia activation, antigen-presenting function and tumor infiltration. In addition, we observed a remodeling of blood vessels, a decrease in anti-inflammatory macrophages and an increased level of monocytes and their mo-DC progeny. This remodeling of the TAM landscape is associated with an increase in CD8 T cell density and activation. Altogether, these results demonstrated that SMg drives the immunosuppressive basal microglia toward an active phenotype with pro-apoptotic and anti-tumoral function and modifies the GB immune landscape. This identifies IAP as targets of choice for a potential mechanism-based therapeutic strategy and SMg as a promising molecule for this application.

Combination drug screen targeting glioblastoma core vulnerabilities reveals pharmacological synergisms.

BACKGROUND: Pharmacological synergisms are an attractive anticancer strategy. However, with more than 5000 approved-drugs and compounds in clinical development, identifying synergistic treatments represents a major challenge. METHODS: High-throughput screening was combined with target deconvolution and functional genomics to reveal targetable vulnerabilities in glioblastoma. The role of the top gene hit was investigated by RNA interference, transcriptomics and immunohistochemistry in glioblastoma patient samples. Drug combination screen using a custom-made library of 88 compounds in association with six inhibitors of the identified glioblastoma vulnerabilities was performed to unveil pharmacological synergisms. Glioblastoma 3D spheroid, organotypic ex vivo and syngeneic orthotopic mouse models were used to validate synergistic treatments. FINDINGS: Nine targetable vulnerabilities were identified in glioblastoma and the top gene hit RRM1 was validated as an independent prognostic factor. The associations of CHK1/MEK and AURKA/BET inhibitors were identified as the most potent amongst 528 tested pairwise drug combinations and their efficacy was validated in 3D spheroid models. The high synergism of AURKA/BET dual inhibition was confirmed in ex vivo and in vivo glioblastoma models, without detectable toxicity. INTERPRETATION: Our work provides strong pre-clinical evidence of the efficacy of AURKA/BET inhibitor combination in glioblastoma and opens new therapeutic avenues for this unmet medical need. Besides, we established the proof-of-concept of a stepwise approach aiming at exploiting drug poly-pharmacology to unveil druggable cancer vulnerabilities and to fast-track the identification of synergistic combinations against refractory cancers. FUNDING: This study was funded by institutional grants and charities.

Pan Aurora Kinase Inhibitor: A Promising Targeted-Therapy in Dedifferentiated Liposarcomas With Differential Efficiency Depending on Sarcoma Molecular Profile.

Soft tissue sarcoma (STS) are rare and aggressive tumours. Their classification includes numerous histological subtypes of frequent poor prognosis. Liposarcomas (LPS) are the most frequent type among them, and the aggressiveness and deep localization of dedifferentiated LPS are linked to high levels of recurrence. Current treatments available today lead to five-year overall survival has remained stuck around 60%-70% for the past three decades. Here, we highlight a correlation between Aurora kinasa A (AURKA) and AURKB mRNA overexpression and a low metastasis - free survival. AURKA and AURKB expression analysis at genomic and protein level on a 9-STS cell lines panel highlighted STS heterogeneity, especially in LPS subtype. AURKA and AURKB inhibition by RNAi and drug targeting with AMG 900, a pan Aurora Kinase inhibitor, in four LPS cell lines reduces cell survival and clonogenic proliferation, inducing apoptosis and polyploidy. When combined with doxorubicin, the standard treatment in STS, aurora kinases inhibitor can be considered as an enhancer of standard treatment or as an independent drug. Kinome analysis suggested its effect was linked to the inhibition of the MAP-kinase pathway, with differential drug resistance profiles depending on molecular characteristics of the tumor. Aurora Kinase inhibition by AMG 900 could be a promising therapy in STS.