We generated ex vivo drug-response and multiomics profiling data for a prospective series of 252 samples from 186 patients with acute myeloid leukemia (AML). A functional precision medicine tumor board (FPMTB) integrated clinical, molecular, and functional data for application in clinical treatment decisions. Actionable drugs were found for 97% of patients with AML, and the recommendations were clinically implemented in 37 relapsed or refractory patients. We report a 59% objective response rate for the individually tailored therapies, including 13 complete responses, as well as bridging five patients with AML to allogeneic hematopoietic stem cell transplantation. Data integration across all cases enabled the identification of drug response biomarkers, such as the association of IL15 overexpression with resistance to FLT3 inhibitors. Integration of molecular profiling and large-scale drug response data across many patients will enable continuous improvement of the FPMTB recommendations, providing a paradigm for individualized implementation of functional precision cancer medicine. Significance: Oncogenomics data can guide clinical treatment decisions, but often such data are neither actionable nor predictive. Functional ex vivo drug testing contributes significant additional, clinically actionable therapeutic insights for individual patients with AML. Such data can be generated in four days, enabling rapid translation through FPMTB. See related commentary by Letai, p. 290. This article is highlighted in the In This Issue feature, p. 275

A defective form of the AIRE protein causes autoimmune destruction of target organs by disturbing the immunological tolerance of patients with a rare monogenic disease, autoimmune polyendocrinopathy (APE)–candidiasis (C)–ectodermal dystrophy (ED), APECED. Recently, experiments on knockout mice revealed that AIRE controls autoimmunity by regulating the transcription of peripheral tissue-restricted antigens in thymic medullary epithelial cells. Thus, AIRE provides a unique model for molecular studies of organ-specific autoimmunity. In order to analyze the molecular and cellular consequences of 16 disease-causing mutations in vitro, we studied the subcellular localization, transactivation capacity, homomultimerization, and complex formation of several mutant AIRE polypeptides. Most of the mutations altered the nucleus–cytoplasm distribution of AIRE and disturbed its association with nuclear dots and cytoplasmic filaments. While the PHD zinc fingers were necessary for the transactivation capacity of AIRE, other regions of AIRE also modulated this function. Consequently, most of the mutations decreased transactivation. The HSR domain was responsible for the homomultimerization activity of AIRE; all the missense mutations of the HSR and the SAND domains decreased this activity, but those in other domains did not. The AIRE protein was present in soluble high-molecular-weight complexes. Mutations in the HSR domain and deletion of PHD zinc fingers disturbed the formation of these complexes. In conclusion, we propose an in vitro model in which AIRE transactivates transcription through heteromeric molecular interactions that are regulated by homomultimerization and conditional localization of AIRE in the nucleus or in the cytoplasm. Hum Mutat 23:245–257, 2004.

High-throughput screening (HTS) enables systematic testing of thousands of chemical compounds for potential use as investigational and therapeutic agents. HTS experiments are often conducted in multi-well plates that inherently bear technical and experimental sources of error. Thus, HTS data processing requires the use of robust quality control procedures before analysis and interpretation. Here, we have implemented an open-source analysis application, Breeze, an integrated quality control and data analysis application for HTS data. Furthermore, Breeze enables a reliable way to identify individual drug sensitivity and resistance patterns in cell lines or patient-derived samples for functional precision medicine applications. The Breeze application provides a complete solution for data quality assessment, dose–response curve fitting and quantification of the drug responses along with interactive visualization of the results. The Breeze application with video tutorial and technical documentation is accessible at https://breeze.fimm.fi; the R source code is publicly available at https://github.com/potdarswapnil/Breeze under GNU General Public License v3.0. swapnil.potdar@helsinki.fi Supplementary data are available at Bioinformatics online.

Purpose: Molecular tumor heterogeneity may have important implications for the efficacy of targeted therapies in metastatic cancers. Inter-metastatic heterogeneity of sensitivity to anticancer agents has not been well explored in colorectal cancer (CRC). Experimental design: We established a platform for ex vivo pharmacogenomic profiling of patient-derived organoids (PDOs) from resected CRC liver metastases. Drug sensitivity testing (n=40 clinically relevant agents) and gene expression profiling were performed of thirty-nine metastases from twenty-two patients. Results: Three drug response clusters were identified among the CRC metastases, based primarily on sensitivities to EGFR and/or MDM2 inhibition, and corresponding with RAS mutations and TP53 activity. Potentially effective therapies, including off-label use of drugs approved for other cancer types, could be nominated for eighteen patients (82%). Antimetabolites and targeted agents lacking a decisive genomic marker had stronger differential activity than most approved chemotherapies. We found limited intra-patient drug sensitivity heterogeneity between PDOs from multiple (2-5) liver metastases from each of ten patients. This was recapitulated at the gene expression level, with a highly proportional degree of transcriptomic and pharmacological variation. One PDO with a multi-drug resistance profile, including resistance to EGFR inhibition in a RAS mutant background, showed sensitivity to MEK plus mTOR/AKT inhibition, corresponding with low-level PTEN expression. Conclusions: Intra-patient inter-metastatic pharmacological heterogeneity was not pronounced and ex vivo drug screening may identify novel treatment options for metastatic CRC. Variation in drug sensitivities was reflected at the transcriptomic level, suggesting potential to develop gene expression-based predictive signatures to guide experimental therapies