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Korrektur zu 10.1038/s41591-021-01511-6

Cancer therapy is currently shifting from broadly used cytotoxic drugs to patient-specific precision therapies. Druggable driver oncogenes, identified by molecular analyses, are present in only a subset of patients. Functional profiling of primary tumor cells could circumvent these limitations, but suitable platforms are unavailable for most cancer entities. Here, we describe an in vitro drug profiling platform for rhabdomyosarcoma (RMS), using a living biobank composed of twenty RMS patient-derived xenografts (PDX) for high-throughput drug testing. Optimized in vitro conditions preserve phenotypic and molecular characteristics of primary PDX cells and are compatible with propagation of cells directly isolated from patient tumors. Besides a heterogeneous spectrum of responses of largely patient-specific vulnerabilities, profiling with a large drug library reveals a strong sensitivity towards AKT inhibitors in a subgroup of RMS. Overall, our study highlights the feasibility of in vitro drug profiling of primary RMS for patient-specific treatment selection in a co-clinical setting., Patient-specific precision medicine approaches are important for future cancer therapies. Here, the authors show that functional drug profiling with Rhabdomyosarcoma cells isolated from PDX and primary patient tumors uncovers patient-specific vulnerabilities.

Cancer therapy is currently shifting from broadly used cytotoxic drugs to patient-specific precision therapies. Druggable driver oncogenes, identified by molecular analyses, are present in only a subset of patients. Functional profiling of primary tumor cells could circumvent these limitations, but suitable platforms are unavailable for most cancer entities. Here, we describe an in vitro drug profiling platform for rhabdomyosarcoma (RMS), using a living biobank composed of twenty RMS patient-derived xenografts (PDX) for high-throughput drug testing. Optimized in vitro conditions preserve phenotypic and molecular characteristics of primary PDX cells and are compatible with propagation of cells directly isolated from patient tumors. Besides a heterogeneous spectrum of responses of largely patient-specific vulnerabilities, profiling with a large drug library reveals a strong sensitivity towards AKT inhibitors in a subgroup of RMS. Overall, our study highlights the feasibility of in vitro drug profiling of primary RMS for patient-specific treatment selection in a co-clinical setting.

Drug sensitivity and resistance testing on diagnostic leukemia samples should provide important functional information to guide actionable target and biomarker discovery. We provide proof of concept data by profiling 60 drugs on 68 acute lymphoblastic leukemia (ALL) samples mostly from resistant disease in co-cultures on bone marrow stromal cells. Patient-derived xenografts retained the original pattern of mutations found in the matched patient material. Stromal co-culture did not prevent leukemia cell cycle activity, while a specific sensitivity profile to cell cycle related drugs identified samples with higher cell proliferation both in vitro and in vivo as leukemia xenografts. In cases with refractory relapses, individual patterns of marked drug resistance, but also exceptional responses to new agents of immediate clinical relevance were detected. The BCL2-inhibitor venetoclax was highly active below 10 nM in BCP-ALL subsets including MLL-AF4 and TCF3-HLF ALL, and in some T-ALLs, predicting in vivo activity as a single agent and in combination with dexamethasone and vincristine. Unexpected sensitivity to dasatinib with IC50 values below 20 nM was detected in two independent T-ALL cohorts, which correlated with similar cytotoxic activity of the SRC Inhibitor KX2-391 and inhibition of SRC phosphorylation. A patient with refractory T-ALL was treated with dasatinib based on drug profiling information and achieved a five-month remission. Thus, drug profiling captures disease-relevant features and unexpected sensitivity to relevant drugs, which warrants further exploration of this functional assay in the context of clinical trials in order to develop drug repurposing strategies for patients with urgent medical needs.

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Supplementary Figures. Figure S1. Coverage of the sgRNA library in HCC-827 and CHP-212 cells. a) Coverage of the sgRNA library by deep sequencing at indicated time points for the HCC-827 cell line. Each time point was measured in duplicates and average percentages are represented here. b) Same as in a) but CHP-212 cell line is used instead. Figure S2. Principal Components Analysis (PCA) plots for different time points in HCC-827 and CHP-212 cells. PCA plots representing the sgRNA counts obtained for both cell lines. Figure S3. Histogram plots of the difference between the maximum and the minimum sgRNA fold changes per gene. These histogram plots show the variability among sgRNAs targeting the same gene calculated as the delta between the maximum and the minimum sgRNA fold changes for each gene for the HCC-827 and the CHP-212 cell lines on day 14. Figure S4. Depleted sgRNAs for kinases in HCC-827 and CHP-212 cells. Time points were measured in duplicates and median fold changes are represented here. Dark green colored dots represent the 1 000 non-targeting control sgRNAs and grey colored dots represent the 57 096 targeting sgRNAs. a-d) Scatter plots of fold changes compared to the control time point are shown for the HCC-827 and the CHP-212 cell line. f,g) Scatter plots of fold changes of 57 096 targeting sgRNAs of the HCC-827 and CHP-212 cell lines at indicated time points. e, f) Scatter plot of fold changes for independent replicates at time point day 14 for HCC-827 (S4e) and CHP-212 (S4f), respectively. g,h) Scatter plots of fold changes of 57 096 targeting sgRNAs of the HCC-827 and CHP-212 cell lines at indicated time points. Figure S5. Estimation of off-target effects. a) Scatter plots of mRNA expression levels expressed in FPKMs were compared to depletion by Q1 for the HCC-827 cell line. Of the 5 % most depleted genes which is equal to 1 450 sgRNAs, more than 90 % were expressed with a FPKMâ >â 1. b) Of the 1 462 most depleted sgRNAs (5 %) for the CHP-212 cell line, more than 87,5 % were expressed with a FPKM >1. Figure S6. MEK inhibitor MEK162 and EGFR inhibitor Erlotinib affected cell viability of the respective cell lines. a,b) HCC-827 and CHP-212 cells were treated with indicated concentrations of Erlotinib (a) or MEK162 (b) and analyzed as described in M&M part. Figure S7. Cytogenetics of HCC-827 and CHP-212 cell lines. (PDF 1451 kb)