ZygosityPredictor.

Summary: ZygosityPredictor provides functionality to evaluate how many copies of a gene are affected by mutations in next generation sequencing data. In cancer samples, the tool processes both somatic and germline mutations. In particular, ZygosityPredictor computes the number of affected copies for single nucleotide variants and small insertions and deletions (Indels). In addition, the tool integrates information at gene level via phasing of several variants and subsequent logic to derive how strongly a gene is affected by mutations and provides a measure of confidence. This information is of particular interest in precision oncology, e.g. when assessing whether unmutated copies of tumor-suppressor genes remain. Availability and implementation: ZygosityPredictor was implemented as an R-package and is available via Bioconductor at https://bioconductor.org/packages/ZygosityPredictor. Detailed documentation is provided in the vignette including application to an example genome.

Evolution of SARS-CoV-2 in the Rhine-Neckar/Heidelberg Region 01/2021 - 07/2023.

In January 2021, the monitoring of circulating variants of SARS-CoV-2 was initiated in Germany under the Corona Surveillance Act, which was discontinued after July 2023. This initiative aimed to enhance pandemic containment, as specific amino acid changes, particularly in the spike protein, were associated with increased transmission and reduced vaccine efficacy. Our group conducted whole genome sequencing using the ARTIC protocol (currently V4) on Illumina's NextSeq 500 platform (and, starting in May 2023, on the MiSeq DX platform) for SARS-CoV-2 positive specimen from patients at Heidelberg University Hospital, associated hospitals, and the public health office in the Rhine-Neckar/Heidelberg region. In total, we sequenced 26,795 SARS-CoV-2-positive samples between January 2021 and July 2023. Valid sequences, meeting the requirements for upload to the German electronic sequencing data hub (DESH) operated by the Robert Koch Institute (RKI), were determined for 24,852 samples, and the lineage/clade could be identified for 25,912 samples. The year 2021 witnessed significant dynamics in the circulating variants in the Rhine-Neckar/Heidelberg region, including A.27.RN, followed by the emergence of B.1.1.7 (Alpha), subsequently displaced by B.1.617.2 (Delta), and the initial occurrences of B.1.1.529 (Omicron). By January 2022, B.1.1.529 had superseded B.1.617.2, dominating with over 90%. The years 2022 and 2023 were then characterized by the dominance of B.1.1.529 and its sublineages, particularly BA.5 and BA.2, and more recently, the emergence of recombinant variants like XBB.1.5. Since the global dominance of B.1.617.2, the identified variant distribution in our local study, apart from a time delay in the spread of new variants, can be considered largely representative of the global distribution. om a time delay in the spread of new variants, can be considered largely representative of the global distribution.

Multi-omic and functional analysis for classification and treatment of sarcomas with FUS-TFCP2 or EWSR1-TFCP2 fusions.

Linking clinical multi-omics with mechanistic studies may improve the understanding of rare cancers. We leverage two precision oncology programs to investigate rhabdomyosarcoma with FUS/EWSR1-TFCP2 fusions, an orphan malignancy without effective therapies. All tumors exhibit outlier ALK expression, partly accompanied by intragenic deletions and aberrant splicing resulting in ALK variants that are oncogenic and sensitive to ALK inhibitors. Additionally, recurrent CKDN2A/MTAP co-deletions provide a rationale for PRMT5-targeted therapies. Functional studies show that FUS-TFCP2 blocks myogenic differentiation, induces transcription of ALK and truncated TERT, and inhibits DNA repair. Unlike other fusion-driven sarcomas, TFCP2-rearranged tumors exhibit genomic instability and signs of defective homologous recombination. DNA methylation profiling demonstrates a close relationship with undifferentiated sarcomas. In two patients, sarcoma was preceded by benign lesions carrying FUS-TFCP2, indicating stepwise sarcomagenesis. This study illustrates the potential of linking precision oncology with preclinical research to gain insight into the classification, pathogenesis, and therapeutic vulnerabilities of rare cancers.

Fibroblast Activation Protein α-Directed Imaging and Therapy of Solitary Fibrous Tumor.

Fibroblast activation protein α (FAPα) is expressed at high levels in several types of tumors. Here, we report the expression pattern of FAPα in solitary fibrous tumor (SFT) and its potential use as a radiotheranostic target. Methods: We analyzed FAPα messenger RNA and protein expression in biopsy samples from SFT patients using immunohistochemistry and multiplexed immunofluorescence. Tracer uptake and detection efficacy were assessed in patients undergoing clinical 68Ga-FAPα inhibitor (FAPI)-46 PET,18F-FDG PET, and contrast-enhanced CT. 90Y-FAPI-46 radioligand therapy was offered to eligible patients with progressive SFT. Results: Among 813 patients and 126 tumor entities analyzed from the prospective observational MASTER program of the German Cancer Consortium, SFT (n = 34) had the highest median FAPα messenger RNA expression. Protein expression was confirmed in tumor biopsies from 29 of 38 SFT patients (76%) in an independent cohort. Most cases showed intermediate to high FAPα expression by immunohistochemistry (24/38 samples, 63%), which was located primarily on the tumor cell surface. Nineteen patients who underwent 68Ga-FAPI-46 PET imaging demonstrated significantly increased tumor uptake, with an SUVmax of 13.2 (interquartile range [IQR], 10.2), and an improved mean detection efficacy of 94.5% (SEM, 4.2%), as compared with 18F-FDG PET (SUVmax, 3.2 [IQR, 3.1]; detection efficacy, 77.3% [SEM, 5.5%]). Eleven patients received a total of 34 cycles (median, 3 cycles [IQR, 2 cycles]) of 90Y-FAPI-46 radioligand therapy, which resulted in disease control in 9 patients (82%). Median progression-free survival was 227 d (IQR, 220 d). Conclusion: FAPα is highly expressed by SFT and may serve as a target for imaging and therapy. Further studies are warranted to define the role of FAPα-directed theranostics in the care of SFT patients.

Phase I/II Study of the WEE1 Inhibitor Adavosertib (AZD1775) in Combination with Carboplatin in Children with Advanced Malignancies: Arm C of the AcSé-ESMART Trial.

PURPOSE: AcSé-ESMART Arm C aimed to define the recommended dose and activity of the WEE1 inhibitor adavosertib in combination with carboplatin in children and young adults with molecularly enriched recurrent/refractory malignancies. PATIENTS AND METHODS: Adavosertib was administered orally, twice every day on Days 1 to 3 and carboplatin intravenously on Day 1 of a 21-day cycle, starting at 100 mg/m2/dose and AUC 5, respectively. Patients were enriched for molecular alterations in cell cycle and/or homologous recombination (HR). RESULTS: Twenty patients (median age: 14.0 years; range: 3.4-23.5) were included; 18 received 69 treatment cycles. Dose-limiting toxicities were prolonged grade 4 neutropenia and grade 3/4 thrombocytopenia requiring transfusions, leading to two de-escalations to adavosertib 75 mg/m2/dose and carboplatin AUC 4; no recommended phase II dose was defined. Main treatment-related toxicities were hematologic and gastrointestinal. Adavosertib exposure in children was equivalent to that in adults; both doses achieved the cell kill target. Overall response rate was 11% (95% confidence interval, 0.0-25.6) with partial responses in 2 patients with neuroblastoma. One patient with medulloblastoma experienced unconfirmed partial response and 5 patients had stable disease beyond four cycles. Seven of these eight patients with clinical benefit had alterations in HR, replication stress, and/or RAS pathway genes with or without TP53 alterations, whereas TP53 pathway alterations alone (8/10) or no relevant alterations (2/10) were present in the 10 patients without benefit. CONCLUSIONS: Adavosertib-carboplatin combination exhibited significant hematologic toxicity. Activity signals and identified potential biomarkers suggest further studies with less hematotoxic DNA-damaging therapy in molecularly enriched pediatric cancers.

An AI-based segmentation and analysis pipeline for high-field MR monitoring of cerebral organoids.

Cerebral organoids recapitulate the structure and function of the developing human brain in vitro, offering a large potential for personalized therapeutic strategies. The enormous growth of this research area over the past decade with its capability for clinical translation makes a non-invasive, automated analysis pipeline of organoids highly desirable. This work presents a novel non-invasive approach to monitor and analyze cerebral organoids over time using high-field magnetic resonance imaging and state-of-the-art tools for automated image analysis. Three specific objectives are addressed, (I) organoid segmentation to investigate organoid development over time, (II) global cysticity classification and (III) local cyst segmentation for organoid quality assessment. We show that organoid growth can be monitored reliably over time and cystic and non-cystic organoids can be separated with high accuracy, with on par or better performance compared to state-of-the-art tools applied to brightfield imaging. Local cyst segmentation is feasible but could be further improved in the future. Overall, these results highlight the potential of the pipeline for clinical application to larger-scale comparative organoid analysis.

Ex vivo drug response profiling for response and outcome prediction in hematologic malignancies: the prospective non-interventional SMARTrial.

Ex vivo drug response profiling is a powerful tool to study genotype-drug response associations and is being explored as a tool set for precision medicine in cancer. Here we conducted a prospective non-interventional trial to investigate feasibility of ex vivo drug response profiling for treatment guidance in hematologic malignancies (SMARTrial, NCT03488641 ). The primary endpoint to provide drug response profiling reports within 7 d was met in 91% of all study participants (N = 80). Secondary endpoint analysis revealed that ex vivo resistance to chemotherapeutic drugs predicted chemotherapy treatment failure in vivo. We confirmed the predictive value of ex vivo response to chemotherapy in a validation cohort of 95 individuals with acute myeloid leukemia treated with daunorubicin and cytarabine. Ex vivo drug response profiles improved ELN-22 risk stratification in individuals with adverse risk. We conclude that ex vivo drug response profiling is clinically feasible and has the potential to predict chemotherapy response in individuals with hematologic malignancies beyond clinically established genetic markers.

NCT/DKFZ MASTER handbook of interpreting whole-genome, transcriptome, and methylome data for precision oncology.

Analysis of selected cancer genes has become an important tool in precision oncology but cannot fully capture the molecular features and, most importantly, vulnerabilities of individual tumors. Observational and interventional studies have shown that decision-making based on comprehensive molecular characterization adds significant clinical value. However, the complexity and heterogeneity of the resulting data are major challenges for disciplines involved in interpretation and recommendations for individualized care, and limited information exists on how to approach multilayered tumor profiles in clinical routine. We report our experience with the practical use of data from whole-genome or exome and RNA sequencing and DNA methylation profiling within the MASTER (Molecularly Aided Stratification for Tumor Eradication Research) program of the National Center for Tumor Diseases (NCT) Heidelberg and Dresden and the German Cancer Research Center (DKFZ). We cover all relevant steps of an end-to-end precision oncology workflow, from sample collection, molecular analysis, and variant prioritization to assigning treatment recommendations and discussion in the molecular tumor board. To provide insight into our approach to multidimensional tumor profiles and guidance on interpreting their biological impact and diagnostic and therapeutic implications, we present case studies from the NCT/DKFZ molecular tumor board that illustrate our daily practice. This manual is intended to be useful for physicians, biologists, and bioinformaticians involved in the clinical interpretation of genome-wide molecular information.

Signaling-induced systematic repression of miRNAs uncovers cancer vulnerabilities and targeted therapy sensitivity.

Targeted therapies are effective in treating cancer, but success depends on identifying cancer vulnerabilities. In our study, we utilize small RNA sequencing to examine the impact of pathway activation on microRNA (miRNA) expression patterns. Interestingly, we discover that miRNAs capable of inhibiting key members of activated pathways are frequently diminished. Building on this observation, we develop an approach that integrates a low-miRNA-expression signature to identify druggable target genes in cancer. We train and validate our approach in colorectal cancer cells and extend it to diverse cancer models using patient-derived in vitro and in vivo systems. Finally, we demonstrate its additional value to support genomic and transcriptomic-based drug prediction strategies in a pan-cancer patient cohort from the National Center for Tumor Diseases (NCT)/German Cancer Consortium (DKTK) Molecularly Aided Stratification for Tumor Eradication (MASTER) precision oncology trial. In conclusion, our strategy can predict cancer vulnerabilities with high sensitivity and accuracy and might be suitable for future therapy recommendations in a variety of cancer subtypes.

BRAFΔß3-αC in-frame deletion mutants differ in their dimerization propensity, HSP90 dependence, and druggability.

In-frame BRAF exon 12 deletions are increasingly identified in various tumor types. The resultant BRAFΔß3-αC oncoproteins usually lack five amino acids in the ß3-αC helix linker and sometimes contain de novo insertions. The dimerization status of BRAFΔß3-αC oncoproteins, their precise pathomechanism, and their direct druggability by RAF inhibitors (RAFi) has been under debate. Here, we functionally characterize BRAFΔLNVTAP>F and two novel mutants, BRAFdelinsFS and BRAFΔLNVT>F, and compare them with other BRAFΔß3-αC oncoproteins. We show that BRAFΔß3-αC oncoproteins not only form stable homodimers and large multiprotein complexes but also require dimerization. Nevertheless, details matter as aromatic amino acids at the deletion junction of some BRAFΔß3-αC oncoproteins, e.g., BRAFΔLNVTAP>F, increase their stability and dimerization propensity while conferring resistance to monomer-favoring RAFi such as dabrafenib or HSP 90/CDC37 inhibition. In contrast, dimer-favoring inhibitors such as naporafenib inhibit all BRAFΔß3-αC mutants in cell lines and patient-derived organoids, suggesting that tumors driven by such oncoproteins are vulnerable to these compounds.

Levodopa-refractory hyperprolactinemia and pituitary findings in inherited disorders of biogenic amine metabolism.

Elevated serum prolactin concentrations occur in inherited disorders of biogenic amine metabolism because dopamine deficiency leads to insufficient inhibition of prolactin secretion. This work from the International Working Group on Neurotransmitter Related Disorders (iNTD) presents the results of the first standardized study on levodopa-refractory hyperprolactinemia (LRHP; >1000 mU/L) and pituitary magnetic resonance imaging (MRI) abnormalities in patients with inherited disorders of biogenic amine metabolism. Twenty-six individuals had LRHP or abnormal pituitary findings on MRI. Tetrahydrobiopterin deficiencies were the most common diagnoses (n = 22). The median age at diagnosis of LRHP was 16 years (range: 2.5-30, 1st-3rd quartiles: 12.25-17 years). Twelve individuals (nine females) had symptoms attributed to hyperprolactinemia: menstruation-related abnormalities (n = 7), pubertal delay or arrest (n = 5), galactorrhea (n = 3), and decreased sexual functions (n = 2). MRI of the pituitary gland was obtained in 21 individuals; six had heterogeneity/hyperplasia of the gland, five had adenoma, and 10 had normal findings. Eleven individuals were treated with the dopamine agonist cabergoline, ameliorating the hyperprolactinemia-related symptoms in all those assessed. Routine monitoring of these symptoms together with prolactin concentrations, especially after the first decade of life, should be taken into consideration during follow-up evaluations. The potential of slow-release levodopa formulations and low-dose dopamine agonists as part of first-line therapy in the prevention and treatment of hyperprolactinemia should be investigated further in animal studies and human trials. This work adds hyperprolactinemia-related findings to the current knowledge of the phenotypic spectrum of inherited disorders of biogenic amine metabolism.

Outcome of immunotherapy in adrenocortical carcinoma: a retrospective cohort study.

OBJECTIVE: Clinical trials with immune checkpoint inhibitors (ICI) in adrenocortical carcinoma (ACC) have yielded contradictory results. We aimed to evaluate treatment response and safety of ICI in ACC in a real-life setting. DESIGN: Retrospective cohort study of 54 patients with advanced ACC receiving ICI as compassionate use at 6 German reference centres between 2016 and 2022. METHODS: Objective response rate (ORR), disease control rate (DCR), progression-free survival (PFS), overall survival (OS), and treatment-related adverse events (TRAE) were assessed. RESULTS: In 52 patients surviving at least 4 weeks after initiation of ICI, ORR was 13.5% (6-26) and DCR was 24% (16-41). PFS was 3.0 months (95% CI, 2.3-3.7). In all patients, median OS was 10.4 months (3.8-17). 17 TRAE occurred in 15 patients, which was associated with a longer PFS of 5.5 (1.9-9.2) vs 2.5 (2.0-3.0) months (HR 0.29, 95% CI, 0.13-0.66, P = 0.001) and OS of 28.2 (9.5-46.8) vs 7.0 (4.1-10.2) months (HR 0.34, 95% CI, 0.12-0.93). Positive tissue staining for programmed cell death ligand 1 (PD-L1) was associated with a longer PFS of 3.2 (2.6-3.8) vs 2.3 (1.6-3.0, P < 0.05) months. Adjusted for concomitant mitotane use, treatment with nivolumab was associated with lower risk of progression (HR 0.36, 0.15-0.90) and death (HR 0.20, 0.06-0.72) compared to pembrolizumab. CONCLUSIONS: In the real-life setting, we observe a response comparable to other second-line therapies and an acceptable safety profile in ACC patients receiving different ICI. The relevance of PD-L1 as a marker of response and the potentially more favourable outcome in nivolumab-treated patients require confirmation.

aRgus: Multilevel visualization of non-synonymous single nucleotide variants & advanced pathogenicity score modeling for genetic vulnerability assessment.

The widespread use of high-throughput sequencing techniques is leading to a rapidly increasing number of disease-associated variants of unknown significance and candidate genes. Integration of knowledge concerning their genetic, protein as well as functional and conservational aspects is necessary for an exhaustive assessment of their relevance and for prioritization of further clinical and functional studies investigating their role in human disease. To collect the necessary information, a multitude of different databases has to be accessed and data extraction from the original sources commonly is not user-friendly and requires advanced bioinformatics skills. This leads to a decreased data accessibility for a relevant number of potential users such as clinicians, geneticist, and clinical researchers. Here, we present aRgus (https://argus.urz.uni-heidelberg.de/), a standalone webtool for simple extraction and intuitive visualization of multi-layered gene, protein, variant, and variant effect prediction data. aRgus provides interactive exploitation of these data within seconds for any known gene of the human genome. In contrast to existing online platforms for compilation of variant data, aRgus complements visualization of chromosomal exon-intron structure and protein domain annotation with ClinVar and gnomAD variant distributions as well as position-specific variant effect prediction score modeling. aRgus thereby enables timely assessment of protein regions vulnerable to variation with single amino acid resolution and provides numerous applications in variant and protein domain interpretation as well as in the design of in vitro experiments.

Targeted therapy of advanced parathyroid carcinoma guided by genomic and transcriptomic profiling.

Parathyroid carcinoma (PC) is an ultra-rare malignancy with a high risk of recurrence after surgery. Tumour-directed systemic treatments for PC are not established. We used whole-genome and RNA sequencing in four patients with advanced PC to identify molecular alterations that could guide clinical management. In two cases, the genomic and transcriptomic profiles provided targets for experimental therapies that resulted in biochemical response and prolonged disease stabilization: (a) immune checkpoint inhibition with pembrolizumab based on high tumour mutational burden and a single-base substitution signature associated with APOBEC (apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like) overactivation; (b) multi-receptor tyrosine kinase inhibition with lenvatinib due to overexpression of FGFR1 (Fibroblast Growth Factor Receptor 1) and RET (Ret Proto-Oncogene) and, (c) later in the course of the disease, PARP (Poly(ADP-Ribose) Polymerase) inhibition with olaparib prompted by signs of defective homologous recombination DNA repair. In addition, our data provided new insights into the molecular landscape of PC with respect to the genome-wide footprints of specific mutational processes and pathogenic germline alterations. These data underscore the potential of comprehensive molecular analyses to improve care for patients with ultra-rare cancers based on insight into disease biology.

rGREAT: an R/bioconductor package for functional enrichment on genomic regions.

SUMMARY: GREAT (Genomic Regions Enrichment of Annotations Tool) is a widely used tool for functional enrichment on genomic regions. However, as an online tool, it has limitations of outdated annotation data, small numbers of supported organisms and gene set collections, and not being extensible for users. Here, we developed a new R/Bioconductorpackage named rGREAT which implements the GREAT algorithm locally. rGREAT by default supports more than 600 organisms and a large number of gene set collections, as well as self-provided gene sets and organisms from users. Additionally, it implements a general method for dealing with background regions. AVAILABILITY AND IMPLEMENTATION: The package rGREAT is freely available from the Bioconductor project: https://bioconductor.org/packages/rGREAT/. The development version is available at https://github.com/jokergoo/rGREAT. Gene Ontology gene sets for more than 600 organisms retrieved from Ensembl BioMart are presented in an R package BioMartGOGeneSets which is available at https://github.com/jokergoo/BioMartGOGeneSets. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Retained functional normal and preleukemic HSCs at diagnosis are associated with good prognosis in DNMT3AmutNPM1mut AMLs.

Acute myeloid leukemia (AML) is a heterogeneous disease characterized by high rate of relapse and mortality. Current chemotherapies whilst successful in eradicating blasts, are less effective in eliminating relapse-causing leukemic stem cells (LSCs). Although LSCs are usually identified as CD34+CD38- cells, there is significant heterogeneity in surface marker expression, and CD34- LSCs exist particularly in NPM1mut AMLs. By analyzing diagnostic primary DNMT3AmutNPM1mut AML samples, we suggest a novel flow cytometry sorting strategy particularly useful for CD34neg AML subtypes. To enrich for LSCs independently of CD34 status, positive selection for GPR56 and negative selection for NKG2D ligands are used. We show that the functional reconstitution capacity of CD34- and CD34+ LSCs as well as their transcriptomes are very similar which support phenotypic plasticity. Furthermore, we show that although CD34+ subpopulations can contain next to LSCs also normal and/or preleukemic hematopoietic stem cells (HSCs), this is not the case in CD34-GPR56+NKG2DL- enriched LSCs which thus can be isolated with high purity. Finally, we show that patients with AML, who retain at the time of diagnosis a reserve of normal and/or preleukemic HSCs in their bone marrow able to reconstitute immunocompromised mice, have significantly longer relapse-free and overall survival than patients with AML in whom functional HSCs are no longer detectable.

simplifyEnrichment: A Bioconductor Package for Clustering and Visualizing Functional Enrichment Results.

Functional enrichment analysis or gene set enrichment analysis is a basic bioinformatics method that evaluates the biological importance of a list of genes of interest. However, it may produce a long list of significant terms with highly redundant information that is difficult to summarize. Current tools to simplify enrichment results by clustering them into groups either still produce redundancy between clusters or do not retain consistent term similarities within clusters. We propose a new method named binary cut for clustering similarity matrices of functional terms. Through comprehensive benchmarks on both simulated and real-world datasets, we demonstrated that binary cut could efficiently cluster functional terms into groups where terms showed consistent similarities within groups and were mutually exclusive between groups. We compared binary cut clustering on the similarity matrices obtained from different similarity measures and found that semantic similarity worked well with binary cut, while similarity matrices based on gene overlap showed less consistent patterns. We implemented the binary cut algorithm in the R package simplifyEnrichment, which additionally provides functionalities for visualizing, summarizing, and comparing the clustering. The simplifyEnrichment package and the documentation are available at https://bioconductor.org/packages/simplifyEnrichment/.

Focal structural variants revealed by whole genome sequencing disrupt the histone demethylase KDM4C in B-cell lymphomas.

Histone methylation-modifiers, such as EZH2 and KMT2D, are recurrently altered in B-cell lymphomas. To comprehensively describe the landscape of alterations affecting genes encoding histone methylation-modifiers in lymphomagenesis we investigated whole genome and transcriptome data of 186 mature B-cell lymphomas sequenced in the ICGC MMML-Seq project. Besides confirming common alterations of KMT2D (47% of cases), EZH2 (17%), SETD1B (5%), PRDM9 (4%), KMT2C (4%), and SETD2 (4%), also identified by prior exome or RNA-sequencing studies, we here found recurrent alterations to KDM4C in chromosome 9p24, encoding a histone demethylase. Focal structural variation was the main mechanism of KDM4C alterations, and was independent from 9p24 amplification. We also identified KDM4C alterations in lymphoma cell lines including a focal homozygous deletion in a classical Hodgkin lymphoma cell line. By integrating RNA-sequencing and genome sequencing data we predict that KDM4C structural variants result in loss-offunction. By functional reconstitution studies in cell lines, we provide evidence that KDM4C can act as a tumor suppressor. Thus, we show that identification of structural variants in whole genome sequencing data adds to the comprehensive description of the mutational landscape of lymphomas and, moreover, establish KDM4C as a putative tumor suppressive gene recurrently altered in subsets of B-cell derived lymphomas.

Comparison of extraction methods for intracellular metabolomics of human tissues.

Analyses of metabolic compounds inside cells or tissues provide high information content since they represent the endpoint of biological information flow and are a snapshot of the integration of many regulatory processes. However, quantification of the abundance of metabolites requires their careful extraction. We present a comprehensive study comparing ten extraction protocols in four human sample types (liver tissue, bone marrow, HL60, and HEK cells) aiming to detect and quantify up to 630 metabolites of different chemical classes. We show that the extraction efficiency and repeatability are highly variable across protocols, tissues, and chemical classes of metabolites. We used different quality metrics including the limit of detection and variability between replicates as well as the sum of concentrations as a global estimate of analytical repeatability of the extraction. The coverage of extracted metabolites depends on the used solvents, which has implications for the design of measurements of different sample types and metabolic compounds of interest. The benchmark dataset can be explored in an easy-to-use, interactive, and flexible online resource (R/shiny app MetaboExtract: http://www.metaboextract.shiny.dkfz.de) for context-specific selection of the optimal extraction method. Furthermore, data processing and conversion functionality underlying the shiny app are accessible as an R package: https://cran.r-project.org/package=MetAlyzer.