Digital PCR cluster predictor: a universal R-package and shiny app for the automated analysis of multiplex digital PCR data.

Digital polymerase chain reaction (dPCR) is an emerging technology that enables accurate and sensitive quantification of nucleic acids. Most available dPCR systems have two channel optics, with ad hoc software limited to the analysis of single and duplex assays. Although multiplexing strategies were developed, variable assay designs, dPCR systems, and the analysis of low DNA input data restricted the ability for a universal automated clustering approach. To overcome these issues, we developed dPCR Cluster Predictor (dPCP), an R package and a Shiny app for automated analysis of up to 4-plex dPCR data. dPCP can analyse and visualize data generated by multiple dPCR systems carrying out accurate and fast clustering not influenced by the amount and integrity of input of nucleic acids. With the companion Shiny app, the functionalities of dPCP can be accessed through a web browser.

Genetic counselling legislation and practice in cancer in EU Member States.

BACKGROUND: Somatic and germline genetic alterations are significant drivers of cancer. Increasing integration of new technologies which profile these alterations requires timely, equitable and high-quality genetic counselling to facilitate accurate diagnoses and informed decision-making by patients and their families in preventive and clinical settings. This article aims to provide an overview of genetic counselling legislation and practice across European Union (EU) Member States to serve as a foundation for future European recommendations and action. METHODS: National legislative databases of all 27 Member States were searched using terms relevant to genetic counselling, translated as appropriate. Interviews with relevant experts from each Member State were conducted to validate legislative search results and provide detailed insights into genetic counselling practice in each country. RESULTS: Genetic counselling is included in national legislative documents of 22 of 27 Member States, with substantial variation in legal mechanisms and prescribed details (i.e. the 'who, what, when and where' of counselling). Practice is similarly varied. Workforce capacity (25 of 27 Member States) and genetic literacy (all Member States) were common reported barriers. Recognition and/or better integration of genetic counsellors and updated legislation and were most commonly noted as the 'most important change' which would improve practice. CONCLUSIONS: This review highlights substantial variability in genetic counselling across EU Member States, as well as common barriers notwithstanding this variation. Future recommendations and action should focus on addressing literacy and capacity challenges through legislative, regulatory and/or strategic approaches at EU, national, regional and/or local levels.

XAB2 promotes Ku eviction from single-ended DNA double-strand breaks independently of the ATM kinase.

Replication-associated single-ended DNA double-strand breaks (seDSBs) are repaired predominantly through RAD51-mediated homologous recombination (HR). Removal of the non-homologous end-joining (NHEJ) factor Ku from resected seDSB ends is crucial for HR. The coordinated actions of MRE11-CtIP nuclease activities orchestrated by ATM define one pathway for Ku eviction. Here, we identify the pre-mRNA splicing protein XAB2 as a factor required for resistance to seDSBs induced by the chemotherapeutic alkylator temozolomide. Moreover, we show that XAB2 prevents Ku retention and abortive HR at seDSBs induced by temozolomide and camptothecin, via a pathway that operates in parallel to the ATM-CtIP-MRE11 axis. Although XAB2 depletion preserved RAD51 focus formation, the resulting RAD51-ssDNA associations were unproductive, leading to increased NHEJ engagement in S/G2 and genetic instability. Overexpression of RAD51 or RAD52 rescued the XAB2 defects and XAB2 loss was synthetically lethal with RAD52 inhibition, providing potential perspectives in cancer therapy.

Understanding the new BRD4-related syndrome: Clinical and genomic delineation with an international cohort study.

BRD4 is part of a multiprotein complex involved in loading the cohesin complex onto DNA, a fundamental process required for cohesin-mediated loop extrusion and formation of Topologically Associating Domains. Pathogenic variations in this complex have been associated with a growing number of syndromes, collectively known as cohesinopathies, the most classic being Cornelia de Lange syndrome. However, no cohort study has been conducted to delineate the clinical and molecular spectrum of BRD4-related disorder. We formed an international collaborative study, and collected 14 new patients, including two fetuses. We performed phenotype and genotype analysis, integrated prenatal findings from fetopathological examinations, phenotypes of pediatric patients and adults. We report the first cohort of patients with BRD4-related disorder and delineate the dysmorphic features at different ages. This work extends the phenotypic spectrum of cohesinopathies and characterize a new clinically relevant and recognizable pattern, distinguishable from the other cohesinopathies.

Different Effects of RNAi-Mediated Downregulation or Chemical Inhibition of NAMPT in an Isogenic IDH Mutant and Wild-Type Glioma Cell Model.

The IDH1R132H mutation in glioma results in the neoenzymatic function of IDH1, leading to the production of the oncometabolite 2-hydroxyglutarate (2-HG), alterations in energy metabolism and changes in the cellular redox household. Although shifts in the redox ratio NADPH/NADP+ were described, the consequences for the NAD+ synthesis pathways and potential therapeutic interventions were largely unexplored. Here, we describe the effects of heterozygous IDH1R132H on the redox system in a CRISPR/Cas edited glioblastoma model and compare them with IDH1 wild-type (IDH1wt) cells. Besides an increase in 2-HG and decrease in NADPH, we observed an increase in NAD+ in IDH1R132H glioblastoma cells. RT-qPCR analysis revealed the upregulation of the expression of the NAD+ synthesis enzyme nicotinamide phosphoribosyltransferase (NAMPT). Knockdown of NAMPT resulted in significantly reduced viability in IDH1R132H glioblastoma cells. Given this dependence of IDH1R132H cells on NAMPT expression, we explored the effects of the NAMPT inhibitors FK866, GMX1778 and GNE-617. Surprisingly, these agents were equally cytotoxic to IDH1R132H and IDH1wt cells. Altogether, our results indicate that targeting the NAD+ synthesis pathway is a promising therapeutic strategy in IDH mutant gliomas; however, the agent should be carefully considered since three small-molecule inhibitors of NAMPT tested in this study were not suitable for this purpose.

A mathematical model of the metastatic bottleneck predicts patient outcome and response to cancer treatment.

Metastases are the main reason for cancer-related deaths. Initiation of metastases, where newly seeded tumor cells expand into colonies, presents a tremendous bottleneck to metastasis formation. Despite its importance, a quantitative description of metastasis initiation and its clinical implications is lacking. Here, we set theoretical grounds for the metastatic bottleneck with a simple stochastic model. The model assumes that the proliferation-to-death rate ratio for the initiating metastatic cells increases when they are surrounded by more of their kind. For a total of 159,191 patients across 13 cancer types, we found that a single cell has an extremely low median probability of successful seeding of the order of 10-8. With increasing colony size, a sharp transition from very unlikely to very likely successful metastasis initiation occurs. The median metastatic bottleneck, defined as the critical colony size that marks this transition, was between 10 and 21 cells. We derived the probability of metastasis occurrence and patient outcome based on primary tumor size at diagnosis and tumor type. The model predicts that the efficacy of patient treatment depends on the primary tumor size but even more so on the severity of the metastatic bottleneck, which is estimated to largely vary between patients. We find that medical interventions aiming at tightening the bottleneck, such as immunotherapy, can be much more efficient than therapies that decrease overall tumor burden, such as chemotherapy.

Metabolomics, machine learning and immunohistochemistry to predict succinate dehydrogenase mutational status in phaeochromocytomas and paragangliomas.

Phaeochromocytomas and paragangliomas (PPGLs) are rare neuroendocrine tumours with a hereditary background in over one-third of patients. Mutations in succinate dehydrogenase (SDH) genes increase the risk for PPGLs and several other tumours. Mutations in subunit B (SDHB) in particular are a risk factor for metastatic disease, further highlighting the importance of identifying SDHx mutations for patient management. Genetic variants of unknown significance, where implications for the patient and family members are unclear, are a problem for interpretation. For such cases, reliable methods for evaluating protein functionality are required. Immunohistochemistry for SDHB (SDHB-IHC) is the method of choice but does not assess functionality at the enzymatic level. Liquid chromatography-mass spectrometry-based measurements of metabolite precursors and products of enzymatic reactions provide an alternative method. Here, we compare SDHB-IHC with metabolite profiling in 189 tumours from 187 PPGL patients. Besides evaluating succinate:fumarate ratios (SFRs), machine learning algorithms were developed to establish predictive models for interpreting metabolite data. Metabolite profiling showed higher diagnostic specificity compared to SDHB-IHC (99.2% versus 92.5%, p = 0.021), whereas sensitivity was comparable. Application of machine learning algorithms to metabolite profiles improved predictive ability over that of the SFR, in particular for hard-to-interpret cases of head and neck paragangliomas (AUC 0.9821 versus 0.9613, p = 0.044). Importantly, the combination of metabolite profiling with SDHB-IHC has complementary utility, as SDHB-IHC correctly classified all but one of the false negatives from metabolite profiling strategies, while metabolite profiling correctly classified all but one of the false negatives/positives from SDHB-IHC. From 186 tumours with confirmed status of SDHx variant pathogenicity, the combination of the two methods resulted in 185 correct predictions, highlighting the benefits of both strategies for patient management. © 2020 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

Patient-Derived Organoids of Cholangiocarcinoma.

Cholangiocarcinoma (CC) is an aggressive malignancy with an inferior prognosis due to limited systemic treatment options. As preclinical models such as CC cell lines are extremely rare, this manuscript reports a protocol of cholangiocarcinoma patient-derived organoid culture as well as a protocol for the transition of 3D organoid lines to 2D cell lines. Tissue samples of non-cancer bile duct and cholangiocarcinoma were obtained during surgical resection. Organoid lines were generated following a standardized protocol. 2D cell lines were generated from established organoid lines following a novel protocol. Subcutaneous and orthotopic patient-derived xenografts were generated from CC organoid lines, histologically examined, and treated using standard CC protocols. Therapeutic responses of organoids and 2D cell lines were examined using standard CC agents. Next-generation exome and RNA sequencing was performed on primary tumors and CC organoid lines. Patient-derived organoids closely recapitulated the original features of the primary tumors on multiple levels. Treatment experiments demonstrated that patient-derived organoids of cholangiocarcinoma and organoid-derived xenografts can be used for the evaluation of novel treatments and may therefore be used in personalized oncology approaches. In summary, this study establishes cholangiocarcinoma organoids and organoid-derived cell lines, thus expanding translational research resources of cholangiocarcinoma.

Patient-derived organoids and orthotopic xenografts of primary and recurrent gliomas represent relevant patient avatars for precision oncology.

Patient-based cancer models are essential tools for studying tumor biology and for the assessment of drug responses in a translational context. We report the establishment a large cohort of unique organoids and patient-derived orthotopic xenografts (PDOX) of various glioma subtypes, including gliomas with mutations in IDH1, and paired longitudinal PDOX from primary and recurrent tumors of the same patient. We show that glioma PDOXs enable long-term propagation of patient tumors and represent clinically relevant patient avatars that retain histopathological, genetic, epigenetic, and transcriptomic features of parental tumors. We find no evidence of mouse-specific clonal evolution in glioma PDOXs. Our cohort captures individual molecular genotypes for precision medicine including mutations in IDH1, ATRX, TP53, MDM2/4, amplification of EGFR, PDGFRA, MET, CDK4/6, MDM2/4, and deletion of CDKN2A/B, PTCH, and PTEN. Matched longitudinal PDOX recapitulate the limited genetic evolution of gliomas observed in patients following treatment. At the histological level, we observe increased vascularization in the rat host as compared to mice. PDOX-derived standardized glioma organoids are amenable to high-throughput drug screens that can be validated in mice. We show clinically relevant responses to temozolomide (TMZ) and to targeted treatments, such as EGFR and CDK4/6 inhibitors in (epi)genetically defined subgroups, according to MGMT promoter and EGFR/CDK status, respectively. Dianhydrogalactitol (VAL-083), a promising bifunctional alkylating agent in the current clinical trial, displayed high therapeutic efficacy, and was able to overcome TMZ resistance in glioblastoma. Our work underscores the clinical relevance of glioma organoids and PDOX models for translational research and personalized treatment studies and represents a unique publicly available resource for precision oncology.

Controlling distinct signaling states in cultured cancer cells provides a new platform for drug discovery.

Cancer cells can switch between signaling pathways to regulate growth under different conditions. In the tumor microenvironment, this likely helps them evade therapies that target specific pathways. We must identify all possible states and utilize them in drug screening programs. One such state is characterized by expression of the transcription factor Hairy and Enhancer of Split 3 (HES3) and sensitivity to HES3 knockdown, and it can be modeled in vitro. Here, we cultured 3 primary human brain cancer cell lines under 3 different culture conditions that maintain low, medium, and high HES3 expression and characterized gene regulation and mechanical phenotype in these states. We assessed gene expression regulation following HES3 knockdown in the HES3-high conditions. We then employed a commonly used human brain tumor cell line to screen Food and Drug Administration (FDA)-approved compounds that specifically target the HES3-high state. We report that cells from multiple patients behave similarly when placed under distinct culture conditions. We identified 37 FDA-approved compounds that specifically kill cancer cells in the high-HES3-expression conditions. Our work reveals a novel signaling state in cancer, biomarkers, a strategy to identify treatments against it, and a set of putative drugs for potential repurposing.-Poser, S. W., Otto, O., Arps-Forker, C., Ge, Y., Herbig, M., Andree, C., Gruetzmann, K., Adasme, M. F., Stodolak, S., Nikolakopoulou, P., Park, D. M., Mcintyre, A., Lesche, M., Dahl, A., Lennig, P., Bornstein, S. R., Schroeck, E., Klink, B., Leker, R. R., Bickle, M., Chrousos, G. P., Schroeder, M., Cannistraci, C. V., Guck, J., Androutsellis-Theotokis, A. Controlling distinct signaling states in cultured cancer cells provides a new platform for drug discovery.

Network-based analysis of prostate cancer cell lines reveals novel marker gene candidates associated with radioresistance and patient relapse.

Radiation therapy is an important and effective treatment option for prostate cancer, but high-risk patients are prone to relapse due to radioresistance of cancer cells. Molecular mechanisms that contribute to radioresistance are not fully understood. Novel computational strategies are needed to identify radioresistance driver genes from hundreds of gene copy number alterations. We developed a network-based approach based on lasso regression in combination with network propagation for the analysis of prostate cancer cell lines with acquired radioresistance to identify clinically relevant marker genes associated with radioresistance in prostate cancer patients. We analyzed established radioresistant cell lines of the prostate cancer cell lines DU145 and LNCaP and compared their gene copy number and expression profiles to their radiosensitive parental cells. We found that radioresistant DU145 showed much more gene copy number alterations than LNCaP and their gene expression profiles were highly cell line specific. We learned a genome-wide prostate cancer-specific gene regulatory network and quantified impacts of differentially expressed genes with directly underlying copy number alterations on known radioresistance marker genes. This revealed several potential driver candidates involved in the regulation of cancer-relevant processes. Importantly, we found that ten driver candidates from DU145 (ADAMTS9, AKR1B10, CXXC5, FST, FOXL1, GRPR, ITGA2, SOX17, STARD4, VGF) and four from LNCaP (FHL5, LYPLAL1, PAK7, TDRD6) were able to distinguish irradiated prostate cancer patients into early and late relapse groups. Moreover, in-depth in vitro validations for VGF (Neurosecretory protein VGF) showed that siRNA-mediated gene silencing increased the radiosensitivity of DU145 and LNCaP cells. Our computational approach enabled to predict novel radioresistance driver gene candidates. Additional preclinical and clinical studies are required to further validate the role of VGF and other candidate genes as potential biomarkers for the prediction of radiotherapy responses and as potential targets for radiosensitization of prostate cancer.

Human gastric cancer modelling using organoids.

OBJECTIVE: Gastric cancer is the second leading cause of cancer-related deaths and the fifth most common malignancy worldwide. In this study, human and mouse gastric cancer organoids were generated to model the disease and perform drug testing to delineate treatment strategies. DESIGN: Human gastric cancer organoid cultures were established, samples classified according to their molecular profile and their response to conventional chemotherapeutics tested. Targeted treatment was performed according to specific druggable mutations. Mouse gastric cancer organoid cultures were generated carrying molecular subtype-specific alterations. RESULTS: Twenty human gastric cancer organoid cultures were established and four selected for a comprehensive in-depth analysis. Organoids demonstrated divergent growth characteristics and morphologies. Immunohistochemistry showed similar characteristics to the corresponding primary tissue. A divergent response to 5-fluoruracil, oxaliplatin, irinotecan, epirubicin and docetaxel treatment was observed. Whole genome sequencing revealed a mutational spectrum that corresponded to the previously identified microsatellite instable, genomic stable and chromosomal instable subtypes of gastric cancer. The mutational landscape allowed targeted therapy with trastuzumab for ERBB2 alterations and palbociclib for CDKN2A loss. Mouse cancer organoids carrying Kras and Tp53 or Apc and Cdh1 mutations were characterised and serve as model system to study the signalling of induced pathways. CONCLUSION: We generated human and mouse gastric cancer organoids modelling typical characteristics and altered pathways of human gastric cancer. Successful interference with activated pathways demonstrates their potential usefulness as living biomarkers for therapy response testing.

Metabolome-guided genomics to identify pathogenic variants in isocitrate dehydrogenase, fumarate hydratase, and succinate dehydrogenase genes in pheochromocytoma and paraganglioma.

PURPOSE: Metabolic aberrations have been described in neoplasms with pathogenic variants (PV) in the Krebs cycle genes encoding succinate dehydrogenase (SDH), fumarate hydratase (FH) and isocitrate dehydrogenase (IDH). In turn, accumulation of oncometabolites succinate, fumarate, and 2-hydroxyglutarate can be employed to identify tumors with those PV . Additionally, such metabolic readouts may aid in genetic variant interpretation and improve diagnostics. METHODS: Using liquid chromatography-mass spectrometry, 395 pheochromocytomas and paragangliomas (PPGLs) from 391 patients were screened for metabolites to indicate Krebs cycle aberrations. Multigene panel sequencing was applied to detect driver PV in cases with indicative metabolite profiles but undetermined genetic drivers. RESULTS: Aberrant Krebs cycle metabolomes identified rare cases of PPGLs with germline PV in FH and somatic PV in IDHx and SDHx, including the first case of a somatic IDH2 PV in PPGL. Metabolomics also reliably identified PPGLs with SDHx loss-of-function (LOF) PV. Therefore we utilized tumor metabolite profiles to further classify variants of unknown significance in SDHx, thereby enabling missense variants associated with SDHx LOF to be distinguished from benign variants. CONCLUSION: We propose incorporation of metabolome data into the diagnostics algorithm in PPGLs to guide genetic testing and variant interpretation and to help identify rare cases with PV in FH and IDHx.

Targeted capture-based NGS is superior to multiplex PCR-based NGS for hereditary BRCA1 and BRCA2 gene analysis in FFPE tumor samples.

BACKGROUND: With the introduction of Olaparib treatment for BRCA-deficient recurrent ovarian cancer, testing for somatic and/or germline mutations in BRCA1/2 genes in tumor tissues became essential for treatment decisions. In most cases only formalin-fixed paraffin-embedded (FFPE) samples, containing fragmented and chemically modified DNA of minor quality, are available. Thus, multiplex PCR-based sequencing is most commonly applied in routine molecular testing, which is predominantly focused on the identification of known hot spot mutations in oncogenes. METHODS: We compared the overall performance of an adjusted targeted capture-based enrichment protocol and a multiplex PCR-based approach for calling of pathogenic SNVs and InDels using DNA extracted from 13 FFPE tissue samples. We further applied both strategies to seven blood samples and five matched FFPE tumor tissues of patients with known germline exon-spanning deletions and gene-wide duplications in BRCA1/2 to evaluate CNV detection based solely on panel NGS data. Finally, we analyzed DNA from FFPE tissues of 11 index patients from families suspected of having hereditary breast and ovarian cancer, of whom no blood samples were available for testing, in order to identify underlying pathogenic germline BRCA1/2 mutations. RESULTS: The multiplex PCR-based protocol produced inhomogeneous coverage among targets of each sample and between samples as well as sporadic amplicon drop out, leading to insufficiently or non-covered nucleotides, which subsequently hindered variant detection. This protocol further led to detection of PCR-artifacts that could easily have been misinterpreted as pathogenic mutations. No such limitations were observed by application of an adjusted targeted capture-based protocol, which allowed for CNV calling with 86% sensitivity and 100% specificity. All pathogenic CNVs were confirmed in the five matched FFPE tumor samples from patients carrying known pathogenic germline mutations and we additionally identified somatic loss of the second allele in BRCA1/2. Furthermore we detected pathogenic BRCA1/2 variants in four the eleven FFPE samples from patients of whom no blood was available for analysis. CONCLUSIONS: We demonstrate that an adjusted targeted capture-based enrichment protocol is superior to commonly applied multiplex PCR-based protocols for reliable BRCA1/2 variant detection, including CNV-detection, using FFPE tumor samples.

The contribution of homology arms to nuclease-assisted genome engineering.

Designer nucleases like CRISPR/Cas9 enable fluent site-directed damage or small mutations in many genomes. Strategies for their use to achieve more complex tasks like regional exchanges for gene humanization or the establishment of conditional alleles are still emerging. To optimize Cas9-assisted targeting, we measured the relationship between targeting frequency and homology length in targeting constructs using a hypoxanthine-guanine phosphoribosyl-transferase assay in mouse embryonic stem cells. Targeting frequency with supercoiled plasmids improved steeply up to 2 kb total homology and continued to increase with even longer homology arms, thereby implying that Cas9-assisted targeting efficiencies can be improved using homology arms of 1 kb or greater. To humanize the Kmt2d gene, we built a hybrid mouse/human targeting construct in a bacterial artificial chromosome by recombineering. To simplify the possible outcomes, we employed a single Cas9 cleavage strategy and best achieved the intended 42 kb regional exchange with a targeting construct including a very long homology arm to recombine ∼42 kb away from the cleavage site. We recommend the use of long homology arm targeting constructs for accurate and efficient complex genome engineering, particularly when combined with the simplifying advantages of using just one Cas9 cleavage at the genome target site.

Identification and Functional Testing of ERCC2 Mutations in a Multi-national Cohort of Patients with Familial Breast- and Ovarian Cancer.

The increasing application of gene panels for familial cancer susceptibility disorders will probably lead to an increased proposal of susceptibility gene candidates. Using ERCC2 DNA repair gene as an example, we show that proof of a possible role in cancer susceptibility requires a detailed dissection and characterization of the underlying mutations for genes with diverse cellular functions (in this case mainly DNA repair and basic cellular transcription). In case of ERCC2, panel sequencing of 1345 index cases from 587 German, 405 Lithuanian and 353 Czech families with breast and ovarian cancer (BC/OC) predisposition revealed 25 mutations (3 frameshift, 2 splice-affecting, 20 missense), all absent or very rare in the ExAC database. While 16 mutations were unique, 9 mutations showed up repeatedly with population-specific appearance. Ten out of eleven mutations that were tested exemplarily in cell-based functional assays exert diminished excision repair efficiency and/or decreased transcriptional activation capability. In order to provide evidence for BC/OC predisposition, we performed familial segregation analyses and screened ethnically matching controls. However, unlike the recently published RECQL example, none of our recurrent ERCC2 mutations showed convincing co-segregation with BC/OC or significant overrepresentation in the BC/OC cohort. Interestingly, we detected that some deleterious founder mutations had an unexpectedly high frequency of > 1% in the corresponding populations, suggesting that either homozygous carriers are not clinically recognized or homozygosity for these mutations is embryonically lethal. In conclusion, we provide a useful resource on the mutational landscape of ERCC2 mutations in hereditary BC/OC patients and, as our key finding, we demonstrate the complexity of correct interpretation for the discovery of "bonafide" breast cancer susceptibility genes.

Comparative analysis of histologically classified oligodendrogliomas reveals characteristic molecular differences between subgroups.

BACKGROUND: Molecular data of histologically classified oligodendrogliomas are available offering the possibility to stratify these human brain tumors into clinically relevant molecular subtypes. METHODS: Gene copy number, mutation, and expression data of 193 histologically classified oligodendrogliomas from The Cancer Genome Atlas (TCGA) were analyzed by well-established computational approaches (unsupervised clustering, statistical testing, network inference). RESULTS: We applied hierarchical clustering to tumor gene copy number profiles and revealed three molecular subgroups within histologically classified oligodendrogliomas. We further screened these subgroups for molecular glioma markers (1p/19q co-deletion, IDH mutation, gain of chromosome 7 and loss of chromosome 10) and found that our subgroups largely resemble known molecular glioma subtypes. We excluded glioblastoma-like tumors (7a10d subgroup) and derived a gene expression signature distinguishing histologically classified oligodendrogliomas with concurrent 1p/19q co-deletion and IDH mutation (1p/19q subgroup) from those with predominant IDH mutation alone (IDHme subgroup). Interestingly, many signature genes were part of signaling pathways involved in the regulation of cell proliferation, differentiation, migration, and cell-cell contacts. We further learned a gene regulatory network associated with the gene expression signature revealing novel putative major regulators with functions in cytoskeleton remodeling (e.g. APBB1IP, VAV1, ARPC1B), apoptosis (CCNL2, CREB3L1), and neural development (e.g. MYTIL, SCRT1, MEF2C) potentially contributing to the manifestation of differences between both subgroups. Moreover, we revealed characteristic expression differences of several HOX and SOX transcription factors suggesting the activity of different glioma stemness programs in both subgroups. CONCLUSIONS: We show that gene copy number profiles alone are sufficient to derive molecular subgroups of histologically classified oligodendrogliomas that are well-embedded into general glioma classification schemes. Moreover, our revealed novel putative major regulators and characteristic stemness signatures indicate that different developmental programs might be active in these subgroups, providing a basis for future studies.

Nivolumab maintenance after salvage autologous stem cell transplantation results in long-term remission in multiple relapsed primary CNS lymphoma.

Recurrence of primary central nervous system lymphoma (PCNSL) after high-dose chemotherapy with autologous stem cell transplantation (ASCT) usually has a poor overall prognosis with limited treatment options. Data on repeated ASCT are sparse. Checkpoint inhibitor maintenance therapy has also not been reported in PCNSL. Here, we report the first documented case of a successful third ASCT in second relapse of PCNSL. Whole-exome sequencing identified a hypermutated tumor genotype. Additionally, immunohistochemistry on pretreatment tumor tissue revealed infiltrates of PD-1+ cytolytic T cells. These alterations provided a rationale for subsequent nivolumab maintenance treatment. Therapy led to a long-term, ongoing complete remission. In eligible patients with recurrent MTX-sensitive PCNSL, multiple long-term remissions can be induced by repetition of high-dose MTX-based chemotherapy followed by autologous retransplantation. Subsequent immune checkpoint inhibitor maintenance therapy might be able to prolong or maintain remission.

Precision oncology based on omics data: The NCT Heidelberg experience.

Precision oncology implies the ability to predict which patients will likely respond to specific cancer therapies based on increasingly accurate, high-resolution molecular diagnostics as well as the functional and mechanistic understanding of individual tumors. While molecular stratification of patients can be achieved through different means, a promising approach is next-generation sequencing of tumor DNA and RNA, which can reveal genomic alterations that have immediate clinical implications. Furthermore, certain genetic alterations are shared across multiple histologic entities, raising the fundamental question of whether tumors should be treated by molecular profile and not tissue of origin. We here describe MASTER (Molecularly Aided Stratification for Tumor Eradication Research), a clinically applicable platform for prospective, biology-driven stratification of younger adults with advanced-stage cancer across all histologies and patients with rare tumors. We illustrate how a standardized workflow for selection and consenting of patients, sample processing, whole-exome/genome and RNA sequencing, bioinformatic analysis, rigorous validation of potentially actionable findings, and data evaluation by a dedicated molecular tumor board enables categorization of patients into different intervention baskets and formulation of evidence-based recommendations for clinical management. Critical next steps will be to increase the number of patients that can be offered comprehensive molecular analysis through collaborations and partnering, to explore ways in which additional technologies can aid in patient stratification and individualization of treatment, to stimulate clinically guided exploratory research projects, and to gradually move away from assessing the therapeutic activity of targeted interventions on a case-by-case basis toward controlled clinical trials of genomics-guided treatments.

Chromosomal instability induced by increased BIRC5/Survivin levels affects tumorigenicity of glioma cells.

BACKGROUND: Survivin, belonging to the inhibitor of apoptosis (IAP) gene family, is abundantly expressed in tumors. It has been hypothesized that Survivin facilitates carcinogenesis by inhibition of apoptosis resulting in improved survival of tumorigenic progeny. Additionally, Survivin plays an essential role during mitosis. Together with its molecular partners Aurora B, Borealin and inner centromere protein it secures bipolar chromosome segregation. However, whether increased Survivin levels contribute to progression of tumors by inducing chromosomal instability remains unclear. METHODS: We overexpressed Survivin in U251-MG, SVGp12, U87-MG, HCT116 and p53-deficient U87-MGshp53 and HCT116p53-/- cells. The resulting phenotype was investigated by FACS-assisted cell cycle analysis, Western Blot analysis, confocal laser scan microscopy, proliferation assays, spectral karyotyping and in a U251-MG xenograft model using immune-deficient mice. RESULTS: Overexpression of Survivin affected cells with knockdown of p53, cells harboring mutant p53 and SV40 large T antigen, respectively, resulting in the increase of cell fractions harboring 4n and >4n DNA contents. Increased γH2AX levels, indicative of DNA damage were monitored in all Survivin-transduced cell lines, but only in p53 wild type cells this was accompanied by an attenuated S-phase entry and activation of p21waf/cip. Overexpression of Survivin caused a DNA damage response characterized by increased appearance pDNA-PKcs foci in cell nuclei and elevated levels of pATM S1981 and pCHK2 T68. Additionally, evolving structural chromosomal aberrations in U251-MG cells transduced with Survivin indicated a DNA-repair by non-homologous end joining recombination. Subcutaneous transplantation of U251-MG cells overexpressing Survivin and mycN instead of mycN oncogene alone generated tumors with shortened latency and decreased apoptosis. Subsequent SKY-analysis of Survivin/mycN-tumors revealed an increase in structural chromosomal aberrations in cells when compared to mycN-tumors. CONCLUSIONS: Our data suggest that increased Survivin levels promote adaptive evolution of tumors through combining induction of genetic heterogeneity with inhibition of apoptosis.