Biology subjects

Marchetto, A.

Publications and source records attributed to Marchetto, A..

13 recordsLinked to original sources

bioRxiv2025

Robust statistical assessment of Oncogenotype to Organotropism translation in xenografted zebrafish

Organotropism results from the functional versatility of metastatic cancer cells to survive and proliferate in diverse microenvironments. This adaptivity can originate in clonal variation of the spreading tumor and is often empowered by epigenetic and molecular reprogramming of cell regulatory circuits. Related to organotropic colonization of metastatic sites are environmentally-sensitive, differential responses of cancer cells to therapeutic attack. Accordingly, understanding the organotropic profile of a cancer and probing the underlying driver mechanisms are of high clinical importance. However, determining systematically the organotropism of one cancer versus the organotropism of another cancer, potentially with the granularity of comparing the same cancer type between patients or tracking the evolution of a cancer in a single patient for the purpose of personalized treatment, has remained very challenging. It requires a host organism that allows observation of the spreading pattern over relatively short experimental times. Moreover, organotropic patterns often tend to be statistically weak and superimposed by experimental variation. Thus, an assay for organotropism must give access to statistical powers that can separate meaningful heterogeneity, i.e., heterogeneity that determines organotropism, from meaningless heterogeneity, i.e., heterogeneity that causes experimental noise. Here we describe an experimental workflow that leverages the physiological properties of zebrafish larvae for an imaging-based assessment of organotropic patterns over a time-frame of 3 days. The workflow incorporates computer vision pipelines to automatically integrate the stochastic spreading behavior of a particular cancer xenograft in tens to hundreds of larvae allowing subtle trends in the colonization of particular organs to emerge above random cell depositions throughout the host organism. We validate our approach with positive control experiments comparing the spreading patterns of a metastatic sarcoma against non-transformed fibroblasts and the spreading patterns of two melanoma cell lines with previously established differences in metastatic propensity. We then show that integration of the spreading pattern of xenografts in 40 - 50 larvae is necessary and sufficient to generate a Fish Metastatic Atlas page that is representative of the organotropism of a particular oncogenotype and experimental condition. Finally, we apply the power of this assay to determine the function of the EWSR1::FLI1 fusion oncogene and its transcriptional target SOX6 as plasticity factors that enhance the adaptive capacity of metastatic Ewing sarcoma.

cancer biology↗

bioRxiv2022

Modeling the Orthosteric Binding Site of the G Protein-Coupled Odorant Receptor OR5K1

With approximately 400 encoding genes in humans, odorant receptors (ORs) are the largest subfamily of class A G protein-coupled receptors (GPCRs). Despite its high relevance and representation, the odorant-GPCRome is structurally poorly characterized: no experimental structures are available, and the low sequence identity of ORs to experimentally solved GPCRs is a significant challenge for their modeling. Moreover, the receptive range of most ORs is unknown. The odorant receptor OR5K1 was recently and comprehensively characterized in terms of cognate agonists. Here we report two additional agonists and functional data of the most potent compound on two mutants, L1043.32 and L2556.51. Experimental data was used to guide the investigation of the binding modes of OR5K1 ligands into the orthosteric binding site using structural information from AI-driven modeling, as recently released in the AlphaFold Protein Structure Database, and from homology modeling. Induced-fit docking simulations were used to sample the binding site conformational space for ensemble docking. Mutagenesis data guided side chain residue sampling and model selection. We obtained models that could better rationalize the different activity of active (agonist) versus inactive molecules with respect to starting models, and also capture differences in activity related to minor structural differences. Therefore, we provide a model refinement protocol that can be applied to model the orthosteric binding site of ORs as well as that of GPCRs with low sequence identity to available templates.

molecular biology↗

bioRxiv2021

Systematic multi-omics cell line profiling uncovers principles of Ewing sarcoma fusion oncogene-mediated gene regulation

Cell lines have been essential for major discoveries in cancer including Ewing sarcoma (EwS). EwS is a highly aggressive pediatric bone or soft-tissue cancer characterized by oncogenic EWSR1-ETS fusion transcription factors converting polymorphic GGAA-microsatellites (mSats) into neo-enhancers. However, further detailed mechanistic evaluation of gene regulation in EwS have been hindered by the limited number of well-characterized cell line models. Here, we present the Ewing Sarcoma Cell Line Atlas (ESCLA) comprising 18 EwS cell lines with inducible EWSR1-ETS knockdown that were profiled by whole-genome-sequencing, DNA methylation arrays, gene expression and splicing arrays, mass spectrometry-based proteomics, and ChIP-seq for EWSR1-ETS and histone marks. Systematic analysis of these multi-dimensional data illuminated hundreds of new potential EWSR1-ETS target genes, the nature of EWSR1-ETS-preferred GGAA-mSats, and potential indirect modes of EWSR1-ETS-mediated gene regulation. Moreover, we identified putative co-regulatory transcription factors and heterogeneously regulated EWSR1-ETS target genes that may have implications for the clinical heterogeneity of EwS. Collectively, our freely available ESCLA constitutes an extremely rich resource for EwS research and highlights the power of leveraging multidimensional and comprehensive datasets to unravel principles of heterogeneous gene regulation by dominant fusion oncogenes.

genomics↗

bioRxiv2021

Translational evidence for RRM2 as a prognostic biomarker and therapeutic target in Ewing sarcoma

PurposeEwing sarcoma (EwS) is a highly aggressive bone- or soft tissue-associated malignancy mostly affecting children, adolescents, and young adults. Although multimodal therapies have strongly improved patients overall survival over the past decades, the development of prognostic biomarkers for risk-based patient stratification and more effective therapies with less adverse effects is stagnating. Thus, new personalized medicine approaches are urgently required. Experimental designGene expression data of EwS and normal tissues were crossed with survival data to identify highly overexpressed, prognostically relevant, and actionable potential targets. RNA-interference and dose-response assays as well as tissue-microarray analyses were carried out to explore the functional role and druggability of a prominent candidate gene in vitro and in vivo, and to validate its suitability as a prognostic biomarker. ResultsEmploying a multilayered screening approach, we discover ribonucleotide reductase regulatory subunit M2 (RRM2) as a promising therapeutic target and prognostic biomarker in EwS. Through analysis of two independent EwS patient cohorts, we show that RRM2 mRNA and protein overexpression is associated with an aggressive clinical phenotype and poor patients overall survival. In agreement, RRM2 silencing as well as pharmacological inhibition by the specific inhibitor triapine (3-AP) significantly reduces EwS growth in vitro and in vivo. Furthermore, we present evidence that pharmacological RRM2 inhibition by triapine can overcome chemoresistance against doxorubicin or gemcitabine, and synergize with cell cycle checkpoint inhibitors (CHEK1 or WEE1). ConclusionsBased on the aggressive phenotype mediated by and the druggability of RRM2 our results provide a translational rationale for exploiting RRM2 as a novel therapeutic target in EwS and prompt further clinical investigations.

cancer biology↗

bioRxiv2021

Systems biology analysis identifies TCF7L1 as a key regulator of metastasis in Ewing sarcoma

Identification of cancer stemness genes is crucial to understanding the underlying biology of therapy resistance, relapse, and metastasis. Ewing sarcoma (EwS) is the second most common bone tumor in children and adolescents. It is a highly aggressive cancer associated with a dismal survival rate (<30%) for patients with metastatic disease at diagnosis ([~]25% of cases). Hence, deciphering the underlying mechanisms of metastasis is imperative. EwS tumors are characterized by a remarkably silent genome with a single driver mutation generating an oncogenic fusion transcription factor (EWSR1-ETS). Thus, EwS constitutes an ideal model to study how perturbation of a transcriptional network by a dominant oncogene can mediate metastasis, even though canonical metastasis-associated genes are not mutated. Here, through the implementation of an integrative systems biology approach, we identified transcription factor 7 like 1 (TCF7L1, alias TCF3) as a prognostically-relevant and EWSR1-ETS suppressed determinant of metastasis in EwS. We demonstrated that conditional TCF7L1 re-expression significantly reduces EwS single-cell migration, invasion and anchorage-independent growth in 3D assays in vitro, and tumorigenesis in vivo mediated by its DNA binding domain. In primary EwS tumors as well as in functional orthotopic in vivo models, low TCF7L1 expression was associated with pro-metastatic gene signatures and a much higher migratory and metastatic capacity of EwS cells, which correlated with poor outcome of EwS patients. Collectively, our findings establish TCF7L1 as a major regulator of metastasis in EwS, which may be utilized as a prognostic biomarker and open inroads to future therapeutic intervention.

cancer biology↗

bioRxiv2019

Oncogenic hijacking of a developmental transcription factor evokes therapeutic vulnerability for ROS-induction in Ewing sarcoma

Ewing sarcoma (EwS) is an aggressive childhood cancer likely originating from mesenchymal stem cells or osteo-chondrogenic progenitors. It is characterized by fusion oncoproteins involving EWSR1 and variable members of the ETS-family of transcription factors (in 85% FLI1). EWSR1-FLI1 can induce target genes by using GGAA-microsatellites (mSats) as enhancers.\n\nHere, we show that EWSR1-FLI1 hijacks the developmental transcription factor SOX6 - a physiological driver of proliferation of osteo-chondrogenic progenitors - by binding to an intronic GGAA-mSat, which promotes EwS growth in vitro and in vivo. Through integration of transcriptome-profiling, published drug-screening data, and functional in vitro and in vivo experiments, we discovered that SOX6 interferes with the antioxidant system resulting in constitutively elevated reactive oxygen species (ROS) levels that create a therapeutic vulnerability toward the ROS-inducing drug Elesclomol.\n\nCollectively, our results exemplify how aberrant activation of a developmental transcription factor by a dominant oncogene can promote malignancy, but provide opportunities for targeted therapy.

cancer biology↗

bioRxiv2019

Biomarker-based outcome prediction in prostate adenocarcinoma depends on the TMPRSS2-ERG status

BackgroundProstate adenocarcinoma (PCa) with/without the TMPRSS2-ERG (T2E)-fusion represent distinct molecular subtypes. ObjectiveTo investigate gene-signatures associated with metastasis in T2E-positive and -negative PCa, and to identify and validate subtype-specific prognostic biomarkers. Design, setting and participantsGene expression and clinicopathological data of two discovery PCa cohorts (total n=783) were separately analyzed regarding the T2E-status. Selected subtype-specific biomarkers were validated in two additional cohorts (total n=405). Outcome measurements and statistical analysisFrom both discovery cohorts, we generated two gene lists ranked by their differential intratumoral expression in patients with/without metastases stratified by T2E-status, which were subjected to gene set enrichment and leading-edge analyses. The resulting top 20 gene-signatures of both gene lists associated with metastasis were analyzed for overlaps between T2E-positive and -negative cases. Genes shared by several functional gene-signatures were tested for their association with event-free survival using the Kaplan-Meier method in a validation cohort. Immunohistochemistry was performed in another validation cohort. Results and limitationsMetastatic T2E-positive and -negative PCa are characterized by different gene-signatures. Five genes (ASPN, BGN, COL1A1, RRM2 and TYMS) were identified whose high expression was significantly associated with worse outcome exclusively in T2E-negative PCa. This was validated in an independent cohort for all genes and additionally for RRM2 by immunohistochemistry in a separate validation cohort. No prognostic biomarkers were identified exclusively for T2E-positive tumors. ConclusionsOur study demonstrates that the prognostic value of biomarkers critically depends on the molecular subtype, i.e. the T2E-status, which should be considered when screening for and applying novel prognostic biomarkers for outcome prediction in PCa. Patient summaryOutcome prediction for PCa is complex. The results of this study highlight that the validity of prognostic biomarkers depends on the molecular subtype, specifically the presence/absence of T2E. The reported new subtype-specific biomarkers exemplify that biomarker-based outcome prediction in PCa should consider the T2E-status.

cancer biology↗

bioRxiv2018

Cooperation of dominant oncogenes with regulatory germline variants shapes clinical outcomes in childhood cancer

INTRODUCTORY PARAGRAPHDeciphering principles of inter-individual tumor heterogeneity is essential for refinement of personalized anti-cancer therapy. Unlike cancers of adulthood, pediatric malignancies including Ewing sarcoma (EwS) feature a striking paucity of somatic alterations except for pathognomonic driver-mutations that cannot explain overt variations in clinical outcome.\n\nHere we demonstrate in the EwS model how cooperation of a dominant oncogene and regulatory variants determine tumor growth, patient survival and drug response.\n\nWe show that binding of the oncogenic EWSR1-FLI1 fusion transcription factor to a polymorphic enhancer-like DNA element controls expression of the transcription factor MYBL2, whose high expression promotes poor patient outcome via activation of pro-proliferative signatures. Analysis of paired germline and tumor whole-genome sequencing data revealed that regulatory variability at this locus is inherited via the germline. CRISPR-mediated interference with this regulatory element almost abolished MYBL2 transcription, and MYBL2 knockdown decreased cell proliferation, cell survival and tumorigenicity of EwS cells. Combined RNA- and ChIP-seq analyses as well as functional experiments and clinical data identified CCNF, BIRC5 and AURKB as direct MYBL2 targets and critical mediators of its phenotype. In drug-response experiments, high MYBL2 levels sensitized EwS cells for inhibition of its activating cyclin dependent kinase CDK2 in vitro and in vivo, suggesting MYBL2 as a predictive biomarker for targeted anti-CDK2-therapy.\n\nCollectively, our findings establish cooperation of somatic mutations and regulatory germline variants as a major determinant of tumor progression and indicate the importance of integrating the regulatory genome in the process of developing new diagnostic and/or therapeutic strategies to fully harness the potential of precision medicine.

cancer biology↗

bioRxiv2018

SOX2 expression identifies Ewing sarcoma patients with high risk for tumor relapse and poor survival

Purpose: Up to 30-40% of Ewing sarcoma (EwS) patients with non-metastatic disease develop local or metastatic relapse within a time range of 2-10 years. This is in part caused by the absence of prognostic biomarkers that can identify high-risk patients to assign them to risk-adapted monitoring and treatment regimens. Since cancer stemness has been associated with tumor relapse and poor outcome, we investigated in the current study the prognostic potential SOX2 (sex determining region Y box 2) - a major transcription factor involved in development and stemness - previously described to contribute to the undifferentiated phenotype of EwS. Methods: Two independent patient cohorts, one consisting of 189 retrospectively collected EwS tumors with corresponding mRNA expression data (test cohort) and the other of 141 prospectively collected formalin-fixed and paraffin embedded resected tumors (validation cohort), were employed to analyze SOX2 expression levels by DNA microarrays or immunohistochemistry, respectively, and to compare them with clinical parameters and patient outcome. Two methods were employed to test the validity of the results at both mRNA and protein levels. Results: Both cohorts showed that only a subset of EwS patients (16-20%) express high SOX2 mRNA or protein levels, which significantly correlated with poor overall survival. Multivariate analyses of our validation cohort revealed that high SOX2 expression represents a major risk factor for survival (HR=3.19; P<0.01) that is independent from metastasis and other known clinical risk-factors at time of diagnosis. Univariate analysis demonstrated that SOX2-high expression correlated with tumor relapse (P=0.001). Median first relapse was at 14.7 months (range: 3.5-180.7). Conclusions: High SOX2 expression constitutes an independent prognostic biomarker for EwS patients with poor outcome, which may help to identify patients with localized disease who are at high risk for tumor relapse within the first two years after diagnosis.

pathology↗

bioRxiv2018

Targeting the CALCB/RAMP1-axis inhibits growth of Ewing sarcoma

Ewing sarcoma (EwS) is an aggressive cancer caused by chromosomal translocations generating fusions of the EWSR1 gene with ETS transcription factors (in 85% FLI1). EWSR1-FLI1 induces gene expression via binding to enhancer-like GGAA-microsatellites, whose activity increases with the number of consecutive GGAA-repeats.\n\nHerein, we investigate the role of the secretory neuropeptide CALCB (calcitonin related polypeptide {beta}) in EwS, which signals via the CGRP-(calcitonin gene-related peptide) receptor complex, containing RAMP1 (receptor activity modifying protein 1) as crucial part for receptor specificity. Analysis of 2,678 gene expression microarrays comprising 50 tumor entities and 71 normal tissue types revealed that CALCB is specifically and highly overexpressed in EwS. Time-course knockdown experiments showed that CALCB expression is tightly linked to that of EWSR1-FLI1. Consistently, gene set enrichment analyses of genes whose expression in primary EwS is correlated to that of CALCB indicated that it is co-expressed with other EWSR1-FLI1 target genes and associated with signatures involved in stemness and proliferation. Chromatin immunoprecipitation followed by sequencing (ChIP-seq) data for EWSR1-FLI1 and histone marks from EwS cells demonstrated that EWSR1-FLI1 binds to a GGAA-microsatellite close to CALCB, which exhibits characteristics of an active enhancer. Reporter assays confirmed the strong EWSR1-FLI1- and length-dependent enhancer activity of this GGAA-microsatellite. Mass-spectrometry analyses of supernatants of EwS cell cultures demonstrated that CALCB is secreted by EwS cells. While short-term RNA interference-mediated CALCB knockdown had no effect on proliferation and clonogenic growth of EwS cells in vitro, its long-term knockdown decreased EwS growth in vitro and in vivo. Similarly, knockdown of RAMP1 reduced clonogenic/spheroidal growth and tumorigenicity, and small-molecule inhibitors directed against the CGRP-receptor comprising RAMP1 reduced growth of EwS.\n\nCollectively, our findings suggest that CALCB is a direct EWSR1-FLI1 target and that targeting the CALCB/RAMP1-axis may offer a new therapeutic strategy for inhibition of EwS growth.

cancer biology↗

bioRxiv2018

Functional genomics identifies AMPD2 as a new prognostic marker for undifferentiated pleomorphic sarcoma

Soft-tissue sarcomas are rare, heterogeneous and often aggressive mesenchymal cancers. Many of them are associated with poor outcome, in part because biomarkers that can reliably identify high-risk patients are lacking. Studies on sarcomas often are limited by small sample sizes rendering the identification of novel biomarkers difficult when focusing only on individual cohorts. However, the increasing number of publicly available omics data opens inroads to overcome this obstacle.\n\nHere, we combine high-throughput transcriptome analyses, immunohistochemistry, and functional assays to show that high adenosine monophosphate deaminase 2 (AMPD2) is a robust prognostic biomarker for worse patient outcome in undifferentiated pleomorphic sarcoma (UPS). Publicly available gene expression and survival data for UPS from two independent studies, The Cancer Genome Atlas (TCGA) and the CINSARC reference dataset, were subjected to survival association testing. Genes, whose high expression was significantly correlated with worse outcome in both cohorts (overall and metastasis-free survival), were considered as prognostic marker candidates. The best candidate, AMPD2, was validated on protein level in an independent tissue microarray. Analysis of DNA copy-number and matched gene expression data indicated that high AMPD2 expression is significantly correlated with copy-number gains at the AMPD2 locus. Gene-set enrichment analyses of AMPD2 co-expressed genes in both UPS gene expression datasets suggested that highly AMPD2 expressing tumors are enriched in gene signatures involved in tumorigenesis. Consistent with this prediction in primary tumors, knockdown of AMPD2 by RNA interference with pooled siRNAs or a doxycycline-inducible shRNA construct in the UPS cell line FPS-1 markedly inhibited proliferation in vitro and tumorigenicity in vivo.\n\nCollectively, these results provide evidence that AMPD2 may serve as a novel biomarker for outcome prediction in UPS. Our study exemplifies how the integration of available omics data, immunohistochemical analyses, and functional experiments can identify novel biomarkers even in a rare sarcoma, which may serve as a blueprint for biomarker identification for other rare cancers.

pathology↗

bioRxiv2017

Systematic identification of cancer-specific MHC-binding peptides with RAVEN

Immunotherapy can revolutionize anti-cancer therapy if specific targets are available. Recurrent somatic mutations in the exome can create highly specific neo-antigens. However, especially pediatric cancers are oligo-mutated and hardly exhibit recurrent neo-antigens. Yet, immunogenic peptides encoded by cancer-specific genes (CSGs), which are virtually not expressed in normal tissues, may enable a targeted immunotherapy of such cancers. Here, we describe an algorithm and provide a user-friendly software named RAVEN (Rich Analysis of Variable gene Expressions in Numerous tissues), which automatizes the systematic and fast identification of CSG-encoded peptides highly affine to Major Histocompatibility Complexes (MHC) starting from publicly available gene expression data. We applied RAVEN to a dataset assembled from more than 2,700 simultaneously normalized gene expression microarrays comprising 50 tumor entities, with a focus on sarcomas and pediatric cancers, and 71 normal tissue types. RAVEN performed a transcriptome-wide scan in each cancer entity for gender-specific CSGs. As a proof-of-concept we identified several established CSGs, but also many novel candidates potentially suitable for targeting multiple cancer types. The specific expression of the most promising CSGs was validated by qRT-PCR in cancer cell lines and by immunohistochemistry in a comprehensive tissue-microarray comprising 412 samples. Subsequently, RAVEN identified likely immunogenic peptides encoded by these CSGs by predicting the affinity to MHCs. Putative highly affine peptides were automatically crosschecked with the UniProt protein-database to exclude sequence identity with abundantly expressed proteins. The predicted affinity of selected peptides was validated in T2-cell peptide-binding assays in which many showed similar kinetics to a very immunogenic influenza control peptide.\n\nCollectively, we provide a comprehensive, exquisitely curated and validated catalogue of cancer-specific and highly MHC-affine peptides across 50 cancer entities. In addition, we developed an intuitive and freely available software to easily apply our algorithm to any gene expression dataset (https://github.com/JSGerke/RAVENsoftware). We anticipate that our peptide libraries and software constitute a rich resource to accelerate the development of novel immunotherapies.

immunology↗

bioRxiv2017

Robust diagnosis of Ewing sarcoma by immunohistochemical detection of super-enhancer-driven EWSR1-ETS targets

Ewing sarcoma is an undifferentiated bone-associated cancer. Although molecular detection of pathognomonic EWSR1-ETS fusions such as EWSR1-FLI1 enables definitive diagnosis, substantial confusion can arise if molecular diagnostics are unavailable. Diagnosis based solely on the conventional immunohistochemical marker CD99 is unreliable due to its abundant expression in morphological mimics. This study aimed to identify novel diagnostic immunohistochemical markers for Ewing sarcoma.\n\nWe analyzed 768 expression microarrays representing 21 tumor entities including Ewing-like sarcomas to nominate candidate biomarkers. These candidates were validated by immunohistochemistry (IHC) in a tissue microarray (TMA) comprising 174 samples. Microarray, chromatin immunoprecipitation and sequencing (ChIP-Seq) data, and reporter assays were employed to analyze their EWSR1-FLI1-dependency.\n\nOur comparative expression analyses revealed that ATP1A1, BCL11B, and GLG1 constitute specific markers for Ewing sarcoma. Analysis of ChIP-Seq and microarray datasets showed that their expression is EWSR1-FLI1-dependent. This outcome corresponded to EWSR1-FLI1-binding to proximal super-enhancers, which showed high activity in reporter assays. Consistently, high ATP1A1, BCL11B, and GLG1 expressions were detected by IHC. Automated cut-off-finding and combination-testing in the TMA demonstrated that detection of high BCL11B and/or GLG1 expression is sufficient to reach 96% specificity for Ewing sarcoma. While 88% of tested Ewing-like sarcomas displayed strong CD99-immunoreactivity, none displayed combined high expression of BCL11B and GLG1.\n\nCollectively, we provide evidence that ATP1A1, BCL11B, and GLG1 are EWSR1-FLI1 targets, of which BCL11B and GLG1 offer a fast, simple and cost-efficient way to diagnose Ewing sarcoma by IHC. We anticipate that these markers will significantly reduce the number of misdiagnosed patients, and thus improve patient care.

pathology↗