Functional genomics of human clear cell sarcoma: genomic, transcriptomic and chemical biology landscape for clear cell sarcoma.

BACKGROUND: Systemic therapy for metastatic clear cell sarcoma (CCS) bearing EWSR1-CREB1/ATF1 fusions remains an unmet clinical need in children, adolescents, and young adults. METHODS: To identify key signaling pathway vulnerabilities in CCS, a multi-pronged approach was taken: (i) genomic and transcriptomic landscape analysis, (ii) integrated chemical biology interrogations, (iii) development of CREB1/ATF1 inhibitors, and (iv) antibody-drug conjugate testing (ADC). The first approach encompassed DNA exome and RNA deep sequencing of the largest human CCS cohort yet reported consisting of 47 patient tumor samples and 8 cell lines. RESULTS: Sequencing revealed recurrent mutations in cell cycle checkpoint, DNA double-strand break repair or DNA mismatch repair genes, with a correspondingly low to intermediate tumor mutational burden. DNA multi-copy gains with corresponding high RNA expression were observed in CCS tumor subsets. CCS cell lines responded to the HER3 ADC patritumab deruxtecan in a dose-dependent manner in vitro, with impaired long term cell viability. CONCLUSION: These studies of the genomic, transcriptomic and chemical biology landscape represent a resource 'atlas' for the field of CCS investigation and drug development. CHK inhibitors are identified as having potential relevance, CREB1 inhibitors non-dependence of CCS on CREB1 activity was established, and the potential utility of HER3 ADC being used in CCS is found.

Sensitization of osteosarcoma to irradiation by targeting nuclear FGFR1.

Over the past 25 years, chemotherapy regimens for osteosarcoma have failed to improve the 65-70% long-term survival rate. Radiation therapy is generally ineffective except for palliative care. We here investigated whether osteosarcoma can be sensitized to radiation therapy targeting specific molecules in osteosarcoma. Large-scale RNA sequencing analysis in osteosarcoma tissues and cell lines revealed that FGFR1 is the most frequently expressed receptor tyrosine kinase in osteosarcoma. Nuclear FGFR1 (nFGFR1) was observed by subcellular localization assays. The functional studies using a FGFR1IIIb antibody or small molecule FGFR1 inhibitors showed that nFGFR1, but not membrane-bound FGFR1, induces G2 cell-cycle checkpoint adaptation, cell survival and polyploidy following irradiation in osteosarcoma cells. Further, the activation of nFGFR1 induces Histone H3 phosphorylation at Ser 10 and c-jun/c-fos expression to contribute cell survival rendering radiation resistance. Furthermore, an in vivo mouse study revealed that radiation resistance can be reversed by the inhibition of nFGFR1. Our findings provide insights into the potential role of nFGFR1 to radiation resistance. Thus, we propose nFGFR1 could be a potential therapeutic target or a biomarker to determine which patients might benefit from radiation therapy.

Machine learning for rhabdomyosarcoma histopathology.

Correctly diagnosing a rare childhood cancer such as sarcoma can be critical to assigning the correct treatment regimen. With a finite number of pathologists worldwide specializing in pediatric/young adult sarcoma histopathology, access to expert differential diagnosis early in case assessment is limited for many global regions. The lack of highly-trained sarcoma pathologists is especially pronounced in low to middle-income countries, where pathology expertise may be limited despite a similar rate of sarcoma incidence. To address this issue in part, we developed a deep learning convolutional neural network (CNN)-based differential diagnosis system to act as a pre-pathologist screening tool that quantifies diagnosis likelihood amongst trained soft-tissue sarcoma subtypes based on whole histopathology tissue slides. The CNN model is trained on a cohort of 424 centrally-reviewed histopathology tissue slides of alveolar rhabdomyosarcoma, embryonal rhabdomyosarcoma and clear-cell sarcoma tumors, all initially diagnosed at the originating institution and subsequently validated by central review. This CNN model was able to accurately classify the withheld testing cohort with resulting receiver operating characteristic (ROC) area under curve (AUC) values above 0.889 for all tested sarcoma subtypes. We subsequently used the CNN model to classify an externally-sourced cohort of human alveolar and embryonal rhabdomyosarcoma samples and a cohort of 318 histopathology tissue sections from genetically engineered mouse models of rhabdomyosarcoma. Finally, we investigated the overall robustness of the trained CNN model with respect to histopathological variations such as anaplasia, and classification outcomes on histopathology slides from untrained disease models. Overall positive results from our validation studies coupled with the limited worldwide availability of sarcoma pathology expertise suggests the potential of machine learning to assist local pathologists in quickly narrowing the differential diagnosis of sarcoma subtype in children, adolescents, and young adults.

Bromodomain 4 inhibition leads to MYCN downregulation in Wilms tumor.

BACKGROUND: Wilms tumor is the most common childhood kidney cancer. Two distinct histological subtypes of Wilms tumor have been described: tumors lacking anaplasia (the favorable subtype) and tumors displaying anaplastic features (the unfavorable subtype). Children with favorable disease generally have a very good prognosis, whereas those with anaplasia are oftentimes refractory to standard treatments and suffer poor outcomes, leading to an unmet clinical need. MYCN dysregulation has been associated with a number of pediatric cancers including Wilms tumor. PROCEDURES: In this context, we undertook a functional genomics approach to uncover novel therapeutic strategies for those patients with anaplastic Wilms tumor. Genomic analysis and in vitro experimentation demonstrate that cell growth can be reduced by modulating MYCN overexpression via bromodomain 4 (BRD4) inhibition in both anaplastic and nonanaplastic Wilms tumor models. RESULTS: We observed a time-dependent reduction of MYCN and MYCC protein levels upon BRD4 inhibition in Wilms tumor cell lines, which led to cell death and proliferation suppression. BRD4 inhibition significantly reduced tumor volumes in Wilms tumor patient-derived xenograft (PDX) mouse models. CONCLUSIONS: We suggest that AZD5153, a novel dual-BRD4 inhibitor, can reduce MYCN levels in both anaplastic and nonanaplastic Wilms tumor cell lines, reduces tumor volume in Wilms tumor PDXs, and should be further explored for its therapeutic potential.

Functional genomic analysis of epithelioid sarcoma reveals distinct proximal and distal subtype biology.

BACKGROUND: Metastatic epithelioid sarcoma (EPS) remains a largely unmet clinical need in children, adolescents and young adults despite the advent of EZH2 inhibitor tazemetostat. METHODS: In order to realise consistently effective drug therapies, a functional genomics approach was used to identify key signalling pathway vulnerabilities in a spectrum of EPS patient samples. EPS biopsies/surgical resections and cell lines were studied by next-generation DNA exome and RNA deep sequencing, then EPS cell cultures were tested against a panel of chemical probes to discover signalling pathway targets with the most significant contributions to EPS tumour cell maintenance. RESULTS: Other biologically inspired functional interrogations of EPS cultures using gene knockdown or chemical probes demonstrated only limited to modest efficacy in vitro. However, our molecular studies uncovered distinguishing features (including retained dysfunctional SMARCB1 expression and elevated GLI3, FYN and CXCL12 expression) of distal, paediatric/young adult-associated EPS versus proximal, adult-associated EPS. CONCLUSIONS: Overall results highlight the complexity of the disease and a limited chemical space for therapeutic advancement. However, subtle differences between the two EPS subtypes highlight the biological disparities between younger and older EPS patients and emphasise the need to approach the two subtypes as molecularly and clinically distinct diseases.

Refractory alveolar rhabdomyosarcoma in an 11-year-old male.

Rhabdomyosarcoma (RMS) is a mesenchymal malignancy phenocopying muscle and is among the leading causes of death from childhood cancer. Metastatic alveolar rhabdomyosarcoma is the most aggressive subtype with an 8% 5-yr disease-free survival rate when a chromosomal fusion is present and a 29% 5-yr disease-free survival rate when negative for a fusion event. The underlying biology of PAX-fusion-negative alveolar rhabdomyosarcoma remains largely unexplored and is exceedingly rare in Li-Fraumeni syndrome patients. Here, we present the case of an 11-yr-old male with fusion-negative alveolar rhabdomyosarcoma studied at end of life with a comprehensive functional genomics characterization, resulting in identification of potential therapeutic targets for broader investigation.

Defining the Extracellular Matrix of Rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is the most common soft-tissue sarcoma of childhood with a propensity to metastasize. Current treatment for patients with RMS includes conventional systemic chemotherapy, radiation therapy, and surgical resection; nevertheless, little to no improvement in long term survival has been achieved in decades-underlining the need for target discovery and new therapeutic approaches to targeting tumor cells or the tumor microenvironment. To evaluate cross-species sarcoma extracellular matrix production, we have used murine models which feature knowledge of the myogenic cell-of-origin. With focus on the RMS/undifferentiated pleomorphic sarcoma (UPS) continuum, we have constructed tissue microarrays of 48 murine and four human sarcomas to analyze expression of seven different collagens, fibrillins, and collagen-modifying proteins, with cross-correlation to RNA deep sequencing. We have uncovered that RMS produces increased expression of type XVIII collagen alpha 1 (COL18A1), which is clinically associated with decreased long-term survival. We have also identified significantly increased RNA expression of COL4A1, FBN2, PLOD1, and PLOD2 in human RMS relative to normal skeletal muscle. These results complement recent studies investigating whether soft tissue sarcomas utilize collagens, fibrillins, and collagen-modifying enzymes to alter the structural integrity of surrounding host extracellular matrix/collagen quaternary structure resulting in improved ability to improve the ability to invade regionally and metastasize, for which therapeutic targeting is possible.

Metastatic pediatric sclerosing epithelioid fibrosarcoma.

Sclerosing epithelioid fibrosarcoma (SEF) is a rare and aggressive soft-tissue sarcoma thought to originate in fibroblasts of the tissues comprising tendons, ligaments, and muscles. Minimally responsive to conventional cytotoxic chemotherapies, >50% of SEF patients experience local recurrence and/or metastatic disease. SEF is most commonly discovered in middle-aged and elderly adults, but also rarely in children. A common gene fusion occurring between the EWSR1 and CREB3L1 genes has been observed in 80%-90% of SEF cases. We describe here the youngest SEF patient reported to date (a 3-yr-old Caucasian male) who presented with numerous bony and lung metastases. Additionally, we perform a comprehensive literature review of all SEF-related articles published since the disease was first characterized. Finally, we describe the generation of an SEF primary cell line, the first such culture to be reported. The patient described here experienced persistent disease progression despite aggressive treatment including multiple resections, radiotherapy, and numerous chemotherapies and targeted therapeutics. Untreated and locally recurrent tumor and metastatic tissue were sequenced by whole-genome, whole-exome, and deep-transcriptome next-generation sequencing with comparison to a patient-matched normal blood sample. Consistent across all sequencing analyses was the disease-defining EWSR1-CREB3L1 fusion as a single feature consensus. We provide an analysis of our genomic findings and discuss potential therapeutic strategies for SEF.

Advancing clinical cohort selection with genomics analysis on a distributed platform.

The affordability of next-generation genomic sequencing and the improvement of medical data management have contributed largely to the evolution of biological analysis from both a clinical and research perspective. Precision medicine is a response to these advancements that places individuals into better-defined subsets based on shared clinical and genetic features. The identification of personalized diagnosis and treatment options is dependent on the ability to draw insights from large-scale, multi-modal analysis of biomedical datasets. Driven by a real use case, we premise that platforms that support precision medicine analysis should maintain data in their optimal data stores, should support distributed storage and query mechanisms, and should scale as more samples are added to the system. We extended a genomics-based columnar data store, GenomicsDB, for ease of use within a distributed analytics platform for clinical and genomic data integration, known as the ODA framework. The framework supports interaction from an i2b2 plugin as well as a notebook environment. We show that the ODA framework exhibits worst-case linear scaling for array size (storage), import time (data construction), and query time for an increasing number of samples. We go on to show worst-case linear time for both import of clinical data and aggregate query execution time within a distributed environment. This work highlights the integration of a distributed genomic database with a distributed compute environment to support scalable and efficient precision medicine queries from a HIPAA-compliant, cohort system in a real-world setting. The ODA framework is currently deployed in production to support precision medicine exploration and analysis from clinicians and researchers at UCLA David Geffen School of Medicine.

Defining an embryonal rhabdomyosarcoma endotype.

Rhabdomyosarcoma (RMS) is the most common childhood soft-tissue sarcoma. The largest subtype of RMS is embryonal rhabdomyosarcoma (ERMS) and accounts for 53% of all RMS. ERMS typically occurs in the head and neck region, bladder, or reproductive organs and portends a promising prognosis when localized; however, when metastatic the 5-yr overall survival rate is ∼43%. The genomic landscape of ERMS demonstrates a range of putative driver mutations, and thus the recognition of the pathological mechanisms driving tumor maintenance should be critical for identifying effective targeted treatments at the level of the individual patients. Here, we report genomic, phenotypic, and bioinformatic analyses for a case of a 3-yr-old male who presented with bladder ERMS. Additionally, we use an unsupervised agglomerative clustering analysis of RNA and whole-exome sequencing data across ERMS and undifferentiated pleomorphic sarcoma (UPS) tumor samples to determine several major endotypes inferring potential targeted treatments for a spectrum of pediatric ERMS patient cases.

In vitro benchmarking of NF-κB inhibitors.

Dysregulated activity of the transcription factors of the nuclear factor κb (NF-κB) family has been implicated in numerous cancer types, inflammatory diseases, autoimmune disease, and other disorders. As such, selective NF-κB pathway inhibition is an attractive target to researchers for preclinical and clinical drug development. A plethora of commercially and clinically available inhibitors claim to be NF-κB specific; however, such claims of specificity are rarely quantitative or benchmarked, making the biomedical literature difficult to contextualize. This imprecision is worsened because some NF-κB reporter systems have low signal-to-noise ratios. Herein, we use a robust, defined, commercially available reporter system to benchmark NF-κB agonists and antagonists for the field. We also functionally characterize a RELA fusion-positive ependymoma cell culture with validated NF-κB inhibitor compounds.

Volasertib preclinical activity in high-risk hepatoblastoma.

Relapsed and metastatic hepatoblastoma represents an unmet clinical need with limited chemotherapy treatment options. In a chemical screen, we identified volasertib as an agent with in vitro activity, inhibiting hepatoblastoma cell growth while sparing normal hepatocytes. Volasertib targets PLK1 and prevents the progression of mitosis, resulting in eventual cell death. PLK1 is overexpressed in hepatoblastoma biopsies relative to normal liver tissue. As a potential therapeutic strategy, we tested the combination of volasertib and the relapse-related hepatoblastoma chemotherapeutic irinotecan. We found both in vitro and in vivo efficacy of this combination, which may merit further preclinical investigation and exploration for a clinical trial concept.

Preclinical testing of the glycogen synthase kinase-3ß inhibitor tideglusib for rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is the most common childhood soft tissue sarcoma. RMS often arise from myogenic precursors and displays a poorly differentiated skeletal muscle phenotype most closely resembling regenerating muscle. GSK3ß is a ubiquitously expressed serine-threonine kinase capable of repressing the terminal myogenic differentiation program in cardiac and skeletal muscle. Recent unbiased chemical screening efforts have prioritized GSK3ß inhibitors as inducers of myodifferentiation in RMS, suggesting efficacy as single agents in suppressing growth and promoting self-renewal in zebrafish transgenic embryonal RMS (eRMS) models in vivo. In this study, we tested the irreversible GSK3ß-inhibitor, tideglusib for in vivo efficacy in patient-derived xenograft models of both alveolar rhabdomyosarcoma (aRMS) and eRMS. Tideglusib had effective on-target pharmacodynamic efficacy, but as a single agent had no effect on tumor progression or myodifferentiation. These results suggest that as monotherapy, GSK3ß inhibitors may not be a viable treatment for aRMS or eRMS.