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.

Plexin-B2 and Semaphorins Do Not Drive Rhabdomyosarcoma Proliferation or Migration.

Rhabdomyosarcoma (RMS) is the most common pediatric soft tissue sarcoma for which subsets of patients have longstanding unmet clinical needs. For example, children with alveolar rhabdomyosarcoma and metastases at diagnosis will experience only 8% disease-free 5-year survival for nonlocalized unresectable recurrent disease. Hence, development of novel therapeutic strategies is urgently needed to improve outcomes. The Plexin-Semaphorin pathway is largely unexplored for sarcoma research. However, emerging interest in the Plexin-Semaphorin signaling axis in pediatric sarcomas has led to phase I cooperative group dose-finding clinical trials, now completed (NCT03320330). In this study, we specifically investigated the protein expression of transmembrane receptor Plexin-B2 and its cognate SEMA4C ligands in clinical RMS tumors and cell models. By RNA interferences, we assessed the role of Plexin-B2 in cell growth and cell migration ability in selected alveolar and embryonal RMS cell model systems. Our results affirmed expression of Plexin-B2 across human samples, while also dissecting expression of the different protein subunits of Plexin-B2 along with the assessment of preferred Semaphorin ligands of Plexin-B2. Plexin-B2 knockdown had positive or negative effects on cell growth, which varied by cell model system. Migration assayed after Plexin-B2 knockdown revealed selective cell line specific migration inhibition, which was independent of Plexin-B2 expression level. Overall, these findings are suggestive of context-specific and possibly patient-specific (stochastic) role of Plexin-B2 and SEMA4 ligands in RMS.

SMARCA4 biology in alveolar rhabdomyosarcoma.

Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma in children and phenocopies a muscle precursor that fails to undergo terminal differentiation. The alveolar subtype (ARMS) has the poorest prognosis and represents the greatest unmet medical need for RMS. Emerging evidence supports the role of epigenetic dysregulation in RMS. Here we show that SMARCA4/BRG1, an ATP-dependent chromatin remodeling enzyme of the SWI/SNF complex, is prominently expressed in primary tumors from ARMS patients and cell cultures. Our validation studies for a CRISPR screen of 400 epigenetic targets identified SMARCA4 as a unique factor for long-term (but not short-term) tumor cell survival in ARMS. A SMARCA4/SMARCA2 protein degrader (ACBI-1) demonstrated similar long-term tumor cell dependence in vitro and in vivo. These results credential SMARCA4 as a tumor cell dependency factor and a therapeutic target in ARMS.

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.

Linear mRNA amplification from as little as 5 ng total RNA for global gene expression analysis.

Gene expression analysis has become an invaluable tool for understanding gene function and regulation. However, global expression analysis requires large RNA quantities or RNA preamplification. We describe an isothermal messenger RNA (mRNA) amplification method, Ribo-SPIA, which generates micrograms of labeled cDNA from 5 ng of total RNA in 1 day for analysis on arrays or by PCR quantification. Highly reproducible GeneChip array performance (R2 > 0.95) was achieved with independent reactions starting with 5-100 ng Universal Human Reference total RNA. Targets prepared by the Ribo-SPIA procedure (20 ng total RNA input) or the Affymetrix Standard Protocol (10 microg total RNA) perform similarly, as indicated by gene call concordance (86%) and good correlation of differential gene expression determination (R2 = 0.82). Accuracy of transcript representation in cDNA generated by the Ribo-SPIA procedure was also demonstrated by PCR quantification of 33 transcripts, comparing differential expression in amplified and nonamplified cDNA (R2 = 0.97 over a range of nearly 10(6) infold change). Thus Ribo-SPIA amplification of mRNA is rapid, robust, highly accurate and reproducible, and sensitive enough to allow quantification of very low abundance transcripts.