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.

Elucidating the transcriptional program of feline injection-site sarcoma using a cross-species mRNA-sequencing approach.

BACKGROUND: Feline injection-site sarcoma (FISS), an aggressive iatrogenic subcutaneous malignancy, is challenging to manage clinically and little is known about the molecular basis of its pathogenesis. Tumor transcriptome profiling has proved valuable for gaining insights into the molecular basis of cancers and for identifying new therapeutic targets. Here, we report the first study of the FISS transcriptome and the first cross-species comparison of the FISS transcriptome with those of anatomically similar soft-tissue sarcomas in dogs and humans. METHODS: Using high-throughput short-read paired-end sequencing, we comparatively profiled FISS tumors vs. normal tissue samples as well as cultured FISS-derived cell lines vs. skin-derived fibroblasts. We analyzed the mRNA-seq data to compare cancer/normal gene expression level, identify biological processes and molecular pathways that are associated with the pathogenesis of FISS, and identify multimegabase genomic regions of potential somatic copy number alteration (SCNA) in FISS. We additionally conducted cross-species analyses to compare the transcriptome of FISS to those of soft-tissue sarcomas in dogs and humans, at the level of cancer/normal gene expression ratios. RESULTS: We found: (1) substantial differential expression biases in feline orthologs of human oncogenes and tumor suppressor genes suggesting conserved functions in FISS; (2) a genomic region with recurrent SCNA in human sarcomas that is syntenic to a feline genomic region of probable SCNA in FISS; and (3) significant overlap of the pattern of transcriptional alterations in FISS with the patterns of transcriptional alterations in soft-tissue sarcomas in humans and in dogs. We demonstrated that a protein, BarH-like homeobox 1 (BARX1), has increased expression in FISS cells at the protein level. We identified 11 drugs and four target proteins as potential new therapies for FISS, and validated that one of them (GSK-1059615) inhibits growth of FISS-derived cells in vitro. CONCLUSIONS: (1) Window-based analysis of mRNA-seq data can uncover SCNAs. (2) The transcriptome of FISS-derived cells is highly consistent with that of FISS tumors. (3) FISS is highly similar to soft-tissue sarcomas in dogs and humans, at the level of gene expression. This work underscores the potential utility of comparative oncology in improving understanding and treatment of FISS.

Probabilistic modeling of personalized drug combinations from integrated chemical screen and molecular data in sarcoma.

BACKGROUND: Cancer patients with advanced disease routinely exhaust available clinical regimens and lack actionable genomic medicine results, leaving a large patient population without effective treatments options when their disease inevitably progresses. To address the unmet clinical need for evidence-based therapy assignment when standard clinical approaches have failed, we have developed a probabilistic computational modeling approach which integrates molecular sequencing data with functional assay data to develop patient-specific combination cancer treatments. METHODS: Tissue taken from a murine model of alveolar rhabdomyosarcoma was used to perform single agent drug screening and DNA/RNA sequencing experiments; results integrated via our computational modeling approach identified a synergistic personalized two-drug combination. Cells derived from the primary murine tumor were allografted into mouse models and used to validate the personalized two-drug combination. Computational modeling of single agent drug screening and RNA sequencing of multiple heterogenous sites from a single patient's epithelioid sarcoma identified a personalized two-drug combination effective across all tumor regions. The heterogeneity-consensus combination was validated in a xenograft model derived from the patient's primary tumor. Cell cultures derived from human and canine undifferentiated pleomorphic sarcoma were assayed by drug screen; computational modeling identified a resistance-abrogating two-drug combination common to both cell cultures. This combination was validated in vitro via a cell regrowth assay. RESULTS: Our computational modeling approach addresses three major challenges in personalized cancer therapy: synergistic drug combination predictions (validated in vitro and in vivo in a genetically engineered murine cancer model), identification of unifying therapeutic targets to overcome intra-tumor heterogeneity (validated in vivo in a human cancer xenograft), and mitigation of cancer cell resistance and rewiring mechanisms (validated in vitro in a human and canine cancer model). CONCLUSIONS: These proof-of-concept studies support the use of an integrative functional approach to personalized combination therapy prediction for the population of high-risk cancer patients lacking viable clinical options and without actionable DNA sequencing-based therapy.

Combination therapy design for maximizing sensitivity and minimizing toxicity.

BACKGROUND: Design of personalized targeted therapies involve modeling of patient sensitivity to various drugs and drug combinations. Majority of studies evaluate the sensitivity of tumor cells to targeted drugs without modeling the effect of the drugs on normal cells. In this article, we consider the individual modeling of drug responses to tumor and normal cells and utilize them to design targeted combination therapies that maximize sensitivity over tumor cells and minimize toxicity over normal cells. RESULTS: The problem is formulated as maximizing sensitivity over tumor cell models while maintaining sensitivity below a threshold over normal cell models. We utilize the constrained structure of tumor proliferation models to design an accelerated lexicographic search algorithm for generating the optimal solution. For comparison purposes, we also designed two suboptimal search algorithms based on evolutionary algorithms and hill-climbing based techniques. Results over synthetic models and models generated from Genomics of Drug Sensitivity in Cancer database shows the ability of the proposed algorithms to arrive at optimal or close to optimal solutions in significantly lower number of steps as compared to exhaustive search. We also present the theoretical analysis of the expected number of comparisons required for the proposed Lexicographic search that compare favorably with the observed number of computations. CONCLUSIONS: The proposed algorithms provide a framework for design of combination therapy that tackles tumor heterogeneity while satisfying toxicity constraints.

Translational Aspects of Epithelioid Sarcoma: Current Consensus.

Epithelioid sarcoma (EpS) is an ultra-rare malignant soft-tissue cancer mostly affecting adolescents and young adults. EpS often exhibits an unfavorable clinical course with fatal outcome in ∼50% of cases despite aggressive multimodal therapies combining surgery, chemotherapy, and irradiation. EpS is traditionally classified in a more common, less aggressive distal (classic) type and a rarer aggressive proximal type. Both subtypes are characterized by a loss of nuclear INI1 expression, most often following homozygous deletion of its encoding gene, SMARCB1-a core subunit of the SWI/SNF chromatin remodeling complex. In 2020, the EZH2 inhibitor tazemetostat was the first targeted therapy approved for EpS, raising new hopes. Still, the vast majority of patients did not benefit from this drug or relapsed rapidly. Further, other recent therapeutic modalities, including immunotherapy, are only effective in a fraction of patients. Thus, novel strategies, specifically targeted to EpS, are urgently needed. To accelerate translational research on EpS and eventually boost the discovery and development of new diagnostic tools and therapeutic options, a vibrant translational research community has formed in past years and held two international EpS digital expert meetings in 2021 and 2023. This review summarizes our current understanding of EpS from the translational research perspective and points to innovative research directions to address the most pressing questions in the field, as defined by expert consensus and patient advocacy groups.

Feasibility of functional precision medicine for guiding treatment of relapsed or refractory pediatric cancers.

Children with rare, relapsed or refractory cancers often face limited treatment options, and few predictive biomarkers are available that can enable personalized treatment recommendations. The implementation of functional precision medicine (FPM), which combines genomic profiling with drug sensitivity testing (DST) of patient-derived tumor cells, has potential to identify treatment options when standard-of-care is exhausted. The goal of this prospective observational study was to generate FPM data for pediatric patients with relapsed or refractory cancer. The primary objective was to determine the feasibility of returning FPM-based treatment recommendations in real time to the FPM tumor board (FPMTB) within a clinically actionable timeframe (<4 weeks). The secondary objective was to assess clinical outcomes from patients enrolled in the study. Twenty-five patients with relapsed or refractory solid and hematological cancers were enrolled; 21 patients underwent DST and 20 also completed genomic profiling. Median turnaround times for DST and genomics were within 10 days and 27 days, respectively. Treatment recommendations were made for 19 patients (76%), of whom 14 received therapeutic interventions. Six patients received subsequent FPM-guided treatments. Among these patients, five (83%) experienced a greater than 1.3-fold improvement in progression-free survival associated with their FPM-guided therapy relative to their previous therapy, and demonstrated a significant increase in progression-free survival and objective response rate compared to those of eight non-guided patients. The findings from our proof-of-principle study illustrate the potential for FPM to positively impact clinical care for pediatric and adolescent patients with relapsed or refractory cancers and warrant further validation in large prospective studies. ClinicalTrials.gov registration: NCT03860376 .

A new approach for prediction of tumor sensitivity to targeted drugs based on functional data.

BACKGROUND: The success of targeted anti-cancer drugs are frequently hindered by the lack of knowledge of the individual pathway of the patient and the extreme data requirements on the estimation of the personalized genetic network of the patient's tumor. The prediction of tumor sensitivity to targeted drugs remains a major challenge in the design of optimal therapeutic strategies. The current sensitivity prediction approaches are primarily based on genetic characterizations of the tumor sample. We propose a novel sensitivity prediction approach based on functional perturbation data that incorporates the drug protein interaction information and sensitivities to a training set of drugs with known targets. RESULTS: We illustrate the high prediction accuracy of our framework on synthetic data generated from the Kyoto Encyclopedia of Genes and Genomes (KEGG) and an experimental dataset of four canine osteosarcoma tumor cultures following application of 60 targeted small-molecule drugs. We achieve a low leave one out cross validation error of <10% for the canine osteosarcoma tumor cultures using a drug screen consisting of 60 targeted drugs. CONCLUSIONS: The proposed framework provides a unique input-output based methodology to model a cancer pathway and predict the effectiveness of targeted anti-cancer drugs. This framework can be developed as a viable approach for personalized cancer therapy.

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.

Probabilistic Boolean Modeling of Pre-clinical Tumor Models for Biomarker Identification in Cancer Drug Development.

As high-throughput sequencing experiments become more widely used in pre-clinical and clinical settings, pharmacogenetic and pharmacogenomic biomarker development plays an increasingly important role in oncology drug development pipelines and programs. Consequently, computer-based learning approaches have entered into use at multiple stages in pre-clinical and clinical pipelines. However, few approaches are available to identify interpretable and implementable biomarkers of response early in the drug development process when only small pre-clinical data packages are available. To address the need for early-stage biomarker development using pre-clinical tumor models, we have adapted the previously published Probabilistic Target Inhibitor Map (PTIM) platform to the challenge of biomarker hypothesis development, and denoted this approach the Probabilistic Target Map-Biomarker (PTM-Biomarker). In this article, we detail the history and design philosophy of PTM-Biomarker, and present two case studies using the biomarker discovery tool to illustrate its utility in guiding cancer drug development. © 2021 Wiley Periodicals LLC.

Functional impact of a germline RET mutation in alveolar rhabdomyosarcoma.

Specific mutations in the RET proto-oncogene are associated with multiple endocrine neoplasia type 2A, a hereditary syndrome characterized by tumorigenesis in multiple glandular elements. In rare instances, MEN2A-associated germline RET mutations have also occurred with non-MEN2A associated cancers. One such germline mutant RET mutation occurred concomitantly in a young adult diagnosed with alveolar rhabdomyosarcoma, a pediatric and young adult soft-tissue cancer with a generally poor prognosis. Although tumor tissue samples were initially unable to provide a viable cell culture for study, tumor tissues were sequenced for molecular characteristics. Through a hierarchical clustering approach, the index case sample was matched to several genetically similar cell models, which were transformed to express the same mutant RET as the index case and used to explore potential therapeutic options for mutant RET-bearing alveolar rhabdomyosarcoma. We also determined whether the RET mutation associated with the index case caused synthetic lethality to select clinical agents. From our investigation, we did not identify synthetic lethality associated with the expression of that patient's RET variant, and overall we did not find experimental evidence for the role of RET in rhabdomyosarcoma progression.

Receptor-driven invasion profiles in diffuse intrinsic pontine glioma.

BACKGROUND: Diffuse intrinsic pontine glioma (DIPG) is a devastating pediatric cancer with unmet clinical need. DIPG is invasive in nature, where tumor cells interweave into the fiber nerve tracts of the pons making the tumor unresectable. Accordingly, novel approaches in combating the disease are of utmost importance and receptor-driven cell invasion in the context of DIPG is under-researched area. Here, we investigated the impact on cell invasion mediated by PLEXINB1, PLEXINB2, platelet growth factor receptor (PDGFR)α, PDGFRß, epithelial growth factor receptor (EGFR), activin receptor 1 (ACVR1), chemokine receptor 4 (CXCR4), and NOTCH1. METHODS: We used previously published RNA-sequencing data to measure gene expression of selected receptors in DIPG tumor tissue versus matched normal tissue controls (n = 18). We assessed protein expression of the corresponding genes using DIPG cell culture models. Then, we performed cell viability and cell invasion assays of DIPG cells stimulated with chemoattractants/ligands. RESULTS: RNA-sequencing data showed increased gene expression of receptor genes such as PLEXINB2, PDGFRα, EGFR, ACVR1, CXCR4, and NOTCH1 in DIPG tumors compared to the control tissues. Representative DIPG cell lines demonstrated correspondingly increased protein expression levels of these genes. Cell viability assays showed minimal effects of growth factors/chemokines on tumor cell growth in most instances. Recombinant SEMA4C, SEM4D, PDGF-AA, PDGF-BB, ACVA, CXCL12, and DLL4 ligand stimulation altered invasion in DIPG cells. CONCLUSIONS: We show that no single growth factor-ligand pair universally induces DIPG cell invasion. However, our results reveal a potential to create a composite of cytokines or anti-cytokines to modulate DIPG cell invasion.

Design considerations of an IL13Rα2 antibody-drug conjugate for diffuse intrinsic pontine glioma.

Diffuse intrinsic pontine glioma (DIPG), a rare pediatric brain tumor, afflicts approximately 350 new patients each year in the United States. DIPG is noted for its lethality, as fewer than 1% of patients survive to five years. Multiple clinical trials involving chemotherapy, radiotherapy, and/or targeted therapy have all failed to improve clinical outcomes. Recently, high-throughput sequencing of a cohort of DIPG samples identified potential therapeutic targets, including interleukin 13 receptor subunit alpha 2 (IL13Rα2) which was expressed in multiple tumor samples and comparably absent in normal brain tissue, identifying IL13Rα2 as a potential therapeutic target in DIPG. In this work, we investigated the role of IL13Rα2 signaling in progression and invasion of DIPG and viability of IL13Rα2 as a therapeutic target through the use of immunoconjugate agents. We discovered that IL13Rα2 stimulation via canonical ligands demonstrates minimal impact on both the cellular proliferation and cellular invasion of DIPG cells, suggesting IL13Rα2 signaling is non-essential for DIPG progression in vitro. However, exposure to an anti-IL13Rα2 antibody-drug conjugate demonstrated potent pharmacological response in DIPG cell models both in vitro and ex ovo in a manner strongly associated with IL13Rα2 expression, supporting the potential use of targeting IL13Rα2 as a DIPG therapy. However, the tested ADC was effective in most but not all cell models, thus selection of the optimal payload will be essential for clinical translation of an anti-IL13Rα2 ADC for DIPG.

Preclinical therapeutics ex ovo quail eggs as a biomimetic automation-ready xenograft platform.

Preclinical cancer research ranges from in vitro studies that are inexpensive and not necessarily reflective of the tumor microenvironment to mouse studies that are better models but prohibitively expensive at scale. Chorioallantoic membrane (CAM) assays utilizing Japanese quail (Coturnix japonica) are a cost-effective screening method to precede and minimize the scope of murine studies for anti-cancer efficacy and drug toxicity. To increase the throughput of CAM assays we have built and optimized an 11-day platform for processing up to 200 quail eggs per screening to evaluate drug efficacy and drug toxicity caused by a therapeutic. We demonstrate ex ovo concordance with murine in vivo studies, even when the in vitro and in vivo studies diverge, suggesting a role for this quail shell-free CAM xenograft assay in the validation of new anti-cancer agents.

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.

Case report for an adolescent with germline RET mutation and alveolar rhabdomyosarcoma.

In this case report we evaluate the genetics of and scientific basis of therapeutic options for a 14-yr-old male patient diagnosed with metastatic PAX3-FOXO1 fusion positive alveolar rhabdomyosarcoma. A distinguishing genetic feature of this patient was a germline RET C634F mutation, which is a known driver of multiple endocrine neoplasia type 2A (MEN2A) cancer. Through sequential DNA and RNA sequencing analyses over the patient's clinical course, a set of gene mutations, amplifications, and overexpressed genes were identified and biological hypotheses generated to explore the biology of RET and coexisting signaling pathways in rhabdomyosarcoma. Somatic genetic abnormalities identified include CDK4 amplification and FGFR4 G388R polymorphism. Because of the initial lack of patient-derived primary cell cultures, these hypotheses were evaluated using several approaches including western blot analysis and pharmacological evaluation with molecularly similar alveolar rhabdomyosarcoma cell lines. Once a primary cell culture became available, the RET inhibitor cabozantinib was tested but showed no appreciable efficacy in vitro, affirming with the western blot negative for RET protein expression that RET germline mutation could be only incidental. In parallel, the patient was treated with cabozantinib without definitive clinical benefit. Parallel chemical screens identified PI3K and HSP90 as potential tumor-specific biological features. Inhibitors of PI3K and HSP90 were further validated in drug combination synergy experiments and shown to be synergistic in the patient-derived culture. We also evaluated the use of JAK/STAT pathway inhibitors in the context of rhabdomyosarcomas bearing the FGFR4 G388R coding variant. Although the patient succumbed to his disease, study of the patient's tumor has generated insights into the biology of RET and other targets in rhabdomyosarcoma.