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Supplementary Figure 1 depicts copy number alterations in the described cohort

To repurpose therapeutics for fibrolamellar carcinoma (FLC), we developed and validated patient-derived xenografts (PDX) from surgical resections. Most agents used clinically and inhibitors of oncogenes overexpressed in FLC showed little efficacy on PDX. A high-throughput functional drug screen found primary and metastatic FLC were vulnerable to clinically available inhibitors of TOPO1 and HDAC and to napabucasin. Napabucasin's efficacy was mediated through reactive oxygen species and inhibition of translation initiation, and specific inhibition of eIF4A was effective. The sensitivity of each PDX line inversely correlated with expression of the antiapoptotic protein Bcl-xL, and inhibition of Bcl-xL synergized with other drugs. Screening directly on cells dissociated from patient resections validated these results. This demonstrates that a direct functional screen on patient tumors provides therapeutically informative data within a clinically useful time frame. Identifying these novel therapeutic targets and combination therapies is an urgent need, as effective therapeutics for FLC are currently unavailable.Significance:Therapeutics informed by genomics have not yielded effective therapies for FLC. A functional screen identified TOPO1, HDAC inhibitors, and napabucasin as efficacious and synergistic with inhibition of Bcl-xL. Validation on cells dissociated directly from patient tumors demonstrates the ability for functional precision medicine in a solid tumor.This article is highlighted in the In This Issue feature, p. 2355

Supplementary Table 1 shows point mutations found in DSRCT samples

Supplementary Figure 3 provides a breakdown of the structural variant types found via whole genome sequencing in DSRCT samples

Supplementary Figure 1 - 6 and Supplementary Tables 1, 2, and 4

Supplementary Figure 2 depicts whole genome sequencing findings

Desmoplastic small round cell tumor (DSRCT) is characterized by the EWSR1–WT1 t(11;22) (p13:q12) translocation. Few additional putative drivers have been identified, and research has suffered from a lack of model systems. Next-generation sequencing (NGS) data from 68 matched tumor-normal samples, whole-genome sequencing data from 10 samples, transcriptomic and affymetrix array data, and a bank of DSRCT patient-derived xenograft (PDX) are presented. EWSR1–WT1 fusions were noted to be simple, balanced events. Recurrent mutations were uncommon, but were noted in TERT (3%), ARID1A (6%), HRAS (5%), and TP53 (3%), and recurrent loss of heterozygosity (LOH) at 11p, 11q, and 16q was identified in 18%, 22%, and 34% of samples, respectively. Comparison of tumor-normal matched versus unmatched analysis suggests overcalling of somatic mutations in prior publications of DSRCT NGS data. Alterations in fibroblast growth factor receptor 4 (FGFR4) were identified in 5 of 68 (7%) of tumor samples, whereas differential overexpression of FGFR4 was confirmed orthogonally using 2 platforms. PDX models harbored the pathognomic EWSR1–WT1 fusion and were highly representative of corresponding tumors. Our analyses confirm DSRCT as a genomically quiet cancer defined by the balanced translocation, t(11;22)(p13:q12), characterized by a paucity of secondary mutations but a significant number of copy number alterations. Against this genomically quiet background, recurrent activating alterations of FGFR4 stood out, and suggest that this receptor tyrosine kinase, also noted to be highly expressed in DSRCT, should be further investigated. Future studies of DSRCT biology and preclinical therapeutic strategies should benefit from the PDX models characterized in this study.Implications:These data describe the general quiescence of the desmoplastic small round cell tumor (DSRCT) genome, present the first available bank of DSRCT model systems, and nominate FGFR4 as a key receptor tyrosine kinase in DSRCT, based on high expression, recurrent amplification, and recurrent activating mutations.

Supplementary Figure 4 shows data related to FGFR4 inhibition in DSRCT and control models

List of compounds in the primary screen

Supplementary Table 2 shows the raw data further described in Figure 3

Supplementary Table 3

Supplementary Figure 3. Ectopic overexpression of EWSR1-WT1 +KTS and -KTS in UF5 cells.

Purpose:Desmoplastic small round cell tumor (DSRCT) is a highly lethal intra-abdominal sarcoma of adolescents and young adults. DSRCT harbors a t(11;22)(p13:q12) that generates the EWSR1-WT1 chimeric transcription factor, the key oncogenic driver of DSRCT. EWSR1-WT1 rewires global gene expression networks and activates aberrant expression of targets that together mediate oncogenesis. EWSR1-WT1 also activates a neural gene expression program.Experimental Design:Among these neural markers, we found prominent expression of neurotrophic tyrosine kinase receptor 3 (NTRK3), a druggable receptor tyrosine kinase. We investigated the regulation of NTRK3 by EWSR1-WT1 and its potential as a therapeutic target in vitro and in vivo, the latter using novel patient-derived models of DSRCT.Results:We found that EWSR1-WT1 binds upstream of NTRK3 and activates its transcription. NTRK3 mRNA is highly expressed in DSRCT compared with other major chimeric transcription factor–driven sarcomas and most DSRCTs are strongly immunoreactive for NTRK3 protein. Remarkably, expression of NTRK3 kinase domain mRNA in DSRCT is also higher than in cancers with NTRK3 fusions. Abrogation of NTRK3 expression by RNAi silencing reduces growth of DSRCT cells and pharmacologic targeting of NTRK3 with entrectinib is effective in both in vitro and in vivo models of DSRCT.Conclusions:Our results indicate that EWSR1-WT1 directly activates NTRK3 expression in DSRCT cells, which are dependent on its expression and activity for growth. Pharmacologic inhibition of NTRK3 by entrectinib significantly reduces growth of DSRCT cells both in vitro and in vivo, providing a rationale for clinical evaluation of NTRK3 as a therapeutic target in DSRCT.

Supplementary Figure 1. Western blot analysis using WT1 C-terminal antibody.

Supplementary Figure 4. Normalized expression of ALK and ROS1 in patient samples.

Supplementary Figure 2. Characterization of SK DSRCT2.

High-risk neuroblastoma is generally metastatic and often lethal. Using genomic profiling of 470 sequential and spatially separated samples from 283 patients, we characterize subtype-specific genetic evolutionary trajectories from diagnosis, through progression and end-stage metastatic disease. Clonal tracing timed disease initiation to embryogenesis. Continuous acquisition of structural variants at disease defining loci (MYCN, TERT, MDM2-CDK4) followed by convergent evolution of mutations targeting shared pathways emerged as the predominant feature of progression. At diagnosis metastatic clones were already established at distant sites where they could stay dormant, only to cause relapses years later and spread via metastasis-to-metastasis and polyclonal seeding after therapy.

In the United States, more than 10 000 cancers occur annually in children aged 0-14 years, and more than 5000 in adolescents aged 15-19. In the last 50 years, significant advances have been made in imaging, molecular pathology, stage and risk assessment, surgical approach, multidisciplinary treatment, and survival for pediatric solid tumors (particularly neuroblastoma, Wilms tumor, rhabdomyosarcoma, and hepatoblastoma). Moreover, the molecular driver for fibrolamellar hepatocellular carcinoma, which occurs in adolescence and young adulthood, has been identified.

Fibrolamellar Hepatocellular Carcinoma (FLC) is a rare liver cancer affecting adolescents and young adults, with no gender or ethnicity predilection and without history of underlying viral hepatitis, cirrhosis, or other known risk factors. Almost all FLC patients present a somatic heterozygous deletion in chromosome 19p13.12, DNAJB1::PRKACA, which is sufficient to drive FLC in mice. A few studies comparing FLC tumors with adjacent non-transformed liver (normal) samples revealed many transcriptional differences. However, there were done in very small datasets and analyzed using different bioinformatic methods, resulting in just 18-47% agreement between them. This study aims to comprehensively characterize the transcriptome of FLC at bulk and spatial single-cell resolution. The whole transcriptome of 109 FLC frozen patient samples, the largest RNA-seq dataset of FLC to date, was sequenced using different library preparation and ribosomal depletion methods. Only paired tumor and normal tissue samples resected from the same patient were used and divided into two groups: exploration (3 datasets, 67 samples) and testing (2 datasets, 17 samples). Additionally, as external validation datasets, RNA-seq samples from previously published studies were collected, including Sorenson et al. (FLC: 26, normal: 9, paired: 8), the TCGA-LIHC study (FLC: 6, normal: 1, paired: 1), Hirsch et al. (FLC: 15, normal: 3, paired: 0) and Francisco et al. (FLC: 27, normal: 10, paired: 9). All were reanalyzed using state-of-the-art bioinformatic methods: mapped to the Human Genome GRCh38.103 and transcripts quantified using Salmon 1.6.0, unsupervised clustering exploration using PCA, tSNE and UMAP, differential expression calculated using DESeq2 1.28.1, and checking for detectability and consistency among datasets. We found 857 up- and 988 down-regulated genes presenting the same dysregulation in the exploration datasets and confirmed in the testing and external datasets. We call these genes the transcriptional FLC signature. The FLC signature was further characterized by comparing it with the genes differentially expressed in other liver cancers: hepatocellular carcinoma (41 paired samples), hepatoblastoma (22 paired samples), and cholangiocarcinoma (27 paired samples). We found 276 up- and 352 down-regulated genes altered in other liver cancers as well as FLC, but 156 up- and 68 down-regulated only in FLC. The 112 genes with the strongest dysregulation (56 up and 56 down) were used for a MERFISH screening, providing for the first time a single-cell spatial transcriptomic characterization of FLC. This showed clear differential expression patterns in tumor, normal, stromal, and infiltrating immune cells, allowing the identification of how different cell types contribute to the transcriptional FLC signature. Citation Format: David Requena, Aldhair Medico, Luis F. Soto, Mahsa Shirani, James A. Saltsman, Gadi Lalazar, Michael P. LaQuaglia, Sanford M. Simon. Bulk and spatial single-cell transcriptomic characterization of fibrolamellar hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 1516.

Fibrolamellar carcinoma (FLC) is a rare, often lethal, liver cancer affecting adolescents and young adults, for which there are no approved therapeutics. The development of therapeutics is hampered by a lack of in vitro models. Organoids have shown utility as a model system for studying many diseases. In this study, tumor tissue and the adjacent non-tumor liver were obtained at the time of surgery. The tissue was dissociated and grown as organoids. We developed 21 patient-derived organoid lines: 12 from metastases, three from the liver tumor and six from adjacent non-tumor liver. These patient-derived FLC organoids recapitulate the histologic morphology, immunohistochemistry, and transcriptome of the patient tumor. Patient-derived FLC organoids were used in a preliminary high-throughput drug screen to show proof of concept for the identification of therapeutics. This model system has the potential to improve our understanding of this rare cancer and holds significant promise for drug testing and development., Stem Cell Reports, 17 (8), ISSN:2213-6711

Background: Recapitulation of the full spectrum of genomic changes driving patient tumors have resulted in increased use of patient-derived xenograft (PDX) models in studies of basic cancer biology and preclinical drug development. Given the translational potential of PDXs and limited availability of pediatric cancer models, we established a PDX program to expand the existing collection of pediatric PDXs in the community and enable pre- and post-clinical studies. Methods: PDX generation requests were integrated into clinical workflows to maximize identification of eligible patients for informed consent and tissue collection at Memorial Sloan Kettering Cancer Center. Methodologies for tissue procurement and cryopreservation were optimized to facilitate implantation into host immunodeficient mice and enable multi-institutional tissue exchange for model building. A bioinformatics pipeline was established to allow molecular validation of engrafted PDXs using a next-generation targeted gene panel (MSK-IMPACT) evaluating concordance based on acquired mutations, copy number alterations and clonal structure. Results: Between November 2016 - October 2021, 379 PDX models were developed (265 distinct models) representing 69 discrete diagnoses. Sarcoma represents the most common model type (50 discrete osteosarcoma, 20 desmoplastic small round cell tumor, 14 Ewing sarcoma, 24 rhabdomyosarcoma, 2 CIC/DUX4 and 2 BCOR-rearranged sarcoma) followed by neuroblastoma (n=35), leukemia (n=44), and Wilms tumor (n=15). While the majority of PDXs were established from recurrent or metastatic tissue, 7 paired diagnostic/pre-therapy and post-therapy or relapse models were generated. Genomic characterization of PDXs demonstrate excellent concordance and recapitulation of single nucleotide variants (90%), structural (88%) and copy number variants (94%) between patient tumor and matched PDX. Discrepancies between matched patient/PDX pairs are due to sub-clonal heterogeneity in source tumors with clonal outgrowth in the PDX. Analysis of serial PDX passages also demonstrate stable recapitulation of the genomic profile. Establishment of a diverse PDX collection allowed preclinical evaluation of 10 targeted agents across a spectrum of pediatric tumors and provided the preclinical rationale for 3 investigator-initiated pediatric clinical trials. Conclusions: Investment in the development of a phenotypically diverse and biologically faithful collection of pediatric PDX models enables the goals of precision medicine. Optimization of PDX workflows and methods has also enabled the development of a pediatric PDX consortium (PROXC - Pediatric Research in Oncology Xenografting Consortium) to further support the development of pre- and post-clinical studies for pediatric cancer. Citation Format: Filemon S. Dela Cruz, Joseph G. McCarter, Daoqi You, Nancy Bouvier, Xinyi Wang, Kristina C. Guillan, Armaan H. Siddiquee, Katie B. Souto, Hongyan Li, Teng Gao, Dominik Glodzik, Daniel Diolaiti, Neerav N. Shukla, Joachim Silber, Umeshkumar K. Bhanot, Faruk Erdem Kombak, Diego F. Coutinho, Shanita Li, Juan E. Arango Ossa, Juan S. Medina-Martinez, Michael V. Ortiz, Emily K. Slotkin, Michael D. Kinnaman, Sameer F. Sait, Tara J. O'Donohue, Marissa Mattar, Maximiliano Meneses, Michael P. LaQuaglia, Todd E. Heaton, Justin T. Gerstle, Nicola Fabbri, Chelsey M. Burke, Irene M. Rodriquez-Sanchez, Christine A. Iacobuzio-Donahue, Julia L. Glade Bender, Ryan D. Roberts, Jason T. Yustein, Nino C. Rainusso, Brian D. Crompton, Elizabeth Stewart, Alejandro Sweet-Cordero, Leanne C. Sayles, Andrika D. Thomas, Michael H. Roehrl, Elisa de Stanchina, Elli Papaemmanuil, Andrew L. Kung. Development of a patient-derived xenograft (PDX) modeling program to enable pediatric precision medicine [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 704.