Roadmap for the next generation of Children's Oncology Group rhabdomyosarcoma trials.

Clinical trials conducted by the Intergroup Rhabdomyosarcoma (RMS) Study Group and the Children's Oncology Group have been pivotal to establishing current standards for diagnosis and therapy for RMS. Recent advancements in understanding the biology and clinical behavior of RMS have led to more nuanced approaches to diagnosis, risk stratification, and treatment. The complexities introduced by these advancements, coupled with the rarity of RMS, pose challenges to conducting large-scale phase 3 clinical trials to evaluate new treatment strategies for RMS. Given these challenges, systematic planning of future clinical trials in RMS is paramount to address pertinent questions regarding the therapeutic efficacy of drugs, biomarkers of response, treatment-related toxicity, and patient quality of life. Herein, the authors outline the proposed strategic approach of the Children's Oncology Group Soft Tissue Sarcoma Committee to the next generation of RMS clinical trials, focusing on five themes: improved novel agent identification and preclinical to clinical translation, more efficient trial development and implementation, expanded opportunities for knowledge generation during trials, therapeutic toxicity reduction and quality of life, and patient engagement.

Pediatric Leukemia Roadmaps Are a Guide for Positive Metastatic Bone Sarcoma Trials.

ALL cures require many MRD therapies. This strategy should drive experiments and trials in metastatic bone sarcomas.

Epigenetic targeting of PGBD5-dependent DNA damage in SMARCB1-deficient sarcomas.

Despite the potential of targeted epigenetic therapies, most cancers do not respond to current epigenetic drugs. The Polycomb repressive complex EZH2 inhibitor tazemetostat was recently approved for the treatment of SMARCB1-deficient epithelioid sarcomas, based on the functional antagonism between PRC2 and loss of SMARCB1. Through the analysis of tazemetostat-treated patient tumors, we recently defined key principles of their response and resistance to EZH2 epigenetic therapy. Here, using transcriptomic inference from SMARCB1-deficient tumor cells, we nominate the DNA damage repair kinase ATR as a target for rational combination EZH2 epigenetic therapy. We show that EZH2 inhibition promotes DNA damage in epithelioid and rhabdoid tumor cells, at least in part via its induction of the transposase-derived PGBD5. We leverage this collateral synthetic lethal dependency to target PGBD5-dependent DNA damage by inhibition of ATR but not CHK1 using elimusertib. Consequently, combined EZH2 and ATR inhibition improves therapeutic responses in diverse patient-derived epithelioid and rhabdoid tumors in vivo. This advances a combination epigenetic therapy based on EZH2-PGBD5 synthetic lethal dependency suitable for immediate translation to clinical trials for patients.

Identification and Pharmacological Targeting of Treatment-Resistant, Stem-like Breast Cancer Cells for Combination Therapy.

Tumors frequently harbor isogenic yet epigenetically distinct subpopulations of multi-potent cells with high tumor-initiating potential-often called Cancer Stem-Like Cells (CSLCs). These can display preferential resistance to standard-of-care chemotherapy. Single-cell analyses can help elucidate Master Regulator (MR) proteins responsible for governing the transcriptional state of these cells, thus revealing complementary dependencies that may be leveraged via combination therapy. Interrogation of single-cell RNA sequencing profiles from seven metastatic breast cancer patients, using perturbational profiles of clinically relevant drugs, identified drugs predicted to invert the activity of MR proteins governing the transcriptional state of chemoresistant CSLCs, which were then validated by CROP-seq assays. The top drug, the anthelmintic albendazole, depleted this subpopulation in vivo without noticeable cytotoxicity. Moreover, sequential cycles of albendazole and paclitaxel-a commonly used chemotherapeutic -displayed significant synergy in a patient-derived xenograft (PDX) from a TNBC patient, suggesting that network-based approaches can help develop mechanism-based combinatorial therapies targeting complementary subpopulations.

Overcoming Clinical Resistance to EZH2 Inhibition Using Rational Epigenetic Combination Therapy.

Epigenetic dependencies have become evident in many cancers. On the basis of antagonism between BAF/SWI-SNF and PRC2 in SMARCB1-deficient sarcomas, we recently completed the clinical trial of the EZH2 inhibitor tazemetostat. However, the principles of tumor response to epigenetic therapy in general, and tazemetostat in particular, remain unknown. Using functional genomics and diverse experimental models, we define molecular mechanisms of tazemetostat resistance in SMARCB1-deficient tumors. We found distinct acquired mutations that converge on the RB1/E2F axis and decouple EZH2-dependent differentiation and cell-cycle control. This allows tumor cells to escape tazemetostat-induced G1 arrest, suggests a general mechanism for effective therapy, and provides prospective biomarkers for therapy stratification, including PRICKLE1. On the basis of this, we develop a combination strategy to circumvent tazemetostat resistance using bypass targeting of AURKB. This offers a paradigm for rational epigenetic combination therapy suitable for translation to clinical trials for epithelioid sarcomas, rhabdoid tumors, and other epigenetically dysregulated cancers. SIGNIFICANCE: Genomic studies of patient epithelioid sarcomas and rhabdoid tumors identify mutations converging on a common pathway for response to EZH2 inhibition. Resistance mutations decouple drug-induced differentiation from cell-cycle control. We identify an epigenetic combination strategy to overcome resistance and improve durability of response, supporting its investigation in clinical trials. See related commentary by Paolini and Souroullas, p. 903. This article is featured in Selected Articles from This Issue, p. 897.

Dynamic network curvature analysis of gene expression reveals novel potential therapeutic targets in sarcoma.

Network properties account for the complex relationship between genes, making it easier to identify complex patterns in their interactions. In this work, we leveraged these network properties for dual purposes. First, we clustered pediatric sarcoma tumors using network information flow as a similarity metric, computed by the Wasserstein distance. We demonstrate that this approach yields the best concordance with histological subtypes, validated against three state-of-the-art methods. Second, to identify molecular targets that would be missed by more conventional methods of analysis, we applied a novel unsupervised method to cluster gene interactomes represented as networks in pediatric sarcoma. RNA-Seq data were mapped to protein-level interactomes to construct weighted networks that were then subjected to a non-Euclidean, multi-scale geometric approach centered on a discrete notion of curvature. This provides a measure of the functional association among genes in the context of their connectivity. In confirmation of the validity of this method, hierarchical clustering revealed the characteristic EWSR1-FLI1 fusion in Ewing sarcoma. Furthermore, assessing the effects of in silico edge perturbations and simulated gene knockouts as quantified by changes in curvature, we found non-trivial gene associations not previously identified.