David W. Ellison

Background: Reirradiation is used for children and adolescents with recurrent ependymoma after prior surgery and focal irradiation. This study assessed the long-term benefits and risks of a second course of fractionated radiotherapy, patient selection, factors associated with progression-free survival (PFS) and overall survival (OS), and the role of craniospinal irradiation (CSI) at first recurrence. Methods: From July 1994 to January 2024, 150 pediatric ependymoma patients at St. Jude Children’s Research Hospital received a second course of fractionated radiotherapy. Sixty-four were enrolled in a prospective trial. Inclusion required conventional fractionation (≥50.4 Gy) for both courses, with CSI for metastatic disease. Kaplan-Meier estimates measured PFS and OS, Cox models assessed associations with covariates, and competing risks analysis evaluated necrosis and death from complications. Results: At 10 and 20 years, PFS/OS for the cohort were 19.5%/34.3% and 9.0%/13.1%, respectively. Females had significantly better outcomes, and survival varied by initial failure pattern. No significant difference in PFS (P = .1351) or OS (P = .2705) was found between focal irradiation and CSI for patients with local failure (LF). Necrosis was higher with proton therapy vs photons; grade 3 necrosis after reirradiation occurred in 19.9%. The 10-year cumulative incidence of death from complications or secondary tumors was 8.5%. Conclusions: A second course of conventionally fractionated radiotherapy can extend survival in recurrent pediatric ependymoma, but prognosis remains poor, especially for those with combined LF and distant failure or adverse features. Craniospinal irradiation did not improve outcomes for LFs. Proton therapy increased necrosis risk, emphasizing the need for careful selection and follow-up.

Childhood cancer survivors have a heightened risk of developing subsequent neoplasms (SN) related to therapy. We analyzed whole-genome, exome, and RNA sequencing of 200 breast, meningioma, and thyroid SNs, which developed a median of 26.4 years after childhood cancer, among 160 survivors. Meningioma and thyroid SNs were enriched for driver gene rearrangements compared with de novo tumors, including NF2-disrupting alterations and kinase fusions potentially induced by radiation. Radiation correlated with increased insertion–deletion signature ID5. Nitrogen mustard treatment correlated with elevated “flat” signature SBS5 in breast and meningioma SNs; in vitro, these agents caused an unresolved flat signature associated with multiple flat signatures from the Catalogue of Somatic Mutations in Cancer. In meningioma, platinum therapy correlated with NF2 splice-site variants. Analysis of 19 multisample survivors revealed intrapatient heterogeneity in meningioma, including clonally independent tumors. These results demonstrate the long-term impact of childhood cancer treatment on the genomes of SNs developing in adulthood, which may guide SN treatment and prevention. Significance:This represents the most comprehensive genomic characterization of SNs from childhood cancer survivors to date, revealing the mutagenic impact of multiple therapies on the SN genome, including the potential impact of nitrogen mustards such as cyclophosphamide. These results may guide the optimization of future cancer treatment regimens to prevent SN development.See related commentary by Bertrums and van Boxtel, p. 1483

Supplementary Figure S1 shows SN sample exclusion, sequencing coverage, and sequencing types. Supplementary Figure S2 shows filtering approaches for exome FFPE artefacts in 33 pediatric tumors with matched FFPE vs. fresh-frozen data. Supplementary Figure S3 shows the correlation between SNV burden in SN exome vs. WGS data. Supplementary Figure S4 shows TCGA exome SNV and indel burden analysis for de novo cancer cohorts. Supplementary Figure S5 shows coverage data and absence of significant coverage effects on mutation burdens. Supplementary Figure S6 shows a comparison of SNV, indel, and SV burdens in 8 ovarian tumors with matched FFPE vs. fresh-frozen data. Supplementary Figure S7 shows de novo signature extraction data for SNV and indel signatures. Supplementary Figure S8 shows SNV signature data for thyroid SNs and dose-response analysis in meningioma SNs. Supplementary Figure S9 shows drug dose response curves in MCF10A cells. Supplementary Figure S10 shows the cisplatin signature in MCF10A cells. Supplementary Figure S11 shows additional details of experimental drug signatures and comparison signatures from other experimental studies. Supplementary Figure S12 shows the effects of simulated 4-OH-cyclophosphamide treatment on SNV signatures in patient tumors. Supplementary Figure S13 shows doublet signatures in SNs. Supplementary Figure S14 shows meningioma SN copy profiles. Supplementary Figure S15 shows details of functional NF2 splicing assays. Supplementary Figure S16 shows how probabilities were predicted for NF2 variant induction by platinum signatures. Supplementary Figure S17 shows breast SN copy profiles. Supplementary Figure S18 shows clonal evolution trees for breast, meningioma, and thyroid SNs. Supplementary Figure S19 shows details of clonal evolution in breast SNs. Supplementary Figure S20 shows details of clonal evolution in meningioma SNs. Supplementary Figure S21 shows details of clonal evolution in thyroid SNs. Supplementary Figure S22 shows selection of high-quality WGS samples for mutational signature analysis based on coverage breadth

Supplementary Table S1 shows SN sample clinical variables and metadata. Supplementary Table S2 shows a comparison of variables between good-quality vs. excluded samples. Supplementary Table S3 shows a summary of prior treatments across SN patients. Supplementary Table S4 shows a summary of original childhood cancer diagnoses for SN patients. Supplementary Table S5 shows metadata for 33 pediatric cancers with matched FFPE and fresh-frozen exome data. Supplementary Table S6 shows a list of coding-region somatic SNVs used for mutation burden analysis. Supplementary Table S7 shows multivariable analysis comparing SNV burdens between cohorts. Supplementary Table S8 shows multivariable analysis comparing age between cohorts. Supplementary Table S9 shows multivariable analysis comparing SNV burdens between thyroid cancer cohorts among samples with coverage below 100x. Supplementary Table S10 shows cancer-predisposing germline alterations among SN patients. Supplementary Table S11 shows a list of coding-region somatic indels used for mutation burden analysis. Supplementary Table S12 shows multivariable analysis comparing indel burdens between cohorts. Supplementary Table S13 shows SNV signature levels among SNs. Supplementary Table S14 shows multivariable analysis comparing SBS5 burdens in breast SNs stratified by prior treatment. Supplementary Table S15 shows multivariable analysis comparing SBS5 burdens in meningioma SNs stratified by prior treatment. Supplementary Table S16 shows multivariable analysis testing SBS5-cyclophosphamide dose-response relationship in meningioma SNs. Supplementary Table S17 shows variation in cyclophosphamide-containing regimens among meningioma SNs. Supplementary Table S18 shows indel signature levels among SNs. Supplementary Table S19 shows multivariable analysis testing ID5-radiation dose-response relationship in each SN type. Supplementary Table S20 shows multivariable analysis testing ID5-radiation dose-response relationship with all 3 SN types combined. Supplementary Table S21 shows NF2-disrupting structural variants detected in meningioma SNs. Supplementary Table S22 shows multivariable analysis comparing driver alteration frequency between meningioma cohorts. Supplementary Table S23 shows driver fusions in thyroid SNs. Supplementary Table S24 shows multivariable analysis comparing mutation group frequency between thyroid cancer cohorts. Supplementary Table S25 shows multivariable analysis comparing driver alteration frequency between thyroid cancer cohorts. Supplementary Table S26 shows multivariable analysis comparing driver alteration frequency between breast cancer cohorts

Childhood cancer survivors have a heightened risk of developing subsequent neoplasms (SN) related to therapy. We analyzed whole-genome, exome, and RNA sequencing of 200 breast, meningioma, and thyroid SNs, which developed a median of 26.4 years after childhood cancer, among 160 survivors. Meningioma and thyroid SNs were enriched for driver gene rearrangements compared with de novo tumors, including NF2-disrupting alterations and kinase fusions potentially induced by radiation. Radiation correlated with increased insertion–deletion signature ID5. Nitrogen mustard treatment correlated with elevated “flat” signature SBS5 in breast and meningioma SNs; in vitro, these agents caused an unresolved flat signature associated with multiple flat signatures from the Catalogue of Somatic Mutations in Cancer. In meningioma, platinum therapy correlated with NF2 splice-site variants. Analysis of 19 multisample survivors revealed intrapatient heterogeneity in meningioma, including clonally independent tumors. These results demonstrate the long-term impact of childhood cancer treatment on the genomes of SNs developing in adulthood, which may guide SN treatment and prevention. Significance: This represents the most comprehensive genomic characterization of SNs from childhood cancer survivors to date, revealing the mutagenic impact of multiple therapies on the SN genome, including the potential impact of nitrogen mustards such as cyclophosphamide. These results may guide the optimization of future cancer treatment regimens to prevent SN development.

Background: Ependymoma (EPN) is the third most common pediatric brain tumor with no targeted therapies available to patients. In supratentorial ependymoma, the most frequent driver alteration is a gene fusion between ZFTA and RELA (denoted ZR), leads to constitutive localization of ZR in the nucleus. Because ZR is not currently druggable, we tested whether ZR expression leads to aberrant protein interactions that could represent therapeutic vulnerabilities. Methods: Using CRISPR-Cas9 pooled screening, we identified many novel druggable ZR interacting proteins including XPO1, CARM1, SMARCA4, and CDK1. We focused on the nuclear export protein (XPO1), given the ability of most XPO1 inhibitors (i.e. Selinexor) to cross the blood brain barrier, FDA approval, and documented safety profiles in children. Results: We found that specific nuclear ZR levels are needed for cell proliferation and are regulated by XPO1. Increased ZR accumulation in the nucleus does not increase oncogenic gene expression but drives tumor cells out of cell cycle, as compared to a defective ZR DNA binding mutant. Treatment of ZR driven patient-derived mouse models with Selinexor impairs cell growth and extends survival of animals in vivo. The combination of Selinexor treatment with Gemcitabine and Ribociclib (used in a clinical trial for relapsed EPN at St Jude Children’s Research Hospital (SJDAWN)) further extends mouse survival. Conclusion: Our findings demonstrate that ZR interacting proteins constitute therapeutic leads, and that XPO1 is critical for titrating ‘goldilocks’ levels of ZR nuclear expression. We identify a novel combination therapy of Selinexor, Gemcitabine, and Ribociclib that may be immediately translated into clinical trials for EPN patients that are currently without targeted treatments.

ZFTA–RELA is the most recurrent genetic alteration seen in paediatric supratentorial ependymoma (EPN) and is sufficient to initiate tumours in mice¹. Despite its oncogenic potential, ZFTA–RELA (ZR) is observed nearly exclusively in childhood EPN, with tumours located distinctly in the supratentorial brain of the central nervous system¹. We proposed that specific chromatin modules accessible during brain development would render distinct cell lineage programs at direct risk of transformation by ZR. To test this hypothesis, we performed combined single-nucleus assay for transposase-accessible chromatin and RNA (snMultiome) sequencing of the developing mouse forebrain compared with ZR-driven mouse and human EPN. We demonstrated that specific developmental lineage programs present in transient progenitor cells and regulated by PLAG/L family transcription factors were at risk of neoplastic transformation. Binding of this chromatin network by ZR or other PLAG/L family motifs targeting fusion oncoproteins led to persistent chromatin accessibility at oncogenic loci and oncogene expression. Cross-species analysis of mouse and human ZR EPN revealed significant cell type heterogeneity indicating incomplete neurogenic and gliogenic differentiation, with a small percentage of cycling progenitor-like or radial glial-like cells that established a putative tumour cell hierarchy. In vivo lineage tracing studies identified neoplastic clones that aggressively dominated tumour growth and established the entire EPN cellular hierarchy. These findings identify developmental epigenomic states that are critical for fusion-oncoprotein-driven transformation and show how these states continue to shape tumour progression.

Figure S13 legend1 from B7-H3 CAR T Cells Are Effective against Ependymomas but Limited by Tumor Size and Immune Response

Figure S4 shows antigen profiling of HER2 in ZFTA-fusion driven EPN cell lines.

Figure S16 shows high potency but limited durability of B7-H3.CAR T-cells against ZFTA-RELA EPN xenograft tumors in vivo.