The Childhood Cancer Data Initiative: Using the Power of Data to Learn From and Improve Outcomes for Every Child and Young Adult With Pediatric Cancer

Rurality, Cardiovascular Risk Factors, and Early Cardiovascular Disease Among Childhood, Adolescent, and Young Adult Cancer Survivors

Purpose: Cardiovascular risk factors (CVRFs) later in life potentiate risk for late cardiovascular disease (CVD) from cardiotoxic treatment among survivors. This study evaluated the association of baseline CVRFs and CVD in the early survivorship period. Methods: This analysis included patients ages 0-29 at initial diagnosis and reported in the institutional cancer registry between 2010 and 2017 (n = 1228). Patients who died within 5 years (n = 168), those not seen in the oncology clinic (n = 312), and those with CVD within one year of diagnosis (n = 17) were excluded. CVRFs (hypertension, diabetes, dyslipidemia, and obesity) within 1 year of initial diagnosis were constructed and extracted from the electronic health record based on discrete observations, ICD9/10 codes, and RxNorm codes for antihypertensives. Results: Among survivors (n = 731), 10 incident cases (1.4%) of CVD were observed between 1 and 5 years after the initial diagnosis. Public health insurance (p = 0.04) and late effects risk strata (p = 0.01) were positively associated with CVD. Among survivors with public insurance (n = 495), two additional cases of CVD were identified from claims data with an incidence of 2.4%. Survivors from rural areas had a 4.1 times greater risk of CVD compared with survivors from urban areas (95% CI: 1.1-15.3), despite adjustment for late effects risk strata. Conclusion: Clinically computable phenotypes for CVRFs among survivors through informatics methods were feasible. Although CVRFs were not associated with CVD in the early survivorship period, survivors from rural areas were more likely to develop CVD.

Genetic and epigenetic bases of long-term adverse effects of childhood cancer therapy

Over the past decade, genome-scale molecular profiling of large childhood cancer survivorship cohorts has led to unprecedented advances in our understanding of the genetic and epigenetic bases of therapy-related adverse health outcomes in this vulnerable population. To facilitate the integration of knowledge generated from these studies into formulating next-generation precision care for survivors of childhood cancer, we summarize key findings of genetic and epigenetic association studies of long-term therapy-related adverse effects including subsequent neoplasms and cardiomyopathies among others. We also discuss therapy-related genotoxicities including clonal haematopoiesis and DNA methylation, which may underlie accelerated molecular ageing. Finally, we highlight enhanced risk prediction models for survivors of childhood cancer that incorporate both genetic factors and treatment exposures, aiming to achieve enhanced accuracy in predicting risks for this population. These new insights will hopefully inspire future studies that harness both expanding omics resources and evolving data science methodology to accelerate the translation of precision medicine for survivors of childhood cancer.

The childhood cancer data initiative: enabling data sharing to drive research advances and transform pediatric cancer diagnosis and treatment

PURPOSE OF REVIEW

With growing emphasis on data-driven research in pediatric oncology, particularly in the context of advances in molecular characterization and precision medicine, there is an urgent need for comprehensive data-sharing initiatives. This review explores how the Childhood Cancer Data Initiative (CCDI) addresses this critical need.

RECENT FINDINGS

CCDI plays a key role in enhancing pediatric cancer research by improving data integration, sharing, and collaboration. Its Molecular Characterization Initiative advances the field by leveraging detailed molecular data to inform clinical trials and therapeutic strategies. For small patient populations, such as those with rhabdomyosarcoma, CCDI's efforts in integrating data across institutions are vital for advancing risk-based treatment strategies to achieve meaningful clinical outcomes.

SUMMARY

CCDI's advancements in data sharing have profound implications for both clinical practice and research. By enabling precise diagnoses, tailoring treatments based on individual genetic profiles, and addressing the challenges associated with small patient populations, CCDI is driving transformative changes in pediatric oncology. Continued support and expansion of such initiatives are crucial to fully realizing their potential in improving outcomes for children with cancer.

Overview of the etiology of childhood cancer and future directions

PURPOSE OF REVIEW

We provide an overview of the etiology of childhood cancer, the state of the literature, and highlight some opportunities for future research, including technological advancements that could be applied to etiologic studies of childhood cancer to accelerate our understanding.

RECENT FINDINGS

Risk factors of childhood cancer were summarized based on demographics and perinatal factors, environmental risk factors, and genetic risk factors. Overall, demographics and perinatal factors are the most well studied in relation to childhood cancer. While environmental risk factors have been implicated, more work is needed to pinpoint specific exposures, identify window(s) of susceptibility, and understand mechanisms. With genome-wide association studies (GWAS), genetic risk factors of eight childhood cancers have emerged, and opportunities remain to conduct GWAS for other cancer types and determine whether risk variants are inherited or de novo. Technological advancements that can shed light into the susceptibility of childhood cancer include metabolomics, using primary teeth as an exposure matrix, and long-read sequencing.

SUMMARY

The development of childhood cancer remains largely not well understood. Collaboration to increase sample size to conduct analyses by histology and/or molecular subtype and application of novel technologies will accelerate our understanding of childhood cancer.

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.

Cancer Informatics: Novel Methods and Applications of Artificial Intelligence in Cancer Care Delivery

OBJECTIVES

To summarize significant research contributions on cancer informatics published in 2023, an extensive search using PubMed/MEDLINE was conducted to identify the scientific contributions published in 2023 that address topics in cancer. The selection process comprised three steps: (i) ten candidate best papers were first selected by the two section editors, (ii) external reviewers from internationally renowned research teams reviewed each candidate best paper, and (iii) the final selection of three best papers was conducted by the editorial board of the Yearbook.

RESULTS

The two selected papers demonstrate advances in the clinical implementation of cancer informatics methodologies. Both studies highlight translation of informatics methodologies to improve cancer outcomes.

CONCLUSIONS

Cancer informatics is a maturing subfield of bioinformatics. As novel methodologies continue to emerge, further emphasis will be placed on rigorous clinical validation and real-world scalability of such solutions to positively impact patient outcomes.

Molecular profiling of 888 pediatric tumors informs future precision trials and data-sharing initiatives in pediatric cancer

To inform clinical trial design and real-world precision pediatric oncology practice, we classified diagnoses, assessed the landscape of mutations, and identified genomic variants matching trials in a large unselected institutional cohort of solid tumors patients sequenced at Dana-Farber / Boston Children's Cancer and Blood Disorders Center. Tumors were sequenced with OncoPanel, a targeted next-generation DNA sequencing panel. Diagnoses were classified according to the International Classification of Diseases for Oncology (ICD-O-3.2). Over 6.5 years, 888 pediatric cancer patients with 95 distinct diagnoses had successful tumor sequencing. Overall, 33% (n = 289/888) of patients had at least 1 variant matching a precision oncology trial protocol, and 14% (41/289) were treated with molecularly targeted therapy. This study highlights opportunities to use genomic data from hospital-based sequencing performed either for research or clinical care to inform ongoing and future precision oncology clinical trials. Furthermore, the study results emphasize the importance of data sharing to define the genomic landscape and targeted treatment opportunities for the large group of rare pediatric cancers we encounter in clinical practice.

Multi-omic validation of the cuproptosis-sphingolipid metabolism network: modulating the immune landscape in osteosarcoma

Background

The current understanding of the mechanisms by which metal ion metabolism promotes the progression and drug resistance of osteosarcoma remains incomplete. This study aims to elucidate the key roles and mechanisms of genes involved in cuproptosis-related sphingolipid metabolism (cuproptosis-SPGs) in regulating the immune landscape, tumor metastasis, and drug resistance in osteosarcoma cells.

Methods

This study employed multi-omics approaches to assess the impact of cuproptosis-SPGs on the prognosis of osteosarcoma patients. Lasso regression analysis was utilized to construct a prognostic model, while multivariate regression analysis was applied to identify key core genes and generate risk coefficients for these genes, thereby calculating a risk score for each osteosarcoma patient. Patients were then stratified into high-risk and low-risk groups based on their risk scores. The ESTIMATE and CIBERSORT algorithms were used to analyze the level of immune cell infiltration within these risk groups to construct the immune landscape. Single-cell analysis was conducted to provide a more precise depiction of the expression patterns of cuproptosis-SPGs among immune cell subtypes. Finally, experiments on osteosarcoma cells were performed to validate the role of the cuproptosis-sphingolipid signaling network in regulating cell migration and apoptosis.

Results

In this study, seven cuproptosis-SPGs were identified and used to construct a prognostic model for osteosarcoma patients. In addition to predicting survival, the model also demonstrated reliability in forecasting the response to chemotherapy drugs. The results showed that a high cuproptosis-sphingolipid metabolism score was closely associated with reduced CD8 T cell infiltration and indicated poor prognosis in osteosarcoma patients. Cellular functional assays revealed that cuproptosis-SPGs regulated the LC3B/ERK signaling pathway, thereby triggering cell death and impairing migration capabilities in osteosarcoma cells.

Conclusion

The impact of cuproptosis-related sphingolipid metabolism on the survival and migration of osteosarcoma cells, as well as on CD8 T cell infiltration, highlights the potential of targeting copper ion metabolism as a promising strategy for osteosarcoma patients.

Promise and Perils of Precision Oncology for Patients With Pediatric and Young Adult Sarcomas

The completion of multiple national pediatric precision oncology platform trials and the incorporation of standardized molecular profiling into the diagnostic care of pediatric and young adult patients with sarcomas have proven the feasibility and potential of the approach. In this work, we explore the current state of the art of precision oncology for pediatric and young adults with sarcoma. We highlight important lessons learned and the challenges that should be addressed in the next generation of trials. The chapter outlines current efforts to improve standardization of molecular assays, harmonization of data collection, and novel molecular tools such as cell-free DNA analyses. Finally, we discuss the impacts and psychosocial outcomes experienced by patients and communication strategies for providers.

Radiation Dose-Volume-Response Relationships for Adverse Events in Childhood Cancer Survivors: Introduction to the Scientific Issues in PENTEC

At its very core, radiation oncology involves a trade-off between the benefits and risks of exposing tumors and normal tissue to relatively high doses of ionizing radiation. This trade-off is particularly critical in childhood cancer survivors (CCS), in whom both benefits and risks can be hugely consequential due to the long life expectancy if the primary cancer is controlled. Estimating the normal tissue-related risks of a specific radiation therapy plan in an individual patient relies on predictive mathematical modeling of empirical data on adverse events. The Pediatric Normal-Tissue Effects in the Clinic (PENTEC) collaborative network was formed to summarize and, when possible, to synthesize dose-volume-response relationships for a range of adverse events incident in CCS based on the literature. Normal-tissue clinical radiation biology in children is particularly challenging for many reasons: (1) Childhood malignancies are relatively uncommon-constituting approximately 1% of new incident cancers in the United States-and biologically heterogeneous, leading to many small series in the literature and large variability within and between series. This creates challenges in synthesizing data across series. (2) CCS are at an elevated risk for a range of adverse health events that are not specific to radiation therapy. Thus, excess relative or absolute risk compared with a reference population becomes the appropriate metric. (3) Various study designs and quantities to express risk are found in the literature, and these are summarized. (4) Adverse effects in CCS often occur 30, 50, or more years after therapy. This limits the information content of series with even very extended follow-up, and lifetime risk estimates are typically extrapolations that become dependent on the mathematical model used. (5) The long latent period means that retrospective dosimetry is required, as individual computed tomography-based radiation therapy plans gradually became available after 1980. (6) Many individual patient-level factors affect outcomes, including age at exposure, attained age, lifestyle exposures, health behaviors, other treatment modalities, dose, fractionation, and dose distribution. (7) Prospective databases with individual patient-level data and radiation dosimetry are being built and will facilitate advances in dose-volume-response modeling. We discuss these challenges and attempts to overcome them in the setting of PENTEC.

NCI Cancer Research Data Commons: Lessons Learned and Future State

More than ever, scientific progress in cancer research hinges on our ability to combine datasets and extract meaningful interpretations to better understand diseases and ultimately inform the development of better treatments and diagnostic tools. To enable the successful sharing and use of big data, the NCI developed the Cancer Research Data Commons (CRDC), providing access to a large, comprehensive, and expanding collection of cancer data. The CRDC is a cloud-based data science infrastructure that eliminates the need for researchers to download and store large-scale datasets by allowing them to perform analysis where data reside. Over the past 10 years, the CRDC has made significant progress in providing access to data and tools along with training and outreach to support the cancer research community. In this review, we provide an overview of the history and the impact of the CRDC to date, lessons learned, and future plans to further promote data sharing, accessibility, interoperability, and reuse. See related articles by Brady et al., p. 1384, Wang et al., p. 1388, and Pot et al., p. 1396.

Extracting Electronic Health Record Neuroblastoma Treatment Data With High Fidelity Using the REDCap Clinical Data Interoperability Services Module

PURPOSE

Although the International Neuroblastoma Risk Group Data Commons (INRGdc) has enabled seminal large cohort studies, the research is limited by the lack of real-world, electronic health record (EHR) treatment data. To address this limitation, we evaluated the feasibility of extracting treatment data directly from EHRs using the REDCap Clinical Data Interoperability Services (CDIS) module for future submission to the INRGdc.

METHODS

Patients enrolled on the Children's Oncology Group neuroblastoma biology study ANBL00B1 (ClinicalTrials.gov identifier: NCT00904241) who received care at the University of Chicago (UChicago) or the Vanderbilt University Medical Center (VUMC) after the go-live dates for the Fast Healthcare Interoperability Resources (FHIR)-compliant EHRs were identified. Antineoplastic drug orders were extracted using the CDIS module. To validate the CDIS output, antineoplastic agents extracted through FHIR were compared with those queried through EHR relational databases (UChicago's Clinical Research Data Warehouse and VUMC's Epic Clarity database) and manual chart review.

RESULTS

The analytic cohort consisted of 41 patients at UChicago and 32 VUMC patients. Antineoplastic drug orders were identified in the extracted EHR records of 39 (95.1%) UChicago patients and 26 (81.3%) VUMC patients. Manual chart review confirmed that patients with missing (n = 8) or discontinued (n = 1) orders in the CDIS output did not receive antineoplastic agents during the timeframe of the study. More than 99% of the antineoplastic drug orders in the EHR relational databases were identified in the corresponding CDIS output.

CONCLUSION

Our results demonstrate the feasibility of extracting EHR treatment data with high fidelity using HL7-FHIR via REDCap CDIS for future submission to the INRGdc.

Rurality, Cardiovascular Risk Factors, and Early Cardiovascular Disease among Childhood, Adolescent, and Young Adult Cancer Survivors

Background and Aims

Cardiovascular risk factors (CVRFs) later in life potentiate risk for late cardiovascular disease (CVD) from cardiotoxic treatment among survivors. This study evaluated the association of baseline CVRFs and CVD in the early survivorship period.

Methods

This analysis included patients ages 0-29 at initial diagnosis and reported in the institutional cancer registry between 2010 and 2017 (n = 1228). Patients who died within five years (n = 168), those not seen in the oncology clinic (n = 312), and those with CVD within one year of diagnosis (n = 17) were excluded. CVRFs (hypertension, diabetes, dyslipidemia, and obesity) within one year of initial diagnosis, were constructed and extracted from the electronic health record based on discrete observations, ICD9/10 codes, and RxNorm codes for antihypertensives.

Results

Among survivors (n = 731), 10 incident cases (1.4%) of CVD were observed between one year and five years after the initial diagnosis. Public health insurance (p = 0.04) and late effects risk strata (p = 0.01) were positively associated with CVD. Among survivors with public insurance(n = 495), two additional cases of CVD were identified from claims data with an incidence of 2.4%. Survivors from rural areas had a 4.1 times greater risk of CVD compared with survivors from urban areas (95% CI: 1.1-15.3), despite adjustment for late effects risk strata.

Conclusions

Clinically computable phenotypes for CVRFs among survivors through informatics methods were feasible. Although CVRFs were not associated with CVD in the early survivorship period, survivors from rural areas were more likely to develop CVD.

Implications for Survivors

Survivors from non-urban areas and those with public insurance may be particularly vulnerable to CVD.

Germline Genetic Testing and Survival Outcomes Among Children With Rhabdomyosarcoma: A Report From the Children's Oncology Group

Importance

Determining the impact of germline cancer-predisposition variants (CPVs) on outcomes could inform novel approaches to testing and treating children with rhabdomyosarcoma.

Objective

To assess whether CPVs are associated with outcome among children with rhabdomyosarcoma.

Design, Setting, and Participants

In this cohort study, data were obtained for individuals, aged 0.01-23.23 years, newly diagnosed with rhabdomyosarcoma who were treated across 171 Children's Oncology Group sites from March 15, 1999, to December 8, 2017. Data analysis was performed from June 16, 2021, to May 15, 2023.

Exposure

The presence of a CPV in 24 rhabdomyosarcoma-associated cancer-predisposition genes (CPGs) or an expanded set of 63 autosomal-dominant CPGs.

Main Outcomes and Measures

Overall survival (OS) and event-free survival (EFS) were the main outcomes, using the Kaplan-Meier estimator to assess survival probabilities and the Cox proportional hazards regression model to adjust for clinical covariates. Analyses were stratified by tumor histology and the fusion status of PAX3 or PAX7 to the FOXO1 gene.

Results

In this study of 580 individuals with rhabdomyosarcoma, the median patient age was 5.9 years (range, 0.01-23.23 years), and the male-to-female ratio was 1.5 to 1 (351 [60.5%] male). For patients with CPVs in rhabdomyosarcoma-associated CPGs, EFS was 48.4% compared with 57.8% for patients without a CPV (P = .10), and OS was 53.7% compared with 65.3% for patients without a CPV (P = .06). After adjustment, patients with CPVs had significantly worse OS (adjusted hazard ratio [AHR], 2.49 [95% CI, 1.39-4.45]; P = .002), and the outcomes were not better among patients with embryonal histology (EFS: AHR, 2.25 [95% CI, 1.25-4.06]; P = .007]; OS: AHR, 2.83 [95% CI, 1.47-5.43]; P = .002]). These associations were not due to the development of a second malignant neoplasm, and importantly, patients with fusion-negative rhabdomyosarcoma who harbored a CPV had similarly inferior outcomes as patients with fusion-positive rhabdomyosarcoma without CPVs (EFS: AHR, 1.35 [95% CI, 0.71-2.59]; P = .37; OS: AHR, 1.71 [95% CI, 0.84-3.47]; P = .14). There were no significant differences in outcome by CPV status of the 63 CPG set.

Conclusions and Relevance

This cohort study identified a group of patients with embryonal rhabdomyosarcoma who had a particularly poor outcome. Other important clinical findings included that individuals with TP53 had poor outcomes independent of second malignant neoplasms and that patients with fusion-negative rhabdomyosarcoma who harbored a CPV had outcomes comparable to patients with fusion-positive rhabdomyosarcoma. These findings suggest that germline CPV testing may aid in clinical prognosis and should be considered in prospective risk-based clinical trials.

Childhood cancer data initiative: Status report

In March 2023, over 800 researchers, clinicians, patients, survivors, and advocates from the pediatric oncology community met to discuss the progress of the National Cancer Institute's Childhood Cancer Data Initiative. We present here the status of the initiative's efforts in building its data ecosystem and updates on key programs, especially the Molecular Characterization Initiative and the planned Coordinated National Initiative for Rare Cancers in Children and Young Adults. These activities aim to improve access to childhood cancer data, foster collaborations, facilitate integrative data analysis, and expand access to molecular characterization, ultimately leading to the development of innovative therapeutic approaches.

Overview of modern genomic tools for diagnosis and precision therapy of childhood solid cancers

PURPOSE OF REVIEW

The application of technology and computational analyses to generate new data types from pediatric solid cancers is transforming diagnostic accuracy. This review provides an overview of such new capabilities in the pursuit of improved treatment for essentially rare and underserved diseases that are the highest cause of mortality in children over one year of age. Sophisticated ways of identifying therapeutic vulnerabilities for highly personalized treatment are presented alongside cutting-edge disease response monitoring by liquid biopsy.

RECENT FINDINGS

Precision molecular profiling data are now being combined with conventional pathology-based evaluation of pediatric cancer tissues. The resulting diagnostic information can be used to guide therapeutic decision-making, including the use of small molecule inhibitors and of immunotherapies. Integrating somatic and germline variant profiles constitutes a critical component of this emerging paradigm, as does tissue-of-origin derivation from methylation profiling, and rapid screening of potential therapies. These new approaches are poised for use in disease response and therapy resistance monitoring.

SUMMARY

The integration of clinical molecular profiling data with pathology can provide a highly precise diagnosis, identify therapeutic vulnerabilities, and monitor patient responses, providing next steps toward precision oncology for improved outcomes, including reducing lifelong treatment-related sequelae.

Recent advances in the treatment of childhood cancers

PURPOSE OF REVIEW

Although cancer remains the leading nonaccidental cause of mortality in children, substantial advances in care have led to 5-year overall survival exceeding 85%. However, improvements in outcomes have not been uniform across malignancies or strata of social determinants of health. The current review highlights recent areas of advancement and anticipated directions for future progress.

RECENT FINDINGS

Incorporation of rational targeted agents into upfront treatment regimens has led to incremental improvements in event-free survival for many children, sometimes with potential reductions in late effects. For rare or challenging-to-treat cancers, the increasing feasibility of molecular profiling has provided specific treatment options to patients with some of the greatest needs. Simultaneously, increased focus is being given to patient-reported outcomes and social determinants of health, the importance ofwhich are becoming readily recognized in providing equitable, quality care. Finally, as survival from malignant diseases improves, breakthroughs in the prevention and management of adverse late effects will promote long-term quality of life.

SUMMARY

Multi-institutional collaboration and risk-adapted approaches have been crucial to recent advancements in the care of children with cancer and inform potential directions for future investigation.

Raising the Bar for Real-World Data in Oncology: Approaches to Quality Across Multiple Dimensions

PURPOSE

Electronic health record (EHR)-based real-world data (RWD) are integral to oncology research, and understanding fitness for use is critical for data users. Complexity of data sources and curation methods necessitate transparency into how quality is approached. We describe the application of data quality dimensions in curating EHR-derived oncology RWD.

METHODS

A targeted review was conducted to summarize data quality dimensions in frameworks published by the European Medicines Agency, The National Institute for Healthcare and Excellence, US Food and Drug Administration, Duke-Margolis Center for Health Policy, and Patient-Centered Outcomes Research Institute. We then characterized quality processes applied to curation of Flatiron Health RWD, which originate from EHRs of a nationwide network of academic and community cancer clinics, across the summarized quality dimensions.

RESULTS

The primary quality dimensions across frameworks were relevance (including subdimensions of availability, sufficiency, and representativeness) and reliability (including subdimensions of accuracy, completeness, provenance, and timeliness). Flatiron Health RWD quality processes were aligned to each dimension. Relevancy to broad or specific use cases is optimized through data set size and variable breadth and depth. Accuracy is addressed using validation approaches, such as comparison with external or internal reference standards or indirect benchmarking, and verification checks for conformance, consistency, and plausibility, selected on the basis of feasibility and criticality of the variable to the intended use case. Completeness is assessed against expected source documentation; provenance by recording data transformation, management procedures, and auditable metadata; and timeliness by setting refresh frequency to minimize data lags.

CONCLUSION

Development of high-quality, scaled, EHR-based RWD requires integration of systematic processes across the data lifecycle. Approaches to quality are optimized through knowledge of data sources, curation processes, and use case needs. By addressing quality dimensions from published frameworks, Flatiron Health RWD enable transparency in determining fitness for real-world evidence generation.

Collaborative Innovations in Childhood Cancer Therapies

The outcome for children with cancer has improved significantly over the past 60 years, with more than 80% of patients today becoming 5-year survivors. Despite this progress, cancer remains the leading cause of death from disease in children in the United States and Europe, with significant short- and long-term toxicity of treatment continuing to impact most children. While the past 15 years have witnessed dramatic scientific innovation for certain cancers in adult patients, pediatric cancer treatment innovation lags increasingly behind. To help bridge the adult-pediatric therapeutic development gap, collaborative efforts are essential among stakeholders within and outside the pediatric oncology community. Prioritizing collaboration in areas such as cancer characterization, target identification and validation, drug discovery, and approaches to currently "undruggable" targets is imperative to improving the outcomes for children with cancer.

Longitudinal Natural History Study of Children and Adults with Rare Solid Tumors: Initial Results for First 200 Participants

Understanding of tumor biology and identification of effective therapies is lacking for many rare tumors. My Pediatric and Adult Rare Tumor (MyPART) network was established to engage patients, advocates, and researchers and conduct a comprehensive longitudinal Natural History Study of Rare Solid Tumors. Through remote or in-person enrollment at the NIH Clinical Center, participants with rare solid tumors ≥4 weeks old complete standardized medical and family history forms, patient reported outcomes, and provide tumor, blood and/or saliva samples. Medical records are extracted for clinical status and treatment history, and tumors undergo genomic analysis. A total of 200 participants (65% female, 35% male, median age at diagnosis 43 years, range = 2-77) enrolled from 46 U.S. states and nine other countries (46% remote, 55% in-person). Frequent diagnoses were neuroendocrine neoplasms (NEN), adrenocortical carcinomas (ACC), medullary thyroid carcinomas (MTC), succinate dehydrogenase (SDH)-deficient gastrointestinal stromal tumors (sdGIST), and chordomas. At enrollment, median years since diagnosis was 3.5 (range = 0-36.6), 63% participants had metastatic disease and 20% had no evidence of disease. Pathogenic germline and tumor mutations included SDHA/B/C (sdGIST), RET (MTC), TP53 and CTNNB1 (ACC), MEN1 (NEN), and SMARCB1 (poorly-differentiated chordoma). Clinically significant anxiety was observed in 20%-35% of adults. Enrollment of participants and comprehensive data collection were feasible. Remote enrollment was critical during the COVID-19 pandemic. Over 30 patients were enrolled with ACC, NEN, and sdGIST, allowing for clinical/genomic analyses across tumors. Longitudinal follow-up and expansion of cohorts are ongoing to advance understanding of disease course and establish external controls for interventional trials.

SIGNIFICANCE

This study demonstrates that comprehensive, tumor-agnostic data and biospecimen collection is feasible to characterize different rare tumors, and speed progress in research. The findings will be foundational to developing external controls groups for single-arm interventional trials, where randomized control trials cannot be conducted because of small patient populations.

Genomic profiling of subcutaneous patient-derived xenografts reveals immune constraints on tumor evolution in childhood solid cancer

Subcutaneous patient-derived xenografts (PDXs) are an important tool for childhood cancer research. Here, we describe a resource of 68 early passage PDXs established from 65 pediatric solid tumor patients. Through genomic profiling of paired PDXs and patient tumors (PTs), we observe low mutational similarity in about 30% of the PT/PDX pairs. Clonal analysis in these pairs show an aggressive PT minor subclone seeds the major clone in the PDX. We show evidence that this subclone is more immunogenic and is likely suppressed by immune responses in the PT. These results suggest interplay between intratumoral heterogeneity and antitumor immunity may underlie the genetic disparity between PTs and PDXs. We further show that PDXs generally recapitulate PTs in copy number and transcriptomic profiles. Finally, we report a gene fusion LRPAP1-PDGFRA. In summary, we report a childhood cancer PDX resource and our study highlights the role of immune constraints on tumor evolution.

Targeted Approaches to Treatment of Pleural Mesothelioma: A Review

Pleural mesothelioma is an aggressive disease that is enriched for inactivating alterations in tumor suppressor genes. Systemic therapeutic strategies for pleural mesothelioma generally involve chemotherapies and immunotherapies that are chosen without consideration of the tumor's molecular profile. As this generalized approach to treatment rarely yields durable responses, alternative therapeutic regimens are urgently indicated. Preclinical studies have identified synthetic lethal protein and metabolic interactions, recurrently overexpressed proteins, and frequent pathway perturbations that may be therapeutically exploited in mesothelioma. This review discusses the mechanism of action of emerging investigational therapies and summarizes findings from phase I-II clinical trials exploring selective, biomarker-driven therapeutic strategies for mesothelioma, with a focus on five common targets. Finally, using lessons learned from these clinical trials, imperatives for successful implementation of targeted therapy in mesothelioma are discussed.