Pediatric brain tumors are now the most common cause of mortality from disease in childhood. Molecular characteristics of pediatric high- and low-grade gliomas (PHGG and PLGG), the most common tumor category overall, are crucial to treatment and outcomes, but the impact of these characteristics and of the variety of cell populations in these tumors is poorly understood. We performed single-cell RNA-sequencing on viably banked single cell samples of high- and low- grade glial tumors from children treated at Children’s Hospital Colorado. These samples are part of ongoing single-cell pediatric brain tumor banking that our group initiated a decade ago. The maturity of this resource, collected over a decade, provides us with the opportunity to perform well-powered outcome association studies. Samples are collected during routine surgery and immediately disaggregated to isolate single cells. These are then viably frozen in DMSO and banked for later use. We have tumors that cover the variety of subtypes in each of these diseases, as well as comprehensive clinical information on these cases, which will allow us to correlate molecular subtypes and research findings with these clinical measures. Here, we perform single-cell RNA-sequencing on 23 samples from patients with PHGG. In PHGG, we aim to understand the extent to which pediatric HGG stem like cells may differentiate into other cell types found in HGG tumors, or whether the non-stemlike cells may be derived from host tissue; whether gene expression is altered in host cells as the result of interactions with tumor stem cells; and the extent to which specific gene expression patterns among tumor cell subpopulations correlate with outcome measures such as mortality or event-free survival. These studies will significantly advance our understanding of disease biology and provide the detailed molecular and functional insights needed to identify new therapeutic targets for these biologically and clinically heterogeneous tumors.

Pediatric brain tumors are now the most common cause of mortality from disease in childhood. Molecular characteristics of pediatric high- and low-grade gliomas (PHGG and PLGG), the most common tumor category overall, are crucial to treatment and outcomes, but the impact of these characteristics and of the variety of cell populations in these tumors is poorly understood. We performed single-cell RNA-sequencing on viably banked single cell samples of high- and low- grade glial tumors from children treated at Children’s Hospital Colorado. These samples are part of ongoing single-cell pediatric brain tumor banking that our group initiated a decade ago. The maturity of this resource, collected over a decade, provides us with the opportunity to perform well-powered outcome association studies. Samples are collected during routine surgery and immediately disaggregated to isolate single cells. These are then viably frozen in DMSO and banked for later use. We have tumors that cover the variety of subtypes in each of these diseases, as well as comprehensive clinical information on these cases, which will allow us to correlate molecular subtypes and research findings with these clinical measures. Here, we perform single-cell RNA-sequencing on 26 samples from patients with PLGG. In PLGG, we will leverage scRNA-Seq analysis to identify lineage specific development and subpopulations within these tumors. We will then evaluate single-cell RNA-sequencing signatures and clinical outcomes of LGG with BRAF WT, KIAA1549:BRAF fusion and BRAFV600E to identify unique drivers of aggressiveness of BRAFV600E tumors. These studies will significantly advance our understanding of disease biology and provide the detailed molecular and functional insights needed to identify new therapeutic targets for these biologically and clinically heterogeneous tumors.

Early T cell precursor acute lymphoblastic leukemia (ETP ALL) is a subtype of T cell acute lymphoblastic leukemia (T-ALL) that arises from an early T cell lineage clone, represents 10-15% of T-ALL cases, and has genetic alterations distinct from non-ETP T-ALL. While the survival for children with ETP ALL is similar to non-ETP T-ALL, the reason for treatment failure differs. Relapse is the most common reason for treatment failure in non-ETP T-ALL, and failure to respond to therapy and attain remission is the most common reason in ETP ALL. It is unknown why ETP ALL responds differently than non-ETP ALL. It is also unknown why some children with ETP ALL are cured, and others are not. The genetic alterations in ETP ALL, as defined by bulk sequencing, are more similar to acute myelogenous leukemia (AML) or T-myeloid mixed-phenotype acute leukemia (TM-MPAL) than T-ALL. We recently received a NIH X01 grant to perform comprehensive genomic profiling on 1262 cases of T-ALL treated on the AALL0434 clinical trial. This sequencing will include whole genome sequencing (WGS), whole exome sequencing (WES), transcriptome profiling (RNA-Seq), and copy number analysis (SNP). Unfortunately, bulk sequencing will not recapitulate clonal architecture or identify rare or heterogeneous cell populations that may help identify high risk patients. Using innovative single cell technologies, we can enhance our understanding of clonal diversity in ETP ALL. We hypothesize that single-cell RNA-Seq will enhance the understanding of the clonal diversity of ETP ALL, improving the understanding of ETP disease biology and allowing for the prospective identification of patients at diagnosis likely to fail conventional therapy who would be better served by alternative approaches. We obtained single-cell RNA-Seq and CITE-seq from 30 cases of ETP ALL, including samples collected at diagnosis from children who responded to treatment, children who failed to respond to treatment, and children who responded to treatment and relapsed. We also obtained scRNA-Seq and CITE-seq on 8 cases of acute myelogenous leukemia, 11 cases of non-ETP T-ALL, and 10 cases of T-myeloid MPAL. This data enables new understanding of leukemogenesis in patients with subtypes of leukemia that have similar immunophenotypes and comparable genomics by bulk sequencing but arise from different hematopoietic progenitors and respond differently to therapy. This work may identify targetable lesions that may be used to tailor future therapy and has the potential to significantly impact the diagnosis and management of patients with ETP ALL, an underserved and understudied population of childhood leukemia.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have collaborated with Aviv Regev at the Broad Institute to compare single-cell RNA-sequencing to single-nuclei RNA-sequencing for pediatric solid tumors. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 40 tissue samples obtained from Neuroblastoma patients as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have collaborated with Aviv Regev at the Broad Institute to compare single-cell RNA-sequencing to single-nuclei RNA-sequencing for pediatric solid tumors. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 59 tissue samples from both Rhabdomyosarcoma patient tumors and matched O-PDXs as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Wilms tumor (WT) is the most common pediatric kidney cancer. WT is characterized by a significant degree of intratumor subclonal histologic and genetic heterogeneity. Histology is the greatest predictor of outcome, and patients with unfavorable histology (diffuse anaplasia) account for 5% of cases, but 50% of deaths from this disease. A critical barrier to understanding therapeutic resistance in WT is that resistant cells, particularly the anaplastic population in unfavorable histology WT, may represent a minor subclone in the tumor. Therefore, prior analyses based on bulk genome and RNA-sequencing may have failed to identify new anaplasia-specific therapeutic targets because of dilution by non-anaplastic cells in the tumor. Our preliminary single-cell RNA-sequencing experiments have revealed substantial transcriptomic heterogeneity in anaplastic and favorable histology WT patient derived xenografts. However, it has been challenging to assign specific cluster(s) to the anaplastic populations unambiguously. The purpose of this project is to resolve the transcriptome of the blastemal, epithelial, and stromal cellular populations in Wilms tumor and to unambiguously identify the expression signature of anaplastic clones in anaplastic histology WT. We aim to achieve this goal by analyzing 23 favorable histology WT and 22 anaplastic histology WT with single-nuclei RNA sequencing. This study will help establish an anaplasia-specific expression signature in unfavorable histology WT. Furthermore, our approach will also identify how tumor-stromal interactions, which play a key role in therapeutic resistance, may differ between anaplastic and favorable histology components within unfavorable histology WT. The long-term intellectual impact of this study is that the expression signature established by our work is likely to advance the understanding of therapeutic resistance in this treatment refractory tumor subtype.

Bulk genomic studies of tens of thousands of acute myeloid leukemia (AML) cells mixed together have cataloged the changes in gene expression and mutations present in at least 10-20% of cells. The discoveries from these studies have implicated a number of new genes in AML formation, progression, and persistence, resulting in further subclassification of the disease. Still, these discoveries have thus far not been translated into improved outcomes for patients. This is in large part due to the heterogeneity of cell types and genomic changes within the cells that are present within a sample. The development of technologies to sequence genomes, quantify transcriptomes and identify surface proteomes of single cells has afforded a new opportunity to dissect and better understand the biology of these distinct cell types. In this study, we perform single-cell RNA sequencing and CITE-seq of 30 AML samples. Using cell types identified from single-cell RNA-sequencing with CITE-seq, cells are sorted based on expression of surface markers unique to phenotypic AML subpopulations. This is followed by whole genome amplification using our newly invented primary template-directed amplification (PTA) to perform accurate variant calling of the 1.2 Mb of the genome most commonly mutated in AML samples, as well as low-pass whole genome sequencing for single cell copy number variation profiling. Data from these studies will be used to identify distinct cell types present in AML samples including cells that appear to be of non-myeloid origin. This data will enable the exploration of transcriptomic changes present in distinct AML subpopulations. We anticipate the new insights afforded by this high-resolution resource will provide a deeper understanding of AML that could uncover new treatment approaches for this deadly pediatric cancer.

Acute lymphoblastic leukemia (ALL) is the most common childhood cancer and remains a leading cause of cancer death in children. Large scale studies examining the genomic landscape of ALL using bulk tumor samples have defined multiple new subtypes, genomic drivers, risk classifying genes and therapeutic targets. However, there are few studies of ALL using single-cell RNA-seq technology to study heterogeneity and the surrounding tumor microenvironment (TME). Previous studies, such as those described here, indicate that single-cell RNA seq studies of AML can provide new insights in the tumor intrinsic and extrinsic factors driving tumor behavior and relapse. Gene expression profiling (GEP) using the 3’ 10x platform of small numbers of matched diagnosis and relapse samples have shown enrichment of a CSF1R signature in the TME at relapse. Single-cell profiling of ALL-stromal cocultures identified a resistant ALL cell population undergoing epithelial mesenchymal transition. Mutational profiling of stem and progenitor populations from leukemia samples was shown to map tumor initiating lesions to developmental stage, indicating that mutational driver and cell of origin is a key determinant of leukemia lineage, and T cell profiling identified autoreactive T cells directed to fusion oncoprotein and mutational neoepitopes. Here, we expand upon previous single-cell studies of ALL, using single-cell RNA seq to profile gene expression, mutational diversity, immunophenotype, TME composition and T cell repertoire in ALL subtypes representative of standard and high risk disease in 95 patients: ETV6-RUNX1-like, KMT2A-rearranged, Ph+, Ph-like, ZNF384-rearranged, B/myeloid mixed phenotype acute leukemia, DUX4-rearranged, MEF2D-rearranged, TCF3::PBX1, hyperdiploid, low hyplodiploid and near haploid ALL. All samples are subject to 5’ 10x single-cell GEP of the tumor, TME and T cell compartments, and B-cell ALL. Simultaneous single-cell cell surface protein sequencing and RNA-seq is incorporated for a subset of tumors with lineage ambiguity. When available, single-cell GEP of relapse samples was obtained. Complementary studies include profiling full length RNA-seq (SMART-seq HT and PacBio) of blast and progenitor cell populations to integrate fusion/mutational profile, expression, and cell of origin.

Single cell gene expression profiling of pediatric central nervous system (CNS) tumors holds great potential to further our understanding of carcinogenesis, augment prognostic indicators, and identify rational therapeutic targets. Whereas the genomic characteristics of these tumors are fairly well-defined in aggregate, the extent to which cellular heterogeneity is associated with carcinogenesis and clinical outcomes is largely unknown. Here we profile single nuclei gene expression in 36 brain tumor specimens from individuals with a diagnosis of ependymoma, glioma, or embryonal CNS tumor with substantial follow up time, as well as non-tumor brain tissue from three pediatric controls. We used the 10X Genomics Single Cell platform to obtain single nuclei for RNA sequencing in conjunction with bulk RNA sequencing. In conjunction with this study, we obtained 5-methyl- and 5-hydroxymethylation profiles on these samples to investigate functional aspects of gene regulation by cytosine modification. The data and results from this study are expected to reveal an abundance of information about pediatric CNS tumors with value for the broader scientific community.

Pediatric brain cancers are the most common solid tumors in children with varying survival rates depending on molecular features of cancer cells and associated microenvironment. Several studies have used single-cell RNA sequencing to define transcriptional programs active in cancer cells and highlighted supportive roles of non-cancerous cells embedded in these tumors. Although application of single-cell RNA sequencing technology has expanded our understanding of intratumoral heterogeneity and underlying transcriptional mechanisms in brain tumors at diagnosis, mechanisms of disease remains elusive. Therefore, the purpose of this proposal is to characterize cellular and transcriptional states of malignant and non-malignant compartments at primary diagnosis and at relapse. In this study, we performed single-nuclei sequencing of 42 patient samples taken at various disease stages (initial diagnosis, progressive disease, and relapsed disease) from 20 patients with low-grade glioma or Atypical Teratoid Rhabdoid Tumor (ATRT). Bulk whole genome and RNA-seq data for these samples are available from the Children’s Brain Tumor Network and the Gabriella Miller Kids First Data Resource Center. Findings from our study will help define the mechanistic shifts of tumor and non-cancerous cells over course of disease progression. Collectively with the single-cell Pediatric Cancer Atlas funded, this project lays the foundation of an important data set focused on lethal relapsed cancers that can continue to be expanded to identify cancer-intrinsic and extrinsic microenvironmental factors supporting recurrence of pediatric brain tumors.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have collaborated with Aviv Regev at the Broad Institute to compare single-cell RNA-sequencing to single-nuclei RNA-sequencing for pediatric solid tumors. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 26 tissue samples from both Retinoblastoma patient tumors and matched O-PDXs as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have developed carefully validated methods to process fresh and frozen tissue for single-cell or single-nucleus RNA-sequencing. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 3 tissue samples from adrenocortical carcinoma patient tumors and 2 matched O-PDX, 1 tissue sample from a germ cell patient tumor, 1 tissue sample from a hepatoblastoma patient tumor, and 3 tissue samples from melanoma patient tumors and 2 matched O-PDX as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have developed carefully validated methods to process fresh and frozen tissue for single-cell or single-nucleus RNA-sequencing. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 17 tissue samples from sarcoma patient tumors and 17 matched O-PDXs as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have developed carefully validated methods to process fresh and frozen tissue for single-cell or single-nucleus RNA-sequencing. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 5 tissue samples from Wilms tumor patient samples and 5 matched O-PDXs as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have developed carefully validated methods to process fresh and frozen tissue for single-cell or single-nucleus RNA-sequencing. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 7 tissue samples from Ewing sarcoma patient tumors and 6 matched O-PDX as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have developed carefully validated methods to process fresh and frozen tissue for single-cell or single-nucleus RNA-sequencing. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 4 tissue samples from rhabdoid tumor patient tumors and 4 matched O-PDX as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Children with metastatic osteosarcoma have an extremely poor prognosis, but little is known about the biologic variables that contribute to metastasis formation. Tumor cells can be found in the circulation of patients with disease burden, but which cells migrate into circulation, and their relationship to the primary tumor and metastatic disease is unknown. This question can not be addressed by traditional bulk sequencing methods that mask the heterogeneity of malignant cells within tumors. Furthermore, it is known that failure of immune surveillance facilitates metastasis, but whether the tumor microenvironment (TME) in osteosarcoma correlates to metastatic disease is unknown. We aim to build a cellular atlas of pediatric osteosarcoma to 1) describe the tumor and immune microenvironment of osteosarcoma using single cell technologies, 2) analyze individual circulating tumor cells (CTCs) by single cell sequencing to describe their phenotypic and phylogenetic relationship to primary and metastatic disease and 3) to correlate tumor and immune single cell gene expression patterns with clinical behavior and biologic features such as genomic alterations. We hypothesize that the TME of osteosarcoma is correlated with clinical variables such as presence of metastasis and response to therapy. By studying circulating tumor cells in the context of primary or metastatic tumors, we aim to demonstrate relationship of CTCs to a heterogeneous tumor, and thereby define the subpopulation with metastatic potential. We will create a cell by cell atlas of primary and metastatic osteosarcoma and CTCs, overlaid with clinical and biologic features. From this atlas we will discover biomarkers predictive of clinical behavior. Knowledge of the TME and features of cells with metastatic potential will inform clinical trials of novel therapeutics that could translate into improved cures for children with osteosarcoma.

Sarcomas are a heterogeneous class of bone and soft tissue tumors comprising over 50 different subtypes and the third most common cancer affecting children. Bone sarcomas in particular account for ~3,500 cases a year and include osteosarcoma, the most common pediatric bone tumor. Despite aggressive chemotherapy and surgical treatment, overall 5-year survivals are ~60% and less than 30% for metastatic disease. There is a dearth of sequencing data for pediatric bone sarcomas, particularly at the single-cell level. Their rarity and high heterogeneity even within the same histologic type has led to major gaps in our understanding of their molecular hallmarks, drivers and evolution. This variability is critical to understanding treatment response and failure, and there remains an urgent need to relate these molecular features to drug sensitivity and patient outcomes. We propose to close this gap by performing single-cell RNA-seq (scRNA-seq) for pediatric bone sarcoma samples. The single-cell level data will allow us to estimate the proportions of cell types in each sample and correlate these with clinical information and outcomes that will be provided for each sample as metadata.

Neuroblastoma is a devastating pediatric cancer, with approximately 50% of diagnosed children experiencing recurrent disease despite aggressive multimodal treatments. Overcoming drug resistance represents a critical challenge in the management of this disease. Leveraging the power of single-cell genomics, we aim to deepen our understanding of neuroblastoma biology, particularly in elucidating complex processes that are not amenable to traditional bulk DNA/RNA sequencing methods, such as cancer cell clonal evolution and therapy resistance. In this study, we conducted a comprehensive single-nuclei RNA sequencing (snRNA-seq) analysis, comparing two sets of paired cell lines: the drug-sensitive CHLA-15 and SMS-KAN, and their drug-resistant counterparts, CHLA20 and SMS-KANR. These cell lines were derived from the same patients, both before and after chemotherapy treatment. Our overarching goal is to unveil distinct cellular states associated with drug resistance by juxtaposing the gene signatures of drug-sensitive and drug-resistant cells.

Pediatric tumors are rare and deadly diseases, currently the leading cause of disease related death in children (Ped), adolescent and young adults (AYA) - Ped-AYA. Gliomas are the most common brain tumor in the Ped-AYA group and malignant high-grade glial lesions remain incurable. The most underserved and understudied group for that disease are the older children, the adolescent group and young adults ranging in age between 15 to 39. Historically, gliomas were explored within two groups: pediatric and adults and AYA glioma were analyzed as a fraction of the adult's population study while patients were distributed through pediatric and adult hospital due to undefined age-related intervention. We identified the unmet need to explore the pediatric population with the AYA age group as these were never studied together. We utilized Ped-AYA HGG samples from the Children's Brain Tumor Network (CBTN). This cohort represents 15 tumor events obtained from 9 patients, with a mix of primary-progression and progression-recurrent tumor pairs. Matched tumor/normal WGS or tumor WGS, tumor RNA-Seq, methylation, and proteogenomics data are available from this cohort through https://github.com/d3b-center/hope-cohort-analysis.

Leukemia is the most frequently diagnosed pediatric cancer, accounting for nearly one third of childhood cancer diagnoses. Although outcomes for pediatric leukemia patients have improved significantly with advents in molecular diagnostics and targeted treatments, a number of patients nonetheless have poor outcomes including treatment-resistant recurrence of their disease. In this dataset, we utilized 10X v2 single-cell RNA sequencing to profile the transcriptomes of 25 pediatric leukemia samples collected from patients at Children’s Mercy Kansas City at single-cell resolution. Viably preserved blood and bone marrow samples collected at initial diagnosis, remission, or recurrence were banked in the Children’s Mercy Tumor Bank biorepository, then profiled for this study. Represented leukemias include B-cell Acute Lymphoblastic Leukemia (B-ALL), T-cell Acute Lymphoblastic Leukemia (T-ALL), and Acute Myeloid Leukemia (AML). Profiled samples include those with well-characterized subtypes (e.g. ETV6::RUNX1 B-ALL) as well as those where a subtype was not determined by standard molecular and cytogenetic methods. Characterization of these samples at single-cell resolution provides a unique opportunity to study the heterogeneity of these cancers, identify subpopulations of interest (e.g. leukemic stem cells), and explore transcriptional similarities between patients with unknown leukemic subtypes and those with a confident diagnosis. Furthering our understanding of the cellular environment of these leukemias is vital for improved diagnosis and treatment selection for pediatric patients afflicted by these cancers.

Samples were multiplexed across three pools. Demultiplexing to create sample-specific FASTQ files was performed via demuxlet based on patient-specific VCF files generated from whole genome or whole exome sequencing. These demultiplexed sample-specific FASTQ files were treated as individual libraries for the ScPCA-nf workflow.

Pediatric solid tumors are rare compared to common adult malignancies and they are also remarkably diverse. For example, rhabdomyosarcomas have features of skeletal muscle, osteosarcomas have features of bone and neuroblastomas have features of cells in the sympathoadrenal lineage. The diversity and rarity of pediatric solid tumors makes it difficult to accelerate biomedical research that can improve patient outcomes. For example, even with the large number of patients treated at St. Jude, it can be difficult to obtain fresh pediatric solid tumor tissue that is suitable for single cell sequencing. To overcome this barrier in the field, we have collaborated with Aviv Regev at the Broad Institute to compare single-cell RNA-sequencing to single-nuclei RNA-sequencing for pediatric solid tumors. Our data show that we can capture the transcriptional heterogeneity of the tumors and the complexity of the tumor microenvironment using single-nuclei RNA-sequencing of patient tumors from the St. Jude biorepository. In addition, over the past 9 years, we have generated 166 orthotopic patient derived xenografts (O-PDXs) representing 21 different pediatric solid tumor types. The O-PDXs and corresponding patient tumors have undergone some of the most comprehensive characterization of any pediatric cancer model including detailed analysis of the clonal heterogeneity (Stewart et al. Nature, 2018). We performed single-cell or single-nuclei RNA-sequencing of 54 tissue samples from both Osteosarcoma patient tumors and matched O-PDXs as part of a larger effort to perform single-cell/single-nuclei RNA-sequencing on a large cohort of patient tumors and O-PDXs. This research proposal will fill a fundamental gap in our knowledge of the transcriptome heterogeneity across pediatric solid tumor clones and of the normal cells found in the tumor microenvironment.

We would greatly appreciate if you cite the listed publications when using this data.

Neuroblastoma is a devastating pediatric cancer, with approximately 50% of diagnosed children experiencing recurrent disease despite aggressive multimodal treatments. Overcoming drug resistance represents a critical challenge in the management of this disease. Leveraging the power of single-cell genomics, we aim to deepen our understanding of neuroblastoma biology, particularly in elucidating complex processes that are not amenable to traditional bulk DNA/RNA sequencing methods, such as cancer cell clonal evolution and therapy resistance.

In this study, we conducted a comprehensive single-nuclei RNA sequencing (snRNA-seq) analysis, comparing matched PDX lines: the drug-sensitive COG-N-603x and its drug-resistant counterpart COG-N-623x, derived from the same patient before and after chemotherapy treatment. Our overarching goal is to unveil distinct cellular states associated with drug resistance by juxtaposing the gene signatures of drug-sensitive and drug-resistant cells.