Number of Projects: 2
Single-cell profiling of Acute Myeloid Leukemia for high-resolution chemo-immunotherapy target discovery
Size: 2.73 GB
30 Downloadable Samples
DiagnosisAcute myeloid leukemia (26), Non-cancerous (2), T-myeloid mixed phenotype acute leukemia (2)
AbstractBulk 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.
Additional Sample Metadata Fieldsparticipant_id, scpca_project_id, submitter, submitter_id
Size: 18.34 GB
100 Downloadable Samples
DiagnosisB-cell acute lymphoblastic leukemia (91), Early T-cell precursor T-cell acute lymphoblastic leukemia (5), Mixed phenotype acute leukemia (3), T-cell acute lymphoblastic leukemia (1)
AbstractAcute 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.
Additional Sample Metadata Fieldsblasts_percentage, participant_id, risk_group, scpca_project_id, submitter, submitter_id, white_blood_cell_count