← BioTransfer GEO Dataset Finder
GEO series

Single-cell Transcriptomic and Proteomic Analysis of Acute Myeloid Leukemia (AML) Patients with Abnormalities on Chromosome 7

GSE271741 Homo sapiens Expression profiling by high throughput sequencing 24 samples 2026/07/01 GPL24676
Summary
Chromosome 7 (chr7) abnormalities are commonly seen in patients with acute myeloid leukemia (AML) or myelodysplastic syndromes and are associated with poor prognosis. Flow cytometry (FCM) is typically used clinically to quantify residual malignancy during treatment but the relationship of cell surface immunophenotype with genetic features is incompletely defined. Single-cell RNA sequencing (scRNA-seq) with oligonucleotide-conjugated antibodies may be able to integrate cytogenetic genotypes found within leukemic clones with specific transcriptomic and immunophenotypic signatures. Bone marrow (BM) aspirate was collected from 12 AML patients with known abnormalities on chr7 according to cytogenetics studies. Among all 12 patients, 3 of them only had monosomy 7 as the sole genetic aberration, while 9 patients had abnormalities on additional chromosomes. By scRNA-seq with oligonucleotide-conjugated antibodies, we identified the correlation between cell types showed distinct features among patients, and cells in different groups had different protein expression profiles. By comparing the expression profile of AML patients with abnormalities on chr7 to HDs, this study provides evidence that leukemic immunophenotype is correlated with chromosomal structural changes. The experiments on a single-cell level were able to identify clones in higher resolution and revealed potential cell surface protein markers that could be used clinically to identify specific malignant populations in patients with myeloid malignancies.
Download
NCBI GEO page ↗ {# Names what the click gives you. "Open in finder" meant nothing to a visitor who arrived from a search engine and has never seen the tool. #} Find more human RNA-seq datasets →
Similar datasets

Search all human RNA-seq datasets in GEO →

Share this dataset

Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.