GEO series
Remodeling of the immune microenvironment is linked to adverse outcome in pediatric T cell acute lymphoblastic leukemia
GSE248287
Homo sapiens
Other; Expression profiling by high throughput sequencing
34 samples
Submitted 2025/07/25
Platform GPL18573
Summary
Changes in the immune microenvironment are frequent in cancers occurring in adult patients, yet our understanding of the pediatric cancer immune microenvironment and its clinical relevance is limited. We investigate the immune microenvironment in pediatric T cell acute lymphoblastic leukemia (T-ALL), using single-cell CITE-seq and immune repertoire analyses. We identify a T-ALL subgroup characterized by a remodeled immune microenvironment, which is associated with adverse clinical outcome in minimal residual disease low patients. This adverse immune landscape is dominated by the presence of a population of non-malignant CD4-CD8-TCRab T cells that interact with CXCL16 expressing non-classical monocytes. Leukemia cell intrinsic transcriptional rewiring in these patients is associated with activation of Rap1 signaling. Inhibiting Rap1 signaling results in increased sensitivity to the BCL2/BCL-XL inhibitor navitoclax. Our study provides insights into the immune microenvironment of pediatric hematologic malignancies, forming the basis for identifying novel (immuno)therapeutic targets and risk stratification for treatment.
Published in
Wiggers CRM, Cho EY, Ozdemir M et al.
· Nature communications 2025
· PMID 41271691
· doi:10.1038/s41467-025-65134-y
This dataset
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Direct links to NCBI, no account and no request form: the whole study as GSE248287_RAW.tar, processed values as the series matrix, the supplementary file directory, and per-sample supplementary files for any of the 34 samples. Raw sequencing reads are also available from ENA.
Also filed as BioProject PRJNA1043165. Searching any of these in the dataset finder brings you back here.
Study design
34 conditions, each sampled once — no replicated groups
Read from 34 sample titles: 34 distinct titles with little repetition. Check it against the sample list below before relying on it.
Samples in this study
0 selected
- GSM7910988 Low_input_RNAseq_invitro_Tcells
- GSM8444428 Normal_PB1_10x5_v1.1
- GSM8444429 Normal_PB2_10x5_v1.1
- GSM8444430 Normal_BM1_10x5_v1.1
- GSM8444431 Normal_BM2_10x5_v1.1
- GSM8444432 PedTALL_P1_Dx_10x5_v1.1
- GSM8444433 PedTALL_P2_Dx_10x5_v1.1
- GSM8444434 PedTALL_P3_Dx_10x5_v1.1
- GSM8444435 PedTALL_P4_Dx_10x5_v1.1
- GSM8444436 PedTALL_P5_Dx_10x5_v1.1
- GSM8444437 PedTALL_P6_Dx_10x5_v1.1
- GSM8444438 PedTALL_P7_Dx_10x5_v1.1
- GSM8444439 PedTALL_P8_Dx_10x5_v1.1
- GSM8444440 PedTALL_P8_D6_10x5_v1.1
- GSM8444441 PedTALL_P8_D32_10x5_v1.1
- GSM8444442 PedTALL_P9_Dx_10x5_v1.1
- GSM8444443 PedTALL_P9_D4_10x5_v1.1
- GSM8444444 PedTALL_P10_Dx_10x5_v1.1
- GSM8444445 PedTALL_P10_D4_10x5_v1.1
- GSM8444446 PedTALL_P10_D47_10x5_v1.1
- GSM8444447 PedTALL_P11_Dx_10x5_v2
- GSM8444448 PedTALL_P11_D4_10x5_v2
- GSM8444449 PedTALL_P11_D32_10x5_v2
- GSM8444450 PedTALL_P12_Dx_10x5_v2
- GSM8444451 PedTALL_P12_D5_10x5_v2
- GSM8444452 PedTALL_P12_D33_10x5_v2
- GSM8444453 PedTALL_P13_Dx_10x5_v2
- GSM8444454 PedTALL_P13_D2_10x5_v2
- GSM8444455 PedTALL_P13_D41_10x5_v2
- GSM8444456 PedTALL_P14_Dx_10x5_v2
- GSM8444457 PedTALL_P14_D2_10x5_v2
- GSM8444458 PedTALL_P14_D32_10x5_v2
- GSM8444459 PedTALL_P15_Dx_10x5_v2
- GSM8444460 PedTALL_P15_D2_10x5_v2
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