Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR18394019_1.fastq.gz | Fastqsanger.gz | |||
| SRR18394019_2.fastq.gz | Fastqsanger.gz |
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Project description:Gene products from the highly variable major histocompatibility locus, including HLA, are essential for self-recognition and immune surveillance of malignancy. Following allogeneic hematopoietic cell transplantation (alloHCT), genetic and epigenetic alterations in HLA can drive disease recurrence, making precise HLA assessment critical for determination of future therapy. However, current methods lack the sensitivity to quantify HLA transcripts at the single cell level, limiting their clinical utility. We introduce scrHLA-typing, a novel method that accurately identifies and quantifies HLA transcripts in single cells using hybridization capture and long-read sequencing. When applied to samples from patients with post-transplant relapse, scrHLA-typing successfully detected allele-specific expression of MHC gene products at clinically actionable levels. By characterizing allele expression in residual leukemia cells, our assay identified differences in expression patterns among patients. This capability highlights scrHLA-typing’s potential to improve risk stratification and guide the selection of appropriate salvage therapies, enhancing personalized treatment strategies after post-transplant relapse.
2025-09-17 | GSE305306 | GEO
Project description:Gene products from the highly variable major histocompatibility locus, including HLA, are essential for self-recognition and immune surveillance of malignancy. Following allogeneic hematopoietic cell transplantation (alloHCT), genetic and epigenetic alterations in HLA can drive disease recurrence, making precise HLA assessment critical for determination of future therapy. However, current methods lack the sensitivity to quantify HLA transcripts at the single cell level, limiting their clinical utility. We introduce scrHLA-typing, a novel method that accurately identifies and quantifies HLA transcripts in single cells using hybridization capture and long-read sequencing. When applied to samples from patients with post-transplant relapse, scrHLA-typing successfully detected allele-specific expression of MHC gene products at clinically actionable levels. By characterizing allele expression in residual leukemia cells, our assay identified differences in expression patterns among patients. This capability highlights scrHLA-typing’s potential to improve risk stratification and guide the selection of appropriate salvage therapies, enhancing personalized treatment strategies after post-transplant relapse.
2025-09-17 | GSE305305 | GEO
Project description:Gene products from the highly variable major histocompatibility locus, including HLA, are essential for self-recognition and immune surveillance of malignancy. Following allogeneic hematopoietic cell transplantation (alloHCT), genetic and epigenetic alterations in HLA can drive disease recurrence, making precise HLA assessment critical for determination of future therapy. However, current methods lack the sensitivity to quantify HLA transcripts at the single cell level, limiting their clinical utility. We introduce scrHLA-typing, a novel method that accurately identifies and quantifies HLA transcripts in single cells using hybridization capture and long-read sequencing. When applied to samples from patients with post-transplant relapse, scrHLA-typing successfully detected allele-specific expression of MHC gene products at clinically actionable levels. By characterizing allele expression in residual leukemia cells, our assay identified differences in expression patterns among patients. This capability highlights scrHLA-typing’s potential to improve risk stratification and guide the selection of appropriate salvage therapies, enhancing personalized treatment strategies after post-transplant relapse.
2025-09-17 | GSE305307 | GEO
Project description:HLA typing by SMRT DNA sequencing
| PRJEB21509 | ENA
Project description:Insulin-dependent diabetes mellitus (T1D) is an organ-specific auto-immune disease caused by the selective destruction of the pancreatic beta cells by inflammatory cells, especially auto-reactive CD8+ T lymphocytes. In this study we evaluated the differential large scale gene expression profiling using cDNA microarrays of T (CD4+ and CD8+) and monocyte (CD14+) cells. In addition, considering that HLA class II profile may influence the expression of these molecules on the surface of peripheral blood cells, and considering that the mechanisms by which HLA class II susceptibility alleles drive the auto-immune response have not been elucidated, we intend to further stratify T1D patients according to the HLA class II profile. 20 pre-pubertal recently diagnosed T1D patients were selected, HLA-DRB1/DQB1 allele typing and separated in two groups. The group 1(G1) had patients with susceptibility alleles and group 2 (G2) with at least one protection allele. To established relationships between genes, the GeneNetwork 1.2 algorithm was used, 6 networks were obtained, TCD4+ G1 patients X controls, TCD4+ G2 patients X controls, and same situation to TCD8+ and CD14+.
2011-06-15 | E-MEXP-3223 | biostudies-arrayexpress