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Contains fulltext : 232033.pdf (Publisher’s version ) (Open Access), Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.

Acute myeloid leukemia (AML) is caused by genetic aberrations that also govern the prognosis of patients and guide risk-adapted and targeted therapy. Genetic aberrations in AML are structurally diverse and currently detected by different diagnostic assays. This study sought to establish whole transcriptome RNA sequencing as single, comprehensive, and flexible platform for AML diagnostics. We developed HAMLET (Human AML Expedited Transcriptomics) as bioinformatics pipeline for simultaneous detection of fusion genes, small variants, tandem duplications, and gene expression with all information assembled in an annotated, user-friendly output file. Whole transcriptome RNA sequencing was performed on 100 AML cases and HAMLET results were validated by reference assays and targeted resequencing. The data showed that HAMLET accurately detected all fusion genes and overexpression of EVI1 irrespective of 3q26 aberrations. In addition, small variants in 13 genes that are often mutated in AML were called with 99.2% sensitivity and 100% specificity, and tandem duplications in FLT3 and KMT2A were detected by a novel algorithm based on soft-clipped reads with 100% sensitivity and 97.1% specificity. In conclusion, HAMLET has the potential to provide accurate comprehensive diagnostic information relevant for AML classification, risk assessment and targeted therapy on a single technology platform.

Contains fulltext : 152413.pdf (publisher's version ) (Open Access)

Contains fulltext : 153253.pdf (publisher's version ) (Open Access)

Item does not contain fulltext, Hematological malignancies often express surface HLA class II, making them attractive targets for CD4+ T cell therapy. We previously demonstrated that HLA class II ligands can be divided into DM-resistant and DM-sensitive antigens. In contrast to presentation of DM-resistant antigens, presentation of DM-sensitive antigens is suppressed by HLA-DM but can be rescued by HLA-DO. We also showed that HLA-DO expression remains low in nonhematopoietic cells under inflammatory conditions, suggesting that DM-sensitive antigens may be ideal T cell targets with a low risk for graft-versus-host disease. Here, we demonstrated that B cell malignancies often express HLA-DO and that levels are in particular high in chronic lymphocytic leukemia. Moreover, we showed that surface presentation of DM-sensitive antigens is regulated by HLA-DO, and that DM-sensitive antigens are relevant T cell targets for B cell malignancies and, especially, chronic lymphocytic leukemia. These data open the perspective to target HLA class II ligands with specific processing and presentation behavior for CD4+ T cell therapy of hematological malignancies.