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Deregulated expression of circular RNAs in acute myeloid leukemia.

ABSTRACT: Circular RNAs (circRNAs) are dynamically regulated during differentiation and show cell type-specific expression, which is altered in cancer and can have a direct impact on its various hallmarks. We hypothesized that circRNA expression is deregulated in acute myeloid leukemia (AML) and that circRNA candidates might contribute to the pathogenesis of the disease. To identify leukemia-associated and differentiation-independent changes in circRNA expression, we determined the circular RNAome of 61 AML patients and 16 healthy hematopoietic stem and progenitor cell (HSPC) samples using ribosomal RNA-depleted RNA sequencing. We found hundreds of circRNAs that were differentially expressed between AML and healthy HSPCs. Gene set analysis found that many of these circRNAs were transcribed from genes implicated in leukemia biology. We discovered a circRNA derived from the T-cell transcription factor gene B cell CLL/lymphoma 11B, circBCL11B, which was exclusively expressed in AML patients, but not detected in healthy HSPCs, and associated with a T-cell-like gene expression signature. We were able to validate this finding in an independent cohort of 332 AML patients. Knockdown of circBCL11B had a negative effect on leukemic cell proliferation and resulted in increased cell death of leukemic cells, thereby suggesting circBCL11B as a novel functionally relevant candidate in AML pathogenesis. In summary, our study enables comprehensive insights into circRNA expression changes upon leukemic transformation and provides valuable information on the biology of leukemic cells and potential novel pathway dependencies that are relevant for AML therapy.

SUBMITTER: Lux S

PROVIDER: S-EPMC7948263 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Background: Previous studies have reported that genes highly expressed in leukemic stem cells (LSC) may dictate the survival probability of patients and expression-based cellular deconvolution may be informative in forecasting prognosis. However, whether the prognosis of acute myeloid leukemia (AML) can be predicted using gene expression and deconvoluted cellular abundances is debatable. Methods: Nine different cell-type abundances of a training set composed of the AML samples of 422 patients, were used to build a model for predicting prognosis by least absolute shrinkage and selection operator Cox regression. This model was validated in two different validation sets, TCGA-LAML and Beat AML (n = 179 and 451, respectively). Results: We introduce a new prognosis predicting model for AML called the LSC activity (LSCA) score, which incorporates the abundance of 5 cell types, granulocyte-monocyte progenitors, common myeloid progenitors, CD45RA + cells, megakaryocyte-erythrocyte progenitors, and multipotent progenitors. Overall survival probabilities between the high and low LSCA score groups were significantly different in TCGA-LAML and Beat AML cohorts (log-rank p-value = 3.3×10-4 and 4.3×10-3, respectively). Also, multivariate Cox regression analysis on these two validation sets shows that LSCA score is independent prognostic factor when considering age, sex, and cytogenetic risk (hazard ratio, HR = 2.17; 95% CI 1.40-3.34; p < 0.001 and HR = 1.20; 95% CI 1.02-1.43; p < 0.03, respectively). The performance of the LSCA score was comparable to other prognostic models, LSC17, APS, and CTC scores, as indicated by the area under the curve. Gene set variation analysis with six LSC-related functional gene sets indicated that high and low LSCA scores are associated with upregulated and downregulated genes in LSCs. Conclusion: We have developed a new prognosis prediction scoring system for AML patients, the LSCA score, which uses deconvoluted cell-type abundance only.

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Deregulated expression of circular RNAs in acute myeloid leukemia.

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