Dataset Information

CD97 is a Critical Regulator of Acute Myeloid Leukemia Stem Cell Function

ABSTRACT: Despite significant efforts to improve therapies for acute myeloid leukemia (AML), clinical outcomes remain poor. Understanding the mechanisms that regulate the development and maintenance of leukemic stem cells (LSC) is important to reveal new therapeutic opportunities. We have identified CD97, a member of the adhesion class of G-protein coupled receptors (GPCRs), as a frequently upregulated antigen of AML blasts that is a critical regulator of blast function. High levels of CD97 correlate with poor prognosis, and silencing of CD97 reduces disease aggressiveness in vivo. In order to analyze the functional pathways associated with CD97 expression, we generated RNA-sequence data from scrambled shRNA transfected (s-shRNA) and CD97 KD human AML cell line HL60, as well as from MLL-AF9 (MA9) transduced GMPs isolated from CD97-/- and WT mice. These phenotypes are due to CD97’s function to promote proliferation, survival, and the maintenance of the undifferentiated state in leukemic blasts. Collectively, our data credential CD97 as a promising therapeutic target on LSCs in AML.

ORGANISM(S): Mus musculus Homo sapiens

PROVIDER: GSE135028 | GEO | 2019/07/30

REPOSITORIES: GEO

ACCESS DATA

Similar Datasets

Project description:Background: Gene expression profiling has shown its ability to identify with high accuracy low cytogenetic risk acute myeloid leukemia such as acute promyelocytic leukemia and leukemias with t(8;21) or inv(16). The aim of this gene expression profiling study was to evaluate to what extent suboptimal samples with low leukemic blast load (range, 2-59%) and/or poor quality control criteria could also be correctly identified. Methods: Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set). Results: With 10-marker classifiers, all training set samples as well as 97 of the 101 test samples with a low blast load, and all 10 samples with poor quality control criteria were correctly classified. Regarding test set samples, the overall error rate of the class prediction was below 4 percent, even though the leukemic blast load was as low as 2%. Sensitivity, specificity, negative and positive predictive values of the class assignments ranged from 91% to 100%. Of note, for acute promyelocytic leukemia and leukemias with t(8;21) or inv(16), the confidence level of the class assignment was influenced by the leukemic blast load. Conclusion: Gene expression profiling and a supervised method requiring 10-marker classifiers enable the identification of favorable cytogenetic risk acute myeloid leukemia even when samples contain low leukemic blast loads or display poor quality control criterion. Specific signatures were first defined so that all 71 acute promyelocytic leukemia, leukemia with t(8;21) or inv(16)-AML as well as cytogenetically normal acute myeloid leukemia samples with at least 60% blasts and good quality control criteria were correctly classified (training set). The classifiers were then evaluated for their ability to assign to the expected class 111 samples considered as suboptimal because of a low leukemic blast load (n=101) and/or poor quality control criteria (n=10) (test set).

Dataset Information

CD97 is a Critical Regulator of Acute Myeloid Leukemia Stem Cell Function

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure