High expression of miR-107 and miR-17 predicts poor prognosis and guides treatment selection in acute myeloid leukemia

Identifying key genes and functionally enriched pathways in acute myeloid leukemia by weighted gene co-expression network analysis

Acute myeloid leukemia (AML) is characterized by the uncontrolled proliferation of myeloid leukemia cells in the bone marrow and other hematopoietic tissues and is highly heterogeneous. While with the progress of sequencing technology, understanding of the AML-related biomarkers is still incomplete. The purpose of this study is to identify potential biomarkers for prognosis of AML. Based on WGCNA analysis of gene mutation expression, methylation level distribution, mRNA expression, and AML-related genes in public databases were employed for investigating potential biomarkers for the prognosis of AML. This study screened a total of 6153 genes by analyzing various changes in 103 acute myeloid leukemia (AML) samples, including gene mutation expression, methylation level distribution, mRNA expression, and AML-related genes in public databases. Moreover, seven AML-related co-expression modules were mined by WGCNA analysis, and twelve biomarkers associated with the AML prognosis were identified from each top 10 genes of the seven co-expression modules. The AML samples were then classified into two subgroups, the prognosis of which is significantly different, based on the expression of these twelve genes. The differentially expressed 7 genes of two subgroups (HOXB-AS3, HOXB3, SLC9C2, CPNE8, MEG8, S1PR5, MIR196B) are mainly involved in glucose metabolism, glutathione biosynthesis, small G protein-mediated signal transduction, and the Rap1 signaling pathway. With the utilization of WGCNA mining, seven gene co-expression modules were identified from the TCGA database, and there are unreported genes that may be potential driver genes of AML and may be the direction to identify the possible molecular signatures to predict survival of AML patients and help guide experiments for potential clinical drug targets.

MicroRNAs Associated with a Bad Prognosis in Acute Myeloid Leukemia and Their Impact on Macrophage Polarization

MicroRNAs (miRNAs) are short, non-coding ribonucleic acids (RNAs) associated with gene expression regulation. Since the discovery of the first miRNA in 1993, thousands of miRNAs have been studied and they have been associated not only with physiological processes, but also with various diseases such as cancer and inflammatory conditions. MiRNAs have proven to be not only significant biomarkers but also an interesting therapeutic target in various diseases, including cancer. In acute myeloid leukemia (AML), miRNAs have been regarded as a welcome addition to the limited therapeutic armamentarium, and there is a vast amount of data on miRNAs and their dysregulation. Macrophages are innate immune cells, present in various tissues involved in both tissue repair and phagocytosis. Based on their polarization, macrophages can be classified into two groups: M1 macrophages with pro-inflammatory functions and M2 macrophages with an anti-inflammatory action. In cancer, M2 macrophages are associated with tumor evasion, metastasis, and a poor outcome. Several miRNAs have been associated with a poor prognosis in AML and with either the M1 or M2 macrophage phenotype. In the present paper, we review miRNAs with a reported negative prognostic significance in cancer with a focus on AML and analyze their potential impact on macrophage polarization.

Effective Prognostic Model for Therapy Response Prediction in Acute Myeloid Leukemia Patients

Acute myeloid leukemia (AML) is a hematopoietic disorder characterized by the malignant transformation of bone marrow-derived myeloid progenitor cells with extremely short survival. To select the optimal treatment options and predict the response to therapy, the stratification of AML patients into risk groups based on genetic factors along with clinical characteristics is carried out. Despite this thorough approach, the therapy response and disease outcome for a particular patient with AML depends on several patient- and tumor-associated factors. Among these, tumor cell resistance to chemotherapeutic agents represents one of the main obstacles for improving survival outcomes in AML patients. In our study, a new prognostic scale for the risk stratification of AML patients based on the detection of the sensitivity or resistance of tumor cells to chemotherapeutic drugs in vitro as well as MDR1 mRNA/P-glycoprotein expression, tumor origin (primary or secondary), cytogenetic abnormalities, and aberrant immunophenotype was developed. This study included 53 patients diagnosed with AML. Patients who received intensive or non-intensive induction therapy were analyzed separately. Using correlation, ROC, and Cox regression analyses, we show that the risk stratification of AML patients in accordance with the developed prognostic scale correlates well with the response to therapy and represents an independent predictive factor for the overall survival of patients with newly diagnosed AML.