Clinical significance of EVI-1 gene expression and aberrations in patient with de-novo acute myeloid and acute lymphoid leukemia

Nabil, Reem; Abdellateif, Mona S.; Gamal, Hend; Hassan, Noha; Badawy, Ragia H.; Ghareeb, Mohamed; Ashry, Mona S. El

doi:10.1016/j.leukres.2023.107019

Cited by 5 publications

(3 citation statements)

References 35 publications

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“…Structural abnormalities of chromosome 3q26 and the corresponding high expression and functional alterations of EVI1 gene are factors of poor prognosis in AML. The proportions of EVI1 overexpression in pediatric AML patients range from 9-23.5%, and its prognostic signi cance remains poorly understood [1,12,[19][20][21][22][23] . In this study, we retrospectively analyzed the clinical data of AML children in our center and found that EVI1 expression levels were indicative for the prognosis of AML children, and the percentage of high EVI1 expression at initial diagnosis of AML was about 24.35%, which correlated with lower CR1 rate and poor OS; high EVI1 expression at the induction treatment stage predicted higher incidence of relapse, and continuous dynamic monitoring of EVI1 with multiple high expression or successive.…”

Section: Discussionmentioning

confidence: 99%

Clinical Significance of Dynamic Monitoring of EVI1 Gene Expression in Pediatric Acute Myeloid Leukemia

Zhang,

Li,

Wang

et al. 2024

Preprint

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Objective To investigate the clinical significance of dynamic monitoring ecotropic virus integration site-1 (EVI1) expression in childhood acute myeloid leukemia (AML). Methods A retrospective analysis was conducted on 113 pediatric AML patients of Wuhan Children's Hospital from 2014 to 2022. The correlation between EVI1 expression levels and clinical indicators including clinical characteristics, first complete remission (CR1), relapse, and overall survival (OS) was analyzed. Receiver operating characteristic (ROC) curve analysis was carried out to comprehend the influence of EVI1 expression on relapse. Results A total of 78 AML children with EVI1 expression at initial diagnosis were eligible, divided into EVI1-positive (EVI1high) and EVI1-negative (EVI1low) groups. FAB classification (P = 0.047) and abnormal karyotype (P = 0.009) showed significant differences between the two groups. The proportion of EVI1 high in individuals with complex and/or monomeric karyotypes was significantly higher than in other cases (P = 0.032). When completing the first induction therapy, the EVI1high group showed a significantly lower CR1 rate than the EVI1low group (P = 0.015). Among 51 cases with EVI1 expression dynamically monitored, those with EVI1 overexpression more than twice had significantly shorter OS (P < 0.05). Among 19 non-HSCT patients undergoing three EVI1 assessments during induction therapy, those with EVI1 overexpression over once had higher relapse rates (P = 0.045). In addition, EVI1 expression level ≥ 83.38% significantly predicted relapse (AUC = 0.833). Conclusion Aberrantly high expression of EVI1 in pediatric AML was associated with poor prognosis. Continuous and dynamic monitoring of EVI1 expression promotes prognostic evaluation. We add some insights into the impact of EVI1 on the AML patients’ OS and survival.

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Section: Discussionmentioning

confidence: 99%

Clinical Significance of Dynamic Monitoring of EVI1 Gene Expression in Pediatric Acute Myeloid Leukemia

Zhang,

Li,

Wang

et al. 2024

Preprint

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“…The upregulation of MECOM and consequent down regulation of network targets is associated with poor prognosis in AML ( 192 ). Hence, EVI1 dysregulation may be a contributor in AML risk stratification ( 197 ) and may be a target for therapeutic intervention. For example, knockdown of EVI1 in K562 cells shows a greater sensitivity to therapeutic drugs (e.g., Imatinib) and amongst other targets (PTGS1, COX-1/2), prevents expression of a gene that affects platelet regulation (ITGA2B) ( 198 ).…”

Section: Biological Mechanisms Of Bmf And/or Hm Predisposition Tfsmentioning

confidence: 99%

Transcription factor genetics and biology in predisposition to bone marrow failure and hematological malignancy

Zerella,

Homan,

Arts

et al. 2023

Front. Oncol.

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Transcription factors (TFs) play a critical role as key mediators of a multitude of developmental pathways, with highly regulated and tightly organized networks crucial for determining both the timing and pattern of tissue development. TFs can act as master regulators of both primitive and definitive hematopoiesis, tightly controlling the behavior of hematopoietic stem and progenitor cells (HSPCs). These networks control the functional regulation of HSPCs including self-renewal, proliferation, and differentiation dynamics, which are essential to normal hematopoiesis. Defining the key players and dynamics of these hematopoietic transcriptional networks is essential to understanding both normal hematopoiesis and how genetic aberrations in TFs and their networks can predispose to hematopoietic disease including bone marrow failure (BMF) and hematological malignancy (HM). Despite their multifaceted and complex involvement in hematological development, advances in genetic screening along with elegant multi-omics and model system studies are shedding light on how hematopoietic TFs interact and network to achieve normal cell fates and their role in disease etiology. This review focuses on TFs which predispose to BMF and HM, identifies potential novel candidate predisposing TF genes, and examines putative biological mechanisms leading to these phenotypes. A better understanding of the genetics and molecular biology of hematopoietic TFs, as well as identifying novel genes and genetic variants predisposing to BMF and HM, will accelerate the development of preventative strategies, improve clinical management and counseling, and help define targeted treatments for these diseases.

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“…Hematopoietic stem cell transplantation is one of the treatment options used to replace diseased cells, which have been destroyed by high doses of chemo or radiotherapy, with healthy ones from a compatible donor [22]. Often the donor is a sibling or family member, but it can also be a stranger with cells compatible with the patient's cells.…”

Section: Introductionmentioning

confidence: 99%

Pattern Recognition of Acute Lymphoblastic Leukemia (ALL) Using Computational Deep Learning

et al. 2023

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Leukemia is a cancer of blood-producing cells, including the bone marrow. Abnormal white blood cells travel through blood vessels and multiply rapidly. Healthy cells in the body become a minority, and the imbalance increases the chances of infection in the body. Leukemia or blood cancer is the most common cancer in children ages 2 -14. Most leukemia in children is treated. Acute lymphocytic leukemia (ALL) is a type of cancer in the blood and bone marrow. It progresses rapidly when immature white blood cells are formed instead of mature ones. Treatments for acute lymphocytic leukemia include drugs and blood transfusions directly into veins, chemotherapy, and all transplantation, which involve transferring organs or tissues within the body or from one person to another. In this paper, Pattern Recognition of Acute Lymphoblastic Leukemia has been proposed using Computational Deep Learning. Pattern recognition technology uses mathematical algorithms to identify patterns in large datasets of data. Analyzing the data, the algorithms can identify patterns indicative of certain states or conditions. In the case of ALL, the algorithm would look for patterns in white blood cell count data that indicate the presence of ALL. These patterns may include changes in the number of white blood cells over time, changes in the composition of the white blood cells, or changes in the levels of certain proteins or gene expressions associated with ALL. The proposed ALLDM model achieved 81.53% (DDS) and 87.92% (SDS) of chemotherapy management, 79.16% (DDS) and 94.31% (SDS) of Stem Cell Transplantation Management, 63.77% (DDS) and 87.37% (SDS) of Radiation therapy Management and 88.92% (DDS) and 85.86% (SDS) of Targeted therapy drugs management.

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Clinical significance of EVI-1 gene expression and aberrations in patient with de-novo acute myeloid and acute lymphoid leukemia

Cited by 5 publications

References 35 publications

Clinical Significance of Dynamic Monitoring of EVI1 Gene Expression in Pediatric Acute Myeloid Leukemia

Clinical Significance of Dynamic Monitoring of EVI1 Gene Expression in Pediatric Acute Myeloid Leukemia

Transcription factor genetics and biology in predisposition to bone marrow failure and hematological malignancy

Pattern Recognition of Acute Lymphoblastic Leukemia (ALL) Using Computational Deep Learning

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