Related Experiment Video
Updated: Feb 13, 2026
08:40
Methyl-binding DNA capture Sequencing for Patient Tissues
Published on: October 31, 2016
9.1K
CDKN2B Methylation Correlates with Survival in AML Patients
Esmat Kamali Dolatabadi1, Mohammadreza Ostadali Dehaghi2, Naser Amirizadeh3
1Department of Biology, Science and Research Branch´ Islamic Azad University, Tehran Iran.
Iranian Journal of Pharmaceutical Research : IJPR
|March 20, 2018
Summary
Aberrant DNA methylation of the CDKN2B gene is linked to poorer survival rates in acute myeloid leukemia (AML) patients. This methylation may serve as a prognostic marker for AML survival.
Area of Science:
- Oncology
- Molecular Biology
- Genetics
Background:
- Aberrant DNA methylation is a key feature in acute myeloid leukemia (AML).
- The clinical significance of DNA methylation changes in AML, particularly for the CDKN2B gene, remains unclear.
Purpose of the Study:
- To investigate the frequency and clinical significance of CDKN2B promoter hyper-methylation and its association with gene expression and patient outcomes in Iranian AML patients.
Main Methods:
- Methylation Specific Melting Curve Analysis (MS-MCA) and real-time PCR were employed.
- Assessed CDKN2B promoter hyper-methylation and gene expression in 59 AML patients.
Main Results:
- CDKN2B hyper-methylation occurred in 37.3% of patients, correlating with reduced gene expression (P=0.007).
- Aberrant CDKN2B methylation was associated with lower survival rates (P=0.043), higher leukemic blast cell proportion (P=0.022), and elevated white blood cell counts (P=0.0123).
- Methylation patterns varied across AML subtypes (M2, M3, M4), but no significant correlation was found with treatment outcome or CDKN2B expression and survival.
Conclusions:
- Aberrant CDKN2B methylation is a molecular mechanism affecting gene expression in AML.
- CDKN2B methylation can be considered a prognostic marker for predicting AML patient survival.
More Related Videos
11:19Correlating Gene-specific DNA Methylation Changes with Expression and Transcriptional Activity of Astrocytic KCNJ10 Kir4.1
Published on: September 26, 2015
8.5K
13:21Comprehensive DNA Methylation Analysis Using a Methyl-CpG-binding Domain Capture-based Method in Chronic Lymphocytic Leukemia Patients
Published on: June 16, 2017
10.6K
Related Concept Videos
02:20Correlations
36.6K
Correlation means that there is a relationship between two or more variables (such as ice cream consumption and crime), but this relationship does not necessarily imply cause and effect. When two variables are correlated, it simply means that as one variable changes, so does the other. We can measure correlation by calculating a statistic known as a correlation coefficient. A correlation coefficient is a number from -1 to +1 that indicates the strength and direction of the relationship between...
36.6K
01:27Correlation and Causation
42.9K
Statistical tests can calculate whether there is a relationship, or correlation, between independent and dependent variables. An indirect relationship of the variables signifies a correlation, while a direct relationship shows causation. If it is determined that no connection exists between the variables, then the correlation is a coincidence.
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
Correlation versus Causation
If the dependent variable increases or decreases when the independent variable increases, there is a positive or negative...
42.9K
01:09Correlation
15.2K
In statistics, two variables are said to be correlated if the values of one variable are associated with the other variable. Depending on the relationship between two variables, correlation can be of three types– positive correlation, negative correlation, and zero correlation.
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
Two variables, for example, a and b, are said to be positively correlated if both variables move in the same direction. In other words, a positive correlation exists between two variables, a and b, if:
15.2K
01:18Survival Curves
732
Survival curves are graphical representations that depict the survival experience of a population over time, offering an intuitive way to track the proportion of individuals who remain event-free at each time point. These curves are widely used in fields such as medicine, public health, and reliability engineering to visualize and compare survival probabilities across different groups or conditions.
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
732
01:19Survival Tree
436
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
436
01:18Introduction To Survival Analysis
831
Survival analysis is a statistical method used to study time-to-event data, where the "event" might represent outcomes like death, disease relapse, system failure, or recovery. A unique feature of survival data is censoring, which occurs when the event of interest has not been observed for some individuals during the study period. This requires specialized techniques to handle incomplete data effectively.
The primary goal of survival analysis is to estimate survival time—the time...
The primary goal of survival analysis is to estimate survival time—the time...
831