RT-PCR (Gene Expression Profiling of Key Oncogenes and Tumor Suppressor Genes in Leukemia)

Published: 3 March 2025| Version 1 | DOI: 10.17632/26956f94vz.1
Contributors:
Amir Jalali, Saja Jawad Obaid Al-Sailawi, Basma Maytham Oleiwi, Sura Hasan Hadi

Description

This study investigates the expression profiles of key oncogenes (FLT3, MYC, CXCR4, KIT) and tumor suppressor genes (TP53, RUNX1, BCR-ABL1) in leukemia patients compared to healthy controls. Using RT-qPCR, significant dysregulation of these genes was observed, highlighting their potential roles in leukemia progression. The findings suggest these genes as promising biomarkers for early diagnosis and therapeutic targets. Statistical analysis revealed significant correlations between specific genes, providing insights into their interactions in leukemia. This research contributes to understanding the molecular mechanisms of leukemia and supports the development of targeted therapies for improved patient outcomes.

Files

Steps to reproduce

1- Obtain ethical approval (ID: IR.ARAKU.REC.1403.040) and collect peripheral blood samples from 38 leukemia patients and 38 healthy controls (February–June 2024). Confirm diagnosis using CBC, bone marrow biopsy, and flow cytometry (WHO guidelines). 2- Extract RNA from white blood cells using the Pars Tos kit (Cat No: A101231). Assess RNA quality (A260/A280 ~2.0) and integrity (agarose gel). Store at -40°C. 3- Synthesize cDNA using the Pars Tos kit (Cat No: A101161). Incubate at 45°C for 60 minutes, then inactivate at 85°C. Store at 4°C or -40°C. 4- Perform qPCR using gene-specific primers (MYC, JAK2, CXCR4, KIT, RUNX1, ETV6, BCR-ABL1, TP53, FLT3, GAPDH). Normalize with GAPDH and calculate fold changes using the ΔΔCt method. 5- Analyze data with SPSS (version 16). Perform t-tests and correlation analyses (p < 0.05). Apply Bonferroni correction for multiple comparisons.

Institutions

Arak University

Categories

Targeted Therapy, Early Diagnosis

Licence