Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network

Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network Publisher Pubmed

Nekoeian S¹ ; Rostami T² ; Norouzy A³ ; Hussein S^{1, 4} ; Tavoosidana G¹ ; Chahardouli B² ; Rostami S² ; Asgari Y⁵ ; Azizi Z¹

Show Affiliations

1. Department of Molecular Medicine, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran
2. Research Institute for Oncology, Hematology and Cell Therapy, Shariati Hospital, Tehran University of Medical Sciences, Tehran, Iran
3. Department of Energy & Environmental Biotechnology, National Institute of Genetic Engineering and Biotechnology (NIGEB), Tehran, Iran
4. Department of Medical Laboratory Science, University of Raparin, Kurdistan Region, Rania, Iraq
5. Department of Medical Biotechnology, School of Advanced Technologies in Medicine, Tehran University of Medical Sciences, Tehran, Iran

Source: Oncology Research Published:2022

Abstract

Acute lymphoblastic leukemia (ALL) is a malignancy of bone marrow lymphoid precursors. Despite effective treatments, the causes of its progression or recurrence are still unknown. Finding prognostic biomarkers is needed for early diagnosis and more effective treatment. This study was performed to identify long non-coding RNAs (lncRNAs) involved in ALL progression by constructing a competitive endogenous RNA (ceRNA) network. These lncRNAs may serve as potential new biomarkers in the development of ALL. The GSE67684 dataset identified changes in lncRNAs and mRNAs involved in ALL progression. Data from this study were re-analyzed, and probes related to lncRNAs were retrieved. Targetscan, miRTarBase, and miRcode databases were used to identify microRNAs (miRNAs) related to the discovered genes and lncRNAs. The ceRNA network was constructed, and the candidate lncRNAs were selected. Finally, the results were validated with reverse transcription quantitative real-time PCR (RT-qPCR). The ceRNA network outcomes demonstrated that the top lncRNAs associated with altered mRNAs in ALL are IRF1-AS1, MCM3AP-AS1, TRAF3IP2-AS1, HOTAIRM1, CRNDE, and TUG1. Investigations of the subnets linked to MCM3AP-AS1, TRAF3IP2-AS1, and IRF1-AS1 indicated that these lncRNAs were considerably related to pathways associated with inflammation, metastasis, and proliferation. Higher expression levels of IRF1-AS1, MCM3AP-AS1, TRAF3IP2-AS1, CRNDE, and TUG1 were found in ALL samples compared to controls. The expression of MCM3AP-AS1, TRAF3IP2-AS1, and IRF1-AS1 is significantly elevated during the progression of ALL, playing an oncogenic role. Due to their role in the main cancer pathways, lncRNAs could be suitable therapeutic and diagnostic targets in ALL. © 2022, Tech Science Press. All rights reserved.

Related Docs

View other Related Docs

1. Flux Variability Analysis Reveals a Tragedy of Commons in Cancer Cells, SN Applied Sciences (2020)

2. Non-Invasive Stemi-Related Biomarkers Based on Meta-Analysis and Gene Prioritization, Computers in Biology and Medicine (2023)

3. Integrative Analyses of Triple Negative Dysregulated Transcripts Compared With Non-Triple Negative Tumors and Their Functional and Molecular Interactions, Journal of Cellular Physiology (2019)

4. Protein-Protein Interaction Network Analysis of Salivary Proteomic Data in Oral Cancer Cases, Asian Pacific Journal of Cancer Prevention (2018)

5. Upregulation of the Long Noncoding Rna Gja9-Mycbp and Pvt1 Is a Potential Diagnostic Biomarker for Acute Lymphoblastic Leukemia, Cancer Reports (2024)

6. Potential Role of Rab6c-As1 Long Noncoding Rna in Different Cancers, Journal of Cellular Physiology (2018)

7. Crosstalk Between Lncrnas in the Apoptotic Pathway and Therapeutic Targets in Cancer, Cytokine and Growth Factor Reviews (2022)

8. Bcl11a and the Correlated Key Genes Ascribable to Globin Switching: An In-Silico Study, Cardiovascular and Hematological Disorders - Drug Targets (2022)

Experts (# of related papers)

View all Related Experts

Nima Rezaei (1)

Mohammad Hossein Modarressi (1)

Style	Citing Format
MLA	Nekoeian S, et al.. "Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network." Oncology Research, vol. 30, no. 6, 2022, pp. 259-268.
APA	Nekoeian S, Rostami T, Norouzy A, Hussein S, Tavoosidana G, Chahardouli B, Rostami S, Asgari Y, Azizi Z (2022). Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network. Oncology Research, 30(6), 259-268.
Chicago	Nekoeian S, Rostami T, Norouzy A, Hussein S, Tavoosidana G, Chahardouli B, Rostami S, Asgari Y, Azizi Z. "Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network." Oncology Research 30, no. 6 (2022): 259-268.
Harvard	Nekoeian S et al. (2022) 'Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network', Oncology Research, 30(6), pp. 259-268.
Vancouver	Nekoeian S, Rostami T, Norouzy A, Hussein S, Tavoosidana G, Chahardouli B, et al.. Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network. Oncology Research. 2022;30(6):259-268.
BibTex	@article{ author = {Nekoeian S and Rostami T and Norouzy A and Hussein S and Tavoosidana G and Chahardouli B and Rostami S and Asgari Y and Azizi Z}, title = {Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network}, journal = {Oncology Research}, volume = {30}, number = {6}, pages = {259-268}, year = {2022} }
RIS	TY - JOUR AU - Nekoeian S AU - Rostami T AU - Norouzy A AU - Hussein S AU - Tavoosidana G AU - Chahardouli B AU - Rostami S AU - Asgari Y AU - Azizi Z TI - Identification of Lncrnas Associated With the Progression of Acute Lymphoblastic Leukemia Using a Competing Endogenous Rnas Network JO - Oncology Research VL - 30 IS - 6 SP - 259 EP - 268 PY - 2022 ER -

Science Communicator Platform

Authors

Authors Affiliations

Abstract