Long non-coding RNA as potential diagnostic markers for acute myeloid leukemia: A systematic review and meta-analysis.
acute myeloid leukemia
biomarker
diagnosis
long noncoding RNA
meta‐analysis
Journal
Cancer medicine
ISSN: 2045-7634
Titre abrégé: Cancer Med
Pays: United States
ID NLM: 101595310
Informations de publication
Date de publication:
Jun 2024
Jun 2024
Historique:
revised:
23
05
2024
received:
22
01
2024
accepted:
28
05
2024
medline:
12
6
2024
pubmed:
12
6
2024
entrez:
12
6
2024
Statut:
ppublish
Résumé
Acute myeloid leukemia (AML) is aggressive type of hematological malignancy. Its poses challenges in early diagnosis, necessitating the identification of an effective biomarker. This study aims to assess the diagnostic accuracy of long noncoding RNAs (lncRNA) in the diagnosis of AML through a meta-analysis. The study is registered on the PROSPERO website with the number 493518. A literature search was conducted in the PubMed, Embase, Hinari, and the Scopus databases to identify relevant studies. We pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristics (ROC) using Stata 14.1 software. Heterogeneity between studies was determined through the I A total of 14 articles covering 19 studies were included in this meta-analysis comprising 1588 AML patients and 529 healthy participants. The overall pooled sensitivity, specificity, PLR, NLR, DOR, and the area under the summary ROC curve were 0.85 (95% CI = 0.78-0.91), 0.82 (95% CI = 0.72-0.89), 4.7 (95% CI = 2.9-7.4), 0.18 (95% CI = 0.12-0.28), 26 (95% CI = 12-53), and 0.90 (95% CI = 0.87-0.93), respectively. Moreover, lncRNAs from non-bone marrow mononuclear cells (BMMC) had superior diagnostic value with pooled sensitivity, specificity, and AUC were 0.93, 0.82, and 0.95, respectively. This meta-analysis demonstrated that circulating lncRNAs can serve as potential diagnostic markers for AML. High accuracy of diagnosis was observed in non-BMMC lncRNAs, given cutoff value, and the GADPH internal reference gene used. However, further studies with large sample size are required to confirm our results.
Sections du résumé
BACKGROUND
BACKGROUND
Acute myeloid leukemia (AML) is aggressive type of hematological malignancy. Its poses challenges in early diagnosis, necessitating the identification of an effective biomarker. This study aims to assess the diagnostic accuracy of long noncoding RNAs (lncRNA) in the diagnosis of AML through a meta-analysis. The study is registered on the PROSPERO website with the number 493518.
METHOD
METHODS
A literature search was conducted in the PubMed, Embase, Hinari, and the Scopus databases to identify relevant studies. We pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and area under the summary receiver operating characteristics (ROC) using Stata 14.1 software. Heterogeneity between studies was determined through the I
RESULTS
RESULTS
A total of 14 articles covering 19 studies were included in this meta-analysis comprising 1588 AML patients and 529 healthy participants. The overall pooled sensitivity, specificity, PLR, NLR, DOR, and the area under the summary ROC curve were 0.85 (95% CI = 0.78-0.91), 0.82 (95% CI = 0.72-0.89), 4.7 (95% CI = 2.9-7.4), 0.18 (95% CI = 0.12-0.28), 26 (95% CI = 12-53), and 0.90 (95% CI = 0.87-0.93), respectively. Moreover, lncRNAs from non-bone marrow mononuclear cells (BMMC) had superior diagnostic value with pooled sensitivity, specificity, and AUC were 0.93, 0.82, and 0.95, respectively.
CONCLUSION
CONCLUSIONS
This meta-analysis demonstrated that circulating lncRNAs can serve as potential diagnostic markers for AML. High accuracy of diagnosis was observed in non-BMMC lncRNAs, given cutoff value, and the GADPH internal reference gene used. However, further studies with large sample size are required to confirm our results.
Substances chimiques
RNA, Long Noncoding
0
Biomarkers, Tumor
0
Types de publication
Journal Article
Systematic Review
Meta-Analysis
Langues
eng
Sous-ensembles de citation
IM
Pagination
e7376Informations de copyright
© 2024 The Author(s). Cancer Medicine published by John Wiley & Sons Ltd.
Références
Arber DA, Orazi A, Hasserjian RP, Borowitz MJ, et al. International consensus classification of myeloid neoplasms and acute leukemias: integrating morphologic, clinical, and genomic data. Blood. 2022;140(11):1200‐1228.
Kantarjian H, Kadia T, Dinardo C, et al. Acute myeloid leukemia: current progress and future directions. Blood Cancer J. 2021;11(2):41.
Dong Y, Shi O, Zeng Q, Lu X, et al. Leukemia incidence trends at the global, regional, and national level between 1990 and 2017. Exp Hematol Oncol. 2020;9:14.
Cancer Stat Facts: Leukemia—Acute Myeloid Leukemia (AML). National Cancer Institute (NIH) Surveillance, Epidemiology, and End Results Program. 2024 Accessed in January 10, https://seer.cancer.gov/statfacts/html/amyl.html
Klepin HD, Rao AV, Pardee TS. Acute myeloid leukemia and myelodysplastic syndromes in older adults. J Clin Oncol. 2014;32(24):2541.
Nagel G, Weber D, Fromm E, et al. Epidemiological, genetic, and clinical characterization by age of newly diagnosed acute myeloid leukemia based on an academic population‐based registry study (AMLSG BiO). Ann Hematol. 2017;96:1993‐2003.
Kung JT, Colognori D, Lee JT. Long noncoding RNAs: past, present, and future. Genetics. 2013;193(3):651‐669.
Iyer MK, Niknafs YS, Malik R, Singhal U, et al. The landscape of long noncoding rnas in the human transcriptome. Nat Genet. 2015;47(3):199‐208.
Zhao L, Wang J, Li Y, Song T, et al. NONCODEV6: an updated database dedicated to long non‐coding rna annotation in both animals and plants. Nucleic Acids Res. 2021;49(D1):D165‐D171.
Ponting CP, Oliver PL, Reik W. Evolution and functions of long noncoding RNAs. Cell. 2009;136(4):629‐641.
Kopp F, Mendell JT. Functional classification and experimental dissection of long noncoding RNAs. Cell. 2018;172(3):393‐407.
Cun S‐E, Zheng JT, Liu R, Zheng L, Wang YM. Research Progress of long non‐coding RNA in acute myeloid leukemia—review. Zhongguo Shi Yan Xue Ye Xue Za Zhi. 2023;31(1):287‐291.
Wang X, Tong Y, Xun T, et al. Functions, mechanisms, and therapeutic implications of noncoding RNA in acute myeloid leukemia. Fundamental Research. 2023;2023.
Bhan A, Soleimani M, Mandal SS. Long noncoding RNA and cancer: a new paradigm. Cancer Res. 2017;77(15):3965‐3981.
Connerty P, Lock RB. The tip of the iceberg—the roles of long noncoding RNAs in acute myeloid leukemia. Wiley Interdiscip Rev RNA. 2023;14(6):e1796.
Mer AS, Lindberg J, Nilsson C, et al. Expression levels of long non‐coding RNAs are prognostic for AML outcome. J Hematol Oncol. 2018;11(1):52.
Heuston EF, Lemon KT, Arceci RJ. The beginning of the road for non‐coding RNAs in normal hematopoiesis and hematologic malignancies. Front Genet. 2011;2:94.
Schmitt AM, Chang HY. Long noncoding RNAs in cancer pathways. Cancer Cell. 2016;29(4):452‐463.
Liu Y, Cheng Z, Pang Y, et al. Role of microRNAs, circRNAs and long noncoding RNAs in acute myeloid leukemia. J Hematol Oncol. 2019;12(1):51.
Sheng H, Zhang J, Ma Y, et al. lncRNA FBXL19‐AS1 is a diagnosis biomarker for paediatric patients with acute myeloid leukemia. J Gene Med. 2021;23(3):e3317.
Newell LF, Cook RJ. Advances in acute myeloid leukemia. BMJ. 2021;375:n2026.
Xiao Q, Lin C, Peng M, et al. Circulating plasma exosomal long non‐coding RNAs LINC00265, LINC00467, UCA1, and SNHG1 as biomarkers for diagnosis and treatment monitoring of acute myeloid leukemia. Front Oncol. 2022;12:1033143.
Zheng J, Song Y, Li Z, et al. The implication of lncRNA expression pattern and potential function of lncRNA RP4‐576H24 2 in acute myeloid leukemia. Cancer Med. 2019;8(17):7143‐7160.
Feng Y, Shen Y, Chen H, et al. Expression profile analysis of long non‐coding RNA in acute myeloid leukemia by microarray and bioinformatics. Cancer Sci. 2018;109(2):340‐353.
Gourvest M, Brousset P, Bousquet MJC. Long noncoding RNAs in acute myeloid leukemia: functional characterization and clinical relevance. Cancers (Basel). 2019;11(11):1638.
Page MJ, McKenzie JE, Bossuyt PM, et al. The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ. 2021;88:105906.
Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS‐2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med. 2011;155(8):529‐536.
Higgins JP, Thompson SG, Deeks JJ, et al. Measuring inconsistency in meta‐analyses. BMJ. 2003;327(7414):557‐560.
Ma L, Kuai WX, Sun XZ, Lu XC, et al. Long noncoding RNA LINC00265 predicts the prognosis of acute myeloid leukemia patients and functions as a promoter by activating PI3K‐AKT pathway. Eur Rev Med Pharmacol Sci. 2018;22(22):7867‐7876.
Tan Z, Zhu K, Yin Y, et al. Long non‐coding RNA ANRIL is a potential indicator of disease progression and poor prognosis in acute myeloid leukemia. Mol Med Rep. 2021;23(2):1.
Wang Y, Li Y, Song HQ, Sun GW. Long non‐coding RNA LINC00899 as a novel serum biomarker for diagnosis and prognosis prediction of acute myeloid leukemia. Eur Rev Med Pharmacol Sci. 2018;22(21):7364‐7370.
Zhang T‐J, Zhou JD, Zhang W, et al. H19 overexpression promotes leukemogenesis and predicts unfavorable prognosis in acute myeloid leukemia. Clin Epigenetics. 2018;10(1):1‐12.
Yang L, Zhou JD, Zhang TJ, et al. Overexpression of lncRNA PANDAR predicts adverse prognosis in acute myeloid leukemia. Cancer Manag Res. 2018;10:4999‐5007.
Jiang Z, Yu Q, Luo X. Identification of long non‐coding RNA MVIH as a prognostic marker and therapeutic target in acute myeloid leukemia. J Clin Lab Anal. 2020;34(4):e23113.
He C, Wang X, Luo J, et al. Long noncoding RNA maternally expressed gene 3 is downregulated, and its insufficiency correlates with poor‐risk stratification, worse treatment response, as well as unfavorable survival data in patients with acute myeloid leukemia. Technol Cancer Res Treat. 2020;19:1533033820945815.
Ruijuan W, Lijuan D, Miao S, Ruyu Y. Expression and clinical significance of lncRNA RBM5‐AS1 in acute myeloid leukemia. Lab Med. 2023;38(1):39‐45. doi:10.3969/j.issn.1673-8640.2023.01.008
Eslami MM, Soufizomorrod M, Ahmadvand M. High expression of long noncoding RNA NORAD is associated with poor clinical outcomes in non‐M3 acute myeloid leukemia patients. Hematol Oncol Stem Cell Ther. 2021;S1658‐3876(21):00065‐0.
Ganji A, Khosravi M, Mosayebi G, et al. Expression and alteration value of long noncoding RNA AB073614 and FER1L4 in patients with acute myeloid leukemia (AML). Asian Pac J Cancer Prev. 2023;24(7):2271‐2277.
Pashaiefar H, Izadifard M, Yaghmaie M, et al. Low expression of long noncoding RNA IRAIN is associated with poor prognosis in non‐M3 acute myeloid leukemia patients. Genet Test Mol Biomarkers. 2018;22(5):288‐294.
Abdelrahman AMN, Diab SM, Shabaan HMK, Ahmed MNA, Nabil R. The study of long noncoding RNA TUG 1 and ZEB2‐AS1 expression in newly diagnosed Egyptian adult acute myeloid leukemia patients. Egypt J Med Hum Genet. 2023;24(1):46.
Shimony S, Stahl M, Stone RM. Acute myeloid leukemia: 2023 update on diagnosis, risk‐stratification, and management. Am J Hematol. 2023;98(3):502‐526.
Glas AS, Lijmer JG, Prins MH, Bonsel GJ, Bossuyt PMM. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol. 2003;56(11):1129‐1135.
Masrour M, Khanmohammadi S, Fallahtafti P, Rezaei N. Long non‐coding RNA as a potential diagnostic biomarker in head and neck squamous cell carcinoma: a systematic review and meta‐analysis. PLoS One. 2023;18(9):e0291921.
Masrour M, Khanmohammadi S, Fallahtafti P, Hashemi SM, Rezaei N. Long non‐coding RNA as a potential diagnostic and prognostic biomarker in melanoma: a systematic review and meta‐analysis. J Cell Mol Med. 2024;28(3):e18109.
Hao Q‐Q, Chen GY, Zhang JH, Sheng JH, Gao Y. Diagnostic value of long noncoding RNAs for hepatocellular carcinoma: a PRISMA‐compliant meta‐analysis. Medicine. 2017;96(28):e7496.
Cao F, Hu Y, Chen Z, et al. Circulating long noncoding RNAs as potential biomarkers for stomach cancer: a systematic review and meta‐analysis. World J Surg Oncol. 2021;19:1‐13.
Mardani M, Rashedi S, Keykhaei M, et al. Long non‐coding RNAs (lncRNAs) as prognostic and diagnostic biomarkers in multiple myeloma: a systematic review and meta‐analysis. Pathol‐Res Pract. 2022;229:153726.
Chen B, Zhang RN, Fan X, et al. Clinical diagnostic value of long non‐coding RNAs in colorectal cancer: a systematic review and meta‐analysis. J Cancer. 2020;11(18):5518‐5526.
Qi P, Zhou X‐Y, Du X. Circulating long non‐coding RNAs in cancer: current status and future perspectives. Mol Cancer. 2016;15:1‐11.
Shi T, Gao G, Cao Y. Long noncoding RNAs as novel biomarkers have a promising future in cancer diagnostics. Dis Markers. 2016;2016:9085195.
Kolenda T, Ryś M, Guglas K, Teresiak A, et al. Quantification of long non‐coding RNAs using qRT‐PCR: comparison of different cDNA synthesis methods and RNA stability. Arch Med Sci. 2021;17(4):1006.
Huang R, Wang Y, Deng Y, et al. Detection of long noncoding RNA expression by real‐time PCR. Methods Mol Biol. 2021;2372:35‐42.
Lee C, Lee LJ, Chong PP, Chang KM, Abdullah M. Selection of reference genes for quantitative studies in acute myeloid leukemia. Malays J Pathol. 2019;41(3):313‐326.
Iempridee T, Wiwithaphon S, Piboonprai K, et al. Identification of reference genes for circulating long noncoding RNA analysis in serum of cervical cancer patients. FEBS Open bio. 2018;8(11):1844‐1854.