The Importance of Selected Dysregulated microRNAs in Diagnosis and Prognosis of Childhood B-Cell Precursor Acute Lymphoblastic Leukemia

Ziętara, Karolina; Lejman, Jan; Wojciechowska, Katarzyna; Lejman, Monika

doi:10.3390/cancers15020428

Cited by 3 publications

(3 citation statements)

References 98 publications

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“…Ziętara, K. J.,et al [44] has expressed the acute leukemia causes fever or chills in the legs. But these events never occur in people with chronic leukemia.…”

Section: B Analysis Based On Symptomsmentioning

confidence: 99%

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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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“…Ziętara, K. J.,et al [44] has expressed the acute leukemia causes fever or chills in the legs. But these events never occur in people with chronic leukemia.…”

Section: B Analysis Based On Symptomsmentioning

confidence: 99%

“…An increase in the size of the gums is called hyperplasia. These symptoms are usually only seen in a small number of people with acute leukemia Ziętara, K. J.,et al [44] The acute leukemia causes fever or chills in the legs. But these events never occur in people with chronic leukemia.…”

Section: B Analysis Based On Symptomsmentioning

confidence: 99%

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

et al. 2023

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“… 8 Recent studies have revealed characteristic expression patterns according to genetic subgroups of pediatric BCP-ALL as well as their prognostic significance. 9 , 10 In addition, novel prognostic factors identified by integrated analysis, including miRNAs and mRNAs, have been reported in several types of malignant tumors 11 ; however, few studies have conducted an integrated analysis focusing on miRNA profiles in a large cohort of pediatric BCP-ALL.…”

Section: Introductionmentioning

confidence: 99%

RNA-seq–based miRNA signature as an independent predictor of relapse in pediatric B-cell acute lymphoblastic leukemia

Kubota,

Ueno,

Tasaka

et al. 2024

Blood Advances

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Aberrant miRNA expression profiles have been associated with disease progression and clinical outcome in pediatric cancers. However, few studies have analyzed genome-wide dysregulation of miRNAs and mRNAs in pediatric B cell precursor acute lymphoblastic leukemia (BCP-ALL). To identify novel prognostic factors, we comprehensively investigated miRNA and mRNA sequencing (miRNA-seq and mRNA-seq) data in poor-outcome pediatric BCP-ALL samples. We analyzed 180 patients, including 43 matched pairs at diagnosis and relapse. Consensus clustering of miRNA expression data revealed a distinct profile characterized by mainly downregulation of miRNAs (referred to as an miR-low cluster; MLC). The MLC profile was not associated with any known genetic subgroups. Intriguingly, patients classified as MLC had significantly shorter event-free survival (median 21 vs 33 months, log-rank P = 3 ×10-5). Furthermore, this poor prognosis was retained even in hyperdiploid ALL. This poor prognostic MLC profiling was confirmed in the validation cohort. Notably, non-MLC profiling at diagnosis often (n= 9/23, Fisher's exact test, P = 0.039) changed into MLC profiling at relapse in the same patient. Integrated analysis of miRNA-seq and mRNA-seq data revealed that the transcriptional profile of MLC was characterized by enrichment of MYC target and oxidative phosphorylation genes, reduced intron retention, and low expression of DICER1. Thus, our miRNA-mRNA integration approach yielded a truly unbiased molecular stratification of pediatric BCP-ALL cases based on a novel prognostic miRNA signature, which may lead to better clinical outcomes.

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Multiple Genetic Polymorphisms within microRNA Targets and Homologous microRNA-Binding Sites: Two More Factors Influencing microRNA-Mediated Regulation of Gene Expression

Giurgiu,

Kaltenbach,

Ahrend

et al. 2023

Advances in Genetic Polymorphisms

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miRNA-mRNA interaction depends on multiple factors such as 3’UTR isoforms, the cell and tissue-specific expression levels of RNA-binding proteins, the sequence context around the mRNA target site, and other mechanisms. Genetic polymorphisms within miRNAs and their target sites appear to be among the most important ones because they influence the mode and outcome of miRNA-mRNA interaction universally and irreversibly. SNP disruption of miRNAs and their binding sites, as well as conformational changes preventing the access of the miRNA to its target site, are adopted as the most credible mechanistic explanations of SNP-mediated effects. The occurrence of multiple SNPs within the same miRNA-binding site implies their combinatorial mode of action. The presence of the repetitive (homologous) binding sites for the same miRNA on its mRNA target may both enhance the miRNA targeting and provide for the backup target site instead of the one disrupted by SNP, thus rescuing the miRNA functionality. While being underexplored, the multiple genetic polymorphisms within the miRNA-binding sites, as well as homologous miRNA-binding sites, may be considered as additional factors influencing miRNA-mediated regulation of gene expression.

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The Importance of Selected Dysregulated microRNAs in Diagnosis and Prognosis of Childhood B-Cell Precursor Acute Lymphoblastic Leukemia

Cited by 3 publications

References 98 publications

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

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

RNA-seq–based miRNA signature as an independent predictor of relapse in pediatric B-cell acute lymphoblastic leukemia

Multiple Genetic Polymorphisms within microRNA Targets and Homologous microRNA-Binding Sites: Two More Factors Influencing microRNA-Mediated Regulation of Gene Expression

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