Tumor-Suppressive and Oncogenic Roles of microRNA-149-5p in Human Cancers

Shen, Yang; Zhao, Nan; Hu, Xinyao; He, Xiaoqin; Xu, Yali; Chen, Jiayu; Chen, Wenliang; Liu, Xin; Zhou, Zhiguang; Cao, Dedong; Xu, Ximing

doi:10.3390/ijms231810823

Cited by 6 publications

(4 citation statements)

References 127 publications

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“…[22] This study showed that miR-149-5p directly targets TNF-α, and increasing miR-149-5p levels can alleviate high glucose-induced dysfunction in endothelial cells. [23] This improvement involved a decrease in ET-1, VWF, and ICAM-1 levels, increased NO production, and enhanced eNOS expression. Additionally, miR-149-5p was found to mitigate cell injury and reduce apoptosis by normalizing endoplasmic reticulum stress markers increased by high glucose levels.…”

Section: Discussionmentioning

confidence: 99%

Utilizing machine learning algorithms to identify biomarkers associated with diabetic nephropathy: A review

Dong,

Liu,

2024

Medicine

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Diabetic nephropathy (DN), a multifaceted disease with various contributing factors, presents challenges in understanding its underlying causes. Uncovering biomarkers linked to this condition can shed light on its pathogenesis and support the creation of new diagnostic and treatment methods. Gene expression data were sourced from accessible public databases, and Weighted Gene Co-expression Network Analysis (WGCNA)was employed to pinpoint gene co-expression modules relevant to DN. Subsequently, various machine learning techniques, such as random forest, lasso regression algorithm (LASSO), and support vector machine-recursive feature elimination (SVM-REF), were utilized for distinguishing DN cases from controls using the identified gene modules. Additionally, functional enrichment analyses were conducted to explore the biological roles of these genes. Our analysis revealed 131 genes showing distinct expression patterns between controlled and uncontrolled groups. During the integrated WCGNA, we identified 61 co-expressed genes encompassing both categories. The enrichment analysis highlighted involvement in various immune responses and complex activities. Techniques like Random Forest, LASSO, and SVM-REF were applied to pinpoint key hub genes, leading to the identification of VWF and DNASE1L3. In the context of DN, they demonstrated significant consistency in both expression and function. Our research uncovered potential biomarkers for DN through the application of WGCNA and various machine learning methods. The results indicate that 2 central genes could serve as innovative diagnostic indicators and therapeutic targets for this disease. This discovery offers fresh perspectives on the development of DN and could contribute to the advancement of new diagnostic and treatment approaches.

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Section: Discussionmentioning

confidence: 99%

Utilizing machine learning algorithms to identify biomarkers associated with diabetic nephropathy: A review

Dong,

Liu,

2024

Medicine

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“…miR-149-5p was downregulated in our EC samples (2 −∆∆CT = 1.64). miR-149-5p is suggested to be a valuable marker for future targeted therapy and prognosis improvement [49]. Although its role as a tumor sup-pressor in multiple human cancer developments has been demonstrated, including cancers of the reproductive system [49,50], fewer studies on the miR-149-5p signaling pathway in EC exist.…”

Section: Ec-relevant Mirnas Identified In Phase I Of the Studymentioning

confidence: 99%

“…miR-149-5p is suggested to be a valuable marker for future targeted therapy and prognosis improvement [49]. Although its role as a tumor sup-pressor in multiple human cancer developments has been demonstrated, including cancers of the reproductive system [49,50], fewer studies on the miR-149-5p signaling pathway in EC exist. One study showed that miR-149-5p was modulated by circular RNA (circRNA), i.e., hsa_circ_0061140, which promoted endometrial carcinoma progression by regulating the miR-149-5p/Stat3 pathway [51].…”

Section: Ec-relevant Mirnas Identified In Phase I Of the Studymentioning

confidence: 99%

Identification of Endometrial Cancer-Specific microRNA Biomarkers in Endometrial Fluid

Yang

Barkley

Bhattarai

et al. 2023

IJMS

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Abnormal uterine bleeding is a common benign gynecological complaint and is also the most common symptom of endometrial cancer (EC). Although many microRNAs have been reported in endometrial carcinoma, most of them were identified from tumor tissues obtained at surgery or from cell lines cultured in laboratories. The objective of this study was to develop a method to detect EC-specific microRNA biomarkers from liquid biopsy samples to improve the early diagnosis of EC in women. Endometrial fluid samples were collected during patient-scheduled in-office visits or in the operating room prior to surgery using the same technique performed for saline infusion sonohysterography (SIS). The total RNA was extracted from the endometrial fluid specimens, followed by quantification, reverse transcription, and real-time PCR arrays. The study was conducted in two phases: exploratory phase I and validation phase II. In total, endometrial fluid samples from 82 patients were collected and processed, with 60 matched non-cancer versus endometrial carcinoma patients used in phase I and 22 in phase II. The 14 microRNA biomarkers, out of 84 miRNA candidates, with the greatest variation in expression from phase I, were selected to enter phase II validation and statistical analysis. Among them, three microRNAs had a consistent and substantial fold-change in upregulation (miR-429, miR-183-5p, and miR-146a-5p). Furthermore, four miRNAs (miR-378c, miR-4705, miR-1321, and miR-362-3p) were uniquely detected. This research elucidated the feasibility of the collection, quantification, and detection of miRNA from endometrial fluid with a minimally invasive procedure performed during a patient in-office visit. The screening of a larger set of clinical samples was necessary to validate these early detection biomarkers for endometrial cancer.

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“…MiRNA can bind to the untranslated region (UTR) of mRNA and regulate the expression of target genes by inhibiting the translation or degradation of mRNA, thereby affecting a variety of intracellular signaling pathways and playing an important role in the formation of tumors (19). The abnormal expression of miRNA in tumor cells can affect the malignant biological behavior of tumor cells (20)(21)(22)(23), and osteosarcoma is no exception. MiRNA have a very important role in the development of osteosarcoma and are clearly associated with many clinical features (24)(25)(26)(27).…”

Section: Introductionmentioning

confidence: 99%

Functional role of MicroRNA/PI3K/AKT axis in osteosarcoma

Yang

Liu

et al. 2023

Front. Oncol.

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Osteosarcoma (OS) is a primary malignant bone tumor that occurs in children and adolescents, and the PI3K/AKT pathway is overactivated in most OS patients. MicroRNAs (miRNAs) are highly conserved endogenous non-protein-coding RNAs that can regulate gene expression by repressing mRNA translation or degrading mRNA. MiRNAs are enriched in the PI3K/AKT pathway, and aberrant PI3K/AKT pathway activation is involved in the development of osteosarcoma. There is increasing evidence that miRNAs can regulate the biological functions of cells by regulating the PI3K/AKT pathway. MiRNA/PI3K/AKT axis can regulate the expression of osteosarcoma-related genes and then regulate cancer progression. MiRNA expression associated with PI3K/AKT pathway is also clearly associated with many clinical features. In addition, PI3K/AKT pathway-associated miRNAs are potential biomarkers for osteosarcoma diagnosis, treatment and prognostic assessment. This article reviews recent research advances on the role and clinical application of PI3K/AKT pathway and miRNA/PI3K/AKT axis in the development of osteosarcoma.

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Tumor-Suppressive and Oncogenic Roles of microRNA-149-5p in Human Cancers

Cited by 6 publications

References 127 publications

Utilizing machine learning algorithms to identify biomarkers associated with diabetic nephropathy: A review

Utilizing machine learning algorithms to identify biomarkers associated with diabetic nephropathy: A review

Identification of Endometrial Cancer-Specific microRNA Biomarkers in Endometrial Fluid

Functional role of MicroRNA/PI3K/AKT axis in osteosarcoma

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