MIR210HG promotes breast cancer progression by IGF2BP1 mediated m6A modification

Cell & Bioscience, Год журнала: 2022, Номер 12(1)

Опубликована: Март 28, 2022

Abstract Background Breast cancer is the most common in women around world, and molecular mechanisms of breast progression metastasis are still unclear. This study aims to clarify function N6,2′-O-dimethyladenosine (m6A) regulation lncRNA MIR210HG cancer. Results High expression was confirmed promoted progression, which mediated by its encoded miR-210. regulated IGF2BP1 m6A modification. highly expressed induced both miR-210 expression, contributed progression. In addition, transcript stabilized co-factor ELAVL1. a direct target MYCN via E-box binding motif. cells. expressions were also increased MYCN. Conclusions cancer, functions as an oncogenic lncRNA, ELAVL1 enhance stability , contributes Interestingly, directly activated MYCN, explains role These findings related mechanism The MYCN/IGF2BP1/ axis may serve alternative

Язык: Английский

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Proposing a hybrid technique of feature fusion and convolutional neural network for melanoma skin cancer detection

Journal of Pathology Informatics, Год журнала: 2023, Номер 14, С. 100341 - 100341

Опубликована: Янв. 1, 2023

Skin cancer is among the most common types worldwide. Automatic identification of skin complicated because poor contrast and apparent resemblance between lesions. The rate human death can be significantly reduced if melanoma could detected quickly using dermoscopy images. This research uses an anisotropic diffusion filtering method on images to remove multiplicative speckle noise. To do this, fast-bounding box (FBB) applied here segment region. We also employ 2 feature extractors represent first one Hybrid Feature Extractor (HFE), second convolutional neural network VGG19-based CNN. HFE combines 3 extraction approaches namely, Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), Speed Up Robust (SURF) into a single fused vector. CNN used extract additional features from test training datasets. 2-feature vector then design classification model. proposed employed datasets ISIC 2017 academic torrents dataset. Our achieves 99.85%, 91.65%, 95.70% in terms accuracy, sensitivity, specificity, respectively, making it more successful than previously machine learning algorithms.

Язык: Английский

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Hybrid Feature Fusion and Machine Learning Approaches for Melanoma Skin Cancer Detection

Опубликована: Янв. 18, 2022

Skin cancer is an exquisite disease globally nowadays. Because of the poor contrast and apparent resemblance between skin lesions, automatic identification complicated. The rate human death can be massively reduced if melanoma detected quickly using dermoscopy images. In this research, anisotropic diffusion filtering method used on images to remove multiplicative speckle noise fast-bounding box (FBB) applied segment region. Furthermore, paper consists two feature extractor parts. One features parts hybrid (HFE) part another convolutional neural network VGG19 based CNN part. HFE portion combines three extraction approaches into a single fused vector: Histogram-Oriented Gradient (HOG), Local Binary Pattern (LBP), Speed Up Robust Feature (SURF). also extract additional from test training datasets. This two-feature vector design classification model. classifier performs whether it or non-melanoma cancer. proposed methodology performed ordinary datasets achieved accuracy 99.85%, sensitivity 91.65%, specificity 95.70%, which makes more successful than previous machine learning algorithms.

Язык: Английский

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Prognostic and diagnostic values of non-coding RNAs as biomarkers for breast cancer: An umbrella review and pan-cancer analysis

Frontiers in Molecular Biosciences, Год журнала: 2023, Номер 10

Опубликована: Янв. 16, 2023

Background: Breast cancer (BC) is the most common in women. The incidence and morbidity of BC are expected to rise rapidly. stage at which diagnosed has a significant impact on clinical outcomes. When detected early, an overall 5-year survival rate up 90% possible. Although numerous studies have been conducted assess prognostic diagnostic values non-coding RNAs (ncRNAs) breast cancer, their potential remains unclear. In this field study, there various systematic reviews meta-analysis that report volumes data. we tried collect all these order re-analyze data without any restriction or RNA type, make it as comprehensive Methods: Three databases, namely, PubMed, Scopus, Web Science (WoS), were searched find relevant studies. After thoroughly searching, screening titles, abstracts, full-text quality included assessed using AMSTAR tool. All required including hazard ratios (HRs), sensitivity (SENS), specificity (SPEC) extracted for further analysis, analyses carried out Stata. Results: part, our initial search three databases produced 10,548 articles, 58 current study. We correlation (ncRNA) expression with different outcomes patients: (OS) (HR = 1.521), disease-free (DFS) 1.33), recurrence-free (RFS) 1.66), progression-free (PFS) 1.71), metastasis-free (MFS) 0.90), disease-specific (DSS) 0.37). eliminating low-quality studies, results did not change significantly. 22 articles 30 datasets retrieved from 8,453 articles. was determined. bivariate random-effects models used value ncRNAs. area under curve (AUC) ncRNAs differentiated patients 0.88 (SENS: 80% SPEC: 82%). There no difference single combined patients. However, microRNAs (miRNAs) higher than long (lncRNAs). No evidence publication bias found Nine miRNAs, four lncRNAs, five gene targets showed OS RFS between normal based pan-cancer demonstrating value. Conclusion: present umbrella review ncRNAs, lncRNAs can be biomarkers patients, regardless sample sources, ethnicity subtype cancer.

Язык: Английский

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Integrative analysis of mutated genes and mutational processes reveals novel mutational biomarkers in colorectal cancer

BMC Bioinformatics, Год журнала: 2022, Номер 23(1)

Опубликована: Апрель 19, 2022

Colorectal cancer (CRC) is one of the leading causes cancer-related deaths worldwide. Recent studies have observed causative mutations in susceptible genes related to colorectal 10 15% patients. This highlights importance identifying for early detection this more effective treatments among high risk individuals. Mutation considered as key point research. Many performed subtyping based on type frequently mutated genes, or proportion mutational processes. However, best our knowledge, combination these features has never been used together task. potential introduce better and inclusive subtype classification approaches using wider range enable biomarker discovery thus inform drug development CRC.In study, we develop a new pipeline novel concept called 'gene-motif', which merges gene information with tri-nucleotide motif sites, identification. We apply International Cancer Genome Consortium (ICGC) CRC samples identify, first time, 3131 gene-motif combinations that are significantly 536 ICGC samples. Using features, identify seven subtypes distinguishable phenotypes biomarkers, including unique signaling pathways, most them targeted treatment options currently available. Interestingly, also several multiple but sequence contexts.Our results highlight considering both mutation identification biomarkers. The presented study demonstrates distinguished phenotypic properties can be effectively treatments. By knowing associated subtypes, personalized plan developed considers specific their genomic lesion.

Язык: Английский

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A Survey on Machine Learning and Internet of Medical Things-Based Approaches for Handling COVID-19: Meta-Analysis

Frontiers in Public Health, Год журнала: 2022, Номер 10

Опубликована: Июнь 23, 2022

Early diagnosis, prioritization, screening, clustering, and tracking of patients with COVID-19, production drugs vaccines are some the applications that have made it necessary to use a new style technology involve, manage, deal this epidemic. Strategies backed by artificial intelligence (A.I.) Internet Things (IoT) been undeniably effective understand how virus works prevent from spreading. Accordingly, main aim survey is critically review ML, IoT, integration IoT ML-based techniques in related diagnosis disease prediction its outbreak. According findings, provided prompt efficient approach spread. On other hand, most studies developed aimed at detection handling challenges associated COVID-19 pandemic. Among different approaches, Convolutional Neural Network (CNN), Support Vector Machine, Genetic CNN, pre-trained followed ResNet demonstrated best performances compared methods.

Язык: Английский

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Regulation of T cell differentiation and function by long noncoding RNAs in homeostasis and cancer

Frontiers in Immunology, Год журнала: 2023, Номер 14

Опубликована: Июнь 6, 2023

Long noncoding RNAs (lncRNAs) increase in genomes of complex organisms and represent the largest group RNA genes transcribed mammalian cells. Previously considered only transcriptional noise, lncRNAs comprise a heterogeneous class transcripts that are emerging as critical regulators T cell-mediated immunity. Here we summarize lncRNA expression landscape different cell subsets highlight recent advances role regulating differentiation, function exhaustion during homeostasis cancer. We discuss molecular mechanisms can serve novel targets to modulate or improve response cancer immunotherapies by modulating immunosuppressive tumor microenvironment.

Язык: Английский

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Regulatory miRNAs, circRNAs and lncRNAs in cell cycle progression of breast cancer

Functional & Integrative Genomics, Год журнала: 2023, Номер 23(3)

Опубликована: Июль 11, 2023

Язык: Английский

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Long Non-Coding RNA Signatures in Lymphopoiesis and Lymphoid Malignancies

Non-Coding RNA, Год журнала: 2023, Номер 9(4), С. 44 - 44

Опубликована: Авг. 1, 2023

Lymphoid cells play a critical role in the immune system, which includes three subgroups of T, B, and NK cells. Recognition complexity human genetics transcriptome lymphopoiesis has revolutionized our understanding regulatory potential RNA normal lymphoid malignancies. Long non-coding RNAs (lncRNAs) are class molecules greater than 200 nucleotides length. LncRNAs have recently attracted much attention due to their roles various biological processes, including gene regulation, chromatin organization, cell cycle control. can also be used for differentiation fate, as expression patterns often specific particular types or developmental stages. Additionally, lncRNAs been implicated differentiation, such regulating T-cell B-cell development, linked immune-associated diseases leukemia lymphoma. In addition, investigated biomarkers diagnosis, prognosis, therapeutic response disease management. this review, we provide an overview current knowledge about physiopathology processes during leukemia.

Язык: Английский

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Exosomes in triple negative breast cancer: From bench to bedside

Cancer Letters, Год журнала: 2021, Номер 527, С. 1 - 9

Опубликована: Дек. 10, 2021

Язык: Английский

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