Breast cancer stem cell-derived extracellular vesicles transfer ARRDC1-AS1 to promote breast carcinogenesis via a miR-4731-5p/AKT1 axis-dependent mechanism

Li, Mingzhu; Lin, Conglin; Cai, Zhibing

doi:10.1016/j.tranon.2023.101639

Cited by 5 publications

(3 citation statements)

References 49 publications

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“…The higher expression of ARRDC1-AS1 was associated with shorter overall survival in patients with liver cancer. These findings were in accordance with findings reported by Li et al They demonstrated that ARRDC1-AS1 overexpression was associated breast cancer by sponging miR-4731-5p and subsequently upregulated AKT1 expression resulting in tumor growth and proliferation 48 , 67 and sponging miR-432-5p and activated PRMT5 expression in glioma, which related to the proliferation, invasion, and poor prognosis of the disease. 68 …”

Section: Discussionsupporting

confidence: 92%

Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach

Anuntakarun,

Khamjerm,

Tangkijvanich

et al. 2024

Bioinform Biol Insights

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Long non-coding RNAs (lncRNAs), which are RNA sequences greater than 200 nucleotides in length, play a crucial role in regulating gene expression and biological processes associated with cancer development and progression. Liver cancer is a major cause of cancer-related mortality worldwide, notably in Thailand. Although machine learning has been extensively used in analyzing RNA-sequencing data for advanced knowledge, the identification of potential lncRNA biomarkers for cancer, particularly focusing on lncRNAs as molecular biomarkers in liver cancer, remains comparatively limited. In this study, our objective was to identify candidate lncRNAs in liver cancer. We employed an expression data set of lncRNAs from patients with liver cancer, which comprised 40 699 lncRNAs sourced from The CancerLivER database. Various feature selection methods and machine-learning approaches were used to identify these candidate lncRNAs. The results showed that the random forest algorithm could predict lncRNAs using features extracted from the database, which achieved an area under the curve (AUC) of 0.840 for classifying lncRNAs between early (stage 1) and late stages (stages 2, 3, and 4) of liver cancer. Five of 23 significant lncRNAs (WAC-AS1, MAPKAPK5-AS1, ARRDC1-AS1, AC133528.2, and RP11-1094M14.11) were differentially expressed between early and late stage of liver cancer. Based on the Gene Expression Profiling Interactive Analysis (GEPIA) database, higher expression of WAC-AS1, MAPKAPK5-AS1, and ARRDC1-AS1 was associated with shorter overall survival. In conclusion, the classification model could predict the early and late stages of liver cancer using the signature expression of lncRNA genes. The identified lncRNAs might be used as early diagnostic and prognostic biomarkers for patients with liver cancer.

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Section: Discussionsupporting

confidence: 92%

Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach

Anuntakarun,

Khamjerm,

Tangkijvanich

et al. 2024

Bioinform Biol Insights

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“…LncRNA ARRDC1-AS1 is also associated with tumor aggressiveness and is overexpressed in breast cancer, colon cancer, and diffuse large B cell lymphoma (DLBCL) [42][43][44][45]. These disul dptosis-associated lncRNAs are promising cancer therapeutic targets.…”

Section: Discussionmentioning

confidence: 99%

Construction and validation of a novel disulfidptosis-related lncRNA signature for prognostic prediction in lung adenocarcinoma

Xu,

Lu,

Yang

et al. 2023

Preprint

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Disulfidptosis is a novel type of cell death caused by disulfide stress and is distinct from other known forms of cell death, including cuproptosis, ferroptosis, pyroptosis, necroptosis, and apoptosis. Transcriptome data and clinical information of 503 LUAD patients was extracted from The Cancer Genome Atlas (TCGA) database. A nomogram was constructed with the risk score based on the expression levels of the 4 disulfidptosis-associated lncRNAs and the clinical characteristics and was according to the results from the univariate and multivariate Cox regression, minimal absolute contraction, and least absolute shrinkage and selection operator (LASSO) regression analyses.Differences in the tumor immune microenvironment (TIME), tumor mutation burden (TMB), and chemotherapeutic treatment sensitivity were compared between the high- and low-risk LUAD patients. LncRNA ARRDC1-AS1 was highly expressed in the LUAD cell lines (A549 and H1299) compared to the BEAS2B cell line (normal lung epithelial cells). Knockdown of ARRDC1-AS1 significantly reduced in vitro proliferation, migration, and invasiveness of A549 cells. LncRNA ARRDC1-AS1 is a promising prognosis prediction biomarker and a therapeutic target in LUAD.

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“…Melanoma CSCs secrete EVs that enhance metastatic ability of non-stem cancer cells via miRNA-592, which activates the MAPK/ERK signaling pathway ( 125 ). Breast CSC-derived EVs carry ARRDC1-AS1 to promote breast cancer malignancy by modulating miR-4731–5p/AKT1 axis to foster tumor growth and aggressiveness ( 123 ). In addition, CSCs secrete certain tumor suppressors out the cells by EVs.…”

Section: The Landscape Of Evs: Classifications and Molecular Constitu...mentioning

confidence: 99%

Modulatory effects of cancer stem cell-derived extracellular vesicles on the tumor immune microenvironment

Li,

Zhang,

Yue

et al. 2024

Front. Immunol.

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Cancer stem cells (CSCs), accounting for only a minor cell proportion (< 1%) within tumors, have profound implications in tumor initiation, metastasis, recurrence, and treatment resistance due to their inherent ability of self-renewal, multi-lineage differentiation, and tumor-initiating potential. In recent years, accumulating studies indicate that CSCs and tumor immune microenvironment act reciprocally in driving tumor progression and diminishing the efficacy of cancer therapies. Extracellular vesicles (EVs), pivotal mediators of intercellular communications, build indispensable biological connections between CSCs and immune cells. By transferring bioactive molecules, including proteins, nucleic acids, and lipids, EVs can exert mutual influence on both CSCs and immune cells. This interaction plays a significant role in reshaping the tumor immune microenvironment, creating conditions favorable for the sustenance and propagation of CSCs. Deciphering the intricate interplay between CSCs and immune cells would provide valuable insights into the mechanisms of CSCs being more susceptible to immune escape. This review will highlight the EV-mediated communications between CSCs and each immune cell lineage in the tumor microenvironment and explore potential therapeutic opportunities.

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Breast cancer stem cell-derived extracellular vesicles transfer ARRDC1-AS1 to promote breast carcinogenesis via a miR-4731-5p/AKT1 axis-dependent mechanism

Cited by 5 publications

References 49 publications

Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach

Classification of Long Non-Coding RNAs s Between Early and Late Stage of Liver Cancers From Non-coding RNA Profiles Using Machine-Learning Approach

Construction and validation of a novel disulfidptosis-related lncRNA signature for prognostic prediction in lung adenocarcinoma

Modulatory effects of cancer stem cell-derived extracellular vesicles on the tumor immune microenvironment

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