Cancer quiescence: non-coding RNAs in the spotlight

Soureas, Konstantinos; Papadimitriou, M.; Panoutsopoulou, Konstantina; Pilala, Katerina-Marina; Scorilas, Andreas; Avgeris, Margaritis

doi:10.1016/j.molmed.2023.07.003

Cited by 6 publications

(6 citation statements)

References 116 publications

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“…Cell cycle dysregulation is a known contributor to uncontrolled cell proliferation and cancer progression 29 , 30 . Abnormalities in cell cycle regulatory proteins, such as cyclins, cyclin-dependent kinases (CDKs) and cyclin-dependent kinase inhibitors, are implicated in this process 31 .…”

Section: Discussionmentioning

confidence: 99%

ACAT1 promotes proliferation and metastasis of bladder cancer via AKT/GSK3β/c-Myc signaling pathway

Wang,

Shan

et al. 2024

J. Cancer

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Acetyl-CoA acetyltransferase 1 (ACAT1) plays a significant role in the regulation of gene expression and tumorigenesis. However, the biological role of ACAT1 in bladder cancer (BLCA) has yet to be elucidated. This research aimed to elucidate the bioinformatics features and biological functions of ACAT1 in BLCA. Here, we demonstrate that ACAT1 is elevated in BLCA tissues and is correlated with specific clinicopathological features and an unfavorable prognosis for survival in BLCA patients. ACAT1 was identified as an independent risk factor in BLCA. Phenotypically, both in vitro and in vivo , ACAT1 knockdown suppressed BLCA cell proliferation and migration, while ACAT1 overexpression had the opposite effect. Mechanistic assays revealed that ACAT1 enhances BLCA cell proliferation and metastasis through the AKT/GSK3β/c-Myc signaling pathway by modulating the cell cycle and EMT. Taken together, the results of our study reveal that ACAT1 is an oncogenic driver in BLCA that enhances tumor proliferation and metastasis, indicating its potential as a diagnostic and therapeutic target for this disease.

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Section: Discussionmentioning

confidence: 99%

ACAT1 promotes proliferation and metastasis of bladder cancer via AKT/GSK3β/c-Myc signaling pathway

Wang,

Shan

et al. 2024

J. Cancer

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“…Origin Response to stress, including chemotherapy, ionising radiation and hypoxia 170 Due to hypoxia, nutrient deprivation, immune surveillance and chemotherapy 82 Cell cycle status Static 21-24, 174 Cell cycle arrest in the G0 or G1 phase 175 Proliferative arrest 25 Growth arrest 58 Arrested in the G0/G1 phase 26 Drug resistance Prevent the toxic effects of systemic therapy 19 Driving treatment resistance 118 Proliferation Asymmetric division (neosis) 15 Reactivate to promote cell proliferation 175…”

Section: Same Pointmentioning

confidence: 99%

“…Extracellular factors mediates dormancy including angiogenic (such as VEGF, 71 Angiostatin 72 ), immune (such as IL‐3, 73 interferon‐γ, 74 growth arrest‐specific protein 6, 75 leukaemia inhibitory factor receptor 76 ), ECM (such as TGF‐β1, 77 TGF‐β2, 35 insulin‐like growth factor 1, 78 E‐selectin, 79 bone morphogenetic protein 7 (BMP7) 80 ) and stress‐induced factors (such as p38 MAPK 81 ). Cancer cell quiescence is a self‐protective mechanism that prevents destruction from hypoxia, nutrient deprivation, immune surveillance and chemotherapy 82 …”

Section: Molecular Mechanisms Of Cancer Cell Entry and Exit From Dorm...mentioning

confidence: 99%

Dormant cancer cells and polyploid giant cancer cells: The roots of cancer recurrence and metastasis

Jiao,

Yu,

Zheng

et al. 2024

Clinical & Translational Med

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Tumour cell dormancy is critical for metastasis and resistance to chemoradiotherapy. Polyploid giant cancer cells (PGCCs) with giant or multiple nuclei and high DNA content have the properties of cancer stem cell and single PGCCs can individually generate tumours in immunodeficient mice. PGCCs represent a dormant form of cancer cells that survive harsh tumour conditions and contribute to tumour recurrence. Hypoxic mimics, chemotherapeutics, radiation and cytotoxic traditional Chinese medicines can induce PGCCs formation through endoreduplication and/or cell fusion. After incubation, dormant PGCCs can recover from the treatment and produce daughter cells with strong proliferative, migratory and invasive abilities via asymmetric cell division. Additionally, PGCCs can resist hypoxia or chemical stress and have a distinct protein signature that involves chromatin remodelling and cell cycle regulation. Dormant PGCCs form the cellular basis for therapeutic resistance, metastatic cascade and disease recurrence. This review summarises regulatory mechanisms governing dormant cancer cells entry and exit of dormancy, which may be used by PGCCs, and potential therapeutic strategies for targeting PGCCs.

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“…LncRNAs regulate the proliferation, apoptosis, metastasis, and drug resistance of tumor cells ( Luo et al, 2017 ; Peng et al, 2017 ; Muller et al, 2019 ; Bhat et al, 2020 ; Wei et al, 2020 ), and their abnormal expression is closely associated with the severity of malignancy in various cancers, including SOC. Moreover, research has shown that ncRNAs could have a potential dynamic role in future cancer therapeutics, supporting personalized treatment decisions and modern precision medicine ( Soureas et al, 2023 ). N6-methyladenosine (m 6 A), a dynamic and reversible post-transcriptional modification commonly found on mRNAs and lncRNAs ( Chen et al, 2020 ), is a promising clinically relevant biomarker and therapeutic target ( Huang et al, 2016 ; Zhao and Cui, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

Identification of potential novel N6-methyladenosine effector-related lncRNA biomarkers for serous ovarian carcinoma: a machine learning-based exploration in the framework of 3P medicine

Ye,

Tong,

Pan

et al. 2024

Front. Pharmacol.

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BackgroundSerous ovarian carcinoma (SOC) is considered the most lethal gynecological malignancy. The current lack of reliable prognostic biomarkers for SOC reduces the efficacy of predictive, preventive, and personalized medicine (PPPM/3PM) in patients with SOC, leading to unsatisfactory therapeutic outcomes. N6-methyladenosine (m6A) modification-associated long noncoding RNAs (lncRNAs) are effective predictors of SOC. In this study, an effective risk prediction model for SOC was constructed based on m6A modification-associated lncRNAs.MethodsTranscriptomic data and clinical information of patients with SOC were downloaded from The Cancer Genome Atlas. Candidate lncRNAs were identified using univariate and multivariate and least absolute shrinkage and selection operator-penalized Cox regression analyses. The molecular mechanisms of m6A effector-related lncRNAs were explored via Gene Ontology, pathway analysis, gene set enrichment analysis, and gene set variation analysis (GSVA). The extent of immune cell infiltration was assessed using various algorithms, including CIBERSORT, Microenvironment Cell Populations counter, xCell, European Prospective Investigation into Cancer and Nutrition, and GSVA. The calcPhenotype algorithm was used to predict responses to the drugs commonly used in ovarian carcinoma therapy. In vitro experiments, such as migration and invasion Transwell assays, wound healing assays, and dot blot assays, were conducted to elucidate the functional roles of candidate lncRNAs.ResultsSix m6A effector-related lncRNAs that were markedly associated with prognosis were used to establish an m6A effector-related lncRNA risk model (m6A-LRM) for SOC. Immune microenvironment analysis suggested that the high-risk group exhibited a proinflammatory state and displayed increased sensitivity to immunotherapy. A nomogram was constructed with the m6A effector-related lncRNAs to assess the prognostic value of the model. Sixteen drugs potentially targeting m6A effector-related lncRNAs were identified. Furthermore, we developed an online web application for clinicians and researchers (https://leley.shinyapps.io/OC_m6A_lnc/). Overexpression of the lncRNA RP11-508M8.1 promoted SOC cell migration and invasion. METTL3 is an upstream regulator of RP11-508M8.1. The preliminary regulatory axis METTL3/m6A/RP11-508M8.1/hsa-miR-1270/ARSD underlying SOC was identified via a combination of in vitro and bioinformatic analyses.ConclusionIn this study, we propose an innovative prognostic risk model and provide novel insights into the mechanism underlying the role of m6A-related lncRNAs in SOC. Incorporating the m6A-LRM into PPPM may help identify high-risk patients and personalize treatment as early as possible.

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Cancer quiescence: non-coding RNAs in the spotlight

Cited by 6 publications

References 116 publications

ACAT1 promotes proliferation and metastasis of bladder cancer via AKT/GSK3β/c-Myc signaling pathway

ACAT1 promotes proliferation and metastasis of bladder cancer via AKT/GSK3β/c-Myc signaling pathway

Dormant cancer cells and polyploid giant cancer cells: The roots of cancer recurrence and metastasis

Identification of potential novel N6-methyladenosine effector-related lncRNA biomarkers for serous ovarian carcinoma: a machine learning-based exploration in the framework of 3P medicine

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