Functions and mechanisms of lncRNA MALAT1 in cancer chemotherapy resistance

Hou, Junhui; Zhang, Gong; Wang, Xia; Wang, Yuan; Wang, Kefeng

doi:10.1186/s40364-023-00467-8

Cited by 26 publications

(13 citation statements)

References 95 publications

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“…MALAT1 is mostly overexpressed in human cancers and its expression is associated with tumor size and stage as well as patients' poor survival (103). MALAT1 has been recently identified as an important RNA which enhances cellular resistance to chemotherapy (104).…”

Section: Common Cernas In the Axesmentioning

confidence: 99%

EZH2: A Critical Competing Endogenous RNA in Cancer Research - A Scoping Review

Salehi-Mazandarani,

Mahmoudian-Hamedani,

Farajzadegan

et al. 2024

Preprint

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In recent years, research on the competing endogenous RNAs (ceRNAs) in cancer is in full swing. These investigations are discovering the importance of critical RNAs in cancer progression. Enhancer of zeste 2 polycomb repressive complex 2 subunit (EZH2) is one of these RNAs that has been identified as a potential therapeutic target in many types of cancer. Up to now, many studies have been conducted to elucidate ceRNA role of EZH2 in cancer. Due to EZH2's dual role as an oncogene and tumor suppressor in cancer, a more thorough exploration of its ceRNA functions may enhance clinical approaches to cancer treatment. In the current scoping review, we searched online databases including PubMed, Web of Science, Scopus, Embase, Cochrane Library, and Google Scholar to identify experimentally-validated ceRNA axes including EZH2 in human cancers. We identified 62 unique axes consisting of 30 microRNAs (miRNAs), 31 long non-coding RNAs (lncRNAs), 9 messenger RNAs (mRNAs), and 14 circular RNAs (circRNAs). Notably, SPRY4-IT1 - miR-101-3p - EZH2 and XIST - miR-101-3p - EZH2 were recurrent axes observed in multiple cancer types. Among the most frequent miRNAs were miR-101-3p, miR-144-3p, and miR-124-3p, and ceRNAs including SPRY4-IT1, XIST, SNHG6, HOXA11-AS, MALAT1, and TUG1 emerged as frequent competitors of EZH2 for miRNA binding. This scoping review highlights the prevalence and diversity of EZH2-containing ceRNA axes in cancer, suggesting their potential as therapeutic targets. Future research should delve deeper into these axes to elucidate their functional significance and assess their clinical applicability.

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Section: Common Cernas In the Axesmentioning

confidence: 99%

EZH2: A Critical Competing Endogenous RNA in Cancer Research - A Scoping Review

Salehi-Mazandarani,

Mahmoudian-Hamedani,

Farajzadegan

et al. 2024

Preprint

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“…Moreover, the interaction of MALAT1 with the nuclear protein hnRNP C has been shown to support the translocation of MALAT1 from the nucleus to the cytoplasm, promoting the transition from the G2 to the M phase [57]. On the other hand, many studies have indicated the role of MALAT1 in the resistance of cancer cells to chemotherapy in chronic myeloid leukemia, head and neck squamous cell carcinoma, and hepatocellular carcinoma [58], increasing the ability to repair DNA, evade cell cycle checkpoints, and regulate apoptosis, autophagy, and stemness of cancer cells. Moreover, MALAT1 stimulates the cell cycle of liver cells.…”

Section: Malat1 In Cell Cycle Regulationmentioning

confidence: 99%

“…Moreover, knockdown of MALAT1 induced the process of apoptosis and cell cycle arrest in the replication phase in human umbilical vein endothelial cells (HUVECs) [71]. Increased MALAT1 expression was demonstrated in acute myeloid leukemia (AML) and chronic myeloid leukemia (CML), and knockout of MALAT1 in AML was found to inhibit proliferation by arresting the cell cycle in the G0/G1 phase and promote apoptosis of cancer cells by increasing the expression of caspase-3, -8, and -9 proteins [58,72].…”

Section: Diseases Related To the Malat1 Genementioning

confidence: 99%

MALAT1: A Long Non-Coding RNA with Multiple Functions and Its Role in Processes Associated with Fat Deposition

Piórkowska,

Zygmunt,

Hunter

et al. 2024

Genes

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Metastasis-associated lung adenocarcinoma transcript 1 (MALAT1) belongs to the lncRNA molecules, which are involved in transcriptional and epigenetic regulation and the control of gene expression, including the mechanism of chromatin remodeling. MALAT1 was first discovered during carcinogenesis in lung adenocarcinoma, hence its name. In humans, 66 of its isoforms have been identified, and in pigs, only 2 are predicted, for which information is available in Ensembl databases (Ensembl Release 111). MALAT1 is expressed in numerous tissues, including adipose, adrenal gland, heart, kidney, liver, ovary, pancreas, sigmoid colon, small intestine, spleen, and testis. MALAT1, as an lncRNA, shows a wide range of functions. It is involved in the regulation of the cell cycle, where it has pro-proliferative effects and high cellular levels during the G1/S and mitotic (M) phases. Moreover, it is involved in invasion, metastasis, and angiogenesis, and it has a crucial function in alternative splicing during carcinogenesis. In addition, MALAT1 plays a significant role in the processes of fat deposition and adipogenesis. The human adipose tissue stem cells, during differentiation into adipocytes, secrete MALAT1 as one the most abundant lncRNAs in the exosomes. MALAT1 expression in fat tissue is positively correlated with adipogenic FABP4 and LPL. This lncRNA is involved in the regulation of PPARγ at the transcription stage, fatty acid metabolism, and insulin signaling. The wide range of MALAT1 functions makes it an interesting target in studies searching for drugs to prevent obesity development in humans. In turn, in farm animals, it can be a source of selection markers to control the fat tissue content.

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“…MALAT1 has been suggested as a potential indicator for the diagnosis and prognosis of cancer. [5][6][7][8][9][10] The epidermal growth factor receptor (EGFR) is a cellular protein that facilitates cell growth. A mutation in the gene for EGFR can make it grow too much, which can cause cancer.…”

Section: Introductionmentioning

confidence: 99%

A graphSAGE discovers synergistic combinations of Gefitinib, paclitaxel, and Icotinib for Lung adenocarcinoma management by targeting human genes and proteins: the RAIN protocol

Sadeghi,

Kiaei,

Boush

et al. 2024

Preprint

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Background: Adenocarcinoma of the lung is the most common type of lung cancer, and it is characterized by distinct cellular and molecular features. It occurs when abnormal lung cells multiply out of control and form a tumor in the outer region of the lungs. Adenocarcinoma of the lung is a serious and life-threatening condition that requires effective and timely management to improve the survival and quality of life of the patients. One of the challenges in this cancer treatment is finding the optimal combination of drugs that can target the genes or proteins that are involved in the disease process. Method: In this article, we propose a novel method to recommend combinations of trending drugs to target its associated proteins/genes, using a Graph Neural Network (GNN) under the RAIN protocol. The RAIN protocol is a three-step framework that consists of: 1) Applying graph neural networks to recommend drug combinations by passing messages between trending drugs for managing disease and genes that act as potential targets for disease; 2) Retrieving relevant articles with clinical trials that include those proposed drugs in previous step using Natural Language Processing (NLP); 3) Analyzing the network meta-analysis to measure the comparative efficacy of the drug combinations. Result: We applied our method to a dataset of nodes and edges that represent the network, where each node is a drug or a gene, and each edge is a p-value between them. We found that the graph neural network recommends combining Gefitinib, Paclitaxel, and Icotinib as the most effective drug combination to target this cancer associated proteins/genes. We reviewed the clinical trials and expert opinions on these medications and found that they support our claim. The network meta-analysis also confirmed the effectiveness of these drugs on associated genes. Conclusion: Our method is a novel and promising approach to recommend trending drugs combination to target cancer associated proteins/genes, using graph neural networks under the RAIN protocol. It can help clinicians and researchers to find the best treatment options for patients, and also provide insights into the underlying mechanisms of the disease.

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Functions and mechanisms of lncRNA MALAT1 in cancer chemotherapy resistance

Cited by 26 publications

References 95 publications

EZH2: A Critical Competing Endogenous RNA in Cancer Research - A Scoping Review

EZH2: A Critical Competing Endogenous RNA in Cancer Research - A Scoping Review

MALAT1: A Long Non-Coding RNA with Multiple Functions and Its Role in Processes Associated with Fat Deposition

A graphSAGE discovers synergistic combinations of Gefitinib, paclitaxel, and Icotinib for Lung adenocarcinoma management by targeting human genes and proteins: the RAIN protocol

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