<scp>LncRNA</scp><scp>SGMS1‐AS1</scp> regulates lung adenocarcinoma cell proliferation, migration, invasion, and <scp>EMT</scp> progression via <scp>miR‐106a‐5p/MYLI9</scp> axis

Liu, Ting; Chen, Yang; Wang, Weizhen; Liu, Chunmei

doi:10.1111/1759-7714.14043

Cited by 24 publications

(15 citation statements)

References 27 publications

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“… 44 SGMS1-AS1 is a newly identified lncRNA transcribed in 25 tissues, including the testis and thyroid. 45 In this study, based on bioinformatic analysis, we found that the expression of microRNA-106a-5p was negatively correlated with the expression of CPT2 and SGMS1-AS1, while the expression of SGMS1-AS1 was positively associated with the expression of CPT2 in colon cancer. In addition, RT-PCR results showed that in both cell lines and clinical specimens, the expression of CPT2 and SGMS1-AS1 was decreased in tumor cell lines and tumor tissues compared with normal colon epithelial cell lines or paraneoplastic tissues, but the expression of microRNA-106a-5p was significantly increased, and the expression level of CPT2 protein was also decreased in colon cancer tissues.…”

Section: Discussionmentioning

confidence: 62%

SGMS1-AS1/MicroRNA-106a-5p/CPT2 Axis as a Novel Target for Regulating Lactate Metabolism in Colon Cancer

Ruochen,

Wenbin,

Chao

et al. 2023

Technol Cancer Res Treat

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Purpose The malignant transformation of cells can lead to aerobic glycolysis, an important form of metabolic reprogramming in colon cancer cells, which can cause the accumulation of lactate and accelerate the proliferation of tumor cells also enhance their chemotherapy drug resistance. The aim of this study was to investigate the possible molecular mechanisms responsible for the increased lactate expression in colon cancer. Methods Several bioinformatics methods, including differential analysis, gene ontology enrichment, univariate and multivariate Cox regression analysis were used to find the lactic acid–related gene carnitine palmitoyltransferase 2. We analyzed the relationship between carnitine palmitoyltransferase 2 and clinical features as well as immune microenvironment. To further explore the mechanism of carnitine palmitoyltransferase 2 in colon cancer, we performed methylation analysis and constructed a competitive endogenous RNA network, which was validated in cell lines and clinical specimens. Results We used bioinformatics to select the lactic acid–related gene carnitine palmitoyltransferase 2 and found low expression of carnitine palmitoyltransferase 2 was associated with poor prognosis in colon cancer. An inhibitory tumor microenvironment was created when carnitine palmitoyltransferase 2 expression was reduced, with decreased CD4 T cells, CD8 T cells, dendritic cells, and B cells but increased cancer-associated fibroblasts. Methylation analysis showed that the abnormal decrease in carnitine palmitoyltransferase 2 might be caused by hypermethylation. We constructed a network of SGMS1-AS1/microRNA-106a-5p/carnitine palmitoyltransferase 2 and verified their expression in cell lines and clinical specimens. Conclusion Our work revealed the possible mechanism of lactate accumulation in colon cancer and explored a new potential treatment for colon cancer by cutting off aerobic glycolysis in tumor cells.

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Section: Discussionmentioning

confidence: 62%

SGMS1-AS1/MicroRNA-106a-5p/CPT2 Axis as a Novel Target for Regulating Lactate Metabolism in Colon Cancer

Ruochen,

Wenbin,

Chao

et al. 2023

Technol Cancer Res Treat

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“…We identify nine genes and find the four genes ( PITPNM3 , MXD4 , ABCB1 , BATF ) that are related to HNSCC in the literature ( Aravind et al, 2021 ; Wu et al, 2019b ; da Silva et al, 2021 ; Duz & Karatas, 2021 ; Wang et al, 2020 ; and Wen et al, 2015 ). We identify fifteen genes and find the seven genes ( EPB41L5 , INPP5J , KRT16 , MS4A1 , MYLIP , PEBP1 , SFTPB ) that are related to LUAD in the literature ( Li et al, 2020a ; Zhang et al, 2020a ; Yuanhua et al, 2019 ; Song et al, 2020 ; Liu et al, 2021b ; Li et al, 2020b ; Zhang et al, 2021 ; Cao et al, 2021 ; and Zhang et al, 2019 ). We identify ten genes and find the four genes ( EDA2R , PCMT1 , QPRT , SKP1 ) that are related to BRCA in the literature ( Liu, Kain & Wang, 2012 ; Kyritsis et al, 2021 ; Liu et al, 2021a ; and Tian et al, 2020 ).…”

Section: Resultsmentioning

confidence: 99%

Feature screening for survival trait with application to TCGA high-dimensional genomic data

Wang¹,

Li²,

Hou³

2022

PeerJ

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Background In high-dimensional survival genomic data, identifying cancer-related genes is a challenging and important subject in the field of bioinformatics. In recent years, many feature screening approaches for survival outcomes with high-dimensional survival genomic data have been developed; however, few studies have systematically compared these methods. The primary purpose of this article is to conduct a series of simulation studies for systematic comparison; the second purpose of this article is to use these feature screening methods to further establish a more accurate prediction model for patient survival based on the survival genomic datasets of The Cancer Genome Atlas (TCGA). Results Simulation studies prove that network-adjusted feature screening measurement performs well and outperforms existing popular univariate independent feature screening methods. In the application of real data, we show that the proposed network-adjusted feature screening approach leads to more accurate survival prediction than alternative methods that do not account for gene-gene dependency information. We also use TCGA clinical survival genetic data to identify biomarkers associated with clinical survival outcomes in patients with various cancers including esophageal, pancreatic, head and neck squamous cell, lung, and breast invasive carcinomas. Conclusions These applications reveal advantages of the new proposed network-adjusted feature selection method over alternative methods that do not consider gene-gene dependency information. We also identify cancer-related genes that are almost detected in the literature. As a result, the network-based screening method is reliable and credible.

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“…This indicates that CDKN2B-AS1, SGMS1-AS1, and LINC02356 suppress Hela cells' EMT. LncRNA SGMS1-AS1 suppresses the growth, invasion, migration, and EMT development of LUAD cells by targeting miR-106a-5p/MYLIP axis, and SGMS1-AS1 was downregulated in LUAD tissue as well as cells, which was connected to excellent prognosis of individuals with lung adenocarcinoma [63].…”

Section: Discussionmentioning

confidence: 99%

Cuproptosis-related lncRNAs as a novel biomarker to predict prognosis and explore biological function in cervical cancer

Fu¹,

Wang²,

Jiang³

et al. 2023

Preprint

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We aim to investigate a prognostic signature of cuproptosis-related long non-coding RNAs (lncRNAs) and to search for effective individualized clinical treatment strategies. Transcription profiles and clinical follow-up data of CC were retrieved from TCGA database. Three cuproptosis-related lncRNAs closely related to the prognosis of patients with CC were identified and used to construct a prognostic signature via LASSO Cox regression. The predictive performance of the signature was evaluated by K-M analysis and ROC analysis. The expression and biological function of the three lncRNAs in CC were verified by CCK-8, wound healing assay, transwell assay, qRT-PCR and WB blot. The ROC curves confirmed the superior predictive performance of the signature compared with conventional clinicopathological characteristics in CC. Furthermore, HIF-1 signaling pathway and TGF-β signaling pathway differed significantly between the two risk groups according to functional enrichment analysis. Finally, the results showed that CDKN2B-AS1 interference, SGMS1-AS1 and LINC02356 overexpression inhibited the proliferation activity of Hela cells. The invasion of Hela cells was remarkably inhibited, significantly attenuated migration functions and also the expressions of TGF-β, Smad2, Smad3 and Smad4 were decreased. The three cuproptosis-related lncRNAs may help predict CC patients' OS and thus could assist clinicians in making personalized treatment plans for CC patients.

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LncRNASGMS1‐AS1 regulates lung adenocarcinoma cell proliferation, migration, invasion, and EMT progression via miR‐106a‐5p/MYLI9 axis

Cited by 24 publications

References 27 publications

SGMS1-AS1/MicroRNA-106a-5p/CPT2 Axis as a Novel Target for Regulating Lactate Metabolism in Colon Cancer

SGMS1-AS1/MicroRNA-106a-5p/CPT2 Axis as a Novel Target for Regulating Lactate Metabolism in Colon Cancer

Feature screening for survival trait with application to TCGA high-dimensional genomic data

Cuproptosis-related lncRNAs as a novel biomarker to predict prognosis and explore biological function in cervical cancer

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