A group of long noncoding RNAs identified by data mining can predict the prognosis of lung adenocarcinoma

Liao, Meijian; Liu, Qing; Li, Bing; Liao, Weijie; Xie, Weidong; Zhang, Y

doi:10.1111/cas.13822

Cited by 14 publications

(14 citation statements)

References 39 publications

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“…The UCSC Xena website (http:// xena.ucsc.edu/) offers tools for the visualization and exploration of TCGA genomic data [18]. According to the coexpression results from Oncomine and an interesting study [11], we performed a search on Siglec-15, SMAD7, ATP5A1 and CD274 (PD-L1) using the Genes viewing mode.…”

Section: Genomic Data and Viewsmentioning

confidence: 99%

Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining

Li¹,

Huang²,

Chen³

et al. 2020

J. Cancer

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Objective: Cancer is expected to be the leading cause of death worldwide within the 21st century and is the single most important obstacle to extending life expectancy. Unfortunately, the most effective approach to combating cancers remains a complex and unsolved problem. Siglec-15 is a member of the Siglec family and plays a conserved regulatory role in the immune system of vertebrates. Previous studies on Siglec-15 have focused on its function in osteoclast regulation. The purpose of this study was to explore the significance of Siglec-15 mRNA in human cancer mainly based on information obtained from online databases. Method: Data were collected from several online databases. Serial analysis of gene expression (SAGE) and Virtual Northern, UALCAN Database Analysis, Catalog of Somatic Mutations in Cancer (COSMIC) analysis, the cBio cancer genomics portal, Cancer Regulome tools and data, Kaplan-Meier Plotter Analysis and the UCSC Xena website were used to analyze the data. Results: Compared with normal tissues, Siglec-15 up-regulation was widely observed in tuomrs. Differences in Siglec-15 expression were associated with different prognoses. Siglec-15 mutations are widely observed in tumors and interact with different genes in different cancer types. Conclusion: Siglec-15 is a potential target for the expansion of cancer immunotherapy.

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Section: Genomic Data and Viewsmentioning

confidence: 99%

Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining

Li¹,

Huang²,

Chen³

et al. 2020

J. Cancer

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“…With a risk score formula, patients were divided into high- and low-risk groups. The risk score predicting model has been proposed as a tool for prognosis prediction in several types of cancers, including colon cancers (Dai et al, 2018 ; Gu et al, 2018 ; Liao et al, 2018 ). However, no study has focused on the prognosis of non-metastatic and metastatic CRC patients.…”

Section: Discussionmentioning

confidence: 99%

Identification of LncRNAs Associated With FOLFOX Chemoresistance in mCRC and Construction of a Predictive Model

Zhang

Sun

et al. 2021

Front. Cell Dev. Biol.

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Oxaliplatin, fluorouracil plus leucovorin (FOLFOX) regimen is the first-line chemotherapy of patients with metastatic colorectal cancer (mCRC). However, studies are limited regarding long non-coding RNAs (lncRNAs) associated with FOLFOX chemotherapy response and prognosis. This study aimed to identify lncRNAs associated with FOLFOX chemotherapy response and prognosis in mCRC patients and to construct a predictive model. We analyzed lncRNA expression in 11 mCRC patients treated with FOLFOX chemotherapy before surgery (four sensitive, seven resistant) by Gene Array Chip. The top eight lncRNAs (AC007193.8, CTD-2008N3.1, FLJ36777, RP11-509J21.4, RP3-508I15.20, LOC100130950, RP5-1042K10.13, and LINC00476) for chemotherapy response were identified according to weighted correlation network analysis (WGCNA). A competitive endogenous RNA (ceRNA) network was then constructed. The crucial functions of the eight lncRNAs enriched in chemotherapy resistance were mitogen-activated protein kinase (MAPK) and proteoglycans signaling pathway. Receiver operating characteristic (ROC) analysis demonstrated that the eight lncRNAs were potent predictors for chemotherapy resistance of mCRC patients. To further identify a signature model lncRNA chemotherapy response and prognosis, the validation set consisted of 196 CRC patients from our center was used to validate lncRNAs expression and prognosis by quantitative PCR (qPCR). The expression of the eight lncRNAs expression between CRC cancerous and adjacent non-cancerous tissues was also verified in the validation data set to determine the prognostic value. A generalized linear model was established to predict the probability of chemotherapy resistance and survival. Our findings showed that the eight-lncRNA signature may be a novel biomarker for the prediction of FOLFOX chemotherapy response and prognosis of mCRC patients.

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“…In addition, although the clinical application of lncRNAs remains scarce, they have the potential to become a diagnostic and prognostic marker and a therapeutic target in patients with LUAD. 27 , 28 Therefore, in this study, we attempted to identify an LUAD-related lncRNA and explore its potential as a diagnostic and prognostic marker.…”

Section: Discussionmentioning

confidence: 99%

A Long Intergenic Non-coding RNA, LINC01426, Promotes Cancer Progression via AZGP1 and Predicts Poor Prognosis in Patients with LUAD

Tian

Han

et al. 2020

Molecular Therapy - Methods & Clinical Development

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Various long non-coding RNAs (lncRNAs) are closely associated with lung adenocarcinoma (LUAD), playing oncogenic or anti-oncogenic roles in tumorigenesis and progression. Herein, we report a novel lncRNA—long intergenic non-protein coding RNA 1426 (LINC01426)—that has not yet been characterized in LUAD. We note that LINC01426 expression was markedly upregulated in LUAD tissues, and that functional assays verified that LINC01426 knockdown markedly inhibited cell proliferation, migration, and invasion in vitro . Xenografts derived from A549 cells knocked down of LINC01426 had evidently lower tumor weights and smaller tumor volumes. Our study also found that LINC01426 bound to hsa-miR-30b-3p as a competitive endogenous RNA in LUAD. Moreover, LINC01426 affected LUAD wound healing by interacting and combining with AZGP1, and LINC01426 expression was significantly associated with tumor-node-metastasis (TNM) staging and prognosis in patients with LUAD. To summarize, our study elucidates the oncogenic roles of LINC01426 in LUAD tumorigenesis and progression. We think that LINC01426 can serve as a potential diagnostic biomarker and therapeutic target in patients with LUAD.

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A group of long noncoding RNAs identified by data mining can predict the prognosis of lung adenocarcinoma

Cited by 14 publications

References 39 publications

Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining

Integrative Analysis of Siglec-15 mRNA in Human Cancers Based on Data Mining

Identification of LncRNAs Associated With FOLFOX Chemoresistance in mCRC and Construction of a Predictive Model

A Long Intergenic Non-coding RNA, LINC01426, Promotes Cancer Progression via AZGP1 and Predicts Poor Prognosis in Patients with LUAD

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