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Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most frequent head and neck cancers worldwide. Long non-coding RNAs (lncRNAs) play a critical role in tumorigenesis. However, the clinical significance of lncRNAs in LSCC remains largely unknown.
Methods: In this study, transcriptome sequencing was performed on 107 LSCC and paired adjacent normal mucosa (ANM) tissues. Furthermore, RNA expression and clinical data of 111 LSCC samples were obtained from The Cancer Genome Atlas (TCGA) database. Bioinformatics analysis were performed to construct a model for predicting the overall survival (OS) of LSCC patients. Moreover, we investigated the roles of lncRNAs in LSCC cells through loss-of-function experiments.
Results: A seven-lncRNAs panel including ENSG00000233397, BARX1-DT, LSAMP-AS1, HOXB-AS4, MNX1-AS1, LINC01385, and LINC02893 was identified. The Kaplan-Meier analysis demonstrated that the seven-lncRNAs panel was significantly associated with OS (HR:6.21 [3.27-11.81], p-value<0.0001), disease-specific survival (DSS) (HR:4.34 [1.83-10.26], p-value=0.0008), and progression-free interval (PFI) (HR:3.78 [1.92-7.43], p-value=0.0001). ROC curves showed the seven-lncRNAs panel predicts OS with good specificity and sensitivity. Separately silencing the seven lncRNAs inhibited the proliferation, migration, and invasion capacity of LSCC cells.
Conclusion: Collectively, this seven-lncRNAs panel is a promising signature for predicting the prognosis of LSCC patients, and these lncRNAs could serve as potential targets for LSCC treatment.
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http://dx.doi.org/10.3389/fonc.2023.1106249 | DOI Listing |
Front Oncol
May 2023
Department of Otolaryngology Head & Neck Surgery, Longgang Otolaryngology Hospital, Shenzhen, Guangdong, China.
Background: Laryngeal squamous cell carcinoma (LSCC) is one of the most frequent head and neck cancers worldwide. Long non-coding RNAs (lncRNAs) play a critical role in tumorigenesis. However, the clinical significance of lncRNAs in LSCC remains largely unknown.
View Article and Find Full Text PDFMol Neurobiol
February 2023
Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, 45 Changchun St., Beijing, China.
Long non-coding RNAs (lncRNAs) have been identified to be involved in the pathogenesis of Alzheimer's disease (AD). In this study, we evaluated whether lncRNAs can be used to discriminate AD patients from controls and patients with other dementias, such as vascular, Parkinson's disease, behavioral variant frontotemporal, and dementia with Lewy body. In this study, we used three datasets to measure the blood lncRNA levels.
View Article and Find Full Text PDFMol Omics
December 2022
Department of Clinical Laboratory, The First Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710061, P. R. China.
Bladder cancer (BC) frequently causes a heavy disease burden for patients because of its easy recurrence. There is still a lack of convenient and effective methods to diagnose or monitor BC in the clinic. Emerging evidence suggests that long non-coding RNAs (lncRNAs) in urine are promising biomarkers for BC diagnosis.
View Article and Find Full Text PDFBiomark Res
February 2020
1School of Life Sciences, Chongqing University, Chongqing, 400044 People's Republic of China.
Background: The prognosis of colorectal cancer (CRC) is still challenging to evaluate or predict. Recently, long non-coding RNAs (lncRNAs) have been found to play an important role in tumorigenesis and prognosis, however, few lncRNAs have been identified in CRC progression. We aimed to establish a lncRNA signature to improve prognosis prediction of CRC.
View Article and Find Full Text PDFAging (Albany NY)
January 2020
Department of Cardiology, The Fourth Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
Analyses of long non-coding RNAs (lncRNAs) and microRNAs (miRNAs) implicated in myocardial infarction (MI) have increased our understanding of gene regulatory mechanisms in MI. However, it is not known how their expression fluctuates over the different stages of MI progression. In this study, we used time-series gene expression data to examine global lncRNA and miRNA expression patterns during the acute phase of MI and at three different time points thereafter.
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