2021
DOI: 10.1007/s10142-021-00812-w
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LINC01087 indicates a poor prognosis of glioma patients with preoperative MRI

Abstract: Long intergenic non-coding RNA 01,087 (LINC01087) has been concerned as an oncogene in breast cancer, while its mechanism in glioma has been little surveyed. Thus, we searched the prognostic value and functional action of LINC01087 in glioma. Glioma patients after preoperative MRI diagnosis were enrolled, and LINC01087, microRNA (miR)-1277-5p, and alkaline ceramidase 3 (ACER3) levels were tested in glioma cancer tissue. The correlation between LINC01087 expression and the survival of patients were analyzed. LI… Show more

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Cited by 10 publications
(6 citation statements)
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References 29 publications
(37 reference statements)
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“…Our results were consistent with the literature regarding the abundance of LINC01087 in BC and ESCA [ 36 , 37 , 38 , 68 ]. Nevertheless, previous research reported a higher expression of LINC01087 in THCA patients than in normal individuals [ 38 ], which was not validated in this study.…”
Section: Discussionsupporting
confidence: 93%
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“…Our results were consistent with the literature regarding the abundance of LINC01087 in BC and ESCA [ 36 , 37 , 38 , 68 ]. Nevertheless, previous research reported a higher expression of LINC01087 in THCA patients than in normal individuals [ 38 ], which was not validated in this study.…”
Section: Discussionsupporting
confidence: 93%
“…The long intergenic non-coding RNA 01087 (LINC01087) is a recently described lncRNA whose function remains poorly investigated. The contribution of LINC01087 to the pathogenesis of cancer, as well as its pivotal role as a biomarker, has been described only in a few oncological indications (i.e., BC, glioma, esophageal squamous cell carcinoma, and thyroid cancer) [ 32 , 36 , 37 , 38 , 39 ]. Recent evidence reported LINC01087 to be overexpressed in glioma patients with respect to healthy subjects [ 36 , 37 ].…”
Section: Introductionmentioning
confidence: 99%
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“…), and glioma cells are tangled with surrounding tissue, resulting in glioma images with diffuse borders, etc. [ 22 ]. In order to better identify the glial tumor areas in MRI images, this study mainly used bendlet transform to make the images of glioma disease in the brain better retain the definition of texture of edges after denoising, and improved the efficiency of the identification of gliomas in the brain.…”
Section: Bendlet Transform For Image Denoisingmentioning
confidence: 99%