&lt;p&gt;Long noncoding RNA HCP5 suppresses skin cutaneous melanoma development by regulating &lt;em&gt;RARRES3&lt;/em&gt; gene expression via sponging miR-12&lt;/p&gt;

Wei, Xihua; Gu, Xuelian; Ma, Min; Lou, Chunxiang

doi:10.2147/ott.s195796

Cited by 32 publications

(27 citation statements)

References 41 publications

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“…[19][20][21] Much evidence suggests that numerous lncRNAs are differentially expressed in melanoma, and their dysregulation is involved in melanoma progression because lncRNAs can act as oncogenic factors or tumor suppressors. [22][23][24] Accordingly, in-depth exploration of lncRNAs' functions in the formation and progression of melanoma is essential for identifying new targets for the diagnosis and management of this fatal disease.…”

Section: Introductionmentioning

confidence: 99%

Long Noncoding RNA LINC00173 Promotes the Malignancy of Melanoma by Promoting the Expression of IRS4 Through Competitive Binding to microRNA-493

Yang¹,

Lei²,

Zeng³

et al. 2020

CMAR

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Purpose: Long intergenic non-protein-coding RNA 173 (LINC00173) plays crucial roles in lung cancer. However, the expression and biological functions of LINC00173 in melanoma have not yet been investigated. In this study, we aimed to characterize the involvement of LINC00173 in melanoma and elucidate its mechanisms of action. Materials and Methods: Reverse-transcription quantitative PCR was performed to measure LINC00173 expression in melanoma. A CCK-8 assay, flow cytometry, and migration and invasion assays were applied to examine melanoma cell proliferation, apoptosis, migration, and invasion, respectively. A xenograft tumor experiment was performed to determine the tumorous growth of melanoma cells in vivo. Results: We found that LINC00173 was upregulated in melanoma tissues and cell lines. High LINC00173 expression was closely associated with TNM stage, lymph node metastasis, and shorter overall survival of patients with melanoma. Functional assays revealed that LINC00173 downregulation inhibited melanoma cell proliferation, migration, and invasion and induced apoptosis, suggesting that LINC00173 acts as an oncogenic RNA. LINC00173 knockdown retarded the tumorous growth of melanoma cells in vivo. Mechanistically, LINC00173 increased insulin receptor substrate 4 (IRS4) expression by sponging microRNA-493 (miR-493), thereby acting as a competing endogenous RNA. The effects of LINC00173 knockdown on the malignant phenotype of melanoma cells were reversed by overexpression of IRS4 or knockdown of miR-493. Conclusion: The LINC00173-miR-493-IRS4 pathway regulates melanoma characteristics by increasing the expression of IRS4 via competitive binding of LINC00173 to miR-493, suggesting that this pathway is a potential target for the diagnosis, prognosis, and/or treatment of melanoma.

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Section: Introductionmentioning

confidence: 99%

Long Noncoding RNA LINC00173 Promotes the Malignancy of Melanoma by Promoting the Expression of IRS4 Through Competitive Binding to microRNA-493

Yang¹,

Lei²,

Zeng³

et al. 2020

CMAR

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“…Three genes, i.e., CLEC7A , CLEC10A , and HAPLN3 have been reported to exhibit prognostic significance with respect to melanoma for the first time, while HCP5 has been reported to inhibit the development of cutaneous melanoma ( 42 ). CLEC7A (also known as dectin-1) encodes for a pattern-recognition receptor expressed by myeloid phagocytes (macrophages, dendritic cells, and neutrophils) that can directly drive the antimicrobial activity ( 43 , 44 ).…”

Section: Discussionmentioning

confidence: 99%

“…The role of the long non-coding RNA (lncRNA) HCP5 in cancer remains controversial. Some reports suggest that HCP5 could induce tumor progression in cases of follicular thyroid carcinoma and lung adenocarcinoma ( 51 – 53 ), while others claim that HCP5 may suppress the development of cutaneous melanoma by modulating RARRES3 expression by sponging miR-12 ( 42 ). Consistent with previous studies, we observed an association between upregulated HCP5 expression and improved survival in melanoma and that HCP5 might boost the anti-tumoral immunity.…”

Section: Discussionmentioning

confidence: 99%

A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma

et al. 2021

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BackgroundCurrently there is no effective prognostic indicator for melanoma, the deadliest skin cancer. Thus, we aimed to develop and validate a nomogram predictive model for predicting survival of melanoma.MethodsFour hundred forty-nine melanoma cases with RNA sequencing (RNA-seq) data from TCGA were randomly divided into the training set I (n = 224) and validation set I (n = 225), 210 melanoma cases with RNA-seq data from Lund cohort of Lund University (available in GSE65904) were used as an external test set. The prognostic gene biomarker was developed and validated based on the above three sets. The developed gene biomarker combined with clinical characteristics was used as variables to develop and validate a nomogram predictive model based on 379 patients with complete clinical data from TCGA (Among 470 cases, 91 cases with missing clinical data were excluded from the study), which were randomly divided into the training set II (n = 189) and validation set II (n = 190). Area under the curve (AUC), concordance index (C-index), calibration curve, and Kaplan-Meier estimate were used to assess predictive performance of the nomogram model.ResultsFour genes, i.e., CLEC7A, CLEC10A, HAPLN3, and HCP5 comprise an immune-related prognostic biomarker. The predictive performance of the biomarker was validated using tROC and log-rank test in the training set I (n = 224, 5-year AUC of 0.683), validation set I (n = 225, 5-year AUC of 0.644), and test set I (n = 210, 5-year AUC of 0.645). The biomarker was also significantly associated with improved survival in the training set (P < 0.01), validation set (P < 0.05), and test set (P < 0.001), respectively. In addition, a nomogram combing the four-gene biomarker and six clinical factors for predicting survival in melanoma was developed in the training set II (n = 189), and validated in the validation set II (n = 190), with a concordance index of 0.736 ± 0.041 and an AUC of 0.832 ± 0.071.ConclusionWe developed and validated a nomogram predictive model combining a four-gene biomarker and six clinical factors for melanoma patients, which could facilitate risk stratification and treatment planning.

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“…For instance, lncRNA TTN-AS1 promotes SKCM development and metastasis by maintaining TTN expression ( Wang et al, 2020 ). LncRNA HCP5 inhibits the development of SKCM through regulation of miR-12 expression ( Wei et al, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

m6A-Related lncRNAs Are Potential Biomarkers for the Prognosis of Metastatic Skin Cutaneous Melanoma

Huang

Lyu

Gao

et al. 2021

Front. Mol. Biosci.

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Background: The incidence of skin cutaneous melanoma (SKCM) has risen more rapidly than any other solid tumor in the past few decades. The median survival for metastatic melanoma is only six to nine months and the 5°years survival rate of patients with conventional therapy is less than 5%. Our aim was to reveal the potential molecular mechanism in m6A modification of lncRNA and provide candidate prognostic biomarkers for metastatic SKCM.Methods: lncRNAs expression level was obtained by re-annotation in TCGA and CCLE datasets. m6A-related lncRNAs were selected though correlation analysis. Univariate cox regression analysis was used to screen out independent prognostic factors. LASSO Cox regression was performed to construct an m6A-related lncRNA model (m6A-LncM). Univariate survival analysis and ROC curve were used to assess the prognostic efficacy of this model and candidate lncRNAs. Enrichment analysis was used to explore the candidate genes’ functions.Results: We obtained 1,086 common m6A-related lncRNAs after Pearson correlation analysis in both two datasets. 130 out of the 1,086 lncRNAs are independent prognostic factors. 24 crucial lncRNAs were filtered after LASSO Cox regression analysis. All the m6A-LncM and the 24 lncRNAs were related to overall survival. Stratified survival analysis of m6A-LncM showed that the model retains its prognostic efficacy in recurrence, radiation therapy and other subgroups. Enrichment analysis also found that these lncRNAs were immune associated.Conclusion: Here, we obtained 24 crucial lncRNAs that may be potential biomarkers to predict survival of metastatic SKCM and may provide a new insight to improve the prognosis of it.

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<p>Long noncoding RNA HCP5 suppresses skin cutaneous melanoma development by regulating <em>RARRES3</em> gene expression via sponging miR-12</p>

Cited by 32 publications

References 41 publications

<p>Long Noncoding RNA <em>LINC00173</em> Promotes the Malignancy of Melanoma by Promoting the Expression of IRS4 Through Competitive Binding to microRNA-493</p>

<p>Long Noncoding RNA <em>LINC00173</em> Promotes the Malignancy of Melanoma by Promoting the Expression of IRS4 Through Competitive Binding to microRNA-493</p>

A Nomogram Combining a Four-Gene Biomarker and Clinical Factors for Predicting Survival of Melanoma

m6A-Related lncRNAs Are Potential Biomarkers for the Prognosis of Metastatic Skin Cutaneous Melanoma

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