&lt;p&gt;A Novel lncRNA ENST00000512916 Facilitates Cell Proliferation, Migration and Cell Cycle Progression in Ameloblastoma&lt;/p&gt;

Sun, Yan; Niu, Xing; Wang, Guannan; Qin, Xue; Chen, Lijie; Zhong, Ming

doi:10.2147/ott.s236158

Cited by 19 publications

(13 citation statements)

References 40 publications

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“…Furthermore, among hypomethylated genes, 337 was up-regulated and 1,231 was down-regulated in ameloblastoma tissues in comparison to normal oral tissues, indicating that m 6 A could be involved in regulation of gene expression. For example, our previous study has confirmed that HOXC13 and HOXC13-AS are both highly expressed in ameloblastoma tissues ( 27 ). Their hypermethylation was found in ameloblastoma than normal oral tissues.…”

Section: Discussionmentioning

confidence: 69%

“…Moreover, the CDS region had the highest fractions of mRNAs among five different regions (Figure 9C). In Figures 10A-C, we displayed the general locations of upmethylated m 6 A sites in ameloblastoma-or other oral diseases-related mRNA [HOXC13 (27)], lncRNA [HOXC13-AS (27)] and circRNA [hsa_circ_0086414 (28)] in ameloblastoma compared to adjacent normal oral tissues. DISCUSSION m 6 A is the most abundant mRNA modification in mammals.…”

Section: Identification Of Rna Binding Proteins (Rbps) Within Differentially Methylated M 6 a Sitesmentioning

confidence: 99%

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Landscape of N6-Methyladenosine Modification Patterns in Human Ameloblastoma

Niu

Liu

et al. 2020

Front. Oncol.

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Objective To comprehensively analyze the global N 6 -methyladenosine (m 6 A) modification pattern in ameloblastoma. Methods m 6 A peaks in ameloblastoma and normal oral tissues were detected by MeRIP-seq. Differentially methylated m 6 A sites within messenger RNAs (mRNAs), long no-coding RNA (lncRNAs) and circular RNA (circRNAs) were identified, followed by functional enrichment analysis. By comprehensively analyzing MeRIP-seq and RNA-seq data, differentially expressed mRNAs, lncRNAs and circRNAs containing differentially methylated sites were identified. RNA binding proteins (RBPs) were then identified for differentially methylated m 6 A sites. Results In total, 3,673 differentially methylated m 6 A sites within coding genes were detected, of which 16.2% (704/3,673) were significantly upmethylated sites in ameloblastoma compared to normal oral tissues. Furthermore, 4,975 differentially methylated m 6 A sites within lncRNAs were identified, of which 29.4% (1,465/4,975) were upmethylated sites in ameloblastoma. We also found 364 differentially methylated m 6 A sites within circRNAs, of which 22.5% (82/364) were upmethylated sites in ameloblastoma. Differentially methylated m 6 A was most often harbored in the CDS (54.10%), followed by 5’UTR (21.71%). Functional enrichment analysis revealed that m 6 A modification could be involved in the development of ameloblastoma by organism developmental processes. A total of 158 RBPs within differentially methylated m 6 A sites were identified, which were significantly involved in mRNA metabolic process, mRNA processing, RNA processing, RNA splicing and RNA transport. Conclusion Our findings for the first time provide m 6 A landscape of human ameloblastoma, which expand the understanding of m 6 A modifications and uncover regulation of lncRNAs and circRNAs through m 6 A modification in ameloblastoma.

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Section: Discussionmentioning

confidence: 69%

Section: Identification Of Rna Binding Proteins (Rbps) Within Differentially Methylated M 6 a Sitesmentioning

confidence: 99%

Landscape of N6-Methyladenosine Modification Patterns in Human Ameloblastoma

Niu

Liu

et al. 2020

Front. Oncol.

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“…is study characterized the ICI landscape and developed ICI score system that may predict survival outcomes as well as the response to immunotherapies, which extended our comprehension about the immune microenvironment of LGG. Immunohistochemistry and flow cytometry are two commonly applied methods to detect tumor-infiltrating immune cells, depending on a certain biomarker [27][28][29].…”

Section: Discussionmentioning

confidence: 99%

Uncovering the Immune Cell Infiltration Landscape in Low-Grade Glioma for Aiding Immunotherapy

Yang

Tian

et al. 2022

Journal of Oncology

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Objective. Low-grade glioma (LGG) mainly threatens the elderly population, with undesirable prognoses. This study uncovered the immune cell infiltration (ICI) landscape in LGG. Methods. RNA-seq profiles of LGG were retrieved from TCGA and CGGA databases. CIBERSORTx and ESTIMATE algorithms were employed to characterize the ICI landscape in LGG tissues. Through unsupervised clustering analysis, ICI subtypes were clustered. ICI scores were computed via principal component analysis (PCA). The differences in survival, tumor-infiltrating immune cells, stromal scores, immune scores, immune checkpoint genes, immune activity genes, and tumor mutation burden (TMB) were assessed between high and low ICI score groups. Results. Three ICI subtypes were constructed in LGG, with distinct survival outcomes, PD-L1 expression, and infiltration levels of immune cells. Furthermore, ICI scores were developed. Both in TCGA and CGGA datasets, low ICI scores were indicative of undesirable outcomes. High ICI scores were significantly correlated to increased infiltration levels of memory B cells, CD8 T cells, CD4 naïve T cells, T follicular helper cells, macrophages M0, and eosinophils, while low ICI scores were characterized by increased infiltration levels of naïve B cells, plasma cells, CD4 memory resting T cells, Tregs, resting NK cells, macrophages M2, and activated dendritic cells. High ICI scores exhibited correlations with lower immune activity genes and immune checkpoint genes. Furthermore, TMB was distinctly reduced in the high ICI score group. Conclusion. The ICI scores may serve as a promising prognostic index and predictive indicator for immunotherapies, extending our understanding of immune microenvironment in LGG.

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“…Extensive RNA sequencing (RNA-seq) profiles by The Cancer Genome Atlas (TCGA) have suggested the implications of epigenetic, transcriptional, and post-transcriptional regulation of long noncoding RNAs (lncRNAs) in diagnosing and curing bladder cancer 9 – 11 . LncRNAs display higher specificity to biological states compared to coding RNAs 12 . Molecular characterizations have motivated to optimize actionable therapeutic strategies against bladder cancer 13 .…”

Section: Introductionmentioning

confidence: 99%

An immune-related lncRNA model for predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer

Hou

Liang

Xie

et al. 2022

Sci Rep

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Long noncoding RNAs (lncRNAs) participate in cancer immunity. We characterized the clinical significance of an immune-related lncRNA model and evaluated its association with immune infiltrations and chemosensitivity in bladder cancer. Transcriptome data of bladder cancer specimens were employed from The Cancer Genome Atlas. Dysregulated immune-related lncRNAs were screened via Pearson correlation and differential expression analyses, followed by recognition of lncRNA pairs. Then, a LASSO regression model was constructed, and receiver operator characteristic curves of one-, three- and five-year survival were established. Akaike information criterion (AIC) value of one-year survival was determined as the cutoff of high- and low-risk subgroups. The differences in survival, clinical features, immune cell infiltrations and chemosensitivity were compared between subgroups. Totally, 90 immune-related lncRNA pairs were identified, 15 of which were screened for constructing the prognostic model. The area under the curves of one-, three- and five-year survival were 0.806, 0.825 and 0.828, confirming the favorable predictive performance of this model. According to the AIC value, we clustered patients into high- and low-risk subgroups. High-risk score indicated unfavorable outcomes. The risk model was related to survival status, age, stage and TNM. Compared with conventional clinicopathological characteristics, the risk model displayed higher predictive efficacy and served as an independent predictor. Also, it could well characterize immune cell infiltration landscape and predict immune checkpoint expression and sensitivity to cisplatin and methotrexate. Collectively, the model conducted by paring immune-related lncRNAs regardless of expressions exhibits a favorable efficacy in predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer.

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<p>A Novel lncRNA ENST00000512916 Facilitates Cell Proliferation, Migration and Cell Cycle Progression in Ameloblastoma</p>

Cited by 19 publications

References 40 publications

Landscape of N6-Methyladenosine Modification Patterns in Human Ameloblastoma

Landscape of N6-Methyladenosine Modification Patterns in Human Ameloblastoma

Uncovering the Immune Cell Infiltration Landscape in Low-Grade Glioma for Aiding Immunotherapy

An immune-related lncRNA model for predicting prognosis, immune landscape and chemotherapeutic response in bladder cancer

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