An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer

Gao, Shun; Wang, Yuan; Xu, Yingkun; Liu, Shengchun

doi:10.3390/jpm13030513

Cited by 4 publications

(2 citation statements)

References 43 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While research on NDUFA6-DT in tumors and gliomas is currently limited, its increasing recognition in the field of oncology is extensive. Previous studies have identified NDUFA6-DT as a prognostic lncRNA in breast [31][32][33] and thyroid cancers [34]. Functioning as a protective factor, it carries potential implications as a cancer prognostic indicator and therapeutic target.…”

Section: Discussionmentioning

confidence: 99%

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas

Huang,

Kong,

Luo

et al. 2024

Genes

View full text Add to dashboard Cite

Gliomas are the most prevalent primary malignant tumors affecting the brain, with high recurrence and mortality rates. Accurate diagnoses and effective treatment challenges persist, emphasizing the need for identifying new biomarkers to guide clinical decisions. Long noncoding RNAs (lncRNAs) hold potential as diagnostic and therapeutic biomarkers in cancer. However, only a limited subset of lncRNAs in gliomas have been explored. Therefore, this study aims to identify lncRNA signatures applicable to patients with gliomas across all grades and explore their clinical significance and potential biological mechanisms. Data used in this study were obtained from TCGA, CGGA, and GEO datasets to identify key lncRNA signatures in gliomas through differential and survival analyses and machine learning algorithms. We examined their associations with the clinical characteristics, gene mutations, diagnosis, and prognosis of gliomas. Functional enrichment analysis was employed to elucidate the potential biological mechanisms associated with these significant lncRNA signatures. We explored competing endogenous RNA (ceRNA) regulatory networks. We found that NDUFA6-DT emerged as a significant lncRNA signature in gliomas, with reduced NDUFA6-DT expression associated with a worse prognosis in gliomas. Nomogram analysis incorporating NDUFA6-DT expression levels exhibited excellent prognostic and predictive capabilities. Functional annotation suggested that NDUFA6-DT might influence immunological responses and synaptic transmission, potentially modifying glioma initiation and progression. The associated ceRNA network revealed the possible presence of the NDUFA6-DT-miR-455-3p-YWHAH/YWHAG axis in low-grade glioma (LGG) and glioblastoma multiforme (GBM), regulating the PI3K-AKT signaling pathway and influencing glioma cell survival and apoptosis. We believe that NDUFA6-DT is a novel lncRNA linked to glioma diagnosis and prognosis, potentially becoming a pivotal biomarker for glioma.

show abstract

Section: Discussionmentioning

confidence: 99%

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas

Huang,

Kong,

Luo

et al. 2024

Genes

View full text Add to dashboard Cite

show abstract

“…These biological activities supply plentiful oxygen and nutrients for rapid tumor growth. Advanced ccRCC is an angiogenesis-dependent tumor 10 , 11 . Therefore, angiogenesis-related biomarkers might be useful for assessing ccRCC prognosis.…”

Section: Introductionmentioning

confidence: 99%

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Chen,

Zhang,

et al. 2024

J. Cancer

View full text Add to dashboard Cite

Background: Tumor angiogenesis is closely related to the progression of clear cell renal cell carcinoma (ccRCC). Long non-coding RNAs (lncRNAs) regulating angiogenesis could be potential biomarkers for predicting ccRCC prognosis. With this study, we aimed to construct a prognostic model based on lncRNAs and explore its underlying mechanisms. Methods: RNA data and clinical information were obtained from The Cancer Genome Atlas (TCGA) database. Angiogenesis-related genes (ARGs) were extracted from the Molecular Signatures database. Pearson correlation and LASSO and COX regression analyses were performed to identify survival-related AR-lncRNAs (sAR-lncRNAs) and construct a prognostic model. The predictive power of the prognostic model was verified according to Kaplan-Meier curve, receiver operating characteristic (ROC) curve and nomogram analyses. The correlation between the prognostic model and clinicopathological characteristics was assessed via univariate and multivariate analyses. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis was subsequently performed to elucidate the mechanisms of the sAR-lncRNAs. In vitro qPCR, immunohistochemistry, migration and invasion assays were conducted to confirm the angiogenic function of sAR-lncRNAs. Results: Three sAR-lncRNAs were used to construct a prognostic model. The model was moderately accurate in predicting 1-, 3-and 5-year ccRCC prognosis, and the risk score according to this model was closely related to clinicopathological characteristics such as T grade and T stage. A nomogram was constructed to precisely estimate the overall survival of ccRCC patients. KEGG enrichment analysis indicated that the MAPK and Notch pathways were highly enriched in high-risk patients. Additionally, we found that the expression of the lncRNAs AC005324.4 and AC104964.4 in the prognostic model was lower in ccRCC cell lines and cancer tissues than in the HK-2 cell line and paracancerous tissues, while the expression of the lncRNA AC087482.1 showed the opposite trend. In a coculture model, knockdown of lncRNA AC005324.4 and lncRNA AC104964.4 significantly promoted the migration and invasion of human umbilical vein endothelial cells (HUVECs), but siR-AC087482.1 transfection alleviated these effects. Conclusions:We constructed a prognostic model based on 3 sAR-lncRNAs and validated its value in clinicopathological characteristics and prognostic prediction of ccRCC patients, providing a new perspective for ccRCC treatment decision making.

show abstract

Identification of cuproptosis-related gene SLC31A1 and upstream LncRNA-miRNA regulatory axis in breast cancer

Wu,

Cheng,

Zhu

et al. 2023

Sci Rep

View full text Add to dashboard Cite

Mounting evidence indicate that cuproptosis, a novel form of programmed cell death, contributes to cancer development and progression. However, a comprehensive analysis regarding the expressions, functions, and regulatory network of cuproptosis-related genes is still lacking. In the present work, cuproptosis-related genes, upstream miRNAs and lncRNAs, and clinical data of breast cancer from TCGA database were analyzed by R language including Cox regression analysis, correlation calculation, ROC curve construction, and survival evaluation, and were further verified by public-available databases. Chemosensitivity and immune infiltration were also evaluated by online tools. SLC31A1 was significantly increased in breast cancer samples than those in normal tissues. SLC31A1 was negatively related to a favorable outcome in breast cancer, and the AUC value increased with the prolongation of follow-up time. LINC01614 and miR-204-5p were potential upstream regulators of SLC31A1. Moreover, SLC31A1 was significantly positively correlated with different immune cells infiltration, immune cell biomarkers, and immune checkpoints in breast cancer. SLC31A1 was a potential cuproptosis-related gene in breast cancer, which was significantly upregulated and was able to predict diagnosis, prognosis, chemosensitivity, and immune infiltration. LINC01640/miR-204-5p/SLC31A1 might be a significant and promising axis during cuproptosis in breast cancer.

show abstract

An Angiogenesis-Related lncRNA Signature Is Associated with Prognosis and Tumor Immune Microenvironment in Breast Cancer

Cited by 4 publications

References 43 publications

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas

LncRNA NDUFA6-DT: A Comprehensive Analysis of a Potential LncRNA Biomarker and Its Regulatory Mechanisms in Gliomas

A Model to Predict Prognosis of Renal Cell Clear Cell Carcinoma Based on 3 Angiogenesis-related Long Non-coding RNAs

Identification of cuproptosis-related gene SLC31A1 and upstream LncRNA-miRNA regulatory axis in breast cancer

Contact Info

Product

Resources

About