Comprehensive Analysis of Novel lncRNA-TF Regulatory Cross Talks and Identification of Core lncRNA-TF Feedback Loops in Sarcoma

Wang, Ke; Ye, Xiangling; Yang, Chengshan; Chen, Guocai; Yao, Nan; Kang, Zhengyang; Shi, Wenqi

doi:10.1089/dna.2020.5385

Cited by 3 publications

(2 citation statements)

References 45 publications

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“…Previous studies proposed that TF-lncRNA positive feedback loops have strong prognostic effects in multiple cancers, such as sarcoma and glioma (38,39). In the field of lung adenocarcinoma, Huang et al found that FOXP3/lncRNA LINC00520 positive feedback loops facilitated cell proliferative and migratory abilities in LUAD through interaction with miR-3611.…”

Section: Discussionmentioning

confidence: 99%

Construction and Characterization of Long Non-Coding RNA-Associated Networks to Reveal Potential Prognostic Biomarkers in Human Lung Adenocarcinoma

et al. 2021

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Lung adenocarcinoma (LUAD) is one type of the malignant tumors with high morbidity and mortality. The molecular mechanism of LUAD is still unclear. Studies demonstrate that lncRNAs play crucial roles in LUAD tumorigenesis and can be used as prognosis biomarkers. Thus, in this study, to identify more robust biomarkers of LUAD, we firstly constructed LUAD-related lncRNA-TF network and performed topological analyses for the network. Results showed that the network was a scale-free network, and some hub genes with high clinical values were identified, such as lncRNA RP11-173A16 and TF ZBTB37. Module analysis on the network revealed one close lncRNA module, which had good prognosis performance in LUAD. Furthermore, through integrating ceRNAs strategy and TF regulatory information, we identified some lncRNA-TF positive feedback loops. Prognostic analysis revealed that ELK4- and BDP1-related feedback loops were significant. Secondly, we constructed the lncRNA-m6A regulator network by merging all the high correlated lncRNA-m6A regulator pairs. Based on the network analysis results, some key m6A-related lncRNAs were identified, such as MIR497HG, FENDRR, and RP1-199J3. We also investigated the relationships between these lncRNAs and immune cell infiltration. Results showed that these m6A-related lncRNAs were high correlated with tumor immunity. All these results provide a new perspective for the diagnostic biomarker and therapeutic target identification of LUAD.

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Section: Discussionmentioning

confidence: 99%

Construction and Characterization of Long Non-Coding RNA-Associated Networks to Reveal Potential Prognostic Biomarkers in Human Lung Adenocarcinoma

et al. 2021

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“…Zaiss discussed the core role undertaken by Forkhead box transcription factors (FTFs) in the regulation of immune responses and homeostasis [19]. It is also worth noting that transcription factors and lncRNA can interact to promote appropriate regulation of gene expression [35,36]. For instance, transcription factor SOX2 activates LINC01561 and promotes the proliferation by modulating SHCBP1 in NSCLC [37].…”

Section: Discussionmentioning

confidence: 99%

Integrated analysis of immune-related genes in endometrial carcinoma

et al. 2020

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Background Exploring novel and sensitive targets is urgent due to the high morbidity of endometrial cancer (EC). The purpose of our study was to explore the transcription factors and immune-related genes in EC and further identify immune-based lncRNA signature as biomarker for predicting survival prognosis. Methods Transcription factors, aberrantly expressed immune-related genes and immune-related lncRNAs were explored through bioinformatics analysis. Cox regression and the least absolute shrinkage and selection operator (LASSO) analysis were conducted to identify the immune and overall survival (OS) related lncRNAs. The accuracy of model was evaluated by Kaplan–Meier method and receiver operating characteristic (ROC) analysis, and the independent prognostic indicator was identified with Cox analysis. Quantitative real-time polymerase chain reaction (qRT-PCR) were conducted to detect the accuracy of our results. Results A network of 29 transcription factors and 17 immune-related genes was constructed. Furthermore, four immune-prognosis-related lncRNAs were screened out. Kaplan–Meier survival analysis and time-dependent ROC analysis revealed a satisfactory predictive potential of the 4-lncRNA model. Consistency was achieved among the results from the training set, testing set and entire cohort. The distributed patterns between the high- and low-risk groups could be distinguished in principal component analysis. Comparisons of the risk score and clinical factors confirmed the four-lncRNA-based signature as an independent prognostic indicator. Last, the reliability of the results was verified by qRT-PCR in 29 cases of endometrial carcinoma and in cells. Conclusions Overall, our study constructed a network of transcription factors and immune-related genes and explored a four immune-related lncRNA signature that could serve as a novel potential biomarker of EC.

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Comprehensive analysis of LMNB2 in pan-cancer and identification of its biological role in sarcoma

Guo,

Zhang,

Luo

et al. 2024

Aging

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Backgrounds: Sarcoma (SARC) is a mesenchymal tumor which often responds poorly to systemic therapy. It is therefore important to look for possible biological markers that could tell the prognosis and the progression of SARC. Methods: A combined evaluation of the Cancer Genome Atlas (TCGA) and genotypic tissue expression (GTEx) portal was used to analyzeLMNB2 expression level in different types of cancer. Kaplan-Meier survival analysis was performed to examine LMNB2 predictive value in over-all survival rate and disease-free survival rate. The association among LMNB2 expression level and immune cell infiltration, microsatellite instability (MSI) and tumor mutational burden (TMB) were analyzed. GO and KEGG enrichment analysis were performed to predicate LMNB2 biological functions. The biological function of LMNB2 was estimated by MTT and flow cytometry assay. Additionally, western blot assay was used to examine protein expression levels. Results: Increased LMNB2 expression was related with worsened cancer type-dependent survival. A relation between LMNB2 expression levels and immune cell infiltration was found. GO and KEGG enrichment analysis indicated that LMNB2 was involved in a series of pathways. Biology function assays revealed that downregulation of LMNB2 impaired proliferation and cell cycle distribution. At the mechanical level, LMNB2 acts as a regulator of cyclinD1 and cyclinE1. Conclusions: Altogether, these data suggest that LMNB2 may serve as a tumor promoter and could be a possible target for cancer therapy.

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Comprehensive Analysis of Novel lncRNA-TF Regulatory Cross Talks and Identification of Core lncRNA-TF Feedback Loops in Sarcoma

Cited by 3 publications

References 45 publications

Construction and Characterization of Long Non-Coding RNA-Associated Networks to Reveal Potential Prognostic Biomarkers in Human Lung Adenocarcinoma

Construction and Characterization of Long Non-Coding RNA-Associated Networks to Reveal Potential Prognostic Biomarkers in Human Lung Adenocarcinoma

Integrated analysis of immune-related genes in endometrial carcinoma

Comprehensive analysis of LMNB2 in pan-cancer and identification of its biological role in sarcoma

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