Signal peptidase 21 suppresses cell proliferation, migration, and invasion via the PTEN-PI3K/Akt signaling pathway in lung adenocarcinoma

Zhang, Na; Cao, Shiguang; Sun, Ruiying; Wang, Yibei; Liu, Luna; Wang, Wei; Xia, Meng

doi:10.7717/peerj.14206

Cited by 3 publications

(2 citation statements)

References 10 publications

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“…(Figure 6C). The five miRNAs comprising the three ERRmiR markers were significantly enriched in the p53 signaling, Cell cycle, PI3K-Akt pathways and so on, which had been widely reported to be associated with LUAD [28][29][30] (Figure 6D).…”

Section: Example 2: Diagnostic Model Of Rcc Using Tissue Samplesmentioning

confidence: 90%

The ratio of interacting miRNAs’ expressions is a robust biomarker for disease classification in multi-center data

Zhang

Ding

et al. 2023

Preprint

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Background Many miRNA-based diagnostic models have been constructed to distinguish diseased individuals. However, due to the inherent differences across different platforms or within multi-center data, the models usually fail in the generalization for medical application. Results Here, we proposed to use the within-sample expression ratios of related miRNA pairs as markers, by utilizing the internal miRNA: miRNA interactions. The ratio of the expression values between each miRNA pair turned out to be more stable cross multiple data source. Moreover, we adopted the genetic algorithm to solve the curse of dimensions when exploring the features. Conclusions The application results on three example datasets demonstrated that the expression ratio of interacting miRNA pair is a promising type of biomarker, which is insensitive to batch effects and has better performance in disease classifications.

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Section: Example 2: Diagnostic Model Of Rcc Using Tissue Samplesmentioning

confidence: 90%

The ratio of interacting miRNAs’ expressions is a robust biomarker for disease classification in multi-center data

Zhang

Ding

et al. 2023

Preprint

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show abstract

“…The performance verification data of the model are shown in Table 4. The five miRNAs of the three ERRmiR markers were significantly enriched in the p53 signaling, cell cycle, and PI3K-Akt pathways, which are widely reported to be associated with LUAD (Huang et al, 2022;Tang et al, 2022;Zhang et al, 2022) (Figure 6D).…”

Section: Prediction Of Lung Adenocarcinoma Using Tissue Errmir Signat...mentioning

confidence: 95%

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data

Ma,

Zhang,

Ding

et al. 2024

Front. Genet.

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MicroRNAs (miRNAs) are promising biomarkers for the early detection of disease, and many miRNA-based diagnostic models have been constructed to distinguish patients and healthy individuals. To thoroughly utilize the miRNA-profiling data across different sequencing platforms or multiple centers, the models accounting the batch effects were demanded for the generalization of medical application. We conducted transcription factor (TF)-mediated miRNA–miRNA interaction network analysis and adopted the within-sample expression ratios of miRNA pairs as predictive markers. The ratio of the expression values between each miRNA pair turned out to be stable across multiple data sources. A genetic algorithm-based classifier was constructed to quantify risk scores of the probability of disease and discriminate disease states from normal states in discovery, with a validation dataset for COVID-19, renal cell carcinoma, and lung adenocarcinoma. The predictive models based on the expression ratio of interacting miRNA pairs demonstrated good performances in the discovery and validation datasets, and the classifier may be used accurately for the early detection of disease.

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The implication of endoplasmic reticulum stress-related genes in lung adenocarcinoma revealed by bioinformatics and single cell RNA sequencing analysis

Zheng

2024

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Background: Endoplasmic reticulum stress (ERS) has the potential to treat a variety of malignant tumors, including lung adenocarcinoma (LUAD). In this study, by leveraging bioinformatics, ERS-related genes were screened to construct a prognostic model for lung adenocarcinoma so as to find new therapeutic strategies. Methods: A variety of bioinformatics algorithms (co-expression analysis, univariate Cox analysis, multivariate Cox analysis and cross-validation) were used to screen ERS-related genes and construct a risk model. Patients with LUAD were divided into training group and testing group in a 1:1 ratio. Receiver operating characteristic curve (ROC), nomogram, independent prognostic analysis and principal component analysis were used to compare the risk scores of the high and low risk groups to verify the validity of the prognostic model. In addition, consensus clustering was used to classify different clusters of LUAD patients which were compared in terms of survival time, immune microenvironment and pathway regulation. The deletion-associated genes were analyzed, combined with single cell sequencing (scRNA-seq), to further investigate screened prognostic risk genes. Results: This study demonstrated the feasibility of a model based on six ERS related genes (SLC2A1, ASPH, SERPINH1, TLR4, CAV3, and SLC6A4), as well as the identification of UMI77, YM155, MG132, and lapatinib as potential therapeutic strategies for LUAD. Risk scores based on this model could be used as independent prognostic factors for LUAD (HR > 1; p < 0.001) and had the highest accuracy in predicting survival compared to clinical features. scRNA-seq found that SERPINH1, ASPH, and SLC2A1 were mainly expressed in malignant cells of various cancer. Conclusions: An accurate risk model was constructed based on six ERS-related genes, which can be used for prognostic prediction and therapeutic strategy design in clinical practice.

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Signal peptidase 21 suppresses cell proliferation, migration, and invasion via the PTEN-PI3K/Akt signaling pathway in lung adenocarcinoma

Cited by 3 publications

References 10 publications

The ratio of interacting miRNAs’ expressions is a robust biomarker for disease classification in multi-center data

The ratio of interacting miRNAs’ expressions is a robust biomarker for disease classification in multi-center data

In search of the ratio of miRNA expression as robust biomarkers for constructing stable diagnostic models among multi-center data

The implication of endoplasmic reticulum stress-related genes in lung adenocarcinoma revealed by bioinformatics and single cell RNA sequencing analysis

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