Systematic identification of key extracellular proteins as the potential biomarkers in lupus nephritis

Zhou, Xue; Zhang, Yuefeng; Wang, Ning

doi:10.3389/fimmu.2022.915784

Cited by 12 publications

(12 citation statements)

References 48 publications

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“… 40 , 41 Similarly, through WGCNA, Chen et al identified the gene modules mostly correlated with gastric cancer and obtained the key genes in the regulatory network. 42 Therefore, to screen the module of entire immune gene cluster involved in the BRCA metastasis, we applied WGCNA to identify the turquoise module with 167 immune genes as the target one, which was associated with BRCA metastasis and used for further screening the MRIGs.…”

Section: Discussionmentioning

confidence: 99%

Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer

Ma,

Hao,

et al. 2024

BCTT

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Background Distant metastasis remains the leading cause of death among patients with breast cancer (BRCA). The process of cancer metastasis involves multiple mechanisms, including compromised immune system. However, not all genes involved in immune function have been comprehensively identified. Methods Firstly 1623 BRCA samples, including transcriptome sequencing and clinical information, were acquired from Gene Expression Omnibus (GSE102818, GSE45255, GSE86166) and The Cancer Genome Atlas-BRCA (TCGA-BRCA) dataset. Subsequently, weighted gene co-expression network analysis (WGCNA) was performed using the GSE102818 dataset to identify the most relevant module to the metastasis of BRCA. Besides, ConsensusClusterPlus was applied to divide TCGA-BRCA patients into two subgroups (G1 and G2). In the meantime, the least absolute shrinkage and selection operator (LASSO) regression analysis was used to construct a metastasis-related immune genes (MRIGs)_score to predict the metastasis and progression of cancer. Importantly, the expression of vital genes was validated through reverse transcription quantitative polymerase chain reaction (RT-qPCR) and immunohistochemistry (IHC). Results The expression pattern of 76 MRIGs screened by WGCNA divided TCGA-BRCA patients into two subgroups (G1 and G2), and the prognosis of G1 group was worse. Also, G1 exhibited a higher mRNA expression level based on stemness index score and Tumor Immune Dysfunction and Exclusion score. In addition, higher MRIGs_score represented the higher probability of progression in BRCA patients. It was worth mentioning that the patients in the G1 group had a high MRIGs_score than those in the G2 group. Importantly, the results of RT-qPCR and IHC demonstrated that fasciculation and elongation protein zeta 1 (FEZ1) and insulin-like growth factor 2 receptor (IGF2R) were risk factors, while interleukin (IL)-1 receptor antagonist (IL1RN) was a protective factor. Conclusion Our study revealed a prognostic model composed of eight immune related genes that could predict the metastasis and progression of BRCA. Higher score represented higher metastasis probability. Besides, the consistency of key genes in BRCA tissue and bioinformatics analysis results from mRNA and protein levels was verified.

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Section: Discussionmentioning

confidence: 99%

Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer

Ma,

Hao,

et al. 2024

BCTT

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“…TGFBI, a protein that is produced in response to transforming growth factor beta (TGF-β), has been shown to have significant implications in various kidney diseases ( 75 – 77 ). It can be detected in both serum and urine, making it accessible for diagnostic purposes ( 76 ). In our research, we observed an upregulation of TGFBI expression in LN, particularly in macrophages, cDCs, and pDCs, indicating its crucial role in these cell types.…”

Section: Discussionmentioning

confidence: 99%

Identification of driver genes in lupus nephritis based on comprehensive bioinformatics and machine learning

Wang,

Hu,

Pei

et al. 2023

Front. Immunol.

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BackgroundLupus nephritis (LN) is a common and severe glomerulonephritis that often occurs as an organ manifestation of systemic lupus erythematosus (SLE). However, the complex pathological mechanisms associated with LN have hindered the progress of targeted therapies.MethodsWe analyzed glomerular tissues from 133 patients with LN and 51 normal controls using data obtained from the GEO database. Differentially expressed genes (DEGs) were identified and subjected to enrichment analysis. Weighted gene co-expression network analysis (WGCNA) was utilized to identify key gene modules. The least absolute shrinkage and selection operator (LASSO) and random forest were used to identify hub genes. We also analyzed immune cell infiltration using CIBERSORT. Additionally, we investigated the relationships between hub genes and clinicopathological features, as well as examined the distribution and expression of hub genes in the kidney.ResultsA total of 270 DEGs were identified in LN. Using weighted gene co-expression network analysis (WGCNA), we clustered these DEGs into 14 modules. Among them, the turquoise module displayed a significant correlation with LN (cor=0.88, p<0.0001). Machine learning techniques identified four hub genes, namely CD53 (AUC=0.995), TGFBI (AUC=0.997), MS4A6A (AUC=0.994), and HERC6 (AUC=0.999), which are involved in inflammation response and immune activation. CIBERSORT analysis suggested that these hub genes may contribute to immune cell infiltration. Furthermore, these hub genes exhibited strong correlations with the classification, renal function, and proteinuria of LN. Interestingly, the highest hub gene expression score was observed in macrophages.ConclusionCD53, TGFBI, MS4A6A, and HERC6 have emerged as promising candidate driver genes for LN. These hub genes hold the potential to offer valuable insights into the molecular diagnosis and treatment of LN.

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“…TGFBI plays a key role in the activation of PI3K/AKT/mTOR/ HIF-1α signaling pathway in RCC Previous literature has reported a close relationship between POSTN and TGFBI [19][20][21][22], We analyzed the correlation between TGFBI and POSTN at RNA, total protein, and phosphoprotein levels and found a positive correlation between the expression of the two (Fig. 6A), whereas previous studies have been performed on POSTN indicating the importance of the AKT/mTOR pathway in RCC [23] .…”

Section: Tgfbi Knockdown Inhibits Expression Of Epithelial-mesenchyma...mentioning

confidence: 99%

TGFBI promotes proliferation and epithelial–mesenchymal transition in renal cell carcinoma through PI3K/AKT/mTOR/HIF-1α pathway

Zhan,

Bai,

Zhao

et al. 2023

Preprint

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Background Renal cell carcinoma (RCC) is presently recognized as the most prevalent kidney tumor. However, the role and underlying mechanism of action of the conversion factor-inducible protein (TGFBI), an extracellular matrix protein, in RCC remain poorly understood. Methods In this study, we employed Western blot, quantitative real-time polymerase chain reaction (qRT-PCR), and immunohistochemistry techniques to assess the expression of TGFBI in RCC tissues or cells. Furthermore, we analyzed the proliferation and migration of RCC cells using CCK8, cloning, scratching, and migration assays. Additionally, we examined apoptosis and cell cycle progression through flow cytometry, analysis. Lastly, we employed gene set enrichment analysis (GSEA) to investigate the biological processes associated with TGFBI, which were subsequently validated. Results The findings indicate that TGFBI exhibits significantly elevated expression levels in both renal cell carcinoma (RCC) tissues and cells. Furthermore, the knockdown of TGFBI in SiRNA transfected cells resulted in the inhibition of RCC cell proliferation, migration, invasiveness, apoptosis, and alteration of the cell cycle. Additionally, TGFBI was found to impede the epithelial-mesenchymal transition (EMT) process in RCC cells. Bioinformatics analysis suggests that TGFBI may exert its influence on various biological processes in RCC through the tumor immune microenvironment. Moreover, our study demonstrates that TGFBI promotes RCC progression by activating the PI3K/AKT/mTOR/HIF-1α Conclusions Our research indicates that TGFBI exhibits high expression in RCC and facilitate RCC progression and metastasis through various molecular mechanisms. Hence, TGFBI has the potential to be a novel therapeutic target for the diagnosis and treatment of RCC in the future.

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Systematic identification of key extracellular proteins as the potential biomarkers in lupus nephritis

Cited by 12 publications

References 48 publications

Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer

Identification and Validation of Novel Metastasis-Related Immune Gene Signature in Breast Cancer

Identification of driver genes in lupus nephritis based on comprehensive bioinformatics and machine learning

TGFBI promotes proliferation and epithelial–mesenchymal transition in renal cell carcinoma through PI3K/AKT/mTOR/HIF-1α pathway

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