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• W4308431156 abstract "Abstract Leucine rich repeat and fibronectin type III domain containing 4(LRFN4) has been reported to be upregulated in multiple tumors and related to prognosis and survival of patients. However, the function of LRFN4 in LUAD is still unclear. Herein, bioinformatic approach was used for the first time to elucidate the relationship between LRFN4 and LUAD. In LUAD tissues, we discovered that LRFN4 mRNA expression was considerably higher. Higher LRFN4 expression was associated with poorer prognosis and higher clinical stage of LUAD patients. Paraffin pathology sections (12 samples including LUAD tissues and paired normal tissues from the Second Affiliated Hospital of Chongqing Medical University) were used to verify the expression of LRFN4 at the protein level by immunohistochemical staining. On the other hand, we identified that LRFN4 expression was related to multiple immune cells that constitute tumor immune microenvironment. Pathway enrichment analysis also suggested the enrichment of several tumor- and immune-related pathways, such as: Hippo pathway, NOD-like pathway, TNF pathway and P53 pathway. Finally, we constructed an 8-gene prognostic risk signature based on 35 LRFN4-related immunomodulators using the Cox regression model, and obtained reasonably good accuracy through Receiver Operating Characteristic curve (ROC curve) validation. The risk signature was further identified as an independent risk factor – was linked with worse survival of LUAD patients. Furthermore, a prognostic risk profile based on LRFN4-related immunomodulators was constructed. Meanwhile, other clinical features were integrated together as prognostic markers to construct a nomogram to predict the long-term survival probability of LUAD patients, and fairly high credibility was obtained by validation of calibration curves." @default.
• W4308431156 created "2022-11-11" @default.
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• W4308431156 date "2022-11-07" @default.
• W4308431156 modified "2023-09-23" @default.
• W4308431156 title "Expression and relationship with immunity of LRFN4 in lung adenocarcinoma: Based on bioinformatics analysis" @default.
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• W4308431156 doi "https://doi.org/10.1101/2022.11.04.22281961" @default.
• W4308431156 hasPublicationYear "2022" @default.
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