RESUMEN
Decoy receptor 3 (DcR3), a novel soluble protein belonging to the tumor necrosis factor receptor (TNFR) family, has been previously associated with tumorigenesis in various cancers. However, in our study, we unexpectedly found that DcR3 may promote patient survival time in colorectal cancer (CRC). Through an analysis of The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) datasets, we discovered that high levels of DcR3 are associated with improved overall survival (OS) and disease-free survival (DFS) in CRC patients. Further investigation revealed that DcR3 is correlated with favorable clinical features in Metastasis 0 (M0) and stage I/II CRC patients, suggesting it may act as a suppressive factor in CRC. Gene Set Enrichment Analysis (GSEA) demonstrated that the high DcR3 group is enriched in the IL-17 signaling pathway and other immune-related pathways, and Single Sample Gene Set Enrichment Analysis (ssGSEA) revealed a higher abundance of Tumor Infiltrating Lymphocytes (TIL) in the DcR3 high group. To better understand the function of DcR3, we constructed a DcR3-associated riskscore (DARS) model using machine learning, comprising three genes (DPP7, KDM3A, and TMEM86B). The DARS model indicated that high riskscore patients have an unfavorable prognosis, and it is associated with advanced stages (III/IV), T3/4 tumors, and N1/2 lymph node involvement. Additionally, high riskscore group exhibited more frequent gene mutations, such as TTN, MUC16, and SYNE1, with SYNE1 mutation being related to poor prognosis. Intriguingly, DcR3 showed higher expression in the low riskscore group. These results suggest that DcR3 could serve as a potential prognostic biomarker in CRC and may play a crucial role in favorably modulating the immune response in this malignancy.
RESUMEN
Backgrounds: Extracellular matrix (ECM) is an important component of tumor microenvironment, and its abnormal expression promotes tumor formation, progression and metastasis. Methods: Weighted gene co-expression network analysis (WGCNA) was used to identify ECM-related hub genes based on The Cancer Genome Atlas (TCGA) colon adenocarcinoma (COAD) data. COAD clinical samples were used to verify the expression of potential biomarkers in tumor tissues, and siRNA was used to explore the role of potential biomarkers in cell proliferation and epithelial-mesenchymal transition (EMT). Results: Three potential biomarkers (LEP, NGF and PCOLCE2) related to prognosis of COAD patients were identified and used to construct ERGPI. Immunohistochemical analysis of clinical samples showed that the three potential biomarkers were highly expressed in tumor tissues of COAD patients. Knockdown of LEP, NGF or PCOLCE2 inhibited COAD cell proliferation and EMT. Dictamnine inhibited tumor cell growth by binding to these three potential biomarkers based on molecular docking and transplanted tumor model. Conclusion: The three biomarkers can provide new ideas for the diagnosis and targeted therapy of COAD patients.
Asunto(s)
Adenocarcinoma , Biomarcadores de Tumor , Neoplasias del Colon , Biología Computacional , Transición Epitelial-Mesenquimal , Matriz Extracelular , Humanos , Biomarcadores de Tumor/genética , Biomarcadores de Tumor/metabolismo , Neoplasias del Colon/genética , Neoplasias del Colon/patología , Neoplasias del Colon/diagnóstico , Neoplasias del Colon/metabolismo , Adenocarcinoma/genética , Adenocarcinoma/diagnóstico , Adenocarcinoma/metabolismo , Adenocarcinoma/patología , Biología Computacional/métodos , Matriz Extracelular/metabolismo , Animales , Transición Epitelial-Mesenquimal/genética , Ratones , Proliferación Celular/genética , Línea Celular Tumoral , Regulación Neoplásica de la Expresión Génica , Pronóstico , Microambiente Tumoral , Simulación del Acoplamiento Molecular , Perfilación de la Expresión Génica , Masculino , Redes Reguladoras de GenesRESUMEN
The orthopedics implants failure management system has been put forward according to the present status. The function of the system and typical failure case reasoning route also have been described. Furthermore, the analysis process has been presented by illustrating a typical failure case analysis.