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BACKGROUND: To explore the serum tumor necrosis factor-alpha stimulated gene-6 (TSG-6) level and its association with disease activity in rheumatoid arthritis (RA) patients. METHODS: We recruited 176 RA patients, 178 non-RA patients (lupus erythematosus, osteoarthritis, ulcerative colitis, ankylosing spondylitis and psoriasis) and 71 healthy subjects. Serum TSG-6 levels were detected by enzyme-linked immunosorbent assay (ELISA). RA patients were divided into inactive RA and active RA groups by disease activity score of 28 joints based on C-reactive protein (DAS28-CRP). The receiver operating characteristic (ROC) curve and Spearman's rank correlation test analyzed the correlation between TSG-6 concentration and RA disease activity. RESULTS: Tumor necrosis factor-alpha stimulated gene-6 levels in the RA group were increased (p < 0.01). TSG-6 concentrations indicated an upward tendency with increased disease activity; The area under the curve (AUC) of TSG-6 for diagnosing RA and assessing the severity of RA were 0.78 and 0.80, respectively; The combination of TSG-6 and anti-mutated citrullinated vimentin antibodies (anti-MCV) (sensitivity:98.4%)improved the diagnostic accuracy of RA. Binary logistic regression analysis showed that TSG-6 was an independent risk factor related to the severity of RA, and OR (95% CI) was 1.2 (1.003-1.453). CONCLUSION: The TSG-6 levels in RA patients were elevated and related to disease activity. Therefore, TSG-6 may serve as a new potential biomarker for evaluating RA disease activity.
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Artritis Reumatoide , Moléculas de Adhesión Celular , Artritis Reumatoide/diagnóstico , Artritis Reumatoide/genética , Autoanticuerpos , Biomarcadores , Moléculas de Adhesión Celular/genética , Ensayo de Inmunoadsorción Enzimática , HumanosRESUMEN
Small cell lung cancer (SCLC), a highly aggressive malignancy, is rapidly at an extensive stage once diagnosed and is one of the leading causes of death from malignancy. In the past decade, the treatment of SCLC has largely remained unchanged, and chemotherapy remains the cornerstone of SCLC treatment. The therapeutic value of adding immune checkpoint inhibitors to chemotherapy for SCLC is low, and only a few SCLC patients have shown a response to immune checkpoint inhibitors. Circulating tumor cells (CTCs) are tumor cells shed from solid tumor masses into the peripheral circulation and are key to tumor metastasis. Single-cell sequencing has revealed that the genetic profiles of individual CTCs are highly heterogeneous and contribute to the poor outcome and prognosis of SCLC patients. Theoretically, phenotypic analysis of CTCs may be able to predict the diagnostic significance of new potential targets for metastatic tumors. In this paper, we will discuss in depth the heterogeneity of CTCs in SCLC and the value of CTCs for the diagnosis and prognosis of SCLC and as relevant tumor markers in metastatic SCLC.
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OBJECTIVES: To identify potential diagnostic markers for small cell lung cancer (SCLC) and investigate the correlation with immune cell infiltration. METHODS: GSE149507 and GSE6044 were used as the training group, while GSE108055 served as validation group A and GSE73160 served as validation group B. Differentially expressed genes (DEGs) were identified and analyzed for functional enrichment. Machine learning (ML) was used to identify candidate diagnostic genes for SCLC. The area under the receiver operating characteristic curves was applied to assess diagnostic efficacy. Immune cell infiltration analyses were carried out. RESULTS: There were 181 DEGs identified. The gene ontology analysis showed that DEGs were enriched in 455 functional annotations, some of which were associated with immunity. The kyoto encyclopedia of genes and genomes analysis revealed that there were 9 signaling pathways enriched. The disease ontology analysis indicated that DEGs were related to 116 diseases. The gene set enrichment analysis results displayed multiple items closely related to immunity. ZWINT and NRCAM were screened using ML and further validated as diagnostic genes. Significant differences were observed in SCLC with normal lung tissue samples among immune cell infiltration characteristics. Strong associations were found between the diagnostic genes and immune cell infiltration. CONCLUSION: This study identified 2 diagnostic genes, ZWINT and NRCAM, that were related to immune cell infiltration by integrating bioinformatics analysis and ML algorithms. These genes could serve as potential diagnostic biomarkers and provide possible molecular targets for immunotherapy in SCLC.
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Biología Computacional , Neoplasias Pulmonares , Aprendizaje Automático , Carcinoma Pulmonar de Células Pequeñas , Humanos , Neoplasias Pulmonares/genética , Neoplasias Pulmonares/inmunología , Neoplasias Pulmonares/patología , Carcinoma Pulmonar de Células Pequeñas/genética , Carcinoma Pulmonar de Células Pequeñas/inmunología , Carcinoma Pulmonar de Células Pequeñas/patología , Biomarcadores de Tumor/genética , Algoritmos , Perfilación de la Expresión Génica , Ontología de GenesRESUMEN
To detect the value of serum interleukin-17 (IL-17), tumour necrosis factor-α (TNF-α), and Dickkopf-1 (DKK-1) in rheumatoid arthritis (RA) at different disease stages. 141 RA patients were randomly obtained and diagnosed in a large tertiary first-class hospital in Jiangxi Province from November 2021 to January 2022. RA was divided into 38 low activity and remission phase (low remission patients), 72 moderate activity patients, 41 high activity patients, according to the disease activity score 28 (DAS28) of RA and 70 healthy controls. IL-17 and TNF-α in serum detected by flow cytometry; DKK-1by ELISA; rheumatoid factor (RF) and C-reactive protein (CRP) by rate scattering turbidimetry; erythrocyte sedimentation rate (ESR) by Widmanstat method; anti-cyclic citrullinated polypeptide antibody (Anti-CCP) by chemiluminescence. The changes among the groups were statistically analysed and evaluated their diagnostic value. â Anti-CCP, CRP, and ESR levels in the moderate-to-high activity group were higher than controls, while IL-17, TNF-α, and DKK-1levels higher than low remission group, moderate activity group and controls (p < 0.05). â¡IL-17, TNF-α and DKK-1 were positively correlated with RA disease activity, with the correlations of IL-17, TNF-α and DKK-1 all over 0.5 (p < 0.05). â¢The ROC curve showed that among all indices the AUC of DKK-1 was the largest, 0. 922, and has the highest sensitivity and negative predictive value for RA, 0.965 and 0.953, respectively. The specificity and positive predictive value of TNF-α is highest, 0.918 and 0.921, respectively, combined them had the highest predictive value in moderate-to-high activity RA, with AUC of 0.968, and had the highest sensitivity of 0.965. The IL-17, TNF-α and DKK-1 levels were elevated in RA and positively correlated with disease activity, involved in the Wnt signalling pathway of inflammatory and joint destructive effects, combining them to monitor the RA disease process and biologically treat the cytokines in the pathogenesis of RA were valuable.
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Artritis Reumatoide , Factor de Necrosis Tumoral alfa , Humanos , Artritis Reumatoide/metabolismo , Proteína C-Reactiva/metabolismo , Citocinas , Interleucina-17 , Factor ReumatoideRESUMEN
Background: Lung cancer (LC) is the leading cause of cancer-related deaths worldwide. Tumor marker (TM) detection can indicate the existence and growth of a tumor and has therefore been used extensively for diagnosing LC. Here, we conducted a bibliometric analysis to examine TM-related publications for LC diagnosis to illustrate the current state and future trends of this field, as well as to identify additional promising TMs with high sensitivity. Methods: Publications regarding TMs in LC diagnosis were downloaded from the Web of Science Core Collection. CiteSpace was applied to perform a bibliometric analysis of journals, cocitation authors, keywords, and references related to this field. VOSviewer was used to generate concise diagrams about countries, institutions, authors, and keywords. Changes in the TM research frontier were analyzed through citation burst detection. Results: A total of 990 studies were analyzed in this work. The collaboration network analysis revealed that the People's Republic of China, Yonsei University, and Molina R were the most productive country, institution, and scholar, respectively. Additionally, Molina R was the author with the most citations. The National Natural Science Foundation of China was the largest funding source. "Carcinoembryonic antigen (CEA) as tumor marker in lung cancer" was the top reference with the most citations, Lung Cancer was the core journal, and "serum tumor marker" experienced a citation burst over the past 5 years. Conclusion: This bibliometric analysis of TMs in LC diagnosis presents the current trends and frontiers in this field. We summarized the research status of this field and the methods to improve the diagnostic efficacy of traditional serum TMs, as well as provided new directions and ideas for improving the LC clinical detection rate. Priority should be given to the transformation of computer-assisted diagnostic technology for clinical applications. In addition, circulating tumor cells, exosomes, and microRNAs were the current most cutting-edge TMs.