166 research outputs found

    Immunobiology of Monocytes/Macrophages in Hepatocellular Carcinoma

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    Aberrant Methylation of Thrombospondin-1 and Its Association with Reduced Expression in Gastric Cardia Adenocarcinoma

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    Aim. Investigate the promoter methylation of the Thrombospondin-1 (TSP1) gene in gastric cardia adenocarcinoma (GCA). Methods. MSP approach, immunohistochemistry method, and RT-PCR were used respectively to examine the promoter methylation of TSP1, its protein and mRNA expression in tumors and corresponding normal tissues. The expression and concentration of TGF-β1 were examined respectively by immunohistochemistry and ELISA method. The status of T cell immunity was examined by Flow cytometry analysis. Results. TSP1 was methylated in 34/96 (35.4%) tumor specimens, which was significantly higher than that in corresponding normal tissues (P < .001). Protein and mRNA expression of TSP1 in GCA tumor tissues were reduced significantly and were associated with TSP1 methylation. The protein expression of TGF-β1 was significantly higher in tumor tissues (P < .001) and was associated with TNM stage and histological differentiation. The concentration of active and total TGF-β1 did not show significant difference between the GCA patients with hypermethylation of TSP1 and without methylation of TSP1 (P > .05). The function of T cell immunity was significantly different between the GCA patients with hypermethylation of TSP1 and without methylation of TSP1. Conclusions. Epigenetic silencing of TSP1 gene by promoter hypermethylation may play an important role in GCA

    The `excess' of primary cosmic ray electrons

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    With the accurate cosmic ray (CR) electron and positron spectra (denoted as Φe\Phi_{\rm e^{-}} and Φe+\Phi_{\rm e^{+}}, respectively) measured by AMS-02 collaboration, the difference between the electron and positron fluxes (i.e., ΔΦ=ΦeΦe+\Delta \Phi=\Phi_{\rm e^{-}}-\Phi_{\rm e^{+}}), dominated by the propagated primary electrons, can be reliably inferred. In the standard model, the spectrum of propagated primary CR electrons at energies 30\geq 30 GeV softens with the increase of energy. The absence of any evidence for such a continuous spectral softening in ΔΦ\Delta \Phi strongly suggests a significant `excess' of primary CR electrons and at energies of 100400100-400 GeV the identified excess component has a flux comparable to that of the observed positron excess. Middle-age but `nearby' supernova remnants (e.g., Monogem and Geminga) are favored sources for such an excess.Comment: 13 pages, 2 figures, Phys. Lett. B, in pres

    Activated monocytes in peritumoral stroma of hepatocellular carcinoma foster immune privilege and disease progression through PD-L1

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    Macrophages (Mφ) are prominent components of solid tumors and exhibit distinct phenotypes in different microenvironments. We have recently found that tumors can alter the normal developmental process of Mφ to trigger transient activation of monocytes in peritumoral stroma. We showed that a fraction of monocytes/Mφ in peritumoral stroma, but not in cancer nests, expresses surface PD-L1 (also termed B7-H1) molecules in tumors from patients with hepatocellular carcinoma (HCC). Monocytes activated by tumors strongly express PD-L1 proteins with kinetics similar to their activation status, and significant correlations were found between the levels of PD-L1+ and HLA-DRhigh on tumor-infiltrating monocytes. Autocrine tumor necrosis factor α and interleukin 10 released from activated monocytes stimulated monocyte expression of PD-L1. The PD-L1+ monocytes effectively suppressed tumor-specific T cell immunity and contributed to the growth of human tumors in vivo; the effect could be reversed by blocking PD-L1 on those monocytes. Moreover, we found that PD-L1 expression on tumor-infiltrating monocytes increased with disease progression, and the intensity of the protein was associated with high mortality and reduced survival in the HCC patients. Thus, expression of PD-L1 on activated monocytes/Mφ may represent a novel mechanism that links the proinflammatory response to immune tolerance in the tumor milieu

    Differential early diagnosis of benign versus malignant lung cancer using systematic pathway flux analysis of peripheral blood leukocytes

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    Early diagnosis of lung cancer is critically important to reduce disease severity and improve overall survival. Newer, minimally invasive biopsy procedures often fail to provide adequate specimens for accurate tumor subtyping or staging which is necessary to inform appropriate use of molecular targeted therapies and immune checkpoint inhibitors. Thus newer approaches to diagnosis and staging in early lung cancer are needed. This exploratory pilot study obtained peripheral blood samples from 139 individuals with clinically evident pulmonary nodules (benign and malignant), as well as ten healthy persons. They were divided into three cohorts: original cohort (n = 99), control cohort (n = 10), and validation cohort (n = 40). Average RNAseq sequencing of leukocytes in these samples were conducted. Subsequently, data was integrated into artificial intelligence (AI)-based computational approach with system-wide gene expression technology to develop a rapid, effective, non-invasive immune index for early diagnosis of lung cancer. An immune-related index system, IM-Index, was defined and validated for the diagnostic application. IM-Index was applied to assess the malignancies of pulmonary nodules of 109 participants (original + control cohorts) with high accuracy (AUC: 0.822 [95% CI: 0.75–0.91, p < 0.001]), and to differentiate between phases of cancer immunoediting concept (odds ratio: 1.17 [95% CI: 1.1–1.25, p < 0.001]). The predictive ability of IM-Index was validated in a validation cohort with a AUC: 0.883 (95% CI: 0.73–1.00, p < 0.001). The difference between molecular mechanisms of adenocarcinoma and squamous carcinoma histology was also determined via the IM-Index (OR: 1.2 [95% CI 1.14–1.35, p = 0.019]). In addition, a structural metabolic behavior pattern and signaling property in host immunity were found (bonferroni correction, p = 1.32e − 16). Taken together our findings indicate that this AI-based approach may be used for “Super Early” cancer diagnosis and amend the current immunotherpay for lung cancer
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