Background Checkpoint-blockade immunotherapy targeting programmed cell death protein 1 (PD-1) has recently shown promising efficacy in hepatocellular carcinoma (HCC). However, the factors affecting and predicting the response to anti-PD-1 immunotherapy in HCC are still unclear. Herein, we report the dynamic variation characteristics and specificities of the gut microbiome during anti-PD-1 immunotherapy in HCC using metagenomic sequencing. Results Fecal samples from patients responding to immunotherapy showed higher taxa richness and more gene counts than those of non-responders. For dynamic analysis during anti-PD-1 immunotherapy, the dissimilarity of beta diversity became prominent across patients as early as Week 6. In non-responders, Proteobacteria increased from Week 3, and became predominant at Week 12. Twenty responder-enriched species, including Akkermansia muciniphila and Ruminococcaceae spp., were further identified. The related functional genes and metabolic pathway analysis, such as carbohydrate metabolism and methanogenesis, verified the potential bioactivities of responder-enriched species. Conclusions Gut microbiome may have a critical impact on the responses of HCC patients treated with anti-PD-1 immunotherapy. The dynamic variation characteristics of the gut microbiome may provide early predictions of the outcomes of immunotherapy in HCC, which is critical for disease-monitoring and treatment decision-making. Electronic supplementary material The online version of this article (10.1186/s40425-019-0650-9) contains supplementary material, which is available to authorized users.
The latent pattern of EBV in gastric carcinoma corresponds to the latency I/II. Some lytic infection genes are expressed in EBVaGCs tissues. BARF1 and BHRF1 genes may play an important role in tumorigenesis of gastric carcinoma.
Malignant gliomas (glioblastoma multiforme) have a poor prognosis with an average patient survival under current treatment regimens ranging between 12 and 14 months. The tumors are characterized by rapid cell growth, extensive neovascularization, and diffuse cellular infiltration of normal brain structures. We have developed a human glioblastoma xenograft model in nude rats that is characterized by a highly infiltrative non-angiogenic phenotype. Upon serial transplantation this phenotype will develop into a highly angiogenic tumor. Thus, we have developed an animal model where we are able to establish two characteristic tumor phenotypes that define human glioblastoma (i.e. diffuse infiltration and high neovascularization). Here we aimed at identifying potential biomarkers expressed by the non-angiogenic and the angiogenic phenotypes and elucidating the molecular pathways involved in the switch from invasive to angiogenic growth. Focusing on membrane-associated proteins, we profiled protein expression during the progression from an invasive to an angiogenic phenotype by analyzing serially transplanted glioma xenografts in rats. Applying isobaric peptide tagging chemistry (iTRAQ) combined with two-dimensional LC and MALDI-TOF/TOF mass spectrometry, we were able to identify several thousand proteins in membrane-enriched fractions of which 1460 were extracted as quantifiable proteins (isoform- and species-specific and present in more than one sample). Known and novel candidate proteins were identified that characterize the switch from a non-angiogenic to a highly angiogenic phenotype. The robustness of the data was corroborated by extensive bioinformatics analysis and by validation of selected proteins on tissue microarrays from xenograft and clinical gliomas. The data point to enhanced intercellular cross-talk and metabolic activity adopted by tumor cells in the angiogenic compared with the non-angiogenic phenotype. In conclusion, we describe molecular profiles that reflect the change from an invasive to an angiogenic brain tumor phenotype. The identified proteins could be further exploited as biomarkers or therapeutic targets for malignant gliomas.
Background In clinical practice, the detection of biomarkers is mostly based on primary tumors for its convenience in acquisition. However, immune checkpoints may express differently between primary and metastatic tumor. Therefore, we aimed to compare the differential expressions of PD-1, PD-L1 and PD-L2 between the primary and metastatic sites of renal cell carcinoma (RCC). Methods Patients diagnosed with RCC by resection or fine needle aspiration of metastasis were included. Immunohistochemistry (IHC) was applied to detect PD-1, PD-L1 and PD-L2 expressions. SPSS 22.0 was applied to conduct Chi-square, consistency tests and Cox’s proportional hazards regression models. GraphPad Prism 6 was used to plot survival curves and R software was used to calculate Predictive accuracy (PA). Results In the whole cohort ( N = 163), IHC results suggested a higher detection rate of PD-L1 in the metastasis than that of the primary site (χ2 = 4.66, p = 0.03), with a low consistent rate of 32.5%. Among different metastatic tumors, PD-1 was highly expressed in the lung/lymph node (65.3%) and poorly expressed in the brain (10.5%) and visceral metastases (12.5%). PD-L1 was highly expressed in lung/lymph node (37.5%) and the bone metastases (12.2%) on the contrary. In terms of survival analysis, patients with PD-1 expression either in the primary or metastasis had a shorter overall survival (OS) (HR: 1.59, 95% CI 1.08–2.36, p = 0.02). Also, PD-L1 expression in the primary was associated with a shorter OS (HR 2.55, 95% CI 1.06–6.15, p = 0.04). In the multivariate analysis, the predictive accuracy of the whole model for PFS was increased from 0.683 to 0.699 after adding PD-1. Conclusion PD-1, PD-L1 and PD-L2 were differentially expressed between primary and metastatic tumors. Histopathological examination of these immune check points in metastatic lesions of mRCC should be noticed, and its accurate diagnosis may be one of the effective ways to realize the individualized treatment. Electronic supplementary material The online version of this article (10.1186/s12885-019-5578-4) contains supplementary material, which is available to authorized users.
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