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Project description:BCN02 was an exploratory, single arm study designed to evaluate a kick-and-kill therapeutic vaccine strategy in early-treated HIV infected individuals. The participants in the study received a MVA.HIVconsv vaccination before and after three cycles of infusion of romidepsin (RMD), an inhibitor of histone deacetylases that acts as a viral latency reversing agent. The inclusion of a monitored antiretroviral pause (MAP) identified 8 individuals with an early viral rebound (pVL > 2,000 HIV RNA copies/mL, < 4 weeks of MAP initiation) and 4, with a late viral rebound (pVL > 2,000 HIV RNA copies/mL, > 4 weeks of MAP initiation). In the present study, a systems biology analysis was conducted to identify the pathways modulated at transcriptomic and epigenetic level during the clinical intervention, involving vaccination and RMD, and to identify biomarkers predictive of HIV viral rebound during MAP. To this end, we studied gene expression and whole-genome DNA methylation in longitudinal PBMC samples prior and after the intervention. The main impact on host transcriptional and epigenetic signatures was observed after vaccination and RMD infusion (Vacc+RMD) with multiple pathways related to HIV infection and immune response showing changes at gene expression and DNA methylation level. Analysis of an independent cohort of individuals treated with RMD alone, showed that these changes were mainly driven by CD4 T cells. DNA methylation patterns in full PBMC obtained after full intervention (Vacc+RMD) allowed to discriminate individuals with an Early versus Late viral rebound. These individuals also showed a differential enrichment on chromatin accessibility and transcription factor binding sites. Intriguingly, 30 of the DMPs between Early and Late rebounders at Vacc+RMD were present already at baseline and were more accentuated after RMD infusion. Overall, this study provides with a deeper understanding of the mechanisms modulated during the BCN02 study and highlights the importance of DNA methylation profiles in HIV cure.
2022-03-28 | GSE185389 | GEO
Project description:BCN02 was an exploratory, single arm study designed to evaluate a kick-and-kill therapeutic vaccine strategy in early-treated HIV infected individuals. The participants in the study received a MVA.HIVconsv vaccination before and after three cycles of infusion of romidepsin (RMD), an inhibitor of histone deacetylases that acts as a viral latency reversing agent. The inclusion of a monitored antiretroviral pause (MAP) identified 8 individuals with an early viral rebound (pVL > 2,000 HIV RNA copies/mL, < 4 weeks of MAP initiation) and 4, with a late viral rebound (pVL > 2,000 HIV RNA copies/mL, > 4 weeks of MAP initiation). In the present study, a systems biology analysis was conducted to identify the pathways modulated at transcriptomic and epigenetic level during the clinical intervention, involving vaccination and RMD, and to identify biomarkers predictive of HIV viral rebound during MAP. To this end, we studied gene expression and whole-genome DNA methylation in longitudinal PBMC samples prior and after the intervention. The main impact on host transcriptional and epigenetic signatures was observed after vaccination and RMD infusion (Vacc+RMD) with multiple pathways related to HIV infection and immune response showing changes at gene expression and DNA methylation level. Analysis of an independent cohort of individuals treated with RMD alone, showed that these changes were mainly driven by CD4 T cells. DNA methylation patterns in full PBMC obtained after full intervention (Vacc+RMD) allowed to discriminate individuals with an Early versus Late viral rebound. These individuals also showed a differential enrichment on chromatin accessibility and transcription factor binding sites. Intriguingly, 30 of the DMPs between Early and Late rebounders at Vacc+RMD were present already at baseline and were more accentuated after RMD infusion. Overall, this study provides with a deeper understanding of the mechanisms modulated during the BCN02 study and highlights the importance of DNA methylation profiles in HIV cure.
2022-03-28 | GSE185390 | GEO
Project description:Methylation profiles predict ATI outcome in the kick-and-kill therapeutic vaccine BCN02 clinical trial
| PRJNA769058 | ENA
Project description:Methylation profiles predict ATI outcome in the kick-and-kill therapeutic vaccine BCN02 clinical trial [450K]
| PRJNA769210 | ENA
Project description:Methylation profiles predict ATI outcome in the kick-and-kill therapeutic vaccine BCN02 clinical trial [EPIC array]
| PRJNA769211 | ENA
Project description:ObjectiveImmunotherapy targeting the programmed cell death protein-1 (PD-1)/programmed cell death protein ligand 1 (PD-L1) pathway has been observed to be efficient in several solid tumors. We aim to investigate the prognostic significance of PD-1/PD-L1 expression profile in intrahepatic cholangiocarcinoma (ICC).Materials and methodsWe investigated the expression of PD-1, PD-L1, CD8+ T cells, and CD68+ macrophages in paired tumor and adjacent normal tissues from 322 ICC patients using tyramide signal amplification (TSA)-based multiplexed immunohistochemistry.ResultsWe found that high proportion of tumor-infiltrating CD8+ PD-1High within CD8+ PD-1+ T cells significantly correlated with advanced TNM stage (P = 0.035). ICC patients with high proportion of CD8+ PD-1High in CD8+ PD-1+ had worse postoperative survival than low proportion patients (P = 0.0037), which was an independently prognostic factor for OS (P = 0.025,). The density of CD68+ PD-L1+ significantly and positively correlated with the density of CD8+ PD-1High (P < 0.0001, r = 0.5927). The proportion of CD68+ PD-L1+ within CD68+ ICC was the risk factor for OS and TTR but not an independently factor for prognosis. The CD68+ PD-L1+ macrophages and CD8+ PD-1High T cells may cooperatively play a role in inhibiting anti-tumor immunity.ConclusionCD68+ PD-L1+ macrophages and CD8+ PD-1High T cells predict unfavorable prognosis, which could also bring new progress about immune target therapy in ICC research.
| S-EPMC7686719 | biostudies-literature
Project description:BackgroundVaccine clinical studies typically provide time-resolved data on adaptive response read-outs in response to the administration of that particular vaccine to a cohort of individuals. However, modeling such data is challenged by the properties of these time-resolved profiles such as non-linearity, scarcity of measurement points, scheduling of the vaccine at multiple time points. Linear Mixed Models (LMM) are often used for the analysis of longitudinal data but their use in these time-resolved immunological data is not common yet. Apart from the modeling challenges mentioned earlier, selection of the optimal model by using information-criterion-based measures is far from being straight-forward. The aim of this study is to provide guidelines for the application and selection of LMMs that deal with the challenging characteristics of the typical data sets in the field of vaccine clinical studies.MethodsWe used antibody measurements in response to Hepatitis-B vaccine with five different adjuvant formulations for demonstration purposes. We built piecewise-linear, piecewise-quadratic and cubic models with transformations of the axes with pre-selected or optimized knot locations where time is a numerical variable. We also investigated models where time is categorical and random effects are shared intercepts between different measurement points. We compared all models by using Akaike Information Criterion (AIC), Bayesian Information Criterion (BIC), Deviance Information Criterion (DIC), variations of conditional AIC and by visual inspection of the model fit in the light of prior biological information.ResultsThere are various ways of dealing with the challenges of the data which have their own advantages and disadvantages. We explain these in detail here. Traditional information-criteria-based measures work well for the coarse selection of the model structure and complexity, however are not efficient at fine tuning of the complexity level of the random effects.ConclusionsWe show that common statistical measures for optimal model complexity are not sufficient. Rather, explicitly accounting for model purpose and biological interpretation is needed to arrive at relevant models.Trial registrationClinical trial registration number for this study: NCT00805389, date of registration: December 9, 2008 (pro-active registration).
| S-EPMC7364493 | biostudies-literature
Project description:The BCN02 (NCT02616874) was a pilot study to evaluate the kick and kill therapy on 15 early-treated individuals that were rolled-over from the BCN01 Study. The participants in the study received two MVA.HIVconsv vaccination before and after the 3-cycle infusion of Romidepsin, an inhibitor of histone deacetylases that act as a latency reversing agent. Additionally, the inclusion of a monitored antiretroviral pause (MAP) allowed tthe identification of 8 individuals with an Early Rebound (pVL > 2,000 HIV RNA copies/mL, < 4 weeks of MAP initiation) and 4, with a Late Rebound (pVL > 2,000 HIV RNA copies/mL, > 4 weeks of MAP initiation). In the present study we studied gene expression at 3 different timepoints: w0 (Bsl), w1 (Vacc), w6 (Vacc+RMD) and applied pairwise comparisons.
2022-03-28 | GSE184653 | GEO
Project description:Cytosine derivative dysregulations represent important epigenetic modifications whose impact on the clinical outcome in chronic lymphocytic leukemia (CLL) is incompletely understood. Hence, global levels of 5-methylcytosine (5-mCyt), 5-hydroxymethylcytosine (5-hmCyt), 5-carboxylcytosine (5-CaCyt) and 5-hydroxymethyluracil were tested in purified B cells from CLL patients (n = 55) and controls (n = 17). The DNA methylation 'writers' (DNA methyltransferases [DNMT1/3A/3B]), 'readers' (methyl-CpG-binding domain [MBD2/4]), 'editors' (ten-eleven translocation [TET1/2/3]) and 'modulators' (SAT1) were also evaluated. Accordingly, patients were stratified into three subgroups. First, a subgroup with a global deficit in cytosine derivatives characterized by hyperlymphocytosis, reduced median progression free survival (PFS = 52 months) and shorter treatment free survival (TFS = 112 months) was identified. In this subgroup, major epigenetic modifications were highlighted including a reduction of 5-mCyt, 5-hmCyt, 5-CaCyt associated with DNMT3A, MBD2/4 and TET1/2 downregulation. Second, the cytosine derivative analysis revealed a subgroup with a partial deficit (PFS = 84, TFS = 120 months), mainly affecting DNA demethylation (5-hmCyt reduction, SAT1 induction). Third, a subgroup epigenetically similar to controls was identified (PFS and TFS > 120 months). The prognostic impact of stratifying CLL patients within three epigenetic subgroups was confirmed in a validation cohort. In conclusion, our results suggest that dysregulations of cytosine derivative regulators represent major events acquired during CLL progression and are independent from IGHV mutational status.
| S-EPMC5630365 | biostudies-literature
Project description:BACKGROUND: Changes in DNA methylation of crucial cancer genes including tumor suppressors can occur early in carcinogenesis, being potentially important early indicators of cancer. The objective of this study was to examine a multiplexed approach to assess the methylation of tumor suppressor genes as tumor stratification and clinical outcome prognostic biomarkers for lung cancer. METHODS: A multicandidate probe panel interrogated DNA for aberrant methylation status in 18 tumor suppressor genes in lung cancer using a methylation-specific multiplex ligation-dependent probe amplification assay (MS-MLPA). Lung cancer cell lines (n = 7), and primary lung tumors (n = 54) were examined using MS-MLPA. RESULTS: Genes frequently methylated in lung cancer cell lines including SCGB3A1, ID4, CCND2 were found among the most commonly methylated in the lung tumors analyzed. HLTF, BNIP3, H2AFX, CACNA1G, TGIF, ID4 and CACNA1A were identified as novel tumor suppressor candidates methylated in lung tumors. The most frequently methylated genes in lung tumors were SCGB3A1 and DLC1 (both 50.0%). Methylation rates for ID4, DCL1, BNIP3, H2AFX, CACNA1G and TIMP3 were significantly different between squamous and adenocarcinomas. Methylation of RUNX3, SCGB3A1, SFRP4, and DLC1 was significantly associated with the extent of the disease when comparing localized versus metastatic tumors. Moreover, methylation of HTLF, SFRP5 and TIMP3 were significantly associated with overall survival. CONCLUSIONS: MS-MLPA can be used for classification of certain types of lung tumors and clinical outcome prediction. This latter is clinically relevant by offering an adjunct strategy for the clinical management of lung cancer patients.
| S-EPMC2955578 | biostudies-literature