Dataset Information

Whole Transcriptome Profiling Identifies CD93 and Other Plasma Cell Survival Factor Genes Associated with Measles-Specific Antibody Response after Vaccination.

ABSTRACT: There are insufficient system-wide transcriptomic (or other) data that help explain the observed inter-individual variability in antibody titers after measles vaccination in otherwise healthy individuals.We performed a transcriptome(mRNA-Seq)-profiling study after in vitro viral stimulation of PBMCs from 30 measles vaccine recipients, selected from a cohort of 764 schoolchildren, based on the highest and lowest antibody titers. We used regression and network biology modeling to define markers associated with neutralizing antibody response.We identified 39 differentially expressed genes that demonstrate significant differences between the high and low antibody responder groups (p-value?0.0002, q-value?0.092), including the top gene CD93 (p<1.0E-13, q<1.0E-09), encoding a receptor required for antigen-driven B-cell differentiation, maintenance of immunoglobulin production and preservation of plasma cells in the bone marrow. Network biology modeling highlighted plasma cell survival (CD93, IL6, CXCL12), chemokine/cytokine activity and cell-cell communication/adhesion/migration as biological processes associated with the observed differential response in the two responder groups.We identified genes and pathways that explain in part, and are associated with, neutralizing antibody titers after measles vaccination. This new knowledge could assist in the identification of biomarkers and predictive signatures of protective immunity that may be useful in the design of new vaccine candidates and in clinical studies.

SUBMITTER: Haralambieva IH

PROVIDER: S-EPMC4987012 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Whole Transcriptome Profiling Identifies CD93 and Other Plasma Cell Survival Factor Genes Associated with Measles-Specific Antibody Response after Vaccination.

Haralambieva Iana H IH Zimmermann Michael T MT Ovsyannikova Inna G IG Grill Diane E DE Oberg Ann L AL Kennedy Richard B RB Poland Gregory A GA

PloS one 20160816 8

<h4>Background</h4>There are insufficient system-wide transcriptomic (or other) data that help explain the observed inter-individual variability in antibody titers after measles vaccination in otherwise healthy individuals.<h4>Methods</h4>We performed a transcriptome(mRNA-Seq)-profiling study after in vitro viral stimulation of PBMCs from 30 measles vaccine recipients, selected from a cohort of 764 schoolchildren, based on the highest and lowest antibody titers. We used regression and network bi ...[more]

PMID: 27529750

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Project description:BackgroundDeveloping analytical methodologies to identify biomarkers in easily accessible body fluids is highly valuable for the early diagnosis and management of cancer patients. Peripheral whole blood is a "nucleic acid-rich" and "inflammatory cell-rich" information reservoir and represents systemic processes altered by the presence of cancer cells.Methodology/principal findingsWe conducted transcriptome profiling of whole blood cells from melanoma patients. To overcome challenges associated with blood-based transcriptome analysis, we used a PAXgene™ tube and NuGEN Ovation™ globin reduction system. The combined use of these systems in microarray resulted in the identification of 78 unique genes differentially expressed in the blood of melanoma patients. Of these, 68 genes were further analyzed by quantitative reverse transcriptase PCR using blood samples from 45 newly diagnosed melanoma patients (stage I to IV) and 50 healthy control individuals. Thirty-nine genes were verified to be differentially expressed in blood samples from melanoma patients. A stepwise logit analysis selected eighteen 2-gene signatures that distinguish melanoma from healthy controls. Of these, a 2-gene signature consisting of PLEK2 and C1QB led to the best result that correctly classified 93.3% melanoma patients and 90% healthy controls. Both genes were upregulated in blood samples of melanoma patients from all stages. Further analysis using blood fractionation showed that CD45(-) and CD45(+) populations were responsible for the altered expression levels of PLEK2 and C1QB, respectively.Conclusions/significanceThe current study provides the first analysis of whole blood-based transcriptome biomarkers for malignant melanoma. The expression of PLEK2, the strongest gene to classify melanoma patients, in CD45(-) subsets illustrates the importance of analyzing whole blood cells for biomarker studies. The study suggests that transcriptome profiling of blood cells could be used for both early detection of melanoma and monitoring of patients for residual disease.

Project description:BackgroundBiomarkers predicting the outcome of HIV-1 virus control in natural infection and after therapeutic interventions in HIV-1 cure trials remain poorly defined. The BCN02 trial (NCT02616874), combined a T-cell vaccine with romidepsin (RMD), a cancer-drug that was used to promote HIV-1 latency reversal and which has also been shown to have beneficial effects on neurofunction. We conducted longitudinal plasma proteomics analyses in trial participants to define biomarkers associated with virus control during monitored antiretroviral pause (MAP) and to identify novel therapeutic targets that can improve future cure strategies.MethodsBCN02 was a phase I, open-label, single-arm clinical trial in early-treated, HIV infected individuals. Longitudinal plasma proteomes were analyzed in 11 BCN02 participants, including 8 participants that showed a rapid HIV-1 plasma rebound during a monitored antiretroviral pause (MAP-NC, 'non-controllers') and 3 that remained off ART with sustained plasma viremia <2000 copies/ml (MAP-C, 'controllers'). Inflammatory and neurological proteomes in plasma were evaluated and integration data analysis (viral and neurocognitive parameters) was performed. Validation studies were conducted in a cohort of untreated HIV-1+ individuals (n = 96) and in vitro viral replication assays using an anti-CD33 antibody were used for functional validation.FindingsInflammatory plasma proteomes in BCN02 participants showed marked longitudinal alterations. Strong proteome differences were also observed between MAP-C and MAP-NC, including in baseline timepoints. CD33/Siglec-3 was the unique plasma marker with the ability to discriminate between MAPC-C and MAP-NC at all study timepoints and showed positive correlations with viral parameters. Analyses in an untreated cohort of PLWH confirmed the positive correlation between viral parameters and CD33 plasma levels, as well as PBMC gene expression. Finally, adding an anti-CD33 antibody to in vitro virus cultures significantly reduced HIV-1 replication and proviral levels in T cells and macrophages.InterpretationThis study indicates that CD33/Siglec-3 may serve as a predictor of HIV-1 control and as potential therapeutic tool to improve future cure strategies.FundingSpanish Science and Innovation Ministry (SAF2017-89726-R and PID2020-119710RB-I00), NIH (P01-AI131568), European Commission (GA101057548) and a Grifols research agreement.

Dataset Information

Whole Transcriptome Profiling Identifies CD93 and Other Plasma Cell Survival Factor Genes Associated with Measles-Specific Antibody Response after Vaccination.

Publications

Whole Transcriptome Profiling Identifies CD93 and Other Plasma Cell Survival Factor Genes Associated with Measles-Specific Antibody Response after Vaccination.

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