Origin and differentiation of human memory CD8 T cells after vaccination.

The differentiation of human memory CD8 T cells is not well understood. Here we address this issue using the live yellow fever virus (YFV) vaccine, which induces long-term immunity in humans. We used in vivo deuterium labelling to mark CD8 T cells that proliferated in response to the virus and then assessed cellular turnover and longevity by quantifying deuterium dilution kinetics in YFV-specific CD8 T cells using mass spectrometry. This longitudinal analysis showed that the memory pool originates from CD8 T cells that divided extensively during the first two weeks after infection and is maintained by quiescent cells that divide less than once every year (doubling time of over 450 days). Although these long-lived YFV-specific memory CD8 T cells did not express effector molecules, their epigenetic landscape resembled that of effector CD8 T cells. This open chromatin profile at effector genes was maintained in memory CD8 T cells isolated even a decade after vaccination, indicating that these cells retain an epigenetic fingerprint of their effector history and remain poised to respond rapidly upon re-exposure to the pathogen.

Next-generation sequencing of human mitochondrial reference genomes uncovers high heteroplasmy frequency.

We describe methods for rapid sequencing of the entire human mitochondrial genome (mtgenome), which involve long-range PCR for specific amplification of the mtgenome, pyrosequencing, quantitative mapping of sequence reads to identify sequence variants and heteroplasmy, as well as de novo sequence assembly. These methods have been used to study 40 publicly available HapMap samples of European (CEU) and African (YRI) ancestry to demonstrate a sequencing error rate <5.63×10(-4), nucleotide diversity of 1.6×10(-3) for CEU and 3.7×10(-3) for YRI, patterns of sequence variation consistent with earlier studies, but a higher rate of heteroplasmy varying between 10% and 50%. These results demonstrate that next-generation sequencing technologies allow interrogation of the mitochondrial genome in greater depth than previously possible which may be of value in biology and medicine.

Phenotype, function, and gene expression profiles of programmed death-1(hi) CD8 T cells in healthy human adults.

T cell dysfunction is an important feature of many chronic viral infections. In particular, it was shown that programmed death-1 (PD-1) regulates T cell dysfunction during chronic lymphocytic choriomeningitis virus infection in mice, and PD-1(hi) cells exhibit an intense exhausted gene signature. These findings were extended to human chronic infections such as HIV, hepatitis C virus, and hepatitis B virus. However, it is not known if PD-1(hi) cells of healthy humans have the traits of exhausted cells. In this study, we provide a comprehensive description of phenotype, function, and gene expression profiles of PD-1(hi) versus PD-1(lo) CD8 T cells in the peripheral blood of healthy human adults as follows: 1) the percentage of naive and memory CD8 T cells varied widely in the peripheral blood cells of healthy humans, and PD-1 was expressed by the memory CD8 T cells; 2) PD-1(hi) CD8 T cells in healthy humans did not significantly correlate with the PD-1(hi) exhausted gene signature of HIV-specific human CD8 T cells or chronic lymphocytic choriomeningitis virus-specific CD8 T cells from mice; 3) PD-1 expression did not directly affect the ability of CD8 T cells to secrete cytokines in healthy adults; 4) PD-1 was expressed by the effector memory compared with terminally differentiated effector CD8 T cells; and 5) finally, an interesting inverse relationship between CD45RA and PD-1 expression was observed. In conclusion, our study shows that most PD-1(hi) CD8 T cells in healthy adult humans are effector memory cells rather than exhausted cells.

Sample preparation method considerations for integrated transcriptomic and proteomic analysis of tumors.

Sample processing protocols that enable compatible recovery of differentially expressed transcripts and proteins are necessary for integration of the multiomics data applied in the analysis of tumors. In this pilot study, we compared two different isolation methods for extracting RNA and protein from laryngopharyngeal tumor tissues and the corresponding adjacent normal sections. In Method 1, RNA and protein were isolated from a single tissue section sequentially and in Method 2, the extraction was carried out using two different sections and two independent and parallel protocols for RNA and protein. RNA and protein from both methods were subjected to RNA-seq and iTRAQ-based LC-MS/MS analysis, respectively. Analysis of data revealed that a higher number of differentially expressed transcripts and proteins were concordant in their regulation trends in Method 1 as compared to Method 2. Cross-method comparison of concordant entities revealed that RNA and protein extraction from the same tissue section (Method 1) recovered more concordant entities that are missed in the other extraction method (Method 2) indicating heterogeneity in distribution of these entities in different tissue sections. Method 1 could thus be the method of choice for integrated analysis of transcriptome and proteome data.

Meta-Analyses of Microarray Datasets Identifies ANO1 and FADD as Prognostic Markers of Head and Neck Cancer.

The head and neck squamous cell carcinoma (HNSCC) transcriptome has been profiled extensively, nevertheless, identifying biomarkers that are clinically relevant and thereby with translational benefit, has been a major challenge. The objective of this study was to use a meta-analysis based approach to catalog candidate biomarkers with high potential for clinical application in HNSCC. Data from publically available microarray series (N = 20) profiled using Agilent (4X44K G4112F) and Affymetrix (HGU133A, U133A_2, U133Plus 2) platforms was downloaded and analyzed in a platform/chip-specific manner (GeneSpring software v12.5, Agilent, USA). Principal Component Analysis (PCA) and clustering analysis was carried out iteratively for segregating outliers; 140 normal and 277 tumor samples from 15 series were included in the final analysis. The analyses identified 181 differentially expressed, concordant and statistically significant genes; STRING analysis revealed interactions between 122 of them, with two major gene clusters connected by multiple nodes (MYC, FOS and HSPA4). Validation in the HNSCC-specific database (N = 528) in The Cancer Genome Atlas (TCGA) identified a panel (ECT2, ANO1, TP63, FADD, EXT1, NCBP2) that was altered in 30% of the samples. Validation in treatment naïve (Group I; N = 12) and post treatment (Group II; N = 12) patients identified 8 genes significantly associated with the disease (Area under curve>0.6). Correlation with recurrence/re-recurrence showed ANO1 had highest efficacy (sensitivity: 0.8, specificity: 0.6) to predict failure in Group I. UBE2V2, PLAC8, FADD and TTK showed high sensitivity (1.00) in Group I while UBE2V2 and CRYM were highly sensitive (>0.8) in predicting re-recurrence in Group II. Further, TCGA analysis showed that ANO1 and FADD, located at 11q13, were co-expressed at transcript level and significantly associated with overall and disease-free survival (p<0.05). The meta-analysis approach adopted in this study has identified candidate markers correlated with disease outcome in HNSCC; further validation in a larger cohort of patients will establish their clinical relevance.

Transcriptomic Profiling of Medial Temporal Lobe Epilepsy.

Epilepsy is one of the most prevalent neurological disorders affecting ~1% of the population. Medial temporal lobe epilepsy (MTLE) is the most frequent type of epilepsy observed in adults who do not respond to pharmacological treatment. The reason for intractability in these patients has not been systematically studied. Further, no markers are available that can predict the subset of patients who will not respond to pharmacotherapy. To identify potential biomarkers of epileptogenicity, we compared the mRNA profiles of surgically resected tissue from seizure zones with non-seizure zones from cases of intractable MTLE. We identified 413 genes that exhibited ≥2-fold change that were statistically significant across these two groups. Several of these differentially expressed genes have not been previously described in the context of MTLE including claudin 11 (CLDN11) and bone morphogenetic protein receptor, type IB (BMPR1B). In addition, we found significant downregulation of a subset of gamma-aminobutyric acid (GABA) associated genes. We also identified molecules such as BACH2 and ADAMTS15, which are already known to be associated with epilepsy. We validated one upregulated molecule, serine/threonine kinase 31 (STK31) and one downregulated molecule, SMARCA4, by immunohistochemical labeling of tissue sections. These molecules need to be further confirmed in large-scale studies to determine their potential use as diagnostic as well as prognostic markers in intractable MTLE.

Gene Expression Profiling of Tuberculous Meningitis Co-infected with HIV.

Tuberculous meningitis (TBM) is a fatal form of Mycobacterium tuberculosis infection of the central nervous system (CNS). The similarities in the clinical and radiological findings in TBM cases with or without HIV make the diagnosis very challenging. Identification of genes, which are differentially expressed in brain tissues of HIV positive and HIV negative TBM patients, would enable better understanding of the molecular aspects of the infection and would also serve as an initial platform to evaluate potential biomarkers. Here, we report the identification of 796 differentially regulated genes in brain tissues of TBM patients co-infected with HIV using oligonucleotide DNA microarrays. We also performed immunohistochemical validation and confirmed the abundance of four gene products-glial fibrillary acidic protein (GFAP), serpin peptidase inhibitor, clade A member 3 (SERPINA3), thymidine phosphorylase (TYMP/ECGF1) and heat shock 70 kDa protein 8 (HSPA8). Our study paves the way for understanding the mechanism of TBM in HIV positive patients and for further validation of potential disease biomarkers.

Gene Expression Profiling of Gastric Cancer.

Gastric cancer is the second leading cause of cancer death worldwide, both in men and women. A genomewide gene expression analysis was carried out to identify differentially expressed genes in gastric adenocarcinoma tissues as compared to adjacent normal tissues. We used Agilent's whole human genome oligonucleotide microarray platform representing ~41,000 genes to carry out gene expression analysis. Two-color microarray analysis was employed to directly compare the expression of genes between tumor and normal tissues. Through this approach, we identified several previously known candidate genes along with a number of novel candidate genes in gastric cancer. Testican-1 (SPOCK1) was one of the novel molecules that was 10-fold upregulated in tumors. Using tissue microarrays, we validated the expression of testican-1 by immunohistochemical staining. It was overexpressed in 56% (160/282) of the cases tested. Pathway analysis led to the identification of several networks in which SPOCK1 was among the topmost networks of interacting genes. By gene enrichment analysis, we identified several genes involved in cell adhesion and cell proliferation to be significantly upregulated while those corresponding to metabolic pathways were significantly downregulated. The differentially expressed genes identified in this study are candidate biomarkers for gastric adenoacarcinoma.