The neuronal sortilin-related receptor SORL1 is genetically associated with Alzheimer disease.

The recycling of the amyloid precursor protein (APP) from the cell surface via the endocytic pathways plays a key role in the generation of amyloid beta peptide (Abeta) in Alzheimer disease. We report here that inherited variants in the SORL1 neuronal sorting receptor are associated with late-onset Alzheimer disease. These variants, which occur in at least two different clusters of intronic sequences within the SORL1 gene (also known as LR11 or SORLA) may regulate tissue-specific expression of SORL1. We also show that SORL1 directs trafficking of APP into recycling pathways and that when SORL1 is underexpressed, APP is sorted into Abeta-generating compartments. These data suggest that inherited or acquired changes in SORL1 expression or function are mechanistically involved in causing Alzheimer disease.

NKG2D regulates production of soluble TRAIL by ex vivo expanded human γδ T cells.

Soluble TRAIL (sTRAIL) can be produced by myeloid-derived cells to kill cancer cells. Whether this mechanism is used by T cells, and if so, how sTRAIL production is regulated, remains unclear. Our previous studies showed that ex vivo expanded human γδ T cells express TRAIL and NK receptor group 2 (R2), member D (NKG2D), and possess potent anticancer activities both in vitro and in vivo. Here, we investigated in greater detail the mechanisms by which γδ T cells utilize TRAIL and NKG2D to kill lung cancer cells. We demonstrate that human lung cancer cells express TRAIL R2 and NKG2D ligands. Blocking TRAIL or NKG2D during γδ T-cell-lung cancer cell co-cultures significantly reduced γδ T-cell-mediated cytotoxicity. Cross-linking NKG2D with anti-NKG2D antibody to mimic ligand binding promoted γδ T cells to produce sTRAIL, which induced apoptosis in lung cancer cells through TRAIL R2. Either neutralizing sTRAIL or blocking lung cancer cell TRAIL R2 significantly reduced γδ T-cell-mediated cytotoxicity to lung cancer cells. This study demonstrates that γδ T cells can mediate anticancer immunity via NKG2D-regulated production of sTRAIL.

Prognostic gene signatures for non-small-cell lung cancer.

Resectable non-small-cell lung cancer (NSCLC) patients have poor prognosis, with 30-50% relapsing within 5 years. Current staging criteria do not fully capture the complexity of this disease. Survival could be improved by identification of those early-stage patients who are most likely to benefit from adjuvant therapy. Molecular classification by using mRNA expression profiles has led to multiple, poorly overlapping signatures. We hypothesized that differing statistical methodologies contribute to this lack of overlap. To test this hypothesis, we analyzed our previously published quantitative RT-PCR dataset with a semisupervised method. A 6-gene signature was identified and validated in 4 independent public microarray datasets that represent a range of tumor histologies and stages. This result demonstrated that at least 2 prognostic signatures can be derived from this single dataset. We next estimated the total number of prognostic signatures in this dataset with a 10-million-signature permutation study. Our 6-gene signature was among the top 0.02% of signatures with maximum verifiability, reaffirming its efficacy. Importantly, this analysis identified 1,789 unique signatures, implying that our dataset contains >500,000 verifiable prognostic signatures for NSCLC. This result appears to rationalize the observed lack of overlap among reported NSCLC prognostic signatures.

Differential utilization of NF-kappaB RELA and RELB in response to extracellular versus intracellular polyIC stimulation in HT1080 cells.

BACKGROUND: Pattern recognition receptors (PRRs) for double-stranded RNA (dsRNA) are components of innate immunity that recognize the presence of viral infection and initiate efficient defense mechanisms. In addition to previously well-characterized signaling pathways that are mediated by PKR and TLR3, new intracellular dsRNA sensors, that are members of CARD and DExD/H box helicase family, have been identified. However, the molecular mechanisms involved in the signaling pathways mediated by these new dsRNA sensors have not been extensively characterized. RESULTS: Here, we studied an intracellular dsRNA pathway in the human fibrosarcoma cell line HT1080, which is distinct from the TLR3-mediated extracellular dsRNA pathway. Particularly, the NF-kB subunits RELA and RELB were differentially utilized by these two dsRNA signaling pathways. In TLR3-mediated dsRNA signaling, siRNA knock-down studies suggested a limited role for RELA on regulation of interferon beta and other cytokines whereas RELB appeared to have a negative regulatory role. By contrast, intracellular dsRNA signaling was dependent on RELA, but not RELB. CONCLUSIONS: Our study suggests that extracellular and intracellular dsRNA signaling pathways may utilize different NF-kB members, and particularly the differential utilization of RELB may be a key mechanism for powerful inductions of NF-kB regulated genes in the intracellular dsRNA signaling pathway.

Genomic DNA functions as a universal external standard in quantitative real-time PCR.

Real-time quantitative PCR (qPCR) is a powerful tool for quantifying specific DNA target sequences. Although determination of relative quantity is widely accepted as a reliable means of measuring differences between samples, there are advantages to being able to determine the absolute copy numbers of a given target. One approach to absolute quantification relies on construction of an accurate standard curve using appropriate external standards of known concentration. We have validated the use of tissue genomic DNA as a universal external standard to facilitate quantification of any target sequence contained in the genome of a given species, addressing several key technical issues regarding its use. This approach was applied to validate mRNA expression of gene candidates identified from microarray data and to determine gene copies in transgenic mice. A simple method that can assist achieving absolute quantification of gene expression would broadly enhance the uses of real-time qPCR and in particular, augment the evaluation of global gene expression studies.

Allogeneic Human Double Negative T Cells as a Novel Immunotherapy for Acute Myeloid Leukemia and Its Underlying Mechanisms.

Purpose: To explore the potential of ex vivo expanded healthy donor-derived allogeneic CD4 and CD8 double-negative cells (DNT) as a novel cellular immunotherapy for leukemia patients.Experimental Design: Clinical-grade DNTs from peripheral blood of healthy donors were expanded and their antileukemic activity and safety were examined using flow cytometry-based in vitro killing assays and xenograft models against AML patient blasts and healthy donor-derived hematopoietic cells. Mechanism of action was investigated using antibody-mediated blocking assays and recombinant protein treatment assays.Results: Expanded DNTs from healthy donors target a majority (36/46) of primary AML cells, including 9 chemotherapy-resistant patient samples in vitro, and significantly reduce the leukemia load in patient-derived xenograft models in a DNT donor-unrestricted manner. Importantly, allogeneic DNTs do not attack normal hematopoietic cells or affect hematopoietic stem/progenitor cell engraftment and differentiation, or cause xenogeneic GVHD in recipients. Mechanistically, DNTs express high levels of NKG2D and DNAM-1 that bind to cognate ligands preferentially expressed on AML cells. Upon recognition of AML cells, DNTs rapidly release IFNγ, which further increases NKG2D and DNAM-1 ligands' expression on AML cells. IFNγ pretreatment enhances the susceptibility of AML cells to DNT-mediated cytotoxicity, including primary AML samples that are otherwise resistant to DNTs, and the effect of IFNγ treatment is abrogated by NKG2D and DNAM-1-blocking antibodies.Conclusions: This study supports healthy donor-derived allogeneic DNTs as a therapy to treat patients with chemotherapy-resistant AML and also reveals interrelated roles of NKG2D, DNAM-1, and IFNγ in selective targeting of AML by DNTs. Clin Cancer Res; 24(2); 370-82. ©2017 AACR.

Cytokine functions in the formative stages of a lymphocyte's life.

Five core cytokines that control lymphocyte differentiation and maintenance have been identified and studied in depth. IL-7 sits at the apex of this cytokine hierarchy in terms of functional significance during lymphocyte development. The IL-7-dominant phase of lymphopoiesis is preceded by the actions of c-Kit ligand (also called stem cell factor; SCF) and fetal liver kinase 2 ligand (Flk-2L); the function of both of these cytokines is essential for the maintenance and development of the progenitor compartment of multiple lineages. IL-7 activity is complemented by two cytokines whose receptors share components of the IL-7 receptor: thymic stromal lymphopoietin (TSLP) and IL-15. The influences of these core cytokines on precursor lymphocyte subsets overlap during development and are often synergistic. Recent studies are beginning to uncover the molecular mechanisms of these interrelated core cytokine functions.

CpG Island microarray probe sequences derived from a physical library are representative of CpG Islands annotated on the human genome.

An effective tool for the global analysis of both DNA methylation status and protein-chromatin interactions is a microarray constructed with sequences containing regulatory elements. One type of array suited for this purpose takes advantage of the strong association between CpG Islands (CGIs) and gene regulatory regions. We have obtained 20,736 clones from a CGI Library and used these to construct CGI arrays. The utility of this library requires proper annotation and assessment of the clones, including CpG content, genomic origin and proximity to neighboring genes. Alignment of clone sequences to the human genome (UCSC hg17) identified 9595 distinct genomic loci; 64% were defined by a single clone while the remaining 36% were represented by multiple, redundant clones. Approximately 68% of the loci were located near a transcription start site. The distribution of these loci covered all 23 chromosomes, with 63% overlapping a bioinformatically identified CGI. The high representation of genomic CGI in this rich collection of clones supports the utilization of microarrays produced with this library for the study of global epigenetic mechanisms and protein-chromatin interactions. A browsable database is available on-line to facilitate exploration of the CGIs in this library and their association with annotated genes or promoter elements.

A Cost-Effectiveness Analysis of Using the JBR.10-Based 15-Gene Expression Signature to Guide Adjuvant Chemotherapy in Early Stage Non-Small-Cell Lung Cancer.

BACKGROUND: Adjuvant chemotherapy (ACT) improved survival in the NCIC Clinical Trials Group JBR.10 trial of resected stage IB/II non-small-cell lung cancer. A prognostic 15-gene expression signature was developed, which may also predict for benefit from ACT. An exploratory economic analysis was conducted to assess the potential cost-effectiveness of using the 15-gene signature in guiding ACT decisions. METHODS: A decision analytic model was populated by study patients with quantitative reverse transcription polymerase chain reaction tumor profiling, current costs, and quality-adjusted survival. Analysis was performed over the 6-year follow-up from the perspective of the Canadian public health care system in 2015 Canadian dollars (discounted 5%/year). Incremental cost-effectiveness and cost-utility ratios were determined for ACT versus observation using clinical stage, gene signature, or a combined approach to select treatment. RESULTS: The mean survival gain of ACT versus observation was higher using the gene signature (1.86 years) compared with clinical stage (1.28 years). Although more costly, ACT guided by the gene signature remained cost-effective at $10,421/life-year gained (95% confidence interval [CI], $466-$19,568 Canadian), comparable to stage-directed selection ($7081/life-year gained; 95% CI, -$2370 to $14,721; P = .52). Incremental cost-utility ratios were $13,452/quality-adjusted life-year (95% CI, $373-$31,949) and $9194/quality-adjusted life-year (95% CI, -$4104 to $23,952), respectively (P = .53). Comparing the standard and test-and-treat approaches, use of the gene signature did not significantly alter survival compared with the standard strategy, but it reduced the ACT rate by 25%. CONCLUSION: If validated, the use of the 15-gene expression signature to select patients for ACT may increase the survival gain of treatment in patients with high-risk stage IB/II non-small-cell lung cancer, while avoiding toxicities in low-risk patients.

Integrating RAS status into prognostic signatures for adenocarcinomas of the lung.

PURPOSE: While the dysregulation of specific pathways in cancer influences both treatment response and outcome, few current prognostic markers explicitly consider differential pathway activation. Here we explore this concept, focusing on K-Ras mutations in lung adenocarcinoma (present in 25%-35% of patients). EXPERIMENTAL DESIGN: The effect of K-Ras mutation status on prognostic accuracy of existing signatures was evaluated in 404 patients. Genes associated with K-Ras mutation status were identified and used to create a RAS pathway activation classifier to provide a more accurate measure of RAS pathway status. Next, 8 million random signatures were evaluated to assess differences in prognosing patients with or without RAS activation. Finally, a prognostic signature was created to target patients with RAS pathway activation. RESULTS: We first show that K-Ras status influences the accuracy of existing prognostic signatures, which are effective in K-Ras-wild-type patients but fail in patients with K-Ras mutations. Next, we show that it is fundamentally more difficult to predict the outcome of patients with RAS activation (RAS(mt)) than that of those without (RAS(wt)). More importantly, we demonstrate that different signatures are prognostic in RAS(wt) and RAS(mt). Finally, to exploit this discovery, we create separate prognostic signatures for RAS(wt) and RAS(mt) patients and show that combining them significantly improves predictions of patient outcome. CONCLUSIONS: We present a nested model for integrated genomic and transcriptomic data. This model is general and is not limited to lung adenocarcinomas but can be expanded to other tumor types and oncogenes.

Appropriateness of using patient-derived xenograft models for pharmacologic evaluation of novel therapies for esophageal/gastro-esophageal junction cancers.

The high morbidity and mortality of patients with esophageal (E) and gastro-esophageal junction (GEJ) cancers, warrants new pre-clinical models for drug testing. The utility of primary tumor xenografts (PTXGs) as pre-clinical models was assessed. Clinicopathological, immunohistochemical markers (p53, p16, Ki-67, Her-2/neu and EGFR), and global mRNA abundance profiles were evaluated to determine selection biases of samples implanted or engrafted, compared with the underlying population. Nine primary E/GEJ adenocarcinoma xenograft lines were further characterized for the spectrum and stability of gene/protein expression over passages. Seven primary esophageal adenocarcinoma xenograft lines were treated with individual or combination chemotherapy. Tumors that were implanted (n=55) in NOD/SCID mice had features suggestive of more aggressive biology than tumors that were never implanted (n=32). Of those implanted, 21/55 engrafted; engraftment was associated with poorly differentiated tumors (p=0.04) and older patients (p=0.01). Expression of immunohistochemical markers were similar between patient sample and corresponding xenograft. mRNA differences observed between patient tumors and first passage xenografts were largely due to loss of human stroma in xenografts. mRNA patterns of early vs late passage xenografts and of small vs large tumors of the same passage were similar. Complete resistance was present in 2/7 xenografts while the remaining tumors showed varying degrees of sensitivity, that remained constant across passages. Because of their ability to recapitulate primary tumor characteristics during engraftment and across serial passaging, PTXGs can be useful clinical systems for assessment of drug sensitivity of human E/GEJ cancers.

Microarray gene expression profiling and analysis in renal cell carcinoma.

BACKGROUND: Renal cell carcinoma (RCC) is the most common cancer in adult kidney. The accuracy of current diagnosis and prognosis of the disease and the effectiveness of the treatment for the disease are limited by the poor understanding of the disease at the molecular level. To better understand the genetics and biology of RCC, we profiled the expression of 7,129 genes in both clear cell RCC tissue and cell lines using oligonucleotide arrays. METHODS: Total RNAs isolated from renal cell tumors, adjacent normal tissue and metastatic RCC cell lines were hybridized to affymatrix HuFL oligonucleotide arrays. Genes were categorized into different functional groups based on the description of the Gene Ontology Consortium and analyzed based on the gene expression levels. Gene expression profiles of the tissue and cell line samples were visualized and classified by singular value decomposition. Reverse transcription polymerase chain reaction was performed to confirm the expression alterations of selected genes in RCC. RESULTS: Selected genes were annotated based on biological processes and clustered into functional groups. The expression levels of genes in each group were also analyzed. Seventy-four commonly differentially expressed genes with more than five-fold changes in RCC tissues were identified. The expression alterations of selected genes from these seventy-four genes were further verified using reverse transcription polymerase chain reaction (RT-PCR). Detailed comparison of gene expression patterns in RCC tissue and RCC cell lines shows significant differences between the two types of samples, but many important expression patterns were preserved. CONCLUSIONS: This is one of the initial studies that examine the functional ontology of a large number of genes in RCC. Extensive annotation, clustering and analysis of a large number of genes based on the gene functional ontology revealed many interesting gene expression patterns in RCC. Most notably, genes involved in cell adhesion were dominantly up-regulated whereas genes involved in transport were dominantly down-regulated. This study reveals significant gene expression alterations in key biological pathways and provides potential insights into understanding the molecular mechanism of renal cell carcinogenesis.

Validation of a histology-independent prognostic gene signature for early-stage, non-small-cell lung cancer including stage IA patients.

BACKGROUND: Patients with early-stage non-small-cell lung carcinoma (NSCLC) may benefit from treatments based on more accurate prognosis. A 15-gene prognostic classifier for NSCLC was identified from mRNA expression profiling of tumor samples from the NCIC CTG JBR.10 trial. In this study, we assessed its value in an independent set of cases. METHODS: Expression profiling was performed on RNA from frozen, resected tumor tissues corresponding to 181 stage I and II NSCLC cases collected at University Health Network (UHN181). Kaplan-Meier methodology was used to estimate 5-year overall survival probabilities, and the prognostic effect of the classifier was assessed using the log-rank test. A Cox proportional hazards model evaluated the signature's effect adjusting for clinical prognostic factors. RESULTS: Expression data of the 15-gene classifier stratified UHN181 cases into high- and low-risk subgroups with significantly different overall survival (hazard ratio [HR] = 1.92; 95% confidence interval [CI], 1.15-3.23; p = 0.012). In a subgroup analysis, this classifier predicted survival in 127 stage I patients (HR = 2.17; 95% CI, 1.12-4.20; p = 0.018) and the smaller subgroup of 48 stage IA patients (HR = 5.61; 95% CI, 1.19-26.45; p = 0.014). The signature was prognostic for both adenocarcinoma and squamous cell carcinoma cases (HR = 1.76, p = 0.058; HR = 4.19, p = 0.045, respectively). CONCLUSION: The prognostic accuracy of a 15-gene classifier was validated in an independent cohort of 181 early-stage NSCLC samples including stage IA cases and in different NSCLC histologic subtypes.

Exploiting the noise: improving biomarkers with ensembles of data analysis methodologies.

BACKGROUND: The advent of personalized medicine requires robust, reproducible biomarkers that indicate which treatment will maximize therapeutic benefit while minimizing side effects and costs. Numerous molecular signatures have been developed over the past decade to fill this need, but their validation and up-take into clinical settings has been poor. Here, we investigate the technical reasons underlying reported failures in biomarker validation for non-small cell lung cancer (NSCLC). METHODS: We evaluated two published prognostic multi-gene biomarkers for NSCLC in an independent 442-patient dataset. We then systematically assessed how technical factors influenced validation success. RESULTS: Both biomarkers validated successfully (biomarker #1: hazard ratio (HR) 1.63, 95% confidence interval (CI) 1.21 to 2.19, P = 0.001; biomarker #2: HR 1.42, 95% CI 1.03 to 1.96, P = 0.030). Further, despite being underpowered for stage-specific analyses, both biomarkers successfully stratified stage II patients and biomarker #1 also stratified stage IB patients. We then systematically evaluated reasons for reported validation failures and find they can be directly attributed to technical challenges in data analysis. By examining 24 separate pre-processing techniques we show that minor alterations in pre-processing can change a successful prognostic biomarker (HR 1.85, 95% CI 1.37 to 2.50, P < 0.001) into one indistinguishable from random chance (HR 1.15, 95% CI 0.86 to 1.54, P = 0.348). Finally, we develop a new method, based on ensembles of analysis methodologies, to exploit this technical variability to improve biomarker robustness and to provide an independent confidence metric. CONCLUSIONS: Biomarkers comprise a fundamental component of personalized medicine. We first validated two NSCLC prognostic biomarkers in an independent patient cohort. Power analyses demonstrate that even this large, 442-patient cohort is under-powered for stage-specific analyses. We then use these results to discover an unexpected sensitivity of validation to subtle data analysis decisions. Finally, we develop a novel algorithmic approach to exploit this sensitivity to improve biomarker robustness.

Association of the 15q25 and 5p15 lung cancer susceptibility regions with gene expression in lung tumor tissue.

BACKGROUND: Genome-wide association studies have identified two independent lung cancer susceptibility loci at chromosome 15q25 and one locus at 5p15. We examined the association of genetic variants in these regions with gene expression in lung tumor tissue, in an effort to elucidate carcinogenic mechanisms by which these variants influence lung cancer risk. METHODS: We used data from 2 independent studies of non-small cell lung carcinoma patients: the JBR.10 clinical trial (n = 131) and a University Health Network (UHN) patient sample in Toronto (n = 181). We genotyped seven 15q25 and five 5p15 variants and examined their association with expression profiles of genes in the corresponding regions, measured by Affymetrix HG-U133A. RESULTS: The minor allele (C) of a variant representing one of the two loci at 15q25 (rs2036534) was associated with increased iron-responsive element binding protein 2 (IREB2) expression in both studies (JBR.10 P = 0.042; UHN P = 0.002). A false discovery rate of 0.05 or less in the UHN sample increased our confidence in this association. The association appears to be more prominent among lung adenocarcinoma patients. We did not detect an association between genotype and expression profile for the other 15q25 locus or for 5p15 variants. CONCLUSIONS: In contrast to previous studies that indicate 15q25 variants are associated with lung cancer risk through an effect on smoking behavior, our results suggest these variants may influence risk through a second mechanism, involving modulation of IREB2 expression. IMPACT: This finding expands on potential mechanisms through which 15q25 variants influence lung cancer risk and may have implications for future research on chemoprevention strategies.

Silencing of thrombospondin-1 is critical for myc-induced metastatic phenotypes in medulloblastoma.

Mechanisms by which c-Myc (Myc) amplification confers aggressive medulloblastoma phenotypes are poorly defined. Here, we show using orthotopic models that high Myc expression promotes cell migration/invasion and induces metastatic tumors, which recapitulate aggressive histologic features of Myc-amplified primary human medulloblastoma. Using ChIP-chip analysis, we identified cell migration and adhesion genes, including Tsp-1/THBS1, ING4, PVRL3, and PPAP2B, as Myc-bound loci in medulloblastoma cells. Expression of Tsp-1 was most consistently and robustly diminished in medulloblastoma cell lines and primary human tumors with high Myc expression (n = 101, P = 0.032). Strikingly, stable Tsp-1 expression significantly attenuated in vitro transformation and invasive/migratory properties of high Myc-expressing medulloblastoma cells without altering cell proliferation, whereas RNA interference-mediated Myc knockdown was consistently accompanied by increased Tsp-1 levels and reduced cell migration and invasion in medulloblastoma cells. Chromatin immunoprecipitation (ChIP) assays revealed colocalization of Myc and obligate partner Max and correlated diminished RNA polymerase II occupancy (∼3-fold decrease, P < 0.01) with increased Myc binding at a core Tsp-1 promoter. Reporter gene and/or gel shift assays confirmed direct repression of Tsp-1 transcription by Myc and also identified JPO2, a Myc interactor associated with metastatic medulloblastoma, as a cofactor in Myc-mediated Tsp-1 repression. These findings indicate the Myc-regulatory network targets Tsp-1 via multiple mechanisms in medulloblastoma transformation, and highlight a novel critical role for Tsp-1 in Myc-mediated aggressive medulloblastoma phenotypes.

Oncolytic targeting of renal cell carcinoma via encephalomyocarditis virus.

Apoptosis is a fundamental host defence mechanism against invading microbes. Inactivation of NF-kappaB attenuates encephalomyocarditis virus (EMCV) virulence by triggering rapid apoptosis of infected cells, thereby pre-emptively limiting viral replication. Recent evidence has shown that hypoxia-inducible factor (HIF) increases NF-kappaB-mediated anti-apoptotic response in clear-cell renal cell carcinoma (CCRCC) that commonly exhibit hyperactivation of HIF due to the loss of its principal negative regulator, von Hippel-Lindau (VHL) tumour suppressor protein. Here, we show that EMCV challenge induces a strong NF-kappaB-dependent gene expression profile concomitant with a lack of interferon-mediated anti-viral response in VHL-null CCRCC, and that multiple established CCRCC cell lines, as well as early-passage primary CCRCC cultured cells, are acutely susceptible to EMCV replication and virulence. Functional restoration of VHL or molecular suppression of HIF or NF-kappaB dramatically reverses CCRCC cellular susceptibility to EMCV-induced killing. Notably, intratumoural EMCV treatment of CCRCC in a murine xenograft model rapidly regresses tumour growth. These findings provide compelling pre-clinical evidence for the usage of EMCV in the treatment of CCRCC and potentially other tumours with elevated HIF/NF-kappaB-survival signature.

CD4+ regulatory T cells require CTLA-4 for the maintenance of systemic tolerance.

Cytotoxic T lymphocyte antigen-4 (CTLA-4) plays a critical role in negatively regulating T cell responses and has also been implicated in the development and function of natural FOXP3(+) regulatory T cells. CTLA-4-deficient mice develop fatal, early onset lymphoproliferative disease. However, chimeric mice containing both CTLA-4-deficient and -sufficient bone marrow (BM)-derived cells do not develop disease, indicating that CTLA-4 can act in trans to maintain T cell self-tolerance. Using genetically mixed blastocyst and BM chimaeras as well as in vivo T cell transfer systems, we demonstrate that in vivo regulation of Ctla4(-/-) T cells in trans by CTLA-4-sufficient T cells is a reversible process that requires the persistent presence of FOXP3(+) regulatory T cells with a diverse TCR repertoire. Based on gene expression studies, the regulatory T cells do not appear to act directly on T cells, suggesting they may instead modulate the stimulatory activities of antigen-presenting cells. These results demonstrate that CTLA-4 is absolutely required for FOXP3(+) regulatory T cell function in vivo.

Understanding prognostic gene expression signatures in lung cancer.

In non-small-cell lung cancer (NSCLC), molecular profiling of tumors has led to the identification of gene expression patterns that are associated with specific phenotypes and prognosis. Such correlations could identify early-stage patients who are at increased risk of disease recurrence and death after complete surgical resection and who might benefit from adjuvant therapy. Profiling may also identify aberrant molecular pathways that might lead to specific molecularly targeted therapies. The technology behind the capturing and correlating of molecular profiles with clinical and biologic endpoints have evolved rapidly since microarrays were first developed a decade ago. In this review, we discuss multiple methods that have been used to derive prognostic gene expression signatures in NSCLC. Despite the diversity in the approaches used, 3 main steps are followed. First, the expression levels of several hundred to tens of thousands of genes are quantified by microarray or quantitative polymerase chain reaction techniques; the data are then preprocessed, normalized, and possibly filtered. In the second step, expression data are combined and grouped by clustering, risk score generation, or other means, to generate a gene signature that correlates with a clinical outcome, usually survival. Finally, the signature is validated in datasets of independent cohorts. This review discusses the concepts and methodologies involved in these analytical steps, primarily to facilitate the understanding of reports on large dataset gene expression studies that focus on prognostic signatures in NSCLC.

Ex vivo transcriptional profiling of human pancreatic islets following chronic exposure to monounsaturated fatty acids.

The aim of this study was to assess the effects of chronic free fatty acid (FFA) exposure on gene expression and the functional state of human pancreatic islets. Chronic exposure of islets to oleate (OA) resulted in a significant reduction in glucose-stimulated insulin secretion (GSIS) compared with control (466+/-82 vs 234+/-57 ng/microg DNA, P<0.05). OA treatment also led to reduction in total insulin content of the islets (17 609+/-3816 vs 10 599+/-3876 ng insulin/microg DNA) and to an increase in the rate of reactive oxygen species (ROS) generation. Interestingly, the suppressive effects of OA on biosynthesis and secretion of insulin were accompanied by alteration in the expression of 40 genes, as determined by microarray analysis and subsequent qPCR validation. The majority of genes regulated by OA encoded metabolic enzymes. The expression of enzymes involved in oxidative defense was elevated, indicating a link between ROS generation and antioxidant defense activation. Additionally, pretreatment of human islets with OA led to a significant increase (30%) in the rate of oxidation of this fatty acid and to a significant decrease (75%) in glucose oxidation. Importantly, individual analysis of gene clusters from the islets of all donors revealed the induction of genes involved in inflammation and immunity, which provides further evidence that FFA are risk factors for the development of type 2 diabetes. In summary, our data indicate that chronic exposure of human islets to FFA activates inflammatory and metabolic pathways that lead to oxidative stress, reduced beta-cell insulin content, and inhibition of GSIS.