Protein profiling in hepatocellular carcinoma by label-free quantitative proteomics in two west african populations.

Background Hepatocellular Carcinoma is the third most common cause of cancer related death worldwide, often diagnosed by measuring serum AFP; a poor performance stand-alone biomarker. With the aim of improving on this, our study focuses on plasma proteins identified by Mass Spectrometry in order to investigate and validate differences seen in the respective proteomes of controls and subjects with LC and HCC. Methods Mass Spectrometry analysis using liquid chromatography electro spray ionization quadrupole time-of-flight was conducted on 339 subjects using a pooled expression profiling approach. ELISA assays were performed on four significantly differentially expressed proteins to validate their expression profiles in subjects from the Gambia and a pilot group from Nigeria. Results from this were collated for statistical multiplexing using logistic regression analysis. Results Twenty-six proteins were identified as differentially expressed between the three subject groups. Direct measurements of four; hemopexin, alpha-1-antitrypsin, apolipoprotein A1 and complement component 3 confirmed their change in abundance in LC and HCC versus control patients. These trends were independently replicated in the pilot validation subjects from Nigeria. The statistical multiplexing of these proteins demonstrated performance comparable to or greater than ALT in identifying liver cirrhosis or carcinogenesis. This exercise also proposed preliminary cut offs with achievable sensitivity, specificity and AUC statistics greater than reported AFP averages. Conclusions The validated changes of expression in these proteins have the potential for development into high-performance tests usable in the diagnosis and or monitoring of HCC and LC patients. The identification of sustained expression trends strengthens the suggestion of these four proteins as worthy candidates for further investigation in the context of liver disease. The statistical combinations also provide a novel inroad of analyses able to propose definitive cut-offs and combinations for evaluation of performance

An examination of cancer-related fatigue through proposed diagnostic criteria in a sample of cancer patients in Taiwan

<p>Abstract</p> <p>Background</p> <p>Fatigue among cancer patients has often been reported in the literature; however, great variations have been documented, ranging from 15% to 90%, probably due to the lack of a widely accepted definition and established diagnostic criteria for cancer-related fatigue. The objective of this study was to evaluate the proposed International Statistical Classification of Diseases and Related Health Problems (10^threvision) (ICD-10) criteria in a sample of cancer patients from a medical center and a regional teaching hospital in northern Taiwan. More accurate prevalence estimates of CRF may result in improved diagnoses and management of one of the most common symptoms associated with cancer and its treatment.</p> <p>Methods</p> <p>Since self-reporting from patients is the most effective and efficient method to measure fatigue, the ICD-10 criteria for fatigue were used. The ICD-10 criteria questionnaire was translated into Chinese and was approved by experts. Patients were recruited from outpatient palliative and oncology clinics and from palliative and oncology inpatient units.</p> <p>Results</p> <p>Of the 265 cancer patients that were interviewed between 21 October 2008 and 28 October 2009, 228 (86%) reported having at least 2 weeks of fatigue in the past month, and further evaluation with the ICD-10 criteria showed that 132 (49.8%) had cancer-related fatigue. Internal consistency was very good, which was indicated by a Cronbach alpha of 0.843.</p> <p>Conclusion</p> <p>The prevalence of diagnosable CRF in the patients in this sample, of whom most were under palliative treatment, was 49.8%, which was probably somewhat lower than in some of the previous reports that have used less-strict criteria. In addition, among the various criteria of the proposed diagnostic criteria, the most frequently reported symptoms in our sample populations were regarding sleep disturbance and physical factors. Although they will require further replication in other samples, these formal diagnostic criteria can serve as a step toward a common language and a better understanding of the severity range of CRF.</p

Synaptic and transcriptionally downregulated genes are associated with cortical thickness differences in autism.

Differences in cortical morphology-in particular, cortical volume, thickness and surface area-have been reported in individuals with autism. However, it is unclear what aspects of genetic and transcriptomic variation are associated with these differences. Here we investigate the genetic correlates of global cortical thickness differences (ΔCT) in children with autism. We used Partial Least Squares Regression (PLSR) on structural MRI data from 548 children (166 with autism, 295 neurotypical children and 87 children with ADHD) and cortical gene expression data from the Allen Institute for Brain Science to identify genetic correlates of ΔCT in autism. We identify that these genes are enriched for synaptic transmission pathways and explain significant variation in ΔCT. These genes are also significantly enriched for genes dysregulated in the autism post-mortem cortex (Odd Ratio (OR) = 1.11, Pcorrected  10-14), driven entirely by downregulated genes (OR = 1.87, Pcorrected  10-15). We validated the enrichment for downregulated genes in two independent data sets: Validation 1 (OR = 1.44, Pcorrected = 0.004) and Validation 2 (OR = 1.30; Pcorrected = 0.001). We conclude that transcriptionally downregulated genes implicated in autism are robustly associated with global changes in cortical thickness variability in children with autism

Global gene expression analyses of bystander and alpha particle irradiated normal human lung fibroblasts: Synchronous and differential responses

<p>Abstract</p> <p>Background</p> <p>The existence of a radiation bystander effect, in which non-irradiated cells respond to signals from irradiated cells, is now well established. It raises concerns for the interpretation of risks arising from exposure to low doses of ionizing radiation. However, the regulatory mechanisms involved in the bystander response have not been well elucidated. To provide insight into the signaling pathways responding in bystanders, we have measured global gene expression four hours after bystander and direct alpha particle exposure of primary human lung fibroblasts.</p> <p>Results</p> <p>Although common p53-regulated radiation response genes like <it>CDKN1A </it>were expressed at elevated levels in the directly exposed cultures, they showed little or no change in the bystanders. In contrast, genes regulated by NFκB, such as <it>PTGS2 </it>(cyclooxygenase-2), <it>IL8 </it>and <it>BCL2A1</it>, responded nearly identically in bystander and irradiated cells. This trend was substantiated by gene ontology and pathway analyses of the microarray data, which suggest that bystander cells mount a full NFκB response, but a muted or partial p53 response. In time-course analyses, quantitative real-time PCR measurements of <it>CDKN1A </it>showed the expected 4-hour peak of expression in irradiated but not bystander cells. In contrast, <it>PTGS2, IL8 </it>and <it>BCL2A1 </it>responded with two waves of expression in both bystander and directly irradiated cells, one peaking at half an hour and the other between four and six hours after irradiation.</p> <p>Conclusion</p> <p>Two major transcriptional hubs that regulate the direct response to ionizing radiation are also implicated in regulation of the bystander response, but to dramatically different degrees. While activation of the p53 response pathway is minimal in bystander cells, the NFκB response is virtually identical in irradiated and bystander cells. This alteration in the balance of signaling is likely to lead to different outcomes in irradiated cells and their bystanders, perhaps leading to greater survival of bystanders and increased risk from any long-term damage they have sustained.</p

Next-gen sequencing identifies non-coding variation disrupting miRNA-binding sites in neurological disorders

Understanding the genetic factors underlying neurodevelopmental and neuropsychiatric disorders is a major challenge given their prevalence and potential severity for quality of life. While large-scale genomic screens have made major advances in this area, for many disorders the genetic underpinnings are complex and poorly understood. To date the field has focused predominantly on protein coding variation, but given the importance of tightly controlled gene expression for normal brain development and disorder, variation that affects non-coding regulatory regions of the genome is likely to play an important role in these phenotypes. Herein we show the importance of 3 prime untranslated region (3'UTR) non-coding regulatory variants across neurodevelopmental and neuropsychiatric disorders. We devised a pipeline for identifying and functionally validating putatively pathogenic variants from next generation sequencing (NGS) data. We applied this pipeline to a cohort of children with severe specific language impairment (SLI) and identified a functional, SLI-associated variant affecting gene regulation in cells and post-mortem human brain. This variant and the affected gene (ARHGEF39) represent new putative risk factors for SLI. Furthermore, we identified 3'UTR regulatory variants across autism, schizophrenia and bipolar disorder NGS cohorts demonstrating their impact on neurodevelopmental and neuropsychiatric disorders. Our findings show the importance of investigating non-coding regulatory variants when determining risk factors contributing to neurodevelopmental and neuropsychiatric disorders. In the future, integration of such regulatory variation with protein coding changes will be essential for uncovering the genetic causes of complex neurological disorders and the fundamental mechanisms underlying health and disease

A population-based study to investigate host genetic factors associated with hepatitis B infection and pathogenesis in the Chinese population

Background Hepatitis B virus (HBV) infection is a significant public health problem that may lead to chronic liver disease, cirrhosis, and hepatocellular carcinoma (HCC). Approximately 30% of the world\u27s population has been infected with HBV and approximately 350 million (5–6%) are persistent carriers. More than 120 million Chinese are infected with HBV. The role of host genetic factors and their interactions with environmental factors leading to chronic HBV infection and its complications are not well understood. We believe that a better understanding of these factors and interactions will lead to more effective diagnostic and therapeutic options. Methods/Design This is a population-based, case-control study protocol to enroll 2200 Han Chinese from medical centers in northern and western China. Adult subjects in the following groups are being enrolled: healthy donors (n = 200), HBV infected persons achieving virus clearance (n = 400), asymptomatic HBV persistent carriers (n = 400), chronic hepatitis B cases (n = 400), decompensated liver cirrhosis with HBV infection cases (n = 400), and hepatocellular carcinoma with HBV infection cases (n = 400). In addition, for haplotype inference and quality control of sample handling and genotyping results, children of 1000 cases will be asked to provide a buccal sample for DNA extraction. With the exception of adult patients presenting with liver cirrhosis or HCC, all other cases and controls will be 40 years or older at enrollment. A questionnaire is being administered to capture dietary and environmental risk factors. Both candidate-gene and genome-wide association approaches will be used to assess the role of single genetic factors and higher order interactions with other genetic or environmental factors in HBV diseases. Conclusion This study is designed and powered to detect single gene effects as well as gene-gene and environmental-gene interactions. The identification of allelic polymorphisms in genes involved in the pathway leading to chronic viral infection, liver cirrhosis and, ultimately, hepatocellular carcinoma would provide insights to those factors leading to HBV replication, liver inflammation, fibrosis, and the carcinogenic process. An understanding of the contribution of host genetic factors and their interactions may inform public health policy, improve diagnostics and clinical management, and provide targets for drug development

Human oocyte-derived methylation differences persist in the placenta revealing widespread transient imprinting

Thousands of regions in gametes have opposing methylation profiles that are largely resolved during the post-fertilization epigenetic reprogramming. However some specific sequences associated with imprinted loci survive this demethylation process. Here we present the data describing the fate of germline-derived methylation in humans. With the exception of a few known paternally methylated germline differentially methylated regions (DMRs) associated with known imprinted domains, we demonstrate that sperm-derived methylation is reprogrammed by the blastocyst stage of development. In contrast a large number of oocyte-derived methylation differences survive to the blastocyst stage and uniquely persist as transiently methylated DMRs only in the placenta. Furthermore, we demonstrate that this phenomenon is exclusive to primates, since no placenta-specific maternal methylation was observed in mouse. Utilizing single cell RNA-seq datasets from human preimplantation embryos we show that following embryonic genome activation the maternally methylated transient DMRs can orchestrate imprinted expression. However despite showing widespread imprinted expression of genes in placenta, allele-specific transcriptional profiling revealed that not all placenta-specific DMRs coordinate imprinted expression and that this maternal methylation may be absent in a minority of samples, suggestive of polymorphic imprinted methylation