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Homo sapiens
22 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Pancreatic cancer is the fourth leading cause of cancer death. Lack of early detection technology for pancreatic cancer invariably leads to a typical clinical presentation of incurable disease at initial diagnosis. Oral fluid (saliva) meets the demand for non-invasive, accessible, and highly efficient diagnostic medium. The level of salivary analytes, such as mRNA and microflora, vary upon disease onset; thus possess valuable signatures for early detection and screening. In this study, we evaluated the performance and translational utilities of the salivary transcriptomic and microbial biomarkers for non-invasive detection of early pancreatic cancer. Two biomarker discovery technologies were used to profile transcriptome in saliva supernatant and microflora in saliva pellet. The Affymetrix Human Genome U133 Plus 2.0 Array was used to discover altered gene expression in saliva supernatant. The Human Oral Microbe Identification Microarray (HOMIM) was used to investigate microflora shift in saliva pellet. Biomarkers selected from both studies were subjected to an independent clinical validation using a cohort of 30 early pancreatic cancer, 30 chronic pancreatitis and 30 healthy matched-control saliva samples. Two panels of salivary biomarkers, including eleven mRNA biomarkers and two microbial biomarkers were discovered and validated for pancreatic cancer detection. The logistic regression model with the combination of three mRNA biomarkers (ACRV1, DMXL2 and DPM1) yielded a ROC-plot AUC value of 0.974 (95% CI, 0.896 to 0.997; P < 0.0001) with 93.3% sensitivity and 90% specificity in distinguishing pancreatic cancer patients from healthy subjects. The logistic regression model with the combination of two bacterial biomarkers (Neisseria elongata and Streptococcus mitis) yielded a ROC-plot AUC value of 0.895 (95% CI, 0.784 to 0.961; P < 0.0001) with 96.4% sensitivity and 82.1% specificity in distinguishing pancreatic cancer patients from healthy subjects. Importantly, the logistic regression model with the combination of four biomarkers (mRNA biomarkers, ACRV1, DMXL2 and DPM1; bacterial biomarker, S. mitis) could differentiate pancreatic cancer patients from all non-cancer subjects (chronic pancreatitis and healthy control), yielding a ROC-plot AUC value of 0.949 (95% CI, 0.877 to 0.985; P < 0.0001) with 92.9% sensitivity and 85.5% specificity. This study comprehensively compared the salivary transcriptome and microflora between pancreatic cancer and control subjects. We have discovered and validated eleven mRNA biomarkers and two microbial biomarkers for early detection of pancreatic cancer in saliva. The logistic regression model with four salivary biomarkers can detect pancreatic cancer specifically without the complication of chronic pancreatitis. This is the first report demonstrating the value of multiplex salivary biomarkers for the non-invasive detection of a high impact systemic cancer.
Publication Title
Salivary transcriptomic biomarkers for detection of resectable pancreatic cancer.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 19 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
A sensitive assay to identify biomarkers that can accurately diagnose the onset of breast cancer using non-invasively collected clinical specimens is ideal for early detection. In this study, we have conducted a prospective sample collection and retrospective blinded validation (PRoBE design) to evaluate the performance and translational utilities of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer. The Affymetrix HG U133 Plus 2.0 Array and 2D-DIGE were used to profile transcriptomes and proteomes in saliva supernatants respectively. Significant variations of salivary transcriptomic and proteomic profiles were observed between breast cancer patients and healthy controls. Eleven transcriptomic biomarker candidates and two proteomic biomarker candidates were selected for a preclinical validation using an independent sample set. Transcriptomic biomarkers were validated by RT-qPCR and proteomic biomarkers were validated by quantitative protein immunoblot. Eight mRNA biomarkers and one protein biomarker have been validated for breast cancer detection, yielding ROC-plot AUC values between 0.665 and 0.959. This report provides proof of concept of salivary biomarkers for the non-invasive detection of breast cancer. The salivary biomarkers discriminatory power paves the way for a PRoBE-design definitive validation study.
Publication Title
Discovery and preclinical validation of salivary transcriptomic and proteomic biomarkers for the non-invasive detection of breast cancer.
Sample Metadata Fields
Disease
View Samples
GSE32939- Homo sapiens
- 6 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We examined the efffects of ligating CD4 expressed by primary human peripheral blood monocytes with soluble MHC Class II.
Publication Title
CD4 ligation on human blood monocytes triggers macrophage differentiation and enhances HIV infection.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Homo sapiens
- 20 Downloadable Samples
- Affymetrix Human Gene 2.0 ST Array (hugene20st)
Description
Retinoic acid Receptor Beta (RARβ) protein encoded by RARβ gene is a nuclear receptor protein that binds to retinoic acid (RA) to mediate RA function in cellular signalling in embryogenic morphogenesis, cell growth and differentiation. However, the function of RARβ in cancer stem cells (CSCs) maintenance of non-small cell lung cancer (NSCLC) is yet to be determined
Publication Title
No associated publication
Sample Metadata Fields
Specimen part
View Samples- Mus musculus
- 872 Downloadable Samples
Affymetrix HT Mouse Genome 430A Array (htmg430a), Illumina MouseRef-8 v2.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
Genetic architecture of insulin resistance in the mouse.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Homo sapiens
- 770 Downloadable Samples
- Affymetrix Human Genome U219 Array (hgu219)
Description
We analyzed samples from 770 male human subjects who are part of the METSIM study. Ethics Committee of the Northern Savo Hospital District approved the study. All participants gave written informed consent. The population-based cross-sectional METSIM study included 10 197 men, aged from 45 to 73 years, who were randomly selected from the population register of the Kuopio town in eastern Finland (population 95000). Every participant had a 1-day outpatient visit to the Clinical Research Unit at the University of Kuopio, including an interview on the history of previous diseases and current drug treatment and an evaluation of glucose tolerance and cardiovascular risk factors. After 12 h of fasting, a 2 h oral 75 g glucose tolerance test was performed and the blood samples were drawn at 0, 30 and 120 min. Plasma glucose was measured by enzymatic hexokinase photometric assay (Konelab Systems reagents; Thermo Fischer Scientific, Vantaa, Finland). Insulin was determined by immunoassay (ADVIA Centaur Insulin IRI no. 02230141; Siemens Medical Solutions Diagnostics, Tarrytown, NY, USA). Height and weight were measured to the nearest 0.5 cm and 0.1 kg, respectively. Waist circumference (at the midpoint between the lateral iliac crest and lowest rib) and hip circumference (at the level of the trochanter major) were measured to the nearest 0.5 cm. Body composition was determined by bioelectrical impedance (RJL Systems) in subjects in the supine position.
Publication Title
Genetic Regulation of Adipose Gene Expression and Cardio-Metabolic Traits.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples GSE38705- Mus musculus
- 510 Downloadable Samples
- Affymetrix HT Mouse Genome 430A Array (htmg430a)
Description
Identify genes involved in regulation of inflammatory responses and gene-environemnt interactions, in macrophages from a set of mouse inbred strains termed the HMDP. The HMDP is a genetically diverse mapping panel comprised of classical inbred and recombinant inbred wild type mice. The RMA values of genes were used for genome wide association as described in Bennett et al Genome Research 2010.
Publication Title
Unraveling inflammatory responses using systems genetics and gene-environment interactions in macrophages.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 439 Downloadable Samples
- Affymetrix HT Mouse Genome 430A Array (htmg430a), Illumina MouseRef-8 v2.0 expression beadchip
Description
Identify genes in the gonadal adipose tissue whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. The RMA values of genes were used for genome wide association as described in Parks et al Cell Metabolism 2015. These data are used to identify candidate genes at loci associated with obesity and dietary responsiveness.
Publication Title
Genetic architecture of insulin resistance in the mouse.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples- Mus musculus
- 424 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
In several models of obesity-induced diabetes, increased lipid accumulation in the liver has been associated with decreased diabetes susceptibility. For instance, deficiency in leptin receptor (db/db) leads to hyperphagia and obesity in both C57BL/6 and C57BLKS mice but, only on the C57BLKS background do the mice develop beta-cell loss leading to severe diabetes while C57BL/6 mice are relatively resistant. Liver triglyceride levels in the resistant C57BL/6 mice are 3 to 4 fold higher than in C57BLKS.
Publication Title
Systems genetics of susceptibility to obesity-induced diabetes in mice.
Sample Metadata Fields
Sex, Age
View Samples- Mus musculus
- 433 Downloadable Samples
- Affymetrix HT Mouse Genome 430A Array (htmg430a), Illumina MouseRef-8 v2.0 expression beadchip
Description
Identify genes in the liver whose expression is under genetic regulation in the Hybrid Mouse Diversity Panel (HMDP). The HMDP comprises classical inbred and recombinant inbred wild type mice. The RMA values of genes were used for genome wide association as described in Parks et al Cell Metabolism 2015. These data are used to identify candidate genes at loci associated with obesity and dietary responsiveness.
Publication Title
Genetic architecture of insulin resistance in the mouse.
Sample Metadata Fields
Sex, Age, Specimen part
View Samples