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Mus musculus
24 Downloadable Samples
Illumina HiSeq 1000
Description
This dataset describe the transcriptomic profiling of cecum, stomach and ileum from wild type, cdx2 conditional knock out and cdx2 ; apc deficient mice, by mRNA-seq. Each condition was analyzed in triplicated experiment to analyze the role of cdx2 in colorectal cancer susceptibilities Overall design: Biological samples from dissected tissue were tested by RNASeq in triplicates resulting into a total of 24 samples.
Publication Title
The Cdx2 homeobox gene suppresses intestinal tumorigenesis through non-cell-autonomous mechanisms.
Sample Metadata Fields
Specimen part, Treatment, Subject
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GSE64385- Homo sapiens
- 12 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
These experiments were designed as a benchmark tool for deconvolution methods. 5 immune cell populations were sorted from 3 healthy donors' peripheral bloods. Peripheral Blood Mononuclear Cells (PBCMs) and PolymorphoNuclear Cells (PMN) were separated using gradient centrifugation. T cells (DAPI-/CD3+/CD14-/CD19-/CD56-), monocytes (DAPI-/CD3-/CD14+/CD19-/CD56-), B cells (DAPI-/CD3-/CD14-/CD19+/CD56-) and NK cells (DAPI-/CD3-/CD14-/CD19-/CD56+) were FACS-sorted from PBMCs and neutrophils (DAPI-/CD66b+/CD19-/CD3-/CD56-/CD14-) were sorted from PMNs. RNA was extracted from the purified cell population, as well as from the HCT116 colon cancer cell line. RNAs from pure populations were then mixed in various proportions.
Publication Title
Estimating the population abundance of tissue-infiltrating immune and stromal cell populations using gene expression.
Sample Metadata Fields
Cell line
View Samples- Homo sapiens
- 78 Downloadable Samples
- Illumina HiSeq 2000
Description
Micro-RNA sequencing of adrenocortical tumors and normal adrenal samples. Overall design: miRNA sequencing of 45 adrenocortical carcinomas (ACC), 30 adrenocortical adenomas (ACA) and 3 normal adrenal samples.
Publication Title
Integrated genomic characterization of adrenocortical carcinoma.
Sample Metadata Fields
Sex, Specimen part, Subject
View Samples- Homo sapiens
- 23 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We have performed gene expression microarray analysis to profile transcriptomic signatures affected by EtOH in human dental pulp stem cells
Publication Title
Genome-wide transcriptomic alterations induced by ethanol treatment in human dental pulp stem cells (DPSCs).
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 16 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We have performed gene expression microarry analysis to profile molecular alterations in normal human oral keratinocytes that are induced by EtOH and/or nicotine. Our goal is to examine molecular signatures that are dysregulated by EtOH or nicotine and define the effects of co-use of alcohol and nicotine on normal oral epithelial cells and potentially on carcinogenesis.
Publication Title
Gene expression signatures affected by ethanol and/or nicotine in normal human normal oral keratinocytes (NHOKs).
Sample Metadata Fields
Specimen part
View Samples- Homo sapiens
- 18 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
Transcriptome analysis of partially degraded and fragmented RNA samples from body fluids
Publication Title
Exon-level expression profiling: a comprehensive transcriptome analysis of oral fluids.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 10 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
We have performed gene expression microarray analysis to profile transcriptomic signatures affected by EtOH during neural differentiation of human embryonic stem cells
Publication Title
Molecular effect of ethanol during neural differentiation of human embryonic stem cells <i>in vitro.</i>
Sample Metadata Fields
Specimen part
View Samples- 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 GSE13364- Mus musculus
- 6 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
Microarray analysis was performed on BWF1 mice spleenocyte cells in control and pCONS treated mice.
Publication Title
Distinct gene signature revealed in white blood cells, CD4(+) and CD8(+) T cells in (NZBx NZW) F1 lupus mice after tolerization with anti-DNA Ig peptide.
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
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