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accession-icon GSE40354
Expression analysis of Arabidopsis ein2 and bak1 mutants treated with the elicitors elf18 and Pep2.
  • organism-icon Arabidopsis thaliana
  • sample-icon 51 Downloadable Samples
  • Technology Badge Icon Affymetrix Arabidopsis ATH1 Genome Array (ath1121501)

Description

Recognition of microbial patterns and host derived damage signals by host pattern recognition receptors is a key step in immune activation in multicellular eukaryotes. Here we show how mutations in ethylene signaling and the coreceptor bak1 affect host immune responses triggered by elicitors.

Publication Title

Layered pattern receptor signaling via ethylene and endogenous elicitor peptides during Arabidopsis immunity to bacterial infection.

Sample Metadata Fields

Treatment, Time

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accession-icon GSE11113
Expression profiling of a high-fertility mouse line by microarray analysis and qPCR.
  • organism-icon Mus musculus
  • sample-icon 24 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Expression 430A Array (moe430a)

Description

The objective of the present study was to identify genes that are involved in increasing the ovulation number in mouse line FL1 that had been selected for high fertility performance.

Publication Title

Expression profiling of a high-fertility mouse line by microarray analysis and qPCR.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP201971
RNA-seq analysis of transcriptome reprofiling triggered by different pattern-recognition receptor types
  • organism-icon Arabidopsis thaliana
  • sample-icon 47 Downloadable Samples
  • Technology Badge IconIllumina HiSeq 2000

Description

Plant cell surface receptors sense microbial pathogens by recognizing microbial structures called pathogen or microbe-associated molecular patterns (PAMPs/MAMPs). There are two major types of plant pattern recognition receptors: 1. Leucine-rich repeat receptor proteins (LRR-RP) and LRR receptor kinases (LRR-RK) and 2. Plant receptor proteins and receptor kinases carrying ectopic lysin motifs (LysM-RP and LysM-RK). In this study, Arabidopsis thaliana responses to three different MAMPs, flg22, nlp20, chitin (C6), via their corresponding receptor types, FLS2 (LRR-RK), RLP23 (LRR-RP), CERK1 (LysM-RK) were compared. Our RNA-seq results indicate that a core set of defense-related genes can be activated through perception of different MAMPs. However, there are also notable differences in the transcriptional changes in response to the various elicitors; flg22 causes broader transcriptome changes than nlp20 and C6, and C6 does not cause late transcriptome changes. Overall design: Arabodopsis seedings were treated with water, flg22, nlp20, or C6 and collected after 1h, 6h and 24h. One sample before treatment was also collected. 4 biological repecates were performed.

Publication Title

Comparing Arabidopsis receptor kinase and receptor protein-mediated immune signaling reveals BIK1-dependent differences.

Sample Metadata Fields

Subject, Time

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accession-icon GSE145120
Gene expression data of different SSc subsets
  • organism-icon Homo sapiens
  • sample-icon 190 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

We here used whole blood gene expression profiling to differentiate SSc patients from healthy controls (HC) and to identify a specific gene expression and predictive genes for SSc-overlap syndromes.

Publication Title

Whole blood gene expression profiling distinguishes systemic sclerosis-overlap syndromes from other subsets.

Sample Metadata Fields

Specimen part, Disease, Disease stage

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accession-icon GSE103340
Patient-derived xenograft model identifies clinically relevant subtype-specific features of colorectal cancer
  • organism-icon Homo sapiens
  • sample-icon 71 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Colorectal cancer (CRC) is a heterogeneous disease classified into four consensus molecular subtype (CMSs) with distinct biological and clinical features. This study aims to understand the value of patient-derived xenografts (PDXs) in relation to these CMSs. A total of 42 primary tumors, recurrences and metastases were used to develop PDXs. Detailed genetic analyses were performed on PDXs and corresponding patient tumors to determine relationship and PDX heterogeneity. Out of 42 tumors 22 (52%) showed successfully PDX engraftment, which was biased towards metastases and CMS1 and CMS4 tumors. Importantly, gene expression analysis revealed a clinical relevant association between an engraftment gene signature and prognosis for stage II patients. Moreover, this gene signature revealed an association between Src pathway activation and positive engraftment. Src pathway activity co-aligned with CMS4 and the levels of fibronectin in tumors and was confirmed by pSrc immunohistochemistry. From this analysis we further deduced that decreased cell cycle activity is a prognostic factor for successful engraftment and related to patient prognosis. However, this is not a general phenomenon, but subtype specific as decreased cell cycle activity was highly prognostic for recurrence-free survival within CMS2 but not in CMS1 and CMS4, while it showed an inverse correlation in CMS3. These data illustrate that CRC PDX establishment is biased toward CMS1 and CMS4, which impacts translation of results derived from pre-clinical studies using PDXs. Moreover, our analysis reveals subtype-specific features, pSrc in CMS4 and low Ki67 in CMS2, which provide novel avenues for therapy and diagnosis.

Publication Title

Capturing colorectal cancer inter-tumor heterogeneity in patient-derived xenograft (PDX) models.

Sample Metadata Fields

Sex, Age, Specimen part, Disease, Disease stage

View Samples
accession-icon GSE65682
Genome-wide blood transcriptional profiling in critically ill patients - MARS consortium
  • organism-icon Homo sapiens
  • sample-icon 802 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

The host response in critically ill patients with sepsis, septic shock remains poorly defined. Considerable research has been conducted to accurately distinguish patients with sepsis from those with non-infectious causes of disease. Technological innovations have positioned systems biology at the forefront of biomarker discovery. Analysis of the whole-blood leukocyte transcriptome enables the assessment of thousands of molecular signals beyond simply measuring several proteins in plasma, which for use as biomarkers is important since combinations of biomarkers likely provide more diagnostic accuracy than the measurement of single ones or a few. Evidence suggests that genome-wide transcriptional profiling of blood leukocytes can assist in differentiating between infection and non-infectious causes of severe disease. Of importance, RNA biomarkers have the potential advantage that they can be measured reliably in rapid quantitative reverse transcriptase polymerase chain reaction (qRT-PCR)-based point of care tests.

Publication Title

A molecular biomarker to diagnose community-acquired pneumonia on intensive care unit admission.

Sample Metadata Fields

Sex, Age

View Samples
accession-icon GSE79462
TGF signaling directs serrated adenomas to the mesenchymal colorectal cancer subtype
  • organism-icon Homo sapiens
  • sample-icon 36 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

TGFβ signaling directs serrated adenomas to the mesenchymal colorectal cancer subtype.

Sample Metadata Fields

Specimen part, Treatment

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accession-icon GSE79461
TGF signaling directs serrated adenomas to the mesenchymal colorectal cancer subtype [organoids]
  • organism-icon Homo sapiens
  • sample-icon 20 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

The aim of this study was to determine the effects of TGF at the premalignant stage of CRC development.

Publication Title

TGFβ signaling directs serrated adenomas to the mesenchymal colorectal cancer subtype.

Sample Metadata Fields

Specimen part, Treatment

View Samples
accession-icon GSE79460
TGF signaling directs serrated adenomas to the mesenchymal colorectal cancer subtype [adenomas]
  • organism-icon Homo sapiens
  • sample-icon 16 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Colorectal cancer can be divided into four consensus molecular subtypes, which might associate with distinct precursor lesions. The aim of this study was to determine the subtype affiliation of two types of colorectal adenomas: tubular adenomas (TAs) and sessile serrated adenomas (SSAs) and to determine the activity of TGF signaling and the role of this cytokine in subtype affiliation.

Publication Title

TGFβ signaling directs serrated adenomas to the mesenchymal colorectal cancer subtype.

Sample Metadata Fields

Specimen part

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accession-icon GSE100550
Consensus Molecular Subtypes of colorectal cancer are recapitulated in in vitro and in vivo models
  • organism-icon Homo sapiens
  • sample-icon 103 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Consensus molecular subtypes of colorectal cancer are recapitulated in in vitro and in vivo models.

Sample Metadata Fields

Specimen part, Disease, Disease stage, Cell line, Subject

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

fund-icon Fund the CCDL

Developed by the Childhood Cancer Data Lab

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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