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accession-icon GSE58866
Expression data of rat insulinoma cells induced with ER stress +/- IRE1 inhibitor treatment
  • organism-icon Rattus norvegicus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Rat Genome 230 2.0 Array (rat2302)

Description

The Akita mutation (C96Y) in the insulin gene results in early onset diabetes in both humans and mice. Expression of the mutant proinsulin (C96Y) causes endoplasmic reticulum (ER) stress in pancreatic -cells and consequently the cell activates the unfolded protein response (UPR). Since the proinsulin is terminally misfolded however, the ER stress is irremediable and chronic activation of the UPR eventually activates apoptosis in the cell population.

Publication Title

IRE1 inhibition perturbs the unfolded protein response in a pancreatic β-cell line expressing mutant proinsulin, but does not sensitize the cells to apoptosis.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE107509
Gene expression profiling of subclinical acute kidney rejection
  • organism-icon Homo sapiens
  • sample-icon 656 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

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.

Sample Metadata Fields

Specimen part

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accession-icon GSE107503
Gene expression profiling of subclinical acute kidney rejection I
  • organism-icon Homo sapiens
  • sample-icon 529 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Sub-clinical acute rejection (subAR) in kidney transplant recipients (KTR) leads to chronic rejection and graft loss. Non-invasive biomarkers are needed to detect subAR. 307 KTR were enrolled into a multi-center observational study. Precise clinical phenotypes (CP) were used to define subAR. Differential gene expression (DGE) data from peripheral blood samples paired with surveillance biopsies were used to train a Random Forests (RF) model to develop a gene expression profile (GEP) for subAR. A separate cohort of paired samples was used to validate the GEP. Clinical endpoints and gene pathway mapping were used to assess clinical validity and biologic relevance. DGE data from 530 samples (130 subAR) collected from 250 KTR yielded a RF model: AUC 0.85; 0.84 after internal validation with bootstrap resampling. We selected a predicted probability threshold favoring specificity and NPV (87% and 88%) over sensitivity and PPV (64% and 61%, respectively). We tested the locked model/threshold on a separate cohort of 138 KTR undergoing surveillance biopsies at our institution (rejection 42; no rejection 96): NPV 78%; PPV 51%; AUC 0.66. Both the CP and GEP of subAR within the first 12 months following transplantation were independently associated with worse graft outcomes at 24 months, including de novo donor-specific antibody (DSA). Serial GEP tracked with response to treatment of subAR. DGE data from both cohorts mapped to gene pathways indicative of allograft rejection.

Publication Title

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.

Sample Metadata Fields

Specimen part

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accession-icon GSE107506
Gene expression profiling of subclinical acute kidney rejection II
  • organism-icon Homo sapiens
  • sample-icon 127 Downloadable Samples
  • Technology Badge Icon Affymetrix HT HG-U133+ PM Array Plate (hthgu133pluspm)

Description

Sub-clinical acute rejection (subAR) in kidney transplant recipients (KTR) leads to chronic rejection and graft loss. Non-invasive biomarkers are needed to detect subAR. 307 KTR were enrolled into a multi-center observational study. Precise clinical phenotypes (CP) were used to define subAR. Differential gene expression (DGE) data from peripheral blood samples paired with surveillance biopsies were used to train a Random Forests (RF) model to develop a gene expression profile (GEP) for subAR. A separate cohort of paired samples was used to validate the GEP. Clinical endpoints and gene pathway mapping were used to assess clinical validity and biologic relevance. DGE data from 530 samples (130 subAR) collected from 250 KTR yielded a RF model: AUC 0.85; 0.84 after internal validation with bootstrap resampling. We selected a predicted probability threshold favoring specificity and NPV (87% and 88%) over sensitivity and PPV (64% and 61%, respectively). We tested the locked model/threshold on a separate cohort of 138 KTR undergoing surveillance biopsies at our institution (rejection 42; no rejection 96): NPV 78%; PPV 51%; AUC 0.66. Both the CP and GEP of subAR within the first 12 months following transplantation were independently associated with worse graft outcomes at 24 months, including de novo donor-specific antibody (DSA). Serial GEP tracked with response to treatment of subAR. DGE data from both cohorts mapped to gene pathways indicative of allograft rejection.

Publication Title

Development and clinical validity of a novel blood-based molecular biomarker for subclinical acute rejection following kidney transplant.

Sample Metadata Fields

No sample metadata fields

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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)

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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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