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accession-icon GSE94417
An integrative transcriptomic and clinical score for mortality prediction in severe alcoholic hepatitis treated with corticosteroids
  • organism-icon Homo sapiens
  • sample-icon 195 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

This SuperSeries is composed of the SubSeries listed below.

Publication Title

Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE103580
Transcriptome profiles of liver biopsy tissues from patients with various stages of alcoholic liver disease
  • organism-icon Homo sapiens
  • sample-icon 86 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Corticosteroids are the current standard of care to improve short-term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre-treatment predictors are lacking. We developed 123-gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA-approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring-based gene expressoin risk classification is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid

Publication Title

Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.

Sample Metadata Fields

Specimen part, Disease

View Samples
accession-icon GSE94397
Transcriptome profiles of liver biopsy tissues from sever alcoholic hepatitis patients (derivation cohort)
  • organism-icon Homo sapiens
  • sample-icon 71 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Corticosteroids are the current standard of care to improve short-term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre-treatment predictors are lacking. We developed 123-gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA-approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring-based gene expressoin risk classificatoin is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid

Publication Title

Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE94399
Transcriptome profiles of liver biopsy tissues from sever alcoholic hepatitis patients (validation cohort, Brussels)
  • organism-icon Homo sapiens
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U219 Array (hgu219)

Description

Corticosteroids are the current standard of care to improve short_term mortality in severe alcoholic hepatitis (AH), although nearly 40% of the patients do not respond and accurate pre_treatment predictors are lacking. We developed 123_gene prognostic score based on molecular and clinical variables before initiation of corticosteroids. Furthermore, The gene signature was implemented in an FDA_approved platform (NanoString), and verified for technical validity and prognostic capability. Here we demonstrated that a Nanostring_based gene expressoin risk classificatoin is useful to predict mortality in patients with severe alcoholic hepatitis who were treated by corticosteroid

Publication Title

Combination of Gene Expression Signature and Model for End-Stage Liver Disease Score Predicts Survival of Patients With Severe Alcoholic Hepatitis.

Sample Metadata Fields

No sample metadata fields

View Samples
accession-icon GSE60542
Revisiting the transcriptional analysis of primary tumors and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer
  • organism-icon Homo sapiens
  • sample-icon 88 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)

Description

The biology underlying nodal metastasis is poorly understood. Transcriptome profiling has helped to characterize both primary tumors seeding nodal metastasis and the metastasis themselves. The interpretation of these data, however, is not without ambiguities. Here we profiled the transcriptomes of 17 papillary thyroid cancer (PTC) nodal metastases, associated primary tumors and primary tumors from N0 patients. We also included patient-matched normal thyroid and lymph node samples as controls to address some limits of previous studies. We found that the transcriptomes of patient-matched primary tumors and metastases were more similar than of unrelated metastases/primary pairs, a result also reported in other organ systems, and that part of this similarity reflected patient background. We found that the comparison of patient-matched primary tumors and metastases was heavily confounded by the presence of lymphoid tissues in the metastasis samples. An original data adjustment procedure was developed to circumvent this problem. It revealed a differential expression of stroma-related gene expression signatures also regulated in other organ systems. The comparison of N0 vs. N+ primary tumors uncovered a signal irreproducible across independent PTC datasets. This signal was also detectable when comparing the normal thyroid tissues adjacent to N0 and N+ tumors, suggesting a cohort specific bias also likely to be present in previous studies with similar statistical power. Classification of N0 vs. N+ yielded an accuracy of 63%, but additional statistical controls not presented in previous studies, revealed that this is likely to occur by chance alone. To address this issue, we used large datasets from The Cancer Genome Atlas and showed that N0 vs. N+ classification rates could not be reached randomly for most cancers. Yet, it was significant, but of limited accuracy (<70%) for thyroid, breast and head and neck cancers.

Publication Title

Revisiting the transcriptional analysis of primary tumours and associated nodal metastases with enhanced biological and statistical controls: application to thyroid cancer.

Sample Metadata Fields

Sex

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accession-icon GSE43556
MicroRNA-34a regulates cardiac ageing and function
  • organism-icon Mus musculus
  • sample-icon 8 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

We compared the heart of 6-weeks-old mice (young) with 18-months-old mice (old)

Publication Title

MicroRNA-34a regulates cardiac ageing and function.

Sample Metadata Fields

Age, Specimen part

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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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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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