Evidence map›Paper›PMID 38698335›Full record

ArticleBMC genomics2024

Integrated transcriptomics and histopathology approach identifies a subset of rejected donor livers with potential suitability for transplantation.

Ankita Srivastava, Alexandra Manchel, John Waters, Manju Ambelil, Benjamin K Barnhart, Jan B Hoek, Ashesh P Shah, Rajanikanth Vadigepalli

Abstract read
In one paragraph

Article in BMC genomics, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ankita SrivastavaDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Alexandra ManchelDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
John WatersDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Manju AmbelilDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Benjamin K BarnhartDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Jan B HoekDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA.
Ashesh P ShahDepartment of Surgery, Thomas Jefferson University Hospital, Jefferson University Hospitals, Philadelphia, PA, USA.
Rajanikanth VadigepalliDaniel Baugh Institute for Functional Genomics and Computational Biology, Department of Pathology and Genomic Medicine, Thomas Jefferson University, Philadelphia, PA, 19107, USA. Rajanikanth.Vadigepalli@jefferson.edu.

Funding

Alcohol Tissue InjuryT32AA007463 · NIAAA · THOMAS JEFFERSON UNIVERSITY · PI HOEK, JOANNES B, VADIGEPALLI, RAJANIKANTH · 1985 to 2021
$9.1M
Ethanol Effects on the Transcriptional Regulatory Network in Liver Regeneration -R01AA018873 · NIAAA · THOMAS JEFFERSON UNIVERSITY · PI SRIVASTAVA, ANKITA · 2009 to 2025
$8.7M
NIAAA NIH HHS R01 AA018873NIAAA NIH HHS T32 AA007463
6 · The paper itself

Abstract

backgroundLiver transplantation is an effective treatment for liver failure. There is a large unmet demand, even as not all donated livers are transplanted. The clinical selection criteria for donor livers based on histopathological evaluation and liver function tests are variable. We integrated transcriptomics and histopathology to characterize donor liver biopsies obtained at the time of organ recovery. We performed RNA sequencing as well as manual and artificial intelligence-based histopathology (10 accepted and 21 rejected for transplantation).

resultsWe identified two transcriptomically distinct rejected subsets (termed rejected-1 and rejected-2), where rejected-2 exhibited a near-complete transcriptomic overlap with the accepted livers, suggesting acceptability from a molecular standpoint. Liver metabolic functional genes were similarly upregulated, and extracellular matrix genes were similarly downregulated in the accepted and rejected-2 groups compared to rejected-1. The transcriptomic pattern of the rejected-2 subset was enriched for a gene expression signature of graft success post-transplantation. Serum AST, ALT, and total bilirubin levels showed similar overlapping patterns. Additional histopathological filtering identified cases with borderline scores and extensive molecular overlap with accepted donor livers.

conclusionsOur integrated approach identified a subset of rejected donor livers that are likely suitable for transplantation, demonstrating the potential to expand the pool of transplantable livers.

Indexed as

Gene Expression ProfilingLiverLiver TransplantationTissue DonorsAdultFemaleGraft RejectionHumansMaleMiddle AgedTranscriptomeArtificial intelligence-based image analysisFunctional enrichmentHistopathological scoringHuman donor liverLiver transplantationRNAseq

Identifiers

PMID38698335
PMCPMC11067109

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.