Evidence map›Paper›PMID 35931808›Full record

ArticleScientific reports2022

A multiomics disease progression signature of low-risk ccRCC.

Philipp Strauss, Mariell Rivedal, Andreas Scherer, Øystein Eikrem, Sigrid Nakken, Christian Beisland, Leif Bostad, Arnar Flatberg, Eleni Skandalou, Vidar Beisvåg and 2 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.1field-weighted citation impact, top 22% of its field
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

6 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Review
  3. Article
  4. Review
  5. Role of FXR in Renal Physiology and Kidney Diseases.International journal of molecular sciences · 2023
    Review
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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

12 authors at 5 institutions in 2 countries.

Philipp StraussDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway. Philipp.Strauss@uib.no.
Mariell RivedalDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
Andreas SchererSpheromics, 81100, Kontiolahti, Finland.
Øystein EikremDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
Sigrid NakkenDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
Christian BeislandDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
Leif BostadDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
Arnar FlatbergDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology, 7491, Trondheim, Norway.
Eleni SkandalouDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
Vidar BeisvågDepartment of Clinical and Molecular Medicine, Norwegian University of Science and Technology, 7491, Trondheim, Norway.
Jessica FurriolDepartment of Medicine, Haukeland University Hospital, 5021, Bergen, Norway.
Hans-Peter MartiDepartment of Clinical Medicine, University of Bergen, 5021, Bergen, Norway.
University of Bergen · NOHaukeland University Hospital · NOInstitute for Molecular Medicine Finland · FINorwegian University of Science and Technology · NOSt Olav's University Hospital · NO

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Identification of ccRCC likely to progress, despite an apparent low risk at the time of surgery, represents a key clinical issue. From a cohort of adult ccRCC patients (n = 443), we selected low-risk tumors progressing within a 5-years average follow-up (progressors: P, n = 8) and non-progressing (NP) tumors (n = 16). Transcriptome sequencing, miRNA sequencing and proteomics were performed on tissues obtained at surgery. We identified 151 proteins, 1167 mRNAs and 63 miRNAs differentially expressed in P compared to NP low-risk tumors. Pathway analysis demonstrated overrepresentation of proteins related to "LXR/RXR and FXR/RXR Activation", "Acute Phase Response Signaling" in NP compared to P samples. Integrating mRNA, miRNA and proteomic data, we developed a 10-component classifier including two proteins, three genes and five miRNAs, effectively differentiating P and NP ccRCC and capturing underlying biological differences, potentially useful to identify "low-risk" patients requiring closer surveillance and treatment adjustments. Key results were validated by immunohistochemistry, qPCR and data from publicly available databases. Our work suggests that LXR, FXR and macrophage activation pathways could be critically involved in the inhibition of the progression of low-risk ccRCC. Furthermore, a 10-component classifier could support an early identification of apparently low-risk ccRCC patients.

Indexed as

Carcinoma, Renal CellKidney NeoplasmsMicroRNAsAdultBiomarkers, TumorDisease ProgressionGene Expression ProfilingGene Expression Regulation, NeoplasticHumansProteomicsRNA, MessengerBiomarkers, TumorMicroRNAsRNA, Messenger

Identifiers

PMID35931808
PMCPMC9356046
OpenAlexW4290080936

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.