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dc.contributor.authorStrauss, Philipp
dc.contributor.authorRivedal, Mariell
dc.contributor.authorScherer, Andreas
dc.contributor.authorEikrem, Øystein Solberg
dc.contributor.authorNakken, Sigrid
dc.contributor.authorBeisland, Christian
dc.contributor.authorBostad, Leif
dc.contributor.authorFlatberg, Arnar
dc.contributor.authorSkandalou, Eleni
dc.contributor.authorBeisvag, Vidar
dc.contributor.authorFurriol, Jessica
dc.contributor.authorMarti, Hans Peter
dc.date.accessioned2022-11-22T07:53:48Z
dc.date.available2022-11-22T07:53:48Z
dc.date.created2022-10-24T10:33:37Z
dc.date.issued2022
dc.identifier.citationScientific Reports. 2022, 12 .en_US
dc.identifier.issn2045-2322
dc.identifier.urihttps://hdl.handle.net/11250/3033249
dc.description.abstractClear 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.en_US
dc.language.isoengen_US
dc.publisherNature Researchen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleA multiomics disease progression signature of low-risk ccRCCen_US
dc.title.alternativeA multiomics disease progression signature of low-risk ccRCCen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.description.versionpublishedVersionen_US
dc.source.pagenumber15en_US
dc.source.volume12en_US
dc.source.journalScientific Reportsen_US
dc.identifier.doi10.1038/s41598-022-17755-2
dc.identifier.cristin2064244
cristin.ispublishedtrue
cristin.fulltextoriginal
cristin.qualitycode1


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Navngivelse 4.0 Internasjonal
Except where otherwise noted, this item's license is described as Navngivelse 4.0 Internasjonal