Non-coding RNA and gene expression analyses of papillary renal neoplasm with reverse polarity (PRNRP) reveal distinct pathological mechanisms from other renal neoplasms.

Renal cancer miRNA papillary renal neoplasm with reversed polarity pathway analysis transcriptome

Journal

Pathology
ISSN: 1465-3931
Titre abrégé: Pathology
Pays: England
ID NLM: 0175411

Informations de publication

Date de publication:
07 Feb 2024
Historique:
received: 09 06 2023
revised: 25 10 2023
accepted: 14 11 2023
medline: 28 2 2024
pubmed: 28 2 2024
entrez: 27 2 2024
Statut: aheadofprint

Résumé

Papillary renal neoplasm with reversed polarity (PRNRP) is a recently described rare renal neoplasm. Traditionally, it was considered a variant of papillary renal cell carcinoma (PRCC). However, several studies reported significant differences between PRNRP and PRCC in terms of clinical, morphological, immunohistochemical and molecular features. Nonetheless, PRNRP remains a poorly understood entity. We used microarray analysis to elucidate the non-coding RNA (ncRNA) and gene expression profiles of 10 PRNRP cases and compared them with other renal neoplasms. Unsupervised cluster analysis showed that PRNRP had distinct expression profiles from either clear cell renal cell carcinoma (ccRCC) or PRCC cases at the level of ncRNA but were less distinct at the level of gene expression. An integrated omic approach determined miRNA:gene interactions that distinguished PRNRP from PRCC and we validated 10 differentially expressed miRNAs and six genes by quantitative RT-PCR. We found that levels of the miRNAs, miR-148a, miR-375 and miR-429, were up-regulated in PRNRP cases compared to ccRCC and PRCC. miRNA target genes, including KRAS and VEGFA oncogenes, and CXCL8, which regulates VEGFA, were also differentially expressed between renal neoplasms. Gene set enrichment analysis (GSEA) determined different activation of metabolic pathways between PRNRP and PRCC cases. Overall, this study is by far the largest molecular study of PRNRP cases and the first to investigate either ncRNA expression or their gene expression by microarray assays.

Identifiants

pubmed: 38413252
pii: S0031-3025(24)00054-0
doi: 10.1016/j.pathol.2023.11.013
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.

Auteurs

Stéphane Nemours (S)

Biogipuzkoa Health Research Institute, Oncology Area, Molecular Oncology Group, San Sebastian, Spain.

María Armesto (M)

Biogipuzkoa Health Research Institute, Oncology Area, Molecular Oncology Group, San Sebastian, Spain.

María Arestín (M)

Biogipuzkoa Health Research Institute, Oncology Area, Molecular Oncology Group, San Sebastian, Spain.

Claudia Manini (C)

Department of Pathology, San Giovanni Bosco Hospital, ASL Città di Torino, Turin, Italy; Department of Sciences of Public Health and Pediatrics, University of Turin, Italy.

Doriana Giustetto (D)

Department of Pathology, Maria Victoria Hospital, ASL Città di Torino, Turin, Italy.

Maris Sperga (M)

Department of Pathology, Stradin's University, Riga, Latvia.

Kristyna Pivovarcikova (K)

Department of Pathology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic.

Delia Pérez-Montiel (D)

Department of Pathology, National Institute of Cancer, Mexico City, Mexico.

Ondrej Hes (O)

Department of Pathology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic.

Michal Michal (M)

Department of Pathology, Faculty of Medicine in Pilsen, Charles University, Pilsen, Czech Republic; Bioptical Laboratory Ltd, Pilsen, Czech Republic.

José I López (JI)

Biocruces-Bizkaia Health Research Institute, Barakaldo, Spain.

Charles H Lawrie (CH)

Biogipuzkoa Health Research Institute, Oncology Area, Molecular Oncology Group, San Sebastian, Spain; IKERBASQUE, Basque Foundation for Science, Bilbao, Spain; Sino-Swiss Institute of Advanced Technology (SSIAT), University of Shanghai, Shanghai, China; Radcliffe Department of Medicine, University of Oxford, Oxford, UK. Electronic address: charles.lawrie@biodonostia.org.

Classifications MeSH