Prostate cancer radiogenomics reveals proliferative gene expression programs associated with distinct MRI-based hypoxia levels.

Digital histopathology Gene expression Gene signature Hypoxia MR-imaging Prostate cancer Radiogenomics

Journal

Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
ISSN: 1879-0887
Titre abrégé: Radiother Oncol
Pays: Ireland
ID NLM: 8407192

Informations de publication

Date de publication:
Nov 2023
Historique:
received: 15 06 2023
revised: 21 08 2023
accepted: 22 08 2023
pubmed: 29 8 2023
medline: 29 8 2023
entrez: 28 8 2023
Statut: ppublish

Résumé

The biology behind individual hypoxia levels in patient tumors is poorly understood. Here, we used radiogenomics to identify associations between magnetic resonance imaging (MRI)-based hypoxia levels and biological processes derived from gene expression data in prostate cancer. For 85 prostate cancer patients, MRI-based hypoxia images were constructed by combining diffusion-weighted images reflecting oxygen consumption and supply. The ability to differentiate hypoxia levels in these images was verified by comparison with matched biopsy sections stained for the hypoxia marker pimonidazole. For MRI-defined hypoxia levels, corresponding hypoxic fractions were calculated and correlated with biopsy gene expression profiles. Biological processes were predicted by gene set enrichment analysis (GSEA) and validated by immunohistochemistry (Ki67 proliferation marker, reactive stroma grade) and RT-PCR (MYC). Genes with correlation between expression level and hypoxic fraction were identified for 56 MRI-based hypoxia levels. At all levels, GSEA identified proliferation as the predominant biological process enriched among the correlating genes. Two independent proliferative gene signatures were developed. The Peak1 signature, upregulated at moderate/severe hypoxia, reflected MYC upregulation and high Ki67-proliferation index of cancer cells in pimonidazole-positive regions. The Peak2 signature, upregulated at mild to non-hypoxic levels, was associated with fibroblast gene signature and reactive stroma grade. High scores of both Peak1 and Peak2 indicated elevated risk of biochemical recurrence in multiple cohorts. Radiogenomics identified two gene expression programs activated at different hypoxia levels, reflecting proliferation of cancer cells and stroma cells. Genes involved in these programs could be candidate targets for intervention.

Sections du résumé

BACKGROUND AND PURPOSE OBJECTIVE
The biology behind individual hypoxia levels in patient tumors is poorly understood. Here, we used radiogenomics to identify associations between magnetic resonance imaging (MRI)-based hypoxia levels and biological processes derived from gene expression data in prostate cancer.
MATERIALS AND METHODS METHODS
For 85 prostate cancer patients, MRI-based hypoxia images were constructed by combining diffusion-weighted images reflecting oxygen consumption and supply. The ability to differentiate hypoxia levels in these images was verified by comparison with matched biopsy sections stained for the hypoxia marker pimonidazole. For MRI-defined hypoxia levels, corresponding hypoxic fractions were calculated and correlated with biopsy gene expression profiles. Biological processes were predicted by gene set enrichment analysis (GSEA) and validated by immunohistochemistry (Ki67 proliferation marker, reactive stroma grade) and RT-PCR (MYC).
RESULTS RESULTS
Genes with correlation between expression level and hypoxic fraction were identified for 56 MRI-based hypoxia levels. At all levels, GSEA identified proliferation as the predominant biological process enriched among the correlating genes. Two independent proliferative gene signatures were developed. The Peak1 signature, upregulated at moderate/severe hypoxia, reflected MYC upregulation and high Ki67-proliferation index of cancer cells in pimonidazole-positive regions. The Peak2 signature, upregulated at mild to non-hypoxic levels, was associated with fibroblast gene signature and reactive stroma grade. High scores of both Peak1 and Peak2 indicated elevated risk of biochemical recurrence in multiple cohorts.
CONCLUSION CONCLUSIONS
Radiogenomics identified two gene expression programs activated at different hypoxia levels, reflecting proliferation of cancer cells and stroma cells. Genes involved in these programs could be candidate targets for intervention.

Identifiants

pubmed: 37640161
pii: S0167-8140(23)89769-9
doi: 10.1016/j.radonc.2023.109875
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

109875

Informations de copyright

Copyright © 2023 Elsevier B.V. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Auteurs

Vilde Eide Skingen (VE)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway.

Tord Hompland (T)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway.

Christina Sæten Fjeldbo (CS)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway.

Unn Beate Salberg (UB)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway.

Hanna Helgeland (H)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway.

Harald Bull Ragnum (HB)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway; Department of Oncology and Hematology, Telemark Hospital Trust, Skien, Norway.

Eva-Katrine Aarnes (EK)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway.

Ljiljana Vlatkovic (L)

Department of Pathology, Oslo University Hospital, Oslo, Norway.

Knut Håkon Hole (KH)

Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.

Therese Seierstad (T)

Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway.

Heidi Lyng (H)

Department of Radiation Biology, Oslo University Hospital, Oslo, Norway; Department of Physics, University of Oslo, Oslo, Norway. Electronic address: heidi.lyng@rr-research.no.

Classifications MeSH