Alternate metabolic programs define regional variation of relevant biological features in renal cell carcinoma progression

Samira A. Brooks, Amir H. Khandani, Julia R. Fielding, Weili Lin, Tiffany Sills, Yueh Lee, Alexandra Arreola, Mathew I. Milowsky, Eric M. Wallen, Michael E. Woods, Angie B. Smith, Mathew E. Nielsen, Joel S. Parker, David S. Lalush, W. Kimryn Rathmell

Research output: Contribution to journalArticle

12 Citations (Scopus)

Abstract

Purpose: Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans. Experimental Design: ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis. Results: Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA- and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype. Conclusions: Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease.

Original languageEnglish (US)
Pages (from-to)2950-2959
Number of pages10
JournalClinical Cancer Research
Volume22
Issue number12
DOIs
StatePublished - Jun 15 2016

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Renal Cell Carcinoma
Neoplasms
Glucose
Pentose Phosphate Pathway
Genetic Heterogeneity
Microarray Analysis
Metabolic Networks and Pathways
Microvessels
Research Design
Magnetic Resonance Spectroscopy
Magnetic Resonance Imaging
Gene Expression
Genes

ASJC Scopus subject areas

  • Oncology
  • Cancer Research

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Alternate metabolic programs define regional variation of relevant biological features in renal cell carcinoma progression. / Brooks, Samira A.; Khandani, Amir H.; Fielding, Julia R.; Lin, Weili; Sills, Tiffany; Lee, Yueh; Arreola, Alexandra; Milowsky, Mathew I.; Wallen, Eric M.; Woods, Michael E.; Smith, Angie B.; Nielsen, Mathew E.; Parker, Joel S.; Lalush, David S.; Rathmell, W. Kimryn.

In: Clinical Cancer Research, Vol. 22, No. 12, 15.06.2016, p. 2950-2959.

Research output: Contribution to journalArticle

Brooks, SA, Khandani, AH, Fielding, JR, Lin, W, Sills, T, Lee, Y, Arreola, A, Milowsky, MI, Wallen, EM, Woods, ME, Smith, AB, Nielsen, ME, Parker, JS, Lalush, DS & Rathmell, WK 2016, 'Alternate metabolic programs define regional variation of relevant biological features in renal cell carcinoma progression', Clinical Cancer Research, vol. 22, no. 12, pp. 2950-2959. https://doi.org/10.1158/1078-0432.CCR-15-2115
Brooks, Samira A. ; Khandani, Amir H. ; Fielding, Julia R. ; Lin, Weili ; Sills, Tiffany ; Lee, Yueh ; Arreola, Alexandra ; Milowsky, Mathew I. ; Wallen, Eric M. ; Woods, Michael E. ; Smith, Angie B. ; Nielsen, Mathew E. ; Parker, Joel S. ; Lalush, David S. ; Rathmell, W. Kimryn. / Alternate metabolic programs define regional variation of relevant biological features in renal cell carcinoma progression. In: Clinical Cancer Research. 2016 ; Vol. 22, No. 12. pp. 2950-2959.
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abstract = "Purpose: Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans. Experimental Design: ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis. Results: Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA- and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype. Conclusions: Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease.",
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AU - Brooks, Samira A.

AU - Khandani, Amir H.

AU - Fielding, Julia R.

AU - Lin, Weili

AU - Sills, Tiffany

AU - Lee, Yueh

AU - Arreola, Alexandra

AU - Milowsky, Mathew I.

AU - Wallen, Eric M.

AU - Woods, Michael E.

AU - Smith, Angie B.

AU - Nielsen, Mathew E.

AU - Parker, Joel S.

AU - Lalush, David S.

AU - Rathmell, W. Kimryn

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N2 - Purpose: Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans. Experimental Design: ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis. Results: Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA- and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype. Conclusions: Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease.

AB - Purpose: Clear cell renal cell carcinoma (ccRCC) has recently been redefined as a highly heterogeneous disease. In addition to genetic heterogeneity, the tumor displays risk variability for developing metastatic disease, therefore underscoring the urgent need for tissue-based prognostic strategies applicable to the clinical setting. We have recently employed the novel PET/magnetic resonance (MR) image modality to enrich our understanding of how tumor heterogeneity can relate to gene expression and tumor biology to assist in defining individualized treatment plans. Experimental Design: ccRCC patients underwent PET/MR imaging, and these images subsequently used to identify areas of varied intensity for sampling. Samples from 8 patients were subjected to histologic, immunohistochemical, and microarray analysis. Results: Tumor subsamples displayed a range of heterogeneity for common features of hypoxia-inducible factor expression and microvessel density, as well as for features closely linked to metabolic processes, such as GLUT1 and FBP1. In addition, gene signatures linked with disease risk (ccA and ccB) also demonstrated variable heterogeneity, with most tumors displaying a dominant panel of features across the sampled regions. Intriguingly, the ccA- and ccB-classified samples corresponded with metabolic features and functional imaging levels. These correlations further linked a variety of metabolic pathways (i.e., the pentose phosphate and mTOR pathways) with the more aggressive, and glucose avid ccB subtype. Conclusions: Higher tumor dependency on exogenous glucose accompanies the development of features associated with the poor risk ccB subgroup. Linking these panels of features may provide the opportunity to create functional maps to enable enhanced visualization of the heterogeneous biologic processes of an individual's disease.

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