Literature DB >> 23142657

Subtype-specific response to bevacizumab is reflected in the metabolome and transcriptome of breast cancer xenografts.

Eldrid Borgan1, Evita M Lindholm, Siver Moestue, Gunhild M Mælandsmo, Ole Christian Lingjærde, Ingrid S Gribbestad, Anne-Lise Børresen-Dale, Olav Engebraaten, Therese Sørlie.   

Abstract

Antiangiogenic therapy with bevacizumab has shown varying results in breast cancer clinical trials. Identifying robust biomarkers for selecting patients who may benefit from such treatment and for monitoring response is important for the future use of bevacizumab. Two established xenograft models representing basal-like and luminal-like breast cancer were used to study bevacizumab treatment response on the metabolic and gene expression levels. Tumor samples were obtained from mice treated with bevacizumab, doxorubicin or a combination of the two drugs, and high resolution magic angle spinning magnetic resonance spectroscopy and gene expression microarray analysis was performed. Combination treatment with bevacizumab showed the strongest growth inhibiting effect in basal-like tumors, and this was reflected by a significant change in the metabolomic and transcriptomic profiles. In the luminal-like xenografts, addition of bevacizumab did not improve the effect of doxorubicin. On the global transcriptomic level, the largest gene expression changes were observed for the most efficient treatment in both models. Glycerophosphocholine showed opposite response in the treated xenografts compared with untreated controls; lower in basal-like and higher in luminal-like tumors. Comparing combination therapy with doxorubicin monotherapy in basal-like xenografts, 14 genes showed significant differential expression, including very low density lipoprotein receptor (VLDLR) and hemoglobin, theta 1 (HBQ1). Bevacizumab-treated tumors were associated with a more hypoxic phenotype, while no evidence was found for associations between bevacizumab treatment and vascular invasion or tumor grade. This study underlines the importance of characterizing biological differences between subtypes of breast cancer to identify personalized biomarkers for improved patient stratification and evaluation of response to therapy.
Copyright © 2012 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.

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Year:  2012        PMID: 23142657      PMCID: PMC5528408          DOI: 10.1016/j.molonc.2012.10.005

Source DB:  PubMed          Journal:  Mol Oncol        ISSN: 1574-7891            Impact factor:   6.603


  47 in total

1.  Missing value estimation methods for DNA microarrays.

Authors:  O Troyanskaya; M Cantor; G Sherlock; P Brown; T Hastie; R Tibshirani; D Botstein; R B Altman
Journal:  Bioinformatics       Date:  2001-06       Impact factor: 6.937

2.  Use of within-array replicate spots for assessing differential expression in microarray experiments.

Authors:  Gordon K Smyth; Joëlle Michaud; Hamish S Scott
Journal:  Bioinformatics       Date:  2005-01-18       Impact factor: 6.937

3.  Bevacizumab for advanced breast cancer: all tied up with a RIBBON?

Authors:  Harold J Burstein
Journal:  J Clin Oncol       Date:  2011-03-07       Impact factor: 44.544

4.  Neoadjuvant chemotherapy of locally advanced breast cancer: predicting response with in vivo (1)H MR spectroscopy--a pilot study at 4 T.

Authors:  Sina Meisamy; Patrick J Bolan; Eva H Baker; Robin L Bliss; Evin Gulbahce; Lenore I Everson; Michael T Nelson; Tim H Emory; Todd M Tuttle; Douglas Yee; Michael Garwood
Journal:  Radiology       Date:  2004-11       Impact factor: 11.105

5.  High-resolution magic angle spinning MRS of breast cancer tissue.

Authors:  Beathe Sitter; Ursula Sonnewald; Manfred Spraul; Hans E Fjösne; Ingrid S Gribbestad
Journal:  NMR Biomed       Date:  2002-08       Impact factor: 4.044

6.  Molecular causes of the aberrant choline phospholipid metabolism in breast cancer.

Authors:  Kristine Glunde; Chunfa Jie; Zaver M Bhujwalla
Journal:  Cancer Res       Date:  2004-06-15       Impact factor: 12.701

7.  Thrombospondins use the VLDL receptor and a nonapoptotic pathway to inhibit cell division in microvascular endothelial cells.

Authors:  Anush Oganesian; Lucas C Armstrong; Mary M Migliorini; Dudley K Strickland; Paul Bornstein
Journal:  Mol Biol Cell       Date:  2007-11-21       Impact factor: 4.138

Review 8.  Modelling breast cancer: one size does not fit all.

Authors:  Tracy Vargo-Gogola; Jeffrey M Rosen
Journal:  Nat Rev Cancer       Date:  2007-09       Impact factor: 60.716

9.  Response of choline metabolites to docetaxel therapy is quantified in vivo by localized (31)P MRS of human breast cancer xenografts and in vitro by high-resolution (31)P NMR spectroscopy of cell extracts.

Authors:  David L Morse; Natarajan Raghunand; Pooja Sadarangani; Shiva Murthi; Constantin Job; Sam Day; Christine Howison; Robert J Gillies
Journal:  Magn Reson Med       Date:  2007-08       Impact factor: 4.668

10.  GOrilla: a tool for discovery and visualization of enriched GO terms in ranked gene lists.

Authors:  Eran Eden; Roy Navon; Israel Steinfeld; Doron Lipson; Zohar Yakhini
Journal:  BMC Bioinformatics       Date:  2009-02-03       Impact factor: 3.169

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  14 in total

Review 1.  Focus on the glycerophosphocholine pathway in choline phospholipid metabolism of cancer.

Authors:  Kanchan Sonkar; Vinay Ayyappan; Caitlin M Tressler; Oluwatobi Adelaja; Ruoqing Cai; Menglin Cheng; Kristine Glunde
Journal:  NMR Biomed       Date:  2019-06-11       Impact factor: 4.044

2.  Subtype-specific response to bevacizumab is reflected in the metabolome and transcriptome of breast cancer xenografts.

Authors:  Eldrid Borgan; Evita M Lindholm; Siver Moestue; Gunhild M Mælandsmo; Ole Christian Lingjærde; Ingrid S Gribbestad; Anne-Lise Børresen-Dale; Olav Engebraaten; Therese Sørlie
Journal:  Mol Oncol       Date:  2012-10-23       Impact factor: 6.603

3.  Metabolic Signatures of Human Breast Cancer.

Authors:  Prachi Mishra; Stefan Ambs
Journal:  Mol Cell Oncol       Date:  2015 Jul-Sep

4.  The future of NMR metabolomics in cancer therapy: towards personalizing treatment and developing targeted drugs?

Authors:  Marie S A Palmnas; Hans J Vogel
Journal:  Metabolites       Date:  2013-05-17

5.  An 18-gene signature for vascular invasion is associated with aggressive features and reduced survival in breast cancer.

Authors:  Monica Mannelqvist; Elisabeth Wik; Ingunn M Stefansson; Lars A Akslen
Journal:  PLoS One       Date:  2014-06-06       Impact factor: 3.240

6.  A serum metabolomic fingerprint of bevacizumab and temsirolimus combination as first-line treatment of metastatic renal cell carcinoma.

Authors:  Elodie Jobard; Ellen Blanc; Sylvie Négrier; Bernard Escudier; Gwenaelle Gravis; Christine Chevreau; Bénédicte Elena-Herrmann; Olivier Trédan
Journal:  Br J Cancer       Date:  2015-09-15       Impact factor: 7.640

Review 7.  Monitoring for Response to Antineoplastic Drugs: The Potential of a Metabolomic Approach.

Authors:  Jodi Rattner; Oliver F Bathe
Journal:  Metabolites       Date:  2017-11-16

8.  Development of a radiosensitivity gene signature for patients with soft tissue sarcoma.

Authors:  Zaixiang Tang; Qinghua Zeng; Yan Li; Xinyan Zhang; Jinlu Ma; Mark J Suto; Bo Xu; Nengjun Yi
Journal:  Oncotarget       Date:  2017-04-18

9.  Re-expression of miR-200c suppresses proliferation, colony formation and in vivo tumor growth of murine claudin-low mammary tumor cells.

Authors:  Robert Jones; Katrina Watson; Anthony Bruce; Sarah Nersesian; Jenna Kitz; Roger Moorehead
Journal:  Oncotarget       Date:  2017-04-04

10.  Feasibility of MR metabolomics for immediate analysis of resection margins during breast cancer surgery.

Authors:  Tone F Bathen; Brigitte Geurts; Beathe Sitter; Hans E Fjøsne; Steinar Lundgren; Lutgarde M Buydens; Ingrid S Gribbestad; Geert Postma; Guro F Giskeødegård
Journal:  PLoS One       Date:  2013-04-17       Impact factor: 3.240

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