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Protein signature predicts response to neoadjuvant treatment with chemotherapy and bevacizumab in HER2-negative breast cancers

Haugen, Mads H. ; Lingjærde, Ole Christian ; Hedenfalk, Ingrid LU orcid ; Garred, Øystein ; Borgen, Elin ; Loman, Niklas LU ; Hatschek, Thomas ; Børresen-Dale, Anne Lise ; Naume, Bjørn and Mills, Gordon B. , et al. (2021) In JCO Precision Oncology 5. p.286-306
Abstract

PURPOSE Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS In the NeoAva phase II clinical trial, patients (N = 132) with large (= 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression... (More)

PURPOSE Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS In the NeoAva phase II clinical trial, patients (N = 132) with large (= 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. RESULTS We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P< .001) and in patients with low RCB (P<.001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P < .001) in an independent phase II clinical trial (PROMIX). CONCLUSION Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.

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Contribution to journal
publication status
published
subject
in
JCO Precision Oncology
volume
5
pages
21 pages
publisher
American Society of Clinical Oncology
external identifiers
  • pmid:34036235
  • scopus:85101718935
ISSN
2473-4284
DOI
10.1200/PO.20.00086
language
English
LU publication?
yes
id
f7ce7082-c3b7-49a6-a1d0-2d347ea135a0
date added to LUP
2021-03-16 08:49:10
date last changed
2024-05-17 06:00:22
@article{f7ce7082-c3b7-49a6-a1d0-2d347ea135a0,
  abstract     = {{<p>PURPOSE Antiangiogenic therapy using bevacizumab has proven effective for a number of cancers; however, in breast cancer (BC), there is an unmet need to identify patients who benefit from such treatment. PATIENTS AND METHODS In the NeoAva phase II clinical trial, patients (N = 132) with large (= 25 mm) human epidermal growth factor receptor 2 (HER2)-negative primary tumors were randomly assigned 1:1 to treatment with neoadjuvant chemotherapy (CTx) alone or in combination with bevacizumab (Bev plus CTx). The ratio of the tumor size after relative to before treatment was calculated into a continuous response scale. Tumor biopsies taken prior to neoadjuvant treatment were analyzed by reverse-phase protein arrays (RPPA) for expression levels of 210 BC-relevant (phospho-) proteins. Lasso regression was used to derive a predictor of tumor shrinkage from the expression of selected proteins prior to treatment. RESULTS We identified a nine-protein signature score named vascular endothelial growth factor inhibition response predictor (ViRP) for use in the Bev plus CTx treatment arm able to predict with accuracy pathologic complete response (pCR) (area under the curve [AUC] = 0.85; 95% CI, 0.74 to 0.97) and low residual cancer burden (RCB 0/I) (AUC = 0.80; 95% CI, 0.68 to 0.93). The ViRP score was significantly lower in patients with pCR (P&lt; .001) and in patients with low RCB (P&lt;.001). The ViRP score was internally validated on mRNA data and the resultant surrogate mRNA ViRP score significantly separated the pCR patients (P = .016). Similarly, the mRNA ViRP score was validated (P &lt; .001) in an independent phase II clinical trial (PROMIX). CONCLUSION Our ViRP score, integrating the expression of nine proteins and validated on mRNA data both internally and in an independent clinical trial, may be used to increase the likelihood of benefit from treatment with bevacizumab combined with chemotherapy in patients with HER2-negative BC.</p>}},
  author       = {{Haugen, Mads H. and Lingjærde, Ole Christian and Hedenfalk, Ingrid and Garred, Øystein and Borgen, Elin and Loman, Niklas and Hatschek, Thomas and Børresen-Dale, Anne Lise and Naume, Bjørn and Mills, Gordon B. and Mælandsmo, Gunhild M. and Engebraaten, Olav}},
  issn         = {{2473-4284}},
  language     = {{eng}},
  pages        = {{286--306}},
  publisher    = {{American Society of Clinical Oncology}},
  series       = {{JCO Precision Oncology}},
  title        = {{Protein signature predicts response to neoadjuvant treatment with chemotherapy and bevacizumab in HER2-negative breast cancers}},
  url          = {{http://dx.doi.org/10.1200/PO.20.00086}},
  doi          = {{10.1200/PO.20.00086}},
  volume       = {{5}},
  year         = {{2021}},
}