Breast Cancer Research and Treatment

, Volume 170, Issue 2, pp 329–341 | Cite as

A gene expression signature of Retinoblastoma loss-of-function predicts resistance to neoadjuvant chemotherapy in ER-positive/HER2-positive breast cancer patients

  • Emanuela Risi
  • Andrea Grilli
  • Ilenia Migliaccio
  • Chiara Biagioni
  • Amelia McCartney
  • Cristina Guarducci
  • Martina Bonechi
  • Matteo Benelli
  • Stefania Vitale
  • Laura Biganzoli
  • Silvio Bicciato
  • Angelo Di Leo
  • Luca Malorni
Clinical trial



HER2-positive (HER2+) breast cancers show heterogeneous response to chemotherapy, with the ER-positive (ER+) subgroup deriving less benefit. Loss of retinoblastoma tumor suppressor gene (RB1) function has been suggested as a cardinal feature of breast cancers that are more sensitive to chemotherapy and conversely resistant to CDK4/6 inhibitors. We performed a retrospective analysis exploring RBsig, a gene signature of RB loss, as a potential predictive marker of response to neoadjuvant chemotherapy in ER+/HER2+ breast cancer patients.


We selected clinical trials of neoadjuvant chemotherapy ± anti-HER2 therapy in HER2+ breast cancer patients with available information on gene expression data, hormone receptor status, and pathological complete response (pCR) rates. RBsig expression was computed in silico and correlated with pCR.


Ten studies fulfilled the inclusion criteria and were included in the analysis (514 patients). Overall, of 211 ER+/HER2+ breast cancer patients, 49 achieved pCR (23%). The pCR rate following chemotherapy ± anti-HER2 drugs in patients with RBsig low expression was significantly lower compared to patients with RBsig high expression (16% vs. 30%, respectively; Fisher’s exact test p = 0.015). The area under the ROC curve (AUC) was 0.62 (p = 0.005). In the 303 ER-negative (ER−)/HER2+ patients treated with chemotherapy ± anti-HER2 drugs, the pCR rate was 43%. No correlation was found between RBsig expression and pCR rate in this group.


Low expression of RBsig identifies a subset of ER+/HER2+ patients with low pCR rates following neoadjuvant chemotherapy ± anti-HER2 therapy. These patients may potentially be spared chemotherapy in favor of anti-HER2, endocrine therapy, and CDK 4/6 inhibitor combinations.


Gene expression profiling RB pathway HER2+ breast cancer Neoadjuvant chemotherapy Predictive marker 



Anthracycline-based chemotherapy


Area under the curve


Breast cancer


Cyclin-dependent kinase




Estrogen receptor


Estrogen receptor positive


Estrogen receptor negative


Endocrine therapy


Gene expression


Anti-HER2 drugs


Human epidermal growth factor receptor-2

HER2 +

Human epidermal growth factor receptor-2 positive


Hormone receptors


Lymph node status


Pathological complete response


Phosphoinositide-3-kinase catalytic alpha polypeptide gene


Progression-free survival


Progesterone receptor


Retinoblastoma tumor suppressor gene


RB1 loss-of-function gene signature


Residual disease


Receiver-operating characteristic


Tumor status


Taxane-based chemotherapy

T + A-based

Taxane–anthracycline-based chemotherapy or ixabepilone–anthracycline-based chemotherapy

T + A-based + H

Taxane–anthracycline-based chemotherapy plus anti-HER2 drugs



We acknowledge the generous support provided by the Sandro Pitigliani Foundation (Prato, Italy), the Breast Cancer Research Foundation (BCRF) (New York, US), the Associazione Italiana per la Ricerca sul Cancro (AIRC) (Milan, Italy), my first AIRC grant (MFAG) 18880 (to L.M.), AIRC Special Program Molecular Clinical Oncology “5 per mille,” and Italian Epigenomics Flagship Project (Epigen) (to S.B.). We are grateful to Patricia de Cremoux and the REMAGUS 02 trial investigators for providing the trial data.

Compliance with ethical standards

Conflicts of interest

A Di Leo is a consultant/advisory board member for AstraZeneca, Bayer, Eisai, Genomic Health, Ipsen, Lilly, Novartis, Pfizer, and Pierre Fabre. L. Malorni is a consultant for AstraZeneca and Pfizer. No potential conflicts of interest were disclosed by the other authors.

Supplementary material

10549_2018_4766_MOESM1_ESM.pdf (137 kb)
Supplementary material 1 (PDF 136 kb)
10549_2018_4766_MOESM2_ESM.pdf (174 kb)
Supplementary material 2 (PDF 173 kb)


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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Emanuela Risi
    • 1
    • 2
  • Andrea Grilli
    • 3
  • Ilenia Migliaccio
    • 2
  • Chiara Biagioni
    • 4
  • Amelia McCartney
    • 1
  • Cristina Guarducci
    • 2
  • Martina Bonechi
    • 2
  • Matteo Benelli
    • 1
  • Stefania Vitale
    • 1
    • 5
  • Laura Biganzoli
    • 1
  • Silvio Bicciato
    • 3
  • Angelo Di Leo
    • 1
  • Luca Malorni
    • 1
    • 2
  1. 1.Sandro Pitigliani Medical Oncology DepartmentHospital of Prato, Istituto Toscano TumoriPratoItaly
  2. 2.Sandro Pitigliani Translational Research UnitHospital of Prato, Istituto Toscano TumoriPratoItaly
  3. 3.Department of Life Science, Center for Genome ResearchUniversity of Modena and Reggio EmiliaModenaItaly
  4. 4.Bioinformatics UnitHospital of PratoPratoItaly
  5. 5.Department of Medical BiotechnologiesUniversity of SienaSienaItaly

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