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Resistance to endocrine therapy in HR + and/or HER2 + breast cancer: the most promising predictive biomarkers

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Abstract

Breast cancer is the most common cancer in women. It is a heterogeneous disease, encompassing different biological subtypes that differ in histological features, outcomes, clinical behaviour and different molecular subtypes. Therapy has progressed substantially over the past years with a reduction both for locoregional and systemic therapy. Endocrine therapies have considerably reduced cancer recurrence and mortality. Despite the major diagnostic and therapeutic innovations, resistance to therapy has become a main challenge, especially in metastatic breast cancer, and became a major factor limiting the use of endocrine therapeutic agents in ER positive breast cancers. Approximately 50% of patients with ER positive metastatic disease achieve a complete or partial response with endocrine therapy. However, in the remaining patients, the benefit is limited due to resistance, intrinsic or acquired, resulting in disease progression and poor outcome.

Tumour heterogeneity as well as acquired genetic changes and therapeutics pressure have been involved in the endocrine therapy resistance. Nowadays, targeted sequencing of genes involved in cancer has provided insights about genomic tumour evolution throughout treatment and resistance driver mutations. Several studies have described multiple alterations in receptor tyrosine kinases, signalling pathways such as Phosphoinositide-3-kinase–protein kinase B/Akt/mTOR (PI3K/Akt/mTOR) and Mitogen-activated protein kinase (MAPK), cell cycle machinery and their implications in endocrine treatment failure.

One of the current concern in cancer is personalized therapy. The focus has been the discovery of new potentially predictive biomarkers capable to identify reliably the most appropriate therapy regimen and which patients will experience disease relapse. The major concern is also to avoid overtreatment/undertreatment and development of resistance.

This review focuses on the most promising predictive biomarkers of resistance in estrogen receptor-positive breast cancer and the emerging role of circulating free-DNA as a powerful tool for longitudinal monitoring of tumour molecular profile throughout treatment.

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Authors and Affiliations

  1. Politécnico de Coimbra, ESTeSC, DCBL, Rua 5 de Outubro—SM Bispo, Apartado, 7006, 3046-854, Coimbra, Portugal

    Flávia Miranda, Fernando Mendes & Diana Martins

  2. i3S-Instituto de Investigação e Inovação em Saúde, Porto, Portugal

    Hugo Prazeres, Diana Martins & Fernando Schmitt

  3. Institute of Molecular Pathology and Immunology of the University of Porto (IPATIMUP), Porto, Portugal

    Hugo Prazeres & Fernando Schmitt

  4. U-Monitor Lda, Porto, Portugal

    Hugo Prazeres

  5. Department of Molecular Pathology, Portuguese Institute of Oncology, Coimbra, Portugal

    Hugo Prazeres

  6. University of Coimbra, Coimbra Institute for Clinical and Biomedical Research (iCBR) area of Environment Genetics and Oncobiology (CIMAGO), Biophysics Institute of Faculty of Medicine, Coimbra, Portugal

    Fernando Mendes & Diana Martins

  7. Center for Innovative Biomedicine and Biotechnology (CIBB), University of Coimbra, Coimbra, Portugal

    Fernando Mendes & Diana Martins

  8. Clinical Academic Center of Coimbra (CACC), Coimbra, Portugal

    Fernando Mendes & Diana Martins

  9. European Association for Professions in Biomedical Sciences, Brussels, Belgique

    Fernando Mendes

  10. Faculty of Medicine, University of Porto (FMUP), Porto, Portugal

    Fernando Schmitt

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  1. Flávia Miranda
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  2. Hugo Prazeres
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  3. Fernando Mendes
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FM, FM, DM and FS drafted the manuscript, performed literature search and created the figures; HP conceived the idea; DM helped in designing the manuscript; DM and FM and FS critically revised the article and helped in the edition of the figures.

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Correspondence to Diana Martins.

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Miranda, F., Prazeres, H., Mendes, F. et al. Resistance to endocrine therapy in HR + and/or HER2 + breast cancer: the most promising predictive biomarkers. Mol Biol Rep 49, 717–733 (2022). https://doi.org/10.1007/s11033-021-06863-3

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