Literature DB >> 28882552

Prognostic and predictive biomarkers in breast cancer: Past, present and future.

Andrea Nicolini1, Paola Ferrari2, Michael J Duffy3.   

Abstract

Following a diagnosis of breast cancer, the most immediate challenges in patient management are the determination of prognosis and identification of the most appropriate adjuvant systemic therapy. Determining prognosis can best be addressed with a combination of traditional clinicopathological prognostic factors, biomarkers such as HER2/neu and specific multigene genes tests. Amongst the best validated prognostic multigene tests are uPA/PAI1, Oncotype DX and MammaPrint. Oncotype DX and MammaPrint, may be used for predicting outcome and aiding adjunct therapy decision making in patients with ER-positive, HER2-negative breast cancers that are either lymph node-negative or node positive (1-3 metastatic nodes), while uPA/PAI-1 may be similarly used in ER-positive, lymph node-negative patients. For selecting likely response to endocrine therapy, both estrogen receptors (ER) and progesterone receptors (PR) should be measured. On the other hand, for identifying likely response to anti-HER2 therapy, determination of HER2 gene amplification or overexpression is necessary. To identify new prognostic and predictive biomarkers for breast cancer, current research is focusing on tumor and circulating DNA (ctDNA) and RNA (e.g., micro RNAs) and circulating tumor cells. A promising ctDNA biomarker is the mutational status of ER (ESR1) for predicting the emergence of resistance to aromatase inhibitors. Challenges for future research include the identification of biomarkers for predicting response to radiotherapy and specific forms of chemotherapy.
Copyright © 2017 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Biomarkers; Breast cancer; Micro RNAs; Prognostic; Therapy predictive

Mesh:

Substances:

Year:  2017        PMID: 28882552     DOI: 10.1016/j.semcancer.2017.08.010

Source DB:  PubMed          Journal:  Semin Cancer Biol        ISSN: 1044-579X            Impact factor:   15.707


  95 in total

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2.  Increased High Molecular Weight FGF2 in Endocrine-Resistant Breast Cancer.

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Journal:  Virchows Arch       Date:  2017-12-12       Impact factor: 4.064

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5.  Comparative Proteome Analysis of Breast Cancer Tissues Highlights the Importance of Glycerol-3-phosphate Dehydrogenase 1 and Monoacylglycerol Lipase in Breast Cancer Metabolism.

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6.  Identification of key differentially expressed genes between ER-positive/HER2-negative breast cancer and ER-negative/HER2-negative breast cancer using integrated bioinformatics analysis.

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Review 7.  Cyclin-dependent kinases in breast cancer: expression pattern and therapeutic implications.

Authors:  Shazia Sofi; Umar Mehraj; Hina Qayoom; Shariqa Aisha; Syed Mohammad Basheeruddin Asdaq; Abdullah Almilaibary; Manzoor A Mir
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Journal:  Mol Cell Biochem       Date:  2019-02-08       Impact factor: 3.396

9.  Background parenchymal enhancement and breast cancer: a review of the emerging evidences about its potential use as imaging biomarker.

Authors:  Rossella Rella; Andrea Contegiacomo; Enida Bufi; Sara Mercogliano; Paolo Belli; Riccardo Manfredi
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10.  A seven-nuclear receptor-based prognostic signature in breast cancer.

Authors:  F Wu; W Chen; X Kang; L Jin; J Bai; H Zhang; X Zhang
Journal:  Clin Transl Oncol       Date:  2020-11-18       Impact factor: 3.405

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