Literature DB >> 27521224

Validated biomarkers: The key to precision treatment in patients with breast cancer.

Michael J Duffy1, Norma O'Donovan2, Enda McDermott3, John Crown4.   

Abstract

Recent DNA sequencing and gene expression studies have shown that at a molecular level, almost every case of breast cancer is unique and different from other breast cancers. For optimum management therefore, every patient should receive treatment that is guided by the molecular composition of their tumor, i.e., precision treatment. While such a scenario is still some distance into the future, biomarkers are beginning to play an important role in preparing the way for precision treatment. In particular, biomarkers are increasingly being used for predicting patient outcome and informing as to the most appropriate type of systemic therapy to be administered. Mandatory biomarkers for every newly diagnosed case of breast cancer are estrogen receptors and progesterone receptors in selecting patients for endocrine treatment and HER2 for identifying patients likely to benefit from anti-HER2 therapy. Amongst the best validated prognostic biomarker tests are uPA/PAI-1, MammaPrint and Oncotype DX. Although currently, there are no biomarkers available for predicting response to specific forms of chemotherapy, uPA/PAI-1 and Oncotype DX can aid the identification of lymph node-negative patients that are most likely to benefit from adjuvant chemotherapy, in general. In order to accelerate progress towards precision treatment for women with breast cancer, we need additional predictive biomarkers, especially for enhancing the positive predictive value for endocrine and anti-HER2 therapies, as well as biomarkers for predicting response to specific forms of chemotherapy. The ultimate biomarker test for achieving the goal of precision treatment for patients with breast cancer will likely require a combination of gene sequencing and transcriptomic analysis of every patient's tumor.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Biomarkers; Breast cancer; Gene signatures; Personalised treatment; Precision treatment

Mesh:

Substances:

Year:  2016        PMID: 27521224     DOI: 10.1016/j.breast.2016.07.009

Source DB:  PubMed          Journal:  Breast        ISSN: 0960-9776            Impact factor:   4.380


  13 in total

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Journal:  Cell Rep       Date:  2018-11-20       Impact factor: 9.423

Review 2.  Protein biomarkers for subtyping breast cancer and implications for future research.

Authors:  Claudius Mueller; Amanda Haymond; Justin B Davis; Alexa Williams; Virginia Espina
Journal:  Expert Rev Proteomics       Date:  2018-01-03       Impact factor: 3.940

3.  Gene expression profiles predictive of cold-induced sweetening in potato.

Authors:  Jonathan Neilson; M Lagüe; S Thomson; F Aurousseau; A M Murphy; B Bizimungu; V Deveaux; Y Bègue; J M E Jacobs; H H Tai
Journal:  Funct Integr Genomics       Date:  2017-02-24       Impact factor: 3.410

4.  Effect of macrophages on breast cancer cell proliferation, and on expression of hormone receptors, uPAR and HER-2.

Authors:  Therése Lindsten; Alexander Hedbrant; Anna Ramberg; Jonny Wijkander; Anja Solterbeck; Margareta Eriksson; Dick Delbro; Ann Erlandsson
Journal:  Int J Oncol       Date:  2017-05-11       Impact factor: 5.650

5.  A case-control study of Metallothionein-1 expression in breast cancer and breast fibroadenoma.

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Journal:  Sci Rep       Date:  2019-05-15       Impact factor: 4.379

6.  Epigenetic biomarkers of ageing are predictive of mortality risk in a longitudinal clinical cohort of individuals diagnosed with oropharyngeal cancer.

Authors:  Rhona A Beynon; Suzanne M Ingle; Ryan Langdon; Margaret May; Andy Ness; Richard M Martin; Matthew Suderman; Kate Ingarfield; Riccardo E Marioni; Daniel L McCartney; Tim Waterboer; Michael Pawlita; Caroline Relton; George Davey Smith; Rebecca C Richmond
Journal:  Clin Epigenetics       Date:  2022-01-03       Impact factor: 6.551

7.  Personalized Computational Models as Biomarkers.

Authors:  Walter Kolch; Dirk Fey
Journal:  J Pers Med       Date:  2017-09-01

8.  TWIST1 Gene Expression as a Biomarker for Predicting Primary Doxorubicin Resistance in Breast Cancer.

Authors:  S Demir; M H Müslümanoğlu; M Müslümanoğlu; S Başaran; Z Z Çalay; A Aydıner; U Vogt; T Çakır; H Kadıoğlu; S Artan
Journal:  Balkan J Med Genet       Date:  2019-12-21       Impact factor: 0.519

9.  Prognostic biomarkers related to breast cancer recurrence identified based on Logit model analysis.

Authors:  Xiaoying Zhou; Chuanguang Xiao; Tong Han; Shusheng Qiu; Meng Wang; Jun Chu; Weike Sun; Liang Li; Lili Lin
Journal:  World J Surg Oncol       Date:  2020-09-25       Impact factor: 2.754

Review 10.  A Narrative Review on Plasminogen Activator Inhibitor-1 and Its (Patho)Physiological Role: To Target or Not to Target?

Authors:  Machteld Sillen; Paul J Declerck
Journal:  Int J Mol Sci       Date:  2021-03-08       Impact factor: 5.923

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