Review
. 2015 Apr;17().
doi: 10.1186/s13058-015-0514-2.

Multigene prognostic tests in breast cancer: past, present, future

Balázs Győrffy  Christos Hatzis  Tara Sanft  Erin Hofstatter  Bilge Aktas  Lajos Pusztai  
  • PMID: 25848861
  •     31 References
  •     80 citations

Abstract

There is growing consensus that multigene prognostic tests provide useful complementary information to tumor size and grade in estrogen receptor (ER)-positive breast cancers. The tests primarily rely on quantification of ER and proliferation-related genes and combine these into multivariate prediction models. Since ER-negative cancers tend to have higher proliferation rates, the prognostic value of current multigene tests in these cancers is limited. First-generation prognostic signatures (Oncotype DX, MammaPrint, Genomic Grade Index) are substantially more accurate to predict recurrence within the first 5 years than in later years. This has become a limitation with the availability of effective extended adjuvant endocrine therapies. Newer tests (Prosigna, EndoPredict, Breast Cancer Index) appear to possess better prognostic value for late recurrences while also remaining predictive of early relapse. Some clinical prediction problems are more difficult to solve than others: there are no clinically useful prognostic signatures for ER-negative cancers, and drug-specific treatment response predictors also remain elusive. Emerging areas of research involve the development of immune gene signatures that carry modest but significant prognostic value independent of proliferation and ER status and represent candidate predictive markers for immune-targeted therapies. Overall metrics of tumor heterogeneity and genome integrity (for example, homologue recombination deficiency score) are emerging as potential new predictive markers for platinum agents. The recent expansion of high-throughput technology platforms including low-cost sequencing of circulating and tumor-derived DNA and RNA and rapid reliable quantification of microRNA offers new opportunities to build extended prediction models across multiplatform data.

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Ivana Sestak, Miguel Martín, +12 authors, Michael Gnant.
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Comprehensive analysis of the aberrantly expressed lncRNA‑associated ceRNA network in breast cancer.
Tayier Tuersong, Linlin Li, Zumureti Abulaiti, Shumei Feng.
Mol Med Rep, 2019 May 07; 19(6). PMID: 31059025    Free PMC article.
Impact of Commercialized Genomic Tests on Adjuvant Treatment Decisions in Early Stage Breast Cancer Patients.
Hazem I Assi, Ibrahim A Alameh, +9 authors, Nagi El Saghir.
J Oncol, 2020 Dec 15; 2020. PMID: 33312202    Free PMC article.
Development and validation of a prognostic nomogram for patients with triple-negative breast cancer with histology of infiltrating duct carcinoma.
Na Jing, Ming-Wei Ma, +7 authors, Hai-Xia Jia.
Ann Transl Med, 2020 Dec 15; 8(21). PMID: 33313192    Free PMC article.
The Tumor Microenvironment as a Driving Force of Breast Cancer Stem Cell Plasticity.
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Cancers (Basel), 2020 Dec 30; 12(12). PMID: 33371274    Free PMC article.
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Chemotherapy and 21-gene recurrence score testing for older breast cancer patients: A competing-risks analysis.
Ping Zhou, Wen-Wen Zhang, +4 authors, San-Gang Wu.
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Magee Equations™ and response to neoadjuvant chemotherapy in ER+/HER2-negative breast cancer: a multi-institutional study.
Rohit Bhargava, Nicole N Esposito, +11 authors, David J Dabbs.
Mod Pathol, 2020 Jul 15; 34(1). PMID: 32661297
A novel prognostic two-gene signature for triple negative breast cancer.
Mansour A Alsaleem, Graham Ball, +14 authors, Emad Rakha.
Mod Pathol, 2020 May 15; 33(11). PMID: 32404959
A nomogram to predict the high-risk RS in HR+/HER2-breast cancer patients older than 50 years of age.
Jing Yu, Jiayi Wu, +6 authors, Kunwei Shen.
J Transl Med, 2021 Feb 18; 19(1). PMID: 33593381    Free PMC article.
Multi-omics approaches in cancer research with applications in tumor subtyping, prognosis, and diagnosis.
Otília Menyhárt, Balázs Győrffy.
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Review.