How to Predict Metastasis in Luminal Breast Cancer? Current Solutions and Future Prospects
Abstract
:1. Introduction
2. The Role of HR Receptors and Hormonal Crosstalk in the Prediction of the Relapse
3. Molecular Subtyping and the Current Molecular Diagnostic Tests
3.1. OncotypeDx Recurrence Score (RS)
3.2. MammaPrint (MP)
3.3. Breast Cancer Index (BCI)
3.4. Prosigna PAM 50 Risk of Recurrence Score (ROR)
3.5. EndoPredict (EP)
3.6. Serum Biomarkers
4. Luminal Tumor Biology and Its Implications on Metastasis
4.1. Models of Metastasis
4.2. Dormancy in Luminal BC
4.3. Challenges of Tumor Heterogeneity and Clonal Evolution
5. Circulating Markers; Established Tests and Future Perspectives
5.1. cfDNA
5.2. Circulating Tumor Cells (CTCs)
5.3. Circulating miRNAs
5.4. Exosomes
5.5. Neutrophil Extracellular Traps
6. Conclusions
Funding
Conflicts of Interest
Abbreviations
BC | Breast cancer |
CTC | Circulating tumor cell |
DTC | Disseminated tumor cell |
ECM | Extracellular matrix |
EMT | Epithelial—mesenchymal transition |
ER | Estrogen receptor |
EV | Extracellular vesicles |
FFPE | Formalin-fixed, paraffin-embedded |
HDS | High dormancy score |
HER2 | Human epidermal growth factor receptor 2 |
HR | Hormone receptors |
HRT | Hormone replacement therapy |
IHC | Immonohistochemistry |
NE | Neutrophil elastase |
NET | Neutrophil extracellular traps |
MBC | Metastatic breast cancer |
RT-PCR | Reverse-transcriptase polymerase-chain-reaction |
PR | Progesterone receptor |
TNBC | Triple-negative breast cancer |
TME | Tumor microenvironment |
TIME | Tumor immune microenvironment |
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Test | Number of Genes/Proteins/Parameters | Lymph Node Involvement | Prognostic/Predictive Value | Recommendations | References |
---|---|---|---|---|---|
OncotypeDx (Genomic Health, Inc.) | 21 genes | N0 | +/+ | ASCO, ESMO, NCCN, St. Gallen | [32,33,34,35,36,37] |
MAGEE (Agendia BV) | 6 parameters | N0 | +/+ | - | [38] |
IHC4 | 4 proteins | N0 | +/+ | - | [39,40] |
MammaPrint | 70 genes | N0-1 | +/+ | ESMO, St.Gallen | [32,34,41,42,43] |
Breast Cancer Index (Bio Theranostics) | 5 genes + 2 biomarkers | N0 | +/+ | - | [40] |
Prosigna PAM 50 (Nanostring) | 50 genes | N0 | +/− | St.Gallen | [32,44] |
EndoPredict (Sividon Diagnostics) | 12 genes | N0-1 | +/+ | St. Gallen | [32,45] |
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Tabor, S.; Szostakowska-Rodzos, M.; Fabisiewicz, A.; Grzybowska, E.A. How to Predict Metastasis in Luminal Breast Cancer? Current Solutions and Future Prospects. Int. J. Mol. Sci. 2020, 21, 8415. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21218415
Tabor S, Szostakowska-Rodzos M, Fabisiewicz A, Grzybowska EA. How to Predict Metastasis in Luminal Breast Cancer? Current Solutions and Future Prospects. International Journal of Molecular Sciences. 2020; 21(21):8415. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21218415
Chicago/Turabian StyleTabor, Sylwia, Małgorzata Szostakowska-Rodzos, Anna Fabisiewicz, and Ewa A. Grzybowska. 2020. "How to Predict Metastasis in Luminal Breast Cancer? Current Solutions and Future Prospects" International Journal of Molecular Sciences 21, no. 21: 8415. https://0-doi-org.brum.beds.ac.uk/10.3390/ijms21218415