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Review
. 2020 Sep 25:6:46.
doi: 10.1038/s41523-020-00188-3. eCollection 2020.

Clinical utility of genomic signatures in young breast cancer patients: a systematic review

Affiliations
Review

Clinical utility of genomic signatures in young breast cancer patients: a systematic review

Cynthia Villarreal-Garza et al. NPJ Breast Cancer. .

Abstract

Risk stratification by genomic signatures has been shown to improve prognostication and guide treatment decisions among patients with hormone-sensitive breast cancer. However, their role in young women has not been fully elucidated. In this review, a systematic search was conducted for published articles and abstracts from major congresses that evaluated the use of genomic signatures in young breast cancer patients. A total of 71 studies were analyzed, including 561,188 patients of whom 27,748 (4.9%) were young. Women aged ≤40 years were subjected to genomic testing at a similar rate to older women but had a higher proportion of intermediate- to high-risk tumors when classified by EndoPredict (p = 0.04), MammaPrint (p < 0.01), and Oncotype DX (p < 0.01). In young women with low genomic risk, 6-year distant recurrence-free survival was 94%, while 5-year overall survival was nearly 100%. Nonetheless, young patients classified as low-risk had a higher tendency to receive chemotherapy compared to their older counterparts. In conclusion, genomic tests are useful tools for identifying young patients in whom chemotherapy omission is appropriate.

Keywords: Breast cancer; Cancer genomics.

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Conflict of interest statement

Competing interestsC.V.G.: Consultancy or advisory role: Roche, Novartis, Pfizer, Eli Lilly; Speaker honoraria: Roche, Myriad Genetics, Novartis. M.L.: Consultancy: Roche and Novartis; Speaker honoraria: Roche, Takeda, Theramex, Novartis, Lilly, Pfizer. H.A.A.: Consultancy and received honoraria: Nanostring, Novartis; Employment: Innate Pharma. The rest of the authors declare no competing interests.

Figures

Fig. 1
Fig. 1. Preferred reporting items for systematic reviews and meta-analyses (PRISMA) flow diagram.
Studies included in the qualitative but not in the quantitative synthesis are those that used data from the same sample of patients.
Fig. 2
Fig. 2. Proportion of patients in each genomic risk category according to age.
a EndoPredict, b MammaPrint, c Oncotype DX (traditional recurrence risk categories), d Oncotype DX (TAILORx recurrence risk categories). Patients aged ≤40 years were predominantly classified as intermediate to high-risk by Oncotype DX (traditional cut-off value of >18:61%; TAILORx threshold of >11:86%) or as high-risk by MammaPrint (65%) and EndoPredict (68%). In contrast, patients aged >40 years were more likely to be assigned a low-risk category (59% when using the traditional threshold of Oncotype, 56% by MammaPrint, and 51% by EndoPredict). Error bars are set to 5%.
Fig. 3
Fig. 3. Proportion of patients that underwent genomic testing with Oncotype DX according to age.
Data were extracted from studies by Poorvu et al., Lund et al., and Williams et al..
Fig. 4
Fig. 4. Proportion of patients that received chemotherapy according to Oncotype DX recurrence score and age.
Data were extracted from studies by and Barcenas et al., Petkov et al., and Poorvu et al..

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