Predicting the response to neoadjuvant therapy for early-stage breast cancer: tumor-, blood-, and imaging-related biomarkers

Wenyong Tan, Ming Yang, Hongli Yang, Fangbin Zhou, Weixi Shen, Wenyong Tan, Ming Yang, Hongli Yang, Fangbin Zhou, Weixi Shen

Abstract

Neoadjuvant therapy (NAT) has been used increasingly in patients with locally advanced or early-stage breast cancer. However, the accurate evaluation and prediction of response to NAT remain the great challenge. Biomarkers could prove useful to identify responders or nonresponders, or even to distinguish between early and delayed responses. These biomarkers could include markers from the tumor itself, such as versatile proteins, genes, and ribonucleic acids, various biological factors or peripheral blood cells, and clinical and pathological features. Possible predictive markers could also include multiple features from functional imaging, such as standard uptake values in positron emission tomography, apparent diffusion coefficient in magnetic resonance, or radiomics imaging biomarkers. In addition, cells that indirectly present the immune status of tumor cells and/or their host could also potentially be used as biomarkers, eg, tumor-infiltrating lymphocytes, tumor-associated macrophages, and myeloid-derived suppressor cells. Though numerous biomarkers have been widely investigated, only estrogen and/or progesterone receptors and human epidermal growth factor receptor have been proven to be reliable biomarkers to predict the response to NAT. They are the only biomarkers recommended in several international guidelines. The other aforementioned biomarkers warrant further validation studies. Some multigene profiling assays that are commercially available, eg, Oncotype DX and MammaPrint, should be used with caution when extrapolated to NAT settings. A panel of combined multilevel biomarkers might be able to predict the response to NAT more robustly than individual biomarkers. To establish such a panel and its prediction model, reliable methods and extensive clinical validation are warranted.

Keywords: biomarker; breast cancer; drug therapy; predictive factor.

Conflict of interest statement

Disclosure The authors report no conflicts of interest in this work.

Figures

Figure 1
Figure 1
The schematic representation of a clinical trial merging biomarkers from tumor, blood, and imaging. Note: This clinical trial (NCT03242551), ie, BINC-B, aims to use a combination of multiple biomarkers to improve their ability to predict the response to neoadjuvant chemotherapy of patients with early-stage breast cancer. Abbreviations: BINC-B, Biomarkers Investigating Neoadjuvant Chemotherapy for Breast cancer; CEC, circulating endothelial cell; ctDNA, circulating tumor DNA; DCE, dynamic contrast enhanced; DWI, diffusion-weighted imaging; MRI, magnetic resonance imaging; NAT, neoadjuvant therapy.

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