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

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.

Early Prediction of Tumor Response to Neoadjuvant Chemotherapy and Clinical Outcome in Breast Cancer Using a Novel FDG-PET Parameter for Cancer Stem Cell Metabolism

“…ER negativity is an established predictor of pCR, but approximately half of ER-negative tumors still cannot achieve pCR to NAC. Predicting pCR with 18 F-FDG PET/CT in breast cancer has been intensively studied, and, currently, the most powerful predictor from this modality is using the change in tumor SUVmax after 1 or 2 cycles of NAC in HER2-positive and TN tumors [34][35][36][37]. This strategy reported a prediction accuracy of 75-80% [34][35][36], which is comparable to the present study.…”

Correlation Between Mammographic Radiomics Features and the Level of Tumor-Infiltrating Lymphocytes in Patients With Triple-Negative Breast Cancer

“…Studies have proved that TIL levels have a strong prognostic value, which can improve the distant recurrence-free survival, disease-free, and overall survival estimates for TNBC patients treated with adjuvant/neoadjuvant chemotherapy (22,23). Increased TIL levels have been observed to be positively correlated with prolonged survival and increased pathological complete response rates (24)(25)(26). Because of the uneven distribution of TILs within the tumor, TIL levels obtained by biopsy in a specific part of the tumor may not reflect the entire tumor.…”

Indications of neoadjuvant chemotherapy for locally advanced Gastric Cancer patients based on pre-treatment clinicalpathological and laboratory parameters

“…Even if NAT could be used to treat specific stages of GC, not all patients would benefit from NAT as expected. Recently, nomograms have been used for tumor prognosis prediction models after NAT [11][12][13][14][15][16]. These models show superior performance compared to conventional staging models [17][18][19][20][21].…”