Tumor metabolism assessed by FDG-PET/CT and tumor proliferation assessed by genomic grade index to predict response to neoadjuvant chemotherapy in triple negative breast cancer.

Groheux, David; Biard, L; Lehmann-Che, J; Teixeira, L; Bouhidel, F A; Poirot, B; Bertheau, P; Merlet, P et al. · Eur J Nucl Med Mol Imaging · 2018

prospective_cohort · Level II

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Abstract

Survival is increased when pathological complete response (pCR) is reached after neoadjuvant chemotherapy (NAC), especially in triple-negative breast cancer (TNBC) patients. Positron emission tomography/computed tomography (PET/CT) with 18F-fluorodeoxyglucose (FDG) and the genomic grade index (GGI), each separately, showed good potential to predict pCR. Our study was designed to evaluate the predictive value for the therapeutic response of a combination of parameters based on FDG-PET, histoclinical features and molecular markers of proliferation. Molecular parameters were measured on pre-treatment biopsy. Tumor metabolic activity was measured using two PET/CT scans, one before and one after 2 cycles of NAC. The pCR was determined on specimen after NAC. Event-free survival (EFS) was estimated using the Kaplan Meier method. Of 55 TNBC patients, 19 (35%) reached pCR after NAC. Tumor grade and Ki67 were not associated with pCR whereas GGI (P = 0.04) and its component KPNA2 (P = 0.04) showed a predictive value. The change of FDG uptake between PET<sub>1</sub> and PET<sub>2</sub> (ΔSUV<sub>max</sub>) was highly associated with pCR (P = 0.0001) but the absolute value of baseline SUV<sub>max</sub> was not (P = 0.11). However, the AUC of pCR prediction increased from 0.63 to 0.76 when baseline SUV<sub>max</sub> was combined with the GGI (P = 0.016). The only two parameters associated with EFS were ΔSUV<sub>max</sub> (P = 0.048) and pathological response (P = 0.014). The early tumor metabolic change during NAC is a powerful parameter to predict pCR and outcome in TNBC patients. The GGI, determined on pretreatment biopsy, is also predictive of pCR and the combination GGI and baseline SUV<sub>max</sub> improves the prediction.

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