DOI: 10.1007/s00259-018-3998-zPages: 1-10

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

1. Saint-Louis Hospital, Department of Nuclear Medicine

2. Sorbonne Paris Cité, University Paris-Diderot

3. Saint-Louis Hospital, Department of Biostatistics

4. University Paris-Diderot, Sorbonne Paris Cité

5. Saint-Louis Hospital, Molecular Oncology Unit

6. Saint-Louis Hospital, Breast Diseases Unit

7. Saint-Louis Hospital, Department of Pathology

8. University Paris-Diderot, Sorbonne Paris Cité

9. Institut Jules Bordet, Université Libre de Bruxelles, Breast Cancer Translational Research Laboratory

Correspondence to:
David Groheux
Tel: +33(0)1.42.49.94.11
Email: dgroheux@yahoo.fr

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Abstract

Purpose

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.

Methods

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.

Results

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 PET1 and PET2 (ΔSUVmax) was highly associated with pCR (P = 0.0001) but the absolute value of baseline SUVmax was not (P = 0.11). However, the AUC of pCR prediction increased from 0.63 to 0.76 when baseline SUVmax was combined with the GGI (P = 0.016). The only two parameters associated with EFS were ΔSUVmax (P = 0.048) and pathological response (P = 0.014).

Conclusions

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 SUVmax improves the prediction.

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  • Accepted: Mar 21, 2018
  • Online: Apr 4, 2018

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