A. Di Leo

Abstract P6-02-07: Metabolomic analysis by nuclear magnetic resonance spectroscopy discriminates hormone receptor positive/HER2 negative breast cancer cell lines resistant to palbociclib

Introduction: Clinical trials of palbociclib in combination with endocrine therapy have recently shown unprecedented activity for the treatment of hormone receptor positive/HER2 negative (HR+/HER2neg) advanced breast cancer. However, de novo and acquired resistance to palbociclib limit its clinical utility. Moreover, combining palbociclib with endocrine therapy increases toxicity and costs of the treatment. Identifying patients more likely to benefit from this compound and understanding the mechanisms of resistance to palbociclib is critical. In this study we investigated whether metabolomic profiles of breast cancer cell lines with acquired resistance to palbociclib (PDR) differ from their sensitive counterpart (PDS). In addition we sought to identify metabolic biomarkers of sensitivity to palbociclib by analyzing a breast cancer cell line unable to acquire resistance to palbociclib. Material and methods: We have established in our lab three PDR HR+/HER2neg breast cancer models (MCF7L, T47D and ZR75-1) by chronically exposing cells to escalating doses of palbociclib. PDR derivatives show IC50 values 6 to 30 times higher than their PDS counterparts. One additional model, CAMA-1, was unable to develop resistance. Whole-cell lysates and conditioned cell culture media from five replicates of each of the PDS and PDR models and from CAMA-1 were analyzed by nuclear magnetic resonance (NMR). Principal component analysis (PCA) was used as first exploratory analysis and as dimension reduction technique. Canonical Analysis (CA) was used to discriminate different groups. Differentially expressed metabolites between PDR and PDS models and between CAMA-1 and PDS cells were analyzed. Results: Unsupervised PCA analyses of H NMR spectra, in which no information about PDS and PDR was inserted in the statistical model, correctly identified individual cell lines on both whole-cell lysates and conditioned media. However this analysis did not discriminate PDS from PDR within each model. Using a supervised approach, in which the statistical model was trained to discriminate between PDS and PDR, these groups were categorized with accuracy of 80% using whole-cell lysates and of 65% using conditioned media, using a cross-validation analysis by repeatedly testing the model on blind samples. CAMA-1 was correctly identified as a PDS model; however it showed a distinct metabolic profile compared to other PDS models. Over 30 metabolites were identified as differentially expressed between PDS and PDR models in lysates and conditioned media, but only glycerophosphocholine levels in conditioned media remained significantly higher in PDR compared to PDS models after correction for multiple testing. Conclusions: In this study we show that analysis of metabolic profile of cells lysates discriminates PDR from PDS cell lines with a high accuracy. Analysis of metabolic pathways implicated in resistance/sensitivity to palbociclib is ongoing and might help identifying new targets to overcome resistance. Additionally, metabolites associated with palbociclib resistance may be potentially tested in clinical samples as biomarkers for patients stratification. Further studies are warranted. Citation Format: Bonechi M, Guarducci C, Meoni G, Tenori L, Biagioni C, Schiff R, Osborne CK, Luchinat C, Di Leo A, Malorni L, Migliaccio I. Metabolomic analysis by nuclear magnetic resonance spectroscopy discriminates hormone receptor positive/HER2 negative breast cancer cell lines resistant to palbociclib [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P6-02-07.

Abstract P1-09-13: A RB-1 loss-of-function gene-signature (RBsig) predicts resistance to neoadjuvant chemotherapy in HER2+/ER+ breast cancer patients

Background: HER2+ breast cancers (BC) are clinically and biologically heterogeneous, with approximately half being ER+. Compared to other BC subtypes, HER2+ ER+ tumors display among the lowest rates of pathological complete response (pCR) following neoadjuvant chemotherapy (NACT) +/− anti-HER2 agents (anti-HER2). Yet in spite of this, HER2+/ER+ patients (pts) are typically treated with NACT plus anti-HER2, with the subsequent related toxicity. Currently there is a lack of predictive biomarkers that identify which subgroups of pts will not respond to such therapy. Inactivation of the Retinoblastoma (Rb) signalling pathway is a frequent event in BC. Previously developed gene-signatures of Rb loss-of-function have shown strong prognostic value and prediction of response to NACT. However, none has been extensively studied in the context of HER2+/ER+ BC. We have recently developed a gene-signature of RB-1 loss-of-function (RBsig) that is prognostic in luminal A-like and luminal B-like BC. Here we report the results of a retrospective in-silico study aimed to determine whether low expression of the RBsig in HER2+/ER+ BC correlates with a low pCR rate following NACT +/− anti-HER2. Methods: We performed a PubMed search for clinical trials of NACT +/− anti-HER2 (trastuzumab, lapatinib, or both) in HER2+ BC pts, and selected studies which had available gene expression data, hormone receptors status and pCR information. In-silico analyses of correlation between RBsig expression and pCR were performed using receiver-operating characteristic (ROC) curves and Fisher exact test to assess the prediction performance of the signature score. The threshold RBsig score was set at the 50th percentile of the score distribution. Results: Out of 16 identified studies, 10 fulfilled the inclusion criteria and were included in the analysis (514 pts). Overall, of the 211 HER2+/ER+ BC pts, 49 achieved pCR (23%); the pCR rate following NACT +/− anti-HER2 of pts with RBsig low expression was significantly lower compared to pts with RBsig high expression (16% vs 30%, respectively; Fisher exact test p=0.0098).The area under the ROC curve (AUC) was 0.62 (95% confidence interval (CI) 0.54-0.7, p=0.005). Results were similar for pts receiving NACT alone (94 pts; pCR rate 13% vs 28% in RBsig low vs RBsig high, respectively; Fisher exact test p=0,06; AUC 0.62, 95% CI 0.5-0.74, p=0.043) or combined with anti-HER2 (117 pts; pCR rate 18% vs 33% in RBsig low vs RBsig high, respectively; Fisher exact test p=0,049; AUC 0.61, 95% CI 0.5-0.72, p=0.041). In 303 HER2+/ ER− pts treated with NACT +/− anti-HER2, the pCR rate was 42%. No correlation was found between RBsig expression score and pCR rate in this group (pCR rate 42% vs 43% in RBsig low vs RBsig high, respectively; Fisher exact test p=0.53; AUC 0.5, 95% CI 0.43-0.56, p=0.973). Conclusions: RBsig identifies a subset of HER2+/ER+ pts with a low pCR rate following NACT +/− anti-HER2. We hypothesize that this signature has the potential to identify pts for whom chemotherapy could be avoided in favour of combinations of endocrine therapy and target therapies. Further refinement and validation in an independent dataset is warranted. Citation Format: Risi E, Grilli A, Migliaccio I, Biagioni C, Guarducci C, Bonechi M, Hart CD, Biganzoli L, Bicciato S, Di Leo A, Malorni L. A RB-1 loss-of-function gene-signature (RBsig) predicts resistance to neoadjuvant chemotherapy in HER2+/ER+ breast cancer patients [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P1-09-13.