A gene expression signature of retinoblastoma loss-of-function is a predictive biomarker of resistance to palbociclib in breast cancer cell lines and is prognostic in patients with ER positive early breast cancer

Luca Malorni, Silvano Piazza, Yari Ciani, Cristina Guarducci, Martina Bonechi, Chiara Biagioni, Christopher D Hart, Roberto Verardo, Angelo Di Leo, Ilenia Migliaccio, Luca Malorni, Silvano Piazza, Yari Ciani, Cristina Guarducci, Martina Bonechi, Chiara Biagioni, Christopher D Hart, Roberto Verardo, Angelo Di Leo, Ilenia Migliaccio

Abstract

Palbociclib is a CDK4/6 inhibitor that received FDA approval for treatment of hormone receptor positive (HR+) HER2 negative (HER2neg) advanced breast cancer. To better personalize patients treatment it is critical to identify subgroups that would mostly benefit from it. We hypothesize that complex alterations of the Retinoblastoma (Rb) pathway might be implicated in resistance to CDK4/6 inhibitors and aim to investigate whether signatures of Rb loss-of-function would identify breast cancer cell lines resistant to palbociclib. We established a gene expression signature of Rb loss-of-function (RBsig) by identifying genes correlated with E2F1 and E2F2 expression in breast cancers within The Cancer Genome Atlas. We assessed the RBsig prognostic role in the METABRIC and in a comprehensive breast cancer meta-dataset. Finally, we analyzed whether RBsig would discriminate palbociclib-sensitive and -resistant breast cancer cells in a large RNA sequencing-based dataset. The RBsig was associated with RB1 genetic status in all tumors (p <7e-32) and in luminal or basal subtypes (p < 7e-11 and p < 0.002, respectively). The RBsig was prognostic in the METABRIC dataset (discovery: HR = 1.93 [1.5-2.4] p = 1.4e-08; validation: HR = 2.01 [1.6-2.5] p = 1.3e-09). Untreated and endocrine treated patients with estrogen receptor positive breast cancer expressing high RBsig had significantly worse recurrence free survival compared to those with low RBsig (HR = 2.37 [1.8 - 3.2] p = 1.87e-08 and HR = 2.62 [1.9- 3.5] p = 8.6e-11, respectively). The RBsig was able to identify palbociclib resistant and sensitive breast cancer cells (ROC AUC = 0,7778). Signatures of RB loss might be helpful in personalizing treatment of patients with HR+/HER2neg breast cancer. Further validation in patients receiving palbociclib is warranted.

Keywords: CDK4/6 inhibitors; breast cancer; retinoblastoma loss of functions.

Conflict of interest statement

CONFLICTS OF INTEREST

L.M.: research grant from Pfizer

A.D.L.: advisory role and lecture fees from Pfizer, Novartis and Lilly

I.M, S.P, Y.C, R.V, C.G, M.B, C.B, C.H have no financial interests to disclose.

Figures

Figure 1. Functional analysis of the RBsig
Figure 1. Functional analysis of the RBsig
Enriched GO terms within the RBsig were plotted in a bi-dimensional space using a clustering algorithm that relies on semantic similarity measures using REVIGO tool [33].
Figure 2. Association between RBsig expression levels…
Figure 2. Association between RBsig expression levels and genetic RB1 status
Boxplots represent the RBsig signature expression according to putative RB1 status (0= diploid, -1=heterozygous loss, -2=complete loss) in all tumors, regardless the molecular subtype and in luminal and basal subtypes in the TCGA dataset [3].
Figure 3. Kaplan-Meier curves according to RBsig…
Figure 3. Kaplan-Meier curves according to RBsig in the METABRIC dataset
Patients included in the discovery set and in the validation set of the METABRIC dataset were stratified according to RBsig expression levels using the mean as cutoff, Kaplan Meier curves were generated and HR were calculated.
Figure 4. Kaplan-Meier curves according to RBsig…
Figure 4. Kaplan-Meier curves according to RBsig in patients with ER+ breast cancer included in the meta-dataset
Patients with ER+ tumors (untreated - upper panel; endocrine treated - bottom panel) included in the meta-dataset were stratified according to RBsig expression levels selecting the best cutoff using the best cutoff algorithm [28], Kaplan Meier curves were generated and HR were calculated.
Figure 5. ROC curves of RBsig on…
Figure 5. ROC curves of RBsig on all breast cancer cell lines
ROC curve analysis was performed on data obtained from breast cancer cell lines analyzed by RNAseq technology. Cells were classified as sensitive or resistant to palbociclib based on the IC 50 value obtained by Finn et al [12] using 300 nanomolar (nM) as threshold

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