Abstract

Inflammatory breast cancer (IBC) is an aggressive disease for which the spectrum of preclinical models was rather limited in the past. More recently, novel cell lines and xenografts have been developed. This study evaluates the transcriptome of an extended series of IBC preclinical models and performed a comparative analysis with patient samples to determine the extent to which the current models recapitulate the molecular characteristics of IBC observed clinically. We demonstrate that the IBC preclinical models are exclusively estrogen receptor (ER)-negative and of the basal-like subtype, which reflects to some extent the predominance of these subtypes in patient samples. The IBC-specific 79-signature we previously reported was retrained and discriminated between IBC and non-IBC preclinical models, but with a relatively high rate of false positive predictions. Further analyses of gene expression profiles revealed important roles for cell proliferation, MYC transcriptional activity, and TNFɑ/NFκB in the biology of IBC. Patterns of MYC expression and transcriptional activity were further explored in patient samples, which revealed interactions with ESR1 expression that are contrasting in IBC and nIBC and notable given the comparatively poor outcomes of ER+ IBC. Our analyses also suggest important roles for NMYC, MXD3, MAX, and MLX in shaping MYC signaling in IBC. Overall, we demonstrate that the IBC preclinical models can be used to unravel cancer cell intrinsic molecular features, and thus constitute valuable research tools. Nevertheless, the current lack of ER-positive IBC models remains a major hurdle, particularly since interactions with the ER pathway appear to be relevant for IBC.

Highlights

  • Inflammatory breast cancer (IBC) is an aggressive and highly metastatic form of breast cancer

  • We demonstrated that the estrogen receptor (ER)/HER2 combined subtypes were the best predictor of the clustering pattern (AIC = 59.881), followed by the ER status (AIC = 63.195), the tumor phenotype (AIC = 70.293), the PR status (AIC = 74.277), and the HER2 status (AIC = 82.575)

  • Given these results and since we observed that all 32 different preclinical models cluster on terminal branches, we argue that the adopted normalization strategy was effective in removing batch-specific expression variation, that relevant gene expression themes are preserved, and that replicate gene expression profiles (GEPs) can be reliably averaged

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Summary

Introduction

Inflammatory breast cancer (IBC) is an aggressive and highly metastatic form of breast cancer. As a consequence of the rapid onset and early metastasis, patients with IBC display an unfavorable prognosis, with 5-year overall survival rates of 40% despite multimodality treatment[2,3,4]. IBC is a clinical diagnosis based on the rapid onset of inflammatory symptoms: patients present with a red, enlarged breast associated with shooting pains and warmth. The need for better, more efficient, and IBC-specific treatment options is underscored by the fact that there are no significant changes in overall survival of patients up till now. IBC can be regarded as a human model for aggressive (breast) cancer behavior in general. A molecular signature predicting pathological complete response to neoadjuvant chemotherapy in IBC was identified[11] and catalogs of genomic alterations were described[12]. The role of the tumor microenvironment (TME) in IBC development and progression has been increasingly emphasized[13,14,15,16,17,18]

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