Mutational landscape of inflammatory breast cancer

Abstract

Background: Inflammatory breast cancer (IBC) is the most pro-metastatic form of BC. Better understanding of its enigmatic pathophysiology is crucial. We report here the largest whole-exome sequencing (WES) study of clinical IBC samples.

Methods: We retrospectively applied WES to 54 untreated IBC primary tumor samples and matched normal DNA. The comparator samples were 102 stage-matched non-IBC samples from TCGA. We compared the somatic mutational profiles, spectra and signatures, copy number alterations (CNAs), HRD and heterogeneity scores, and frequencies of actionable genomic alterations (AGAs) between IBCs and non-IBCs. The comparisons were adjusted for the molecular subtypes.

Results: The number of somatic mutations, TMB, and mutational spectra were not different between IBCs and non-IBCs, and no gene was differentially mutated or showed differential frequency of CNAs. Among the COSMIC signatures, only the age-related signature was more frequent in non-IBCs than in IBCs. We also identified in IBCs two new mutational signatures not associated with any environmental exposure, one of them having been previously related to HIF pathway activation. Overall, the HRD score was not different between both groups, but was higher in TN IBCs than TN non-IBCs. IBCs were less frequently classified as heterogeneous according to heterogeneity H-index than non-IBCs (21% vs 33%), and clonal mutations were more frequent and subclonal mutations less frequent in IBCs. More than 50% of patients with IBC harbored at least one high-level of evidence (LOE) AGA (OncoKB LOE 1-2, ESCAT LOE I-II), similarly to patients with non-IBC.

Conclusions: We provide the largest mutational landscape of IBC. Only a few subtle differences were identified with non-IBCs. The most clinically relevant one was the higher HRD score in TN IBCs than in TN non-IBCs, whereas the most intriguing one was the smaller intratumor heterogeneity of IBCs.

Keywords: Copy number alteration; Inflammatory breast cancer; Mutation; Whole-exome sequencing.

Fig. 1

Distribution of alterations of the top 31 genes mutated in IBCs. Oncoprint of the top 31 genes mutated in at least two IBC samples. Top: Number of smatic mutations in each sample. IHC-based molecular subtypes and IBC/non-IBC groups are color-coded as indicated in the legend. Bottom: somatic gene mutations color-coded according to the legend. The genes are ordered from top to bottom by decreasing percentage of altered IBCs right panel). The percentages of mutation in IBCs and non-IBCs are shown to the right of the Oncoprint

Fig. 2

Mutational processes of somatic SNVs in IBCs. A Proportions of base substitutions with respect to single-nucleotide-mutation contexts in IBCs and non-IBCs. B Similar to A but with respect to tri-nucleotide mutation contexts. C Proportions of the most represented COSMIC mutational signatures in the whole population age-related: signature 1; homologous recombination deficiency HRD: signature 3; APOBEC activation: signatures 2 and 13; mismatch repair: signatures 6, 20 and 26; POLE: signature 10). The signatures, IHC-based molecular subtypes and IBC/non-IBC groups are color-coded according to the legend

Fig. 3

Frequency plots of CNAs in IBCs. Frequencies vertical axis, from 0 to 100%) are plotted as a function of chromosome location for IBCs top) and non-IBCs middle). Vertical lines indicate chromosome boundaries. The CNAs are color-coded as indicated in the legend: gains red), amplifications dark red), losses green), and deletions dark green)

Fig. 4

HRD score, heterogeneity index and mutational clonality in IBCs. A Box-plot of HRD score in non-IBC and IBC samples. B Contingency table between HRD score and IBC/non-IBC groups. C Similar to A/, but per molecular subtype. D Box-plot of Heterogeneity H) index in non-IBC and IBC samples. E Contingency table between the tumor heterogeneity status and IBC/non-IBC groups. F Box-plot of the percentages of clonal and subclonal mutations in non-IBC and IBC samples

Fig. 5

Percentages of patients with AGAs in IBCs. A Bar-plots of the percentages of patients with IBC and non-IBC displaying at least one OncoKB AGA. The p-value is for the Fisher’s exact test. B Similar to A, but for OncoKB LOE 1–2 AGAs. C Similar to A, but for OncoKB LOE 3–4 AGAs. D Similar to A, but for ESCAT LOE I–II AGAs