Mutational profiles in triple-negative breast cancer defined by ultradeep multigene sequencing show high rates of PI3K pathway alterations and clinically relevant entity subgroup specific differences

Mark Kriegsmann, Volker Endris, Thomas Wolf, Nicole Pfarr, Albrecht Stenzinger, Sibylle Loibl, Carsten Denkert, Andreas Schneeweiss, Jan Budczies, Peter Sinn, Wilko Weichert, Mark Kriegsmann, Volker Endris, Thomas Wolf, Nicole Pfarr, Albrecht Stenzinger, Sibylle Loibl, Carsten Denkert, Andreas Schneeweiss, Jan Budczies, Peter Sinn, Wilko Weichert

Abstract

Mutational profiling of triple-negative breast cancer (TNBC) by whole exome sequencing (WES) yielded a landscape of genomic alterations in this tumor entity. However, the clinical significance of these findings remains enigmatic. Further, integration of WES in routine diagnostics using formalin-fixed paraffin-embedded (FFPE) material is currently not feasible. Therefore, we designed and validated a breast cancer specific gene panel for semiconductor-based sequencing comprising 137 amplicons covering mutational hotspots in 44 genes and applied this panel on a cohort of 104 well-characterized FFPE TNBC with complete clinical follow-up. TP53 mutations were present in more than 80% of cases. PI3K pathway alterations (29.8%) comprising mainly PIK3CA mutations (22.1%) but also mutations and/or amplifications/deletions in other PI3K-associated genes (7.7%) were far more frequently observed, when compared to WES data. Alterations in MAPK signaling genes (8.7%) and cell-cycle regulators (14.4%) were also frequent. Mutational profiles were linked to TNBC subgroups defined by morphology and immunohistochemistry. Alterations in cell-cycle pathway regulators were linked with better overall (p=0.053) but not disease free survival. Taken together, we could demonstrate that breast cancer targeted hotspot sequencing is feasible in a routine setting and yields reliable and clinically meaningful results. Mutational spectra were linked to clinical and immunohistochemically defined parameters.

Conflict of interest statement

Conflict of interest

The authors declare that there is no conflict of interest.

Figures

Figure 1. Distribution of molecular alterations sorted…
Figure 1. Distribution of molecular alterations sorted for molecularly defined subtypes in TNBC
Figure 2. Molecular alterations in TNBC depicted…
Figure 2. Molecular alterations in TNBC depicted in the pathway context
The darkness of the boxes indicates frequency of mutations of the respective gene. A white small circle within a box indicates deletions, a black small circle amplifications. Arrow: Activation. Bar: Inhibition. Dotted line: Degradation. Flash: Transcriptional upregulation.
Figure 3. Subclonality and overlap of pathway…
Figure 3. Subclonality and overlap of pathway alterations
(A) Percentage of events with allele frequencies below 40% for the two most frequently mutated TNBC genes TP53 and PIK3CA. (B) Overlap of pathway alterations.
Figure 4. Immunohistochmically defined subgoups and molecular…
Figure 4. Immunohistochmically defined subgoups and molecular profiles
(A) Immunohistochemical classification algorithm (according to Elsawaf et al. [12]) (B) Distribution of pathway alterations according to IHC TNBC subgroups.
Figure 5. Overall survival of patients stratified…
Figure 5. Overall survival of patients stratified for the presence/absence of mutations in TP53
(A), the PI3K pathway (B), cell cycle pathways (C) and MAPK associated pathways (D).

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