A poor prognosis gene transcription signature associated with PIK3CA mutation in ER+ breast cancer.
Loi S, Haibe-Kains B, Sotiriou C, Lallemand F, Piccart MJ, Wayne P and McArthur GA
Background: The phosphathidylinositol-3-kinase (PI3K) signaling
pathway is commonly deregulated in breast cancer tumor biology. This
pathway contains many potential therapeutic targets. However, the
literature reporting the association between histopathological
correlates and clinical outcome has been inconsistent probably due to
the multiple mechanisms of activation and complex downstream
Methods: 173 estrogen receptor positive
breast cancers (ER+BC )were sequenced for PIK3CA activating mutations.
Corresponding gene expression profiles were available for 161 patients.
Ingenuity Pathway Analysis software was used to generate interaction
networks and test for enrichment of cellular functions between PIK3CA
mutation positive and normal samples.
Results: PIK3CA mutations were found in
45 samples (26%). The majority of mutations (80%) were found on exon
20. There was no significant association with mutation and lymph node
status, tumor grade or age, and a borderline association with tumor
size (p=0.056). No difference in mean gene expression level of AKT,
PTEN, ERBB2, STMN between PIK3CA mutation positive samples and wild
type was found. In contrast, TP53 and MYC levels were significantly
different (p= 0.03, p= 0.01 respectively). There was no association
between mutation status and clinical outcome (log rank p value =0.3).
Contrasting gene expression profiles of mutation positive samples and
wild type revealed 81 significantly differentially expressed genes
(p<0.001) highly enriched for genes involved in cellular morphology,
protein synthesis and gene expression. A gene-expression and
interaction-based outcome predictor consisting of 35 genes was then
constructed. This gene set could predict clinical outcome in 1228
independent ER+ BC samples HR: 1.39(95%CI 1.23-1.58) p<0.001.
Conclusions: PIK3CA mutations per se were
not significantly associated with a distinct phenotype or clinical
outcome in our dataset of 173 ER+ BC samples. However, we have
identified important gene interaction networks related to PI3K pathway
signaling due to PIK3CA mutations which may be useful for prognostic
and predictive markers and therapeutic development in ER+ BC.