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Positive correlation between transcriptomic stemness and PI3K/AKT/mTOR signaling scores in breast cancer, and a counterintuitive relationship with PIK3CA genotype.

Published version
Peer-reviewed

Change log

Abstract

A PI3Kα-selective inhibitor has recently been approved for use in breast tumors harboring mutations in PIK3CA, the gene encoding p110α. Preclinical studies have suggested that the PI3K/AKT/mTOR signaling pathway influences stemness, a dedifferentiation-related cellular phenotype associated with aggressive cancer. However, to date, no direct evidence for such a correlation has been demonstrated in human tumors. In two independent human breast cancer cohorts, encompassing nearly 3,000 tumor samples, transcriptional footprint-based analysis uncovered a positive linear association between transcriptionally-inferred PI3K/AKT/mTOR signaling scores and stemness scores. Unexpectedly, stratification of tumors according to PIK3CA genotype revealed a "biphasic" relationship of mutant PIK3CA allele dosage with these scores. Relative to tumor samples without PIK3CA mutations, the presence of a single copy of a hotspot PIK3CA variant was associated with lower PI3K/AKT/mTOR signaling and stemness scores, whereas the presence of multiple copies of PIK3CA hotspot mutations correlated with higher PI3K/AKT/mTOR signaling and stemness scores. This observation was recapitulated in a human cell model of heterozygous and homozygous PIK3CAH1047R expression. Collectively, our analysis (1) provides evidence for a signaling strength-dependent PI3K-stemness relationship in human breast cancer; (2) supports evaluation of the potential benefit of patient stratification based on a combination of conventional PI3K pathway genetic information with transcriptomic indices of PI3K signaling activation.

Description

Funder: pten research foundation


Funder: cancer research uk; funder-id: http://dx.doi.org/10.13039/501100000289

Keywords

Research Article, Medicine and health sciences, Biology and life sciences, Research and analysis methods

Journal Title

PLoS Genet

Conference Name

Journal ISSN

1553-7390
1553-7404

Volume Title

17

Publisher

Public Library of Science (PLoS)
Sponsorship
Cancer Research UK (unknown)
Cancer Research UK (unknown)
Cancer Research UK (unknown)
Cancer Research UK (60098573)
Cancer Research UK (unknown)
Cancer Research UK (CB4140)
Cancer Research UK (CRUK-A3086)
Cancer Research UK (CRUK-A9401)
Cancer Research UK (CRUK-A16942)
Cancer Research UK (CRUK-A7325)
Cancer Research UK (unknown)
Cancer Research UK (unknown)
Cancer Research UK (unknown)
Cambridge University Hospitals NHS Foundation Trust (CUH) (RG51913)
Cambridge University Hospitals NHS Foundation Trust (CUH) (unknown)
Department of Health (via National Institute for Health Research (NIHR)) (unknown)
Department of Health (via National Institute for Health Research (NIHR)) (NF-SI-0515-10090)
Cancer Research UK (CRUK-A7199)
Cancer Research UK (CRUK-A15580)