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. 2024 Nov;131(9):1543-1554.
doi: 10.1038/s41416-024-02852-y. Epub 2024 Sep 25.

Functional activation of the AKT-mTOR signalling axis in a real-world metastatic breast cancer cohort

Deepika Prasad #  1 , Elisa Baldelli #  2 , Edik M Blais  3 , Justin Davis  4 , Emna El Gazzah  1 , Claudius Mueller  4 , Alison Gomeiz  1   2 , Aisha Ibrahim  1 , Avani Vinayak Newrekar  1 , Brian A Corgiat  4 , Rick Dunetz  5 , Emanuel F Petricoin Iii  1   2 , Qi Wei  6 , Mariaelena Pierobon  7   8
Affiliations

Functional activation of the AKT-mTOR signalling axis in a real-world metastatic breast cancer cohort

Deepika Prasad et al. Br J Cancer. 2024 Nov.

Abstract

Background: Mutations of the PIK3CA/AKT/mTOR axis are common events in metastatic breast cancers (MBCs). This study was designed to evaluate the extent to which genetic alterations of the PIK3CA/AKT/mTOR can predict protein activation of this signalling axis in MBCs.

Methods: Molecular profiles were generated by CLIA-certified laboratories from a real-world evidence cohort of 171 MBC patients. Genetic alterations of the PIK3CA pathway were measured using next-generation sequencing. Activation levels of AKT and downstream signalling molecules were quantified using two orthogonal proteomic methods. Protein activity was correlated with underlying genomic profiles and response to CDK4/6 inhibition in combination with endocrine treatment (ET).

Results: Oncogenic alterations of the PIK3CA/AKT/PTEN pathway were identified in 49.7% of cases. Genomic profiles emerged as poor predictors of protein activity (AUC:0.69), and AKT phosphorylation levels mimicked those of mutant lesions in 76.9% of wild-type tumours. High phosphorylation levels of the PI3K/AKT/mTOR downstream target p70S6 Kinase (T389) were associated with shorter PFS in patients treated with CDK4/6 inhibitors in combination with ET (HR:4.18 95%CI:1.19-14.63); this association was not seen when patients were classified by mutational status.

Conclusions: Phosphoprotein-based measurements of drug targets and downstream substrates should be captured along with genomic information to identify MBCs driven by the PI3K/AKT/mTOR signalling.

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Conflict of interest statement

The authors are inventors of US Government and University-assigned patents and patent applications covering aspects of the technologies. As inventors, they are entitled to receive royalties as provided by US Law and George Mason University policy. MP and EFP receive royalties from Theralink Technologies, Inc. MP and EFP are consultants to and/or shareholders of Theralink Technologies, Inc; EFP is a shareholder and consultant of Perthera, Inc.

Figures

Fig. 1
Fig. 1. Study workflow and genomic characterisation of 176 MBCs retrospectively identified from a real-world evidence database.
Summary of the molecular information collected from each of the 176 patients enroled in the study (a). Overall study design along with the molecular information available for each cohort and data processing pipeline (b). Packed bubble graph depicting the most frequent genomic alterations identified across the 176 patients in the Side-Out cohort (c); the dimension of each circle is proportional to the number of occurrences. Red circles indicate genes detected in at least 10% of the study population. Matrix illustrating frequency and co-occurrences of the ten most frequently mutated or amplified genes in the Side-Out cohort (d and e, respectively).
Fig. 2
Fig. 2. Frequencies of oncogenic alterations of members of the PIK3CA pathway in the Side-Out study compared to two cohorts of MBC patients enroled in a single academic institution.
Matrix illustrating frequencies of mutations and amplifications across ten members of the PIK3CA pathway in the Side-Out cohort (a); tumours were subdivided based on the molecular subtypes. HR+/HER2- tumours are shown in the top panel (a). Cumulative number of cases with genetic alterations of members of the PIK3CA pathway by tumour subtype in the Side-Out cohort (b) and the Inserm cohort retrieved from the GENIE database (c). Matrix illustrating frequencies of mutations and amplifications across ten members of the PIK3CA pathway in the Inserm cohort (d); tumours were subdivided based on the molecular subtypes; HR+/HER2- tumours are shown in the top panel.
Fig. 3
Fig. 3. Functional activation of the AKT-mTOR signalling axis in MBCs based on underlying oncogenic alterations of genes encoding for members of the PIK3CA pathway.
Mosaic plots showing correlations between mutational status and phosphorylated levels of AKT (pAKT) measured by IHC and classified on a dichotomous scale (high versus low) (a). The proportion of patients with high AKT activity was first compared between wild-type and PIK3CA, AKT and PTEN mutant/amplified tumours. The analysis was then extended to compare AKT activity in wild-type tumours and lesions with any genetic alterations of the PIK3CA pathway (PIK3CA pathway alterations). Tile plots summarising frequencies of genetic alterations of the PIK3CA pathway along with phosphorylated AKT levels measured by IHC (b). Unsupervised hierarchical clustering Ward’s method assessing activation of six members of the PI3K/AKT/mTOR signalling axis in wild-type tumours and lesions harbouring oncogenic alterations of the PIK3CA pathway (c). Functional protein activation was measured on a continuous scale using RPPA percentile scores. Tumours’ molecular subtypes are listed and colour-coded on the x-axis. On the y-axis, samples with underlying genomic alterations are shown in black. RPPA continuous data are shown on a blue (low activation) to red (high activation) scale. Violin plots comparing activation of the signalling molecules in samples harbouring alterations of any gene of the PIK3CA axis and wild-type tumours (d); sample median is shown for each plot and asterisks denote comparisons that were statistically different (p < 0.01). The receiver operating characteristic (ROC) curve shows the performance of mutations of the PIK3CA pathway as potential classifiers for predicting AKT phosphorylation levels in MBCs along with the corresponding area under the curve (AUC) (e). Violin plots comparing activation levels of signalling molecules across the three most frequently detected PIK3CA oncogenic mutations (f).
Fig. 4
Fig. 4. Activation of the AKT-mTOR signalling axis in HR+/HER2- MBCs and their implications for predicting survival to first-line treatment with a CDK4/6 inhibitor in combination with endocrine treatment.
Violin plots comparing activation levels, measured as RPPA percentile scores, of signalling molecules in HR+/HER2- MBCs harbouring alterations of any gene of the PIK3CA axis (a); sample median is shown for each plot, and asterisks denote comparisons that were statistically different (p < 0.02). The receiver operating characteristic (ROC) curve shows the performance of mutations of the PIK3CA pathway as potential classifiers for predicting AKT phosphorylation levels in HR+/HER2- MBCs along with the corresponding area under the curve (AUC) (b). Heat map capturing activation levels of AKT (S473) and (T308) across 29 cell lines publicly available in the DepMap database. HR+/Her2- cells are shown in blue (c). Heat map showing PIK3CA dependency in 38 cell lines that underwent CRISPR and Ribonucleic acid interference (RNAi) screening (d). Unsupervised hierarchical clustering using Ward’s method assessing activation of the PI3K/AKT/mTOR signalling axis in the MCF-7, T47D and T47D abemaciclib-resistant cells; functional protein activation was measured on a continuous scale using RPPA values (e). Cell viability line plot of MCF-7 and T47D cells treated with capivasertib (range from 0.01–10 μM) along with box plot depicting the RPPA continuous values of phospho-AKT (T308) and phospho-4EBP1 (S65) and (T70) (p < 0.01). Median, highest and lowest values of experimental replicates are shown; asterisks denote comparisons that are statistically significant (f). Cell viability line plot of T47D parental and abemaciclib-resistant cells treated with buparlisib (range from 0.007 to 1 μM) along with box plot depicting the RPPA continuous values of phospho-AKT (T308) and phospho-p70S6 Kinase (T389) (p < 0.01 and 0.05, respectively). Medians, highest and lowest values of experimental replicates are shown; the asterisks denote comparisons that are statistically significant (g). Kaplan-Meier plot along with hazard ratio for progression-free survival in days and 95% confidence interval for patients with genomic alterations of any members of the PIK3CA pathway (HR: 0.58; CI: 0.14–2.36), PIK3CA (HR:0.67; CI 0.19–2.38), and phospho-p70 S6 Kinase (T389) activity (HR: 4.18; CI: 1.19–14.63) (h). P70S6 kinase activity levels were classified on a binary scale (high/low) based on the population median of the continuous RPPA data. Diagram showing a workflow for integrating multi-omic-based profiling for allocating patients to targeted treatments against members of the PI3K/AKT/mTOR pathway (i).
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