Use of metabolic imaging to monitor heterogeneity of tumour response following therapeutic mTORC1/2 pathway inhibition
The PI3K-mTOR-AKT pathway regulates tumour proliferation, gene expression and metabolism, but pathway inhibition induces heterogeneous feedback reactivation, limiting anti-tumour responses. Measuring heterogeneity of pathway inhibition in tissues using protein biomarker phosphorylation or location is challenging. An integrated multi-modal imaging workflow was developed to assess the heterogeneity of AZD2014 (mTORC1/2 inhibitor) response in a PTEN-null renal cancer model. Spatial responses of metabolite biomarkers were analysed by mass spectrometry imaging (MSI). Control and treated tumours were classified according to metabolite-defined regions enriched in control versus AZD2014-treated tumours, respectively. Noticeably, AZD2014-treated tumours retained regions similar to regions dominant in untreated tumours. Imaging mass cytometry analysis of protein biomarkers in 'control-like' regions following AZD2014 treatment showed reduced phospho-S6, indicating suppression, but retained high expression of the glucose transporter GLUT1. Increasing PI3K-AKT inhibition by combining with AZD8186 (PI3Kβ inhibitor) further decreased the control-like metabolic signature, showing PI3K-dependent resistance. This demonstrates that MSI-based workflows yield novel insights into the pharmacodynamic effects of mTORC1/2 inhibition in tumours, which classical biomarkers do not resolve. Coupling these workflows with spatial-omics approaches can deliver greater insights into heterogeneity of treatment response.
Authors
- Mariia Yuneva (ORCID: https://orcid.org/0000-0003-3455-9374)
- George Poulogiannis (ORCID: https://orcid.org/0000-0002-0529-8614)
- John F. Marshall (ORCID: https://orcid.org/0000-0002-0494-2295)
- Alan Race (ORCID: https://orcid.org/0000-0001-8996-2641)
- Josephine Bunch (ORCID: https://orcid.org/0000-0002-4257-1296)
- Kevin Michael Brindle (ORCID: https://orcid.org/0000-0003-3883-6287)
- Richard J. A. Goodwin (ORCID: https://orcid.org/0000-0001-5699-8488)
- Grégory Hamm (ORCID: https://orcid.org/0000-0002-0769-9411)
- Urszula M. Polanska (ORCID: https://orcid.org/0000-0003-1017-594X)
- Stephanie Ling (ORCID: https://orcid.org/0000-0002-1237-091X)
- Simon T. Barry (ORCID: https://orcid.org/0000-0002-8511-0588)
- Zoltán Takáts (ORCID: https://orcid.org/0000-0002-0795-3467)
- Andrew D. Campbell (ORCID: https://orcid.org/0000-0003-3930-1276)
- Owen J. Sansom (ORCID: https://orcid.org/0000-0001-9540-3010)
- Alex Dexter (ORCID: https://orcid.org/0000-0001-8536-4417)
- Shreya Sharma (ORCID: https://orcid.org/0000-0002-7527-8993)
Institutions
- AstraZeneca (United Kingdom) (GB)
- National Physical Laboratory (GB)
- The Francis Crick Institute (GB)
- Cancer Institute (WIA) (IN)
- Rosalind Franklin Institute (GB)
- Lymphatic Education & Research Network (US)
- Imperial College London (GB)
Publication Details
- Journal
- Disease Models & Mechanisms
- Published
- 2025-02-01
- DOI
- https://doi.org/10.1242/dmm.050804
- Citations
- 3
- Primary Topic
- Cancer, Hypoxia, and Metabolism
- Type
- article
- Field-Weighted Citation Impact
- 2.81
Funders
- AstraZeneca
- Cancer Research UK
- Medical Research Council