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Microenvironment-triggered multimodal precision diagnostics

Abstract

Therapeutic outcomes in oncology may be aided by precision diagnostics that offer early detection, localization and the opportunity to monitor response to therapy. Here, we report a multimodal nanosensor engineered to target tumours through acidosis, respond to proteases in the microenvironment to release urinary reporters and (optionally) carry positron emission tomography probes to enable localization of primary and metastatic cancers in mouse models of colorectal cancer. We present a paradigm wherein this multimodal sensor can be employed longitudinally to assess burden of disease non-invasively, including tumour progression and response to chemotherapy. Specifically, we showed that acidosis-mediated tumour insertion enhanced on-target release of matrix metalloproteinase-responsive reporters in urine. Subsequent on-demand loading of the radiotracer 64Cu allowed pH-dependent tumour visualization, enabling enriched microenvironmental characterization when compared with the conventional metabolic tracer 18F-fluorodeoxyglucose. Through tailored target specificities, this modular platform has the capacity to be engineered as a pan-cancer test that may guide treatment decisions for numerous tumour types.

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Fig. 1: Targeting multivalent nanosensors to invasive CRC through tumour acidosis.
Fig. 2: Positron-emitting radionuclide-loaded 64Cu-PRISM achieved multimodal monitoring of CRC lung nodules.
Fig. 3: PRISM-enabled longitudinal, multimodal monitoring and imaging of CRC liver nodules.
Fig. 4: Non-invasive multimodal monitoring of the therapeutic response to a first-line chemotherapeutic by PRISM.

Data availability

The Cancer Genome Atlas (TCGA) Research Network (http://cancergenome.nih.gov) and FireBrowse (http://firebrowse.org) are open access resources with enriched cancer genomics data. All data that support the findings of this study are available within the article and Supplementary Information or from the corresponding author (sbhatia@mit.edu) upon reasonable request.

Code availability

The accompanying code can be found on GitHub (https://github.com/lhaomit/PK-model-for-PRISM). The code was run on MATLAB_R2018b. The model description is available in the Supplementary Information.

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Acknowledgements

We thank the Koch Institute Swanson Biotechnology Center for technical support, specifically V. Spanoudaki, S. Malstrom, M. Pandya and S. Elmiligy from the KI Animal Imaging & Preclinical Testing Core for assistance with PET-CT and IVIS imaging; M. Farhoud and P. Zakrzewski from Emit Imaging for cryo-fluorescence tomography; K. Cormier from the KI Histology Core for tissue sectioning and staining; D. Yun from the KI Nanotechnology Materials Core for electron microscopy imaging; R. Cook and A. Leshinsky from the KI Biopolymers & Proteomics Core for HPLC and mass spectrometry; W. Salman from the Keck Microscopy Facility for confocal microscopy; and D. Ma from the KI Bioinformatics & Computing Core for assistance with transcriptome data analysis. We also thank A. Warren for initial discussions of this work; A. Soleimany and J. Voog for critical reading of the manuscript. This study was supported in part by a Koch Institute Support Grant (P30-CA14051) from the National Cancer Institute (Swanson Biotechnology Center), a Core Center Grant (P30-ES002109) from the National Institute of Environmental Health Sciences, by the Koch Institute Frontier Research Program via the Casey and Family Foundation Cancer Research Fund, the Virginia and D.K. Ludwig Fund for Cancer Research, and the Koch Institute Marble Center for Cancer Nanomedicine. L.H. was supported by a KI Quinquennial Cancer Research Fellowship and fellowships from the American Cancer Society and the Ludwig Center for Molecular Oncology at MIT. S.N.B is a Howard Hughes Medical Institute investigator. This study is dedicated to Sanjiv Sam Gambhir, who inspired a generation of scientists with his vision for the role of precision health and integrated diagnostics and whom we tragically lost too soon.

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Contributions

L.H., H.E.F., F.B.G. and S.N.B. conceived and designed the research. L.H. carried out all the experiments and analysed the data. N.R. performed the immunofluorescent studies and data analysis. R.T.Z., E.M.P. and H.K. assisted with the animal studies. H.M. assisted with the PET-CT imaging. O.J.K. assisted with the PET-CT data analysis. L.H., H.E.F. and S.N.B. wrote the manuscript with feedback from all the authors.

Corresponding author

Correspondence to Sangeeta N. Bhatia.

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Competing interests

S.N.B. and L.H. are listed as inventors on a patent application49 related to the content of this work. S.N.B. holds equity in Glympse Bio, Satellite Bio, Cend Therapeutics and Catalio Capital; is a director at Vertex; consults for Moderna, and receives sponsored research funding from Johnson & Johnson. All the other authors declare no competing interests.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–19, Tables 1 and 2, and note.

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Supplementary Video 1

Coronal view of the cryo-fluorescence tomography in Fig. 1b.

Supplementary Video 2

Sagittal view of the cryo-fluorescence tomography in Fig. 1b.

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Hao, L., Rohani, N., Zhao, R.T. et al. Microenvironment-triggered multimodal precision diagnostics. Nat. Mater. 20, 1440–1448 (2021). https://doi.org/10.1038/s41563-021-01042-y

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