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.
Your institute does not have access to this article
Subscribe to Nature+
Get immediate online access to the entire Nature family of 50+ journals
Subscribe to Journal
Get full journal access for 1 year
only $8.25 per issue
All prices are NET prices.
VAT will be added later in the checkout.
Tax calculation will be finalised during checkout.
Get time limited or full article access on ReadCube.
All prices are NET prices.
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 (email@example.com) upon reasonable request.
Punt, C. J., Koopman, M. & Vermeulen, L. From tumour heterogeneity to advances in precision treatment of colorectal cancer. Nat. Rev. Clin. Oncol. 14, 235–246 (2017).
Siriwardena, A. K., Mason, J. M., Mullamitha, S., Hancock, H. C. & Jegatheeswaran, S. Management of colorectal cancer presenting with synchronous liver metastases. Nat. Rev. Clin. Oncol. 11, 446–459 (2014).
Lennon, A. M. et al. Feasibility of blood testing combined with PET-CT to screen for cancer and guide intervention. Science 369, eabb9601 (2020).
Bach, P. B. et al. Benefits and harms of CT screening for lung cancer: a systematic review. JAMA 307, 2418–2429 (2012).
Chabon, J. J. et al. Integrating genomic features for non-invasive early lung cancer detection. Nature 580, 245–251 (2020).
Cohen, J. D. et al. Detection and localization of surgically resectable cancers with a multi-analyte blood test. Science 359, 926–930 (2018).
Liu, M. C. et al. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann. Oncol. 31, 745–759 (2020).
Aalipour, A. et al. Engineered immune cells as highly sensitive cancer diagnostics. Nat. Biotechnol. 37, 531–539 (2019).
Kirkpatrick, J. D. et al. Urinary detection of lung cancer in mice via noninvasive pulmonary protease profiling. Sci. Transl. Med. 12, eaaw0262 (2020).
Rakhit, C. P. et al. Early detection of pre-malignant lesions in a KRAS(G12D)-driven mouse lung cancer model by monitoring circulating free DNA. Dis. Model Mech. 12, dmm036863 (2019).
Hori, S. S. & Gambhir, S. S. Mathematical model identifies blood biomarker-based early cancer detection strategies and limitations. Sci. Transl. Med. 3, 109ra116 (2011).
van der Stok, E. P., Spaander, M. C. W., Grunhagen, D. J., Verhoef, C. & Kuipers, E. J. Surveillance after curative treatment for colorectal cancer. Nat. Rev. Clin. Oncol. 14, 297–315 (2017).
Rojas Llimpe, F. L. et al. Imaging in resectable colorectal liver metastasis patients with or without preoperative chemotherapy: results of the PROMETEO-01 study. Br. J. Cancer 111, 667–673 (2014).
Weissleder, R., Tung, C. H., Mahmood, U. & Bogdanov, A. Jr In vivo imaging of tumors with protease-activated near-infrared fluorescent probes. Nat. Biotechnol. 17, 375–378 (1999).
Ronald, J. A., Chuang, H. Y., Dragulescu-Andrasi, A., Hori, S. S. & Gambhir, S. S. Detecting cancers through tumor-activatable minicircles that lead to a detectable blood biomarker. Proc. Natl Acad. Sci. USA 112, 3068–3073 (2015).
Kwong, G. A. et al. Mass-encoded synthetic biomarkers for multiplexed urinary monitoring of disease. Nat. Biotechnol. 31, 63–70 (2013).
Kwon, E. J., Dudani, J. S. & Bhatia, S. N. Ultrasensitive tumour-penetrating nanosensors of protease activity. Nat. Biomed. Eng. 1, 0054 (2017).
Dudani, J. S., Ibrahim, M., Kirkpatrick, J., Warren, A. D. & Bhatia, S. N. Classification of prostate cancer using a protease activity nanosensor library. Proc. Natl Acad. Sci. USA 115, 8954–8959 (2018).
Webb, B. A., Chimenti, M., Jacobson, M. P. & Barber, D. L. Dysregulated pH: a perfect storm for cancer progression. Nat. Rev. Cancer 11, 671–677 (2011).
Quail, D. F. & Joyce, J. A. Microenvironmental regulation of tumor progression and metastasis. Nat. Med. 19, 1423–1437 (2013).
Hanahan, D. & Weinberg, R. A. Hallmarks of cancer: the next generation. Cell 144, 646–674 (2011).
Cremolini, C. et al. First-line chemotherapy for mCRC—a review and evidence-based algorithm. Nat. Rev. Clin. Oncol. 12, 607–619 (2015).
Weerakkody, D. et al. Family of pH (low) insertion peptides for tumor targeting. Proc. Natl Acad. Sci. USA 110, 5834–5839 (2013).
Wyatt, L. C. et al. Peptides of pHLIP family for targeted intracellular and extracellular delivery of cargo molecules to tumors. Proc. Natl Acad. Sci. USA 115, E2811–E2818 (2018).
Danino, T. et al. Programmable probiotics for detection of cancer in urine. Sci. Transl. Med. 7, 289ra284 (2015).
Dumitru, C. D., Antonysamy, M. A., Tomai, M. A. & Lipson, K. E. Potentiation of the anti-tumor effects of imidazoquinoline immune response modifiers by cyclophosphamide. Cancer Biol. Ther. 10, 155–165 (2010).
Estrella, V. et al. Acidity generated by the tumor microenvironment drives local invasion. Cancer Res. 73, 1524–1535 (2013).
Corbet, C. & Feron, O. Tumour acidosis: from the passenger to the driver’s seat. Nat. Rev. Cancer 17, 577–593 (2017).
Kalbasi, A. & Ribas, A. Tumour-intrinsic resistance to immune checkpoint blockade. Nat. Rev. Immunol. 20, 25–39 (2019).
Holohan, C., Van Schaeybroeck, S., Longley, D. B. & Johnston, P. G. Cancer drug resistance: an evolving paradigm. Nat. Rev. Cancer 13, 714–726 (2013).
Rohani, N. et al. Acidification of tumor at stromal boundaries drives transcriptome alterations associated with aggressive phenotypes. Cancer Res. 79, 1952–1966 (2019).
Damaghi, M. et al. Chronic acidosis in the tumour microenvironment selects for overexpression of LAMP2 in the plasma membrane. Nat. Commun. 6, 8752 (2015).
Swietach, P., Vaughan-Jones, R. D. & Harris, A. L. Regulation of tumor pH and the role of carbonic anhydrase 9. Cancer Metastasis Rev. 26, 299–310 (2007).
Kumar, S. et al. Magnetic resonance imaging in lung: a review of its potential for radiotherapy. Br. J. Radiol. 89, 20150431 (2016).
Longo, D. L. et al. In vivo imaging of tumor metabolism and acidosis by combining PET and MRI-CEST pH imaging. Cancer Res. 76, 6463–6470 (2016).
Roper, J. et al. Corrigendum: in vivo genome editing and organoid transplantation models of colorectal cancer and metastasis. Nat. Biotechnol. 35, 1211 (2017).
Walker-Samuel, S. et al. In vivo imaging of glucose uptake and metabolism in tumors. Nat. Med. 19, 1067–1072 (2013).
Chiche, J. et al. Hypoxia-inducible carbonic anhydrase IX and XII promote tumor cell growth by counteracting acidosis through the regulation of the intracellular pH. Cancer Res. 69, 358–368 (2009).
Yuan, Y. et al. Furin-mediated intracellular self-assembly of olsalazine nanoparticles for enhanced magnetic resonance imaging and tumour therapy. Nat. Mater. 18, 1376–1383 (2019).
Lindeman, L. R. et al. Differentiating lung cancer and infection based on measurements of extracellular pH with acidoCEST MRI. Sci. Rep. 9, 13002 (2019).
Park, J. H. et al. Magnetic iron oxide nanoworms for tumor targeting and imaging. Adv. Mater. 20, 1630–1635 (2008).
Jailkhani, N. et al. Noninvasive imaging of tumor progression, metastasis, and fibrosis using a nanobody targeting the extracellular matrix. Proc. Natl Acad. Sci. USA 116, 14181–14190 (2019).
Larimer, B. M. et al. Granzyme B PET imaging as a predictive biomarker of immunotherapy response. Cancer Res. 77, 2318–2327 (2017).
Huang, G. et al. PET imaging of occult tumours by temporal integration of tumour-acidosis signals from pH-sensitive 64Cu-labelled polymers. Nat. Biomed. Eng. 4, 314–324 (2020).
Wyatt, L. C., Lewis, J. S., Andreev, O. A., Reshetnyak, Y. K. & Engelman, D. M. Applications of pHLIP technology for cancer imaging and therapy. Trends Biotechnol. 35, 653–664 (2017).
Viola-Villegas, N. T. et al. Understanding the pharmacological properties of a metabolic PET tracer in prostate cancer. Proc. Natl Acad. Sci. USA 111, 7254–7259 (2014).
Chang, J. et al. Chemotherapy-generated cell debris stimulates colon carcinoma tumor growth via osteopontin. FASEB J. 33, 114–125 (2019).
Warren, A. D., Kwong, G. A., Wood, D. K., Lin, K. Y. & Bhatia, S. N. Point-of-care diagnostics for noncommunicable diseases using synthetic urinary biomarkers and paper microfluidics. Proc. Natl Acad. Sci. USA 111, 3671–3676 (2014).
Bhatia, S. N. et al. Sensors for detecting and imaging of cancer metastasis. US Patent Application No. 16/745,748 (2020).
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.
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.
Peer review information Nature Materials thanks Jeff Bulte and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.
Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
About this article
Cite this article
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