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Engineered immune cells as highly sensitive cancer diagnostics

Nature Biotechnology volume 37, pages 531–539 (2019)Cite this article

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Abstract

Endogenous biomarkers remain at the forefront of early disease detection efforts, but many lack the sensitivities and specificities necessary to influence disease management. Here, we describe a cell-based in vivo sensor for highly sensitive early cancer detection. We engineer macrophages to produce a synthetic reporter on adopting an M2 tumor-associated metabolic profile by coupling luciferase expression to activation of the arginase-1 promoter. After adoptive transfer in colorectal and breast mouse tumor models, the engineered macrophages migrated to the tumors and activated arginase-1 so that they could be detected by bioluminescence imaging and luciferase measured in the blood. The macrophage sensor detected tumors as small as 25–50 mm3 by blood luciferase measurements, even in the presence of concomitant inflammation, and was more sensitive than clinically used protein and nucleic acid cancer biomarkers. Macrophage sensors also effectively tracked the immunological response in muscle and lung models of inflammation, suggesting the potential utility of this approach in disease states other than cancer.

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Fig. 1: Schematic of diagnostic adoptive cell transfer.
Fig. 2: M2 macrophages are identified by Arg1 expression in vitro and in vivo.
Fig. 3: Macrophages exhibit chemokine mediated migration toward tumors in vitro and in vivo.
Fig. 4: Macrophage sensors enable detection and visualization of small tumors in vivo.
Fig. 5: Macrophage sensors track the immunological response in two models of acute inflammation and wound healing.
Fig. 6: Macrophage sensors outperform clinically used cancer biomarkers.

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Data availability

The data supporting the findings of this study are available within the paper and its Supplementary Information files.

Change history

  • 18 December 2019

    In the version of this Article originally published, the ORCID for Sanjiv S. Gambhir was incorrect; the correct ORCID is 0000-0002-2711-7554. This has now been amended.

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Acknowledgements

Funding for this work was provided by the Canary Foundation (S.S.G.) and National Cancer Institute grant R01 CA082214 (S.S.G.). A.A. has received support from the National Institutes of General Medical Sciences Medical Scientist Training Program T32 training grant GM007365, the Paul and Daisy Soros Fellowship, and the Bio-X Graduate Student Fellowship. We would like to thank P. Chu for help with tissue processing.

Author information

Author notes

  1. These authors contributed equally: Hui-Yen Chuang, Surya Murty, Aloma L. D’Souza.

Authors and Affiliations

  1. Department of Bioengineering, Stanford University School of Medicine, Stanford, CA, USA

    Amin Aalipour, Surya Murty, Elise R. Robinson & Sanjiv S. Gambhir

  2. Molecular Imaging Program at Stanford, Stanford University School of Medicine, Stanford, CA, USA

    Amin Aalipour, Hui-Yen Chuang, Surya Murty, Aloma L. D’Souza, Seung-min Park, Chirag B. Patel, Corinne Beinat, Ivana Martinić, Gayatri Gowrishankar, Elise R. Robinson, Eamon Aalipour, Zahra Zhian & Sanjiv S. Gambhir

  3. Department of Radiology, Stanford University School of Medicine, Stanford, CA, USA

    Hui-Yen Chuang, Aloma L. D’Souza, Seung-min Park, Chirag B. Patel, Corinne Beinat, Ivana Martinić, Gayatri Gowrishankar, Eamon Aalipour, Zahra Zhian & Sanjiv S. Gambhir

  4. Department of Cancer Biology, Stanford University School of Medicine, Stanford, CA, USA

    Gunsagar S. Gulati

  5. Department of Neurology and Neurological Sciences, Stanford University School of Medicine, Stanford, CA, USA

    Chirag B. Patel

  6. Division of Blood and Marrow Transplantation, Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA

    Federico Simonetta

  7. Canary Center at Stanford for Cancer Early Detection, Stanford University School of Medicine, Palo Alto, CA, USA

    Sanjiv S. Gambhir

  8. Department of Materials Science and Engineering, Stanford University, Stanford, CA, USA

    Sanjiv S. Gambhir

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Contributions

A.A. and S.S.G conceived the project and designed all experiments. A.A., H.-Y.C., S.M., G.S.G., G.G., C.B.P, C.B., F.S., I.M. and E.R.R. conducted the experiments. A.A., A.L.D., S.P., G.S.G., C.B.P., C.B., E.A. and Z.Z. contributed to data analysis. A.A. and S.S.G. wrote the manuscript with contributions from all authors.

Corresponding author

Correspondence to Sanjiv S. Gambhir.

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Competing interests

A.A. and S.S.G. are co-inventors of a patent filed on the subject of this work which has been licensed by Earli, Inc. S.S.G. is a co-founder of Earli, Inc., which develops and translates early cancer detection strategies.

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Supplementary Figure 1 Metabolic and cytokine drivers of Arg1 expression in macrophages.

(a) 100 mM Lactic acid induces expression of Fizz1 and Arg1 mRNA in both bone marrow-derived (left) and RAW264.7 (right) macrophages 24 h after stimulation. n = 2 independent cultures for each macrophage type (b) Arg1 protein levels exhibit a dose-dependent response to IL-4, IL-13, and TCM as measured by arginase activity assays. 25 ng/mL IL-4 p = 0.005, t = 4.78, df = 5 (n = 3 independent cultures) and Low TCM p = 0.0035, t = 5.203, df = 5 (n = 3 independent cultures) by two-tailed unpaired t-test vs. control (n = 4 independent cultures). ** indicates statistical significance at p < 0.01. Data is shown as mean ± standard error of the mean (s.e.m). BMDM, bone marrow-derived macrophage; TCM, tumor conditioned media.

Supplementary Figure 2 VivoTrack 680 labeling of RAW264.7 macrophages.

Uniform labeling of macrophages (green) was observed with 2–3 orders of magnitude of fluorescence above unstained macrophages (blue). Experiment performed twice with similar results.

Supplementary Figure 3 Flow cytometry gating strategy for macrophage sorting.

(a) Flow cytometry gating strategy for adoptively transferred (VT680+) and native (VT680-) macrophages in tumor (n = 2 independent mice), spleen (n = 5 independent mice), lung (n = 3 independent mice), and liver (n = 3 independent mice). Populations for CD11b+F4/80+ cells were well-separated in all tissues and adoptively transferred macrophages were gated based on a fluorescence minus one control. Representative plots from n = 2 independent mice shown. FMO, fluorescence minus one. (b) Average fractional makeup of administered (VT680+) vs. endogenous (VT680-) macrophages present in various tissues five days after adoptive transfer shown across n = 2 (tumor, tumor spleen) and n = 3 (healthy spleen, healthy lung, healthy liver) independent mice.

Supplementary Figure 4 Immunofluorescence of macrophage localization relative to hypoxia in CT26 tumors.

Immunofluorescence of CT26 tumors from mice injected with fluorescently labeled bone marrow-derived monocytes (bottom) reveals co-localization of macrophages (red) with regions of hypoxia (green). Immunofluorescence of a CT26 tumor from mice not injected with pimonidazole and injected with non-fluorescently labeled bone marrow-derived monocytes (top) does not yield any signal in the green or red channels confirming specificity. Images are shown at 10x magnification and scale bars measure 250 μm. Representative images from n = 2 independent mice shown for each treatment. CB640, CellBrite 640; BMDM, bone marrow-derived monocytes.

Supplementary Figure 5 pArg1-Gluc reporter plasmid map.

The pArg1-Gluc construct contains the Gaussia Dura Luciferase immediately downstream of the 3780 base pair Arg1 enhancer/promoter sequence. The construct also contains the gene for eGFP under the control of the constitutive CMV promoter for cell sorting and determining transfection efficiency.

Supplementary Figure 6 Lung microtumors in a model of metastatic breast cancer.

One week after intravenous injection of 4T1 cells, visualized disease burden remains localized to the lungs by bioluminescence imaging (left). Representative image from n = 7 independent mice shown. Ex vivo examination of the lungs also reveals non-elevated microtumors lining the lung pleura (right). Representative image from n = 2 independent mice shown. Scale bars measure 1 cm.

Supplementary Figure 7 Macrophage sensor optimization in the subcutaneous localized model of colorectal cancer.

(a) Tumor volumes measured by digital caliper are well-correlated with tumor volumes estimated by bioluminescence imaging (Pearson r = 0.9581, r2 = 0.918, two-tailed p = 0.0007, n = 7 independent mice). Dashed lines show 95% confidence interval of the linear regression. (b) The engineered macrophage sensor was unable to detect visibly necrotic tumors with volumes > 1,500 mm3 (n = 11 independent healthy mice and n = 5 independent tumor-bearing mice). (c) In detection of 50–250 mm3 localized subcutaneous tumors (n = 7 independent mice), elevated plasma Gluc compared to healthy controls (n = 4 independent mice) was apparent 24 h after macrophage sensor injection but signal declined in subsequent days in both healthy and tumor bearing mice. (d) In the same tumor model, 1 million (n = 6 independent mice) and 2 million (n = 6 independent mice) injected macrophage sensors were unable to reliably distinguish tumor bearing mice from healthy controls (n = 6 independent mice). Data is shown as mean ± s.e.m. RLU, relative luminescence units.

Supplementary Figure 8 Bone marrow-derived monocyte purity and electroporation efficiency.

(a) Harvested BMDMs exhibited 96.3% purity by F4/80 staining after 5 days of differentiation in 20 ng/mL murine macrophage colony stimulating factor. Experiment performed 3 times with similar results. (b) BMDMs were electroporated with the pArg1-Gluc reporter plasmid with an efficiency of > 80% and viability ~60% as quantified by flow cytometry. Experiment performed 3 times with similar results.

Supplementary Figure 9 The effect of intravenously injected macrophage sensor on tumor progression.

Intravenous injection of BMDM sensor in subcutaneous tumor-bearing mice (n = 4) leads to an initial regression (Day 4, p = 0.0579, t = 2.451, df = 5, two-tailed unpaired t-test) of tumor volume relative to vehicle injected mice (n = 3) followed by resumption of exponential growth. Left plot shows growth of individual tumors and right plot shows average tumor volumes. Mice were sacrificed upon tumors exceeding 15 mm in any dimension and average tumor volumes in right plot are only shown for time points in which all mice in a group were still alive. Data in left panel shown as mean ± s.e.m. BMDM, bone marrow-derived macrophage.

Supplementary Figure 10 Deletion mutation limit of detection with locked nucleic acid probes.

Real-time qPCR amplification plots of CT26 and wildtype Balb/c genomic DNA show that the chromosome 7 (left) and 19 (right) deletions can be detected at allele frequencies of 0.1 and 1% respectively. Each condition is shown in triplicate. RFU, relative fluorescence units; AF, allele frequency.

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Aalipour, A., Chuang, HY., Murty, S. et al. Engineered immune cells as highly sensitive cancer diagnostics. Nat Biotechnol 37, 531–539 (2019). https://doi.org/10.1038/s41587-019-0064-8

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