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Urinary detection of early responses to checkpoint blockade and of resistance to it via protease-cleaved antibody-conjugated sensors

Nature Biomedical Engineering volume 6, pages 310–324 (2022)Cite this article

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Abstract

Immune checkpoint blockade (ICB) therapy does not benefit the majority of treated patients, and those who respond to the therapy can become resistant to it. Here we report the design and performance of systemically administered protease activity sensors conjugated to anti-programmed cell death protein 1 (αPD1) antibodies for the monitoring of antitumour responses to ICB therapy. The sensors consist of a library of mass-barcoded protease substrates that, when cleaved by tumour proteases and immune proteases, are released into urine, where they can be detected by mass spectrometry. By using syngeneic mouse models of colorectal cancer, we show that random forest classifiers trained on mass spectrometry signatures from a library of αPD1-conjugated mass-barcoded activity sensors for differentially expressed tumour proteases and immune proteases can be used to detect early antitumour responses and discriminate resistance to ICB therapy driven by loss-of-function mutations in either the B2m or Jak1 genes. Biomarkers of protease activity may facilitate the assessment of early responses to ICB therapy and the classification of refractory tumours based on resistance mechanisms.

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Fig. 1: Antibody binding and therapeutic efficacy are unaffected by peptide conjugation.
Fig. 2: Sensing T cell killing of tumour cells by antibody–GzmB sensor conjugates.
Fig. 3: Urinary detection of ICB therapeutic response by administration of antibody–GzmB sensor conjugates.
Fig. 4: ICB resistance by LOF mutations in B2m and Jak1 leads to reduced GzmB activity.
Fig. 5: Proteases are dysregulated in ICB response and resistance.
Fig. 6: Mass-barcoded peptide sensors for multiplexed detection of protease activity.
Fig. 7: Urinary classification of ICB response and resistance.

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Data availability

The main data supporting the results in this study are available within the paper and its Supplementary Information. The sequencing datasets generated from murine tumours and analysed from human samples (Riaz, N. et al.11) have been deposited in NCBI’s Gene Expression Omnibus and are accessible through the GEO Series accession numbers GSE192796 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE192796) and GSE91061 (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE91061), respectively. Other data generated and analysed during the study are available from the corresponding author on reasonable request. Source data for tumour burdens are provided with this paper.

Code availability

All codes used in this work are available on request from the corresponding author.

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Acknowledgements

This work was funded by the NIH Director’s New Innovator Award DP2HD091793 and the National Cancer Institute R01 grant 5R01CA237210. Q.D.M. and A.S. were supported by the NSF Graduate Research Fellowships Program (Grant No. DGE-1650044). G.A.K. holds a Career Award at the Scientific Interface from the Burroughs Wellcome Fund. P.Q. is an ISAC Marylou Ingram Scholar and a Carol Ann and David D. Flanagan Faculty Fellow. This work was performed in part at the Georgia Tech Institute for Electronics and Nanotechnology, a member of the National Nanotechnology Coordinated Infrastructure, which is supported by the National Science Foundation (Grant ECCS-1542174). This content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. We thank the staff at Georgia Tech mass spectrometry core, flow cytometry analysis core and the animal facility for their assistance in performing our studies.

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Author notes

  1. These authors contributed equally: Quoc D. Mac, Anirudh Sivakumar.

Authors and Affiliations

  1. Wallace H. Coulter Department of Biomedical Engineering, Georgia Tech College of Engineering and Emory School of Medicine, Atlanta, GA, USA

    Quoc D. Mac, Anirudh Sivakumar, Hathaichanok Phuengkham, Congmin Xu, James R. Bowen, Fang-Yi Su, Samuel Z. Stentz, Hyoungjun Sim, Adrian M. Harris, Tonia T. Li, Peng Qiu & Gabriel A. Kwong

  2. Parker H. Petit Institute for Bioengineering and Bioscience, Atlanta, GA, USA

    Peng Qiu & Gabriel A. Kwong

  3. The Georgia Immunoengineering Consortium, Emory University and Georgia Tech, Atlanta, GA, USA

    Peng Qiu & Gabriel A. Kwong

  4. Winship Cancer Institute, Emory University, Atlanta, GA, USA

    Peng Qiu & Gabriel A. Kwong

  5. Institute for Electronics and Nanotechnology, Georgia Tech, Atlanta, GA, USA

    Gabriel A. Kwong

  6. Integrated Cancer Research Center, Georgia Tech, Atlanta, GA, USA

    Gabriel A. Kwong

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  1. Quoc D. Mac
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Contributions

Q.D.M., J.R.B. and G.A.K. conceived the idea. Q.D.M., A.S., H.P., C.X., J.R.B, F.-Y.S., S.Z.S., P.Q. and G.A.K. designed experiments and interpreted results. Q.D.M., A.S., H.P., C.X., J.R.B, F.-Y.S., S.Z.S., H.S., A.M.H. and T.T.L. carried out the experiments. Q.D.M., A.S. and G.A.K. wrote the manuscript.

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Correspondence to Gabriel A. Kwong.

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G.A.K. is co-founder of and serves as consultant to Glympse Bio and Satellite Bio. This study could affect his personal financial status. The terms of this arrangement have been reviewed and approved by Georgia Tech in accordance with its conflict-of-interest policies. Q.D.M., J.R.B. and G.A.K are listed as inventors on a patent application (PCT/US2019/050530) pertaining to the results of the paper. The patent applicant is the Georgia Tech Research Corporation. The names of the inventors are Quoc Mac, James Bowen and Gabriel Kwong. The patent is currently pending/published (publication number WO2020055952A1). The mass-barcoded antibody–sensor conjugates and related applications are covered in this patent.

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Extended data

Extended Data Fig. 1 Synthesis strategy for antibody-sensor conjugates for biodistribution of antibody and GzmB cleavage.

a, Synthetic scheme of antibody-sensor conjugate labelled with near infrared fluorophore VT750 to determine antibody biodistribution. b, Synthetic scheme of NIR activatable GzmB probe, consisting of fluorescently quenched GzmB substrate conjugated to αPD1 antibody.

Extended Data Fig. 2 Biodistribution of antibody-sensor conjugates and GzmB cleavage.

a, Schematic of antibody-sensor conjugate labelled with near infrared fluorophore VT750 to determine antibody biodistribution. b, Representative whole organ images and c, quantification of distribution of fluorescent signal in tumour and major organs (dLNs, tumour draining lymph nodes) (two-way ANOVA with Sidak’s post-test and correction for multiple comparisons, ns = not significant, n = 5 biological replicates, error bars depict s.e.m.). d, Schematic and in vitro cleavage of NIR activatable GzmB probe labelled with quenched near infrared fluorophore 800CW to localize site of probe activation (FC, fold change; ****P < 0.0001, n = 3 technically independent wells, error bars depict s.e.m.). e, Representative whole organ images and f, quantification of reporter fluorescence after treatment with Iso-GS or αPD1-GS (two-way ANOVA with Sidak’s post-test and correction for multiple comparisons, *P = 0.040, n = 4-5 biological replicates, error bars depict s.e.m.).

Extended Data Fig. 3 Diagnostic performance of αPD1-GS in ICB nonresponsive models.

a, Average and b, individual tumour growth curves of CT26 tumour bearing mice treated with either αCTLA4-GS or matched IgG2 isotype control (Iso-GS) (two-way ANOVA with Sidak’s post-test and correction for multiple comparisons, ns = not significant, n = 10-11 biological replicates, error bars depict s.e.m.). Black arrows denote the treatment time points. c, Normalized urine fluorescence of mice with CT26 tumours after each administration of αCTLA4-GS or Iso-GS (two-way ANOVA with Sidak’s post-test and correction for multiple comparisons, ns = not significant, n = 10-11 biological replicates). d, Average and e, individual tumour growth curves of CT26 tumour bearing mice treated with αPD1-GS or matched IgG1 isotype control (Iso-GS) (two-way ANOVA with Sidak’s post-test and correction for multiple comparisons, ns = not significant, n = 6 biological replicates, error bars depict s.e.m.). Black arrows denote the treatment time points. f, Normalized urine fluorescence of mice with CT26 tumours after each administration of αPD1-GS or Iso-GS (two-way ANOVA with Sidak’s post-test and correction for multiple comparisons, ns = not significant, n = 6 biological replicates).

Source data

Extended Data Fig. 4 Differential expression analysis of proteases in ICB response and resistance.

a, Heatmaps showing row-normalized expression (FPKM) of proteases differentially expressed between αPD1-treated WT tumours and IgG1-treated controls (n = 5 biological replicates). b, (Left) Volcano plots summarizing differentially expressed proteases between αPD1-treated B2m−/− and Jak1−/− MC38 tumours (n = 5 biological replicates). The threshold for differentially expressed genes (opaque dots) was defined as P value ≤ 0.05 and |log2(fold change)| ≥ 1. (Right) Heatmaps showing row-normalized expression (FPKM) of proteases differentially expressed between B2m−/− and Jak1−/− MC38 tumours (n = 5 biological replicates). c, (Left) Volcano plots summarizing differentially expressed proteases between human tumours from responders (CR + PR) and non-responders (PD) (n = 5 independent patient samples). The threshold for differentially expressed genes was defined as P value ≤ 0.01 and |log2(fold change)| ≥ 1. (Right) Heatmaps showing row-normalized expression (FPKM) of proteases differentially expressed between human tumours from responders (CR + PR) and non-responders (PD) (n = 5 independent patient samples).

Supplementary information

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Source data

Source Data Fig. 1

Source data for tumour burden.

Source Data Fig. 3

Source data for tumour burden.

Source Data Fig. 4

Source data for tumour burden.

Source Data Extended Data Fig. 3

Source data for tumour burden.

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Mac, Q.D., Sivakumar, A., Phuengkham, H. et al. Urinary detection of early responses to checkpoint blockade and of resistance to it via protease-cleaved antibody-conjugated sensors. Nat. Biomed. Eng 6, 310–324 (2022). https://doi.org/10.1038/s41551-022-00852-y

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