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Oxyhaemoglobin saturation NIR-IIb imaging for assessing cancer metabolism and predicting the response to immunotherapy

Nature Nanotechnology volume 19, pages 124–130 (2024)Cite this article

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Abstract

In vivo quantitative assessment of oxyhaemoglobin saturation (sO2) status in tumour-associated vessels could provide insights into cancer metabolism and behaviour. Here we develop a non-invasive in vivo sO2 imaging technique to visualize the sO2 levels of healthy and tumour tissue based on photoluminescence bioimaging in the near-infrared IIb (NIR-IIb; 1,500–1,700 nm) window. Real-time dynamic sO2 imaging with a high frame rate (33 Hz) reveals the cerebral arteries and veins through intact mouse scalp/skull, and this imaging is consistent with the haemodynamic analysis results. Utilizing our non-invasive sO2 imaging, the tumour-associated-vessel sO2 levels of various cancer models are evaluated. A positive correlation between the tumour-associated-vessel sO2 levels and the basal oxygen consumption rate of corresponding cancer cells at the early stages of tumorigenesis suggests that cancer cells modulate the tumour metabolic microenvironment. We also find that a positive therapeutic response to the checkpoint blockade cancer immunotherapy could lead to a dramatic decrease of the tumour-associated-vessel sO2 levels. Two-plex dynamic NIR-IIb imaging can be used to simultaneously observe tumour-vessel sO2 and PD-L1, allowing a more accurate prediction of immunotherapy response.

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Fig. 1: NIR-IIb luminescent pEr nanoprobe for assessing blood oxygen saturation.
Fig. 2: In vivo non-invasive dynamic sO2 imaging of mouse cerebral vasculature.
Fig. 3: In vivo sO2 imaging and TAV-sO2 assessment of different tumour models.
Fig. 4: In vivo two-plex tumour imaging in the same NIR-IIb window utilizing pEr and ErNPs.

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Data availability

Source data are available for Figs. 1–4. Other data that support the findings of this study are available from the corresponding author upon request. Source data are provided with this paper.

Code availability

The code that has been used for this work is available from the corresponding authors upon request.

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Acknowledgements

This study was supported by the National Key Research and Development Program of China (number 2021YFA1200900 for C.C. and Y.Z; number 2022YFA1207300 for Y.Z.) and the China Postdoctoral Science Foundation (number 2021M690804 for C.W.). We thank L. Zhou and S. Yu, HORIBA (China), for assistance with spectra and quantum yield measurement. We also thank Z. Ma for assistance with principal-component analysis.

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  1. These authors contributed equally: Zhiguo Fang, Chenlei Wang, Jingrun Yang.

Authors and Affiliations

  1. CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety, CAS Center for Excellence in Nanoscience, National Center for Nanoscience and Technology, Chinese Academy of Sciences, Beijing, China

    Zhiguo Fang, Chenlei Wang, Jingrun Yang, Zhizheng Song, Chunyu Xie, Yu Ji, Chunying Chen, Zhiyuan Hu & Yeteng Zhong

  2. University of Chinese Academy of Sciences, Beijing, China

    Zhiguo Fang, Chenlei Wang, Zhizheng Song, Chunyu Xie, Qiang Zheng, Chunying Chen, Zhiyuan Hu & Yeteng Zhong

  3. Department of General Surgery, the First Medical Center of Chinese PLA General Hospital, Beijing, China

    Jingrun Yang & Xiaohui Du

  4. School of Life Science and Technology, Xidian University, Xi’an, China

    Yu Ji & Zhongliang Wang

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Contributions

Y.Z. and Z.F. conceived and designed the experiments. Z.F., C.W., J.Y., Y.J., C.X., Z.S. and Q.Z. performed the experiments. Z.F., C.W., J.Y., Z.W., X.D., C.C., Z.H. and Y.Z. analysed the data and wrote the paper. All authors discussed the results and commented on the paper.

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Correspondence to Chunying Chen, Zhiyuan Hu or Yeteng Zhong.

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Nature Nanotechnology thanks Hak Soo Choi and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary Figs. 1–19.

Reporting Summary

Supplementary Video 1

Real-time NIR-IIb in vivo dynamic sO2 imaging (650:980 model) of mouse cerebral blood flow in a BALB/c mouse brain. Total video time, 15 s; frame rate, 33 Hz; playing at 1× speed.

Supplementary Video 2

Real-time NIR-IIb in vivo dynamic sO2 imaging (650:980 model) of a 4T1 tumour mouse. Total video time, 24 s; frame rate, 30 Hz; playing at 2× speed.

Supplementary Video 3

Two-plex NIR-IIb in vivo dynamic co-localization imaging of a CT26 tumour mouse at 24 h post-treatment of ErNPs-aPDL1. The sO2 imaging was performed in the 650:808 model. Total video time, 10 s; frame rate, 10 Hz; playing at 2× speed.

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Fang, Z., Wang, C., Yang, J. et al. Oxyhaemoglobin saturation NIR-IIb imaging for assessing cancer metabolism and predicting the response to immunotherapy. Nat. Nanotechnol. 19, 124–130 (2024). https://doi.org/10.1038/s41565-023-01501-4

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