High-spatiotemporal resolution deuterium metabolic imaging enables in vivo phenotyping of intra- and intertumoral heterogeneity.

Authors

Xinjie Liu, Sufei Wang, Jinrui Zhao, ShaSha Wang, Peng Sun, Xin Zhou, Maili Liu, Chaoyang Liu, Lucio Frydman, Qingjia Bao

Published in

Science advances. Volume 12. Issue 34. Pages eaef4377. Aug 21, 2026. Epub Aug 21, 2026.

Abstract

Intra- and intertumoral heterogeneities raise fundamental biological questions and have important implications for accurate cancer diagnosis, prognosis, and treatment. These heterogeneities reflect tumor complexity, including a pronounced diversity in metabolic phenotypes and profiles. This study demonstrates that in vivo deuterium metabolic imaging (DMI) data acquired with sufficiently high spatiotemporal resolution provide a minimally invasive approach to assess these heterogeneities. A multifrequency DMI approach was used to examine tumor heterogeneities within and between colon cancer models. Regions of high and low glucose enrichment and labeled lactate accumulation could thus be detected; these were analyzed using unsupervised clustering strategies based on k-means clustering of area-under-the-curve information, and principal components analysis with Gaussian mixture modeling. Spatial alignment of these imaging-derived clusters for ²H-glucose and ²H-lactate showed good agreement with each other as well as with histological sections, validating the biological relevance of the identified subregions. Immunohistochemical analyses showed that glucose-enriched subregions were positively correlated with the expression of GLUT1 and DLAT, while lactate-enriched areas showed elevated expression of LDHA and MCT4. These results demonstrate that in vivo DMI can distinguish metabolically distinct subregions within viable tumors and between tumor models. DMI-based metabolic maps could thus provide the means to characterize intra- and intertumoral heterogeneities, paving the way for imaging-based metabolic phenotyping in precision oncology.

PMID:
42627885
Bibliographic data and abstract were imported from PubMed on 22 Aug 2026.

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