From imaging to multi-omics: decoding the tumor microenvironment in colorectal cancer
Colorectal cancer (CRC) remains one of the most common and lethal malignancies worldwide, characterized by substantial heterogeneity in response to immunotherapy. Accumulating evidence indicates that the tumor microenvironment (TME) plays a pivotal role in determining both treatment response and clinical outcomes. In recent years, radiomics has emerged as a promising non-invasive approach that extracts quantitative features from routine medical images, enabling whole-tumor characterization of the TME and intratumoral heterogeneity. Concurrently, the advent of pathomics allows high-throughput, quantitative profiling of tumor architecture and immune cell spatial distribution, offering complementary insights into the microscopic heterogeneity of the TME. With advances in genomics and transcriptomics, radiomic and pathomic features can now be integrated with molecular data to unravel CRC heterogeneity and TME properties across multiple scales—from macroscopic phenotypes to underlying molecular mechanisms. This narrative review organizes CRC radiomics evidence around direct TME components, vascular-invasion-related phenotypes, and TME-associated tumor-intrinsic features. It further examines cross-scale integration with genomics, transcriptomics, pathomics, and emerging single-cell, spatial-omics, and multimodal-fusion approaches. Collectively, imaging-driven multi-omics integration provides a scalable cross-scale framework for the non-invasive and quantitative assessment of CRC TME-related features, with potential value for precision risk stratification, although its clinical utility and role in therapeutic decision-making remain to be established through prospective validation.
Authors
- Liaoyuan Wang (ORCID: https://orcid.org/0000-0002-7584-6532)
- Bin Zhang (ORCID: https://orcid.org/0000-0002-6286-6227)
- Wenlong Zhang (ORCID: https://orcid.org/0000-0002-6313-2241)
- Yue Gu
- Hui Shen
- Bo Lai
- Xue Han (ORCID: https://orcid.org/0009-0006-3058-4694)
- Liya Gong
- Shuixing Zhang
- Jinyi Zheng
- Jinping Yuan
- Yuxin Xiong
- Xuewei Wu
- Xin Liu
Institutions
- First Affiliated Hospital of Jinan University (CN)
Publication Details
- Journal
- Journal of Translational Medicine
- Published
- 2026-09-19
- DOI
- https://doi.org/10.1186/s12967-026-08958-6
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00