Nature Communications (Aug 2024)
METI: deep profiling of tumor ecosystems by integrating cell morphology and spatial transcriptomics
- Jiahui Jiang,
- Yunhe Liu,
- Jiangjiang Qin,
- Jianfeng Chen,
- Jingjing Wu,
- Melissa P. Pizzi,
- Rossana Lazcano,
- Kohei Yamashita,
- Zhiyuan Xu,
- Guangsheng Pei,
- Kyung Serk Cho,
- Yanshuo Chu,
- Ansam Sinjab,
- Fuduan Peng,
- Xinmiao Yan,
- Guangchun Han,
- Ruiping Wang,
- Enyu Dai,
- Yibo Dai,
- Bogdan A. Czerniak,
- Andrew Futreal,
- Anirban Maitra,
- Alexander Lazar,
- Humam Kadara,
- Amir A. Jazaeri,
- Xiangdong Cheng,
- Jaffer Ajani,
- Jianjun Gao,
- Jian Hu,
- Linghua Wang
Affiliations
- Jiahui Jiang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Yunhe Liu
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Jiangjiang Qin
- Department of Gastric Surgery, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital
- Jianfeng Chen
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center
- Jingjing Wu
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center
- Melissa P. Pizzi
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center
- Rossana Lazcano
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center
- Kohei Yamashita
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center
- Zhiyuan Xu
- Department of Gastric Surgery, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital
- Guangsheng Pei
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Kyung Serk Cho
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Yanshuo Chu
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Ansam Sinjab
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center
- Fuduan Peng
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Xinmiao Yan
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Guangchun Han
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Ruiping Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Enyu Dai
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Yibo Dai
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Bogdan A. Czerniak
- Department of Pathology, The University of Texas MD Anderson Cancer Center
- Andrew Futreal
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- Anirban Maitra
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center
- Alexander Lazar
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center
- Humam Kadara
- Department of Translational Molecular Pathology, The University of Texas MD Anderson Cancer Center
- Amir A. Jazaeri
- Department of Gynecologic Oncology and Reproductive Medicine, The University of Texas MD Anderson Cancer Center
- Xiangdong Cheng
- Department of Gastric Surgery, Cancer Hospital of the University of Chinese Academy of Sciences, Zhejiang Cancer Hospital
- Jaffer Ajani
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center
- Jianjun Gao
- Department of Genitourinary Medical Oncology, The University of Texas MD Anderson Cancer Center
- Jian Hu
- Department of Human Genetics, Emory School of Medicine
- Linghua Wang
- Department of Genomic Medicine, The University of Texas MD Anderson Cancer Center
- DOI
- https://doi.org/10.1038/s41467-024-51708-9
- Journal volume & issue
-
Vol. 15,
no. 1
pp. 1 – 13
Abstract
Abstract Recent advances in spatial transcriptomics (ST) techniques provide valuable insights into cellular interactions within the tumor microenvironment (TME). However, most analytical tools lack consideration of histological features and rely on matched single-cell RNA sequencing data, limiting their effectiveness in TME studies. To address this, we introduce the Morphology-Enhanced Spatial Transcriptome Analysis Integrator (METI), an end-to-end framework that maps cancer cells and TME components, stratifies cell types and states, and analyzes cell co-localization. By integrating spatial transcriptomics, cell morphology, and curated gene signatures, METI enhances our understanding of the molecular landscape and cellular interactions within the tissue. We evaluate the performance of METI on ST data generated from various tumor tissues, including gastric, lung, and bladder cancers, as well as premalignant tissues. We also conduct a quantitative comparison of METI with existing clustering and cell deconvolution tools, demonstrating METI’s robust and consistent performance.
