Multi‐omics integration driving precision medicine in non‐small cell lung cancer: From molecular mechanisms to clinical translation
- 1Graduate School of Chinese PLA Medical School Chinese PLA General Hospital Beijing China
- 2Senior Department of Oncology, the Fifth Medical Centre Chinese PLA General Hospital Beijing China
Abstract
Background The molecular heterogeneity and therapeutic resistance of non‐small cell lung cancer (NSCLC) remain significant clinical challenges. In recent years, the integration of multi‐omics technologies has driven a paradigm shift in NSCLC research, evolving from static bulk sequencing to dynamic evolutionary tracking and high‐resolution single‐cell analysis. Main body Rather than a conventional catalogue of sequencing technologies, this review systematically addresses precision oncology through a clinical‐problem‐oriented framework. We emphasise the role of single‐cell and spatial multi‐omics in decoding the tumour immune microenvironment and uncovering rare, aggressive cellular subpopulations responsible for therapeutic resistance. Furthermore, we highlight the integration of metabolomics—particularly lipid metabolic reprogramming—in understanding adaptive resistance to tyrosine kinase inhibitors (TKI). We also comprehensively discuss current precision medicine practices, including spatial transcriptomics‐guided antibody‐drug conjugate (ADC) development, the clinical rationale for dual‐target bispecific antibodies, and liquid biopsy for real‐time longitudinal tracking. Crucially, we critically evaluate the current translational chasm and reproducibility crisis, demonstrating how artificial intelligence and advanced bioinformatics pipelines (e.g., MOFA+ and LASSO) can overcome data heterogeneity to extract robust prognostic signatures. Conclusions By bridging the gap between high‐dimensional data and prospective clinical validation, integrated multi‐omics holds unprecedented promise for advancing personalised NSCLC management and ultimately improving patient outcomes.
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BibTeX
@article{gao2026multiomics,
title = {{Multi‐omics integration driving precision medicine in non‐small cell lung cancer: From molecular mechanisms to clinical translation}},
author = {Yuang Gao and Liyan Lin and Hongrui Zhou and Muchen Li and Yunye Mao and Xiangwei Ge and Yangyang Jia and Yupu Li and Shu Sheng and JinZhao Zhai and Boyu Qin and Jinliang Wang},
journal = {Clinical and Translational Discovery},
year = {2026},
month = oct,
doi = {10.1002/ctd2.70187},
url = {https://doi.org/10.1002/ctd2.70187},
note = {CC BY},
}
RIS
TY - JOUR
TI - Multi‐omics integration driving precision medicine in non‐small cell lung cancer: From molecular mechanisms to clinical translation
AU - Yuang Gao
AU - Liyan Lin
AU - Hongrui Zhou
AU - Muchen Li
AU - Yunye Mao
AU - Xiangwei Ge
AU - Yangyang Jia
AU - Yupu Li
AU - Shu Sheng
AU - JinZhao Zhai
AU - Boyu Qin
AU - Jinliang Wang
PY - 2026
DA - 2026/10/26
JO - Clinical and Translational Discovery
DO - 10.1002/ctd2.70187
UR - https://doi.org/10.1002/ctd2.70187
AB - Background The molecular heterogeneity and therapeutic resistance of non‐small cell lung cancer (NSCLC) remain significant clinical challenges. In recent years, the integration of multi‐omics technologies has driven a paradigm shift in NSCLC research, evolving from static bulk sequencing to dynamic evolutionary tracking and high‐resolution single‐cell analysis. Main body Rather than a conventional catalogue of sequencing technologies, this review systematically addresses precision oncology through a clinical‐problem‐oriented framework. We emphasise the role of single‐cell and spatial multi‐omics in decoding the tumour immune microenvironment and uncovering rare, aggressive cellular subpopulations responsible for therapeutic resistance. Furthermore, we highlight the integration of metabolomics—particularly lipid metabolic reprogramming—in understanding adaptive resistance to tyrosine kinase inhibitors (TKI). We also comprehensively discuss current precision medicine practices, including spatial transcriptomics‐guided antibody‐drug conjugate (ADC) development, the clinical rationale for dual‐target bispecific antibodies, and liquid biopsy for real‐time longitudinal tracking. Crucially, we critically evaluate the current translational chasm and reproducibility crisis, demonstrating how artificial intelligence and advanced bioinformatics pipelines (e.g., MOFA+ and LASSO) can overcome data heterogeneity to extract robust prognostic signatures. Conclusions By bridging the gap between high‐dimensional data and prospective clinical validation, integrated multi‐omics holds unprecedented promise for advancing personalised NSCLC management and ultimately improving patient outcomes.
SN - 2768-0622
ER -