Frontiers in oncology · 2026
Genetic associations link lung cancer liability to brain imaging phenotypes and nominate an FN1-associated tumor-oligodendrocyte program in small-cell lung cancer.
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Xu Kai, Xu Peihang, Su Kunsong, Liu Zhenkun, Hao Yang, Feng Hongxiang, Che Guowei, Zhou Qinghua, Zhai Xiaoqian
Аннотация
BACKGROUND: Brain metastasis is a major cause of mortality in lung cancer, particularly in small-cell lung cancer (SCLC). Whether genetic susceptibility to lung cancer is associated with brain structural and functional traits relevant to metastatic vulnerability remains unclear. We investigated subtype-specific genetic associations with brain imaging phenotypes and explored the biological context of the SCLC-associated white-matter signal.
METHODS: Bidirectional two-sample Mendelian randomization (MR) was performed using European genome-wide association study summary statistics for three lung cancer subtypes, 3,935 structural MRI phenotypes, and 191 resting-state functional MRI traits. MR findings were evaluated using genetic-correlation and sensitivity analyses. Public single-cell and spatial transcriptomic datasets from brain metastases, computational ligand-receptor inference, and virtual perturbation modeling were used to explore the SCLC-related findings.
RESULTS: SCLC genetic liability showed the clearest white-matter-related pattern, involving the superior cerebellar peduncle and cerebellar-related functional connectivity, whereas lung squamous cell carcinoma was mainly associated with frontal and parietal traits. Single-cell analysis identified mature-like, intermediate, and reactive-like oligodendrocyte states. Reactive-like cells exhibited reduced myelination-associated genes and enhanced stress-response programs. Computational analyses prioritized an FN1-associated tumor-oligodendrocyte interaction program, with neuronal-like malignant SCLC cells as the major predicted sender population. Cross-dataset, spatial, and virtual perturbation analyses provided additional exploratory support for tumor-derived FN1 as a candidate niche-organizing signal associated with reactive oligodendrocyte remodeling.
CONCLUSIONS: Lung cancer subtypes show distinct genetic associations with brain phenotypes. The SCLC findings and exploratory multi-omics analyses support an FN1-centered tumor-oligodendrocyte model that warrants experimental validation.
METHODS: Bidirectional two-sample Mendelian randomization (MR) was performed using European genome-wide association study summary statistics for three lung cancer subtypes, 3,935 structural MRI phenotypes, and 191 resting-state functional MRI traits. MR findings were evaluated using genetic-correlation and sensitivity analyses. Public single-cell and spatial transcriptomic datasets from brain metastases, computational ligand-receptor inference, and virtual perturbation modeling were used to explore the SCLC-related findings.
RESULTS: SCLC genetic liability showed the clearest white-matter-related pattern, involving the superior cerebellar peduncle and cerebellar-related functional connectivity, whereas lung squamous cell carcinoma was mainly associated with frontal and parietal traits. Single-cell analysis identified mature-like, intermediate, and reactive-like oligodendrocyte states. Reactive-like cells exhibited reduced myelination-associated genes and enhanced stress-response programs. Computational analyses prioritized an FN1-associated tumor-oligodendrocyte interaction program, with neuronal-like malignant SCLC cells as the major predicted sender population. Cross-dataset, spatial, and virtual perturbation analyses provided additional exploratory support for tumor-derived FN1 as a candidate niche-organizing signal associated with reactive oligodendrocyte remodeling.
CONCLUSIONS: Lung cancer subtypes show distinct genetic associations with brain phenotypes. The SCLC findings and exploratory multi-omics analyses support an FN1-centered tumor-oligodendrocyte model that warrants experimental validation.