Researchers at VIB and VUB have developed a sequencing-driven approach to study how immune cells behave within lung tumors. By combining a patient-relevant mouse model with single-cell RNA sequencing and spatial transcriptomics, the team created a detailed immune map of lung adenocarcinoma, the most common subtype of lung cancer. The work, published in Nature Communications, highlights how sequencing technologies can provide deeper insight into tumor immune environments.
A central feature of the study is a lung adenocarcinoma model in which tumors develop directly in the lung. Unlike subcutaneous models, this system enables analysis of tumor nodules alongside surrounding healthy tissue, reflecting how patient samples are handled in clinical settings. When paired with single-cell sequencing, the model allows researchers to profile immune cell populations in a more representative biological context. Comparisons with human datasets showed that the model reproduces key immune characteristics, including dysfunctional natural killer cells and increased regulatory and exhausted T cells.
“We created a lung cancer model that closely mimics how tumors grow in patients,” says senior author Damya Laoui. “Combined with a new tracking method for cells, this allow us to tell the difference between immune cells inside the tumor tissue and those that are just passing by in the bloodstream. That distinction makes a big difference. It allows us to see much more clearly how immune cells behave and change once they are inside the tumor.”
To enhance the resolution of sequencing data, the researchers developed SEPARATE-Seq (Streptavidin Enabled PARtitioning And Tag Evaluation for RNA-Sequencing). This method builds on single-cell RNA sequencing by labeling immune cells in the bloodstream, making it possible to distinguish circulating cells from those embedded in tumor tissue. As a result, gene expression data can be interpreted with greater spatial and biological accuracy.
“Location matters enormously,” explains Prof. Damya Laoui. “An immune cell inside a blood vessel is not experiencing the same signals as one embedded in tumor tissue. With SEPARATE-Seq, we can finally resolve that difference at single-cell resolution.”
By integrating SEPARATE-Seq with spatial transcriptomics, the team linked sequencing data to precise locations within the tumor. This approach revealed distinct immune patterns, including macrophage populations at tumor edges, interferon-related cellular hubs, hypoxic neutrophil infiltration, plasma cell enrichment, and a shift of natural killer cells toward an immature, dysfunctional state. Many of these sequencing-derived features were also observed in human lung adenocarcinoma samples.
The researchers also provide a multiomics dataset through an interactive online tool, offering a resource for scientists using sequencing technologies to investigate tumor immunology and lung cancer biology.
Publication details:
Bardet, P.M.R., Allonsius, L., Hadadi, E. et al. Multiomics immune profiling of a patient-relevant orthotopic lung cancer model using SEPARATE-Seq. Nat Commun (2026). https://doi.org/10.1038/s41467-026-72247-5
A central feature of the study is a lung adenocarcinoma model in which tumors develop directly in the lung. Unlike subcutaneous models, this system enables analysis of tumor nodules alongside surrounding healthy tissue, reflecting how patient samples are handled in clinical settings. When paired with single-cell sequencing, the model allows researchers to profile immune cell populations in a more representative biological context. Comparisons with human datasets showed that the model reproduces key immune characteristics, including dysfunctional natural killer cells and increased regulatory and exhausted T cells.
“We created a lung cancer model that closely mimics how tumors grow in patients,” says senior author Damya Laoui. “Combined with a new tracking method for cells, this allow us to tell the difference between immune cells inside the tumor tissue and those that are just passing by in the bloodstream. That distinction makes a big difference. It allows us to see much more clearly how immune cells behave and change once they are inside the tumor.”
To enhance the resolution of sequencing data, the researchers developed SEPARATE-Seq (Streptavidin Enabled PARtitioning And Tag Evaluation for RNA-Sequencing). This method builds on single-cell RNA sequencing by labeling immune cells in the bloodstream, making it possible to distinguish circulating cells from those embedded in tumor tissue. As a result, gene expression data can be interpreted with greater spatial and biological accuracy.
“Location matters enormously,” explains Prof. Damya Laoui. “An immune cell inside a blood vessel is not experiencing the same signals as one embedded in tumor tissue. With SEPARATE-Seq, we can finally resolve that difference at single-cell resolution.”
By integrating SEPARATE-Seq with spatial transcriptomics, the team linked sequencing data to precise locations within the tumor. This approach revealed distinct immune patterns, including macrophage populations at tumor edges, interferon-related cellular hubs, hypoxic neutrophil infiltration, plasma cell enrichment, and a shift of natural killer cells toward an immature, dysfunctional state. Many of these sequencing-derived features were also observed in human lung adenocarcinoma samples.
The researchers also provide a multiomics dataset through an interactive online tool, offering a resource for scientists using sequencing technologies to investigate tumor immunology and lung cancer biology.
Publication details:
Bardet, P.M.R., Allonsius, L., Hadadi, E. et al. Multiomics immune profiling of a patient-relevant orthotopic lung cancer model using SEPARATE-Seq. Nat Commun (2026). https://doi.org/10.1038/s41467-026-72247-5