Ovarian cancer-derived IL-4 promotes immunotherapy resistance
Cell. 2024;187(26):7492-7510.e22. DOI 10.1016/j.cell.2024.10.006. PMID 39481380. PMCID PMC11682930.
How to cite
AMA
Mollaoglu G, Tepper A, Falcomatà C, Potak HT, Pia L, Amabile A, et al. Ovarian cancer-derived IL-4 promotes immunotherapy resistance. Cell. 2024;187(26):7492-7510.e22. doi:10.1016/j.cell.2024.10.006APA
Mollaoglu, G., Tepper, A., Falcomatà, C., Potak, H. T., Pia, L., Amabile, A., et al. (2024). Ovarian cancer-derived IL-4 promotes immunotherapy resistance. Cell, 187(26), 7492-7510.e22. https://doi.org/10.1016/j.cell.2024.10.006BibTeX
@article{mollaoglu2024ovarian,
title = {Ovarian cancer-derived IL-4 promotes immunotherapy resistance},
author = {Mollaoglu, G. and Tepper, A. and Falcomat{\`a}, C. and Potak, H. T. and Pia, L. and Amabile, A. and others},
journal = {Cell},
volume = {187},
number = {26},
pages = {7492--7510.e22},
year = {2024},
doi = {10.1016/j.cell.2024.10.006},
pmid = {39481380}
}Ovarian cancer barely responds to immunotherapy. Checkpoint blockade against PD-1 helps fewer than 10% of patients, in part because the ovarian tumor microenvironment is immune-suppressed and dominated by macrophages. Why some tumors resist while others respond has been hard to explain.
Using a spatial genomics screen in a mouse model, the team tested cancer-cell signals that talk to macrophages. Interleukin-4 (IL-4) made by the cancer cells stood out: it steers macrophages into an immunosuppressive state and drives resistance to anti-PD-1. Only a small fraction of cancer cells needs to make IL-4 to suppress the surrounding neighborhood.
Blocking IL-4 signaling on its own did little, but combined with anti-PD-1 it turned non-responsive tumors into responsive ones, pointing to IL-4 receptor blockade as a way to make ovarian cancer respond to immunotherapy.
Key findings
- Cancer-cell-derived IL-4 drives resistance to anti-PD-1 in ovarian cancer. Checkpoint blockade produces objective responses in under 10% of ovarian cancer patients; here, deleting IL-4 from the cancer cells restored sensitivity, with anti-PD-1 delaying ascites and extending survival only when IL-4 was absent.
- Losing cancer-derived CCL7 produced an immune-excluded tumor microenvironment. Cyclic immunofluorescence of 26 markers across 4.3 million cells showed control tumors averaged 27% myeloid cells and 7.5% lymphocytes, versus 14% and 4.5% in CCL7-knockout tumors.
- Removing IL-4 remodeled the microenvironment toward anti-tumor immunity. IL-4-knockout tumors carried fewer immunosuppressive macrophages and more exhausted CD8 T cells, and formed large lymphoid aggregates — biggest in anti-PD-1-treated mice — resolved by density clustering of at least 750 cells on whole-slide images.
CyteFinder II HT in the methods
“Slides were automatically imaged on the RareCyte Cytefinder II HT using the following channels: UV, cy3, cy5, and cy7. Imaging was performed with the following parameters: Binning: 1 × 1; Objective: 20x; Numerical Aperture: 0.75; Resolution: 0.325 um/pixel. Image exposures were optimized for each channel to avoid signal saturation but kept constant across samples.”
— Mollaoglu et al., Cell (2024), Methods, “Cyclic immunofluorescence”
Disclosure: RareCyte is named in the competing-interests statement of the publication cited above.
Why it matters for CyteFinder II HT users
If you are weighing the CyteFinder II HT for a tissue study, look at what its imaging arm carried here. The paper's case rests on where immune cells sit relative to cancer cells, a spatial question you cannot answer from a dissociated sample. The authors used cyclic immunofluorescence to read out 26 lineage and cell-state markers, among them CD4, CD8, F4/80, CD31 and PD-1, across 4.3 million cells of ovarian tumor tissue, scanning every slide automatically on the CyteFinder II HT in four channels at 20x and 0.325 µm per pixel. That let them measure immune composition cell by cell, quantify how far T cells sat from cancer clones, and find the large lymphoid aggregates that formed only when IL-4 was lost. Two things carry over to your own work. Automated whole-slide capture holds exposures constant across samples, so counts stay comparable. And running many cyclic rounds on one section lets you place lineage and immune markers on the same tissue rather than reading them off separate stains.
