- [Resource Hub](/) - [Publication](/?resource-type=publication#library) - Ex Vivo Immuno-Oncology Platform Reveals Spatial T Cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer # Ex Vivo Immuno-Oncology Platform Reveals Spatial T Cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer Sakrepatna Nagaraj A, Salko M, Sirsikar A, Kang Z, Erkan EP, Pietilä EA, et al. Cancer Immunology Research . 2026;14(4):625-639. DOI [10.1158/2326-6066.cir-25-0743](https://doi.org/10.1158/2326-6066.cir-25-0743). PMID 41563843. PMCID PMC7618831. How to cite ### AMA Sakrepatna Nagaraj A, Salko M, Sirsikar A, Kang Z, Erkan EP, Pietilä EA, et al. Ex Vivo Immuno-Oncology Platform Reveals Spatial T Cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer. Cancer Immunol Res . 2026;14(4):625-639. doi:10.1158/2326-6066.cir-25-0743 ### APA Sakrepatna Nagaraj, A., Salko, M., Sirsikar, A., Kang, Z., Erkan, E. P., Pietilä, E. A., et al. (2026). Ex Vivo Immuno-Oncology Platform Reveals Spatial T Cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer. Cancer Immunology Research , 14(4), 625-639. https://doi.org/10.1158/2326-6066.cir-25-0743 ### BibTeX @article{sakrepatnanagaraj2026exvivo, title = {Ex Vivo Immuno-Oncology Platform Reveals Spatial T Cell Infiltration Patterns Linked to ATR Inhibition Responses in High-Grade Serous Ovarian Cancer}, author = {Sakrepatna Nagaraj, A. and Salko, M. and Sirsikar, A. and Kang, Z. and Erkan, E. P. and Pietil{\"a}, E. A. and others}, journal = {Cancer Immunology Research}, volume = {14}, number = {4}, pages = {625--639}, year = {2026}, doi = {10.1158/2326-6066.cir-25-0743}, pmid = {41563843} } High-grade serous ovarian cancer is usually found late and rarely responds to immunotherapy, and the lab models used to study it tend to lose the patient's own immune cells or lean on rodent-derived matrices that do not reflect human tissue. This team grew immunocompetent cultures directly from fresh patient tumors on a gel made from human omentum, then used them to test ATR inhibitors alongside immune checkpoint blockade. Pairing that ex vivo drug testing with spatial imaging of the matching tumors, they found that tumors responding to ATR inhibition carried more tumor-infiltrating T cells and higher replication stress in their cancer cells. Those spatial patterns held up as candidate biomarkers, pointing toward which patients might benefit from pairing ATR inhibitors with immunotherapy. [Read publication at Cancer Immunology Research](https://pmc.ncbi.nlm.nih.gov/articles/PMC7618831/) ## Key findings - The platform processed 47 tumors from 44 high-grade serous ovarian cancer patients and grew immunocompetent patient-derived cultures (iPDCs) from 37 of them. The cultures were grown on a gel derived from human omentum rather than a rodent matrix, keeping the tumors' own immune cells intact. - Response to the checkpoint inhibitor pembrolizumab tracked with homologous-recombination status. Among the cultures tested, 3 of 4 homologous-recombination-deficient cultures responded while none of the homologous-recombination-proficient cultures did, matching what is seen clinically. - A 15-marker tissue cyclic immunofluorescence panel on FFPE tumors from 12 patients linked spatial T-cell patterns to drug response. Tumors that responded to ATR inhibition carried significantly higher intratumoral infiltration of PD-1 + CD8 + T cells than nonresponders. - The imaging tied local T-cell activation to tumor replication stress. PD-1 + CD8 + T cells sitting next to replication-stress-high (pRPA32 + ) tumor cells expressed significantly more granzyme B than those next to pRPA32 − cells. ## CyteFinder II in the methods “FFPE tumor tissue sections from 12 PDS patient samples were sequentially stained with validated antibodies (Supplementary Table S7) and scanned using CyteFinder II (RareCyte) as outlined in the t-CycIF protocol ( 36 ). Images from each cycle of staining were stitched and registered to create one high-plex image using the ASHLAR algorithm (RRID:SCR_016266; ref. 37 ).” — Sakrepatna Nagaraj et al., Cancer Immunology Research (2026), Methods, “t-CycIF staining and image analysis” ## Why it matters for CyteFinder II users If you are weighing the CyteFinder II for a tissue study, look at what its imaging was asked to carry here. The finding the authors build toward — that PD-1 + CD8 + T cells sit significantly closer to the tumor–stroma interface in patients whose tumors respond to ATR inhibition — is a claim about position. You cannot make it from dissociated cells, and you cannot make it from a single field of view. It needs single-cell coordinates across whole FFPE sections, in enough markers to tell tumor cells, CD8 T cells and myeloid cells apart at once. Here the CyteFinder II scanned FFPE tumor sections through a 15-marker tissue cyclic immunofluorescence (t-CycIF) panel, one staining cycle at a time, and the ASHLAR algorithm stitched and registered the cycles into one high-plex image spanning the whole tissue section. That image is what the spatial neighborhood analysis reads. And the steps after it stayed open and yours to choose — ASHLAR for registration, StarDist for segmentation, CyLinter for quality control — rather than a closed pipeline. 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