{"doi":"10.1101/2025.07.15.664474","title":"S-Nitrosylated COX-2 is a TME-regulated breast cancer biomarker of mesenchymal phenotypes","abstract":"Abstract COX-2 is an inducible enzyme key to the production of inflammatory prostaglandins. COX-2 also has tumor intrinsic oncogenic activity in mouse models of breast cancer. Previously, we reported increased expression of Cys-526-nitrosylated COX-2 (SNO-COX-2), but not non-nitrosylated COX-2, with progression of early-stage human breast cancer to invasive ductal carcinoma. Here, we used a 3D culture model of early-stage human breast cancer (MCF10DCIS cells) to investigate the relationship between SNO-COX-2 expression and mesenchymal/invasive tumor cell morphology. We find that SNO-COX-2, but not non-nitrosylated COX-2, closely associated with mesenchymal phenotypes induced by fibrillar type I collagen. Interestingly, invasive phenotypes did not associate with induction of the classic epithelial-to-mesenchymal transition (EMT) markers SNAIL , CDH2 (N-cadherin), and VIM (vimentin). By contrast TGFβ-1 strongly induced EMT-related transcripts, but not SNO-COX-2 protein expression or mesenchymal phenotypes. These observations suggest that in MCF10DCIS cells, SNO-COX-2 associates with mesenchymal phenotypes more strongly than non-nitrosylated COX-2 protein, or expression of classic EMT transcripts. In a mouse model with breast tumor heterogeneity, mesenchymal tumor regions also have increased SNO-COX-2 expression. Testing 300 distinct tumor microenvironment conditions, we find SNO-COX-2 protein expression is driven by inflammation, wound resolution, and cancer-associated factors, especially TNC, SPP1, decorin, fibrillar type I and III collagens, INF-γ, and IL-4/13, with evidence for specific extracellular matrix-ligand interactions driving both high and low SNO-COX-2 expression. In sum, in MCF10DCIS cells, expression of SNO-COX-2 is highly microenvironment-dependent and strongly associated with invasive/mesenchymal growth, indicating potential for SNO-COX-2 as a biomarker to assess risk of early-stage breast cancer progression.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":571575,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9614,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":479592,"name":"AeSoon Bensen","orcid":"0000-0003-4421-8370","position":1,"is_corresponding":false},{"id":560850,"name":"Mark Dane","orcid":"0000-0003-3742-9866","position":2,"is_corresponding":false},{"id":1477280,"name":"Jane Arterberry","orcid":"0000-0003-3243-0649","position":3,"is_corresponding":false},{"id":511525,"name":"Rebecca Smith","orcid":"0000-0002-3087-5639","position":4,"is_corresponding":false},{"id":1892,"name":"James E. Korkola","orcid":null,"position":5,"is_corresponding":false},{"id":378493,"name":"Pepper Schedin","orcid":"0000-0003-4244-987X","position":6,"is_corresponding":false},{"id":1129187,"name":"Reuben Hoffmann","orcid":"0000-0001-9554-2977","position":0,"is_corresponding":true}],"reference_count":54,"raw_metadata":null,"created_at":"2026-07-19T02:57:15.755535Z","pmid":"40791519","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}