{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T05:55:29Z","timestamp":1790920529694,"version":"4.1.0"},"reference-count":30,"publisher":"Frontiers Media SA","license":[{"start":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T00:00:00Z","timestamp":1790899200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["frontiersin.org"],"crossmark-restriction":true},"short-container-title":["Front. Public Health"],"abstract":"<jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Ovarian cancer (OC), particularly high-grade serous ovarian carcinoma (HGSOC), remains a lethal gynecological malignancy characterized by frequent recurrence and treatment resistance. Ferroptosis is governed by nutrient-related metabolic processes involving iron handling, cystine\u2013glutathione antioxidant defense, lipid peroxidation, amino-acid metabolism, and cellular energy metabolism. However, the organization of these programs across bulk tumors and individual tumor-microenvironment compartments remains incompletely understood.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Bulk RNA-sequencing data from The Cancer Genome Atlas ovarian cancer cohort (TCGA-OV) were analyzed in 421 primary tumors, with 419 patients evaluable for overall survival, using a curated 40-gene ferroptosis\u2013nutrient-metabolic panel. Gene correlations, module scores, survival associations, a 10-fold cross-validated LASSO-Cox ferroptosis risk score (FRS), immune-marker enrichment, and immune-checkpoint correlations were evaluated. Single-cell RNA-sequencing data from GSE146026 were analyzed in a 10x cohort of 9,609 cells from 6 patients, with a Smart-seq2 cohort of 1,297 cells used for consistency analyses. Selected genes were further validated by RT-qPCR in hTERT FNE1, NIH:OVCAR-3, and Caov-3 cells.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>\n                      FTL, RPL8, FTH1, LDHA, and GPX4 showed the highest mean expression in TCGA-OV. Lower SLC7A11 expression was associated with shorter survival (HR\u202f=\u202f0.83 per SD, 95% CI 0.73\u20130.94,\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.004), whereas higher LPCAT3 expression was associated with shorter survival (HR\u202f=\u202f1.19,\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.010), although neither survived false-discovery-rate correction. The two-gene FRS separated survival groups (log-rank\n                      <jats:italic>p<\/jats:italic>\n                      =\u202f0.019) but showed modest discrimination (C-index\u202f=\u202f0.56; held-out concordance\u202f=\u202f0.55). The ferroptosis\u2013nutrition score correlated most strongly with macrophage marker enrichment (rho\u202f=\u202f0.46). At single-cell resolution, the overall score was highest in fibroblasts, epithelial tumor cells, and macrophages, whereas the iron-storage module was highest in macrophages. Cross-platform concordance was observed between 10x and Smart-seq2 (rho\u202f=\u202f0.63) and between epithelial pseudobulk and TCGA-OV bulk expression (rho\u202f=\u202f0.65). RT-qPCR confirmed higher expression of FTL, FTH1, GPX4, SLC7A11, and LPCAT3 in both ovarian-cancer cell lines than in hTERT FNE1.\n                    <\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>Ferroptosis-related nutrient-metabolic genes display coordinated but cell-type-specific organization in ovarian cancer and are linked to immune-marker enrichment. RT-qPCR provides orthogonal expression-level validation of selected candidates. The FRS remains exploratory, and the transcriptomic scores should not be interpreted as direct measures of ferroptotic activity or clinical nutritional status.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.3389\/fpubh.2026.1967476","type":"journal-article","created":{"date-parts":[[2026,10,2]],"date-time":"2026-10-02T05:36:09Z","timestamp":1790919369000},"update-policy":"https:\/\/doi.org\/10.3389\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Ferroptosis and nutrient-metabolic pathway genes in ovarian cancer: integrated bulk and single-cell analysis of Iron-metabolic programs, immune-marker enrichment, and prognosis"],"prefix":"10.3389","volume":"14","author":[{"given":"Yan","family":"Xing","sequence":"first","affiliation":[{"name":"Department of Reproductive Medicine, Qingdao Municipal Hospital","place":["Qingdao, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lulu","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Reproductive Medicine, Qingdao Municipal Hospital","place":["Qingdao, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Wenjuan","family":"Ling","sequence":"additional","affiliation":[{"name":"Department of Reproductive Medicine, Qingdao Municipal Hospital","place":["Qingdao, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Lingling","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Reproductive Medicine, Qingdao Municipal Hospital","place":["Qingdao, China"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1965","published-online":{"date-parts":[[2026,10,2]]},"reference":[{"key":"ref1","doi-asserted-by":"publisher","first-page":"209","DOI":"10.3322\/caac.21660","article-title":"Global Cancer statistics 2020: GLOBOCAN estimates of incidence and 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