Background: The prognosis of older patients with ovarian cancer is poor. We evaluated the effect of chronological age and different treatment characteristics on the prognosis of older patients with ovarian cancer; Methods: The study retrospectively analyzed patients aged over 60 years who underwent cytoreduction followed by platinum-based adjuvant chemotherapy between January 2011 and December 2019 in two national centers in China. Propensity score matching (PSM, 1:1) was performed to stratify the comorbidity- and treatment-related factors. The Kaplan–Meier method was employed to estimate progression-free survival (PFS) in the original cohort and the cohort after PSM; Results: A total of 324 patients were evaluated. The Age ≥ 70 group often received more neoadjuvant chemotherapy (62.3% vs. 31.2%, p < 0.001), more discontinuation of adjuvant chemotherapy (31.2% vs. 10.8%, p < 0.001), and had more severe chemotherapy-related toxicity (45.6% vs. 34.2%, p = 0.040) than the Age < 70 group. After matching, the PFS of the Age < 70 group was not significantly different from the Age ≥ 70 group (median PFS = 12.4 and 11.9 months, respectively, p = 0.850). Furthermore, the advanced FIGO stage, non-R0 cytoreduction, and discontinuation of adjuvant chemotherapy were all found to be poor prognostic factors. Serum albumin level <40 g/L (HR = 2.441, p = 0.018) and age ≥ 70 years (HR = 2.639, p = 0.008) led to more severe chemotherapy-related toxicity. Additionally, poor renal function (HR = 5.128, p = 0.002) was in association with discontinuation of adjuvant chemotherapy; Conclusions: The chronological age of older patients cannot be seen as a poor prognostic factor. Older patients may benefit most from R0 cytoreduction followed by the completion of chemotherapy. Postoperative poor renal function and serum albumin level <40 g/L may help predict the discontinuation of adjuvant chemotherapy.

Background/Objectives: Ovarian cancer has the highest mortality among gynecological malignancies, with platinum resistance significantly contributing to poor prognosis. We aimed to develop a multimodal model (MMHC-OCPR) to predict platinum response and recurrence risk, enabling earlier personalized treatment and improved outcomes. Methods: This multicenter retrospective study included a combined cohort of 431 patients, comprising 1182 whole slide images (WSIs) curated from two independent datasets. The primary cohort consisted of 376 patients from the National Cancer Center (China), which was further partitioned into training, validation and internal test sets to ensure model development and evaluation. An additional external test cohort was incorporated using publicly available data from TCGA, enhancing the generalizability of our findings. We implemented a weakly supervised multiple instance learning framework to integrate histopathological imaging with clinicopathological variables, further strengthened by the incorporation of the transformer-based pretrained encoder UNI2-h, which enhanced the model’s predictive performance. Results: All patients in the primary cohort had pathology slides collected from primary ovarian tumors and metastatic tumor, along with clinical factors related to prognosis and treatment response. The baseline platinum response classifier using primary WSIs achieved an AUC of 0.896 in the internal test group and 0.876 in the external test group. Integration of metastatic WSIs and clinical data inputs yielded a superior AUC of 0.914 in the internal test set. The recurrence risk model demonstrated a C-index of 0.801, rising to 0.838 after multimodal enhancement. The model stratified patients into low-, intermediate- and high-risk groups with 2-year progression-free survival rates of 77.3%, 48.0% and 2.0%, respectively. Conclusions: Our model enables the early detection of platinum resistance, guiding timely treatment intensification. The recurrence risk stratification supports personalized management by identifying patients with favorable outcomes following surgery and chemotherapy, potentially sparing them from maintenance therapy to reduce associated toxicity, cost, and enhance quality of life.

Ovarian cancer is the deadliest gynecological malignancy. The main obstacle in treating high‐grade serous ovarian cancer (HGSOC) is platinum resistance. The mechanistic interface between tumor metabolic reprogramming and platinum resistance remains undefined. We integrated proteomic and metabolomic profiling of 97 primary HGSOC tumors to map the molecular landscape. Unsupervised clustering identified three subtypes. Subtype 3 exhibited a higher platinum resistance rate (64.5%), as well as worse overall ( p = 0.001) and recurrence‐free ( p = 0.0001) survival. At the molecular level, both Subtypes 2 and 3 tumors displayed phenotypes of activated lipid metabolism. However, Subtype 3 tumors were unique, exhibiting potential divergence between lipid metabolism and bioenergetics. The arachidonic acid metabolism pathway was upregulated ( p = 2.0 × 10 ⁻⁶ ), and the key enzyme cyclooxygenase‐2 (COX‐2) was overexpressed ( p < 0.001). Subtype 3 tumors exhibited an inflammation‐associated state with the highest infiltration of M2‐like macrophages ( p = 0.007). Single‐cell transcriptomics revealed increased expression of PTGS2 (encoding COX‐2, p = 0.001) and CD163 ( p < 2.2 × 10 ⁻¹⁶ ) in macrophages from platinum‐resistant HGSOC. Multiplex immunofluorescence confirmed that platinum‐resistant tumors had a higher proportion of COX‐2 ⁺ cells in M2‐like macrophages ( p = 0.010). These findings define a high‐risk HGSOC subtype characterized by inflammation‐related lipid metabolism. This suggests targeting the arachidonic acid metabolism pathway as a way to overcome platinum resistance.