Background: Defects in DNA damage repair (DDR) system may lead to genomic instability and manifest as increased immunogenicity. DDR deficiency is prevalent in ovarian cancer (OvCa); however, the association of DDR mutation with immune profiles in OvCa remains largely unknown. This knowledge will provide an essential basis to the rational design of biomarker‐guided immune combination therapy of OvCa in the future.Methods: Whole‐exome sequencing data of 587 OvCa from The Cancer Genome Atlas (TCGA) were used to determine the expression profiles of 47 immune‐related genes and the abundance of tumor‐infiltrating immune cells. A Chinese OvCa cohort (n = 220) tested by next‐generation sequencing (NGS) was used to validate the association between DDR status and tumor mutation burden (TMB).Results: A total of 19.3% in TCGA cohort and 25.9% in Chinese cohort harbored at least one DDR somatic mutation. DDR deficiency exhibited a distinct immune profile with significant higher expression levels of PTPRCAP, CCL5, IFI16, LAG3, IL15RA, and GBP1 in OvCa in the TCGA cohort. Different DDR pathway deficiency displayed various immune profiles. Increased levels of Th1 cells, TMB, and neoantigen were also observed in DDR‐deficient tumors.Conclusions: DDR deficiency was associated with specific immune signatures in OvCa. Our findings emphasize the urgent need for biomarker‐guided rational immune combination therapy to maximize the OvCa patients who could benefit from immunotherapy.

Guan J, et al. J Gynecol Oncol. 2021 May;32(4):e60. https://doi.org/10.3802/jgo.2021.32.e60

Background: Optimal management for endometrial cancer in patients with clinically negative lymph nodes is still under debate. Several prediction models for lymphatic dissemination of early-stage endometrial cancer have been developed. However, external validation is rare, and decision curve analysis has hardly been applied for these models. Objective: To develop and validate a nomogram to predict lymph node metastasis of presumed stage I and II endometrial cancer. Study Design: The prediction nomogram was developed by using multivariable logistic regression with data for 700 EC patients who underwent initial surgery from 2006 to 2017 at Peking University People's Hospital (training dataset), Beijing. External validation was performed in 727 eligible patients from Fudan University Shanghai Cancer Center (validation dataset), Shanghai. Results: For the 700 women in the training dataset, the lymph node metastasis rate was 8.0% (56/700). Lymphovascular space invasion, histological grade, cervical stromal invasion, and myometrial invasion were independent prognostic factors in the training dataset. We generated a nomogram based on these pathological factors. To determine the clinical usefulness of our nomogram, we compared it with the Mayo criteria. For our nomogram, the area under the receiver operating characteristic curve (AUC) was 0.85 as compared with 0.63 for the Mayo criteria. In the validation dataset, the AUC was 0.78 as compared with 0.57 for the Mayo criteria. The nomogram was well-calibrated in both the training and validation datasets. At a 10% probability threshold, our nomogram decreased almost 29 unnecessary lymphadenectomies per 100 patients than the Mayo criteria without missing more metastatic disease. Conclusion: We developed a nomogram to predict lymph node metastasis in patients with early-stage endometrial cancer in China. This prediction model may help clinicians in decision-making for patients with early-stage endometrial cancer, especially for the patient with incomplete surgery, reducing overtreatment, and medical costs.

Epithelial ovarian carcinoma (EOC) is one of the most common gynecologic malignancies with a high mortality rate. Serum biomarkers and imaging approaches are insufficient in identifying EOC patients at an early stage. This study is to set up a combination of proteins from serum small extracellular vesicles (sEVs) for the diagnosis of early-stage EOC and to determine its performance. A biomarker for early-stage ovarian cancer (BESOC) cohort was used as a Chinese multi-center population-based biomarker study and registered as a Chinese Clinical Trial ChiCTR2000040136. The sEV protein levels of CA125, HE4, and C5a were measured in 299 subjects. Logistic regression was exploited to calculate the odds ratio and to create the sEV protein model for the predicted probability and subsequently receiver-operating characteristic (ROC) analysis. The combined sEV marker panel of CA125, HE4, and C5a as a sEV model obtained an area under curve (AUC) of 0.912, which was greater than the serum model (0.809), by ROC analysis to identify EOC patients from the whole cohort. With the cutoff of 0.370, the sensitivity and specificity of the sEV model were 0.80 and 0.89, which were much better performance than the serum markers (sensitivity: 0.55~0.66; specificity: 0.59~0.68) and the risk of ovarian malignancy algorithm (ROMA) index approved by the U.S. Food and Drug Administration (sensitivity: 0.65; specificity: 0.61), to identify EOC patients from patients with benign ovarian diseases or other controls. The sEV levels of CA125 significantly differed among early-stage and late-stage EOC (p < 0.001). Moreover, the AUC of ROC to identify early-stage EOC patients was 0.888. Further investigation revealed that the sEV levels of these 3 proteins significantly decreased after cytoreductive surgery (CA125, p = 0.008; HE4, p = 0.025; C5a, p = 0.044). In summary, our study showed that CA125, HE4, and C5a levels in serum sEVs can identify EOC patients at the early stage, elucidating the possibility of using a sEV model for the diagnosis of early-stage EOC.

Objective This study aimed to prospectively evaluate the efficacy and safety of anlotinib in patients with platinum resistant/refractory ovarian cancer. Methods In this prospective, single arm, phase II study, patients with platinum resistant/refractory ovarian cancer received anlotinib (12 mg once daily; days 1–14; 21 days per cycle) until disease progression, unacceptable toxicity, or study withdrawal. The study was conducted between May 2019 and May 2021. The primary endpoint was objective response rate. Secondary endpoints were disease control rate, progression free survival, overall survival, and safety. An exploratory biomarker analysis was performed to evaluate the correlation of baseline TP53 mutation status with outcomes. Results 33 of 34 enrolled patients received at least one dose of anlotinib. The objective response rate was 31.2% (95% confidence interval (CI) 16.1% to 50.0%), with 2 (6.3%) complete and 8 (25.0%) partial responses. In total, 14 (43.8%) patients achieved stable disease, resulting in a disease control rate of 75.0% (95% CI 56.6% to 88.5%). With a median follow-up of 4.6 months (range 0.5–17.2) at data cut-off (September 16, 2022), median progression free survival was 5.3 months (95% CI 4.04 to 6.56) and median overall survival was not reached. In a subgroup analysis, patients with a TP53 mutation showed a trend towards worse progression free survival than those with the wild-type TP53 (4.4 months vs 8.4 months; hazard ratio 2.48 (95% CI 0.91 to 6.76), p=0.067). Common adverse events were hypertension (42.4%), hand–foot syndrome (27.3%), and fatigue (24.2%). Grade 3 events were reported in 3 (9.1%) patients and no grade 4–5 events or deaths were observed. Conclusion Anlotinib showed antitumor activity with an acceptable safety profile in patients with platinum resistant/refractory ovarian cancer, and it might be a potential treatment in this population.