Background: The aim of this study was to explore the clinicopathological characteristics of recurrent adult-type granulosa cell tumor of the ovary (AGCOT) and evaluated the treatment results to define the prognostic parameters for survival after recurrence. Results: A retrospective review of 40 patients with recurrent AGCOT, who were treated in the Cancer Hospital at the Chinese Academy of Medical Sciences from 2000 to 2015 was conducted. The impact of clinical and pathological characteristics, progression-free survival (PFS), and post-recurrence therapeutic approaches on prognosis were analyzed. Among the 40 recurrent patients, there were 10 cases where the relapse was uncontrolled, 24 cases had second relapses, and 6 cases without further relapses at the time of our follow-up. The median PFS was 61 months (range, 7-408 months), and the median time interval between the first and the second relapses (R-PFS) was 25 months (range, 0–94 months). The median time interval between the first relapse and death (R-OS) was 90 months (range, 2–216 months). PFS ≥ 61 months (P = 0.004) and post-recurrence therapeutic approach (P < 0.001) were independent risk factors for repeated recurrences. The age at recurrence (P = 0.031) and post-recurrence therapeutic approach (P = 0.001) were independent risk factors for death after recurrence. Conclusion: Among patients with recurrent AGCOT, those with long PFS had good prognoses. Maximal cytoreductive effort should be made after recurrence. Complete resection and postoperative adjuvant chemotherapy may improve the prognosis of patients with recurrent AGCOT.

Background: Female breast and five gynecological cancers remain substantial burden in China and worldwide. GLOBOCAN 2022 has recently updated the estimates of cancer burden. This study aims to depict the profiles of disease burden and to compare the age-specific rates of female breast and five gynecological cancers in China with those in other countries. Methods: The latest estimates of incidence and mortality of female breast and five gynecological cancers from various regions and countries were extracted from the GLOBOCAN 2022 database. We compared the proportion of total cases or deaths for cancers affecting female breast and five gynecological cancers and other tumor types in China and globally. Correlation analysis was conducted to evaluate the relationship between age-standardized incidence rate (ASIR) or age-standardized mortality rate (ASMR) and the Human Development Index (HDI). Additionally, age-specific rate curves were plotted for ten exemplary countries with different income levels. Results: Female breast and five gynecological cancers in China accounted for 30.2% of all newly diagnosed cancer cases. Breast cancer and cervical cancer are the most commonly diagnosed, with nearly 507,000 new cases, representing 23.48% of the new cases. The incidence rates of breast, uterine corpus, ovarian, and vulvar cancers were positively associated with HDI tiers. Chinese women aged 50– 54 years are experiencing high incidence rates of breast, cervix uteri, corpus uteri, and ovarian cancers. Conclusions: Female breast and five gynecological cancers continue to be a significant health concern for women in China and worldwide. It is crucial to implement comprehensive prevention strategies tailored to address the increasing trend among younger individuals and reduce regional disparities.

Objective To analyze the clinical characteristics, diagnosis, and treatment of ovarian juvenile granulosa cell tumor. Methods The clinical and pathological data of six patients with ovarian juvenile granulosa cell tumor was collected. Results The mean age of disease onset was 20.5 years (range 12 to 33). All six patients had an adnexal mass located laterally in the pelvis, and two developed ascites. All patients had fertility-sparing surgery with complete staging. The mean size of the tumors was 15.3 cm (range 5 to 35). Ovarian sex cord stromal tumors were diagnosed or highly suspected from the frozen sections for all patients. Five patients received three to six courses of postoperative adjuvant chemotherapy, with three receiving a bleomycin/etoposide/cisplatin regimen and two receiving a paclitaxel/carboplatin regimen. The five stage I patients had no recurrence with 52 to 155 months of follow-up. The patient with stage IIIB disease had a recurrence 55 months’ later and underwent reoperation and chemotherapy. This patient remained disease-free 30 months after the reoperation. Conclusions Fertility-sparing surgery is the treatment of choice for ovarian juvenile granulosa cell tumor and the overall prognosis is good.

High-grade serous ovarian cancer (HGSOC) presents significant challenges due to its heterogeneity and late-stage diagnoses. Using single-cell and spatial transcriptomics to elucidate the complex landscape of HGSOC to understand its underlying mechanism. Our analysis reveals significant inter- and intra-tumoral diversity, manifested through distinct cellular subpopulations and varied microenvironmental niches. Notably, our findings highlight a widespread immunosuppressive environment, marked by complex networks of cell-cell interactions, particularly evident in areas of elevated tumor cell density within metastatic samples. We identify the exclusive presence of COL14A1+ neoplastic cells in metastatic specimens, alongside a strong correlation between CD8A+ NKT cells and poor prognosis, and elevated CHODL expression in HGSOC metastasis tissues. Furthermore, knockdown experiments targeting CHODL demonstrate its role in reducing migration and invasion abilities in HGSOC cells. A pivotal discovery of our study is the delineation of specific cellular signatures correlated with adverse outcomes, notably a subset of CHODL+ neoplastic cells characterized by a distinct metabolic phenotype with a predilection for lipid metabolism. The therapeutic targeting of this metabolic pathway with existing inhibitors appears promising in curbing tumor proliferation. These findings enhance our understanding of HGSOC heterogeneity and reveal potential therapeutic targets, promising more effective management strategies for this aggressive cancer subtype.

Pretherapeutic serological parameters play a predictive role in pathologic risk factors (PRF), which correlate with treatment and prognosis in cervical cancer (CC). However, the method of pre-operative prediction to PRF is limited and the clinical availability of machine learning methods remains unknown in CC. Overall, 1260 early-stage CC patients treated with radical hysterectomy (RH) were randomly split into training and test cohorts. Six machine learning classifiers, including Gradient Boosting Machine, Support Vector Machine with Gaussian kernel, Random Forest, Conditional Random Forest, Naive Bayes, and Elastic Net, were used to derive diagnostic information from nine clinical factors and 75 parameters readily available from pretreatment peripheral blood tests. The best results were obtained by RF in deep stromal infiltration prediction with an accuracy of 70.8% and AUC of 0.767. The highest accuracy and AUC for predicting lymphatic metastasis with Cforest were 64.3% and 0.620, respectively. The highest accuracy of prediction for lymphavascular space invasion with EN was 59.7% and the AUC was 0.628. Blood markers, including D-dimer and uric acid, were associated with PRF. Machine learning methods can provide critical diagnostic prediction on PRF in CC before surgical intervention. The use of predictive algorithms may facilitate individualized treatment options through diagnostic stratification.