Tingting Yao

Distribution and maturity of tertiary lymphoid structures predict recurrence-free survival in cervical cancer

Reliable biomarkers are needed to predict outcomes in patients with cervical cancer treated with immune checkpoint inhibitors. This study aimed to develop a novel immune classification system based on tertiary lymphoid structure maturation to stratify prognosis and PD-1 inhibitor response. Surgical specimens from 451 patients with cervical cancer were analyzed to evaluate tertiary lymphoid structure spatial distribution (tumor region vs invasive margin) and maturity. Using machine learning, 4 parameters-tumor region score, invasive margin score, and tertiary lymphoid structure maturity in both regions-were integrated to establish an Immune Score-based classification (immune class I, immune class II, and immune class III). The model was validated in an external cohort of 58 PD-1 inhibitor-treated patients and compared with the International Federation of Gynecology and Obstetrics staging and combined positive score. Tertiary lymphoid structure positivity was more frequent in the invasive margin (58.2%) than in the tumor region (44.6%). All 4 tertiary lymphoid structure parameters independently predicted recurrence-free survival. The immune classification categorized patients into 3 groups with distinct 5-year recurrence-free survival rates (immune class I: 52.4%; immune class II: 78.1%; immune class III: 91.3%), outperforming International Federation of Gynecology and Obstetrics staging. In the PD-1 inhibitor cohort, higher immune class correlated with improved objective response rates (immune class I: 26.3%; immune class II: 56.3%; immune class III: 87.5%) and showed better predictive accuracy than the combined positive score. Immune class remained the only independent prognostic factor across all patient cohorts. This first tertiary lymphoid structure-based immune classification system effectively stratifies recurrence-free survival and PD-1 inhibitor response in cervical cancer, surpassing conventional staging methods. It underscores the clinical relevance of tertiary lymphoid structure organization and maturation, providing a practical tool for personalizing immunotherapy strategies.

Development and Validation of a Nomogram to Predict the Probability of Venous Thromboembolism in Patients with Epithelial Ovarian Cancer

Objective To identify predictive factors and develop a nomogram to predict the probability of venous thromboembolism for epithelial ovarian cancer patients. Methods: Our study cohort was composed of 208 EOC patients who had received initial treatment in Sun Yat-sen Memorial Hospital from January 2016 to March 2020. Clinicopathological variables predictive of VTE were identified using univariate logistic analysis. A multivariate logistic regression model was used to select the predictive factors used for nomogram. The accuracy of nomogram was evaluated by the Concordance index (C-index), the area under the receiver–operator characteristic (ROC) curve, area under concentration-time curve (AUC) and the calibration curve. Results: Advancing age (hazard ratio [HR], 1.042; 95% confidence interval [CI], 1.000-1.085; P = .048), higher D-dimer level (HR, 1.144; 95%CI, 1.020-1.283; P = .022), lower PR immunohistochemical positive rate (HR, 0.186; 95%CI, 0.034-1.065; P = .059) and higher Ki67 immunohistochemical positive rate (HR, 4.502; 95%CI, 1.637-12.380; P = .004) were found to be independent risk factors for VTE, and were used to construct the nomogram. The C-index for VTE prediction of the nomogram was 0.75. Conclusions: We constructed and validated a nomogram able to quantify the risk of VTE for EOC patients, which can be applied in recognizing EOC patients with high risk of VTE.

Clinical characteristics of vulvar basal cell carcinoma: a multi-center, retrospective study in China

This study aimed to summarize the clinical characteristics of basal cell carcinoma in a Chinese population over a 20-year period and identify key factors associated with vulvar basal cell carcinoma across different International Federation of Gynaecology and Obstetrics (FIGO) stages. This retrospective study included all adult patients with vulvar basal cell carcinoma treated at multiple Chinese grade A tertiary hospitals from 2003 to 2023. Patient demographic characteristics, symptoms, tumor characteristics, and treatment information were collected and analyzed. Univariate and multi-variable logistic regression analyses were performed to identify potential risk factors. A total of 100 patients with a vulvar basal cell carcinoma diagnosis were identified. Among the 100 patients, 14 patients were excluded due to unknown FIGO staging and 86 patients (45 [52.3%] FIGO IA group, 41 [47.7%] FIGO non-IA group; median age 65 years; interquartile range; 55-70 years) were included into the final analysis. The majority of patients were post-menopausal (n = 67; 77.9%). All patients were treated surgically by wide local excision (n = 65, 75.8%) or radical vulvectomy (n = 21, 24.4%). The majority were located on the labia majora (n = 56, 80%). In the univariate analysis, greater parity, defined as each additional live birth, was independently associated with an increased likelihood of vulvar basal cell carcinoma of FIGO stage >IA (odds ratio [OR] 1.524, 95% confidence interval [CI] 1.108 to 2.097, p = .010). After adjustment for confounding variables, greater parity remained a significant predictor of more advanced disease (non-IA FIGO stage) in vulvar basal cell carcinoma (adjusted OR 2.320, 95% CI 1.024 to 5.258, p = .044). This study demonstrated a significant association between greater parity and more advanced (FIGO stage >IA) vulvar basal cell carcinoma.

Preoperative prediction model of lymph node metastasis in the inguinal and femoral region based on radiomics and artificial intelligence

To predict preoperative inguinal lymph node metastasis in vulvar cancer patients using a machine learning model based on imaging features and clinical data from pelvic magnetic resonance imaging (MRI). 52 vulvar cancer patients were divided into a training set (n=37) and validation set (n=15). Clinical data and MRI images were collected, and regions of interest were delineated by experienced radiologists. A total of 1688 quantitative imaging features were extracted using the Radcloud platform. Dimensionality reduction and feature selection were applied, resulting in a radiomics signature. Clinical characteristics were screened, and a combined model integrating the radiomics signature and significant clinical features was constructed using logistic regression. Four machine learning classifiers (K nearest neighbor, random forest, adaptive boosting, and latent dirichlet allocation) were trained and validated. Model performance was evaluated using the receiver operating characteristic curve and the area under the curve (AUC), as well as decision curve analysis. The radiomics score significantly differentiated between lymph node metastasis positive and negative patients in both the training and validation sets. The combined model demonstrated excellent discrimination, with AUC values of 0.941 and 0.933 in the training and validation sets, respectively. The calibration curve and decision curve analysis confirmed the model's high predictive accuracy and clinical utility. Among the machine learning classifiers, latent dirichlet allocation and random forest models achieved AUC values >0.7 in the validation set. Integrating all four classifiers resulted in a total model with an AUC of 0.717 in the validation set. Radiomics combined with artificial intelligence can provide a new method for prediction of inguinal lymph node metastasis of vulvar cancer before surgery.

Squamous cell carcinoma antigen combined with HPV-16 infection in predicting high-grade squamous intraepithelial lesions of the cervix

An early screening of HPV and the Thinprep Cytology Test (TCT) can effectively prevent cervical cancer. However, patients with high-grade cervical intraepithelial neoplasia usually escape current screening methods and commonly develop cervical cancer. Hence, to identify effective and specific screening methods for high-grade cervical intraepithelial neoplasia is of vital necessity. In this study, 541 patients collected in Sun Yat-Sen hospital from January 2007 to December 2016 were selected. HPV genotype detection and SCC-ag detection were done in these patients. It was found that when serum SCC-ag level exceeded over 0.39 ng/ml in HPV-16 positive patients, the sensitivity and specificity of this novel approach to predict high-grade cervical intraepithelial neoplasia could reach to 83.1% and 62.1%, respectively. The result suggested that the combination of serum SCC-ag level and HPV-16 infection could be used as a novel approach for high-grade cervical intraepithelial neoplasia screening.Impact statement

Neutrophil extracellular traps enhance platinum resistance in ovarian cancer via SHP-1 activation

Platinum resistance continues to be a major therapeutic challenge in ovarian cancer, driving disease recurrence and limiting patient survival. In this study, we identify a significant enrichment of neutrophil extracellular traps (NETs) within the tumor microenvironment of platinum-resistant ovarian tumors. These NETs actively contribute to malignant progression by promoting epithelial-mesenchymal transition and fostering chemotherapy resistance. Mechanistically, we demonstrate that NETs drive chemoresistance through the unexpected activation of SHP-1. Although traditionally recognized as a tumor suppressor, SHP-1 assumes an oncogenic function in this context. Specifically, NETs trigger TGF-β signaling, resulting in Smad2 phosphorylation, which subsequently promotes both the enzymatic activation and nuclear translocation of SHP-1. Once in the nucleus, SHP-1 enhances RNA polymerase II-mediated transcription and nucleotide excision repair, ultimately enabling cancer cells to evade cisplatin-induced cytotoxicity. Our in vivo experiments corroborate these findings that elevated NETs levels exhibit poor response to cisplatin, while pharmacological inhibition of NETs effectively restores drug sensitivity. This study not only advances our understanding of microenvironment-driven drug resistance but also highlights the therapeutic potential of targeting the NETs/SHP-1 axis to overcome platinum resistance in ovarian cancer.