JLJing Liu
Papers(3)
Research progress on …Molecular and Immune …Comprehensive clinica…
Collaborators(10)
Li LiQin XuLele ZangYanhong ZhuoYaxin KangHuai-Wu LuHuaiwu LuLele ChangShengtao ZhouSonghua Huang
Institutions(8)
Chengdu University Of…Qilu Hospital of Shan…Fujian Provincial Can…Union HospitalSchool of Basic Medic…Sun Yat Sen Memorial …Sichuan University We…Nanjing Second Hospit…

Papers

Research progress on correlative prediction factors and prediction models of endometriosis associated ovarian carcinoma

Background: Endometriosis is a common benign disease in women of childbearing age, with a malignant change rate of about 1%. Endometriosis associated ovarian cancer (EAOC), which usually occurs in the ovaries, is a serious threat to women’s health. Early identification of high-risk groups of EMs malignant transformation is of great significance for the prevention and treatment of EAOC. However, there is still a lack of specific and sensitive prediction factors. In recent years, scholars at home and abroad have used traditional statistical methods and machine learning to explore EAOC related prediction factors and prediction models. This paper mainly reviews and evaluates the diagnosis and prediction model of EAOC. Methods: Studies were identified by searching the CNKI, PubMed and Web of Science Core Collection, (WOSCC) till 2023, Data which met the inclusion criteria of clinical studies were evaluated about the quality. This paper analyzes and summarizes the prediction factors and prediction models in the literature. Results: After screening, 7 relevant studies were finally obtained. Prediction factors included: age, menstruation, menopausal status, course of disease, infertility associated with endometriosis, history of single estrogen use during menopause, serological indexes: human epididymis protein 4, carbohydrate antigen 125(CA125), ovarian malignancy risk algorithm, indications for ultrasound examination: cyst shape, structure and blood flow signal, etc. Prediction models: Alignment diagram, Multivariate logistic regression model, Gail model, Gradient Boosting Decision Tree and Lasso-logistics regression. Conclusion: Related models were in good agreement with the actual situation, and have good sensitivity and specificity. The relevant prediction factors and prediction models were summarized to provide reference and new thinking for the research of prediction models in the field of EAOC, in order to develop standardized long-term management strategies for high-risk groups of EAOC and realize the advance of the diagnosis threshold of patients with EAOC.

Molecular and Immune Correlates of Response to First-Line De-escalated Chemotherapy plus Penpulimab and Anlotinib in Advanced Cervical Cancer

Abstract The standard of care for advanced cervical cancer includes chemotherapy, antiangiogenic, and/or immune checkpoint blockade regimens. Although effective, it leads to pleiotropic side effects. Deescalation chemotherapy together with immunotargeted therapies has been proven effective and less toxic in other cancers. In this study, we conducted a multicenter, single-arm, phase II study of first-line deescalated platinum-based chemotherapy plus anlotinib and penpulimab, followed by maintenance therapy solely with anlotinib and penpulimab in patients with PD-L1–positive, persistent, recurrent, or metastatic cervical cancer. Of 32 efficacy-evaluable patients, 30 (93.8%, 95% confidence interval, 79.2%–99.2%) had an investigator-confirmed objective response. Single-nucleus RNA sequencing implied enhanced chemotaxis and proliferative activity of tumor-infiltrating T cells, and activated germinal center B cells portended optimal treatment response. Patients with a high tertiary lymphoid structure-to-tumor area ratio exhibited better survival. Our findings lay the groundwork for the feasibility of first-line de-escalated chemotherapy plus anlotinib and penpulimab in patients with metastatic, persistent, or recurrent cervical cancer. Significance: We recruited 34 patients with advanced cervical cancer receiving two cycles of platinum-based chemotherapy plus anlotinib and penpulimab, followed by maintenance therapy solely with anlotinib and penpulimab, and showed safety and efficacy of this deescalation regimen. This work highlights the potential for personalized treatment strategies and feasibility of reduced-toxicity regimens.

Comprehensive clinical analysis of gastric-type endocervical adenocarcinoma: a real-world multicenter study

Gastric-type endocervical adenocarcinoma (G-EAC) is a rare malignancy, and its clinicopathological characteristics remain poorly defined. This study aimed to evaluate the real-world features, treatment patterns, and outcomes of patients with G-EAC. Clinical data from 124 patients diagnosed with G-EAC between 2012 and 2024 across four tertiary hospitals in China were retrospectively analyzed. Clinicopathological features, therapeutic approaches, and survival outcomes were assessed. Overall survival (OS) was the primary endpoint. Kaplan-Meier and Cox regression analyses were performed to identify prognostic factors. The median diagnostic age was 55 years (range, 33-82). At presentation, 62.1% of patients had invasion or metastasis, most commonly lymphovascular (47.6%). Surgery was performed in 81.5% of cases, and 84.7% received chemotherapy, primarily platinum-based (81.5%). Radiotherapy was administered to 69.4%. The 1-, 3-, and 5-year OS rates were 78.6%, 54.8%, and 46.1%, respectively. Older age (≥65 years; HR, 4.71; 95% CI, 1.52-14.58; G-EAC exhibits aggressive behavior and unfavorable prognosis, with a 5-year OS of 46.1%. Multimodal treatment, particularly surgery combined with chemotherapy, remains the cornerstone of management and may improve survival. Prospective multicenter studies are warranted to further define optimal therapeutic strategies for this rare entity.

1Works
3Papers
33Collaborators
EndometriosisOvarian Neoplasms

Positions

Researcher

Chengdu University of Traditional Chinese Medicine

Education

2013

PhD

University of Florida · Biostatistics

2013

Master

University of Minnesota Twin Cities · Statistics

2011

Bachelor

Peking University · School of Mathematical Science