1.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
2.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
3.Integrated Transcriptomic Landscape and Deep Learning Based Survival Prediction in Uterine Sarcomas
Yaolin SONG ; Guangqi LI ; Zhenqi ZHANG ; Yinbo LIU ; Huiqing JIA ; Chao ZHANG ; Jigang WANG ; Yanjiao HU ; Fengyun HAO ; Xianglan LIU ; Yunxia XIE ; Ding MA ; Ganghua LI ; Zaixian TAI ; Xiaoming XING
Cancer Research and Treatment 2025;57(1):250-266
Purpose:
The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs).
Materials and Methods:
Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients.
Results:
A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804.
Conclusion
USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.
4. Risk analysis of re⁃fracture after percutaneous kyphoplasty in elderly patients with osteoporotic thoracolumbar compression fractures and construction of a columnar graph prediction model
Lei SUN ; Xing-Yu WANG ; Shui-Hua XIE
Acta Anatomica Sinica 2024;55(1):98-104
Objective To investigate the risk factors for re-fracture after percutaneous kyphoplasty (PKP) in elderly patients with osteoporotic thoracolumbar compression fractures and to construct a line graph prediction model. Methods One hundred and eighty-two elderly patients with osteoporotic thoracolumbar compression fractures treated with PKP from January 2016 to November 2019 were selected for the study‚ and the patients were continuously followed up for 3 years after surgery. Clinical data were collected from both groups; Receiver operating characteristic (ROC) curve analysis was performed on the measures; Logistic regression analysis was performed to determine the independent risk factors affecting postoperative re-fracture in PKP; the R language software 4. 0 “rms” package was used to construct a predictive model for the line graph‚ and the calibration and decision curves were used to internally validate the predictive model for the line graph and for clinical evaluation of predictive performance. Results The differences between the two groups were statistically significant (P<0. 05) in terms of bone mineral density (BMD)‚ number of injured vertebrae‚ single-segment cement injection‚ type of cement distribution‚ cement leakage‚ difference in vertebral body height before and after PKP‚ and change in posterior convexity angle. The area under the curve (AUC) for BMD‚ number of injured vertebrae‚ single-segment cement injection volume‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity change were 0. 772‚ 0. 732‚ 0. 722‚ 0. 801‚ and 0. 813‚ respectively‚ and the best cutoff values were -3. 1‚ 2‚ 3. 9 ml‚ 0. 4 mm‚ and 8. 7°‚ respectively. BMD‚ number of injured vertebrae‚ single-segment cement injection volume‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity change were independent risk factors for re-fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fractures. The calibration curve of the column line graph prediction model was close to the original curve and the ideal curve with a C-index of 0. 818 (95% CI: 0. 762-0. 883)‚ and the model fit was good; the threshold value of the column line graph prediction model was >0. 22‚ which could provide a net clinical benefit‚ and the net clinical benefit was higher than the independent predictors. Conclusion BMD‚ number of injured vertebrae‚ single-segment cement injection‚ cement leakage‚ pre-and post-PKP vertebral height difference‚ and posterior convexity angle change are independent risk factors affecting the recurrent fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fracture‚ and this study constructs a column line graph model to predict the recurrent fracture after PKP in elderly patients with osteoporotic thoracolumbar compression fracture as a predictor for clinical. This study provides an important reference for clinical prevention and treatment‚ and has clinical application value.
5.Mechanism of Sanhuang Xiexintang in Protecting Stress Gastric Ulcer in Rats
Yilin ZHONG ; Ran XIE ; Jiameng LI ; Shuang LIU ; Junying LI ; Mengnan ZANG ; Xing LIU ; Jinsong LIU ; Feng SUI ; Pengqian WANG
Chinese Journal of Experimental Traditional Medical Formulae 2024;30(10):45-53
ObjectiveTo explore the molecular mechanism of Sanhuang Xiexintang (SHXXT) in protecting stress gastric ulcer (SGU) in rats through network pharmacology, molecular docking, and animal experiments. MethodThe active ingredients and corresponding targets in SHXXT were collected and screened from the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP), Traditional Chinese Medicine Information Database (TCMID), Bioinformation Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM), and Swiss Target Prediction database. SGU-related targets were screened from the Online Mendelian Inheritance in Man (OMIM), Therapeutic Target Database (TTD), GeneCards database, and PharmGKB database. Herbal-ingredient-target (H-C-T) network was constructed by using Cytoscape 3.9.1 software. Protein-protein interaction (PPI) of drug and disease intersection targets was analyzed by using the Protein Interaction Platform (STRING) database. Gene ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted through the Database for Annotation Visualization and Integrated Discovery (DAVID). The active ingredients and key targets were validated using AutodockVina 1.2.2 molecular docking software, and the experimental results were further validated through animal experiments. ResultThe 55 active ingredients were screened, and 255 potential target genes for SHXXT treatment of SGU were predicted. The PPI analysis showed that protein kinase B (Akt), phosphatase and tensin homolog deleted on chromosome ten (PTEN), tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and cyclooxygenase-2 (COX-2) are the core targets of SHXXT for protecting SGU. GO and KEGG analyses showed that SHXXT may affect the development of SGU by regulating various biological processes such as the phosphoinositide 3-kinase (PI3K)/Akt signaling pathway and inflammatory processes. The molecular docking results showed that both the active ingredients and key targets had good binding ability. Animal experiments showed that compared with the blank group, the ulcer index (UI) of the model group was significantly increased (P<0.01), and the serum levels of TNF-α and IL-1β significantly increased (P<0.01). The phosphorylation level of PTEN in gastric mucosal tissue was significantly down-regulated (P<0.05). The phosphorylation levels of PI3K, Akt, and nuclear factor kappa-B (NF-κB) were significantly up-regulated (P<0.05). Compared with the model group, the UI of the treatment group was significantly reduced (P<0.01), and the serum levels of TNF-α and IL-1β were significantly reduced (P<0.01). The phosphorylation level of PTEN in gastric mucosal tissue was significantly up-regulated (P<0.01), and the phosphorylation levels of PI3K, Akt, and NF-κB were significantly downregulated (P<0.01). ConclusionThe application of network pharmacology prediction, molecular docking simulation, and animal experimental validation confirms that SHXXT regulates the PI3K/Akt/NF-κB signaling pathway to regulate the inflammatory response of rats and thus protects the gastric mucosa of SGU rats.
6.Efficacy and safety of camrelizumab monoclonal antibody combined with molecular-targeted therapy in elderly patients with advanced hepatocellular carcinoma
Long CHENG ; Yue ZHANG ; Yushen LIU ; Zhaoqing DU ; Zhaoyang GUO ; Yangwei FAN ; Ting LI ; Xu GAO ; Enrui XIE ; Zixuan XING ; Wenhua WU ; Yinying WU ; Mingbo YANG ; Jie LI ; Yu ZHANG ; Wen KANG ; Wenjun WANG ; Fanpu JI ; Jiang GUO ; Ning GAO
Journal of Clinical Hepatology 2024;40(10):2034-2041
Objective To investigate the efficacy and safety of camrelizumab monoclonal antibody combined with molecular-targeted therapy in elderly patients with unresectable or advanced hepatocellular carcinoma(HCC).Methods A retrospective analysis was performed for the patients with unresectable/advanced HCC who attended six hospitals from January 1,2019 to March 31,2021,and all patients received camrelizumab monoclonal antibody treatment,among whom 84.8%also received targeted therapy.According to the age of the patients,they were divided into elderly group(≥65 years)and non-elderly group(<65 years).The two groups were assessed in terms of overall survival(OS),progression-free survival(PFS),objective response rate(ORR),disease control rate(DCR),and immune-related adverse events(irAE).The chi-square test or the Fisher's exact test was used for comparison of categorical data between groups;the independent samples t-test was used for comparison of normally distributed continuous data,and the Mann-Whitney U test was used for comparison of non-normally distributed continuous data between two groups.The Kaplan-Meier method was used for survival analysis,and the log-rank test was used for comparison of survival curves.Univariate and multivariate Cox proportional hazards regression analyses were used to determine the independent influencing factors for PFS and DCR at 6 months.Results A total of 99 HCC patients were enrolled,with 27 in the elderly group and 72 in the non-elderly group.The elderly group had an OS rate of 67.8%,an ORR of 44.4%,and a DCR of 74.1%at 12 months and a median PFS of 6.4(95%confidence interval[CI]:3.0-12.4)months,with no significant differences compared with the non-elderly group(all P>0.05).The median OS was unavailable for the elderly group,while the non-elderly group had an OS of 18.9(95%CI:13.0-24.8)months;there was no significant difference between the two groups(P=0.485).The univariate and multivariate Cox regression analyses showed that major vascular invasion(MVI)was an independent risk factor for PFS(hazard ratio[HR]=2.603,95%CI:1.136-5.964,P=0.024)and DCR(HR=3.963,95%CI:1.671-9.397,P=0.002)at 6 months,while age,sex,etiology of HBV infection,presence of extrahepatic metastasis,Child-Pugh class B,and alpha-fetoprotein>400 ng/mL were not associated with PFS or DCR at 6 months.For the elderly group,the incidence rates of any irAE and grade 3/4 irAE were 51.9%and 25.9%,respectively,with no significant differences compared with the non-elderly group(P>0.05),and skin disease was the most common irAE in both groups(39.4%).Conclusion Camrelizumab monoclonal antibody combined with molecular-targeted therapy has similar efficacy and safety in patients with unresectable/advanced HCC aged≥65 years and those aged<65 years.MVI is associated with suboptimal response to immunotherapy and poor prognosis.
7.Mechanism of cuproptosis and its role in liver diseases
Mingqiang ZHU ; Xing XIE ; Qicheng LIAO ; Xiao HE ; Youming DING ; Xiaohua WANG
Journal of Clinical Hepatology 2024;40(11):2332-2337
Cuproptosis is a new type of cell death that depends on intracellular copper accumulation to trigger the aggregation of mitochondrial lipoacylated protein and the degradation of iron-sulfur cluster protein,with a different mechanism of action from autophagy,ferroptosis,pyroptosis,and necroptosis.Cuproptosis is closely association with the development of liver cancer and resistance to antitumor drugs,as well as the progression of various liver diseases such as hereditary liver diseases,nonalcoholic fatty liver disease,viral hepatitis,and liver cirrhosis.This article summarizes the mechanism of cuproptosis and its role in liver diseases,in order to provide a reference for further research and treatment of liver diseases.
8.Research status of quercetin-mediated MAPK signaling pathway in prevention and treatment of osteoporosis
Ke-Xin YUAN ; Xing-Wen XIE ; Ding-Peng LI ; Yi-Sheng JING ; Wei-Wei HUANG ; Xue-Tao WANG ; Hao-Dong YANG ; Wen YAN ; Yong-Wu MA
The Chinese Journal of Clinical Pharmacology 2024;40(9):1375-1379
Quercetin can mediate the activation of mitogen-activated protein kinase(MAPK)signaling pathways to prevent osteoporosis(OP).This paper comprehensively discusses the interrelationship between MAPK and osteoporosis-related cells based on the latest domestic and international research.Additionally,it elucidates the research progress of quercetin in mediating the MAPK signaling pathway for OP prevention.The aim is to provide an effective foundation for the clinical prevention and treatment of OP and the in-depth development of quercetin.
9.A Comprehensive Study of the Association between LEPR Gene rs1137101 Variant and Risk of Digestive System Cancers
Qiong Wei HU ; Guang Wei ZHOU ; Wei Guang ZHOU ; Xi Jia LIAO ; Xing Jia SHI ; FengYang XIE ; Heng Shou LI ; Yong WANG ; Hong Xian FENG ; Li Xiu GU ; Feng Bi CHEN
Biomedical and Environmental Sciences 2024;37(5):445-456
Objective The leptin receptor,encoded by the LEPR gene,is involved in tumorigenesis.A potential functional variant of LEPR,rs1137101(Gln223Arg),has been extensively investigated for its contribution to the risk of digestive system(DS)cancers,but results remain conflicting rather than conclusive.Here,we performed a case-control study and subsequent meta-analysis to examine the association between rs1137101 and DS cancer risk. Methods A total of 1,727 patients with cancer(gastric/liver/colorectal:460/480/787)and 800 healthy controls were recruited.Genotyping of rs1137101 was conducted using a polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP)assay and confirmed using Sanger sequencing.Twenty-four eligible studies were included in the meta-analysis. Results After Bonferroni correction,the case-control study revealed that rs1137101 was significantly associated with the risk of liver cancer in the Hubei Chinese population.The meta-analysis suggested that rs1137101 is significantly associated with the risk of overall DS,gastric,and liver cancer in the Chinese population. Conclusion The LEPR rs1137101 variant may be a genetic biomarker for susceptibility to DS cancers(especially liver and gastric cancer)in the Chinese population.
10.Prevalence and epidemiological characteristics of major chronic diseases in people living with HIV in Taizhou, Zhejiang Province, 1998-2022
Tingting WANG ; Shanling WANG ; Yating WANG ; Yali XIE ; Weiwei SHEN ; Xiaoxiao CHEN ; Xing LIU ; Haijiang LIN ; Na HE
Chinese Journal of Epidemiology 2024;45(7):983-989
Objective:To understand the prevalence of major chronic diseases of diabetes, cardiovascular disease and malignant tumor in people living with HIV in Taizhou.Methods:The data were collected from China Information System for Disease Control and Prevention and Taizhou Chronic Disease Information Management System. A total of 5 126 people living HIV under follow-up in Taizhou from 1998 to 2022 were included in the analysis. Software SAS 9.4 was used for χ 2 test, trend analysis and logistic regression analysis. Results:In the 5 126 people living with HIV, the reported prevalence rates of diabetes,cardiovascular disease and malignant tumor were 10.28% (527/5 126),3.98% (204/5 126) and 6.01% (308/5 126), respectively. 37.00% (195/527) and 48.58% (256/527), 40.20% (82/204) and 48.53% (99/204), 37.66% (116/308) and 48.38% (149/308) were diagnosed as diabetes, cardiovascular disease and malignant tumor before and after confirmation of HIV infection. From 2013 to 2022, the proportion of HIV infected people diagnosed with diabetes, cardiovascular disease and malignant tumor after confirmation increased (trend χ2=79.98, P<0.001; trend χ2=17.44, P<0.001; trend χ2=32.06, P<0.001). Based on the analysis on the factors for complicated chronic diseases in people living with HIV, it was found that women under 60 years old (a OR=0.66, 95% CI: 0.50-0.86) and those with access to antiviral treatment for >5 years before 2016 (a OR=0.54,95% CI:0.37-0.78) were less likely to develop complicated chronic diseases, and those under 60 years old with initial CD4 +T lymphocytes counts <200 cells/μl (a OR=1.32, 95% CI: 1.02-1.70), those aged 40-49 and 50-59 years (a OR=2.88, 95% CI:2.20-3.79; a OR=5.43, 95% CI: 4.10-7.21) as well as those without a record of treatment medication use after 2016 (a OR=1.95,95% CI:1.20-3.16) were more likely to develop complicated chronic diseases. The probability of developing complicated chronic diseases might increase with age in people living with HIV. Conclusions:From 1998 to 2022, there was a certain proportion of complicated chronic diseases among HIV infected individuals in Taizhou, and the proportion of diagnosed cases increased after HIV infection was confirmed. It is necessary to conduct early chronic disease screening, behavior intervention and standardized management in people living with HIV.

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