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.Effect of oxaliplatin on the activation of hepatic stellate cells and its mechanism
Cunkai WANG ; Yijun WANG ; Dandan WANG ; Xiaoli XIE ; Hongyu LIU ; Yun BAI ; Huiqing JIANG ; Yuzhen WANG
Journal of Clinical Hepatology 2024;40(6):1142-1148
Objective To investigate the effect of oxaliplatin on the activation of hepatic stellate cells(HSCs),as well as the association of oxaliplatin with microRNA-30a-5p and autophagy.Methods HSC-LX2 cells were cultured and divided into groups according to the following three protocols:control group,PDGF treatment group,oxaliplatin treatment group,oxaliplatin+PDGF treatment group;control group,microRNA-30a-5p transfection group,PDGF treatment group,microRNA-30a-5p transfection+PDGF treatment group;control group,3-MA group,microRNA-30a-5p inhibitor group,microRNA-30a-5p inhibitor+3-MA group.Western Blot was used to measure the expression of HSC activation-related proteins(Collagen-I and alpha-smooth muscle actin[α-SMA])and HSC autophagy-related proteins(Beclin-1,P62,and LC3B);LysoTracker staining and immunofluorescence assay were used to measure the expression of LC3B autophagosomes;RT-PCR was used to measure the expression level of microRNA-30a-5p;bioinformatics techniques were used to predict the potential targets of microRNA-30a-5p in HSCs.The independent-samples t test was used for comparison of normally distributed continuous data between two groups;a one-way analysis of variance was used for comparison between multiple groups,and the least significant difference t-test was used for further comparison between two groups.Results After the cells were treated with oxaliplatin,RT-PCR results showed that the oxaliplatin treatment group had a significantly higher expression level of microRNA-30a-5p than the control group(P<0.01);Western Blot showed that the oxaliplatin treatment group had significant reductions in the expression levels of the HSC activation-related proteins α-SMA and Collagen-Ⅰ and the autophagy-related proteins Beclin 1 and LC3BⅡ/Ⅰ(all P<0.001);immunofluorescence assay showed that the oxaliplatin treatment group had a significantly lower number of autophagosomes than the control group(P<0.05).After HSC-LX2 cells were transfected with microRNA-30a-5p mimic,compared with the control group,the microRNA-30a-5p mimic group had significant reductions in the expression levels of the autophagy-related proteins Beclin 1 and LC3BⅡ/Ⅰ(P<0.05)and the HSC activation-related protein Collagen-Ⅰ(P<0.001);after HSC-LX2 cells were transfected with microRNA-30a-5p inhibitor,Western Blot showed that compared with the control group,the microRNA-30a-5p inhibitor group had significant increases in the expression levels of the HSC activation-related proteins Collagen-Ⅰ and α-SMA and the autophagy-related protein Beclin 1(t=2.41,2.32,and 4.57,all P<0.05).Western Blot showed that compared with the control group,the microRNA-30a-5p inhibitor group had significant increases in the expression levels of the HSC autophagy-related protein Beclin 1 and the HSC activation-related protein α-SMA(both P<0.05),and after the treatment with the autophagy inhibitor 3-MA,there were no significant differences in the expression of these proteins between the two groups(P>0.05).The bioinformatics analysis using TargetScan,PicTar,and miRanda databases showed that the autophagy-related protein Beclin-1 might be a potential target of miRNA-30a-5p.Conclusion Oxaliplatin can inhibit the activation of HSCs by upregulating the expression of microRNA-30a-5p,which provides new ideas and a new target for the treatment of liver fibrosis.
5.Xiaozhong-Zhitong mixture induces M2 polarization of mouse microglia by inhibiting TLR4/MyD88/NF-κB signaling pathway
Jing XIE ; Zhijun HE ; Tao LIU ; Xiaotao WEI ; Weiwei WANG ; Yuanyuan SONG ; Huiqing TIAN
Chinese Journal of Pathophysiology 2024;40(9):1589-1597
AIM:To investigate the effects of Xiaozhong-Zhitong mixture(XZZT)on M2 polarization and Toll-like receptor 4(TLR4)/myeloid differentiation factor 88(MyD88)/nuclear factor-κB(NF-κB)signaling pathway in mouse microglia(BV2 cells).METHODS:The BV2 cells were divided into 5 groups:blank group,model group[lipo-polysaccharide(LPS)+hypoxia],TAK-242(resatorvid,a TLR4 inhibitor)group(LPS+hypoxia+TAK-242),XZZT group(LPS+hypoxia+XZZT),and TAK-242+XZZT group(LPS+hypoxia+TAK-242+XZZT).Flow cytometry was used to detect early apoptosis and cell cycle of BV2 cells,and immunofluorescence staining was employed to detect the positive expres-sion of M1-type marker inducible nitric oxide synthase(iNOS)and M2-type marker CD206.Western blot was utilized to detect the expression of TLR4/MyD88/NF-κB signaling pathway-related proteins,including TLR4,MyD88,NF-κB p65,phosphorylated p65(p-p65),phosphorylated transforming growth factor-β-activated kinase 1(p-TAK1),and phosphory-lated IκB kinase α/β(p-IKKα/β).RT-qPCR was used to detect the mRNA expression of interleukin-1β(IL-1β),IL-10,tumor necrosis factor-α(TNF-α),TLR4,MyD88,and NF-κB p65.RESULTS:Compared with model group,the rate of early apoptosis was significantly decreased in XZZT group(P<0.01),the percentage of cells arrested in the S phase was significantly increased(P<0.01),and the protein levels of TLR4,MyD88,NF-κB p65,p-IKKα/β,p-p65,and p-TAK1 were significantly decreased(P<0.05 or P<0.01).Additionally,IL-1β,TNF-α,TLR4,MyD88 and NF-κB p65 mRNA expression levels were significantly decreased(P<0.05 or P<0.01),while IL-10 mRNA expression was significantly in-creased(P<0.05).Compared with TAK-242 group,the average percentage of iNOS positive area was significantly de-creased,while CD206 was significantly increased in TAK-242+XZZT group(P<0.01).CONCLUSION:The XZZT has the effect of inducing M2 polarization of mouse microglia,and the mechanism may be linked to the inhibition of TLR4/MyD88/NF-κB signaling pathway.
6.Establishment of the norm of Core Occupational Stress Scale for workers of electronic manufacturing industry in China
Manqi HUANG ; Huiqing CHEN ; Xiaoyi LI ; Danping XIE ; Jiewei ZHENG ; Min YANG ; Jiabin CHEN ; Jin WANG ; Xiaoman LIU
China Occupational Medicine 2023;50(5):556-560
{L-End}Objective To establish the norm of Core Occupational Stress Scale (COSS) for electronic manufacturing industry workers in China. {L-End}Methods A total of 3 049 workers from five electronic manufacturing enterprises in four prefecture-level cities concentrated distribution of the electronics manufacturing industry in China were selected as research subjects using a stratified sampling method. COSS was used to investigate occupational stress levels, and the mean norm, percentile norm and threshold norms were established. {L-End}Results The average score of COSS for the electronic manufacturing industry workers in China was (43.5±7.4) points, and the average scores of social support, organization and reward, demand and effort, and autonomy dimensions were (9.5±3.1), (15.1±3.9), (13.1±3.0), and (5.7±2.0) points, respectively. A total score of 0.0-<47.0 points was determined as no occupational stress, 47.0-<51.0 points as mild occupational stress, 51.0-≤54.0 points as moderate occupational stress, and >54.0 points as severe occupational stress. {L-End}Conclusion The norm of COSS for workers in China's electronics manufacturing industry has been established, which can provide a reference for the evaluation and intervention of their occupational stress levels.
7.Summary of the best evidence on non-pharmacological interventions for orthostatic hypotension in patients with Parkinson disease
Meihong XIE ; Wei KE ; Huiqing MA ; Fenhui WANG ; Ying NI ; Mingqing DU ; Yifei SUN ; Huixian ZHA ; Hongyun YAN
Chinese Journal of Modern Nursing 2023;29(23):3143-3149
Objective:To search for and summarize the best evidence on non-pharmacological interventions for orthostatic hypotension in patients with Parkinson disease.Methods:Based on the 6S model, the relevant guidelines, clinical decisions, evidence summaries, systematic reviews and expert consensus on non-pharmacological interventions for orthostatic hypotension in Parkinson disease patients were systematically retrieved from domestic and foreign databases. The search time was from the establishment of the database to December 2022. Two researchers independently screened the literature, evaluated the quality of the included literature, and extracted and summarized evidence that met the quality standards.Results:A total of 15 articles were included, including 4 guidelines, 2 clinical decision-making articles, 1 evidence summary article, 3 systematic evaluations and 5 expert consensus articles. A total of 24 pieces of best evidence were summarized from 7 aspects, including purpose, evaluation, capacity intervention, exercise intervention, posture intervention, physical intervention, health education and support.Conclusions:The best evidence on non-pharmacological intervention for orthostatic hypotension in patients with Parkinson disease can provide a reference for the practice of clinical medical staffs. It is suggested to apply the best evidence in combination with the patient's condition, preference and clinical environment, so as to reduce the incidence of orthostatic hypotension in patients with Parkinson disease and to ensure the safety of patients.
8.Aspirin inhibits the growth of hypertrophic scar in rabbit ears via regulating Wnt/β-catenin signal pathway.
Zhihu LIN ; Xiao HAN ; Mengyao ZHANG ; Jiaqin XU ; Haihong LI ; Jianda ZHOU ; Huiqing XIE
Journal of Central South University(Medical Sciences) 2022;47(6):698-706
OBJECTIVES:
Steroidal anti-inflammatory drugs have certain side effects in the treatment of hypertrophic scar, and the scar recurrence is easy after withdrawal of steroid anti-inflammatory drugs. Finding reliable alternative drugs is an effective means to improve this defect. Aspirin, a traditional non-steroidal anti-inflammatory drug, is safe for topical use and has anti-inflammatory effects similar to those of steroidal anti-inflammatory drugs, which may have similar effects on the treatment of hypertrophic scar. This study aims to investigate the inhibitory effect of aspirin on the proliferation of hypertrophic scar in rabbit ears and the underlying mechanism.
METHODS:
The rabbit ear hypertrophic scar models were prepared. The rabbits were randomly divided into a normal skin group (group A), a blank control group (group B), a 0.9% NaCl group (group C), a 0.2% aspirin group (group D), a 0.5% aspirin group (group E), a 2% aspirin group (group F), and a triamcinolone acetonide group (group G). Macroscopic observation of hyperplasia was performed 8 weeks after local injection of the scar, followed by collecting the scar tissue samples for HE staining, Masson staining, and immunohistochemistry, respectively to assess the proliferation of fibroblasts and collagen fibers, and calculate the hypertrophic index, microvessel density, and immunohistochemical score.
RESULTS:
All rabbit ear hypertrophic scar models were successfully constructed. In groups B and C, the hypertrophic scar edge was irregular, with reddish protruding epidermis, significant contracture and hard touch. In group D, E, and F, with the increase of aspirin administration concentration, the scar became thinner and gradually flat, the proliferation of fibrocytes and collagen fibers was weakened, and the hypertrophic index was gradually decreased (P<0.05). Immunohistochemistry showed that the expression of β-catenin was decreased in the group D, E and F in turn, and the immunohistochemical score was gradually decreased (P<0.05). There was no significant difference in hypertrophic index, microvessel density, and immunohistochemical score (all P>0.05).
CONCLUSIONS
Local injection of aspirin can reduce the generation of hypertrophic scar in a dose-dependent manner within a certain concentration range; aspirin inhibits the growth of hypertrophic scar in rabbit ears by inhibiting Wnt/β-catenin signal pathway; 2% aspirin and 40 mg/mL triamcinolone acetonide have similar curative efficacy on hypertrophic scar.
Animals
;
Anti-Inflammatory Agents/therapeutic use*
;
Aspirin/therapeutic use*
;
Cicatrix, Hypertrophic/pathology*
;
Collagen
;
Rabbits
;
Signal Transduction
;
Triamcinolone Acetonide/therapeutic use*
;
beta Catenin/metabolism*
9.Research advances in the regulation of epithelial-mesenchymal transition and targeted therapy for liver fibrosis
Yongjuan WANG ; Xiaoli XIE ; Huiqing JIANG
Journal of Clinical Hepatology 2021;37(1):165-168
The pathological basis of liver fibrosis is the deposition of extracellular matrix (ECM), and myofibroblasts are the main source of ECM. Epithelial-mesenchymal transition (EMT) is one of production mechanisms of myofibroblasts. At present, a large number of studies have shown that intervention of key EMT molecules and signaling pathways as targets can reduce liver fibrosis. Based on literature review, this article summarizes the signaling pathways associated with EMT, important regulatory molecules, and drugs targeting EMT in the treatment of liver fibrosis, so as to provide new ideas for the treatment of liver fibrosis.
10.Value of a microRNA risk score model in predicting the prognosis of hepatocellular carcinoma
Xiuhong HUANG ; Xiaoli XIE ; Huiqing JIANG
Journal of Clinical Hepatology 2021;37(5):1110-1115.
ObjectiveTo screen out the microRNAs (miRNAs) associated with the prognosis of hepatocellular carcinoma (HCC) through data mining of miRNA transcriptome data of HCC downloaded from The Cancer Genome Atlas (TCGA) database, to establish a miRNA risk score model, and to investigate its value in predicting the prognosis of HCC. MethodsThe miRNA expression data and clinical data of HCC samples were downloaded from TCGA database and R language was used to screen out differentially expressed miRNAs between HCC tissue and adjacent tissue, which were randomly divided into training set and testing set after being integrated into clinical data. Univariate Cox regression analysis and least absolute shrinkage and selection operator (LASSO) Cox regression analysis were performed for the training set to screen out the miRNAs associated with the prognosis of HCC, and then a miRNA risk score model was established. The Kaplan-Meier method was used to evaluate the robustness of the model and whether it could predict the prognosis of patients in the same clinical stage. Finally, the receiver operating characteristic (ROC) curve was plotted and the area under the ROC curve (AUC) was calculated to compare the predictive accuracy of the model versus TNM staging in the training set, the testing set, and the entire set. ResultsA total of 300 differentially expressed miRNAs were screened out and the LASSO Cox regression analysis revealed that hsa-miR-139-5p, hsa-miR-1180-3p, hsa-miR-1269b, hsa-miR-3680-3p, hsa-miR-509-3-5p, and hsa-miR-31-5p were associated with the prognosis of HCC. The risk score was calculated for each sample according to the established miRNA risk score model, and the samples were divided into high-risk group and low-risk group according to the median risk score. The Kaplan-Meier curve showed that in both training and testing sets, the high-risk group had a significantly lower survival rate than the low-risk group (P<0.05). The ROC curve was used to evaluate the prediction efficiency of this model, and the results showed that in the training set, the testing set, and the entire set, the miRNA model had an AUC of 0.817, 0.808, and 0.814, respectively, while TNM staging had an AUC of 0.667, 0.665, and 0.663, respectively. The results of independent prognostic analysis also showed that this miRNA score model could be used as an independent prognostic factor for HCC (P<0.05). ConclusionHsa-miR-139-5p, hsa-miR-1180-3p, hsa-miR-1269b, hsa-miR-3680-3p, hsa-miR-509-3-5p, and hsa-miR-31-5p are associated with the prognosis of HCC, and the miRNA risk score model has a better prediction accuracy than TNM staging in the training set, the testing set, and the entire set. The stratified analysis also shows that the model can predict the prognosis of patients within the same TNM stage, and therefore, it has a certain reference value in clinical practice and can be used as an independent model for predicting the prognosis of HCC patients.

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