A 71-year-old male presented with esophageal cancer and severe aortic valve regurgitation. Treatment strategies for such patients are controversial. Considering the risks of cardiopulmonary bypass and potential esophageal cancer metastasis, we successfully performed transcatheter aortic valve implantation and minimally invasive three-incision thoracolaparoscopy combined with radical resection of esophageal cancer (McKeown) simultaneously in the elderly patient who did not require neoadjuvant treatment. This dual minimally invasive procedure took 6 hours and the patient recovered smoothly without any surgical complications.

ObjectiveTo explore effect of Xianlian Jiedu prescription on the recurrence of colorectal cancer （CRC） and investigate the related mechanisms. MethodsA postoperative recurrence model was established in 25 Balb/c mice by injecting CT26 cells subcutaneously into the armpit， followed by surgical removal of 99% of the subcutaneous tumor. The mice were randomly divided into model group， low-dose Xianlian Jiedu prescription （XLJDP-L） group （6.45 g·kg^-1·d^-1）， medium-dose Xianlian Jiedu prescription （XLJDP-M） group （12.9 g·kg^-1·d^-1）， high-dose Xianlian Jiedu prescription （XLJDP-H） group （25.8 g·kg^-1·d^-1）， and 5-fluorouracil （5-FU） group （1×10^-3 g·kg^-1·d^-1）. The mice were euthanized after 14 days of continuous intervention， and recurrent tumor tissue was harvested. Hematoxylin and eosin （HE） staining was used to observe pathological and morphological changes in the recurrent tumor tissue. Immunohistochemistry （IHC） was employed to assess the expression of proliferating cell nuclear antigen （Ki67）， vascular endothelial growth factor （VEGF）， and platelet-endothelial cell adhesion molecule （CD31） in recurrent tumor tissue. The Western blot was used to detect the protein expression levels of angiopoietin-2 （ANG-2）， VEGF， phosphorylated-protein kinase B （p-Akt）， protein kinase B （Akt）， phosphorylated-phosphatidylinositol 3-kinase （p-PI3K）， and phosphatidylinositol 3-kinase （PI3K） in recurrent tumor tissue. ResultsBefore treatment， there were no statistical differences in tumor volume， tumor weight， and body mass among the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group compared to the model group， indicating model stability. After treatment， compared with those in the model group， the tumor volume and tumor weight in the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly reduced （P<0.01）， showing dose dependency. Meanwhile， there were no significant differences in body weight among the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group compared to the model group. HE staining showed that compared with that in the model group， tumor tissue in the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group had loosely arranged cells， increased intercellular spaces， small and shriveled nuclei， light staining， fewer mitotic figures and atypical nuclei， and increased necrotic areas. IHC showed that compared with those of the model group， the positive rates of Ki67， VEGF， and CD31 in the recurrent tumor tissue of the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly reduced （P<0.01） in a dose-dependent manner. Western blot results showed that compared with those of the model group， the protein expression levels of ANG-2 and VEGF in the recurrent tumor tissue of the XLJDP-L， XLJDP-M， and XLJDP-H groups and the 5-FU group were significantly downregulated （P<0.05， P<0.01）， and the p-Akt/Akt and p-PI3K/PI3K ratios were significantly decreased in a dose-dependent manner （P<0.05， P<0.01）. ConclusionXianlian Jiedu prescription significantly inhibits the recurrence of CRC in mice after subcutaneous tumor surgery. The mechanism may involve regulating the PI3K/Akt pathway and downregulating key angiogenic proteins such as ANG-2， VEGF， and CD31.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Background: s/Aims: Sarcomatoid hepatocellular carcinoma (HCC) is a rare histological subtype of HCC characterized by extremely poor prognosis; however, its molecular characterization has not been elucidated. Methods: In this study, we conducted an integrated multiomics study of whole-exome sequencing, RNA-seq, spatial transcriptome, and immunohistochemical analyses of 28 paired sarcomatoid tumor components and conventional HCC components from 10 patients with sarcomatoid HCC, in order to identify frequently altered genes, infer the tumor subclonal architectures, track the genomic evolution, and delineate the transcriptional characteristics of sarcomatoid HCCs. Results: Our results showed that the sarcomatoid HCCs had poor prognosis. The sarcomatoid tumor components and the conventional HCC components were derived from common ancestors, mostly accessing similar mutational processes. Clonal phylogenies demonstrated branched tumor evolution during sarcomatoid HCC development and progression. TP53 mutation commonly occurred at tumor initiation, whereas ARID2 mutation often occurred later. Transcriptome analyses revealed the epithelial–mesenchymal transition (EMT) and hypoxic phenotype in sarcomatoid tumor components, which were confirmed by immunohistochemical staining. Moreover, we identified ARID2 mutations in 70% (7/10) of patients with sarcomatoid HCC but only 1–5% of patients with non-sarcomatoid HCC. Biofunctional investigations revealed that inactivating mutation of ARID2 contributes to HCC growth and metastasis and induces EMT in a hypoxic microenvironment. Conclusions We offer a comprehensive description of the molecular basis for sarcomatoid HCC, and identify genomic alteration (ARID2 mutation) together with the tumor microenvironment (hypoxic microenvironment), that may contribute to the formation of the sarcomatoid tumor component through EMT, leading to sarcomatoid HCC development and progression.

Purpose: Biomarkers predicting clinically significant prostate cancer (sPC) before biopsy are currently lacking. This study aimed to develop a non-invasive urine test to predict sPC in at-risk men using urinary metabolomic profiles. Materials and Methods: Urine samples from 934 at-risk subjects and 268 treatment-naïve PC patients were subjected to liquid chromatography/mass spectrophotometry (LC-MS)-based metabolomics profiling using both C18 and hydrophilic interaction liquid chromatography (HILIC) column analyses. Four models were constructed (training cohort [n=647]) and validated (validation cohort [n=344]) for different purposes. Model I differentiates PC from benign cases. Models II, III, and a Gleason score model (model GS) predict sPC that is defined as National Comprehensive Cancer Network (NCCN)-categorized favorable-intermediate risk group or higher (Model II), unfavorable-intermediate risk group or higher (Model III), and GS ≥7 PC (model GS), respectively. The metabolomic panels and predicting models were constructed using logistic regression and Akaike information criterion. Results: The best metabolomic panels from the HILIC column include 25, 27, 28 and 26 metabolites in Models I, II, III, and GS, respectively, with area under the curve (AUC) values ranging between 0.82 and 0.91 in the training cohort and between 0.77 and 0.86 in the validation cohort. The combination of the metabolomic panels and five baseline clinical factors that include serum prostate-specific antigen, age, family history of PC, previously negative biopsy, and abnormal digital rectal examination results significantly increased AUCs (range 0.88–0.91). At 90% sensitivity (validation cohort), 33%, 34%, 41%, and 36% of unnecessary biopsies were avoided in Models I, II, III, and GS, respectively. The above results were successfully validated using LC-MS with the C18 column. Conclusions Urinary metabolomic profiles with baseline clinical factors may accurately predict sPC in men with elevated risk before biopsy.

Objective To analyze the dynamic changes and influencing factors of Mycobacterium tuberculosis(TB)infection in grade-1 students in senior high school at the time of enrollment and one year after enrollment.Methods In 2022,TB screening was carried out among grade-2 students in 4 senior high schools in Binhai and Xiqing Districts of Tianjin.Basic information of students was collected,and TB infection detection results of grade-1 students in senior high school at the time of enrollment were collected retrospectively.Positive rate,strong positive rate and positive conversion rate from tuberculin skin test(TST)results of students were compared.Univariate and multiva-riate logistic regression models were used to analyze the relevant influencing factors for positive conversion of TST results.Results The overall positive rate of 1 839 students one year after enrollment was higher than that at the enrollment(46.82％vs 33.12％),while strong positive rate was lower(12.51％vs 13.00％),both with statisti-cally significant differences(both P＜0.001).One year after enrollment,64 out of 1 230 students who were origi-nally negative for TST in their first year of senior high school turned positive,with a positive conversion rate of 5.20％(95％CI:3.93％-6.48％).One year after enrollment,TST results showed that the average diameter of induration was 5(2,8)mm,diameter was 2(0,5)mm at the enrollment of the first year of senior high school,but the difference was not statistically significant(P=0.478).The difference range of average diameter of induration was±21 mm,39.70％of students being within±2 mm.Students with increased and decreased average diameter of induration accounted for 65.09％and 28.49％,respectively.Multivariate logistic regression analysis result showed that students in boarding school had a higher risk of positive conversion compared with non-boarding school students(OR=4.842,95％CI:2.794-8.392).Conclusion The screening of TB infection among grade-2 students in senior high school should be strengthened,with a focus on boarding school students.Early detection of tuberculosis patients and newly infected individuals can provide reference for implementing precise prevention and control.

Objective To explore the biological mechanisms of isorhamnetin(ISO)inhibition of breast cancer(BC)progression and effects on paclitaxel sensitivity by in vivo and in vitro experiments.Methods The effects of ISO on MDA-MB-231 cell viability,migration,invasion and apoptosis were explored by CCK-8,scratch,Transwell invasion and apoptosis assays.ISO biological functions were analyzed and core target genes were identified by genome-wide microarrays,functional enrichment and protein-protein interactions(PPI).CYP1B1 expression characterization and prognosis in BC were assessed by quantitative Real-time polymerase chain reaction(qRT-PCR),Western blotting(WB),and Kaplan-Meier plotter database.The effects of CYP1B1 overexpression on MDA-MB-231 cell viability,migration,invasion and apoptosis were explored by CCK-8,scratch,Transwell invasion and apoptosis assays.The effects of ISO and CYP1B1 on BC tumor growth were analyzed by establishing a subcutaneous graft tumor animal model and verified by histological analysis with immunohistochemistry(IHC)and hematoxylin and eosin(HE)staining.The effects of ISO and CYP1B1 on NF-κB signaling were analyzed by qRT-PCR and WB.The effect of ISO combined with paclitaxel on BC progression was analyzed by in vitro and in vivo experiments.Results The results of CCK-8 assay showed that ISO inhibited the viability of MDA-MB-231 cells with an IC50 value of 11.93 μmol/L;the scratch,Transwell invasion and apoptosis assays confirmed that ISO inhibited the migration and invasion of MDA-MB-231 cells and promoted apoptosis(P＜0.05).Volcano plot showed a total of 80 differentially expressed genes(DEGs),of which ISO promoted the expression of 27 genes and inhibited the expression of 53 genes.Gene set enrichment analyses showed that DEGs were mainly enriched in the signaling of organic hydroxyl compound metabolic process,inflammatory response,sterol metabolic process,and nuclear factor-κB(NF-κB).qRT-PCR,WB,and Kaplan-Meier plotter results showed that CYP1B1 mRNA and protein expression was increased in BC and mediated worse prognosis(P＜0.05).CCK-8,scratch,Transwell invasion and apoptosis assays showed that CYP1B1 overexpression enhanced MDA-MB-231 cell viability,migration and invasion,and inhibited apoptosis,which was reversed by the addition of ISO(P＜0.05).The results of in vivo experiments showed that ISO downregulated CYP1B1 expression and attenuated NF-κB signaling(P＜0.05).The results of in vitro and in vivo experiments showed that ISO combined with paclitaxel significantly inhibited BC cell viability and tumor growth(P＜0.05).Conclusion ISO inhibits BC malignant biological behavior by modulating the CYP1B1/NF-κB signaling axis,and ISO enhances paclitaxel sensitivity.