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.

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.

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.

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.

OBJECTIVE: To study the clinical efficacy of Wenyang Lishui Formula (WYLSF) in preventing ovarian hyperstimulation syndrome (OHSS) and explore the suitable range of estradiol (E₂) on the human chorionic gonadotropin (HCG) day in patients with OHSS using WYLSF. METHODS: Part I: eligible patients at high risk for OHSS undergoing ovulation induction between January and December, 2023 were randomized into 2 groups based on the actual treatment. The treatment group received 200 mL WYLSF formula twice daily for 5 days after oocyte retrieval in a combination of lifestyle coaching (LC) intervention including regular diet and exercise, whereas the LC group received LC intervention alone. The incidence of OHSS, OHSS self-assessment scales, changes in E₂ levels on HCG day and 5 days after oocyte retrieval, ovarian morphology changes, and menstrual recovery were compared between the two groups. Part II: patients at high risk for OHSS treated with WYLSF were studied. The optimal E₂ threshold on the HCG day was determined using the maximum selection test, and a multivariate analysis was adopted to compare the relationship between different E₂ levels on HCG day and hospitalization rate, incidence of moderate to severe OHSS, and self-assessment scales, to explore the preventive effect of WYLSF on OHSS in patients with varying E₂ levels. RESULTS: A total of 120 patients were included in the Part I analysis. The treatment group (60 cases) showed a significant reduction in the incidence, duration, and severity of abdominal distension, as well as the incidence of vomiting compared with the LC group (P<0.05). The post-retrieval E₂ levels in the treatment group decreased significantly more (P=0.032). Among 1,652 patients treated with WYLSF in the Part II, 90 patients with ⩽ 10092 pmol/L, 159 with >31074 pmol/L, and 1,403 in the middle range group were formed based on E₂ levels on HCG day in Part two analysis. Univariate and regression analyses showed that patients with E₂ levels >31073 pmol/L had a significantly higher incidence of moderate to severe OHSS compared to those with E₂ levels ⩽ 10092 pmol/L (P<0.05). CONCLUSIONS WYLSF can effectively reduce specific symptoms in high-risk OHSS patients after ovulation induction and significantly lower E₂ levels. It may be more suitable for high-risk OHSS patients with E₂ levels <31073 pmol/L on HCG day. (Registration No. MR-11-23-032493, https://www.medicalresearch.org.cn/login ).
Humans ; Ovarian Hyperstimulation Syndrome/blood* ; Female ; Adult ; Prospective Studies ; Drugs, Chinese Herbal/pharmacology* ; Estradiol/blood* ; Ovulation Induction ; Chorionic Gonadotropin

Environmental toxicants have been linked to aging and age-related diseases. The emerging evidence has shown that the enhancement of detoxification gene expression is a common transcriptome marker of long-lived mice, Drosophila melanogaster, and Caenorhabditis elegans. Meanwhile, the resistance to toxicants was increased in long-lived animals. Here, we show that farnesoid X receptor (FXR) agonist obeticholic acid (OCA), a marketed drug for the treatment of cholestasis, may extend the lifespan and healthspan both in C. elegans and chemical-induced early senescent mice. Furthermore, OCA increased the resistance of worms to toxicants and activated the expression of detoxification genes in both mice and C. elegans. The longevity effects of OCA were attenuated in Fxr ^-/- mice and Fxr homologous nhr-8 and daf-12 mutant C. elegans. In addition, metabolome analysis revealed that OCA increased the endogenous agonist levels of the pregnane X receptor (PXR), a major nuclear receptor for detoxification regulation, in the liver of mice. Together, our findings suggest that OCA has the potential to lengthen lifespan and healthspan by activating nuclear receptor-mediated detoxification functions, thus, targeting FXR may offer to promote longevity.