Objective To describe the significance of the pretreatment inflammatory indicators in predicting the prognosis of patients with esophageal squamous cell carcinoma (ESCC) after undergoing radical radiotherapy. Methods The data of 246 ESCC patients who underwent radical radiotherapy were retrospectively collected. Receiver operating characteristic (ROC) curves were drawn to determine the optimal cutoff values for platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and systemic immune-inflammation index (SII). The Kaplan-Meier method was used for survival analysis. We conducted univariate and multivariate analyses by using the Cox proportional risk regression model. Software R (version 4.2.0) was used to create the nomogram of prognostic factors. Results The results of the ROC curve analysis showed that the optimal cutoff values of PLR, NLR, and SII were 146.06, 2.67, and 493.97, respectively. The overall response rates were 77.6% and 64.5% in the low and high NLR groups, respectively (P<0.05). The results of the Kaplan-Meier survival analysis revealed that the prognosis of patients in the low PLR, NLR, and SII group was better than that of patients in the high PLR, NLR, and SII group (all P<0.05). The results of the multivariate Cox regression analysis showed that gender, treatment modalities, T stage, and NLR were independent factors affecting the overall survival (OS). In addition, T stage and NLR were independent factors affecting the progression-free survival (PFS) (all P<0.05). The nomogram models of OS and PFS prediction were established based on multivariate analysis. The C-index values were 0.703 and 0.668. The calibration curves showed excellent consistency between the predicted and observed OS and PFS. Conclusion The pretreatment values of PLR, NLR, and SII are correlated with the prognosis of patients with ESCC who underwent radical radiotherapy. Moreover, NLR is an independent factor affecting the OS and PFS of ESCC patients. The NLR-based nomogram model has a good predictive ability.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

The trillions of commensal microorganisms living in the gut lumen profoundly influence the physiology and pathophysiology of the liver through a unique gut-liver axis. Disruptions in the gut microbial communities, arising from environmental and genetic factors, can lead to altered microbial metabolism, impaired intestinal barrier and translocation of microbial components to the liver. These alterations collaboratively contribute to the pathogenesis of liver disease, and their continuous impact throughout the disease course plays a critical role in hepatocarcinogenesis. Persistent inflammatory responses, metabolic rearrangements and suppressed immunosurveillance induced by microbial products underlie the pro-carcinogenic mechanisms of gut microbiota. Meanwhile, intrahepatic microbiota derived from the gut also emerges as a novel player in the development and progression of liver cancer. In this review, we first discuss the causes of gut dysbiosis in liver disease, and then specify the pivotal role of gut microbiota in the malignant progression from chronic liver diseases to hepatobiliary cancers. We also delve into the cellular and molecular interactions between microbes and liver cancer microenvironment, aiming to decipher the underlying mechanism for the malignant transition processes. At last, we summarize the current progress in the clinical implications of gut microbiota for liver cancer, shedding light on microbiota-based strategies for liver cancer prevention, diagnosis and therapy.

OBJECTIVES: To investigate the medium- and long-term efficacy of percutaneous mechanical thrombectomy (PMT) combined with stent implantation for treatment of iliac vein stenosis with lower extremity deep venous thrombosis (LEDVT). METHODS: Clinical and follow-up data of 125 patients with iliac vein stenosis and LEDVT who underwent PMT and stent implantation at five hospitals in northern Zhejiang province from January 2017 to June 2021 were collected. The thrombus clearance rate, thrombus recurrence rate, patency rate of iliac vein stents and post-thrombotic syndrome (PTS) occurrence rate were documented, and safety indicators such as bleeding, death, pulmonary embolism, stent fracture and displacement were assessed. RESULTS: Among 125 patients, for clearance of limb thrombosis, there were 8 cases of grade I (6.4%), 10 cases of grade II (8.0%), and 107 cases of grade III (85.6%). Patients were followed up for a median period of 74 months. According to the Villalta score, the recurrence rates of limb thrombosis at 12, 24 and 36 months were 8.48%, 8.93% and 10.91%; the iliac vein patency rates were 91.52%, 91.07%, and 89.09%; and the incidences of PTS were 5.08%, 5.36% and 6.36%, respectively. There were no major adverse events such as death, massive pulmonary embolism or severe hepatic and renal insufficiency, and no readmission intervention events due to stent fracture or other incidence were found. CONCLUSIONS PMT combined with iliac vein stent implantation is effective for patients with iliac vein stenosis complicated by LEDVT with good medium- and long-term efficacy and safety, which is worthy of clinical application.
Humans ; Stents ; Iliac Vein/pathology* ; Venous Thrombosis/surgery* ; Thrombectomy/methods* ; Female ; Male ; Middle Aged ; Aged ; Adult ; Constriction, Pathologic/surgery* ; Treatment Outcome ; Follow-Up Studies

Recent studies have indicated that the expression of ubiquitin-specific protease 51 (USP51), a novel deubiquitinating enzyme (DUB) that mediates protein degradation as part of the ubiquitin‒proteasome system (UPS), is associated with tumor progression and therapeutic resistance in multiple malignancies. However, the underlying mechanisms and signaling networks involved in USP51-mediated regulation of malignant phenotypes remain largely unknown. The present study provides evidence of USP51's functions as the prominent DUB in chemoresistant triple-negative breast cancer (TNBC) cells. At the molecular level, ectopic expression of USP51 stabilized the 78 kDa Glucose-Regulated Protein (GRP78) protein through deubiquitination, thereby increasing its expression and localization on the cell surface. Furthermore, the upregulation of cell surface GRP78 increased the activity of ATP binding cassette subfamily B member 1 (ABCB1), the main efflux pump of doxorubicin (DOX), ultimately decreasing its accumulation in TNBC cells and promoting the development of drug resistance both in vitro and in vivo. Clinically, we found significant correlations among USP51, GRP78, and ABCB1 expression in TNBC patients with chemoresistance. Elevated USP51, GRP78, and ABCB1 levels were also strongly associated with a poor patient prognosis. Importantly, we revealed an alternative intervention for specific pharmacological targeting of USP51 for TNBC cell chemosensitization. In conclusion, these findings collectively indicate that the USP51/GRP78/ABCB1 network is a key contributor to the malignant progression and chemotherapeutic resistance of TNBC cells, underscoring the pivotal role of USP51 as a novel therapeutic target for cancer management.

Objective:To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China.Methods:Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (＜60, 60-＜70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values.Results:A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening.Conclusion:To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.

Objective:To determine the total and age-specific cut-off values of total prostate specific antigen (tPSA) and the ratio of free PSA divided total PSA (fPSA/tPSA) for screening prostate cancer in China.Methods:Based on the Chinese Colorectal, Breast, Lung, Liver, and Stomach cancer Screening Trial (C-BLAST) and the Tianjin Common Cancer Case Cohort (TJ4C), males who were not diagnosed with any cancers at baseline since 2017 and received both tPSA and fPSA testes were selected. Based on Cox regression, the overall and age-specific (＜60, 60-＜70, and ≥70 years) accuracy and optimal cut-off values of tPSA and fPSA/tPSA ratio for screening prostate cancer were evaluated with time-dependent receiver operating characteristic curve (tdROC) and area under curve (AUC). Bootstrap resampling was used to internally validate the stability of the optimal cut-off value, and the PLCO study was used to externally validate the accuracy under different cut-off values.Results:A total of 5 180 participants were included in the study, and after a median follow-up of 1.48 years, a total of 332 prostate cancer patients were included. In the total population, the tdAUC of tPSA and fPSA/tPSA screening for prostate cancer were 0.852 and 0.748, respectively, with the optimal cut-off values of 5.08 ng/ml and 0.173, respectively. After age stratification, the age specific cut-off values of tPSA in the <60, 60-<70, and ≥70 age groups were 3.13, 4.82, and 11.54 ng/ml, respectively, while the age-specific cut-off values of fPSA/tPSA were 0.153, 0.135, and 0.130, respectively. Under the age-specific cut-off values, the sensitivities of tPSA screening for prostate cancer in males <60, 60-70, and ≥70 years old were 92.3%, 82.0%, and 77.6%, respectively, while the specificities were 84.7%, 81.3%, and 75.4%, respectively. The age-specific sensitivities of fPSA/tPSA for screening prostate cancer were 74.4%, 53.3%, and 55.9%, respectively, while the specificities were 83.8%, 83.7%, and 83.7%, respectively. Both bootstrap's internal validation and PLCO external validation provided similar results. The combination of tPSA and fPSA/tPSA could further improve the accuracy of screening.Conclusion:To improve the screening effects, it is recommended that age-specific cut-off values of tPSA and fPSA/tPSA should be used to screen for prostate cancer in the general risk population.

Objective:To investigate the importance of cell block and immunohistochemistry in the accurate diagnosis of serous effusion.Methods:A retrospective study was conducted on 3 124 cases of serous effusion from the Department of Pathology, Beijing Hospital from 2018 to 2022, include 2 213 cases of pleural effusion, 768 cases of peritoneal effusion, 143 cases of pericardial effusion. There were 1 699 males (54.4%) and 1 425 females (45.6%), average age 69 years old. Of which 1 292 cases were prepared with cell blocks and examined with immunohistochemical stain.Results:The percentage of malignant diagnosis increased from 64.9% (839/1 292) to 84.0% (1 086/1 292) after cell block preparation, and 1 086 cases were accurately diagnosed with histological type and/or origin of primary tumor. The undetermined diagnosis of suspected malignancy decreased from 13.3% (172/1 292) to 0.1% (1/1 292) and that of atypical hyperplasia from 18.8% (243/1 292) to 0.4% (5/1 292). The negative result for malignancy rate increased from 3.0% (38/1 292) to 15.5% (200/1 292). The differences highlighted above were statistically significant (Pearson′s chi-squared test=12.739, P<0.01). Conclusion:Application of immunohistochemistry based on cell block can significantly improve malignant diagnosis in serous effusion, identify tumor origin and histological type as well as decrease the uncertain diagnosis.

AIM:To investigate the effect of vaccarin(VAC)on endothelial dysfunction in type 2 diabetes mellitus(T2DM),and to uncover the underlying mechanisms.METHODS:(1)C57BL/6 mice received intraperitoneal injection of streptozotocin and were fed with a high-fat diet(21.8 kJ/kg,60%of the energy source was fat)to construct a T2DM mouse model.Thirty mice were randomly divided into control,T2DM and T2DM+VAC groups,with 10 mice in each group.The mice in T2DM+VAC group were given 1 mg/kg VAC via oral gavage for 6 weeks,while those in control and T2DM groups were given the same volume of PBS.The mRNA and protein expression levels of BCL2-interacting pro-tein 3(BNIP3),PTEN-induced kinase 1(PINK1)and parkin in the thoracic aorta were detected by RT-qPCR and West-ern blot.(2)Human umbilical vein endothelial cells(HUVECs)were stimulated by high glucose(HG;35 mmol/L glu-cose).Mitochondrial membrane potential,autophagy and mitochondrial superoxide levels were detected using JC-1,acri-dine orange(AO)and MitoSOX staining,respectively.RESULTS:Compared with control group,the mRNA and protein levels of BNIP3,PINK1 and parkin were significantly increased in the thoracic aorta of T2DM mice(P<0.05).Compared with T2DM group,the mRNA and protein levels of BNIP3,PINK1 and parkin in the thoracic aorta were significantly re-duced in T2DM+VAC group(P<0.05).The results of JC-1,AO and MitoSOX staining showed that VAC attenuated the decrease in mitochondrial membrane potential and the increase in autophagy and mitochondrial superoxide levels in HG-in-duced HUVECs.Treatment with VAC also inhibited HG-mediated mitochondrial damage in HUVECs after BNIP3 overex-pression.The effect of miR-570-3p mimic on mitochondrial damage was similar to VAC.RT-qPCR and Western blot showed that both miR-570-3p mimic and VAC significantly reduced the mRNA and protein levels of BNIP3,PINK1 and parkin.In contrast,inhibition of miR-570-3p exhibited the opposite effects.CONCLUSION:Treatment with VAC alle-viated endothelial dysfunction in T2DM by inhibiting HG-induced mitochondrial dysfunction through miR-570-3p/BNIP3.