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BackgroundBasement membranes (BMs) have recently emerged as significant players in cancer progression and metastasis, rendering them promising targets for potential anti-cancer therapies. Here, we aimed to develop a novel signature of basement membrane-related genes (BMRGs) for the prediction of clinical prognosis and tumor microenvironment in hepatocellular carcinoma (HCC).MethodsThe differentially expressed BMRGs were subjected to univariate Cox regression analysis to identify BMRGs with prognostic significance. A six-BMRGs risk score model was constructed using Least Absolute Shrinkage Selection Operator (LASSO) Cox regression. Furthermore, a nomogram incorporating the BMRGs score and other clinicopathological features was developed for accurate prediction of survival rate in patients with HCC.ResultsA total of 121 differentially expressed BMRGs were screened from the TCGA HCC cohort. The functions of these BMRGs were significantly enriched in the extracellular matrix structure and signal transduction. The six-BMRGs risk score, comprising CD151, CTSA, MMP1, ROBO3, ADAMTS5 and MEP1A, was established for the prediction of clinical prognosis, tumor microenvironment characteristics, and immunotherapy response in HCC. Kaplan-Meier analysis revealed that the BMRGs score-high group showed a significantly shorter overall survival than BMRGs score-low group. A nomogram showed that the BMRGs score could be used as a new effective clinical predictor and can be combined with other clinical variables to improve the prognosis of patients with HCC. Furthermore, the high BMRGs score subgroup exhibited an immunosuppressive state characterized by infiltration of macrophages and T-regulatory cells, elevated tumor immune dysfunction and exclusion (TIDE) score, as well as enhanced expression of immune checkpoints including PD-1, PD-L1, CTLA4, PD-L2, HAVCR2, and TIGIT. Finally, a multi-step analysis was conducted to identify two pivotal hub genes, PKM and ITGA3, in the high-scoring group of BMRGs, which exhibited significant associations with an unfavorable prognosis in HCC.ConclusionOur study suggests that the BMRGs score can serve as a robust biomarker for predicting clinical outcomes and evaluating the tumor microenvironment in patients with HCC, thereby facilitating more effective clinical implementation of immunotherapy.

BackgroundNormal hepatic functional reserve is the key to avoiding liver failure after liver surgery. This study investigated the assessment of hepatic functional reserve using liver shear wave velocity (LSWV) combined with biochemical indicators, tumor volume, and portal vein diameter.MethodsIn this single-center prospective study, a total of 123 patients with hepatocellular carcinoma (HCC) were divided into a test group (n=92) and a validation group (n=31). All patients were Child-Pugh grade A. The indocyanine green retention rate at 15 min (ICG-R15), liver shear wave velocity (LSWV), portal vein diameter (Dpv), alanine aminotransferase (ALT), aspartate transaminase (AST), alkaline phosphatase (ALP), γ-glutamyl transpeptidase (γ-GGT), albumin (ALB), prothrombin time (PT), and also liver tumor volume (maximum diameter ≤5 cm) were measured. In the test group, multiple parameters were used to evaluate hepatic functional reserve, and the multiparametric model was established. Receiver operating characteristic (ROC) curve analysis was conducted to assess the diagnostic performance of the multiparametric model. In the validation group, the predictive effectiveness of the multiparametric model was analyzed using consistency tests.ResultsIt was revealed that LSWV, ALB, and PT were statistically significant in evaluation of the hepatic functional reserve (P

BackgroundThe degree of inflammation and immune status is widely recognized to be associated with intrahepatic cholangiocarcinoma (ICC) and is closely linked to poor postoperative survival. The purpose of this study was to evaluate whether the systemic immune-inflammatory index (SII) and the albumin bilirubin (ALBI) grade together exhibit better predictive strength compared to SII and ALBI separately in patients with ICC undergoing curative surgical resection.MethodsA retrospective analysis was performed on a cohort of 374 patients with histologically confirmed ICC who underwent curative surgical resection from January 2016 to January 2020 at three medical centers. The cohort was divided into a training set comprising 258 patients and a validation set consisting of 116 patients. Subsequently, the prognostic predictive abilities of three indicators, namely SII, ALBI, and SII+ALBI grade, were evaluated. Independent risk factors were identified through univariate and multivariate analyses. The identified independent risk factors were then utilized to construct a nomogram prediction model, and the predictive strength of the nomogram prediction model was assessed through Receiver Operating Characteristic (ROC) survival curves and calibration curves.ResultsUnivariate analysis of the training set, consisting of 258 eligible patients with ICC, revealed that SII, ALBI, and SII+ALBI grade were significant prognostic factors for overall survival (OS) and recurrence-free survival (RFS) (p < 0.05). Multivariate analysis revealed the independent significance of SII+ALBI grade as a risk factor for postoperative OS and RFS (p < 0.05). Furthermore, we conducted an analysis of the correlation between SII, ALBI, SII+ALBI grade, and clinical features, indicating that SII+ALBI grade exhibited stronger associations with clinical and pathological characteristics compared to SII and ALBI. We constructed a predictive model for postoperative survival in ICC based on SII+ALBI grade, as determined by the results of multivariate analysis. Evaluation of the model’s predictive strength was performed through ROC survival curves and calibration curves in the training set and validation set, revealing favorable predictive performance.ConclusionThe SII+ALBI grade, a novel classification based on inflammatory and immune status, serves as a reliable prognostic indicator for postoperative OS and RFS in patients with ICC.

BackgroundSurgery is an important means for patients with colorectal liver metastases (CRLM) to improve their long-term survival, and accurate screening of high-risk factors is crucial to guiding postoperative monitoring and treatment. With this in mind, the aim of this study was to investigate the expression levels and prognostic roles of Mismatch Repair (MMR), Ki67, and Lymphovascular invasion(LVI) in the tumor tissues of colorectal of CRLM.Methods85 Patients with CRLM who received surgical treatment for liver metastases after colorectal cancer resection from June, 2017 and Jan, 2020 were included in this study. Independent risk factors affecting the survival of patients with CRLM were investigated using a Cox regression model and the Kaplan-Meier method, and a nomogram for predicting the OS of patients with CRLM was established according to a Cox multivariate regression model. Calibration plots and Kaplan-Meier curves were used to assess the performance of the nomogram.ResultsThe median survival time was 39 months (95% CI: 32.05-45.950), and MMR, Ki67 and LVI were significantly correlated with prognosis. Univariate analysis indicated that larger metastasis size (p=0.028), more than one liver metastases (p=0.001),higher serum CA199 (p

Radiomics was proposed by Lambin et al. in 2012 and since then there has been an explosion of related research. There has been significant interest in developing high-throughput methods that can automatically extract a large number of quantitative image features from medical images for better diagnostic or predictive performance. There have also been numerous radiomics investigations on intrahepatic cholangiocarcinoma in recent years, but no pertinent review materials are readily available. This work discusses the modeling analysis of radiomics for the prediction of lymph node metastasis, microvascular invasion, and early recurrence of intrahepatic cholangiocarcinoma, as well as the use of deep learning. This paper briefly reviews the current status of radiomics research to provide a reference for future studies.

Background: Basement membranes (BMs) have recently emerged as significant players in cancer progression and metastasis, rendering them promising targets for potential anti-cancer therapies. Here, we aimed to develop a novel signature of basement membrane-related genes (BMRGs) for the prediction of clinical prognosis and tumor microenvironment in hepatocellular carcinoma (HCC). Methods: The differentially expressed BMRGs were subjected to univariate Cox regression analysis to identify BMRGs with prognostic significance. A six-BMRGs risk score model was constructed using Least Absolute Shrinkage Selection Operator (LASSO) Cox regression. Furthermore, a nomogram incorporating the BMRGs score and other clinicopathological features was developed for accurate prediction of survival rate in patients with HCC. Results: A total of 121 differentially expressed BMRGs were screened from the TCGA HCC cohort. The functions of these BMRGs were significantly enriched in the extracellular matrix structure and signal transduction. The six-BMRGs risk score, comprising CD151, CTSA, MMP1, ROBO3, ADAMTS5 and MEP1A, was established for the prediction of clinical prognosis, tumor microenvironment characteristics, and immunotherapy response in HCC. Kaplan-Meier analysis revealed that the BMRGs score-high group showed a significantly shorter overall survival than BMRGs score-low group. A nomogramshowed that the BMRGs score could be used as a new effective clinical predictor and can be combined with other clinical variables to improve the prognosis of patients with HCC. Furthermore, the high BMRGs score subgroup exhibited an immunosuppressive state characterized by infiltration of macrophages and T-regulatory cells, elevated tumor immune dysfunction and exclusion (TIDE) score, as well as enhanced expression of immune checkpoints including PD-1, PD-L1, CTLA4, PD-L2, HAVCR2, and TIGIT. Finally, a multi-step analysis was conducted to identify two pivotal hub genes, PKM and ITGA3, in the high-scoring group of BMRGs, which exhibited significant associations with an unfavorable prognosis in HCC. Conclusion: Our study suggests that the BMRGs score can serve as a robust biomarker for predicting clinical outcomes and evaluating the tumor microenvironment in patients with HCC, thereby facilitating more effective clinical implementation of immunotherapy. [ABSTRACT FROM AUTHOR]