CBX1 is involved in hepatocellular carcinoma progression and resistance to sorafenib and lenvatinib via IGF-1R/AKT/SNAIL signaling pathway.

BACKGROUND: Chromobox Homolog 1 (CBX1) plays a crucial role in the pathogenesis of numerous diseases, including the evolution and advancement of diverse cancers. The role of CBX1 in pan-cancer and its mechanism in hepatocellular carcinoma (HCC), however, remains to be further investigated. METHODS: Bioinformatics approaches were harnessed to scrutinize CBX1's expression profile, its association with tumor staging, and its potential impact on patient outcomes across various cancers. Single-cell RNA sequencing data facilitated the investigation of CBX1 expression patterns at the individual cell level. The CBX1 expression levels in HCC and adjacent non-tumor tissues were quantified through Real-Time Polymerase Chain Reaction (RT-PCR), Western Blotting (WB), and Immunohistochemical analyses. A tissue microarray was employed to explore the relationship between CBX1 levels, patient prognosis, and clinicopathological characteristics in HCC. Various in vitro assays-including CCK-8, colony formation, Transwell invasion, and scratch tests-were conducted to assess the proliferative and motility properties of HCC cells upon modulation of CBX1 expression. Moreover, the functional impact of CBX1 on HCC was further discerned through xenograft studies in nude mice. RESULTS: CBX1 was found to be upregulated in most cancer forms, with heightened expression correlating with adverse patient prognoses. Within the context of HCC, elevated levels of CBX1 were consistently indicative of poorer clinical outcomes. Suppression of CBX1 through knockdown methodologies markedly diminished HCC cell proliferation, invasive capabilities, migratory activity, Epithelial-mesenchymal transition (EMT) processes, and resistance to Tyrosine kinase inhibitors (TKIs). Contrastingly, CBX1 augmentation facilitated the opposite effects. Subsequent investigative efforts revealed CBX1 to be a promoter of EMT and a contributor to increased TKI resistance within HCC cells, mediated via the IGF-1R/AKT/SNAIL signaling axis. The oncogenic activities of CBX1 proved to be attenuable either by AKT pathway inhibition or by targeted silencing of IGF-1R. CONCLUSIONS: The broad overexpression of CBX1 in pan-cancer and specifically in HCC positions it as a putative oncogenic entity. It is implicated in forwarding HCC progression and exacerbating TKI resistance through its interaction with the IGF-1R/AKT/SNAIL signaling cascade.

Gender disparities in all-cause mortality among individuals with early-onset cardiovascular diseases.

BACKGROUND AND OBJECTIVE: Gender disparities in mortality among individuals with early-onset cardiovascular disease (CVD) remain uncertain. This study aimed to investigate gender differences in all-cause mortality and identify influencing factors. METHODS: Data extracted from the Kailuan Study, a prospective cohort study initiated in 2006, were analyzed. A total of 2,829 participants with early-onset CVD were included. Cox proportional hazard models were used to assess hazard ratios (HR) and 95% confidence intervals (CI) for gender disparities in all-cause mortality, adjusting for various factors. RESULTS: Males experienced a median follow-up duration of 7.54 years with 276 recorded deaths, and females had a median follow-up of 6.45 years with 105 recorded deaths. Gender disparities in all-cause mortality were observed, with men experiencing a higher all-cause mortality risk compared to women (HR: 1.42, 95% CI: 1.04, 1.92) in the fully adjusted model. Both in men and women with early-onset CVD, elevated hs-CRP levels and an eGFR < 60 mL/min/1.73m2 notably escalated the risk of all-cause mortality. Furthermore, the utilization of antiplatelet agents and successful blood glucose control might mitigate the risk of all-cause mortality. Smoking and eGFR decline modified the association between gender and all-cause death, women were more vulnerable to tobacco consumption and kidney misfunctioning than men (P-interaction = 0.019). CONCLUSION: The study highlights gender disparities in all-cause mortality among individuals with early-onset CVD, with men experiencing a higher risk of mortality compared to women. Addressing these disparities is important for improving outcomes in this population. Further research is needed to develop sex-specific interventions and strategies to reduce gender-related mortality disparities in early-onset CVD.

Peripheral Lymphocytes in Primary Liver Cancers: Elevated NK and CD8+ T Cells and Dysregulated Selenium Metabolism.

Peripheral blood lymphocytes (PBLs), which play a pivotal role in orchestrating the immune system, garner minimal attention in hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). The impact of primary liver cancers on PBLs remains unexplored. In this study, flow cytometry facilitated the quantification of cell populations, while transcriptome of PBLs was executed utilizing 10× single-cell sequencing technology. Additionally, pertinent cases were curated from the GEO database. Subsequent bioinformatics and statistical analyses were conducted utilizing R (4.2.1) software. Elevated counts of NK cells and CD8+ T cells were observed in both ICC and HCC when compared to benign liver disease (BLD). In the multivariate Cox model, NK cells and CD8+ T cells emerged as independent risk factors for recurrence-free survival. Single-cell sequencing of PBLs uncovered the downregulation of TGFß signaling in tumor-derived CD8+ T cells. Pathway enrichment analysis, based on differential expression profiling, highlighted aberrations in selenium metabolism. Proteomic analysis of preoperative and postoperative peripheral blood samples from patients undergoing tumor resection revealed a significant upregulation of SELENBP1 and a significant downregulation of SEPP1. Primary liver cancer has a definite impact on PBLs, manifested by alterations in cellular quantities and selenoprotein metabolism.

Weight fluctuations preceding and succeeding heart failure diagnosis: Implications for all-cause mortality.

OBJECTIVE: This study aims to explore the ramifications of weight fluctuations preceding and succeeding the identification of heart failure (HF) on all-cause mortality. METHODS: The research cohort comprised individuals engaged in the Kailuan Group's health assessments from 2006 to 2018, who were subsequently diagnosed with HF. The moment of HF recognition marked the commencement of the monitoring period, culminating either at the instance of comprehensive mortality or at the conclusion of the monitoring phase (December 31, 2021). RESULTS: Throughout an average monitoring span of 5.8±3.5 years, from the 3115 qualified participants, 957 instances (30.7%) encountered comprehensive mortality. The COX proportional hazards regression model's outcomes revealed that, post the adjustment for potential confounders, in comparison to the Q3 category, the Q1 category had the highest hazard ratios (95% confidence intervals) of 1.71 (1.43-2.05). CONCLUSION: Weight reduction before and post the HF diagnosis stands as an autonomous risk determinant for comprehensive mortality.

Tumor Radiomic Features on Pretreatment MRI to Predict Response to Lenvatinib plus an Anti-PD-1 Antibody in Advanced Hepatocellular Carcinoma: A Multicenter Study.

Introduction: Lenvatinib plus an anti-PD-1 antibody has shown promising antitumor effects in patients with advanced hepatocellular carcinoma (HCC), but with clinical benefit limited to a subset of patients. We developed and validated a radiomic-based model to predict objective response to this combination therapy in advanced HCC patients. Methods: Patients (N = 170) who received first-line combination therapy with lenvatinib plus an anti-PD-1 antibody were retrospectively enrolled from 9 Chinese centers; 124 and 46 into the training and validation cohorts, respectively. Radiomic features were extracted from pretreatment contrast-enhanced MRI. After feature selection, clinicopathologic, radiomic, and clinicopathologic-radiomic models were built using a neural network. The performance of models, incremental predictive value of radiomic features compared with clinicopathologic features and relationship between radiomic features and survivals were assessed. Results: The clinicopathologic model modestly predicted objective response with an AUC of 0.748 (95% CI: 0.656-0.840) and 0.702 (95% CI: 0.547-0.884) in the training and validation cohorts, respectively. The radiomic model predicted response with an AUC of 0.886 (95% CI: 0.815-0.957) and 0.820 (95% CI: 0.648-0.984), respectively, with good calibration and clinical utility. The incremental predictive value of radiomic features to clinicopathologic features was confirmed with a net reclassification index of 47.9% (p < 0.001) and 41.5% (p = 0.025) in the training and validation cohorts, respectively. Furthermore, radiomic features were associated with overall survival and progression-free survival both in the training and validation cohorts, but modified albumin-bilirubin grade and neutrophil-to-lymphocyte ratio were not. Conclusion: Radiomic features extracted from pretreatment MRI can predict individualized objective response to combination therapy with lenvatinib plus an anti-PD-1 antibody in patients with unresectable or advanced HCC, provide incremental predictive value over clinicopathologic features, and are associated with overall survival and progression-free survival after initiation of this combination regimen.

Atrial fibrillation increases the risk of new-onset myocardial infarction amongst working-age population: a propensity-matched study.

OBJECTIVE: The aim of this study was to investigate the association between atrial fibrillation (AF) and new-onset myocardial infarction (MI) among a working-age population in an industrial city of North China. METHODS: In total 77,670 participants aged under 60 years were selected for this cohort study. Participants were divided into an AF group (n = 121) and a non-AF group (n = 74,565) based on their medical histories. Thereafter, 121 participants from the AF group were propensity-matched with 363 participants from the non-AF group. All participants were followed up from June 2006 to December 2020; new-onset MI was regarded as the endpoint of this study. Multivariate Cox proportional hazards regression analysis models were designed to analyze the correlation between AF and new-onset MI. RESULTS: During the 14-year follow-up, eight cases of new-onset MI were documented in the AF group, while five cases were documented in the non-AF group. The cumulative incidence of new-onset MI in the AF group (7.40%) was markedly higher than in the non-AF group (1.41%; p < 0.001). Atrial fibrillation was associated with an increased risk of new-onset MI in both univariate analysis (hazard ratio: 5.202, 95% confidence interval [CI]: 1.700-15.913) and multivariable-adjusted analysis (hazard ratio: 5.335, 95% CI: 1.683-16.910). CONCLUSION: Atrial fibrillation increased the risk of new-onset MI amongst working-age individuals in an industrial city of North China.

Development of the Scientific, Transparent and Applicable Rankings (STAR) tool for clinical practice guidelines.

BACKGROUND: This study aimed to develop a comprehensive instrument for evaluating and ranking clinical practice guidelines, named Scientific, Transparent and Applicable Rankings tool (STAR), and test its reliability, validity, and usability. METHODS: This study set up a multidisciplinary working group including guideline methodologists, statisticians, journal editors, clinicians, and other experts. Scoping review, Delphi methods, and hierarchical analysis were used to develop the STAR tool. We evaluated the instrument's intrinsic and interrater reliability, content and criterion validity, and usability. RESULTS: STAR contained 39 items grouped into 11 domains. The mean intrinsic reliability of the domains, indicated by Cronbach's α coefficient, was 0.588 (95% confidence interval [CI]: 0.414, 0.762). Interrater reliability as assessed with Cohen's kappa coefficient was 0.774 (95% CI: 0.740, 0.807) for methodological evaluators and 0.618 (95% CI: 0.587, 0.648) for clinical evaluators. The overall content validity index was 0.905. Pearson's r correlation for criterion validity was 0.885 (95% CI: 0.804, 0.932). The mean usability score of the items was 4.6 and the median time spent to evaluate each guideline was 20 min. CONCLUSION: The instrument performed well in terms of reliability, validity, and efficiency, and can be used for comprehensively evaluating and ranking guidelines.

Visual Perception and Convolutional Neural Network-Based Robotic Autonomous Lung Ultrasound Scanning Localization System.

Under the situation of severe COVID-19 epidemic, lung ultrasound (LUS) has been proved to be an effective and convenient method to diagnose and evaluate the extent of respiratory disease. However, the traditional clinical ultrasound (US) scanning requires doctors not only to be in close contact with patients but also to have rich experience. In order to alleviate the shortage of medical resources and reduce the work stress and risk of infection for doctors, we propose a visual perception and convolutional neural network (CNN)-based robotic autonomous LUS scanning localization system to realize scanned target recognition, probe pose solution and movement, and the acquisition of US images. The LUS scanned targets are identified through the target segmentation and localization algorithm based on the improved CNN, which is using the depth camera to collect the image information; furthermore, the method based on multiscale compensation normal vector is used to solve the attitude of the probe; finally, a position control strategy based on force feedback is designed to optimize the position and attitude of the probe, which can not only obtain high-quality US images but also ensure the safety of patients and the system. The results of human LUS scanning experiment verify the accuracy and feasibility of the system. The positioning accuracy of the scanned targets is 15.63 ± 0.18 mm, and the distance accuracy and rotation angle accuracy of the probe position calculation are 6.38 ± 0.25 mm and 8.60° ±2.29° , respectively. More importantly, the obtained high-quality US images can clearly capture the main pathological features of the lung. The system is expected to be applied in clinical practice.

A novel myeloid cell marker genes related signature can indicate immune infiltration and predict prognosis of hepatocellular carcinoma: Integrated analysis of bulk and single-cell RNA sequencing.

Myeloid cells are physiologically related to innate immunity and inflammation. Tumor-associated myeloid cells gained increasing interest because of their critical roles in tumor progression and anticancer immune responses in human malignancies. However, the associations between tumor-associated myeloid cell-related genes and hepatocellular carcinoma have yet to be revealed. Here, through the integrating analysis of bulk and single-cell RNA (scRNA) sequencing of public HCC samples, we developed a gene signature to investigate the role of HCC-specific myeloid signature genes in HCC patients. We firstly defined 317 myeloid cell marker genes through analyzing scRNA data of HCC from the GEO dataset. After selecting the differentially expressed genes, eleven genes were also proved prognostic. Then we built a gene signature from the TCGA cohort and verified further with the ICGC dataset by applying the LASSO Cox method. An eight genes signature (FABP5, C15orf48, PABPC1, TUBA1B, AKR1C3, NQO1, AKR1B10, SPP1) was achieved finally. Patients in the high risk group correlated with higher tumor stages and poor survival than those in the low-risk group. The risk score was proved to be an independent risk factor for prognosis. The high risk group had higher infiltrations of dendritic cells, macrophages and Tregs. And the APC co-inhibition, T cell co-inhibition pathways were also activated. Besides, the risk score positively correlated with multidrug resistance proteins. In conclusion, our myeloid cell marker genes related signature can predict patients' survival and may also indicate the levels of immune infiltration and drug resistance.

Effects of p-cresol, a uremic toxin, on cancer cells.

Background: Though p-cresol exists at a low concentration in the blood, it accumulates in various organs of uremic patients. Previous research has shown that the p-cresol promoted bladder cancer cell invasion and migration. This study aims to see if p-cresol had similar effects on kidney cancer cells and liver cancer cells. Methods: For 48 hours, 786-O human renal cancer cells and HepG2 human liver cancer cells were treated with p-cresol at concentrations of 0, 10, 20, 40, and 70 µM. The effects of p-cresol on cell viability, apoptosis, migration, and invasion were then analyzed using the CCK-8, TUNEL, and Transwell migration/invasion assays, respectively. Results: P-cresol at 0 to 70 µM for 48 hours had no significant toxic effects on 786-O cells or HepG2 cells. We chose 40 µM p-cresol for 48 hours for the following experiment. The viability and proliferation of 786-O cells and HepG2 cells were unaffected after 48 hours of treatment, with 40 µM p-cresol. However, 40 µM p-cresol for 48 hours promoted HepG2 cell migration and invasion but did not have the same effect on the 786-O cell line. Conclusions: P-cresol may be responsible for HepG2 cells' malignant biological behavior. Because the liver is the primary site of p-cresol metabolism, it is important to study the responses of cancer cells in the liver to p-cresol.

A Novel Approach Based on Gut Microbiota Analysis and Network Pharmacology to Explain the Mechanisms of Action of Cichorium intybus L. Formula in the Improvement of Hyperuricemic Nephropathy in Rats.

Background: Cichorium intybus L. formula (CILF) is a traditional Chinese medicine (TCM) widely used in the treatment of gout and hyperuricemic nephropathy (HN). The aim of this research was to investigate the potential protective effect of CILF against HN and elucidated the underlying mechanism. Methods: CILF water extract was administered to an HN rat model established by adenine combined with ethambutol. The levels of uric acid (UA), serum urea nitrogen (UREA), and creatinine (CREA) were detected. Changes in the pathology and histology of the kidney were observed by hematoxylin-eosin staining. The 16S rRNA of the gut microbiota was sequenced. The binding ability of the main ingredients of CILF to key targets was analyzed by network pharmacology and molecular docking. The expression levels of the related mRNAs and proteins in the kidney were evaluated by RT-qPCR and immunohistochemistry analysis. Results: CILF administration significantly alleviated increases in UA, UREA, and CREA, structural damage, and kidney dysfunction. Gut microbiota analysis was applied to explore the pharmacological mechanism of the effects of CILF on bacterial diversity and microbiota structure in HN. CILF decreased the abundance of Bacteroides. In addition, it increased the abundance of Lactobacillaceae, Erysipelotrichaceae, Lachnospiraceae, Ruminococcaceae, and Bifidobacterium. Based on network pharmacology and molecular docking analysis, CILF profoundly influenced the IL17, TNF and AGE-RAGE signaling pathway. Additionally, CILF inhibited the expression of STAT3, VEGFA and SIRT1 to improve the symptoms of nephropathy. Our research suggested that CILF protects against kidney dysfunction in rats with HN induced by adenine combined with ethambutol. Conclusion: Our findings on the anti-HN effects of CILF and its mechanism of action, from the viewpoint of systems biology, and elaborated that CILF can alter the diversity and community structure of the gut microbiota in HN, providing new approaches for the prevention and treatment of HN.

Association of genetic variants in Leptin, leptin receptor and adiponectin with hypertension risk and circulating Leptin/Adiponectin changes.

BACKGROUNDS: Hypertension is inheritable, and some candidate genes such as leptin and adiponectin have drawn special concerns. OBJECTIVES: We performed a meta-analysis on the association of 7 genetic variants in genes encoding leptin, leptin receptor and adiponectin with hypertension risk and circulating leptin/adiponectin changes. METHODS: Literature search, report selection and data extraction were performed by two authors independently. Effect sizes are expressed as odds ratio (OR) or standard mean difference (SMD) with 95% confidence interval (CI). RESULTS: Total 32 reports (7432 cases with hypertension and 9218 controls) were meta-analyzed. Overall analyses indicated that rs7799039 (dominant model: OR = 1.67; 95 % CI: 1.03 to 2.71; P = 0.038) and (TTTC)n (allelic model: OR = 1.53; 95 % CI: 1.05 to 2.23; P = 0.028) were significantly associated with hypertension risk. Subgroup analyses indicated that hypertension type, race, diabetes, genotyping method and quality score might be potential causes for between-study heterogeneity. Besides rs2241766, no evidence of publication bias existed for the other variants. Carriers of rs7799039-AG genotype had significantly higher leptin concentrations than carriers of rs7799039-GG genotype (SMD = 1.98; 95 % CI: 0.07 to 3.89; P = 0.042). In Mendelian randomization analyses, an increment of leptin concentrations by 1 ng/mL was causally associated with a 25 % significantly increased risk of hypertension (95 % CI: 1.02 to 10+; P < 0.05). CONCLUSIONS: Our findings indicated that leptin gene rs7799039 and (TTTC)n were potential hypertension-candidacy loci, and importantly high circulating leptin concentrations causally precipitated the development of hypertension.

Integration of network pharmacology and intestinal flora to investigate the mechanism of action of Chinese herbal Cichorium intybus formula in attenuating adenine and ethambutol hydrochloride-induced hyperuricemic nephropathy in rats.

CONTEXT: Cichorium intybus L. (Asteraceae) formula (CF) has been applied as a folk medicine to treat hyperuricemic nephropathy (HN). However, the exact mechanism remains unclear. OBJECTIVE: To explore the therapeutic effect and mechanism of CF on HN. MATERIALS AND METHODS: Through network pharmacological methods, the targets of the active component of CF against HN were obtained. Subsequently, Male Wistar rats were divided into control, HN, allopurinol (50 mg/kg), CF high-dose (8.64 g/kg) and CF low-dose (2.16 g/kg) groups. The HN model was induced via intragastric administration of adenine (100 mg/kg) and ethambutol hydrochloride (250 mg/kg) for 3 weeks. After CF treatment, biochemical indicators including UA, UREA and CREA were measured. Then, HE staining, qRT-PCR and gut microbiota analysis were conducted to further explore the mechanism. RESULTS: The network pharmacology identified 83 key targets, 6 core genes and 200 signalling pathways involved in the treatment of HN. Compared to the HN group, CF (8.64 g/kg) significantly reduced the levels of UA, UREA and CREA (from 2.4 to 1.57 µMol/L, from 15.87 to 11.05 mMol/L and from 64.83 to 54.83 µMol/L, respectively), and mitigated renal damage. Furthermore, CF inhibited the expression of IL-6, TP53, TNF and JUN. It also altered the composition of gut microbiota, and ameliorated HN by increasing the relative abundance of some probiotics. CONCLUSIONS: This work elucidated the therapeutic effect and underlying mechanism by which CF protects against HN from the view of the biodiversity of the intestinal flora, thus providing a scientific basis for the usage of CF.

Hepatic Arterial Infusion Chemotherapy with Oxaliplatin Plus Raltitrexed as an Alternative Option in Advanced Hepatocellular Carcinoma Patients with Failure of, or Unsuitability for, Transarterial Chemoembolization.

Background and Objectives: To assess the efficacy and safety of hepatic arterial infusion chemotherapy (HAIC) with oxaliplatin plus raltitrexed (HAICROX) as an alternative treatment option for advanced hepatocellular carcinoma (HCC) patients who are ineligible for, or failed, the transarterial chemoembolization (TACE) treatment. Materials and Methods: From July 2020 to November 2021, a total of 35 HCC patients were enrolled and received HAIC with oxaliplatin plus raltitrexed. The overall survival (OS) and time to progression (TTP) were primary and secondary endpoints, respectively. The tumor response was assessed by the modified response evaluation criteria in solid tumors (mRECIST), and the adverse events were investigated using the common terminology criteria for adverse events version 5.0 (CTCAE 5.0). Results: The median OS and TTP were 10 months (95% confidence interval (CI): 5.5-14.6) and 3.5 months (95% CI: 2.3-4.7), respectively. By means of multivariate analysis, anti-programmed cell death protein 1 (anti-PD-1) immunotherapy was found to be an independent prognostic factor for better survival. No patients experienced toxicity-related death. Thrombocytopenia, alanine aminotransferase (ALT), and aspartate aminotransferase (AST) elevation were the most common toxicities. No grade 3 or higher adverse events related to HAICROX were observed. Conclusion: HAICROX showed valuable efficacy and tolerable toxicity in advanced HCC patients who progressed on TACE or were ineligible for TACE. HAICROX is a promising treatment for advanced-stage HCC patients with TACE failure or ineligibility.

Recurrence Outcome in Hepatocellular Carcinoma within Milan Criteria Undergoing Microwave Ablation with or without Transarterial Chemoembolization.

Background and Objectives: The recurrence outcome in patients who underwent microwave ablation (MWA) with or without transarterial chemoembolization (TACE) for hepatocellular carcinoma (HCC) within Milan criteria remains unclear. The aim of this retrospective study was to identify the predictive factors of recurrence in these patients. Materials and Methods: From May 2018 to April 2021, 66 patients with HCC within Milan criteria were enrolled. Local tumor progression (LTP) and recurrence-free survival (RFS) were evaluated. Univariate and multivariate analyses were used to evaluate the risk factors of recurrence. The propensity score analysis was conducted to reduce potential confounding bias. Results: During the median follow-up of 25.07 months (95% confidence interval [CI], 21.85, 28.28), the median time to LTP and RFS were 20.10 (95%CI, 14.67, 25.53) and 13.03 (95%CI, 6.36, 19.70) months. No group difference (MWA vs. MWA + TACE) was found in 1-year cumulative LTP (p = 0.575) and RFS (p = 0.515), but meaningful significant differences were found in two-year recurrence (LTP, p = 0.007 and RFS, p = 0.037). Univariate and multivariate analyses revealed that treatment received before ablation was an independent risk factor of LTP (hazard ratio [HR] 4.37, 95%CI, 1.44, 13.32) and RFS (HR 3.41, 95%CI, 1.49, 7.81). Conclusions: The LTP and RFS in the MWA group were similar to that in the MWA combined with TACE. For HCC within Milan criteria, both groups preferentially selected MWA. More endeavor and rigorous surveillance should be taken to relapse prevention, in patients who have received previous treatment.

Efficacy of Transarterial Chemoembolization Combined with Molecular Targeted Agents for Unresectable Hepatocellular Carcinoma: A Network Meta-Analysis.

Transarterial chemoembolization (TACE) combined with tyrosine kinase inhibitors (TKIs) is the mainstay treatment for unresectable hepatocellular carcinoma (uHCC). However, studies investigating different combinations of agents have shown inconsistent results. Here, we used network meta-analysis (NMA) to compare different agents across 41 studies (36 cohort studies and five RCTs) in 11,540 patients. Multiple RCTs and cohort studies were searched to evaluate TACE combined with different TKIs. Outcomes of interest included overall survival (OS), progression-free survival (PFS), and tumor response. NMA used a random-effects consistency model to pool evidence from direct and indirect comparisons. Hazard ratio (HR) and relative risks (RR) with 95% confidence intervals (CI) were analyzed. Further, heterogeneity and publication bias analyses were performed and agents were ranked. TACE plus lenvatinib provided the maximal OS (Rank probability: 0.7559), PFS (Rank probability: 0.8595), CR (Rank probability: 0.4179), and DCR (Rank probability: 0.3857). TACE plus anlotinib demonstrated the highest PR (p = 0.62649) and ORR (p = 0.51158). SD was more often associated with TACE plus sorafenib (Rank probability: 0.601685). TACE plus lenvatinib provides optimal treatment for uHCC based on the highest ranking of OS, PFS, and DCR rates. However, given the lack of statistically significant OS benefit, shared decision making should include other TKIs as acceptable alternatives.

scGraph: a graph neural network-based approach to automatically identify cell types.

MOTIVATION: Single-cell technologies play a crucial role in revolutionizing biological research over the past decade, which strengthens our understanding in cell differentiation, development and regulation from a single-cell level perspective. Single-cell RNA sequencing (scRNA-seq) is one of the most common single cell technologies, which enables probing transcriptional states in thousands of cells in one experiment. Identification of cell types from scRNA-seq measurements is a fundamental and crucial question to answer. Most previous studies directly take gene expression as input while ignoring the comprehensive gene-gene interactions. RESULTS: We propose scGraph, an automatic cell identification algorithm leveraging gene interaction relationships to enhance the performance of the cell-type identification. scGraph is based on a graph neural network to aggregate the information of interacting genes. In a series of experiments, we demonstrate that scGraph is accurate and outperforms eight comparison methods in the task of cell-type identification. Moreover, scGraph automatically learns the gene interaction relationships from biological data and the pathway enrichment analysis shows consistent findings with previous analysis, providing insights on the analysis of regulatory mechanism. AVAILABILITY AND IMPLEMENTATION: scGraph is freely available at https://github.com/QijinYin/scGraph and https://figshare.com/articles/software/scGraph/17157743. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Prognostic Significance of Tumor Growth Rate (TGR) in Patients with Huge Hepatocellular Carcinoma Undergoing Transcatheter Arterial Chemoembolization.

The prognostic value of the tumor growth rate (TGR) in huge hepatocellular carcinoma (HHCC) patients treated with transcatheter arterial chemoembolization (TACE) as an initial treatment remains unclear. This two-center retrospective study was conducted in 97 patients suffering from HHCC. Demographic characteristics, oncology characteristics, and some serological markers were collected for analysis. The TGR was significantly linear and associated with the risk of death when applied to restricted cubic splines. The optimal cut-off value of TGR was -8.6%/month, and patients were divided into two groups according to TGR. Kaplan-Meier analysis showed that the high-TGR group had a poorer prognosis. TGR (hazard ratio (HR), 2.06; 95% confidence interval (CI), 1.23-3.43; p = 0.006), presence of portal vein tumor thrombus (PVTT) (HR, 1.93; 95% CI, 1.13-3.27; p = 0.016), and subsequent combination therapy (HR, 0.59; 95% CI, 0.35-0.99; p = 0.047) were independent predictors of OS in the multivariate analysis. The model with TGR was superior to the model without TGR in the DCA analysis. Patients who underwent subsequent combination therapy showed a longer survival in the high-TGR group. This study demonstrated that higher TGR was associated with a worse prognosis in patients with HHCC. These findings will distinguish patients who demand more personalized combination therapy and rigorous surveillance.

Identification of a Pyroptosis-Related Gene Signature for Predicting Overall Survival and Response to Immunotherapy in Hepatocellular Carcinoma.

Pyroptosis is a novel kind of cellular necrosis and shown to be involved in cancer progression. However, the diverse expression, prognosis and associations with immune status of pyroptosis-related genes in Hepatocellular carcinoma (HCC) have yet to be analyzed. Herein, the expression profiles and corresponding clinical characteristics of HCC samples were collected from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Then a pyroptosis-related gene signature was built by applying the least absolute shrinkage and selection operator (LASSO) Cox regression model from the TCGA cohort, while the GEO datasets were applied for verification. Twenty-four pyroptosis-related genes were found to be differentially expressed between HCC and normal samples. A five pyroptosis-related gene signature (GSDME, CASP8, SCAF11, NOD2, CASP6) was constructed according to LASSO Cox regression model. Patients in the low-risk group had better survival rates than those in the high-risk group. The risk score was proved to be an independent prognostic factor for overall survival (OS). The risk score correlated with immune infiltrations and immunotherapy responses. GSEA indicated that endocytosis, ubiquitin mediated proteolysis and regulation of autophagy were enriched in the high-risk group, while drug metabolism cytochrome P450 and tryptophan metabolism were enriched in the low-risk group. In conclusion, our pyroptosis-related gene signature can be used for survival prediction and may also predict the response of immunotherapy.

Multi-labelled proteins recognition for high-throughput microscopy images using deep convolutional neural networks.

BACKGROUND: Proteins are of extremely vital importance in the human body, and no movement or activity can be performed without proteins. Currently, microscopy imaging technologies developed rapidly are employed to observe proteins in various cells and tissues. In addition, due to the complex and crowded cellular environments as well as various types and sizes of proteins, a considerable number of protein images are generated every day and cannot be classified manually. Therefore, an automatic and accurate method should be designed to properly solve and analyse protein images with mixed patterns. RESULTS: In this paper, we first propose a novel customized architecture with adaptive concatenate pooling and "buffering" layers in the classifier part, which could make the networks more adaptive to training and testing datasets, and develop a novel hard sampler at the end of our network to effectively mine the samples from small classes. Furthermore, a new loss is presented to handle the label imbalance based on the effectiveness of samples. In addition, in our method, several novel and effective optimization strategies are adopted to solve the difficult training-time optimization problem and further increase the accuracy by post-processing. CONCLUSION: Our methods outperformed the SOTA method of multi-labelled protein classification on the HPA dataset, GapNet-PL, by above 2% in the F1 score. Therefore, experimental results based on the test set split from the Human Protein Atlas dataset show that our methods have good performance in automatically classifying multi-class and multi-labelled high-throughput microscopy protein images.