Integrating bioinformatics and machine learning methods to analyze diagnostic biomarkers for HBV-induced hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is a malignant tumor. It is estimated that approximately 50-80% of HCC cases worldwide are caused by hepatitis b virus (HBV) infection, and other pathogenic factors have been shown to promote the development of HCC when coexisting with HBV. Understanding the molecular mechanisms of HBV-induced hepatocellular carcinoma (HBV-HCC) is crucial for the prevention, diagnosis, and treatment of the disease. In this study, we analyzed the molecular mechanisms of HBV-induced HCC by combining bioinformatics and deep learning methods. Firstly, we collected a gene set related to HBV-HCC from the GEO database, performed differential analysis and WGCNA analysis to identify genes with abnormal expression in tumors and high relevance to tumors. We used three deep learning methods, Lasso, random forest, and SVM, to identify key genes RACGAP1, ECT2, and NDC80. By establishing a diagnostic model, we determined the accuracy of key genes in diagnosing HBV-HCC. In the training set, RACGAP1(AUC:0.976), ECT2(AUC:0.969), and NDC80 (AUC: 0.976) showed high accuracy. They also exhibited good accuracy in the validation set: RACGAP1(AUC:0.878), ECT2(AUC:0.731), and NDC80(AUC:0.915). The key genes were found to be highly expressed in liver cancer tissues compared to normal liver tissues, and survival analysis indicated that high expression of key genes was associated with poor prognosis in liver cancer patients. This suggests a close relationship between key genes RACGAP1, ECT2, and NDC80 and the occurrence and progression of HBV-HCC. Molecular docking results showed that the key genes could spontaneously bind to the anti-hepatocellular carcinoma drugs Lenvatinib, Regorafenib, and Sorafenib with strong binding activity. Therefore, ECT2, NDC80, and RACGAP1 may serve as potential biomarkers for the diagnosis of HBV-HCC and as targets for the development of targeted therapeutic drugs.

Etiology and Outcomes of Patients with Extreme Hyperbilirubinemia in Korea: A Retrospective Cohort Study.

Background/Aim: Extreme hyperbilirubinemia is occasionally observed in intensive care unit (ICU) and non-ICU settings. This study examined the etiologies of extreme hyperbilirubinemia (bilirubin level ≥12 mg/dL) and the factors associated with the 30-day mortality. Methods: This retrospective observational cohort study identified 439 patients with extreme hyperbilirubinemia at the Gyeongsang National University Changwon Hospital between 2016 and 2020. The patients were classified into three groups and 11 diseases according to their etiology. The risk factors associated with 30-day mortality at the baseline were investigated using the Cox proportional hazards model. Results: Of 439 patients with extreme hyperbilirubinemia, 287, 78, and 74 were in the liver cirrhosis/malignancy group, the ischemic injury group, and the benign hepatobiliary-pancreatic etiological group, respectively, with corresponding 30-day mortality rates of 42.9%, 76.9%, and 17.6%. The most common disease leading to hyperbilirubinemia was a pancreatobiliary malignancy (28.7%), followed by liver cirrhosis (17.3%), hepatocellular carcinoma (10.9%), and liver metastases (8.4%). The etiologies of hyperbilirubinemia, obstructive jaundice, infection, albumin level, creatinine level, and prothrombin time-international normalized ratio were independently associated with the 30-day mortality. Conclusions: This study suggests three etiologies of extreme hyperbilirubinemia in the ICU and non-ICU settings. The prognosis of patients with extreme hyperbilirubinemia depends largely on the etiology and the presence of obstructive jaundice.

Developing an advanced diagnostic model for hepatocellular carcinoma through multi-omics integration leveraging diverse cell-death patterns.

Introduction: Hepatocellular carcinoma (HCC), representing more than 80% of primary liver cancer cases, lacks satisfactory etiology and diagnostic methods. This study aimed to elucidate the role of programmed cell death-associated genes (CDRGs) in HCC by constructing a diagnostic model using single-cell RNA sequencing (scRNA-seq) and RNA sequencing (RNA-seq) data. Methods: Six categories of CDRGs, including apoptosis, necroptosis, autophagy, pyroptosis, ferroptosis, and cuproptosis, were collected. RNA-seq data from blood-derived exosomes were sourced from the exoRBase database, RNA-seq data from cancer tissues from the TCGA database, and scRNA-seq data from the GEO database. Subsequently, we intersected the differentially expressed genes (DEGs) of the HCC cohort from exoRBase and TCGA databases with CDRGs, as well as DEGs obtained from single-cell datasets. Candidate biomarker genes were then screened using clinical indicators and a machine learning approach, resulting in the construction of a seven-gene diagnostic model for HCC. Additionally, scRNA-seq and spatial transcriptome sequencing (stRNA-seq) data of HCC from the Mendeley data portal were used to investigate the underlying mechanisms of these seven key genes and their association with immune checkpoint blockade (ICB) therapy. Finally, we validated the expression of key molecules in tissues and blood-derived exosomes through quantitative Polymerase Chain Reaction (qPCR) and immunohistochemistry experiments. Results: Collectively, we obtained a total of 50 samples and 104,288 single cells. Following the meticulous screening, we established a seven-gene diagnostic model for HCC, demonstrating high diagnostic efficacy in both the exoRBase HCC cohort (training set: AUC = 1; testing set: AUC = 0.847) and TCGA HCC cohort (training set: AUC = 1; testing set: AUC = 0.976). Subsequent analysis revealed that HCC cluster 3 exhibited a higher stemness index and could serve as the starting point for the differentiation trajectory of HCC cells, also displaying more abundant interactions with other cell types in the microenvironment. Notably, key genes TRIB3 and NQO1 displayed elevated expression levels in HCC cells. Experimental validation further confirmed their elevated expression in both tumor tissues and blood-derived exosomes of cancer patients. Additionally, stRNA analysis not only substantiated these findings but also suggested that patients with high TRIB3 and NQO1 expression might respond more favorably to ICB therapy. Conclusions: The seven-gene diagnostic model demonstrated remarkable accuracy in HCC screening, with TRIB3 emerging as a promising diagnostic tool and therapeutic target for HCC.

Beyond pixels: Graph filtration learning unveils new dimensions in hepatocellular carcinoma imaging.

This editorial explores the emerging role of Graph Filtration Learning (GFL) in revolutionizing Hepatocellular carcinoma (HCC) imaging analysis. As traditional pixel-based methods reach their limits, GFL offers a novel approach to capture complex topological features in medical images. By representing imaging data as graphs and leveraging persistent homology, GFL unveils new dimensions of information that were previously inaccessible. This paradigm shift holds promise for enhancing HCC diagnosis, treatment planning, and prognostication. We discuss the principles of GFL, its potential applications in HCC imaging, and the challenges in translating this innovative technique into clinical practice.

Mitotic catastrophe heterogeneity: implications for prognosis and immunotherapy in hepatocellular carcinoma.

Background and aims: The mitotic catastrophe (MC) pathway plays an important role in hepatocellular carcinoma (HCC) progression and tumor microenvironment (TME) regulation. However, the mechanisms linking MC heterogeneity to immune evasion and treatment response remain unclear. Methods: Based on 94 previously published highly correlated genes for MC, HCC patients' data from the Cancer Genome Atlas (TCGA) and changes in immune signatures and prognostic stratification were studied. Time and spatial-specific differences for MCGs were assessed by single-cell RNA sequencing and spatial transcriptome (ST) analysis. Multiple external databases (GEO, ICGC) were employed to construct an MC-related riskscore model. Results: Identification of two MC-related subtypes in HCC patients from TCGA, with clear differences in immune signatures and prognostic risk stratification. Spatial mapping further associates low MC tumor regions with significant immune escape-related signaling. Nomogram combining MC riskscore and traditional indicators was validated great effect for early prediction of HCC patient outcomes. Conclusion: MC heterogeneity enables immune escape and therapy resistance in HCC. The MC gene signature serves as a reliable prognostic indicator for liver cancer. By revealing clear immune and spatial heterogeneity of HCC, our integrated approach provides contextual therapeutic strategies for optimal clinical decision-making.

CDKL3 is a promising biomarker for diagnosis and prognosis prediction in patients with hepatocellular carcinoma.

Cyclin-dependent kinase-like 3 (CDKL3) has been identified as an oncogene in certain types of tumors. Nonetheless, its function in hepatocellular carcinoma (HCC) is poorly understood. In this study, we conducted a comprehensive analysis of CDKL3 based on data from the HCC cohort of The Cancer Genome Atlas (TCGA). Our analysis included gene expression, diagnosis, prognosis, functional enrichment, tumor microenvironment and metabolic characteristics, tumor burden, mRNA expression-based stemness, alternative splicing, and prediction of therapy response. Additionally, we performed a cell counting kit-8 assay, TdT-mediated dUTP nick-end Labeling staining, migration assay, wound healing assay, colony formation assay, and nude mouse experiments to confirm the functional relevance of CDKL3 in HCC. Our findings showed that CDKL3 was significantly upregulated in HCC patients compared to controls. Various bioinformatic analyses suggested that CDKL3 could serve as a potential marker for HCC diagnosis and prognosis. Furthermore, CDKL3 was found to be involved in various mechanisms linked to the development of HCC, including copy number variation, tumor burden, genomic heterogeneity, cancer stemness, and alternative splicing of CDKL3. Notably, CDKL3 was also closely correlated with tumor immune cell infiltration and the expression of immune checkpoint markers. Additionally, CDKL3 was shown to independently function as a risk predictor for overall survival in HCC patients by multivariate Cox regression analysis. Furthermore, the knockdown of CDKL3 significantly inhibited cell proliferation in vitro and in vivo, indicating its role as an oncogene in HCC. Taken together, our findings suggest that CDKL3 shows promise as a biomarker for the detection and treatment outcome prediction of HCC patients.

Dual Enzyme-Locked Activation Reporter for Accurate Liver Cancer Surveillance.

Activatable probes with a higher signal-to-background ratio and accuracy are essential for monitoring liver cancer as well as intraoperative fluorescence navigation. However, the presence of only one biomarker is usually not sufficient to meet the high requirement of a signal-to-background ratio in cancer surveillance, leading to the risk of misdiagnosis. In this work, a dual-locked activation response probe, Si-NTR-LAP, for nitroreductase and leucine aminopeptidase was reported. This dual-locked probe provides better tumor recognition and a higher signal-to-noise ratio than that of single-locked probes (Si-LAP and Si-NTR). In both the subcutaneous tumor model and the more complex orthotopic hepatocellular carcinoma model, the probe was able to identify tumor tissue with high specificity and accurately differentiate the boundaries between tumor tissue and normal tissue. Therefore, the dual-locked probe may provide a new and practical strategy for applying to real patient tumor tissue samples.

Monocyte distribution width as a promising biomarker for differential diagnosis of chronic hepatitis, cirrhosis, and hepatocellular carcinoma.

Objective: We aimed to investigate the association and diagnostic value of monocyte distribution width (MDW) for chronic hepatitis B (CHB), liver cirrhosis (LC), and hepatocellular carcinoma (HCC). Methods: MDW levels were measured in 483 individuals (103 CHB, 77 LC, 153 HCC, and 150 controls). MDW was detected using UniCel Dx900 for specific cell volume parameters and the distribution of cell volumes. Results: Our findings revealed a dynamic upward change in MDW levels across different stages of chronic liver disease, from CHB to LC and HCC. In CHB, MDW levels were highest among HBeAg-positive CHB patients and exhibited a negative correlation with HBV markers while positively correlating with ALT levels. In LC, MDW showed a positive association with the pathological progression of LC, demonstrating consistency with CP scores. MDW proved to be equally effective as traditional detection for diagnosing LC. In HCC, MDW was positively correlated with HCC occurrence and development, with higher levels observed in the high MDW group, which also exhibited elevated AFP levels, MELD scores, and 90-day mortality rates. MDW surpassed predictive models in its effectiveness for diagnosing HCC, as well as CHB and LC, with respective areas under the curve of 0.882, 0.978, and 0.973. Furthermore, MDW emerged as an independent predictor of HCC. Conclusion: MDW holds significant diagnostic efficacy in identifying CHB, LC, and HCC. These findings suggest that MDW could serve as a promising biomarker for predicting the severity of liver diseases and aid in rational clinical treatment strategies.

Hepatocellular carcinoma outcomes and potential implications for surveillance in elderly patients.

International liver societies recommend hepatocellular carcinoma (HCC) surveillance for those at high-risk of developing HCC. While previous studies have shown the benefits of surveillance for middle-aged patients, but its necessity for elderly patients is unclear. This study aimed to assess the benefits of HCC surveillance in the elderly by comparing diagnosis mode of HCC. Consecutive, elderly patients aged 75 years or older who were newly diagnosed with HCC were screened at our institution between January 2009 and December 2021. Patients were grouped into those who were diagnosed with HCC during surveillance (n = 235, surveillance group) and those who were diagnosed with HCC due to symptoms (n = 184, symptomatic group). The study outcome was overall survival. It was compared in the overall cohort and a propensity score (PS)-matched cohort. Early-stage diagnosis was more frequent in the surveillance group than in the symptomatic group (mUICC stage I/II: 72.3% vs. 39.1%, p < 0.001). The overall survival rate was better in the surveillance group than in the symptomatic group (median 4.4 vs. 2.1 years, log-rank p < 0.001). In multivariable-adjusted models, the hazard ratio (HR) of mortality of the surveillance group compared to the symptomatic group was 0.64 (95% confidence interval (CI): 0.47-0.87). However, further adjustment for the tumor stage markedly attenuated this association, which was no longer statistically significant (adjusted HR = 0.75; 95% CI: 0.54-1.02). In the PS-matched cohort analysis, outcomes were similar when the PS matching variables included the tumor stage. In contrast, when PS matching variables did not include the tumor stage, outcomes were better for the surveillance group. The surveillance group of elderly patients showed better survival than the symptomatic group, which was largely explained by earlier tumor stage at diagnosis. This suggests that the overall outcome of elderly HCC patients could be improved by increasing surveillance-detected cases compared to symptom-driven cases.

Establishment of diagnostic model and identification of diagnostic markers between liver cancer and cirrhosis based on multi-chip and machine learning.

OBJECTIVE: Most cases of hepatocellular carcinoma (HCC) arise as a consequence of cirrhosis. In this study, our objective is to construct a comprehensive diagnostic model that investigates the diagnostic markers distinguishing between cirrhosis and HCC. METHODS: Based on multiple GEO datasets containing cirrhosis and HCC samples, we used lasso regression, random forest (RF)-recursive feature elimination (RFE) and receiver operator characteristic analysis to screen for characteristic genes. Subsequently, we integrated these genes into a multivariable logistic regression model and validated the linear prediction scores in both training and validation cohorts. The ssGSEA algorithm was used to estimate the fraction of infiltrating immune cells in the samples. Finally, molecular typing for patients with cirrhosis was performed using the CCP algorithm. RESULTS: The study identified 137 differentially expressed genes (DEGs) and selected five significant genes (CXCL14, CAP2, FCN2, CCBE1 and UBE2C) to construct a diagnostic model. In both the training and validation cohorts, the model exhibited an area under the curve (AUC) greater than 0.9 and a kappa value of approximately 0.9. Additionally, the calibration curve demonstrated excellent concordance between observed and predicted incidence rates. Comparatively, HCC displayed overall downregulation of infiltrating immune cells compared to cirrhosis. Notably, CCBE1 showed strong correlations with the tumour immune microenvironment as well as genes associated with cell death and cellular ageing processes. Furthermore, cirrhosis subtypes with high linear predictive scores were enriched in multiple cancer-related pathways. CONCLUSION: In conclusion, we successfully identified diagnostic markers distinguishing between cirrhosis and hepatocellular carcinoma and developed a novel diagnostic model for discriminating the two conditions. CCBE1 might exert a pivotal role in regulating the tumour microenvironment, cell death and senescence.

ACG Clinical Guideline: Focal Liver Lesions.

Focal liver lesions (FLLs) have become an increasingly common finding on abdominal imaging, especially asymptomatic and incidental liver lesions. Gastroenterologists and hepatologists often see these patients in consultation and make recommendations for management of multiple types of liver lesions, including hepatocellular adenoma, focal nodular hyperplasia, hemangioma, and hepatic cystic lesions including polycystic liver disease. Malignancy is important to consider in the differential diagnosis of FLLs, and healthcare providers must be familiar with the diagnosis and management of FLLs. This American College of Gastroenterology practice guideline uses the best evidence available to make diagnosis and management recommendations for the most common FLLs.

Misdiagnosis Based on Neoplastic Markers-Extremely High Alpha-Fetoprotein in Patients with Intrahepatic Cholangiocarcinoma with Literature Review of the Published Cases.

Background: Alpha-fetoprotein (AFP) and carbohydrate antigen 19-9 (CA 19-9) are two tumor markers that are widely used in the differential diagnosis in patients with primary liver tumors. Very high levels of AFP are sporadically observed in patients with intrahepatic cholangiocarcinoma (ICC) and may cause an incorrect initial diagnosis of hepatocellular carcinoma (HCC). Methods: Two cases of tumors in cirrhotic livers were described, in which the initial diagnosis, based on very high AFP levels (Patient I: 10,464 ng/mL, Patient II: 2212 ng/mL, reference range: ≤8.04 ng/mL) was HCC. In addition, the PubMed database was searched for cases of ICC with elevated AFP. Discussion: In both individuals, liver cirrhosis was diagnosed, but there was no typical rapid "washout" in the contrast-enhanced computed tomography. Based on the histological assessment of samples obtained in the core biopsies, the initially assumed diagnosis of HCC was changed to ICC in both cases. Only nine cases of patients with ICC and high AFP levels were found in the PubMed database. The AFP levels ranged from slightly elevated to over 16,000 ng/mL. Conclusions: A very high AFP level does not necessarily correlate with the presence of HCC. Therefore, the diagnosis has to be verified histologically, when the radiological imaging is uncertain in patients with liver cirrhosis.

Pink-on-pink: hepatocellular carcinoma metastatic to oncocytic carcinoma of the thyroid.

Hepatocellular carcinoma typically metastasizes within the liver and may involve extrahepatic sites such as the lungs, adrenal glands, and bones at advanced stages. However, hepatocellular carcinoma metastasis to the thyroid is very uncommon and tumor-to-tumor metastasis from a hepatocellular cancer to a thyroid neoplasm is extremely rare. In this report, we present a case of a 70-year-old man with a hepatocellular carcinoma metastasizing to oncocytic thyroid carcinoma, emphasizing the importance of clinical history and of a multidisciplinary approach, as well as the usefulness of site-specific immunohistochemical markers, in diagnosing and managing cases of Rosai's metastasis, especially when donor and recipient neoplasms share similar histologic features.

Exploring Glypican-3 as a Molecular Target in Hepatocellular Carcinoma: Perspectives on Diagnosis and Precision Immunotherapy Strategies.

Liver cancer, primarily hepatocellular carcinoma (HCC), is the second leading cause of cancer-related deaths globally. It is typically characterized by rapid progression, poor prognosis, and high mortality rates. Given these challenges, the search for molecular targets aiding early diagnosis and targeted therapy remains imperative. Glypican 3 (GPC3), a cell-surface glycoprotein, emerges as a promising candidate for addressing HCC Overexpressed in HCC tissues; GPC3 is a credible immunohistochemical marker for liver cancer diagnosis and a potential marker for liquid biopsy through soluble GPC3 in serum. Various immunotherapies targeting GPC3 have been developed, including vaccines, anti-GPC3 immunotoxins, and chimeric antigen receptor-modified cells. This review comprehensively covers the structure, physicochemical properties, biological functions, and clinical applications of GPC3. It explores diagnostic and treatment strategies centered around GPC3, offering hope for improved early detection and targeted therapies in the challenging landscape of HCC.

Diagnostic value of carbohydrate antigen 50 in biliary tract cancer: A large-scale multicenter study.

BACKGROUND: To date, carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) have been widely used for the screening, diagnosis and prediction of biliary tract cancer (BTC) patients. However, few studies with large sample sizes of carbohydrate antigen 50 (CA50) were reported in BTC patients. METHODS: A total of 1121 patients from the Liver Cancer Clin-Bio Databank of Anhui Hepatobiliary Surgery Union between January 2017 and December 2022 were included in this study (673 in the training cohort and 448 in the validation cohort): among them, 458 with BTC, 178 with hepatocellular carcinoma (HCC), 23 with combined hepatocellular-cholangiocarcinoma, and 462 with nontumor patients. Receiver operating characteristic (ROC) curves and decision curve analysis (DCA) were used to evaluate the diagnostic efficacy and clinical usefulness. RESULTS: ROC curves obtained by combining CA50, CA19-9, and AFP showed that the AUC value of the diagnostic MODEL 1 was 0.885 (95% CI 0.856-0.885, specificity 70.3%, and sensitivity 84.0%) in the training cohort and 0.879 (0.841-0.917, 76.7%, and 84.3%) in the validation cohort. In addition, comparing iCCA and HCC (235 in the training cohort, 157 in the validation cohort), the AUC values of the diagnostic MODEL 2 were 0.893 (95% CI 0.853-0.933, specificity 96%, and sensitivity 68.6%) in the training cohort and 0.872 (95% CI 0.818-0.927, 94.2%, and 64.6%) in the validation cohort. CONCLUSION: The model combining CA50, CA19-9, and AFP not only has good diagnostic value for BTC but also has good diagnostic value for distinguishing iCCA and HCC.

Comparison of the Ability of Gadobenate Dimeglumine and Gadolinium Ethoxybenzyl Dimeglumine to Display the major Features for Noninvasively Diagnosing Hepatocellular Carcinoma According to the LI-RADS 2018v.

OBJECTIVE: To compare the ability of gadolinium ethoxybenzyl dimeglumine (Gd-EOB-DTPA) and gadobenate dimeglumine (Gd-BOPTA) to display the 3 major features recommended by the Liver Imaging Reporting and Data System (LI-RADS 2018v) for diagnosing hepatocellular carcinoma (HCC). MATERIALS AND METHODS: In this retrospective study, we included 98 HCC lesions that were scanned with either Gd-EOB-DTPA-MR or Gd-BOPTA-M.For each lesion, we collected multiple variables, including size and enhancement pattern in the arterial phase (AP), portal venous phase (PVP), transitional phase (TP), delayed phase (DP), and hepatobiliary phase (HBP). The lesion-to-liver contrast (LLC) was measured and calculated for each phase and then compared between the 2 contrast agents. A P value < .05 was considered statistically significant. The display efficiency of the LLC between Gd-BOPTA and Gd-EOB-DTPA for HCC features was evaluated by receiver operating characteristic (ROC) curve analysis. RESULTS: Between Gd-BOPTA and Gd-EOB-DTPA, significant differences were observed regarding the display efficiency for capsule enhancement and the LLC in the AP/PVP/DP (P < .05), but there was no significant difference regarding the LLC in the TP/HBP. Both Gd-BOPTA and Gd-EOB-DTPA had good display efficiency in each phase (AUCmin > 0.750). When conducting a total evaluation of the combined data across the 5 phases, the display efficiency was excellent (AUC > 0.950). CONCLUSION: Gd-BOPTA and Gd-EOB-DTPA are liver-specific contrast agents widely used in clinical practice. They have their own characteristics in displaying the 3 main signs of HCC. For accurate noninvasive diagnosis, the choice of agent should be made according to the specific situation.

Anti-BIRC5 autoantibody serves as a valuable biomarker for diagnosing AFP-negative hepatocellular carcinoma.

Background: Autoantibodies targeting tumor-associated antigens (TAAbs) have emerged as promising biomarkers for early cancer detection. This research aimed to assess the diagnostic capacity of anti-BIRC5 autoantibody in detecting AFP-negative hepatocellular carcinoma (ANHCC). Methods: This research was carried out in three stages (discovery phase, validation phase, and evaluation phase) and included a total of 744 participants. Firstly, the anti-BIRC5 autoantibody was discovered using protein microarray, exhibiting a higher positive rate in ANHCC samples (ANHCCs) compared to normal control samples (NCs). Secondly, the anti-BIRC5 autoantibody was validated through enzyme-linked immunosorbent assay (ELISA) in 85 ANHCCs and 85 NCs from two clinical centers (Zhengzhou and Nanchang). Lastly, the diagnostic usefulness of the anti-BIRC5 autoantibody for hepatocellular carcinoma (HCC) was evaluated by ELISA in a cohort consisting of an additional 149 AFP-positive hepatocellular carcinoma samples (APHCCs), 95 ANHCCs and 244 NCs. The association of elevated autoantibody to high expression of BIRC5 in HCC was further explored by the database from prognosis, immune infiltration, DNA methylation, and gene mutation level. Results: In the validation phase, the area under the ROC curve (AUC) of anti-BIRC5 autoantibody to distinguish ANHCCs from NCs in Zhengzhou and Nanchang centers was 0.733 and 0.745, respectively. In the evaluation phase, the AUCs of anti-BIRC5 autoantibody for identifying ANHCCs and HCCs from NCs were 0.738 and 0.726, respectively. Furthermore, when combined with AFP, the AUC for identifying HCCs from NCs increased to 0.914 with a sensitivity of 77.5% and specificity of 91.8%. High expression of BIRC5 gene is not only correlated with poor prognosis of HCCs, but also significantly associated with infiltration of immune cells, DNA methylation, and gene mutation. Conclusion: The findings suggest that the anti-BIRC5 autoantibody could serve as a potential biomarker for ANHCC, in addition to its supplementary role alongside AFP in the diagnosis of HCC. Next, we can carry out specific verification and explore the function of anti-BIRC5 autoantibody in the occurrence and development of HCC.

PPIH acts as a potential predictive biomarker for patients with common solid tumors.

BACKGROUND: Our previous studies have indicated that mRNA and protein levels of PPIH are significantly upregulated in Hepatocellular Carcinoma (LIHC) and could act as predictive biomarkers for patients with LIHC. Nonetheless, the expression and implications of PPIH in the etiology and progression of common solid tumors have yet to be explored, including its potential as a serum tumor marker. METHODS: We employed bioinformatics analyses, augmented with clinical sample evaluations, to investigate the mRNA and protein expression and gene regulation networks of PPIH in various solid tumors. We also assessed the association between PPIH expression and overall survival (OS) in cancer patients using Kaplan-Meier analysis with TCGA database information. Furthermore, we evaluated the feasibility and diagnostic efficacy of PPIH as a serum marker by integrating serological studies with established clinical tumor markers. RESULTS: Through pan-cancer analysis, we found that the expression levels of PPIH mRNA in multiple tumors were significantly different from those in normal tissues. This study is the first to report that PPIH mRNA and protein levels are markedly elevated in LIHC, Colon adenocarcinoma (COAD), and Breast cancer (BC), and are associated with a worse prognosis in these cancer patients. Conversely, serum PPIH levels are decreased in patients with these tumors (LIHC, COAD, BC, gastric cancer), and when combined with traditional tumor markers, offer enhanced sensitivity and specificity for diagnosis. CONCLUSION: Our findings propose that PPIH may serve as a valuable predictive biomarker in tumor patients, and its secreted protein could be a potential serum marker, providing insights into the role of PPIH in cancer development and progression.

KLF15-activated MARCH2 boosts cell proliferation and epithelial-mesenchymal transition and presents diagnostic significance for hepatocellular carcinoma.

PURPOSE: Membrane associated ubiquitin ligase MARCH2 majorly involves in inflammation response and protein trafficking. However, its comprehensive role in hepatocellular carcinoma (HCC) is largely unknown. METHODS: Firstly, multiple bioinformatic analyses were applied to determine MARCH2 mRNA level, its expression comparison in diverse molecular and immune subtypes, and diagnostic value in HCC. Subsequently, RNA-seq, real-time quantitative PCR, immunohistochemistry and cell proliferation assay are used to explore the epithelial-mesenchymal transition (EMT) and proliferation by gene-silencing or overexpressing in cultured HCC cells or in vivo xenograft. Moreover, dual luciferase reporter assay and immunoblotting are delved into verify the transcription factor that activating MARCH2 promoter. RESULTS: Multiple bioinformatic analyses demonstrate that MARCH2 is upregulated in multiple cancer types and exhibits startling diagnostic value as well as distinct molecular and immune subtypes in HCC. RNA-seq analysis reveals MARCH2 may promote EMT, cell proliferation and migration in HepG2 cells. Furthermore, overexpression of MARCH2 triggers EMT and significantly enhances HCC cell migration, proliferation and colony formation in a ligase activity-dependent manner. Additionally, above observations are validated in the HepG2 mice xenografts. For up-stream mechanism, transcription factor KLF15 is highly expressed in HCC and activates MARCH2 expression. CONCLUSION: KLF15 activated MARCH2 triggers EMT and serves as a fascinating biomarker for precise diagnosis of HCC. Consequently, MARCH2 emerges as a promising candidate for target therapy in cancer management.

Nomogram and calculator for predicting the prognosis of patients with giant hepatocellular carcinoma.

OBJECTIVES: This study aimed to explore the factors affecting the overall survival (OS) of giant hepatocellular carcinoma (G-HCC) patients and establish a nomogram and an Internet-based OS calculator for evaluating the OS of G-HCC patients. RESEARCH DESIGN AND METHODS: A total of 2445 G-HCC patients were searched in the SEER database. The independent variables affecting OS of G-HCC patients were determined by univariate and multivariate analyses, and a nomogram and Internet-based OS calculator were established. The accuracy of the nomogram was evaluated by the C-index, the AUC curve, and calibration curve. RESULTS: Grade, surgery, radiotherapy, chemotherapy, T-staging, M-staging, AFP, and fibrosis were identified as independent variables affecting OS. These variables were included in the nomogram model and Internet-based OS calculator to evaluate OS in G-HCC patients. The C-indices and AUC of the nomogram are better than AJCC-staging system. Similarly, the calibration curves revealed that the actual survival was consistent with nomogram-based survival. CONCLUSION: The nomogram and Internet-based OS calculator are superior to the traditional AJCC-staging system in the reliability and convenience of prognosis assessment for G-HCC patients, which is more conducive for clinicians to predict the survival of G-HCC patients and make the best treatment strategy.