Indicator For Hepatocellular Carcinoma Research Articles

Deciphering the role of KLRB1: a novel prognostic indicator in hepatocellular carcinoma

BackgroundHepatocellular carcinoma (HCC) represents a significant global health challenge with high incidence and mortality rates. T cells and natural killer (NK) cells are pivotal in this context, yet HCC can evade immune surveillance. CD161 (KLRB1), a C-type lectin receptor, modulates immune responses and is expressed on NK cells and a subset of T cells. Its relevance in HCC remains poorly understood, with conflicting findings regarding its impact on patient prognosis.MethodsUtilizing TCGA data and single-cell analysis, we investigated the biological functions of KLRB1 in HCC. Peripheral blood samples from 126 HCC patients were collected to assess KLRB1 expression on NK and T cells. The diagnostic performance of KLRB1 on NK and CD8 + T cells was evaluated using receiver operating characteristic curve (ROC) analysis, while its prognostic significance was assessed using Kaplan-Meier analysis and COX regression models.ResultsAnalysis of TCGA data revealed a significant correlation between KLRB1 expression and immune activation, particularly T cell activation. Single-cell data further demonstrated elevated KLRB1 expression in tissue-resident NK and T cells within HCC, which co-expressed markers of immune activation. Clinical data showed downregulated KLRB1 expression on NK and T cells in HCC patients compared to health individuals, with lower expression levels correlating with poorer prognosis.ConclusionKLRB1 emerges as a promising biomarker in HCC, with its downregulation on peripheral blood NK and T cells suggesting potential prognostic value. Further elucidation of KLRB1’s role in HCC may pave the way for the development of targeted immunotherapies and the improvement of patient outcomes.

An integrated analysis of Dynamin 1 Like: A new potential prognostic indicator in hepatocellular carcinoma.

Dynamin 1 Like (DNM1L), a member of dynamin superfamily capable of mediating mitochondrial outer membrane division, plays a key role in the progression of different types of tumors. However, the prognostic value, clinical significance of DNM1L and its specific mechanism involved in tumorigenesis of hepatocellular carcinoma (HCC) have not been investigated clearly. In this study, we found that the expression of DNM1L were significantly higher in HCC tissues than adjacent/normal liver tissues based on multiple data sets obtained from TCGA, GEO and ONCOMINE database, also its protein expression form Drp1 is significantly higher in HCC tissues than adjacent tissues, and is related to the degree of differentiation. Kaplan-Meier curves suggested that high DNM1L expression prominently correlated with poorer overall survival, progression-free survival, relapse-free survival and disease-specific survival. Multivariate analysis showed that higher DNM1L expression was independent prognostic factors of shorter overall survival and disease-free survival. Kyoto Encyclopedia of Genes and Genomes and Gene set enrichment analysis analysis combined with validation experiments revealed the regulatory role of DNM1L on key molecules in the metabolism of xenobiotics by cytochrome p450 pathway, and DNM1L may also affects invasion and metastasis capability of HCC by mediating extracellular matrix-receptor interaction pathway. Moreover, analysis showed that higher DNM1L, CYP2C9, CYP3A4, CYP1A2 expression were associated with the resistance to sorafenib therapy. TIMER and CIBERSORT analysis indicated that the increase of DNM1L expression may affect the infiltration of immune cells in the tumor microenvironment. Taken together, the above results indicated that DNM1L could be able to serve as a promising independent predictor and therapeutic target for HCC patients.

Mitochondrial Lipid Metabolism Genes as Diagnostic and Prognostic Indicators in Hepatocellular Carcinoma.

Due to the heterogeneity of Hepatocellular carcinoma (HCC), there is an urgent need for reliable diagnosis and prognosis. Mitochondria-mediated abnormal lipid metabolism affects the occurrence and progression of HCC. This study aims to investigate the potential of mitochondrial lipid metabolism (MTLM) genes as diagnostic and independent prognostic biomarkers for HCC. MTLM genes were screened from the Gene Expression Omnibus (GEO) and Gene Set Enrichment Analysis (GSEA) databases, followed by an evaluation of their diagnostic values in both The Cancer Genome Atlas Program (TCGA) and the Affiliated Cancer Hospital of Guangxi Medical University (GXMU) cohort. The TCGA dataset was utilized to construct a gene signature and investigate the prognostic significance, immune infiltration, and copy number alterations. The validity of the prognostic signature was confirmed through GEO, International Cancer Genome Consortium (ICGC), and GXMU cohorts. The diagnostic receiver operating characteristic (ROC) curve revealed that eight MTLM genes have excellent diagnostic of HCC. A prognostic signature comprising 5 MTLM genes with robust predictive value was constructed using the lasso regression algorithm based on TCGA data. The results of the Stepwise regression model showed that the combination of signature and routine clinical parameters had a higher area under the curve (AUC) compared to a single risk score. Further, a nomogram was constructed to predict the survival probability of HCC, and the calibration curves demonstrated a perfect predictive ability. Finally, the risk score also unveiled the different immune and mutation statuses between the two different risk groups. MTLT-related genes may serve as diagnostic and prognostic biomarkers for HCC as well as novel therapeutic targets, which may be beneficial for facilitating further understanding the molecular pathogenesis and providing potential therapeutic strategies for HCC.

Gene-based cancer-testis antigens as prognostic indicators in hepatocellular carcinoma

Cancer/testis antigens (CTAs) are reproductive tissue-restricted genes, frequently ectopic expressed in tumors. CTA genes associate with a poor prognosis in some solid tumors, due to their potential roles in the tumorigenesis and progression. However, whether CTAs relate with hepatocellular carcinoma (HCC) remains unclear. In this study, the prognostic signatures based on CTA genes were investigated and validated in three cohorts including Chinese HCC patients with hepatitis B virus infection (CHCC-HBV), International Cancer Genome Consortium (ICGC) and The Cancer Genome Atlas (TCGA) cohorts. Univariate, LASSO, and multivariate Cox regression analyses were used to screen prognostic genes and develop the prognostic gene signature. A prognosis model was established with six CTA genes (SSX1, CTCFL, OIP5, CEP55, NOL4, and TPPP2) in CHCC-HBV cohort, and further validated in the ICGC and TCGA cohorts. The CTA signature was an essential prognostic predictor independent of other clinical pathological factors. High-risk group exhibited up-regulated cell cycle-related and tumor-related pathways and more M0 macrophage, activated mast cell, activated memory CD4+ T cell, and memory B cell infiltration. Furthermore, CTA signature correlated with the sensitivity to multiple chemotherapy drugs. Our results highlighted that the CTA gene profiling was a prognostic assessment tool for HCC patients.

Role of NCF2 as a potential prognostic factor and immune infiltration indicator in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the major causes of cancer-related deaths globally. The tumor microenvironment (TME) plays a crucial role in the prognosis and treatment of HCC. Hence, it is important to exploit new biomarkers for survival surveillance and TME estimation of HCC. HCC samples data was collected from The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) database, and clinical samples were collected from our center. The TME of HCC were explored with ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumor tissues using Expression data), ssGSEA (single sample Gene Sets Enrichment Analysis) and CIBERSORT algorithm. Differentially expressed genes were analyzed with functional enrichment analysis. Immunohistochemistry was implemented to validate the results. Based on TCGA database, we found that Neutrophil Cytosolic Factor 2 (NCF2) was significantly associated with the prognosis of HCC patients, involved in immune-related biological processes of HCC and closely associated with some types of immunocompetent cells. The survival analysis based on NCF2 expression assessed by immunohistochemistry also confirmed that NCF2-positive group had a shorter relapse free survival (RFS) and overall survival (OS) than NCF2-negative group. Multivariate Cox regression revealed NCF2 expression level and lymphovascular space invasion (LVSI) were independent risk factors for HCC patients. Receiver operating characteristic curves showed that the combination of NCF2 and LVSI had higher predictive efficacy on the 1-year RFS rate and 5-year OS rate than each of them alone. Besides, the expression level of NCF2 was positively associated with M0 and M2 macrophages infiltration. Furthermore, NCF2 expression was positively correlated with CSF1, IL4, IL10, CD206, CD163, CSF1R and TGFβ1. We proposed that higher NCF2 expression predicted an adverse prognosis and more M2 macrophages infiltration in HCC patients.

EVALUATION OF DIAGNOSTIC VALIDITY OF PIVKA-II FOR DIAGNOSIS OF HEPATOCELLULAR CARCINOMA IN PATIENTS OF CIRRHOSIS WITH LIVER NODULES PRESENTED IN A TERTIARY CARE HOSPITAL OF LAHORE

Objectives: To evaluate the diagnostic validity of PIVKA-II for Hepatocellular carcinoma in cirrhotic patients with uncertain liver nodules on Ultrasound.
 Methods: This was a cross-sectional study conducted in 01-11-2020 and 31-12-2021 at Hepatitis clinic at Jinnah Hospital Lahore. Patients who fulfilled the selection criteria(n=100) were enlisted for this study. Blood samples were obtained to test for PVKA-11 and AFP in cirrhotic patients who had liver nodules that had been previously verified by ultrasound imaging. Data were entered and analyzed in SPSS ver: 21.0. Sensitivity, specificity and predictive values were calculated using CT imaging and biopsy as gold standard. ROC curve evaluating AFP, PIVKA-II, and a combination as indicators for Hepatocellular carcinoma at 95% Confidence Interval was calculated with a p < .05 value was taken as statistical significant.
 Results: HCC was confirmed in 45 of the 100 instances, and it was invariably at an early or very early stage. At a threshold of 62.5 mAU/mL, PIVKA-II and HCC were significantly correlated (P =.015 and P =.036, respectively) in univariate and multivariate analyses. For AFP, 7.5 ng/mL was the ideal cut-off. For PIVKA- II, sensitivity was 62% and specificity was 91% , while for AFP, they are 66% and 69% respectively. The positive and negative predictive values for PIVKA-II were 81% and 74%, respectively, while for AFP sensitivity was 63% and specificity was 72%. The combination of both biomarkers improved the precision of diagnosing HCC (sensitivity = 74%, specificity = 95.5%, NPV = 81%, PPV = 92%, and AUC = 0.781).
 Conclusion: PIVKA-II is a valid indicator for defining the characteristics of liver nodules in cirrhosis and when combined with AFP, it signifies superior accuracy for HCC diagnosis.

Abstract 1721: Spatial distribution of immune cells as quantitative prognosis indicator in hepatocellular carcinoma

Abstract Background: We previously demonstrated that the analysis of the tumor microenvironment (TME) in histopathology images via tissue segmentation [1] and cell density in lymphocyte-rich area [2] impacts prognosis and treatment in hepatocellular carcinoma (HCC). Few biomarker models exist to prognosticate patients with HCC via the automated analysis of TME at the cellular level. Methods: Clinical outcomes data and histopathology images of 351 patients with HCC were obtained from TCGA. We advanced a deep learning-based algorithm to analyze the tumor volume and spatial distribution of nuclei in TME. This was based on combination of two models: the PAIP2019 dataset was used for DenseNet-based HCC segmentation, which showed the performance of 0.8582 on the F1-score metric [3]; HoverNet-based cell detection model, which showed the performance of 0.654 on the binary PQ metric, annotated lymphocytes, macrophages, and neutrophils on the MonuSac dataset [4]. Results: The HCC segmentation model divided the TME into tumoral, marginal, and peritumoral areas by image processing. The marginal and peritumoral areas were defined as inner 50 um area and outer 100 um area from the estimated tumoral boundary, respectively. The ratios of neutrophils, lymphocytes, macrophages to the total cell count on marginal and peritumoral areas were calculated through integration of HCC segmentation and cell detection models. The proportions of leukocytes were subjected into Cox proportional hazard analysis. The results of Cox proportional hazard analysis calculated the proportions of macrophages and lymphocytes to other cells in the TME. The macrophage proportion on the peritumoral area was a significant prognostic indicator showing Log(hazard ratio) (-2.42 ± 2.14, p=0.026). The lymphocyte proportion on both areas of the peritumor and margins showed significant Log(hazard ratio) (-1.70 ± 1.61, p=0.042). Conclusions: The retrospective analysis of the TME using deep learning-assisted algorithm combining tissue segmentation and cell detection models reveals that the ratio of lymphocytes and macrophages in the peri-tumoral areas of HCC TME significantly impact prognosis. Further analyses in the prospective studies may provide more information about cellular biomarkers. [1] Kim et al. Cancer Res 2020 (80) (16 Supp) 2631 [2] Park et al. Journal of Clinical Oncology 39, no. 15_suppl (May 20, 2021) 4107-4107 [3] Kim, Yoo Jung, Jang, Hyungjoon, Lee, Kyoungbun et al. Medical Image Analysis 67 (2021): 101854. [4] Verma, Ruchika. IEEE Transactions on Medical Imaging 39 (2020): 1380-1391. [5] Graham, Simon. Medical Image Analysis 58 (2019): 101563. Citation Format: Hongseok Lee, Kyungdoc Kim, Guhyun Kang, Kyu-Hwan Jung, Sunyoung S. Lee. Spatial distribution of immune cells as quantitative prognosis indicator in hepatocellular carcinoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2022; 2022 Apr 8-13. Philadelphia (PA): AACR; Cancer Res 2022;82(12_Suppl):Abstract nr 1721.

Downregulation of MARC2 Promotes Immune Escape and Is Associated With Immunosuppression of Hepatocellular Carcinoma.

The N-reductive enzyme system (NRES), composed of MARC1, MARC2, CYB5, and CYB5R, is responsible for the reduction of N-oxygenated compounds and participates in several physiological processes. For example, MARC2 serves as an important prognostic indicator and is downregulated in hepatocellular carcinoma, and the downregulation of MARC2 is critical to the regulation of lipid metabolism and cell cycle progression. However, the role of MARC2 in tumor immune microenvironment modification had not previously been investigated. In this study, we found that downregulation of MARC2 was associated with the differentiation of CD4+T cells into regulatory T cells (Tregs). Furthermore, restoring the expression of MARC2 could increase the expression of HLA-C and B2M via PPARA-related lipid metabolism signaling pathways, which could facilitate tumor antigen presentation to the tumor-infiltrating T cells. Additionally, MARC2 expression negatively correlated with several immune checkpoints. The immune checkpoint burden was generated based on 28 MARC2-related immune checkpoints. Patients with a higher immune checkpoint burden were predicted to have a poorer prognosis and a lower level of activated CD8+ T cells. The results showed that expression of the NRES is a prognostic indicator of hepatocellular carcinoma and MARC2 contributes significantly to predict the prognosis. Finally, loss of MARC2 in HCC patients was found to facilitate immune escape and was associated with immunosuppression.

The Prognostic Value of Combined Preoperative and Postoperative Inflammation Indicators in Hepatocellular Carcinoma after Partial Hepatectomy

Purpose: The current clinical stage of hepatocellular carcinoma (HCC) is insufficient to predict the prognosis. Previous studies have shown that various preoperative inflammation indicators can predict the prognosis of HCC, but the role of postoperative inflammation indicators remains unclear. The purpose of this study was to explore the prognostic value of postoperative inflammation indicators and establish a clinical prognostic model combining preoperative and postoperative inflammation indicators. Methods: 88 patients with primary HCC from Beijing Tsinghua ChangGung Hospital in the National Hepatobiliary Standard Database were included in the study. Preoperative and postoperative prognostic models were established based on preoperative clinicopathological features and combined with postoperative inflammation indicators. The prognostic value of the four models was evaluated by the area under the curve of time-dependent receiver operating characteristic curves (td-AUC). Results: Multivariate analysis of preoperative clinicopathological indicators found that preoperative alpha-fetoprotein (AFP), platelet-lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), Prognostic Nutritional Index (PNI), tumor number and microvascular invasion were independent prognostic factors for disease-free survival (DFS). Introducing the postoperative inflammatory indicators for multivariate analysis found that preoperative AFP, PLR, LMR, PNI and postoperative neutrophil-lymphocyte ratio (NLR) and PLR were independent prognostic factors for DFS and establish a postoperative model. The postoperative model had higher td-AUC values than the preoperative model, TNM stage, Barcelona Clinic Liver Cancer (BCLC) stage in 1-year (0.849 VS 0.826, 0.514 and 0.532), 2-year (0.809 VS 0.799, 0.513 and 0.527), and 3-year (0.784 VS 0.783, 0.509 and 0.529) after surgery. Conclusions: Postoperative inflammation indicators are valuable prognostic indicators, and the predictive performance of the combined model is better than preoperative stage, TNM stage and BCLC stage.

English

BACKGROUND The ratio between the serum neutrophil count and the serum lymphocyte count is termed as Neutrophil to Lymphocyte Ratio (NLR). It is considered to be an individualistic prognostic indicator in hepatocellular carcinoma, colorectal carcinoma and various ovarian tumours. We wanted to assess the Neutrophil‑to‑ Lymphocyte Ratio (NLR) in the head and neck cancer patients and compare it with those of normal subjects. METHODS This is a prospective study involving two cohorts i.e. 1) patients of head and neck cancers and 2) healthy normal subjects of the same age group. Total study duration was 3 years and the study sample included 49 patients and 49 healthy subjects. RESULTS Results of the present study showed that the Neutrophil-to-Lymphocyte Ratio (NLR) of histopathologically proven cases of Squamous Cell Carcinoma of the oral cavity (OSCC) showed a significantly higher median of 2.9 (p < 0.001) compared to the NLR in normal (control) individuals. CONCLUSIONS NLR may be helpful in identifying patients with adverse tumour biology as it is a feasible, cost-effective, and potential biomarker. KEYWORDS Neutrophil-to-Lymphocyte Ratio, Squamous Cell Carcinoma, Head and Neck, Malignancy

TP53 R249G/S mutation as an independent prognosis indicator in hepatocellular carcinoma.

e16622 Background: Many cancers could be driven by some specially mutations exampled as EGFR in lung cancer, influenced prognosis prominently. However, there were few related studies in liver cancer, although primary liver cancer was a common malignant tumor causing high morbidity and mortality. Methods: 97 patients diagnosed with primary hepatocellular carcinoma were enrolled in this study. Operative tissue samples were collected and analyzed using hybridization capture based NGS ERSeq method from all patients. Results: 1088 somatic mutations were identified in tissue samples. Targeted-capture sequencing of 1,021 genes that are frequently mutated in solid tumors revealed that the most frequently mutated genes were TP53 (59%), TERT (32%) and AXIN1 (19%). By using the least absolute shrinkage and selection operator (LASSO), the recurrence risks were constructed on the basis of five-gene mutations, AXIN1, CTNNB1, LRP1B, PDGFRA and TP53. The ROC curve was 0.813 and 0.882 in training and validation cohorts, respectively. TP53 R249G/S point mutation was predicted prognostic independently. Up to 60% TP53 R249S mutated patients occurred recurrence, while less than 30% TP53 R249 wildtype patients occurred recurrence ( P = 0.0002). Patients with R249G/S point mutation showed a worse prognosis. The median disease-free survival time was 8.0 VS 45.0 months in R249G/S mutated group (n = 79) and R249- wildtype (n = 18) group, respectively (Log-rank test, P = 0.0364). Conclusions: In various cancer types, TP53 has a broad-spectrum mutation, but only in hepatocellular carcinoma, TP53 mutations are highly concentrated at the R249 point, which was considered to be related to aflatoxin infection, and mutations at this site can significantly affect the prognosis of patients. The discovery of this target also provide clue for subsequent targeted treatment of liver cancer.

Prognostic Indicators in Hepatocellular Carcinoma (HCC) in a Moroccan Population

Prognostic Indicators in Hepatocellular Carcinoma (HCC) in a Moroccan Population

Prognostic ability of inflammation-based markers in radioembolization for hepatocellular carcinoma.

Aim:Inflammation-based markers, such as the neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR), have recently been used as prognostic indicators in hepatocellular carcinoma (HCC). We aimed to determine whether NLR and PLR may predict response to yttrium-90 transarterial radioembolization (TARE) as primary treatment for HCC.Methods:We performed a retrospective review of a prospectively collected database of HCC cases (1994–2019) and selected patients who received TARE as primary treatment (n = 42). Laboratory studies were used to calculate NLR and PLR. Response to TARE was determined using the modified response evaluation criteria in solid tumors (mRECIST). Patients were classified as non-responders (stable or progressive disease) or responders (partial or complete response) to treatment based on mRECIST.Results:Receiver operating characteristic curves identified a pre-treatment NLR cutoff of ≥ 2.83 and a pre-treatment PLR cutoff of ≥ 83 for predicting non-response to treatment. Pre-treatment NLR ≥ 2.83 was the only significant predictor of non-response to TARE in multivariate logistic regression analysis (odds ratio 7.83, P = 0.036). On time to progression analysis, both pre-treatment NLR ≥ 2.83 and pre-treatment PLR ≥ 83 were associated with a higher proportion of tumor progression at 6 months post-treatment (43.6% vs. 10.0%, P = 0.014, log-rank) and (38.6% vs. 0%, P = 0.010, log-rank), respectively.Conclusion:NLR confers prognostic value and may be superior to PLR in determining response to TARE as primary treatment for HCC. Future studies are necessary to validate these findings in a larger cohort.

Verification of inflammation-based prognostic marker as a prognostic indicator in hepatocellular carcinoma.

AimAlthough inflammation‐based markers in cancer have been used for prognostic prediction, the most useful marker for hepatocellular carcinoma (HCC) has not been established. We investigated the usefulness of various inflammation‐based markers in HCC patients after hepatectomy.MethodsA total of 478 patients who underwent initial hepatectomy for HCC from 2009 to 2015 and were diagnosed with pathological HCC were included in this retrospective study. Inflammation‐based markers consisted of the C‐reactive protein to albumin ratio (CAR), Glasgow prognostic score (GPS), neutrophil to lymphocyte ratio, lymphocyte to monocyte ratio, platelet to lymphocyte ratio and prognostic index. Univariate and multivariate analyses for overall survival (OS) and disease‐free survival (DFS) using the Cox proportional hazard model were carried out. Kaplan‐Meier analysis and log‐rank test were used for comparison of OS and DFS. To reduce influences of selection bias and confounders for stratifying CAR, clinicopathological characteristics of patients were balanced by propensity score matching.ResultsMultivariate analysis identified only high CAR (>0.027) as an indicator of poor OS, and high CAR and high GPS (1‐2) as indicators of poor DFS among inflammation‐based markers. After propensity score matching, 124 patients each with low CAR and high CAR were matched. High CAR was correlated with both poor OS and DFS.ConclusionC‐reactive protein to albumin ratio was the most valuable prognostic indicator after hepatectomy for HCC among inflammation‐based markers.

Overexpression of TONSL might be an independent unfavorable prognostic indicator in hepatocellular carcinoma

BackgroundTONSL has been suggested to function as an oncogene in lung, esophageal and cervical cancer. This study was aimed to identify the expression of TONSL and its role in hepatocellular carcinoma (HCC). MethodsBy data mining in the Cancer Genome Atlas (TCGA) and Human Protein Atlas (HPA) databases, the expression profile of TONSL, its clinical significance, the potential mechanisms of its dysregulation and its underlying biological function in HCC were investigated. ResultsTONSL was significantly upregulated in HCC tissues relative to normal liver tissues (P < 0.05). High TONSL expression was significantly correlated with advanced TNM stage, poorly differentiated tumors, vascular invasion, elevated serum alpha-fetoprotein expression and a worse prognosis (all P < 0.05). Multivariate analysis further confirmed that TONSL overexpression was an independent risk factor for poor overall survival (OS) and recurrence-free survival (RFS) in HCC (all P < 0.05). Additionally, 16% of HCC cases (n = 370) had TONSL DNA amplification. The total methylation level of TONSL was moderately and negatively correlated with its mRNA expression (P < 0.05). TONSL was predictively targeted by miR-133b, which was downregulated in HCC and negatively related to TONSL mRNA expression (all P < 0.05). Kaplan-Meier analyses demonstrated that low miR-133b expression was significantly associated with poor OS and RFS (all P < 0.05). Moreover, gene set enrichment analysis revealed that cases with TONSL overexpression were enriched in cell cycle regulation pathways (all P < 0.05). ConclusionsTONSL holds promise for serving as a prognostic biomarker for HCC. DNA amplification, hypomethylation and miR-133b downregulation could be the mechanisms associated with TONSL upregulation in HCC. TONSL might function as an oncogene via cell cycle regulation pathways in HCC.

Integrated analysis of competing endogenous RNA network revealing potential prognostic biomarkers of hepatocellular carcinoma.

Objective: The goal of our study is to identify a competing endogenous RNA (ceRNA) network using dysregulated RNAs between HCC tumors and the adjacent normal liver tissues from The Cancer Genome Atlas (TCGA) datasets, and to investigate underlying prognostic indicators in hepatocellular carcinoma (HCC) patients.Methods: All of the RNA- and miRNA-sequencing datasets of HCC were obtained from TCGA, and dysregulated RNAs between HCC tumors and the adjacent normal liver tissues were investigated by DESeq and edgeR algorithm. Survival analysis was used to confirm underlying prognostic indicators.Results: In the present study, we constructed a ceRNA network based on 16 differentially expressed genes (DEGs), 7 differentially expressed microRNAs and 34 differentially expressed long non-coding RNAs (DELs). Among these dysregulated RNAs, three DELs (AP002478.1, HTR2A-AS1, and ERVMER61-1) and six DEGs (enhancer of zeste homolog 2 [EZH2], kinesin family member 23 [KIF23], chromobox 2 [CBX2], centrosomal protein 55 [CEP55], cell division cycle 25A [CDC25A], and claspin [CLSPN]) were used for construct a prognostic signature for HCC overall survival (OS), and performed well in HCC OS (adjusted P<0.0001, adjusted hazard ratio = 2.761, 95% confidence interval = 1.838-4.147). Comprehensive survival analysis demonstrated that this prognostic signature may be act as an independent prognostic indicator of HCC OS. Functional assessment of these dysregulated DEGs in the ceRNA network and gene set enrichment of this prognostic signature suggest that both were enriched in the biological processes and pathways of the cell cycle, cell division and cell proliferation.Conclusions: Our current study constructed a ceRNA network for HCC, and developed a prognostic signature that may act as an independent indicator for HCC OS.

Resistive Part of Impedance as a Possible Indicator of Hepatocellular Carcinoma

In this work, the multi-frequency impedance both in normal and liver cancer tissues was studied. This was to investigate the feasibility to detect liver cancer by a low cost, easy to use, and a relatively non-invasive electrical impedance measure technique, and thus potentially improving liver cancer diagnosis. Hepatocellular carcinoma (HCC) was induced in male Wistar rats by the administration of diethylnitrosamine (DEN) during 16weeks. The electrical impedances at a frequency sweep of 10-100KHz in the whole body and 10-60KHz in the liver were taken at the end of the treatment. The electrical impedance showed that the real component values of the impedance change in HCC. In addition, we found that the imaginary component was not associated with HCC. Our results suggest that the electrical impedance may be used as a diagnostic HCC tool.

Small Nucleolar RNA Host Gene 18 Acts as a Tumor Suppressor and a Diagnostic Indicator in Hepatocellular Carcinoma.

Background:Noncoding RNAs are crucial regulators acting as either tumor suppressor genes or oncogenes in human cancer progression. The aberrant expression of noncoding RNAs has been confirmed in different kinds of cancers. Hepatocellular carcinoma is one of the most common malignant tumors worldwide, characterized by insidious onset, great malignancy, and high rates of recurrence and metastasis. Due to lack of early predictive markers, numerous patients are diagnosed in the late stages. As therapeutic options for advanced patients are quite limited, great efforts have been made to screen patients at early stages. A previous study reported that small nucleolar RNA host gene 18 played crucial role in glioma. However, its functions and roles in hepatocellular carcinoma are unknown.Purpose:To explore its functional role and diagnostic value in hepatocellular carcinoma, we investigated its expression level.Methods:We performed real-time quantitative polymerase chain reaction in tumor tissues and adjacent noncancerous tissues derived from patients with hepatocellular carcinoma as well as in plasma, including samples from the healthy control, patients with hepatitis B, cirrhosis, and hepatocellular carcinoma.Results:Small nucleolar RNA host gene 18 was downregulated in liver tissues compared to paired adjacent noncancerous tissues (P < .0001). Meanwhile, plasma small nucleolar RNA host gene 18 showed a relatively high sensitivity and specificity (75.61% and 73.49%) for distinguishing patients with hepatocellular carcinoma whose α-fetoprotein levels were below 200 ng/mL from the healthy controls.Conclusion:Our study suggested that small nucleolar RNA host gene 18 might act as a tumor suppressor gene in hepatocellular carcinoma and potentially a diagnostic indicator to distinguish hepatocellular carcinoma from the healthy control and cirrhosis.

Short-Term Outcomes following Hepatectomy in Elderly Patients with Hepatocellular Carcinoma: An Analysis of 10,805 Septuagenarians and 2,381 Octo- and Nonagenarians in Japan

Background: As the population is aging, the indication for hepatocellular carcinoma (HCC) resection in patients aged over 80 years will increase. Japan is facing the most aging society worldwide. We examined the safety of hepatectomy in octogenarians and nonagenarians using large-scale data from the Diagnosis Procedure Combination database, a national administrative database in Japan. Method: We conducted a survey to collect data for all inpatients from 2007 and 2012. We identified 27,094 patients who underwent hepatectomy for HCC. Patients' age was divided into the following five categories: ≤59, 60-69, 70-79, 80-84, and ≥85 years (n = 5,099, 8,809, 10,805, 2,011, and 370, respectively). The primary outcomes of hepatectomy were in-hospital death within 90 days and complications. Logistic regression analyses were performed to analyze the impact of age on the outcomes with the adjustment of other individual-level factors. Results: The mortality and morbidity rates were 2.6 and 23.4%, respectively. Compared with patients in their 70s, the mortality rate was significantly lower in patients aged ≤59 years (odds ratio [OR], 0.34; 95% confidence interval [CI], 0.26-0.45; p < 0.01) and in those in their 60s (OR, 0.63; 95% CI, 0.53-0.74; p < 0.01). However, no significant difference was observed in patients aged 80-84 years (OR, 1.03; 95% CI, 0.78-1.385; p = 0.844) and those aged ≥85 years (OR, 0.95; 95% CI, 0.50-1.79; p = 0.870). Based on the multivariate logistic regression analysis, age ≥70 years, male gender, low hospital volume, and surgical procedure were identified as independent predictors of mortality. Conclusions: The operative risk for hepatectomy gradually increases with age until patients are in their 70s, and it appears to reach a plateau among septuagenarian. Indeed, age over 70 years can also be a risk factor for HCC. By considering the aging risk, surgeons can attain good outcome after hepatectomy even in octo- and nonagenarian patients.

A new molecular mechanism underlying the EGCG-mediated autophagic modulation of AFP in HepG2 cells

Epigallocatechingallate (EGCG) is a major bioactive component of green tea and is associated with health benefits against multiple diseases including cancer. As an indicator of hepatocellular carcinoma (HCC), high levels of α-fetal protein (AFP) are related to malignant differentiation and poor prognosis of cancer cells. In this study, EGCG can effectively reduce AFP secretion and simultaneously induce AFP aggregation in human HCC HepG2 cells. EGCG-stimulated autophagy induces the degradation of AFP aggregates in HepG2 cells. Furthermore, we thoroughly studied the underlying molecular mechanisms behind EGCG-stimulated autophagy by using large-scale all-atom molecular dynamics simulations, which revealed a novel molecular mechanism. EGCG directly interacts with LC3-I protein, readily exposing the pivotal Gly-120 site of the latter to other important binding partners such as 1,2-distearoyl-sn-glycero-3-phosphoethanolamine and promoting the synthesis of LC3-II, a characteristic autophagosomal marker. Our results suggest that EGCG is critical in regulating AFP secretion and in modulating autophagic activities of HepG2 cells, providing a molecular basis for potentially preventing and treating HCC.