Normal Liver Tissue Samples Research Articles

CT radiomics based on different machine learning models for classifying gross tumor volume and normal liver tissue in hepatocellular carcinoma

Background & aimsThe present study utilized extracted computed tomography radiomics features to classify the gross tumor volume and normal liver tissue in hepatocellular carcinoma by mainstream machine learning methods, aiming to establish an automatic classification model.MethodsWe recruited 104 pathologically confirmed hepatocellular carcinoma patients for this study. GTV and normal liver tissue samples were manually segmented into regions of interest and randomly divided into five-fold cross-validation groups. Dimensionality reduction using LASSO regression. Radiomics models were constructed via logistic regression, support vector machine (SVM), random forest, Xgboost, and Adaboost algorithms. The diagnostic efficacy, discrimination, and calibration of algorithms were verified using area under the receiver operating characteristic curve (AUC) analyses and calibration plot comparison.ResultsSeven screened radiomics features excelled at distinguishing the gross tumor area. The Xgboost machine learning algorithm had the best discrimination and comprehensive diagnostic performance with an AUC of 0.9975 [95% confidence interval (CI): 0.9973–0.9978] and mean MCC of 0.9369. SVM had the second best discrimination and diagnostic performance with an AUC of 0.9846 (95% CI: 0.9835– 0.9857), mean Matthews correlation coefficient (MCC)of 0.9105, and a better calibration. All other algorithms showed an excellent ability to distinguish between gross tumor area and normal liver tissue (mean AUC 0.9825, 0.9861,0.9727,0.9644 for Adaboost, random forest, logistic regression, naivem Bayes algorithm respectively).ConclusionCT radiomics based on machine learning algorithms can accurately classify GTV and normal liver tissue, while the Xgboost and SVM algorithms served as the best complementary algorithms.

DNA methylation alterations of ADCY5, MICAL2, and PLEKHG2 during the developmental stage of cryptogenic hepatocellular carcinoma.

The aim of this study was to clarify the significance of DNA methylation alterations of cryptogenic hepatocellular carcinomas (HCCs). Using the Infinium assay, we performed genome-wide DNA methylation analysis of 250 liver tissue samples, including noncancerous liver tissue (U-N) and corresponding cancerous tissue (U-T) from patients with cryptogenic HCC without a history of excessive alcohol use and hepatitis virus infection, and whose U-N samples showed no remarkable histological features (no microscopic evidence of simple steatosis, any form of hepatitis including nonalcoholic steatohepatitis, or liver cirrhosis). We identified 3272 probes that showed significant differences of DNA methylation levels between U-N and normal liver tissue samples from patients without HCC, indicating that a distinct DNA methylation profile had already been established at the precancerous U-N stage. U-Ns have a DNA methylation profile differing from that of noncancerous liver tissue of patients with nonalcoholic steatohepatitis-related, viral hepatitis-related, and alcoholic liver disease-related HCCs. Such DNA methylation alterations in U-Ns were inherited by U-Ts. The U-Ns showed DNA methylation alteration of ADCY5, resulting in alteration of its mRNA expression, whereas noncancerous liver tissue of patients with nonalcoholic steatohepatitis-, viral hepatitis-, or alcoholic liver disease-related HCCs did not. DNA methylation levels of MICAL2 and PLEKHG2 in U-Ts were correlated with larger tumor diameter and portal vein involvement, respectively. U-N-specific DNA hypermethylation of ADCY5 may have significance, even from the precancerous stage in liver showing no remarkable histological features. DNA hypomethylation of MICAL2 and PLEKHG2 may determine the clinicopathological features of cryptogenic HCC.

METTL3-Mediated STING Upregulation and Activation in Kupffer Cells Contribute to Radiation-Induced Liver Disease via Pyroptosis

Purpose: Radiation therapy is a vital adjuvant treatment for liver cancer, although the challenge of radiation-induced liver diseases (RILDs) limits its implementation. Kupffer cells (KCs) are a crucial cell population of the hepatic immune system and their biological function can be modulated by multiple epigenetic RNA modifications, including N6-methyladenosine (m6A) methylation. However, the mechanism for m6A methylation in KC-induced inflammatory response in RILD remains unclear. The present study investigated the function of m6A modification in KCs contributing to RILD. Methods and Materials: Methylated RNA-immunoprecipitation sequencing (MeRIP-seq) and RNA transcriptome sequencing were used to explore the m6A methylation profile of primary KCs isolated from mice after irradiation with 3 × 8 Gy. Western blotting and quantitative real-time polymerase chain reaction were used to evaluate gene expression. DNA pull-down and CHIP assays were performed to verify target gene binding and identify binding site. Results: MeRIP-seq revealed a significantly increased m6A modification level in human KCs after irradiation, suggesting the potential role of upregulated m6A in RILD. In addition, the study results corroborated that methyltransferase-like 3 (METTL3) acts as a main modulator to promote the methylation and gene expression of TEAD1, leading to STING-NLRP3 signaling activation. Importantly, it was shown that IGF2BP2 functions as an m6A “reader” to recognize methylated TEAD1 mRNA and promote its stability. METTL3/TEAD1 knockdown abolished the activation of STING-NLRP3 signaling and protected against RILD in addition to suppressing inflammatory cytokines and hepatocyte apoptosis. Moreover, clinically collected human normal liver tissue samples post-irradiation showed increased expression of STING and IL-1β in KCs compared to the non-irradiation group. Notably, STING pharmacological inhibition alleviated irradiation-induced liver injury in mice, indicating its potential therapeutic role in RILD. Conclusions: The results of our study reveal that TEAD1-STING-NLRP3 signaling activation contributes to RILD via METTL3-dependent m6A modification.

Constitutive photomorphogenic protein 1 ubiquitinates interleukin-1 receptor accessory protein in human liver cancer.

Constitutive photomorphogenic protein 1 (COP1) plays a pivotal role in the development and progression of several human cancers and is reported to be upregulated in liver cancer. However, the role of COP1 in human liver cancer is unclear. We analyzed the COP1 expression in normal liver and liver cancer tissue samples using western blot and immunohistochemical analysis. We overexpressed and silenced COP1 in HepG2 and Huh7 cells and analyzed the effect on liver cancer cell proliferation. Additionally, COP1 was used as a bait to screen COP1-interacting proteins in a human cDNA library in a yeast two-hybrid screen and the results were confirmed with co-immunoprecipitation (co-IP) assays. Moreover, immunofluorescence staining was performed to assess co-localization. The protein levels of COP1 and mIL1RAcP were determined in clinical samples. COP1 was upregulated in liver cancer samples compared to that in normal tissue samples. COP1 overexpression promoted proliferation of liver cancer cells, while COP1 knockdown exerted the opposite effect. Yeast two-hybrid screen identified interleukin-1 receptor accessory protein (IL1RAP) as a potential COP1-interacting protein. Co-IP assays further confirmed that COP1 interacts with both preIL1RAP and membrane-bound form of IL1RAP (mIL1RAP). Furthermore, COP1 upregulated mIL1RAP protein levels and promoted nuclear translocation and activation of the nuclear factor kappa B (NF-κB) (p50/p65) dimer. Additionally, we demonstrated that COP1 regulated mIL1RAP expression through K63-linked polyubiquitination, suggesting that COP1 plays a role in stabilizing mIL1RAP. Finally, the protein levels of COP1 and mIL1RAcP were found to be positively correlated in clinical samples. COP1 regulates IL1RAP, which in turn results in activation of the NF-κB signaling. Our findings suggest that the COP1/IL1RAP/NF-κB axis promotes proliferation of liver cancer cells and is a potential target for the treatment of liver cancer.

Long non-coding RNAs CCAT1 and CCAT2 in colorectal liver metastases are tumor-suppressive via MYC interaction and might predict patient outcomes.

Liver metastases severely reduce the long term survival of colorectal cancer patients. Long non-coding RNAs (lncRNAs) CCAT1 and CCAT2 have previously been found to be associated with impaired patient outcomes in primary colorectal cancer. We aimed to elucidate the role of CCAT1 and CCAT2 in colorectal liver metastases. Total RNA was isolated from 97 human tissue samples of colorectal liver metastases and adjacent normal liver tissue. Gene expression analysis was performed by RT-qPCR and Multiplex ELISA and correlated with patient characteristics and survival. Gene expression, cancer cell migration, invasion, and proliferation were studied after siRNA-mediated knockdown of CCAT1, CCAT2, and MYC in metastatic colorectal cancer cell lines Colo205 and HROC277Met2. Elevated expression levels of lncRNAs CCAT1 and CCAT2, and their common target MYC in colorectal liver metastases were associated with prolonged progression-free survival after liver resection. High expression of CCAT1 was likewise associated with prolonged overall survival. Knockdown of CCAT1, CCAT2, and MYC resulted in increased migratory and invasive potential in metastatic colorectal cancer cell lines. Gene expression analysis revealed alterations in constituents of Wnt signaling following knockdown. Our findings demonstrate tumor-suppressive functions of lncRNAs CCAT1 and CCAT2 in colorectal liver metastases. They suppress Wnt signaling directly and indirectly through target gene MYC and might prevent further metastatic spread from colorectal liver metastases.

A TNFα/Miz1-positive feedback loop inhibits mitophagy in hepatocytes and propagates non-alcoholic steatohepatitis

Non-alcoholic steatohepatitis (NASH) is a chronic inflammatory disease that can further progress to cirrhosis and hepatocellular carcinoma. However, the key molecular mechanisms behind this process have not been clarified. We analyzed human NASH and normal liver tissue samples by RNA-sequencing and liquid chromatography-mass spectrometry, identifying hepatocyte cytosolic protein Myc-interacting zinc-finger protein 1 (Miz1) as a potential target in NASH progression. We established a Western diet+fructose-induced NASH model in hepatocyte-specific Miz1 knockout and adeno-associated virus type 8-overexpressing mice. Human NASH liver organoids were used to confirm the mechanism, and immunoprecipitation and mass spectrometry were used to detect proteins that could interact with Miz1. We demonstrate that Miz1 is reduced in hepatocytes in human NASH. Miz1 is shown to bind to peroxiredoxin 6 (PRDX6), retaining it in the cytosol, blocking its interaction with mitochondrial Parkin at Cys431, and inhibiting Parkin-mediated mitophagy. In NASH livers, loss of hepatocyte Miz1 results in PRDX6-mediated inhibition of mitophagy, increased dysfunctional mitochondria in hepatocytes, and production of proinflammatory cytokines, including TNFα, by hepatic macrophages. Crucially, the increased production of TNFα results in a further reduction in hepatocyte Miz1 by E3-ubiquitination. This produces a positive feedback loop of TNFα-mediated hepatocyte Miz1 degradation, resulting in PRDX6-mediated inhibition of hepatocyte mitophagy, with the accumulation of dysfunctional mitochondria in hepatocytes and increased macrophage TNFα production. Our study identified hepatocyte Miz1 as a suppressor of NASH progression via its role in mitophagy; we also identified a positive feedback loop by which TNFα production induces degradation of cytosolic Miz1, which inhibits mitophagy and thus leads to increased macrophage TNFα production. Interruption of this positive feedback loop could be a strategy to inhibit the progression of NASH. Non-alcoholic steatohepatitis (NASH) is a chronic inflammatory disease that can further develop into cirrhosis and hepatocellular carcinoma. However, the key molecular mechanism of this process has not been fully clarified. Herein, we identified a positive feedback loop of macrophage TNFα-mediated hepatocyte Miz1 degradation, resulting in PRDX6-mediated inhibition of hepatocyte mitophagy, aggravation of mitochondrial damage and increased macrophage TNFα production. Our findings not only provide mechanistic insight into NASH progression but also provide potential therapeutic targets for patients with NASH. Our human NASH liver organoid culture is therefore a useful platform for exploring treatment strategies for NASH development.

Autofluorescence-Raman Spectroscopy for Ex Vivo Mapping Colorectal Liver Metastases and Liver Tissue

IntroductionIdentifying colorectal liver metastases (CRLM) during liver resection could assist in achieving clear surgical margins, which is an important prognostic variable for both disease-free and overall survival. The aim of this study was to investigate the effect of auto-fluorescence (AF) and Raman spectroscopy for ex vivo label-free discrimination of CRLMs from normal liver tissue. Secondary aims include exploring options for multimodal AF-Raman integration with respect to diagnosis accuracy and imaging speed on human liver tissue and CRLM. MethodsLiver samples were obtained from patients undergoing liver surgery for CRLM who provided informed consent (15 patients were recruited). AF and Raman spectroscopy was performed on CRLM and normal liver tissue samples and then compared to histology. ResultsAF emission spectra demonstrated that the 671 nm and 775/785 nm excitation wavelengths provided the highest contrast, as normal liver tissue elicited on average around eight-fold higher AF intensity compared to CRLM. The use of the 785 nm wavelength had the advantage of enabling Raman spectroscopy measurements from CRLM regions, allowing discrimination of CRLM from regions of normal liver tissue eliciting unusual low AF intensity, preventing misclassification. Proof-of-concept experiments using small pieces of CRLM samples covered by large normal liver tissue demonstrated the feasibility of a dual-modality AF-Raman for detection of positive margins within few minutes. ConclusionsAF imaging and Raman spectroscopy can discriminate CRLM from normal liver tissue in an ex vivo setting. These results suggest the potential for developing integrated multimodal AF-Raman imaging techniques for intraoperative assessment of surgical margins.

A Framework for Harmonization of Radiomics Data for Multicenter Studies and Clinical Trials

Variability in computed tomography images intrinsic to individual scanners limits the application of radiomics in clinical and research settings. The development of reproducible and generalizable radiomics-based models to assess lesions requires harmonization of data. The purpose of this study was to develop, test, and analyze the efficacy of a radiomics data harmonization model. Radiomic features from biopsy-proven untreated hepatic metastasis (N = 380) acquired from 167 unique patients with pancreatic, colon, and breast cancers were analyzed. Radiomic features from volume-match 551 samples of normal liver tissue and 188 hepatic cysts were included as references. A novel linear mixed effect model was used to identify effects associated with lesion size, tissue type, and scanner model. Six separate machine learning models were then used to test the effectiveness of radiomic feature harmonization using multivariate analysis. Proposed model identifies and removes scanner-associated effects while preserving cancer-specific functional dependence of radiomic features on the tumor size. Data harmonization improves the performance of classification models by reducing the scanner-associated variability. For example, the multiclass logistic regression model, LogitBoost, demonstrated the improvement in sensitivity in the range from 15% to 40% for each type of liver metastasis, whereas the overall model accuracy and the kappa coefficient increased by 5% and 8% accordingly. The model removed scanner-associated effects while preserving cancer-specific functional dependence of radiomic features.

CircPAK1 promotes the progression of hepatocellular carcinoma via modulation of YAP nucleus localization by interacting with 14-3-3ζ

BackgroundCircular RNA (circRNA), a new class of non-coding RNA, has obvious correlations with the occurrence and development of many diseases, including tumors. This study aimed to investigate the potential roles of circPAK1 in hepatocellular carcinoma (HCC).MethodsHigh-throughput sequencing was performed on 3 pairs of HCC and matched normal tissues to determine the upregulated circRNAs. The expression level of circPAK1 was detected by qRT-PCR in HCC and paired with normal liver tissue samples. The effects of circPAK1 on proliferation, invasion, metastasis and apoptosis of HCC cells were evaluated by in vitro and in vivo experiments. We also constructed Chitosan/si-circPAK1 (CS/si-circPAK1) nanocomplexes using Chitosan material to evaluate its in vivo therapeutic effect on HCC. High-throughput sequencing, RNA-sequencing, RNA probe pull-down, RNA immunoprecipitation and Co-Immunoprecipitation assays were performed to explore the relationship between circPAK1, 14–3-3ζ, p-LATS1 and YAP. Exosomes isolated from lenvatinib-resistant HCC cell lines were used to evaluate the relationship between exosomal circPAK1 and lenvatinib resistance.ResultsCircPAK1, a novel circRNA, is highly expressed in HCC tumor tissues and cell lines as well as correlated with poor outcomes in HCC patients. Functionally, circPAK1 knockdown inhibited HCC cell proliferation, migration, invasion and angiogenesis while circPAK1 overexpression promoted HCC progression. The tumor-promoting phenotypes of circPAK1 on HCC were also confirmed by animal experiments. Importantly, the application of CS/si-circPAK1 nanocomplexes showed a better therapeutic effect on tumor growth and metastasis. Mechanistically, circPAK1 enhanced HCC progression by inactivating the Hippo signaling pathway, and this kind of inactivation is based on its competitively binding of 14–3-3 ζ with YAP, which weakens the recruitment and cytoplasmic fixation of 14–3-3 ζ to YAP, thus promoting YAP nucleus localization. Additionally, circPAK1 could be transported by exosomes from lenvatinib-resistant cells to sensitive cells and induce lenvatinib resistance of receipt cells.ConclusionCircPAK1 exerts its oncogenic function by competitively binding 14–3-3 ζ with YAP, thus promoting YAP nucleus localization, leading to the inactivation of a Hippo signaling pathway. Exosomal circPAK1 may drive resistance to lenvatinib, providing a potential therapeutic target for HCC patients.

Identification of Prognostic Factors in Cholangiocarcinoma Based on Integrated ceRNA Network Analysis.

This study is aimed at screening prognostic biomarkers in cholangiocarcinoma (CHOL) based on competitive endogenous RNA (ceRNA) regulatory network analysis. Microarray data for lncRNAs, mRNA, and miRNAs were downloaded from the GEO and TCGA databases. Differentially expressed RNAs (DERs) were identified in CHOL and normal liver tissue samples. WGCNA was used to identify disease-related gene modules. By integrating the information from the starBase and DIANA-LncBasev2 databases, we constructed a ceRNA network. Survival analysis was performed, and a prognostic gene-based prognostic score (PS) model was generated. The correlation between gene expression and immune cell infiltration or immune-related feature genes was analyzed using TIMER. Finally, real-time quantitative PCR (RT-qPCR) was used to verify the expression of the 10 DERs with independent prognosis. A large cohort of DERs was identified in the CHOL and control samples. The ceRNA network consisted of 6 lncRNAs, 2 miRNAs, 90 mRNAs, and 98 nodes. Ten genes were identified as prognosis-related genes, and a ten-gene signature PS model was constructed, which exhibited a good prognosis predictive ability for risk assessment of CHOL patients (AUC value = 0.975). Four genes, ELF4, AGXT, ABCG2, and LDHD, were associated with immune cell infiltration and closely correlated with immune-related feature genes (CD14, CD163, CD33, etc.) in CHOL. Additionally, the consistency rate of the RT-qPCR results and bioinformatics analysis was 80%, implying a relatively high reliability of the bioinformatic analysis results. Our findings suggest that the ten-signature gene PS model has significant prognostic predictive value for patients with CHOL. These four immune-related DERs are involved in the progression of CHOL and may be useful prognostic biomarkers for CHOLs.

A cohesin-associated gene score may predict immune checkpoint blockade in hepatocellular carcinoma.

Stromal antigen 1 (STAG1), a component of cohesion, is overexpressed in various cancers, but it is unclear whether it has a role in the transcriptional regulation of hepatocellular carcinoma (HCC). To test this hypothesis, here, we screened global HCC datasets and performed multiscale embedded gene co‐expression network analysis to identify the potential functional modules of differentially expressed STAG1 co‐expressed genes. The putative transcriptional targets of STAG1 were identified using chromatin immunoprecipitation followed by high‐throughput DNA sequencing. The cohesin‐associated gene score (CAGS) was quantified using the The Cancer Genome Atlas HCC cohort and single‐sample gene set enrichment analysis. Distinct cohesin‐associated gene patterns were identified by calculating the euclidean distance of each patient. We assessed the potential ability of the CAGS in predicting immune checkpoint blockade (ICB) treatment response using IMvigor210 and GSE78220 cohorts. STAG1 was upregulated in 3313 HCC tissue samples compared with 2692 normal liver tissue samples (standard mean difference = 0.54). A total of three cohesin‐associated gene patterns were identified, where cluster 2 had a high TP53 mutated rate and a poor survival outcome. Low CAGS predicted a significant survival advantage but presaged poor immunotherapy response. Differentially expressed STAG1 co‐expression genes were enriched in the mitotic cell cycle, lymphocyte activation, and blood vessel development. PDS5A and PDGFRA were predicted as the downstream transcriptional targets of STAG1. In summary, STAG1 is significantly upregulated in global HCC tissue samples and may participate in blood vessel development and the mitotic cell cycle. A cohesin‐associated gene scoring system may have potential to predict the ICB response.

Abstract 5703: Quantification of DNA methylation for carcinogenic risk estimation in patients with non-alcoholic steatohepatitis

Abstract Background: In recent years, non-alcoholic steatohepatitis (NASH) has become the main cause of hepatocellular carcinoma (HCC). As a means of improving the treatment of NASH-related HCCs based on early detection, this study investigated the feasibility of carcinogenic risk estimation in patients with NASH. Results: Normal liver tissue (NLT), non-cancerous liver tissue (N) showing histological findings compatible with non-alcoholic fatty liver (NAFL) from patients without HCC (NAFL-O), N showing NASH from patients without HCC (NASH-O), N showing NAFL from patients with HCC (NAFL-W), N showing NASH from patients with HCC (NASH-W) and NASH-related HCC (T) were analyzed. An initial cohort of 171 tissue samples and a validation cohort of 55 tissue samples (226 samples in total) were used. Genome-wide DNA methylation screening using the Infinium HumanMethylation450 BeadChip and DNA methylation quantification using high-performance liquid chromatography (HPLC) with a newly developed anion-exchange column were performed. Based on the Infinium assay, 4,050 CpG sites showed significant alterations of DNA methylation in 22 NASH-W samples relative to 36 NLT samples in the initial cohort, indicating that DNA methylation alterations had occurred in the NASH-W samples. On 3,234 of the 4,050 CpG sites, DNA methylation alterations in NASH-W samples relative to NLT samples were inherited by or strengthened in 22 T samples (Jonckheere-Terpstra trend test). Among the 3,234 CpG sites, receiver operating characteristic curve analysis identified 415 CpG sites discriminating NASH-W from NLT samples with area under the curve values of more than 0.95. Among the 415 CpG sites, we focused on 21 CpG sites showing more than 85% specificity, even for discrimination of NASH-W from 91 NASH-O samples. The DNA methylation status of these 21 CpG sites was able to predict the coincidence of HCC independently from histopathological findings such as ballooning and fibrosis stage (Brunt classification). The methylation status of 5 candidate marker CpG sites was assessed using a HPLC-based system, which will be easily introduced into clinical laboratories, and for 3 of them sufficient sensitivity and specificity was successfully validated in the validation cohort. By combining these 3 CpG sites including the ZC3H3 gene, of which expression alternation may affect the post-transcriptional regulation of various tumor-related genes, 10 NAFL-W and 11 NASH-W samples from which HCCs had already arisen were confirmed to show carcinogenic risk with 95% sensitivity in the validation cohort. Conclusions: After a further prospective validation study using a larger cohort, carcinogenic risk estimation in liver biopsy specimens of patients with NASH may become clinically applicable using this HPLC-based system for quantification of DNA methylation. Citation Format: Junko Kuramoto, Eri Arai, Mao Fujimoto, Ying Tian, Yuriko Yamada, Takuya Yotani, Satomi Makiuchi, Noboru Tsuda, Hidenori Ojima, Moto Fukai, Yosuke Seki, Kazunori Kasama, Nobuaki Funahashi, Haruhide Udagawa, Takao Nammo, Kazuki Yasuda, Akinobu Taketomi, Tatsuya Kanto, Yae Kanai. Quantification of DNA methylation for carcinogenic risk estimation in patients with non-alcoholic steatohepatitis [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 5703.

Key genes in the liver fibrosis process are mined based on single-cell transcriptomics

At present, there is no effective treatment for liver fibrosis, and treatment options are limited. Liver fibrosis remains a cancer with a high mortality rate. During liver injury, hepatic stellate cells transdifferentiate into myofibroblasts capable of proliferation, migration, and invasion. The transcriptomes of more than 60,000 human single cells were analyzed in 9 cirrhotic tissue samples and 11 normal liver tissue samples in order to identify key regulatory factors and core driver genes for myofibroblast transformation. Through cell communication analysis, we obtained the key cytokines of hepatic stellate cells regulating myofibroblasts, such as PDGFA, PDGFAR, PGF, NTF3, etc. At the same time, we also obtained key driver genes related to myofibroblast characteristics, such as LUM,GGT5, RBP1, ASPN,DCN, etc., through single-nucleus consensus weighted gene co-expression network analysis (scWGCNA). In addition, since APOE also plays a very important role in myofibroblasts, we also explored the driver genes associated with APOE, such as THY1,MMP2,COL3A1, etc. We analyzed the core driver gene of hepatic stellate cell transformation into myofibroblasts at the single-cell level in the process of liver fibrosis, providing valuable information for the future targeted gene diagnosis and treatment of liver fibrosis.

E-cadherin and aquaporin 1 co-expression analysis in hepatocellular carcinoma: a pilot study

Hepatocellular carcinoma (HCC) is the main primary liver malignancy, being associated with both health and economic burden worldwide. Recently, novel molecular markers and possible therapeutic targets were identified. Different adhesion molecules, as well as possible angiogenesis-associated targets can be prime candidates when investigating novel therapies. Considering these premises, our goal was to study the co-existence of E-cadherin and aquaporin 1 (AQP1) in a series of HCC diagnosed patients. Utilizing archived tissue fragments from 17 patients diagnosed with well-to-moderate and poorly differentiated HCC, as well as four samples of normal liver tissue and using a highly specific biotin-free tyramide amplification technique, we have assessed here the expression of E-cadherin and AQP1 during HCC carcinogenesis. Moreover, as we have observed that some of the AQP1 expression seems membrane-bound, we have sought to evaluate their co-localization. Our data showed, as expected, that E-cadherin decreases from control tissue to low-grade and respectively, high-grade HCC. AQP1 was expressed, also as already known, at the level of endothelial blood vessels and bile ducts epithelia, however, we have showed here for the first time that this water pore is also expressed in the cytoplasm and membranes of hepatocytes, both in control and HCC tissue. Moreover, AQP1 expression parallels the decrease of E-cadherin expression during carcinogenesis, but together with this downregulation, we have also found a spatial decrease in the colocalization of the two proteins. Altogether, utilizing a biotin-free tyramide signal amplification technique, this study shows for the first time that AQP1 is expressed at the level of liver epithelia, in both control and HCC tissue.

Prognostic Value of Stem Cell Index-Related Characteristics in Primary Hepatocellular Carcinoma.

The objective of this study is to form a cancer stem cell index-based model to stratify HCC risk and predict survival. After screening the Tumor Genome Atlas (TCGA) of liver and normal liver tissue samples, we obtained differentially expressed genes (DEGs). We employed a weighted correlation network analysis (WGCNA) and differentially expressed genes were studied in HCC to find the modules most associated with cancer stem cells (mRNAsi). At the same time, gene ontology and Kyoto Genome Encyclopedia (KEGG) were used for functional annotation and combined with LASSO, univariate, and multivariate COX regression analyses, a prediction model of key module genes of cancer stem cells was developed. The model's clinical efficacy was measured using the C index, calibration curve, multiindex ROC curve, and clinical decision curve. WGCNA found that black modules were most correlated with tumour stem cell index. Seven genes (CSDC2, GNA14, LGI2, MMRN1, PDE2A, SELP, and STK32B) were filtered by univariate, LASSO, and multivariate Cox regression analyses to establish the primary HCC model. The survival analysis and ROC curve in the TCGA training and validation cohort showed good performance. The independent prognostic factor of primary HCC was risk score, according to univariate and multivariate Cox regression analyses. It is found that the stem cell index model of 7 genes could predict factors independently, indicating that signatures of the stem cell will play a significant role in liver cancer survival prediction and risk stratification.

Single-Cell Sequencing of Hepatocellular Carcinoma Reveals Cell Interactions and Cell Heterogeneity in the Microenvironment.

BackgroundHepatocellular carcinoma (HCC) is the main histological subtype of liver cancer, which has the characteristics of poor prognosis and high fatality rate. Single-cell sequencing can provide quantitative and unbiased characterization of cell heterogeneity by analyzing the molecular profile of the whole genome of thousands of single cells. Thus, the purpose of this study was to identify novel prognostic markers for HCC based on single-cell sequencing data.MethodsSingle-cell sequencing of 21 HCC samples and 256 normal liver tissue samples in the GSE124395 dataset was collected from the Gene Expression Omnibus (GEO) database. The quality-controlled cells were grouped by unsupervised cluster analysis and identified the marker genes of each cell cluster. Hereafter, these cell clusters were annotated by singleR and CellMarker according to the expression patterns of the marker genes. Pseudotime analysis was performed to construct the trajectory of cell evolution and to define hub genes in the evolution process. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were used to explore the potential regulatory mechanism of hub genes in HCC. Next, the differential expression of hub genes and the correlation of the expression of these genes with patients’ survival and diagnosis were investigated in The Cancer Genome Atlas (TCGA) database.ResultsA total of 9 clusters corresponding to 9 cell types, including NKT cells, hepatocytes, endothelial cells, Kupffer cells, EPCAM+ cells, cancer cells, plasma cells (B cells), immature B cells, and myofibroblasts were identified. We screened 63 key genes related to cell differentiation through trajectory analysis, which were enriched in the process of coagulation. Ultimately, we identified 10 survival-related hub genes in the TCGA database, namely ALDOB, APOC3, APOH, CYP2E1, CYP3A4, GC, HRG, LINC01554, PDK4, and TXN.ConclusionIn conclusion, ALDOB, APOC3, APOH, CYP2E1, CYP3A4, GC, HRG, LINC01554, PDK4, and TXN may serve as hub genes in the diagnosis and prognosis for HCC.

Small nucleolar RNA 42 promotes the growth of hepatocellular carcinoma through the p53 signaling pathway

Recent studies show that small nucleolar RNAs (snoRNAs) play an important role in tumorigenesis. SNORA42 is a potential therapeutic target and prognostic biomarker for various cancers, and the aim of the present study was to investigate the function and clinical relevance of SNORA42 in hepatocellular carcinoma (HCC). We detected the expression levels of SNORA42 in HCC and normal liver tissue samples, as well as in tumor and hepatocyte-derived cell lines. SNORA42 was significantly upregulated in the HCC tissues and cells compared to the adjacent liver tissues and normal hepatocytes. Furthermore, overexpression of SNORA42 correlated with poor prognosis in the HCC patients. Knocking down SNORA42 in HCC cell lines decreased their proliferation, migration and invasion in vitro, and inhibited tumor growth and metastasis in vivo. In contrast, ectopic expression of SNORA42 promoted HCC cell proliferation and inhibited apoptosis. Mechanistically, SNORA42 exerted its oncogenic effects by targeting the p53 signaling pathway and cell cycle transition. In conclusion, SNORA42 acted as an oncogene in HCC and was a potential prognostic biomarker and therapeutic target.

Expression and Clinical Significance of OX40 and OX40L mRNA in Hepatocellular Carcinoma.

In a retrospective study, the expression of mRNA of membrane receptor OX40 and its ligand OX40L in liver tissues was analyzed in 34 patients with hepatocellular carcinoma in order to assess their clinical implications and prognostic value. Expression of mRNA was analyzed by reverse transcription PCR and TaqMan probes. Expression of OX40 mRNA was significantly higher in tumor specimens in paired comparison with the samples of adjacent non-tumor tissue or normal liver tissue of control patients. In contrast, expression of OX40L mRNA was lower in tumor tissue in paired comparison with the samples of adjacent non-tumor tissue or normal liver tissue. The clinical and pathological analysis showed that expression of OX40 mRNA significantly correlated with the degree of tumor differentiation; there was an insignificant decreasing trend in the length of recurrence-free period. It was hypothesized that microenvironment of hepatocellular carcinoma can induce immunosuppression due to dysregulation of the expression of OX40 and OX40L in tumor tissue, which promotes tumor growth.

LncRNA MYLK-AS1 facilitates tumor progression and angiogenesis by targeting miR-424-5p/E2F7 axis and activating VEGFR-2 signaling pathway in hepatocellular carcinoma

BackgroundLong non-coding RNAs (lncRNAs) are crucial in the invasion, angiogenesis, progression, and metastasis of hepatocellular carcinoma (HCC). The lncRNA MYLK-AS1 promotes the growth and invasion of HCC through the EGFR/HER2-ERK1/2 signaling pathway. However, the clinical significance of MYLK-AS1 in HCC still needs to be further determined.MethodsBioinformatic analysis was performed to determine the potential relationship among MYLK-AS1, miRNAs and mRNAs. A total of 156 samples of normal liver and paired HCC tissues from HCC patients were used to evaluate MYLK-AS1 expression by qRT-PCR. Human HCC cell lines were used to evaluate the colony formation, cell proliferation, migration, invasion, cell cycle and apoptosis after transfection of lentiviral short-hairpin RNAs (shRNAs) targeting MYLK-AS1 or MYLK-AS1 vectors. The competitive endogenous RNA (ceRNA) mechanism was clarified using fluorescence in situ hybridization (FISH), Western blotting, qPCR, RNA binding protein immunoprecipitation (RIP), and dual luciferase reporter analysis.ResultsMYLK-AS1 up-regulation was detected in the HCC tumor tissues and cell lines associated with the enhancement of the angiogenesis and tumor progression. The down-regulation of MYLK-AS1 reversed the effects on angiogenesis, proliferation, invasion and metastasis in the HCC cells and in vivo. MYLK-AS1 acted as ceRNA, capable of regulating the angiogenesis in HCC, while the microRNA miR-424-5p was the direct target of MYLK-AS1. Promoting the angiogenesis and the tumor proliferation, the complex MYLK-AS1/miR-424-5p activated the VEGFR-2 signaling through E2F7, whereas the specific targeting of E2F transcription factor 7 (E2F7) by miR-424-5p, was indicated by the mechanism studies.ConclusionsMYLK-AS1 and E2F7 are closely related to some malignant clinicopathological features and prognosis of HCC, thus the MYLK-AS1/ miR-424-5p/E2F7 signaling pathway might represent a promising treatment strategy to combat HCC.

Diagnostic value of clusterin immunostaining in hepatocellular carcinoma

BackgroundHistologic distinction between well differentiated hepatocellular carcinoma (HCC) and benign hepatocellular mass lesions is a known challenge. Existing biomarkers are of limited diagnostic value. Our previous studies observed an enhanced canalicular expression pattern of clusterin (CLU) in HCC, which was not observed in benign hepatocellular mass lesions such as hepatocellular adenoma. The aim of this study was to further investigate its diagnostic value for HCC by examining the expression pattern of CLU in a large number of non-hepatocellular tumors, and by comparing it with two other commonly used hepatocellular markers pCEA and CD10 that also show a canalicular staining pattern in HCC.MethodsEnhanced canalicular staining patterns of CLU, pCEA and CD10 were analyzed on 54 surgically resected well to moderately differentiated HCCs on whole tissue sections, of which 37 had surrounding regenerative nodules while the remaining 17 had a non-cirrhotic background. CLU immunostaining was also performed on tissue microarray sections that contained 74 HCCs (40 of which were also stained for pCEA and CD10), 55 normal liver tissue samples, and 1305 non-hepatocellular tumors from multiple organs.ResultsEnhanced CLU canalicular staining was observed in 70% (89/128) HCCs but not in regenerative nodules, normal liver tissues or any non-hepatocellular tumors. The sensitivity and specificity for enhanced canalicular staining pattern of CLU in HCCs were 0.70 and 1.00. This enhanced canalicular pattern was observed in only 26 and 23% HCCs for CD10 and pCEA, respectively. These results further demonstrate that the distinctive enhanced canalicular pattern of CLU is unique to HCC.ConclusionsCLU is superior to pCEA and CD10 as a diagnostic immunomarker in that it can help distinguish well to moderately differentiated HCC not only from non-HCC malignancies but also from benign hepatocellular mass lesions.