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Genome Medicine Nov 2023Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural...
BACKGROUND
Early detection of hepatocellular carcinoma (HCC) is important in order to improve patient prognosis and survival rate. Methylation sequencing combined with neural networks to identify cell-free DNA (cfDNA) carrying aberrant methylation offers an appealing and non-invasive approach for HCC detection. However, some limitations exist in traditional methylation detection technologies and models, which may impede their performance in the read-level detection of HCC.
METHODS
We developed a low DNA damage and high-fidelity methylation detection method called No End-repair Enzymatic Methyl-seq (NEEM-seq). We further developed a read-level neural detection model called DeepTrace that can better identify HCC-derived sequencing reads through a pre-trained and fine-tuned neural network. After pre-training on 11 million reads from NEEM-seq, DeepTrace was fine-tuned using 1.2 million HCC-derived reads from tumor tissue DNA after noise reduction, and 2.7 million non-tumor reads from non-tumor cfDNA. We validated the model using data from 130 individuals with cfDNA whole-genome NEEM-seq at around 1.6X depth.
RESULTS
NEEM-seq overcomes the drawbacks of traditional enzymatic methylation sequencing methods by avoiding the introduction of unmethylation errors in cfDNA. DeepTrace outperformed other models in identifying HCC-derived reads and detecting HCC individuals. Based on the whole-genome NEEM-seq data of cfDNA, our model showed high accuracy of 96.2%, sensitivity of 93.6%, and specificity of 98.5% in the validation cohort consisting of 62 HCC patients, 48 liver disease patients, and 20 healthy individuals. In the early stage of HCC (BCLC 0/A and TNM I), the sensitivity of DeepTrace was 89.6 and 89.5% respectively, outperforming Alpha Fetoprotein (AFP) which showed much lower sensitivity in both BCLC 0/A (50.5%) and TNM I (44.7%).
CONCLUSIONS
By combining high-fidelity methylation data from NEEM-seq with the DeepTrace model, our method has great potential for HCC early detection with high sensitivity and specificity, making it potentially suitable for clinical applications. DeepTrace: https://github.com/Bamrock/DeepTrace.
Topics: Humans; Carcinoma, Hepatocellular; Liver Neoplasms; Cell-Free Nucleic Acids; Biomarkers, Tumor; DNA, Neoplasm; DNA Methylation; Neural Networks, Computer
PubMed: 37936230
DOI: 10.1186/s13073-023-01238-8 -
Aging Jul 2023Sorafenib, a small-molecule inhibitor targeting several tyrosine kinase pathways, is the standard treatment for advanced hepatocellular carcinoma (HCC). However, not all...
Sorafenib, a small-molecule inhibitor targeting several tyrosine kinase pathways, is the standard treatment for advanced hepatocellular carcinoma (HCC). However, not all patients with HCC respond well to sorafenib, and 30% of patients develop resistance to sorafenib after short-term treatment. Galectin-1 modulates cell-cell and cell-matrix interactions and plays a crucial role in HCC progression. However, whether Galectin-1 regulates receptor tyrosine kinases by sensitizing HCC to sorafenib remains unclear. Herein, we established a sorafenib-resistant HCC cell line (Huh-7/SR) and determined that Galectin-1 expression was significantly higher in Huh-7/SR cells than in parent cells. Galectin-1 knockdown reduced sorafenib resistance in Huh-7/SR cells, whereas Galectin-1 overexpression in Huh-7 cells increased sorafenib resistance. Galectin-1 regulated ferroptosis by inhibiting excessive lipid peroxidation, protecting sorafenib-resistant HCC cells from sorafenib-mediated ferroptosis. Galectin-1 expression was positively correlated with poor prognostic outcomes for HCC patients. Galectin-1 overexpression promoted the phosphorylation of AXL receptor tyrosine kinase (AXL) and MET proto-oncogene, receptor tyrosine kinase (MET) signaling, which increased sorafenib resistance. MET and AXL were highly expressed in patients with HCC, and AXL expression was positively correlated with Galectin-1 expression. These findings indicate that Galectin-1 regulates sorafenib resistance in HCC cells through AXL and MET signaling. Consequently, Galectin-1 is a promising therapeutic target for reducing sorafenib resistance and sorafenib-mediated ferroptosis in patients with HCC.
Topics: Humans; Carcinoma, Hepatocellular; Cell Line, Tumor; Drug Resistance, Neoplasm; Ferroptosis; Galectin 1; Liver Neoplasms; Receptor Protein-Tyrosine Kinases; Sorafenib
PubMed: 37433225
DOI: 10.18632/aging.204867 -
Acta Biochimica Et Biophysica Sinica Nov 2023The development of effective precision treatments for liver cancers has been hindered by the scarcity of preclinical models that accurately reflect the heterogeneity of... (Review)
Review
The development of effective precision treatments for liver cancers has been hindered by the scarcity of preclinical models that accurately reflect the heterogeneity of this disease. Recent progress in developing patient-derived liver cancer cell lines and organoids has paved the way for precision medicine research. These expandable resources of liver cancer cell models enable a full spectrum of pharmacogenomic analysis for liver cancers. Moreover, patient-derived and short-term cultured two-dimensional tumor cells or three-dimensional organoids can serve as patient avatars, allowing for the prediction of patients' response to drugs and facilitating personalized treatment for liver cancer patients. Furthermore, the current novel techniques have expanded the scope of cancer research, including innovative organoid culture, gene editing and bioengineering. In this review, we provide an overview of the progress in patient-derived liver cancer cell models, focusing on their applications in precision and personalized medicine research. We also discuss the challenges and future perspectives in this field.
Topics: Humans; Precision Medicine; Liver Neoplasms; Organoids; Cell Line
PubMed: 37766458
DOI: 10.3724/abbs.2023224 -
The Turkish Journal of Gastroenterology... Jul 2023Exosomes are tiny vesicles secreted by cells, with a diameter of 40-160 nm, which contain proteins, DNA, mRNA, long noncoding RNA, etc. Because of the low sensitivity... (Review)
Review
Exosomes are tiny vesicles secreted by cells, with a diameter of 40-160 nm, which contain proteins, DNA, mRNA, long noncoding RNA, etc. Because of the low sensitivity and specificity of the conventional biomarkers for liver diseases, it is of utmost importance to discover novel, sensitive, specific, and non-invasive biomarkers. Exosomal long noncoding RNAs have been considered as potential diagnostic, prognostic, or predictive biomarkers in a wide range of liver pathologies. In this review, we discuss the recent progress on exosomal long noncoding RNAs that serve as potential diagnostic, prognostic, or predictive markers and molecular targets in patients with hepatocellular carcinoma, cholestatic liver injury, viral hepatitis, and alcohol-related liver diseases.
Topics: Humans; RNA, Long Noncoding; Carcinoma, Hepatocellular; Biomarkers; Liver Neoplasms; Biomarkers, Tumor
PubMed: 37326156
DOI: 10.5152/tjg.2023.22741 -
EBioMedicine Feb 2024Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites....
BACKGROUND
Previous metabolic profiling of liver cancer has mostly used untargeted metabolomic approaches and was unable to quantitate the absolute concentrations of metabolites. In this study, we examined the association between the concentrations of 186 targeted metabolites and liver cancer risk using prediagnostic plasma samples collected up to 14 years prior to the clinical diagnosis of liver cancer.
METHODS
We conducted a nested case-control study (n = 322 liver cancer cases, n = 322 matched controls) within the Shanghai Men's Health Study. Conditional logistic regression models adjusted for demographics, lifestyle factors, dietary habits, and related medical histories were used to estimate the odds ratios. Restricted cubic spline functions were used to characterise the dose-response relationships between metabolite concentrations and liver cancer risk.
FINDINGS
After adjusting for potential confounders and correcting for multiple testing, 28 metabolites were associated with liver cancer risk. Significant non-linear relationships were observed for 22 metabolites. The primary bile acid biosynthesis and phenylalanine, tyrosine and tryptophan biosynthesis were found to be important pathways involved in the aetiology of liver cancer. A metabolic score consisting of 10 metabolites significantly improved the predictive ability of traditional epidemiological risk factors for liver cancer, with an optimism-corrected AUC increased from 0.84 (95% CI: 0.81-0.87) to 0.89 (95% CI: 0.86-0.91).
INTERPRETATION
This study characterised the dose-response relationships between metabolites and liver cancer risk, providing insights into the complex metabolic perturbations prior to the clinical diagnosis of liver cancer. The metabolic score may serve as a candidate risk predictor for liver cancer.
FUNDING
National Key Project of Research and Development Program of China [2021YFC2500404, 2021YFC2500405]; US National Institutes of Health [subcontract of UM1 CA173640].
Topics: Male; Humans; Case-Control Studies; Prospective Studies; China; Risk Factors; Metabolomics; Liver Neoplasms; Research
PubMed: 38306896
DOI: 10.1016/j.ebiom.2024.104990 -
Korean Journal of Radiology Jun 2024Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is... (Review)
Review
Hepatocellular carcinoma (HCC) is a biologically heterogeneous tumor characterized by varying degrees of aggressiveness. The current treatment strategy for HCC is predominantly determined by the overall tumor burden, and does not address the diverse prognoses of patients with HCC owing to its heterogeneity. Therefore, the prognostication of HCC using imaging data is crucial for optimizing patient management. Although some radiologic features have been demonstrated to be indicative of the biologic behavior of HCC, traditional radiologic methods for HCC prognostication are based on visually-assessed prognostic findings, and are limited by subjectivity and inter-observer variability. Consequently, artificial intelligence has emerged as a promising method for image-based prognostication of HCC. Unlike traditional radiologic image analysis, artificial intelligence based on radiomics or deep learning utilizes numerous image-derived quantitative features, potentially offering an objective, detailed, and comprehensive analysis of the tumor phenotypes. Artificial intelligence, particularly radiomics has displayed potential in a variety of applications, including the prediction of microvascular invasion, recurrence risk after locoregional treatment, and response to systemic therapy. This review highlights the potential value of artificial intelligence in the prognostication of HCC as well as its limitations and future prospects.
Topics: Humans; Liver Neoplasms; Carcinoma, Hepatocellular; Artificial Intelligence; Prognosis; Image Interpretation, Computer-Assisted
PubMed: 38807336
DOI: 10.3348/kjr.2024.0070 -
World Journal of Surgical Oncology Sep 2023Although WD repeat and high-mobility group box DNA binding protein 1 (WDHD1) played an essential role in DNA replication, chromosome stability, and DNA damage repair,...
BACKGROUND
Although WD repeat and high-mobility group box DNA binding protein 1 (WDHD1) played an essential role in DNA replication, chromosome stability, and DNA damage repair, the panoramic picture of WDHD1 in human tumors remains unclear. Hence, this study aims to comprehensively characterize WDHD1 across 33 human cancers.
METHODS
Based on publicly available databases such as TCGA, GTEx, and HPA, we used a bioinformatics approach to systematically explore the genomic features and biological functions of WDHD1 in pan-cancer.
RESULTS
WDHD1 mRNA levels were significantly increased in more than 20 types of tumor tissues. Elevated WDHD1 expression was associated with significantly shorter overall survival (OS) in 10 tumors. Furthermore, in uterine corpus endometrial carcinoma (UCEC) and liver hepatocellular carcinoma (LIHC), WDHD1 expression was significantly associated with higher histological grades and pathological stages. In addition, WDHD1 had a high diagnostic value among 16 tumors (area under the ROC curve [AUC] > 0.9). Functional enrichment analyses suggested that WDHD1 probably participated in many oncogenic pathways such as E2F and MYC targets (false discovery rate [FDR] < 0.05), and it was involved in the processes of DNA replication and DNA damage repair (p.adjust < 0.05). WDHD1 expression also correlated with the half-maximal inhibitory concentrations (IC50) of rapamycin (4 out of 10 cancers) and paclitaxel (10 out of 10 cancers). Overall, WDHD1 was negatively associated with immune cell infiltration and might promote tumor immune escape. Our analysis of genomic alterations suggested that WDHD1 was altered in 1.5% of pan-cancer cohorts and the "mutation" was the predominant type of alteration. Finally, through correlation analysis, we found that WDHD1 might be closely associated with tumor heterogeneity, tumor stemness, mismatch repair (MMR), and RNA methylation modification, which were all processes associated with the tumor progression.
CONCLUSIONS
Our pan-cancer analysis of WDHD1 provides valuable insights into the genomic characterization and biological functions of WDHD1 in human cancers and offers some theoretical support for the future use of WDHD1-targeted therapies, immunotherapies, and chemotherapeutic combinations for the management of tumors.
Topics: Humans; Computational Biology; Immunotherapy; Carcinoma, Hepatocellular; Biomarkers; Liver Neoplasms; Prognosis; DNA-Binding Proteins
PubMed: 37759234
DOI: 10.1186/s12957-023-03187-3 -
Physics in Medicine and Biology Oct 2023External beam radiation therapy (EBRT) of liver cancers can cause local liver atrophy as a result of tissue damage or hypertrophy as a result of liver regeneration....
External beam radiation therapy (EBRT) of liver cancers can cause local liver atrophy as a result of tissue damage or hypertrophy as a result of liver regeneration. Predicting those volumetric changes would enable new strategies for liver function preservation during treatment planning. However, understanding of the spatial dose/volume relationship is still limited. This study leverages the use of deep learning-based segmentation and biomechanical deformable image registration (DIR) to analyze and predict this relationship. Pre- and Post-EBRT imaging data were collected for 100 patients treated for hepatocellular carcinomas, cholangiocarcinoma or CRC with intensity-modulated radiotherapy (IMRT) with prescription doses ranging from 50 to 100 Gy delivered in 10-28 fractions. For each patient, DIR between the portal and venous (PV) phase of a diagnostic computed tomography (CT) scan acquired before radiation therapy (RT) planning, and a PV phase of a diagnostic CT scan acquired after the end of RT (on average 147 ± 36 d) was performed to calculate Jacobian maps representing volume changes in the liver. These volume change maps were used: (i): to analyze the dose/volume relationship in the whole liver and individual Couinaud's segments; and (ii): to investigate the use of deep-learning to predict a Jacobian map solely based on the pre-RT diagnostic CT and planned dose distribution. Moderate correlations between mean equivalent dose in 2 Gy fractions (EQD2) and volume change was observed for all liver sub-regions analyzed individually with Pearson correlationranging from -0.36 to -067. The predicted volume change maps showed a significantly stronger voxel-wise correlation with the DIR-based volume change maps than when considering the original EQD2 distribution (0.63 ± 0.24 versus 0.55 ± 23, respectively), demonstrating the ability of the proposed approach to establish complex relationships between planned dose and liver volume response months after treatment, which represents a promising prediction tool for the development of future adaptive and personalized liver radiation therapy strategies.
Topics: Humans; Radiotherapy Dosage; Liver Neoplasms; Carcinoma, Hepatocellular; Radiotherapy Planning, Computer-Assisted; Cone-Beam Computed Tomography
PubMed: 37714187
DOI: 10.1088/1361-6560/acfa5f -
Molecular Cancer Apr 2024Sorafenib is a major nonsurgical option for patients with advanced hepatocellular carcinoma (HCC); however, its clinical efficacy is largely undermined by the...
BACKGROUND AND AIMS
Sorafenib is a major nonsurgical option for patients with advanced hepatocellular carcinoma (HCC); however, its clinical efficacy is largely undermined by the acquisition of resistance. The aim of this study was to identify the key lncRNA involved in the regulation of the sorafenib response in HCC.
MATERIALS AND METHODS
A clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein 9 (Cas9) single-guide RNA (sgRNA) synergistic activation mediator (SAM)-pooled lncRNA library was applied to screen for the key lncRNA regulated by sorafenib treatment. The role of the identified lncRNA in mediating the sorafenib response in HCC was examined in vitro and in vivo. The underlying mechanism was delineated by proteomic analysis. The clinical significance of the expression of the identified lncRNA was evaluated by multiplex immunostaining on a human HCC microtissue array.
RESULTS
CRISPR/Cas9 lncRNA library screening revealed that Linc01056 was among the most downregulated lncRNAs in sorafenib-resistant HCC cells. Knockdown of Linc01056 reduced the sensitivity of HCC cells to sorafenib, suppressing apoptosis in vitro and promoting tumour growth in mice in vivo. Proteomic analysis revealed that Linc01056 knockdown in sorafenib-treated HCC cells induced genes related to fatty acid oxidation (FAO) while repressing glycolysis-associated genes, leading to a metabolic switch favouring higher intracellular energy production. FAO inhibition in HCC cells with Linc01056 knockdown significantly restored sensitivity to sorafenib. Mechanistically, we determined that PPARα is the critical molecule governing the metabolic switch upon Linc01056 knockdown in HCC cells and indeed, PPARα inhibition restored the sorafenib response in HCC cells in vitro and HCC tumours in vivo. Clinically, Linc01056 expression predicted optimal overall and progression-free survival outcomes in HCC patients and predicted a better sorafenib response. Linc01056 expression indicated a low FAO level in HCC.
CONCLUSION
Our study identified Linc01056 as a critical epigenetic regulator and potential therapeutic target in the regulation of the sorafenib response in HCC.
Topics: Humans; Mice; Animals; Sorafenib; Carcinoma, Hepatocellular; RNA, Long Noncoding; Liver Neoplasms; RNA, Guide, CRISPR-Cas Systems; PPAR alpha; Proteomics; Cell Line, Tumor; Drug Resistance, Neoplasm; Gene Expression Regulation, Neoplastic
PubMed: 38582885
DOI: 10.1186/s12943-024-01988-y -
Digestive and Liver Disease : Official... Apr 2024The systemic treatment of hepatocellular carcinoma (HCC) is changing rapidly. After a decade of tyrosine kinase inhibitors (TKIs), as the only therapeutic option for the... (Review)
Review
The systemic treatment of hepatocellular carcinoma (HCC) is changing rapidly. After a decade of tyrosine kinase inhibitors (TKIs), as the only therapeutic option for the treatment of advanced HCC, in the last few years several phase III trials demonstrated the efficacy of immune checkpoint inhibitors (ICIs). The combination of the anti-PD-L1 atezolizumab and the anti-vascular endothelial growth factor (VEGF) bevacizumab demonstrated the superiority over sorafenib and currently represents the standard of care treatment for advanced HCC. In addition, the combination of durvalumab (an anti-PD-L1) and tremelimumab (an anti-CTLA4) proved to be superior to sorafenib, and in the same trial durvalumab monotherapy showed non-inferiority compared to sorafenib. However, early reports suggest an influence of HCC etiology in modulating the response to these drugs. In particular, a lower effectiveness of ICIs has been suggested in patients with non-viral HCC (in particular non-alcoholic fatty liver disease). Nevertheless, randomized controlled trials available to date have not been stratified for etiology and data suggesting a possible impact of etiology in the outcome of patients managed with ICIs derive from subgroup not pre-specified analyses. In this review, we aim to examine the potential impact of HCC etiology on the response to immunotherapy regimens for HCC.
Topics: Humans; Carcinoma, Hepatocellular; Sorafenib; Liver Neoplasms; Digestive System Diseases; Immunotherapy
PubMed: 37758610
DOI: 10.1016/j.dld.2023.08.062