mTOR/HDAC1 Crosstalk Mediated Suppression of ADH1A and ALDH2 Links Alcohol Metabolism to Hepatocellular Carcinoma Onset and Progression in silico

ALDH2 as an immunological and prognostic biomarker: Insights from pan-cancer analysis

Aldehyde dehydrogenase 2 (ALDH2) plays a critical role in safeguarding cells against acetaldehyde toxicity and is closely linked to human metabolism. Nevertheless, the involvement of ALDH2 in cancer remains enigmatic. This investigation seeks to comprehensively assess ALDH2's significance in pan-cancer. We conducted an all-encompassing analysis of pan-cancer utilizing multiple databases, including TCGA, linkedomicshs, UALCAN, and Kaplan-Meier plotter. We employed diverse algorithms such as EPIC, MCPCOUNTER, TIDTIMER, xCell, MCP-counter, CIBERSORT, quanTIseq, and EPIC to examine the connection between ALDH2 expression and immune cell infiltration. Single-cell sequencing analysis furnished insights into ALDH2's functional status in pan-cancer. Immunohistochemical staining was performed to validate ALDH2 expression in cancer tissues. In a comprehensive assessment, we observed that tumor tissues demonstrated diminished ALDH2 expression levels compared to normal tissues across 16 different cancer types. ALDH2 expression exhibited a significant positive correlation with the infiltration of immune cells, including CD4 + T cells, CD8 + T cells, neutrophils, B cells, and macrophages, in various tumor types. Moreover, this study explored the association between ALDH2 and patient survival, examined the methylation patterns of ALDH2 in normal and primary tumor tissues, and delved into genetic variations and mutations of ALDH2 in tumors. The findings suggest that ALDH2 could serve as a valuable prognostic biomarker in pan-cancer, closely linked to the tumor's immune microenvironment.

Research Progress on the Correlation between Acetaldehyde Dehydrogenase 2 and Hepatocellular Carcinoma Development

Hepatocellular carcinoma (HCC) is the predominant pathologic type of primary liver cancer. It is a malignant tumor of liver epithelial cells. There are many ways to treat HCC, but the survival rate for HCC patients remains low. Therefore, understanding the underlying mechanisms by which HCC occurs and develops is critical to explore new therapeutic targets. Aldehyde dehydrogenase 2 (ALDH2) is an important player in the redox reaction of ethanol with endogenous aldehyde products released by lipid peroxidation. Increasing evidence suggests that ALDH2 is a crucial regulator of human tumor development, including HCC. Therefore, clarifying the relationship between ALDH2 and HCC is helpful for formulating rational treatment strategies. This review highlights the regulatory roles of ALDH2 in the development of HCC, elucidates the multiple potential mechanisms by which ALDH2 regulates the development of HCC, and summarizes the progress of research on ALDH2 gene polymorphisms and HCC susceptibility. Meanwhile, we envision viable strategies for targeting ALDH2 in the treatment of HCC SIGNIFICANCE STATEMENT: Numerous studies have aimed to explore novel therapeutic targets for HCC, and ALDH2 has been reported to be a critical regulator of HCC progression. This review discusses the functions, molecular mechanisms, and clinical significance of ALDH2 in the development of HCC and examines the prospects of ALDH2-based therapy for HCC.

Identification of subclusters and prognostic genes based on glycolysis/gluconeogenesis in hepatocellular carcinoma

Background

This study aimed to examine glycolysis/gluconeogenesis-related genes in hepatocellular carcinoma (HCC) and evaluate their potential roles in HCC progression and immunotherapy response.

Methods

Data analyzed in this study were collected from GSE14520, GSE76427, GSE174570, The Cancer Genome Atlas (TCGA), PXD006512, and GSE149614 datasets, metabolic pathways were collected from MSigDB database. Differentially expressed genes (DEGs) were identified between HCC and controls. Differentially expressed glycolysis/gluconeogenesis-related genes (candidate genes) were obtained and consensus clustering was performed based on the expression of candidate genes. Bioinformatics analysis was used to evaluate candidate genes and screen prognostic genes. Finally, the key results were tested in HCC patients.

Results

Thirteen differentially expressed glycolysis/gluconeogenesis-related genes were validated in additional datasets. Consensus clustering analysis identified two distinct patient clusters (C1 and C2) with different prognoses and immune microenvironments. Immune score and tumor purity were significantly higher in C1 than in C2, and CD4+ memory activated T cell, Tfh, Tregs, and macrophage M0 were higher infiltrated in HCC and C1 group. The study also identified five intersecting DEGs from candidate genes in TCGA, GSE14520, and GSE141198 as prognostic genes, which had a protective role in HCC patient prognosis. Compared with the control group, the prognostic genes all showed decreased expression in HCC patients in RT-qPCR and Western blot analyses. Flow cytometry verified the abnormal infiltration level of immune cells in HCC patients.

Conclusion

Results showed that glycolysis/gluconeogenesis-related genes were associated with patient prognosis, immune microenvironment, and response to immunotherapy in HCC. It suggests that the model based on five prognostic genes may valuable for predicting the prognosis and immunotherapy response of HCC patients.

Autophagy and biotransformation affect sorafenib resistance in hepatocellular carcinoma

As sorafenib is a first-line drug for treating advanced hepatocellular carcinoma, sorafenib resistance has historically attracted attention. However, most of this attention has been focused on a series of mechanisms related to drug resistance arising after sorafenib treatment. In this study, we used proteomic techniques to explore the potential mechanisms by which pretreatment factors affect sorafenib resistance. The degree of redundant pathway PI3K/AKT activation, biotransformation capacity, and autophagy level in hepatocellular carcinoma patients prior to sorafenib treatment might affect their sensitivity to sorafenib, in which ADH1A and STING1 are key molecules. These three factors could interact mechanistically to promote tumor cell survival, might be malignant features of tumor cells, and are associated with hepatocellular carcinoma prognosis. Our study suggests possible avenues of therapeutic intervention for patients with sorafenib-resistance and the potential application of immunotherapy with the aim of improving the survival of such patients.

Exploring the mechanisms underlying the therapeutic effect of the Radix Bupleuri-Rhizoma Cyperi herb pair on hepatocellular carcinoma using multilevel data integration and molecular docking

Traditional Chinese medicine (TCM) is a promising and effective treatment for cancer with minimal side effects through a multi-active ingredient multitarget network. Radix Bupleuri and Rhizoma Cyperi are listed as herbs dispersing stagnated liver Qi in China. They have been used clinically to treat liver diseases for many years and recent pharmacological studies have shown that they inhibit the proliferation of hepatocellular carcinoma (HCC). However, the pharmacological mechanisms, potential targets, and clinical value of the Radix Bupleuri-Rhizoma Cyperi herb pair (CXP) for suppressing HCC growth have not been fully elucidated. We identified 44 CXP targets involved in the treatment of HCC using the GEO dataset and HERB database. An analysis of the Traditional Chinese Medicine System Pharmacology Database (TCMSP) showed that CXP exerts synergistic effects through 4 active ingredients, including quercetin, stigmasterol, isorhamnetin, and kaempferol. GO and KEGG analyses revealed that CXP mainly regulates HCC progression through metabolic pathways, the p53 signaling pathway, and the cell cycle. Additionally, we applied The Cancer Genome Atlas (TCGA)-liver hepatocellular carcinoma (LIHC) database to perform the expression patterns, clinical features, and prognosis of 6 genes (CCNB1, CDK1, CDK4, MYC, CDKN2A, and CHEK1) in cell cycle pathways to reveal that CXP suppresses HCC clinical therapeutic value. Moreover, based on molecular docking, we further verified that CXP exerts its anti-HCC activity through the interaction of multiple active components with cell cycle-related genes. We systematically revealed the potential pharmacological mechanisms and targets of CXP in HCC using multilevel data integration and molecular docking strategies.

Machine learning algorithm and deep neural networks identified a novel subtype in hepatocellular carcinoma

BACKGROUND: Hepatocellular carcinoma (HCC) is one of the most common malignant tumors. Due to the lack of specific characteristics in the early stage of the disease, patients are usually diagnosed in the advanced stage of disease progression. OBJECTIVE: This study used machine learning algorithms to identify key genes in the progression of hepatocellular carcinoma and constructed a prediction model to predict the survival risk of HCC patients. METHODS: The transcriptome data and clinical information were downloaded from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). The differential expression analysis and COX proportional-hazards model participated in the identification of survival-related genes. K-Means, Random forests, and LASSO regression are involved in identifying novel subtypes of HCC and screening key genes. The prediction model was constructed by deep neural networks (DNN), and Gene Set Enrichment Analysis (GSEA) reveals the metabolic pathways where key genes are located. RESULTS: Two subtypes were identified with significantly different survival rates (p< 0.0001, AUC = 0.720) and 17 key genes associated with the subtypes. The accuracy rate of the deep neural network prediction model is greater than 93.3%. The GSEA analysis found that the survival-related genes were significantly enriched in hallmark gene sets in the MSigDB database. CONCLUSIONS: In this study, we used machine learning algorithms to screen out 17 genes related to the survival risk of HCC patients, and trained a DNN model based on them to predict the survival risk of HCC patients. The genes that make up the model are all key genes that affect the formation and development of cancer.

Screening potential biomarkers of cholangiocarcinoma based on gene chip meta-analysis and small-sample experimental research

Cholangiocarcinoma (CCA) is a rare malignant tumor associated with poor prognosis. This study aimed to identify CCA biomarkers by investigating differentially expressed genes (DEGs) between CCA patients and healthy subjects obtained from the Gene Expression Omnibus database. Bioinformatics tools, including the Illumina BaseSpace Correlation Engine (BSCE) and Gene Expression Profiling Interactive Analysis (GEPIA), were used. The initial DEGs from GSE26566, GSE31370, and GSE77984 were analyzed using GEO2R and Venn, and protein–protein interaction networks were constructed using STRING. The BSCE was applied to assess curated CCA studies to select additional DEGs and them DEGs across the 10 biosets, which was supported by findings in the literature. The final 18 DEGs with clinical significance for CCA were further verified using GEPIA. These included CEACAM6, EPCAM, LAMC2, MMP11, KRT7, KRT17, KRT19, SFN, and SOX9, which were upregulated, and ADH1A, ALDOB, AOX1, CTH, FGA, FGB, FGG, GSTA1, and OTC, which were downregulated in CCA patients. Among these 18 genes, 56 groups of genes (two in each group) were significantly related, and none were independently and differentially expressed. The hub genes FGA, OTC, CTH, and MMP11, which were most correlated with the 18 DEGs, were screened using STRING. The significantly low expression of FGA, OTC, and CTH and significantly high expression of MMP11 were verified by immunohistochemical analysis. Overall, four CCA biomarkers were identified that might regulate the occurrence and development of this disease and affect the patient survival rate, and they have the potential to become diagnostic and therapeutic targets for patients with CCA.

Integrative analysis of the characteristic of lipid metabolism-related genes for the prognostic prediction of hepatocellular carcinoma

BACKGROUND

Dysregulation of lipid metabolism is implicated in the progression of hepatocellular carcinoma (HCC). We therefore investigated the molecular characteristics of lipid-metabolism-related genes in HCC.

METHODS

Multi-dimensional bioinformatics analysis was conducted to comprehensively identify the lipid metabolism-related genes (LMRGs) from public databases, as well as the clinical information, immune features, and biological characteristics of HCC. The IMGR were then used to classify HCC into molecular phenotypes. Six lipid metabolism-related genes sets with the potential to predict the prognosis of HCC patients were identified.

RESULTS

A total of 770 HCC patients with complete clinical information and corresponding 776 LMRGs were downloaded from 3 databases. Univariate cox and non-negative matrix factorization analyses were used to classify HCC patients into 2 clusters. This molecular classification was associated with overall survival, clinical characteristics, and immune cells. The biological function of the differentially expressed LMRGs in the 2 clusters showed the genes associated with tumor-related metabolism pathways. A combination of multivariate/univariate cox regression and least absolute shrinkage and selection operator analyses were conducted to build a 6 LMRGs signature (6-IS) to predict the prognosis of HCC. The 6-IS signature was found to be an independent prognostic factor. Performance of the 6-IS prognostic signature was verified in a validation set and compared with an external data set. Results revealed the 6-IS signature could effectively predict the prognosis of patients with HCC.

CONCLUSIONS

This study provides new insights into the role of LMRG in the pathogenesis of HCC and presents a novel prognostic signature 6-IS monitoring the clinical course of HCC.

The general law of plasma proteome alterations occurring in the lifetime of Chinese individuals reveals the importance of immunity

Background: Aging is characterized by a continuous loss of protein homeostasis. A closer examination of peripheral blood, which houses proteins from nearly all tissues and cells, helped identify several biomarkers and other aspects of aging biology. To further explore the general law of aging and identify key time nodes and associated aging biology, we collected 97 plasma samples from 253 healthy individuals aged 0-100 years without adverse outcomes to conduct nano-Ultra High Performance Liquid Chromatography-Mass Spectrometry/Mass Spectrometry (nano-UHPLC-MS/MS) and weighted gene co-expression network analysis (WGCNA).

Results: Through biological processes and key biological pathways identified in discrete age group modules, our analyses highlighted a strong correlation between alterations in the immune system and aging process. We also identified hub genes associated with distinct age groups that revealed alterations not only in protein expression but also in signaling cascade. Among them, hub genes from age groups of 0-20 years old and 71-100 years old are mostly involved in infectious diseases and the immune system. In addition, CDC5L and HMGB2 were the key transcription factors (TFs) regulating genes expression in people aged between 51-60 and 71-100 years of age. They were shown to not only be independent but also mutually regulate certain hub gene expressions.

Conclusions: This study reveals that the plasma proteome undergoes a complex alteration over the lifetime of a human. In this process, the immune system is crucial throughout the lifespan of a human being. However, the underlying mechanism(s) regulating differential protein expressions at distinct ages remains to be elucidated.

An advanced network pharmacology study to explore the novel molecular mechanism of Compound Kushen Injection for treating hepatocellular carcinoma by bioinformatics and experimental verification

Background

Compound Kushen Injection (CKI) is a Chinese patent drug that exerts curative effects in the clinical treatment of hepatocellular carcinoma (HCC). This study aimed to explore the targets and potential pharmacological mechanisms of CKI in the treatment of HCC.

Methods

In this study, network pharmacology was used in combination with molecular biology experiments to predict and verify the molecular mechanism of CKI in the treatment of HCC. The constituents of CKI were identified by UHPLC-MS/MS and literature search. The targets corresponding to these compounds and the targets related to HCC were collected based on public databases. To screen out the potential hub targets of CKI in the treatment of HCC, a compound-HCC target network was constructed. The underlying pharmacological mechanism was explored through the subsequent enrichment analysis. Interactive Gene Expression Profiling Analysis and Kaplan-Meier plotter were used to examine the expression and prognostic value of hub genes. Furthermore, the effects of CKI on HCC were verified through molecular docking simulations and cell experiments in vitro.

Results

Network analysis revealed that BCHE, SRD5A2, EPHX2, ADH1C, ADH1A and CDK1 were the key targets of CKI in the treatment of HCC. Among them, only CDK1 was highly expressed in HCC tissues, while the other 5 targets were lowly expressed. Furthermore, the six hub genes were all closely related to the prognosis of HCC patients in survival analysis. Molecular docking revealed that there was an efficient binding potential between the constituents of CKI and BCHE. Experiments in vitro proved that CKI inhibited the proliferation of HepG2 cells and up-regulated SRD5A2 and ADH1A, while down-regulated CDK1 and EPHX2.

Conclusions

This study revealed and verified the targets of CKI on HCC based on network pharmacology and experiments and provided a scientific reference for further mechanism research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12906-022-03530-3.

Spatial maps of hepatocellular carcinoma transcriptomes highlight an unexplored landscape of heterogeneity and a novel gene signature for survival

Background

Hepatocellular carcinoma (HCC) often presents with satellite nodules, rendering current curative treatments ineffective in many patients. The heterogeneity of HCC is a major challenge in personalized medicine. The emergence of spatial transcriptomics (ST) provides a powerful strategy for delineating the complex molecular landscapes of tumours.

Methods

In this study, the heterogeneity of tissue-wide gene expression in tumour and adjacent nonneoplastic tissues using ST technology were investigated. The transcriptomes of nearly 10,820 tissue regions and identified the main gene expression clusters and their specific marker genes (differentially expressed genes, DEGs) in patients were analysed. The DEGs were analysed from two perspectives. First, two distinct gene profiles were identified to be associated with satellite nodules and conducted a more comprehensive analysis of both gene profiles. Their clinical relevance in human HCC was validated with Kaplan–Meier (KM) Plotter. Second, DEGs were screened with The Cancer Genome Atlas (TCGA) database to divide the HCC cohort into high- and low-risk groups according to Cox analysis. HCC patients from the International Cancer Genome Consortium (ICGC) cohort were used for validation. KM analysis was used to compare the overall survival (OS) between the high- and low-risk groups. Univariate and multivariate Cox analyses were applied to determine the independent predictors for OS.

Results

Novel markers for the prediction of satellite nodules were identified and a tumour clusters-specific marker gene signature model (6 genes) for HCC prognosis was constructed.

Conclusion

The establishment of marker gene profiles may be an important step towards an unbiased view of HCC, and the 6-gene signature can be used for prognostic prediction in HCC. This analysis will help us to clarify one of the possible sources of HCC heterogeneity and uncover pathogenic mechanisms and novel antitumour drug targets.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12935-021-02430-9.

Crosstalk between epigenetics and mTOR as a gateway to new insights in pathophysiology and treatment of Alzheimer's disease

Epigenetics in the current times has become a gateway to acquire answers to questions that were left unanswered by classical and modern genetics, be it resolving the complex mystery behind neurodegenerative disorders or understanding the complexity behind life-threatening cancers. It has presented to the world an entirely new dimension and has added a dynamic angle to an otherwise static field of genetics. Alzheimer's disease is one of the most prevalent neurodegenerative disorders is largely found to be a result of alterations in epigenetic pathways. These changes majorly comprise an imbalance in DNA methylation levels and altered acetylation and methylation of histones. They are often seen to cross-link with metabolic regulatory pathways such as that of mTOR, contributing significantly to the pathophysiology of AD. This review focusses on the study of the interplay of the mTOR regulatory pathway with that of epigenetic machinery that may elevate the rate of early diagnosis and prove to be a gateway to the development of an efficient and novel therapeutic strategy for the treatment of Alzheimer's disease at an early stage.

ALDH2 is a prognostic biomarker and related with immune infiltrates in HCC

Hepatocellular carcinoma is a malignant type of carcinoma with complicated pathogenesis. For HCC patients, there is not only a lack of valuable therapeutic targets, but also a lack of prognostic biomarker. The protein encoded by Aldehyde Dehydrogenase 2 Family Member (ALDH2) is a critical member of the aldehyde dehydrogenase family. Many researchers have found that ALDH2 mutations play an important role in the activation of hepatocellular carcinoma carcinogenic pathways. However, the clinicopathological meaning of ALDH2 in HCC and its relation with immune infiltration is still indistinguishable. In this study, we explored the expression of ALDH2 in 41 HCC tissues by immunohistochemistry. The clinicopathological meaning and molecular function of ALDH2 were analyzed and evaluated through comprehensive bioinformatics. ALDH2 expression in HCC was validated in TCGA, GEO and Oncomine databases, and a survival of ALDH2 based on TCGA database was analysed. LinkedOmics was used to classify the co-expressed genes of ALDH2 and its regulatory factors. The relation between ALDH2 and immune infiltration in HCC was further explored by TIMER. IHC results showed decreased levels of ALDH2 in HCC tumor tissues compared with corresponding normal liver tissues. The pathological grade and prognosis of patients with low expression of the ALDH2 gene were worse. Bioinformatics analysis results showed that ALDH2 was considerably down-regulated in cancer tissues compared with corresponding normal liver tissues in 8 GEO series and TCGA profile (all P<0.05). A nomogram was designed using expression of ALDH2 and clinical factors. ALDH2 was correlated with dendritic cells and macrophages in immune infiltration. In conclusion, ALDH2 has significant prognostic value in hepatocellular carcinoma and they may play key roles in regulating tumor progression and the immune cells infiltration. Our results suggest that ALDH2 may be a new type of tumor biomarker, which can be used to judge the prognosis, targeted therapy and immunotherapy of patients with HCC.

Exosome-derived miR-2682-5p suppresses cell viability and migration by HDAC1-silence-mediated upregulation of ADH1A in non-small cell lung cancer

Introduction: Increasing evidence indicated that miR-2682-5p acted as a tumor suppressor in various cancers. The current study aimed to investigate the biological function of exosomal miR-2682-5p in non-small cell lung cancer (NSCLC).Methods: The expression of miR-2682-5p in NSCLC tissues and adjacent non-tumor tissues, NSCLC cell lines and human embryonic lung fibroblast, as well as serum and serum exosomes of NSCLC patients and healthy donors was detected by RT-qPCR. The effects of miR-2682-5p on the viability, migration, and apoptosis of NSCLC cells were detected by CCK-8, Transwell, and flow cytometry assays. Dual-luciferase reporter gene and RNA immunoprecipitation assays were used to evalutate the relationship between miR-2682-5p and HDAC1.Results: Low expressed miR-2682-5p was found in tumor tissues, cell lines, serum, and serum exosomes of NSCLC patients. MiR-2682-5p overexpression suppressed NSCLC cell viability and migration and promoted apoptosis, while miR-2682-5p knockdown showed the opposite results. Furthermore, exosomes from healthy donor serum inhibited NSCLC cell viability and migration and promoted apoptosis. Dual-luciferase reporter gene and RNA immunoprecipitation assays verified that HDAC1 was a target of miR-2682-5p. HDAC1 overexpression abolished the effects of miR-2682-5p mimic on NSCLC cell viability, migration, and apoptosis. Chromatin immunoprecipitation assay indicated that HDAC1 bound to the promoter region of ADH1A. Upregulation of ADH1A counteracted the effects of HDAC1 overexpression on NSCLC cell viability, migration, and apoptosis.Conclusion: Taken together, exosomal miR-2682-5p inhibited NSCLC cell viability and migration and promoted apoptosis by the HDAC1/ADH1A axis, and this result might provide a novel therapeutic target for NSCLC.

The role of ALDH2 in tumorigenesis and tumor progression: Targeting ALDH2 as a potential cancer treatment

A major mitochondrial enzyme for protecting cells from acetaldehyde toxicity is aldehyde dehydrogenase 2 (ALDH2). The correlation between ALDH2 dysfunction and tumorigenesis/growth/metastasis has been widely reported. Either low or high ALDH2 expression contributes to tumor progression and varies among different tumor types. Furthermore, the ALDH2∗2 polymorphism (rs671) is the most common single nucleotide polymorphism (SNP) in Asia. Epidemiological studies associate ALDH2∗2 with tumorigenesis and progression. This study summarizes the essential functions and potential ALDH2 mechanisms in the occurrence, progression, and treatment of tumors in various types of cancer. Our study indicates that ALDH2 is a potential therapeutic target for cancer therapy.

Role of ALDH2 in Hepatic Disorders: Gene Polymorphism and Disease Pathogenesis

Aldehyde dehydrogenase 2 (ALDH2) is a key enzyme of alcohol metabolism and it is involved in the cellular mechanism of alcohol liver disease. ALDH2 gene mutations exist in about 8% of the world's population, with the incidence reaching 45% in East Asia. The mutations will result in impairment of enzyme activity and accumulation of acetaldehyde, facilitating the progression of other liver diseases, including non-alcoholic fatty liver diseases, viral hepatitis and hepatocellular carcinoma, through adduct formation and inflammatory responses. In this review, we seek to summarize recent research progress on the correlation between ALDH2 gene polymorphism and multiple liver diseases, with an attempt to provide clues for better understanding of the disease mechanism and for strategy making.

Prognostic implications of alcohol dehydrogenases in hepatocellular carcinoma

Background

Hepatocellular carcinoma (HCC) is a malignancy with high incidence and mortality rates worldwide. Alcohol dehydrogenases (ADHs) are huge family of dehydrogenase enzymes and associated with the prognosis of various cancers. However, comprehensive analysis of prognostic implications related to ADHs in HCC is still lacking and largely unknown.

Methods

The expression profiles and corresponding clinical information of HCC were obtained from The Cancer Genome Atlas (TCGA). Wilcoxon signed-rank test was employed to evaluate the expression of ADHs. Cox regression and Kaplan-Meier analyses were used to investigate the association between clinicopathological characteristics and survival. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses were performed and visualized using R/BiocManager package.

Results

We found that the expression of ADH1A, ADH1B, ADH1C, ADH4, and ADH6 was significantly downregulated in HCC samples compared to normal liver samples. Our univariate and multivariate Cox regression analyses results showed that high expression of ADH1A, ADH1B, ADH1C, ADH4, and ADH6 was considered as an independent factor with an improved prognosis for the survival of HCC patients. Moreover, our Kaplan-Meier analysis results also revealed that high expression of AHD1A, ADH1B, ADH1C, ADH4, and ADH6 was significantly associated with good survival rate in HCC patients. In addition, GO, KEGG, and GSEA analyses unveiled several oncogenic signaling pathways were negatively associated high expression of ADHs in HCC.

Conclusion

In the present study, our results provide the potential prognostic biomarkers or molecular targets for the patients with HCC.

Construction of a prognosis-predicting model based on autophagy-related genes for hepatocellular carcinoma (HCC) patients

Background: Autophagy, a highly conserved cellular catabolic process by which the eukaryotic cells deliver autophagosomes engulfing cellular proteins and organelles to lysosomes for degradation, is critical for maintaining cellular homeostasis in response to various signals and nutrient stresses. The dysregulation of autophagy has been noted in the pathogenesis of cancers. Our study aims to investigate the prognosis-predicting value of autophagy-related genes (ARG) in hepatocellular carcinoma (HCC).

Results: The signature was constructed based on eight ARGs, which stratified HCC patients into high- and low-risk groups in terms of overall survival (OS) (Hazard Ratio, HR=4.641, 95% Confidential Interval, CI, 3.365-5.917, P=0.000). The ARG signature is an independent prognostic indicator for HCC patients (HR = 1.286, 95% CI, 1.194-1.385; P < 0.001). The area under the receiver operating characteristic (ROC) curve (AUC) for 5-year survival is 0.765.

Conclusion: This study provides a potential prognostic signature for predicting the prognosis of HCC patients and molecular insights into the significance of autophagy in HCC.

Methods: Sixty-two differentially expressed ARGs and the clinical characteristics and basic information of the 369 enrolled HCC patients were retrieved from The Cancer Genome Atlas (TCGA) database. the Cox proportional hazard regression analysis was adopted to identify survival-related ARGs, based on which a prognosis predicting signature was constructed.

Functional crosstalk between mTORC1/p70S6K pathway and heterochromatin organization in stress-induced senescence of MSCs

Background

Stem cell senescence has been proposed as one of the major drivers of aging, and MSC senescence contributes to aging-related diseases. Activation of mTORC1 pathway and heterochromatin organization have been characterized as two characteristics of senescent cells; however, whether mTORC1 pathway interacts with heterochromatin organization and contributes to MSC senescence remains unknown. In this study, we investigated the interaction between heterochromatin organization and mTORC1/p70S6K pathway in stress-induced MSC senescence.

Methods

The stress-induced senescence models were established in human umbilical cord-derived MSCs by doxorubicin (Dox) or H₂O₂. Cellular senescence was evaluated by β-Gal activity, upregulation of cell cycle suppressor genes, and expression of SASP. Activation of heterochromatin organization and mTORC1 pathway was determined by Western blot and immunofluorescent staining. A D-galactose (D-Gal)-induced aging model was established in rats to evaluate the crosstalk between heterochromatin and mTORC1 pathway in vivo.

Results

We found that heterochromatin organization was provoked at the early stage of Dox- or H₂O₂-induced senescence. Disruption of heterochromatin organization led to robust DNA damage response and exacerbated cellular senescence. Suppression of mTORC1/p70S6K pathway by either rapamycin or p70S6K knockdown promoted heterochromatin organization and ameliorated Dox- or H₂O₂-induced DNA damage and senescence. In contrast, direct activation of mTORC1 by MHY1485 impaired heterochromatin organization and aggravated stress-induced senescence. Moreover, concomitant activation of mTORC1 pathway and heterochromatin organization was found in D-galactose-induced osteoporosis model in rats. Rapamycin alleviated cellular senescence and promoted heterochromatin organization in BMSCs derived from D-galactose-treated rats.

Conclusions

Altogether, our study indicates the existence of a complex interplay between the mTORC1/p70S6K pathway and the heterochromatin organization during stress-induced MSC senescence, with important implications for the understanding of aging as well as for its prevention and treatment.