ALDH2 Repression Promotes Lung Tumor Progression via Accumulated Acetaldehyde and DNA Damage

Targeting ALDH2 to augment platinum-based chemosensitivity through ferroptosis in lung adenocarcinoma

Ferroptosis is a regulated cell death driven by iron-dependent lipid peroxidation and associated with drug resistance in lung adenocarcinoma (LUAD). It's found that aldehyde dehydrogenase 2 (ALDH2), which is highly mutated in East Asian populations, is correlated with response to chemotherapy in LUAD patients. The rs671 variant knock-in, downregulation, and pharmacological inhibition of ALDH2 render LUAD cells more vulnerable to ferroptosis inducers and platinum-based chemotherapy. ALDH2 inhibits ferroptosis through the detoxification of 4-hydroxynonenal and malondialdehyde, the product of lipid peroxidation, as well as the production of NADH at the same time. Besides, ALDH2 deficiency leads to elevated intracellular pH (pHi), thus inhibiting the ERK/CREB1/GPX4 axis. Interestingly, ALDH2 is also regulated by CREB1, and the ALDH2 enzyme activity was decreased with elevated pHi. What's more, the elevated pHi caused by impaired ALDH2 activity promotes the biosynthesis of lipid droplets to counteract ferroptosis. At last, the effect of ALDH2 on ferroptosis and chemosensitivity is confirmed in patient-derived organoids and xenograft models. Collectively, this study demonstrates that ALDH2 deficiency confers sensitivity to platinum through ferroptosis in LUAD, and targeting ALDH2 is a promising new strategy to enhance the sensitivity of platinum-based chemotherapy for the treatment of LUAD patients.

Impaired Osteogenesis in Human Induced Pluripotent Stem Cells with Acetaldehyde Dehydrogenase 2 Mutations

Acetaldehyde dehydrogenase 2 (ALDH2) is the second enzyme involved in the breakdown of acetaldehyde into acetic acid during the process of alcohol metabolism. Roughly 40% of East Asians carry one or two ALDH2*2 alleles, and the presence of ALDH2 genetic mutations in individuals may affect the bone remodeling cycle owing to accumulation of acetaldehyde in the body. In this study, we investigated the effects of ALDH2 mutations on bone remodeling. In this study, we examined the effects of ALDH2 polymorphisms on in vitro osteogensis using human induced pluripotent stem cells (hiPSCs). We differentiated wild-type (ALDH2*1/*1-) and ALDH2*1/*2-genotyped hiPSCs into osteoblasts (OBs) and confirmed their OB characteristics. Acetaldehyde was administered to confirm the impact caused by the mutation during OB differentiation. Calcium deposits formed during osteogenesis were significantly decreased in ALDH2*1/*2 OBs. The expression of osteogenic markers were also decreased in acetaldehyde-treated OBs differentiated from the ALDH2*1/*2 hiPSCs. Furthermore, the impact of ALDH2 polymorphism and acetaldehyde-induced stress on inflammatory factors such as 4-hydroxynonenal and tumor necrosis factor α was confirmed. Our findings suggest that individuals with ALDH2 deficiency may face challenges in acetaldehyde breakdown, rendering them susceptible to disturbances in normal bone remodeling therefore, caution should be exercised regarding alcohol consumption. In this proof-of-concept study, we were able to suggest these findings as a result of a disease-in-a-dish concept using hiPSCs derived from individuals bearing a certain mutation. This study also shows the potential of patient-derived hiPSCs for disease modeling with a specific condition.

Integrated bioinformatics analysis and experimental validation to understand tryptophan metabolism-related genes in hepatocellular carcinoma

Background: Tryptophan (Trp) metabolism is closely related to tumor immunity, and its disorder can cause an immunosuppressive microenvironment, promoting the occurrence and development of hepatocellular carcinoma (HCC). The aim of this study is to explore and validate the independent prognostic genes in patients suffered from HCC. Methods: The transcriptome data of GSE87630 from GEO database were downloaded to analyze differentially expressed genes (DECs) which were intersected with the gene sets of Trp metabolism from MsigDB database. Univariate/multivariate COX regression was performed to identify the genes with independent prognostic significance. TCGA, GTEx, UALCAN, and GEPIA2 databases were applied to analyze DEGs for prognosis. RNA seq data of HCC from TCGA database were collected for Lasso regression analysis. The ssGSEA algorithm was used to perform the analysis of TCGA data. The effects of the candidate differential gene on HCC cells proliferation and migration were evaluated using EdU immunofluorescence and transwell assays. Results: Trp metabolism-related DECs for HCCs were obtained, including MAOB, CYP1A2, KYNU, CYP2E1, ALDH2, CYP2C18, TDO2, AOX1, CYP3A4 and INMT. Moreover, multivariate COX regression results showed that ALDH2 can serve as an independent prognostic molecule and its transcriptional and translational levels were significantly reduced in the tumor tissues. The low expression of ALDH2 was associated with poor prognosis. Overexpression of ALDH2 dramatically reduced the HCC cells proliferation and migration. Conclusion: ALDH2 is associated with Trp metabolism and its downregulation in HCC has a potential value on prognosis. Overexpression of ALDH2 can reduce the proliferation and migration of HCC cells.

Aldehyde dehydrogenase 2 family member repression promotes colorectal cancer progression by JNK/p38 MAPK pathways-mediated apoptosis and DNA damage

BACKGROUND

Aldehyde (ALDH2) dysfunction has been verified to contribute to human cancers.

AIM

To investigate the molecular mechanism and biological function of ALDH2 in colorectal cancer (CRC) progression.

METHODS

Human CRC cells with high expression of ALDH2 were screened. After shRNA ALDH2 (sh-ALDH2) transfection, phenotypes [proliferation, apoptosis, acetaldehyde (ACE) accumulation, DNA damage] of CRC cells were verified using cell counting kit-8, flow cytometry, ACE assay, and comet assays. Western blotting was used for evaluation of the apoptosis proteins (Bax and Bcl-2) and JNK/p38 MAPK pathway-associated proteins. We subjected CVT-10216 (a selective ALDH2 inhibitor) to nude mice for establishment of SK-CO-1 mouse xenograft model and observed the occurrence of CRC.

RESULTS

The inhibition of ALDH2 could promote the malignant structures of CRC cells, including apoptosis, ACE level, and DNA damage, and cell proliferation was decreased in the sh-ALDH2 group, whereas ALDH2 agonist Alda-1 reversed features. ALDH2 repression can cause ACE accumulation, whereas ACE enhanced CRC cell features related to increased DNA damage. Additionally, ALDH2 repression led to JNK/P38 MAPK activation, and apoptosis, ACE accumulation, and DNA damage were inhibited after p38 MAPK inhibitor SB203580 and JNK inhibitor SP600125 addition. ACE accumulation and raised DNA damage were recognized in CVT-10216 treated-mouse tumor tissues in vivo.

CONCLUSION

The repression of ALDH2 led to ACE accumulation, inducing cell apoptosis and DNA damage by the JNK/p38 MAPK signaling pathway activation in CRC.

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.

Aldehyde Dehydrogenase 2 (ALDH2): A novel sorafenib target in hepatocellular carcinoma unraveled by the proteome-wide cellular thermal shift assay

Sorafenib is a multikinase inhibitor indicated for first-line treatment of unresectable hepatocellular carcinoma. Despite its widespread use in the clinic, the existing knowledge of sorafenib mode-of-action remains incomplete. To build upon the current understanding, we used the Cellular Thermal Shift Assay (CETSA) coupled to Mass Spectrometry (CETSA-MS) to monitor compound binding to its target proteins in the cellular context on a proteome-wide scale. Among the potential sorafenib targets, we identified aldehyde dehydrogenase 2 (ALDH2), an enzyme that plays a major role in alcohol metabolism. We validated the interaction of sorafenib with ALDH2 by orthogonal methods using pure recombinant protein, proving that this interaction is not mediated by other cellular components. Moreover, we showed that sorafenib inhibits ALDH2 activity, supporting a functional role for this interaction. Finally, we were able to demonstrate that both ALDH2 protein expression and activity were reduced in sorafenib-resistant cells compared to the parental cell line. Overall, our study allowed the identification of ALDH2 as a novel sorafenib target and sheds light on its potential role in both hepatocellular carcinoma and sorafenib resistance condition.

ALDH2 is a novel biomarker and exerts an inhibitory effect on melanoma

Melanoma is a malignant skin tumor. This study aimed to explore and assess the effect of novel biomarkers on the progression of melanoma. Differently expressed genes (DEGs) were screened from GSE3189 and GSE46517 datasets of Gene Expression Omnibus database using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted based on the identified DEGs. Hub genes were identified and assessed using protein-protein interaction networks, principal component analysis, and receiver operating characteristic curves. Quantitative real-time polymerase chain reaction was employed to measure the mRNA expression levels. TIMER revealed the association between aldehyde dehydrogenase 2 (ALDH2) and tumor immune microenvironment. The viability, proliferation, migration, and invasion were detected by cell counting kit-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Total 241 common DEGs were screened out from GSE3189 and GSE46517 datasets. We determined 6 hub genes with high prediction values for melanoma, which could distinguish tumor samples from normal samples. ALDH2, ADH1B, ALDH3A2, DPT, EPHX2, and GATM were down-regulated in A375 and SK-MEL-2 cells, compared with the human normal melanin cell line (PIG1 cells). ALDH2 was selected as the candidate gene in this research, presenting a high diagnostic and predictive value for melanoma. ALDH2 had a positive correlation with the infiltrating levels of immune cells in melanoma microenvironment. Overexpression of ALDH2 inhibited cell viability, proliferation, migration, and invasion of A375/SK-MEL-2 cells. ALDH2 is a new gene biomarker of melanoma, which exerts an inhibitory effect on melanoma.

Endoplasmic reticulum stress in the pathogenesis of alcoholic liver disease

The endoplasmic reticulum (ER) plays a pivotal role in protein synthesis, folding, and modification. Under stress conditions such as oxidative stress and inflammation, the ER can become overwhelmed, leading to an accumulation of misfolded proteins and ensuing ER stress. This triggers the unfolded protein response (UPR) designed to restore ER homeostasis. Alcoholic liver disease (ALD), a spectrum disorder resulting from chronic alcohol consumption, encompasses conditions from fatty liver and alcoholic hepatitis to cirrhosis. Metabolites of alcohol can incite oxidative stress and inflammation in hepatic cells, instigating ER stress. Prolonged alcohol exposure further disrupts protein homeostasis, exacerbating ER stress which can lead to irreversible hepatocellular damage and ALD progression. Elucidating the contribution of ER stress to ALD pathogenesis may pave the way for innovative therapeutic interventions. This review delves into ER stress, its basic signaling pathways, and its role in the alcoholic liver injury.

Integrative Analysis of Single-Cell and Bulk RNA Sequencing Reveals Prognostic Characteristics of Macrophage Polarization-Related Genes in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is a group of cancers with poor prognosis. The combination of single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing (RNA-seq) can identify important genes involved in cancer development and progression from a broader perspective.

Methods

The scRNA-seq data and bulk RNA-seq data of LUAD were downloaded from the Gene Expression Omnibus (GEO) database and the Cancer Genome Atlas (TCGA) database. Analyzing scRNA-seq for core cells in the GSE131907 dataset, and the uniform manifold approximation and projection (UMAP) was used for dimensionality reduction and cluster identification. Macrophage polarization-associated subtypes were acquired from the TCGA-LUAD dataset after analysis, followed by further identification of differentially expressed genes (DEGs) in the TCGA-LUAD dataset (normal/LUAD tissue samples, two subtypes). Venn diagrams were utilized to visualize differentially expressed and highly variable macrophage polarization-related genes. Subsequently, a prognostic risk model for LUAD patients was constructed by univariate Cox and Least Absolute Shrinkage and Selection Operator (LASSO), and the model was investigated for stability in the external data GSE72094. After analyzing the correlation between the trait genes and significantly mutated genes, the immune infiltration between the high/low-risk groups was then examined. The Monocle package was applied to analyze the pseudo-temporal trajectory analysis of different cell clusters in macrophage clusters. Subsequently, cell clusters of data macrophages were selected as key cell clusters to explore the role of characteristic genes in different cell populations and to identify transcription factors (TFs) that affect signature genes. Finally, qPCR were employed to validate the expression levels of prognosis signature genes in LUAD.

Results

424 macrophage highly variable genes, 3920 DEGs, and 9561 DEGs were obtained from macrophage clusters, the macrophage polarization-related subtypes, and normal/LUAD tissue samples, respectively. Twenty-eight differentially expressed and highly mutated MPRGs were obtained. A prognostic risk model with 7 DE-MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) was constructed. This prognostic model still has a good prediction effect in the GSE72094 dataset. ZNF536 and DNAH9 were mutated in the low-risk group, while COL11A1 was mutated in the high-risk group, and they were highly correlated with the characteristic genes. A total of 11 immune cells were significantly different in the high/low-risk groups. Five cell types were again identified in the macrophage cluster, and then NK cells: CD56hiCD62L+ differentiated earlier and were present mainly on 2 branches. While macrophages were present on 2 branches and differentiated later. It was found that the expression levels of BCLAF1 and MAX were higher in cluster 1, which might be the TFs affecting the expression of the characteristic genes. Moreover, qPCR confirmed that the expression of the prognosis genes was generally consistent with the results of the bioinformatic analysis.

Conclusion

Seven MPRGs (RGS13, ADRB2, DDIT4, MS4A2, ALDH2, CTSH, and PKM) were identified as prognostic genes for LUAD and revealed the mechanisms of MPRGs at the single-cell level.

Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma

BACKGROUND

Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunotherapy significantly. As such, dendritic cells are important in killing tumors and influencing tumor microenvironment, whereas their roles in lung adenocarcinoma (LUAD) are largely unknown.

METHODS

In this study, 1658 LUAD patients from different cohorts were included. In addition, 724 cancer patients who received immunotherapy were also included. To identify DC marker genes in LUAD, we used single-cell RNAsequencing data for analysis and determined 83 genes as DC marker genes. Following that, integrative machine learning procedure was developed to construct a signature for DC marker genes.

RESULTS

Using TCGA bulk-RNA sequencing data as the training set, we developed a signature consisting of seven genes and classified patients by their risk status. Another six independent cohorts demonstrated the signature' s prognostic power, and multivariate analysis demonstrated it was an independent prognostic factor. LUAD patients in the high-risk group displayed more advanced features, discriminatory immune-cell infiltrations and immunosuppressive states. Cell-cell communication analysis indicates that tumor cells with lower risk scores communicate more actively with the tumor microenvironment. Eight independent immunotherapy cohorts revealed that patients with low-risk had better immunotherapy responses. Drug sensitivity analysis indicated that targeted therapy agents exhibited greater sensitivity to low-risk patients, while chemotherapy agents displayed greater sensitivity to high-risk patients. In vitro experiments confirmed that CTSH is a novel protective factor for LUAD.

CONCLUSIONS

An unique signature based on DC marker genes that is highly predictive of LUAD patients' prognosis and response to immunotherapy. CTSH is a new biomarker for LUAD.

In-depth single-cell and bulk-RNA sequencing developed a NETosis-related gene signature affects non-small-cell lung cancer prognosis and tumor microenvironment: results from over 3,000 patients

Background

Cell death caused by neutrophil extracellular traps (NETs) is known as NETosis. Despite the increasing importance of NETosis in cancer diagnosis and treatment, its role in Non-Small-Cell Lung Cancer (NSCLC) remains unclear.

Methods

A total of 3298 NSCLC patients from different cohorts were included. The AUCell method was used to compute cells' NETosis scores from single-cell RNA-sequencing data. DEGs in sc-RNA dataset were obtained by the Seurat's "FindAllMarkers" function, and DEGs in bulk-RNA dataset were acquired by the DESeq2 package. ConsensusClusterPlus package was used to group patients into different NETosis subtypes, and the Enet algorithm was used to construct the NETosis-Related Riskscore (NETRS). Enrichment analyses were conducted using the GSVA and ClusterProfiler packages. Six distinct algorithms were utilized to evaluate patients' immune cell infiltration level. Patients' SNV and CNV data were analyzed by maftools and GISTIC2.0, respectively. Drug information was obtained from the GDSC1, and predicted by the Oncopredict package. Patient response to immunotherapy was evaluated by the TIDE algorithm in conjunction with the phs000452 immunotherapy cohort. Six NRGs' differential expression was verified using qRT-PCR and immunohistochemistry.

Results

Among all cell types, neutrophils had the highest AUCell score. By Intersecting the DEGs between high and low NETosis classes, DEGs between normal and LUAD tissues, and prognostic related genes, 61 prognostic related NRGs were identified. Based on the 61 NRGs, all LUAD patients can be divided into two clusters, showing different prognostic and TME characteristics. Enet regression identified the NETRS composed of 18 NRGs. NETRS significantly associated with LUAD patients' clinical characteristics, and patients at different NETRS groups showed significant differences on prognosis, TME characteristics, immune-related molecules' expression levels, gene mutation frequencies, response to immunotherapy, and drug sensitivity. Besides, NETRS was more powerful than 20 published gene signatures in predicting LUAD patients' survival. Nine independent cohorts confirmed that NETRS is also valuable in predicting the prognosis of all NSCLC patients. Finally, six NRGs' expression was confirmed using three independent datasets, qRT-PCR and immunohistochemistry.

Conclusion

NETRS can serves as a valuable prognostic indicator for patients with NSCLC, providing insights into the tumor microenvironment and predicting the response to cancer therapy.

Host ALDH2 deficiency aggravates nonalcoholic steatohepatitis through gut-liver axis

Nonalcoholic steatohepatitis (NASH) is the major cause of liver dysfunction. Animal and population studies have shown that mitochondrial aldehyde dehydrogenase (ALDH2) is implicated in fatty liver disease. However, the role of ALDH2 in NASH and the underlying mechanisms remains unclear. To address this issue, ALDH2 knockout (ALDH2-/-) mice and wild-type littermate mice were fed a methionine-and choline-deficient (MCD) diet to induce a NASH model. Fecal, serum, and liver samples were collected and analyzed to investigate the impact of the gut microbiota and bile acids on this process. We found that MCD-fed ALDH2-/- mice exhibited increased serum pro-inflammation cytokines, hepatic inflammation and fat accumulation than their wild-type littermates. MCD-fed ALDH2-/- mice exhibited worsened MCD-induced intestinal inflammation and barrier damage, and gut microbiota disorder. Furthermore, mice receiving microbiota from MCD-fed ALDH2-/- mice had increased severity of NASH compared to those receiving microbiota from MCD-fed wild-type mice. Notably, the intestinal Lactobacillus was significantly reduced in MCD-fed ALDH2-/- mice, and gavage with Lactobacillus cocktail significantly improved MCD-induced NASH. Finally, we found that ALDH2-/- mice had reduced levels of bile salt hydrolase and specific bile acids, especially lithocholic acid (LCA), accompanied by downregulated expression of the intestinal FXR-FGF15 pathway. Supplementation of LCA in ALDH2-/- mice upregulated intestinal FXR-FGF15 pathway and alleviated NASH. In summary, ALDH2 plays a critical role in the development of NASH through modulation of gut microbiota and bile acid. The findings suggest that supplementing with Lactobacillus or LCA could be a promising therapeutic approach for treating NASH exacerbated by ALDH2 deficiency.

Dissecting the alternation landscape of mitochondrial metabolism-related genes in lung adenocarcinoma and their latent mechanisms

Lung adenocarcinoma (LUAD) is the most common histological subtype of lung cancer with high incidence and unsatisfactory prognosis. The majority of LUAD patients eventually succumb to local and/or distinct metastatic recurrence. Genomic research of LUAD has broadened our understanding of this disease's biology and improved target therapies. However, the alternation landscape and characteristics of mitochondrial metabolism-related genes (MMRGs) in LUAD progression remain poorly understood. We performed a comprehensive analysis to identify the function and mechanism of MMRGs in LUAD based on the TCGA and GEO databases, which might offer therapeutic values for clinical researchers. Then, we figured out three hub prognosis-associated MMRGs (also termed as PMMRGs: ACOT11, ALDH2, and TXNRD1) that were engaged in the evolution of LUAD. To investigate the correlation between clinicopathological characteristics and MMRGs, we divided LUAD samples into two clusters (C1 and C2) based on key MMRGs. In addition, important pathways and the immune infiltration landscape affected by LUAD clusters were also delineated. Further, we nominated potential regulatory mechanisms underlying the MMRGs in LUAD development and progression. In conclusion, our integrative analysis enables a more comprehensive understanding of the mutation landscape of MMRGs in LUAD and provides an opportunity for more precise treatment.

Analysis of Aldehyde Dehydrogenase 2 as a Prognostic Marker Associated with Immune Cell infiltration and Chemotherapy Efficacy in Head and Neck Squamous Cell Carcinoma

Background: Previous investigations have demonstrated the role of Aldehyde Dehydrogenase 2 (ALDH2) levels in the cancer initiation and progression, prognosis, and treatment response in kinds of malignancies. However, its significance in the head and neck squamous cell carcinoma (HNSC) by different human papillomavirus (HPV) statuses remains unclear. Methods: We conducted an in-depth analysis of ALDH2 in HNSC using various bioinformatics tools, investigating its expression, alteration, differential levels, prognostic significance, molecular interactions, immune characteristics, and conducting experimental validation through immunohistochemistry (IHC) arrays and Western blot to compare expression levels between tumor and normal tissues, analyze the associations with clinicopathological features, and investigate its responses to chemotherapies. Results: ALDH2 levels are downregulated in HNSC tissues and associated with higher American Joint Committee on Cancer (AJCC) T classification and worse overall survival in HPV-unrelated HNSC, yet not in HPV-related HNSC. ALDH2 is positively regulated by copy-number variation and negatively regulated by DNA methylation. The association of ALDH2 with prognosis may be due to its interaction with ALDH6A1, and its co-expressed genes are predictive biomarkers of HNSC. We also found high ALDH2 levels in bulk tumors are associated with increased immune surveillance cells, such as naïve B cells and M1 macrophages in HPV-unrelated HNSC. IHC and western blot showed that ALDH2 is downregulated in the oral cavity, hypopharyngeal cancers, and well-differentiated carcinoma. In vitro, low ALDH2 levels showed reduced response to 5-fluorouracil in HNSC-derived cell lines. Conclusion: Our analyses revealed the genetic and cellular targets and drug response of ALDH2 in HNSC. We also found ALDH2 is involved in regulating the immune response of the tumor microenvironment, and high levels of ALDH2 in bulk HNSC may enhance antitumor immunity, which could improve prognosis. These findings suggest that ALDH2 could be a potential biomarker in improving risk stratification and tailoring treatment strategies in HNSC patients, especially in the HPV-unrelated subgroup.

ALDH2 promotes cancer stemness and metastasis in colorectal cancer through activating β-catenin signaling

Colorectal cancer (CRC) is the primary cause of death from gastrointestinal cancers. Aldehyde dehydrogenase 2 (ALDH2), a crucial mitochondrial enzyme for the oxidative pathway of alcohol metabolism, plays a dual role in cancer progression. In some cancers, it is tumor suppressive; in others, it drives cancer progression. However, whether targeting ALDH2 has any therapeutic implications or prognostic value in CRC is still unclear. Here, we investigated the role of ALDH2 in CRC progression by targeting its enzymatic activity rather than gene expression. We found that inhibiting ALDH2 by CVT-10216 and daidzein significantly decrease migration and stemness properties of both DLD-1 and HCT 116 cells, whereas activating ALDH2 by Alda-1 enhances migration rate. Concomitantly, ALDH2 inhibition by both CVT-10216 and daidzein downregulates the mRNA levels of fibronectin, snail, twist, MMP7, CD44, c-Myc, SOX2, and OCT-4, which are oncogenic in the advanced stage of CRC. Furthermore, Gene Set Enrichment Analysis (GSEA) on ALDH2 co-expressed genes from The Cancer Genome Atlas (TCGA) revealed that MYC target gene sets are upregulated. We found that ALDH2 inhibition decreased the nuclear protein levels of pGSK3β serine 9 and c-Myc. This suggests that ALDH2 probably targets β-catenin signaling in CRC cells. Together, our results demonstrate the prognostic value of ALDH2 in CRC as it regulates both CRC stemness and migration. Our findings also propose that the plant-derived isoflavone daidzein could be a potential chemotherapeutic drug targeting ALDH2 in CRC.

Pathogenic mechanisms and regulatory factors involved in alcoholic liver disease

Alcoholism is a widespread and damaging behaviour of people throughout the world. Long-term alcohol consumption has resulted in alcoholic liver disease (ALD) being the leading cause of chronic liver disease. Many metabolic enzymes, including alcohol dehydrogenases such as ADH, CYP2E1, and CATacetaldehyde dehydrogenases ALDHsand nonoxidative metabolizing enzymes such as SULT, UGT, and FAEES, are involved in the metabolism of ethanol, the main component in alcoholic beverages. Ethanol consumption changes the functional or expression profiles of various regulatory factors, such as kinases, transcription factors, and microRNAs. Therefore, the underlying mechanisms of ALD are complex, involving inflammation, mitochondrial damage, endoplasmic reticulum stress, nitrification, and oxidative stress. Moreover, recent evidence has demonstrated that the gut-liver axis plays a critical role in ALD pathogenesis. For example, ethanol damages the intestinal barrier, resulting in the release of endotoxins and alterations in intestinal flora content and bile acid metabolism. However, ALD therapies show low effectiveness. Therefore, this review summarizes ethanol metabolism pathways and highly influential pathogenic mechanisms and regulatory factors involved in ALD pathology with the aim of new therapeutic insights.

Odorant-responsive biological receptors and electronic noses for volatile organic compounds with aldehyde for human health and diseases: A perspective review

Volatile organic compounds (VOCs) are gaseous chemicals found in ambient air and exhaled breath. In particular, highly reactive aldehydes are frequently found in polluted air and have been linked to various diseases. Thus, extensive studies have been carried out to elucidate disease-specific aldehydes released from the body to develop potential biomarkers for diagnostic purposes. Mammals possess innate sensory systems, such as receptors and ion channels, to detect these VOCs and maintain physiological homeostasis. Recently, electronic biosensors such as the electronic nose have been developed for disease diagnosis. This review aims to present an overview of natural sensory receptors that can detect reactive aldehydes, as well as electronic noses that have the potential to diagnose certain diseases. In this regard, this review focuses on eight aldehydes that are well-defined as biomarkers in human health and disease. It offers insights into the biological aspects and technological advances in detecting aldehyde-containing VOCs. Therefore, this review will aid in understanding the role of aldehyde-containing VOCs in human health and disease and the technological advances for improved diagnosis.

Disruption of the Molecular Regulation of Mitochondrial Metabolism in Airway and Lung Epithelial Cells by Cigarette Smoke: Are Aldehydes the Culprit?

Chronic obstructive pulmonary disease (COPD) is a devastating lung disease for which cigarette smoking is the main risk factor. Acetaldehyde, acrolein, and formaldehyde are short-chain aldehydes known to be formed during pyrolysis and combustion of tobacco and have been linked to respiratory toxicity. Mitochondrial dysfunction is suggested to be mechanistically and causally involved in the pathogenesis of smoking-associated lung diseases such as COPD. Cigarette smoke (CS) has been shown to impair the molecular regulation of mitochondrial metabolism and content in epithelial cells of the airways and lungs. Although it is unknown which specific chemicals present in CS are responsible for this, it has been suggested that aldehydes may be involved. Therefore, it has been proposed by the World Health Organization to regulate aldehydes in commercially-available cigarettes. In this review, we comprehensively describe and discuss the impact of acetaldehyde, acrolein, and formaldehyde on mitochondrial function and content and the molecular pathways controlling this (biogenesis versus mitophagy) in epithelial cells of the airways and lungs. In addition, potential therapeutic applications targeting (aldehyde-induced) mitochondrial dysfunction, as well as regulatory implications, and the necessary required future studies to provide scientific support for this regulation, have been covered in this review.

ALDH2 as a potential stem cell-related biomarker in lung adenocarcinoma: Comprehensive multi-omics analysis

Lung adenocarcinoma (LUAD) is the most prevalent lung cancer and one of the leading causes of death. Previous research found a link between LUAD and Aldehyde Dehydrogenase 2 (ALDH2), a member of aldehyde dehydrogenase gene (ALDH) superfamily. In this study, we identified additional useful prognostic markers for early LUAD identification and targeting LUAD therapy by analyzing the expression level, epigenetic mechanism, and signaling activities of ALDH2 in LUAD patients. The obtained results demonstrated that ALDH2 gene and protein expression significantly downregulated in LUAD patient samples. Furthermore, The American Joint Committee on Cancer (AJCC) reported that diminished ALDH2 expression was closely linked to worse overall survival (OS) in different stages of LUAD. Considerably, ALDH2 showed aberrant DNA methylation status in LUAD cancer. ALDH2 was found to be downregulated in the proteomic expression profile of several cell biology signaling pathways, particularly stem cell-related pathways. Finally, the relationship of ALDH2 activity with stem cell-related factors and immune system were reported. In conclusion, the downregulation of ALDH2, abnormal DNA methylation, and the consequent deficit of stemness signaling pathways are relevant prognostic and therapeutic markers in LUAD.

Association of Different Combinations of ALDH2 rs671, APOE rs429358, rs7412 Polymorphisms with Hypertension in Middle-Aged and Elderly People: A Case-Control Study

Background

Hypertensive patients have a younger trend, and studies on the role of genetic factors in hypertension susceptibility have been inconsistent. Aldehyde dehydrogenases 2 (ALDH2) and apolipoprotein E (APOE) are involved in the pathophysiological processes of hypertension. To investigate the relationship of ALDH2 and APOE polymorphisms with hypertension in middle-aged (30-59 years old) and elderly (≥60 years old) persons.

Methods

Two thousand six hundred and ten hypertensive patients and 1921 controls were included (between 30 and 100 years old). The genotypes of common polymorphisms in APOE and ALDH2 genes (APOE rs429358, rs7412, and ALDH2 rs671) of the subjects were analyzed by polymerase-chain reaction (PCR)-microarray. Statistical analyses (Student's t-test, Mann-Whitney U-test, χ ² test, and logistic regression analysis) were performed with SPSS v21.0.

Results

There were 4531 participants (66.60 ± 12.10 years old) in this study, including 3057 (67.5%) males and 1474 (32.5%) females. There were no significant differences in distributions of ALDH2 rs671, APOE rs429358/rs7412 genotypes and alleles between hypertensive patients and controls. Persons with ALDH2 rs671 G/A or A/A genotype were less likely to have hypertension (G/A+A/A vs G/G: gender-, age-, smoking-, and drinking-adjusted OR 0.885, 95% CI 0.785-0.997, P=0.045), while ALDH2 rs671 A/A+APOE rs429358 or rs7412 wild-type genotype may decrease the risk of hypertension. In middle-aged group, ALDH2 rs671 G/A+APOE rs429358 T/C carriers (adjusted OR 0.547, 95% CI 0.350-0.856, P=0.008), and ALDH2 rs671 A/A+APOE rs7412 C/C genotypes (adjusted OR 0.567, 95% CI 0.361-0.891, P=0.014) were less likely to have hypertension. In elderly group, APOE rs7412 T/T carriers were more likely to have hypertension (rs671 T/T vs C/C: adjusted OR 4.755, 95% CI 1.075-21.027, P=0.040; rs671 T/T vs C/C or C/T: adjusted OR 4.734, 95% CI 1.071-20.928, P=0.040).

Conclusion

Polymorphism-polymorphism interactions of ALDH2 rs671 and APOE rs429358/rs7412 may effect on hypertension susceptibility. Different genotypes comparison shows different roles in middle-aged and elderly people, respectively.

Identification and validation of a risk model and molecular subtypes based on tryptophan metabolism-related genes to predict the clinical prognosis and tumor immune microenvironment in lower-grade glioma

Background

Lower-grade glioma (LGG) is one of the most common malignant tumors in the central nervous system (CNS). Accumulating evidence have demonstrated that tryptophan metabolism is significant in tumor. Therefore, this study aims to comprehensively clarify the relationship between tryptophan metabolism-related genes (TRGs) and LGGs.

Methods

The expression level of TRGs in LGG and normal tissues was first analyzed. Next, the key TRGs with prognostic value and differential expression in LGGs were identified using the least absolute shrinkage and selection operator (LASSO) regression analysis. Subsequently, a risk model was constructed and Consensus clustering analysis was conducted based on the expression level of key TRGs. Then, the prognostic value, clinicopathological factors, and tumor immune microenvironment (TIME) characteristics between different risk groups and molecular subtypes were analyzed. Finally, the expression, prognosis, and TIME of each key TRGs were analyzed separately in LGG patients.

Results

A total of 510 patients with LGG from The Cancer Genome Atlas (TCGA) dataset and 1,152 normal tissues from the Genotype-Tissue Expression (GTEx) dataset were included to evaluate the expression level of TRGs. After LASSO regression analysis, we identified six key TRGs and constructed a TRGs risk model. The survival analysis revealed that the risk model was the independent predictor in LGG patients. And the nomogram containing risk scores and independent clinicopathological factors could accurately predict the prognosis of LGG patients. In addition, the results of the Consensus cluster analysis based on the expression of the six TRGs showed that it could classify the LGG patients into two distinct clusters, with significant differences in prognosis, clinicopathological factors and TIME between these two clusters. Finally, we validated the expression, prognosis and immune infiltration of six key TRGs in patients with LGG.

Conclusion

This study demonstrated that tryptophan metabolism plays an important role in the progression of LGG. In addition, the risk model and the molecular subtypes we constructed not only could be used as an indicator to predict the prognosis of LGG patients but also were closely related to the clinicopathological factors and TIME of LGG patients. Overall, our study provides theoretical support for the ultimate realization of precision treatment for patients with LGG.

High ALDH2 expression is associated with better prognosis in patients with gastric cancer

The relationship among alcohol, acetaldehyde, and gastric cancer (GC) is a very interesting research direction. Although many studies have focused on the correlation between ALDH2 polymorphism and GC, ALDH2 expression in GC and its relationship with the prognosis of GC patients remain to be fully understood. To explore these, 455 GC cases were included in this study. The relationships of ALDH2 expression with patients' survival and clinicopathological characteristics were assessed. The immune infiltration characteristics of ALDH2 in GC were also analyzed. Furthermore, the gene regulatory network and functional pathways of ALDH2 in GC were investigated. We found that high expression of ALDH2 was associated with better prognosis in GC patients. GC patients with high ALDH2 expression had a lower degree of pathological malignancy, consistent with our hypothesis that ALDH2 may play as a tumor suppressor role in GC. Mechanistically, ALDH2 may cooperate with genes such as C5orf32, TSPAN8 and RILP to inhibit GC progression via regulating multiple signaling pathways and chemical carcinogenesis. Therefore, our study suggested that ALDH2, an important variant gene in Asians, might serve as a prognostic marker and a potential therapeutic target for patients with GC.

Prognostic necroptosis-related gene signature aids immunotherapy in lung adenocarcinoma

Background: Necroptosis is a phenomenon of cellular necrosis resulting from cell membrane rupture by the corresponding activation of Receptor Interacting Protein Kinase 3 (RIPK3) and Mixed Lineage Kinase domain-Like protein (MLKL) under programmed regulation. It is reported that necroptosis is closely related to the development of tumors, but the prognostic role and biological function of necroptosis in lung adenocarcinoma (LUAD), the most important cause of cancer-related deaths, is still obscure. Methods: In this study, we constructed a prognostic Necroptosis-related gene signature based on the RNA transcription data of LUAD patients from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as well as the corresponding clinical information. Kaplan-Meier analysis, receiver operating characteristic (ROC), and Cox regression were made to validate and evaluate the model. We analyzed the immune landscape in LUAD and the relationship between the signature and immunotherapy regimens. Results: Five genes (RIPK3, MLKL, TLR2, TNFRSF1A, and ALDH2) were used to construct the prognostic signature, and patients were divided into high and low-risk groups in line with the risk score. Cox regression showed that risk score was an independent prognostic factor. Nomogram was created for predicting the survival rate of LUAD patients. Patients in high and low-risk groups have different tumor purity, tumor immunogenicity, and different sensitivity to common antitumor drugs. Conclusion: Our results highlight the association of necroptosis with LUAD and its potential use in guiding immunotherapy.

Alcohol as a Non-UV Social-Environmental Risk Factor for Melanoma

Although cancer mortality has declined among the general population, the incidence of melanoma continues to rise. While identifying high-risk cohorts with genetic risk factors improves public health initiatives and clinical care management, recognizing modifiable risk factors such as social-environmental risk factors would also affect the methods of patient outreach and education. One major modifiable social-environmental risk factor associated with melanoma is ultraviolet (UV) radiation. However, not all forms of melanoma are correlated with sun exposure or occur in sun-exposed areas. Additionally, UV exposure is rarely associated with tumor progression. Another social-environmental factor, pregnancy, does not explain the sharply increased incidence of melanoma. Recent studies have demonstrated that alcohol consumption is positively linked with an increased risk of cancers, including melanoma. This perspective review paper summarizes epidemiological data correlating melanoma incidence with alcohol consumption, describes the biochemical mechanisms of ethanol metabolism, and discusses how ethanol and ethanol metabolites contribute to human cancer, including melanoma.

Long Noncoding RNA SNHG16 Regulates the Growth of Human Lung Cancer Cells by Modulating the Expression of Aldehyde Dehydrogenase 2 (ALDH2)

The involvement of long noncoding RNA (lncRNA) SNHG16 has been reported in several human cancers. Notwithstanding, the role of lncRNA SNHG16 is yet largely unknown in human lung cancer. Consequently, this study was undertaken to investigate the role and therapeutic potential of SNHG16 in human lung cancer. The results showed a significant (P < 0.05) transcriptional upregulation of SNHG16 in lung cancer tissues and cell lines. However, downregulation of SNHG16 resulted in significant (P < 0.05) inhibition of lung cancer A549 and SK-LU-1 cell proliferation. DAPI and annexin V/PI assays revealed apoptosis to be responsible for inhibition of cell proliferation and colony formation observed upon SNHG16 knockdown. This was accompanied by enhancement of Bax and suppression of Bcl-2 expression in A549 and SK-LU-1 cells. Transwell assays revealed that silencing of SNHG16 also significantly (P < 0.05) inhibited migration and invasion of A549 and SK-LU-1 cells. Bioinformatic analysis revealed that SNHG16 interacted with ALDH2 to exert its effects in human lung cancer cells. The expression of ALDH2 was found to be significantly (P < 0.05) suppressed in human lung cancer tissues and cell lines. Overexpression of ALDH2 inhibited the proliferation and colony formation of the A549 and SK-LU-1 cells. However, silencing of ALDH2 could avoid the tumor-suppressive effects of SNHG16 knockdown. Finally, SNHG16 silencing was also found to inhibit in vivo tumor growth. Collectively, the study unveils the molecular role of SNHG16 in regulating the development of lung cancer by interacting with ALDH2.

Prognostic Implication of Energy Metabolism-Related Gene Signatures in Lung Adenocarcinoma

Background

Lung adenocarcinoma (LUAD) is the major non-small-cell lung cancer pathological subtype with poor prognosis worldwide. Herein, we aimed to build an energy metabolism-associated prognostic gene signature to predict patient survival.

Methods

The gene expression profiles of patients with LUAD were downloaded from the TCGA and GEO databases, and energy metabolism (EM)-related genes were downloaded from the GeneCards database. Univariate Cox and LASSO analyses were performed to identify the prognostic EM-associated gene signatures. Kaplan–Meier and receiver operating characteristic (ROC) curves were plotted to validate the predictive effect of the prognostic signatures. A CIBERSORT analysis was used to evaluate the correlation between the risk model and immune cells. A nomogram was used to predict the survival probability of LUAD based on a risk model.

Results

We constructed a prognostic signature comprising 13 EM-related genes (AGER, AHSG, ALDH2, CIDEC, CYP17A1, FBP1, GNB3, GZMB, IGFBP1, SORD, SOX2, TRH and TYMS). The Kaplan–Meier curves validated the good predictive ability of the prognostic signature in TCGA AND two GEO datasets (p<0.0001, p=0.00021, and p=0.0034, respectively). The area under the curve (AUC) of the ROC curves also validated the predictive accuracy of the risk model. We built a nomogram to predict the survival probability of LUAD, and the calibration curves showed good predictive ability. Finally, a functional analysis also unveiled the different immune statuses between the two different risk groups.

Conclusion

Our study constructed and verified a novel EM-related prognostic gene signature that could improve the individualized prediction of survival probability in LUAD.

Network based systems biology approach to identify diseasome and comorbidity associations of Systemic Sclerosis with cancers

Systemic Sclerosis (SSc) is an autoimmune disease associated with changes in the skin's structure in which the immune system attacks the body. A recent meta-analysis has reported a high incidence of cancer prognosis including lung cancer (LC), leukemia (LK), and lymphoma (LP) in patients with SSc as comorbidity but its underlying mechanistic details are yet to be revealed. To address this research gap, bioinformatics methodologies were developed to explore the comorbidity interactions between a pair of diseases. Firstly, appropriate gene expression datasets from different repositories on SSc and its comorbidities were collected. Then the interconnection between SSc and its cancer comorbidities was identified by applying the developed pipelines. The pipeline was designed as a generic workflow to demonstrate a premise comorbid condition that integrate regarding gene expression data, tissue/organ meta-data, Gene Ontology (GO), Molecular pathways, and other online resources, and analyze them with Gene Set Enrichment Analysis (GSEA), Pathway enrichment and Semantic Similarity (SS). The pipeline was implemented in R and can be accessed through our Github repository: https://github.com/hiddenntreasure/comorbidity. Our result suggests that SSc and its cancer comorbidities share differentially expressed genes, functional terms (gene ontology), and pathways. The findings have led to a better understanding of disease pathways and our developed methodologies may be applied to any set of diseases for finding any association between them. This research may be used by physicians, researchers, biologists, and others.

Commentary on: Evaluation of spice and herb as phyto-derived selective modulators of human retinaldehyde dehydrogenases using simple in vitro method

It is commonly known that aldehyde dehydrogenases (ALDHs) are a promising therapeutic target in many diseases. Bui et al. - the authors of the paper I am discussing here (Biosci Rep (2021) 41(5): BSR20210491; DOI: https://doi.org/10.1042/BSR20210491) - point that there is a lack of research on the use of spices and herbs as the sources of naturally occurring modulators of ALDH activity. In order to carry out this type of research, the authors prepared ethanolic extracts of 22 spices and herbs. The main objective of the study was to investigate retinaldehyde dehydrogenases (RALDHs), of which retinal is the main substrate and ALDH2, the mitochondrial isoform, having acetaldehyde as the main substrate. The obtained results indicated that the tested extracts exhibited differential regulatory effects on RALDHs/ALDH2 and some of them showed a potential selective inhibition of the activity of RALDHs.

FDX1 can Impact the Prognosis and Mediate the Metabolism of Lung Adenocarcinoma

Background: Lung cancer has emerged as one of the most common cancers in recent years. The mitochondrial electron transport chain (ETC) is closely connected with metabolic pathways and inflammatory response. However, the influence of ETC-associated genes on the tumor immune response and the pathogenesis of lung cancer is not clear and needs further exploration.

Methods: The RNA-sequencing transcriptome and clinical characteristic data of LUAD were downloaded from the Cancer Genome Atlas (TCGA) database. The LASSO algorithm was used to build the risk signature, and the prediction model was evaluated by the survival analysis and receiver operating characteristic curve. We explored the function of FDX1 through flow cytometry, molecular biological methods, and liquid chromatography–tandem mass spectrometry/mass spectrometry (LC–MS/MS).

Results: 12 genes (FDX1, FDX2, LOXL2, ASPH, GLRX2, ALDH2, CYCS, AKR1A1, MAOB, RDH16, CYBB, and CYB5A) were selected to build the risk signature, and the risk score was calculated with the coefficients from the LASSO algorithm. The 1-year, 3-year, and 5-year area under the curve (AUC) of ROC curves of the dataset were 0.7, 0.674, and 0.692, respectively. Univariate Cox analysis and multivariate Cox regression analysis indicated that the risk signature is an independent risk factor for LUAD patients. Among these genes, we focused on the FDX1 gene, and we found that knockdown of FDX1 neither inhibited tumor cell growth nor did it induce apoptosis or abnormal cell cycle distribution. But FDX1 could promote the ATP production. Furthermore, our study showed that FDX1 was closely related to the glucose metabolism, fatty acid oxidation, and amino acid metabolism.

Conclusion: Collectively, this study provides new clues about carcinogenesis induced by ETC-associated genes in LUAD and paves the way for finding potential targets of LUAD.

ALDH2 promotes uterine corpus endometrial carcinoma proliferation and construction of clinical survival prognostic model

UCEC is one of the three common malignant tumors of the female reproductive tract. According to reports, the cure rate of early UCEC can reach 95%. Therefore, the development of prognostic markers will help UCEC patients to find the disease earlier and develop treatment earlier. The ALDH family was first discovered to be the essential gene of the ethanol metabolism pathway in the body. Recent studies have shown that ALDH can participate in the regulation of cancer. In our research, we explored the expression of the ALDH family in 33 cancers. It was found that ALDH2 was abnormally expressed in UCEC. Besides, in vivo and in vitro experiments were conducted to explore the effect of ALDH2 expression on the proliferation of UCEC cell lines. Meanwhile, the change of its expression is not due to gene mutations, but is regulated by miR-135-3p. At the same time, the impact of ALDH2 changes on the survival of UCEC patients is deeply discussed. Finally, a nomogram for predicting survival was constructed, with a C-index of 0.798 and AUC of 0.764. This study suggests that ALDH2 may play a crucial role in UCEC progression and has the potential as a prognostic biomarker of UCEC.

Uncovering cancer vulnerabilities by machine learning prediction of synthetic lethality

BACKGROUND

Synthetic lethality describes a genetic interaction between two perturbations, leading to cell death, whereas neither event alone has a significant effect on cell viability. This concept can be exploited to specifically target tumor cells. CRISPR viability screens have been widely employed to identify cancer vulnerabilities. However, an approach to systematically infer genetic interactions from viability screens is missing.

METHODS

Here we describe PAn-canceR Inferred Synthetic lethalities (PARIS), a machine learning approach to identify cancer vulnerabilities. PARIS predicts synthetic lethal (SL) interactions by combining CRISPR viability screens with genomics and transcriptomics data across hundreds of cancer cell lines profiled within the Cancer Dependency Map.

RESULTS

Using PARIS, we predicted 15 high confidence SL interactions within 549 DNA damage repair (DDR) genes. We show experimental validation of an SL interaction between the tumor suppressor CDKN2A, thymidine phosphorylase (TYMP) and the thymidylate synthase (TYMS), which may allow stratifying patients for treatment with TYMS inhibitors. Using genome-wide mapping of SL interactions for DDR genes, we unraveled a dependency between the aldehyde dehydrogenase ALDH2 and the BRCA-interacting protein BRIP1. Our results suggest BRIP1 as a potential therapeutic target in ~ 30% of all tumors, which express low levels of ALDH2.

CONCLUSIONS

PARIS is an unbiased, scalable and easy to adapt platform to identify SL interactions that should aid in improving cancer therapy with increased availability of cancer genomics data.

Proteomic-Based Analysis of Hypoxia- and Physioxia-Responsive Proteins and Pathways in Diffuse Large B-Cell Lymphoma

Hypoxia is a common feature in most tumors, including hematological malignancies. There is a lack of studies on hypoxia- and physioxia-induced global proteome changes in lymphoma. Here, we sought to explore how the proteome of diffuse large B-cell lymphoma (DLBCL) changes when cells are exposed to acute hypoxic stress (1% of O₂) and physioxia (5% of O₂) for a long-time. A total of 8239 proteins were identified by LC–MS/MS, of which 718, 513, and 486 had significant changes, in abundance, in the Ri-1, U2904, and U2932 cell lines, respectively. We observed that changes in B-NHL proteome profiles induced by hypoxia and physioxia were quantitatively similar in each cell line; however, differentially abundant proteins (DAPs) were specific to a certain cell line. A significant downregulation of several ribosome proteins indicated a translational inhibition of new ribosome protein synthesis in hypoxia, what was confirmed in a pathway enrichment analysis. In addition, downregulated proteins highlighted the altered cell cycle, metabolism, and interferon signaling. As expected, the enrichment of upregulated proteins revealed terms related to metabolism, HIF1 signaling, and response to oxidative stress. In accordance to our results, physioxia induced weaker changes in the protein abundance when compared to those induced by hypoxia. Our data provide new evidence for understanding mechanisms by which DLBCL cells respond to a variable oxygen level. Furthermore, this study reveals multiple hypoxia-responsive proteins showing an altered abundance in hypoxic and physioxic DLBCL. It remains to be investigated whether changes in the proteomes of DLBCL under normoxia and physioxia have functional consequences on lymphoma development and progression.

Aldehyde dehydrogenase 2 alleviates monosodium iodoacetate-induced oxidative stress, inflammation and apoptosis in chondrocytes via inhibiting aquaporin 4 expression

BACKGROUND

Knee osteoarthritis (KOA) is a common cause of disability among the elderly. We aimed to explore the effects of aldehyde dehydrogenase (ALDH) 2 on the progression of KOA and identifying the potential mechanisms.

METHODS

First, ALDH2 expression in knee joint effusion of patients with KOA and the levels of oxidative stress-related markers were determined. After ALDH2 overexpression in monosodium iodoacetate (MIA)-treated SW1353 cells, cell viability was tested with CCK-8 assay. Subsequently, oxidative stress and inflammation-associated factors were measured. Meanwhile, cell apoptosis was assessed with TUNEL staining and expression of apoptosis-related proteins was detected by western blotting. To analyze the mechanism of ALDH2 in KOA, aquaporin 4 (AQP4) expression was determined using western blotting following ALDH2-upregulation. Subsequently, AQP4 was overexpressed to evaluate the changing of oxidative stress, inflammation and apoptosis in SW1353 cells exposed to MIA with ALDH2 overexpression.

RESULTS

Results indicated that knee joint effusion with higher ALDH2 expression displayed lower oxidative stress. In addition, significantly upregulated ALDH2 expression was observed in MIA-treated SW1353 cells. ALDH2 overexpression oxidative stress, inflammation and apoptosis in SW1353 cells exposed to MIA. Moreover, MIA-triggered elevated expression of AQP4, which was reduced by ALDH2 overexpression. By contrast, AQP4-upregulation abrogated the inhibitory effects of ALDH2 on oxidative stress, inflammation and apoptosis in MIA-induced SW1353 cells.

CONCLUSIONS

ALDH2 inactivates the expression of AQP4, by which mechanism the MIA-induced oxidative stress, inflammation and apoptosis injuries were alleviated, which provides a novel insight for understanding the mechanism of KOA and a promising target for the treatment of this disease.

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.

Aldehyde Dehydrogenase 2 Protects Against Lipopolysaccharide-Induced Myocardial Injury by Suppressing Mitophagy

Sepsis is defined as life-threatening organ dysfunction caused by a dysregulated host response to infection. Sepsis-induced circulatory and cardiac dysfunction is associated with high mortality rates. Mitophagy, a specific form of autophagy, is excessively activated in lipopolysaccharide-induced myocardial injury. The present study investigated whether aldehyde dehydrogenase 2 (ALDH2) regulates mitophagy in sepsis-induced myocardial dysfunction. After lipopolysaccharide administration, cardiac dysfunction, inflammatory cell infiltration, biochemical indicators of myocardial cell injury, and cardiomyocyte apoptosis were ameliorated in mice by ALDH2 activation or overexpression. In contrast, cardiac dysfunction and cardiomyocyte apoptosis were exacerbated in mice followed ALDH2 inhibition. Moreover, ALDH2 activation or overexpression regulated mitophagy by suppressing the expression of phosphatase and tensin homolog-induced putative kinase 1 (PINK1)/Parkin, by preventing the accumulation of 4-hydroxy-trans-nonenal. Conversely, ALDH2 inhibition promoted the expression of LC3B by increasing 4-hydroxy-trans-2-nonenal accumulation. Consequently, ALDH2 may protect the heart from lipopolysaccharide-induced injury by suppressing PINK1/Parkin-dependent mitophagy.

Aldehyde Dehydrogenase 2 Mediates Alcohol-Induced Colorectal Cancer Immune Escape through Stabilizing PD-L1 Expression

Despite the great success of immunotherapy in a small subset of cancer patients, most colorectal cancer (CRC) patients do not respond to programmed cell death receptor 1 (PD-1) blockade immunotherapy. There is an urgent medical need to elucidate how cancer cells evade immune response and to develop novel means to boost the efficacy of immune checkpoint inhibitors. In this study, alcohol induces ligand programmed cell death receptor 1 (PD-L1) expression of CRC cells in vitro and in vivo. Alcohol exposure is shown to induce aldehyde dehydrogenase 2 (ALDH2) expression that is a crucial enzyme involved in alcohol metabolism, and low level of lymphocytes infiltration in the murine CRC model and patients. Intriguingly, ALDH2 and PD-L1 protein expression are positively correlated in tumor tissues from the CRC patients. Mechanistically, ALDH2 stabilizes PD-L1 protein expression by physically interacting with the intracellular segment of PD-L1 and inhibiting its proteasome-dependent degradation mediated by an E3 ubiquitin ligase Speckle Type POZ Protein (SPOP). Importantly, inhibition of ALDH2 reduces PD-L1 protein in CRC cells and promotes tumor-infiltrating T cells (TILs) infiltration, presumably leading to the significant potentiation of anti-PD-1 antibody efficacy in a mouse CT26 CRC model. The findings highlight a crucial role played by ALDH2 to facilitate alcohol-mediated tumor escape from immunity surveillance and promote tumor progression.

Identifying Novel Susceptibility Genes for Colorectal Cancer Risk From a Transcriptome-Wide Association Study of 125,478 Subjects

BACKGROUND AND AIMS

Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes.

METHODS

Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted.

RESULTS

We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis.

CONCLUSIONS

Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.

Novel Gene Signatures Predictive of Patient Recurrence-Free Survival and Castration Resistance in Prostate Cancer

Simple Summary

Molecular signatures predictive of recurrence-free survival (RFS) and castration resistance are critical for treatment decision-making in prostate cancer (PCa), but the robustness of current signatures is limited. This study aims to identify castration-resistant PCa (CRPC)-associated genes and develop robust RFS and CRPC signatures. Among 287 genes differentially expressed between localized CRPC and hormone-sensitive PCa (HSPC) samples, 6 genes constituted a signature (CRPC-derived prognosis signature, CRPCPS) that predicted RFS. Moreover, a 3-gene panel derived from the 6 CRPCPS genes was capable of distinguishing CRPC from HSPC. The CRPCPS predicted RFS in 5/9 cohorts in the multivariate analysis and maintained prognostic in patients stratified by tumor stage, Gleason score, and lymph node metastasis status. It also predicted overall survival and metastasis-free survival. Notably, the signature was validated in another six independent cohorts. These findings suggest that these two signatures could be robust tools for predicting RFS and CRPC in clinical practice.

Abstract

Molecular signatures predictive of recurrence-free survival (RFS) and castration resistance are critical for treatment decision-making in prostate cancer (PCa), but the robustness of current signatures is limited. Here, we applied the Robust Rank Aggregation (RRA) method to PCa transcriptome profiles and identified 287 genes differentially expressed between localized castration-resistant PCa (CRPC) and hormone-sensitive PCa (HSPC). Least absolute shrinkage and selection operator (LASSO) and stepwise Cox regression analyses of the 287 genes developed a 6-gene signature predictive of RFS in PCa. This signature included NPEPL1, VWF, LMO7, ALDH2, NUAK1, and TPT1, and was named CRPC-derived prognosis signature (CRPCPS). Interestingly, three of these 6 genes constituted another signature capable of distinguishing CRPC from HSPC. The CRPCPS predicted RFS in 5/9 cohorts in the multivariate analysis and remained valid in patients stratified by tumor stage, Gleason score, and lymph node status. The signature also predicted overall survival and metastasis-free survival. The signature’s robustness was demonstrated by the C-index (0.55–0.74) and the calibration plot in all nine cohorts and the 3-, 5-, and 8-year area under the receiver operating characteristic curve (0.67–0.77) in three cohorts. The nomogram analyses demonstrated CRPCPS’ clinical applicability. The CRPCPS thus appears useful for RFS prediction in PCa.

A glycolysis-related gene expression signature in predicting recurrence of breast cancer

Metabolic change is the hallmark of cancer. In the present study, we aimed to develop a glycolysis-related gene signature to predict the prognosis of breast cancer patients. Gene expression profiles and clinical data of breast cancer patients were obtained from the GEO database. A four-gene based signature (ALDH2, PRKACB, STMN1 and ZNF292) was developed to separate patients into high-risk and low-risk groups. Patients in the low-risk group had significantly better prognosis than those in the high-risk group. Time-dependent ROC analysis demonstrated that the glycolysis-related gene signature had excellent prognostic accuracy. We further confirmed the expression of the four prognostic genes in breast cancer and paracancerous tissue samples using qRT-PCR analysis. Expression level of PRKACB was higher in paracancerous tissues, while STMN1 and ZNF292 were overexpressed in tumor samples, no significant difference was observed in ALDH2 expression level. Global proteome data of 105 TCGA breast cancer samples obtained from the Clinical Proteomic Tumor Analysis Consortium (CPTAC) were used to evaluate the prognostic value in protein levels. Consistently, high expression level of PRKACB protein was associated with favorable prognosis, while high ZNF292 and STMN1 protein expression levels indicated poor prognosis. The glycolysis-related gene signature might provide an effective prognostic predictor and a new insight for individualize management of breast cancer patients.

A Recurrence-Specific Gene-Based Prognosis Prediction Model for Lung Adenocarcinoma through Machine Learning Algorithm

Background

After curative surgical resection, about 30-75% lung adenocarcinoma (LUAD) patients suffer from recurrence with dismal survival outcomes. Identification of patients with high risk of recurrence to impose intense therapy is urgently needed.

Materials and Methods

Gene expression data of LUAD were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were calculated by comparing the recurrent and primary tissues. Prognostic genes associated with the recurrence-free survival (RFS) of LUAD patients were identified using univariate analysis. LASSO Cox regression and multivariate Cox analysis were applied to extract key genes and establish the prediction model.

Results

We detected 37 DEGs between primary and recurrent LUAD tumors. Using univariate analysis, 31 DEGs were found to be significantly associated with RFS. We established the RFS prediction model including thirteen genes using the LASSO Cox regression. In the training cohort, we classified patients into high- and low-risk groups and found that patients in the high-risk group suffered from worse RFS compared to those in the low-risk group (P < 0.01). Concordant results were confirmed in the internal and external validation cohort. The efficiency of the prediction model was also confirmed under different clinical subgroups. The high-risk group was significantly identified as the risk factor of recurrence in LUAD by the multivariate Cox analysis (HR = 13.37, P = 0.01). Compared to clinicopathological features, our prediction model possessed higher accuracy to identify patients with high risk of recurrence (AUC = 96.3%). Finally, we found that the G2M checkpoint pathway was enriched both in recurrent tumors and primary tumors of high-risk patients.

Conclusions

Our recurrence-specific gene-based prognostic prediction model provides extra information about the risk of recurrence in LUAD, which is conducive for clinicians to conduct individualized therapy in clinic.

Establishment of the Prognostic Index Reflecting Tumor Immune Microenvironment of Lung Adenocarcinoma Based on Metabolism-Related Genes

Background: The incidence of lung adenocarcinoma (LUAD) increased substantially in recent years. A systematic investigation of the metabolic genomics pattern is critical to improve the treatment and prognosis of LUAD. This study aimed to analyze the relationship between tumor microenvironment (TME) and metabolism-related genes of LUAD.

Methods: The data was extracted from TCGA and GEO datasets. The metabolism-related gene expression profile and the corresponding clinical data of LUAD patients were then integrated. The survival-related genes were screened out using univariate COX regression and lasso regression analysis. The latent properties and molecular mechanisms of these LUAD-specific metabolism-related genes were investigated by computational biology.

Results: A novel prognostic model was established based on 8 metabolism-related genes, including TYMS, ALDH2, PKM, GNPNAT1, LDHA, ENTPD2, NT5E, and MAOB. The immune infiltration of LUAD was also analyzed using CIBERSORT algorithms and TIMER database. In addition, the high- and low-risk groups exhibited distinct layout modes in the principal component analysis.

Conclusions: In summary, our studies identified clinically significant metabolism-related genes, which were potential signature for LUAD diagnosis, monitoring, and prognosis.

A model of twenty-three metabolic-related genes predicting overall survival for lung adenocarcinoma

Background

The highest rate of cancer-related deaths worldwide is from lung adenocarcinoma (LUAD) annually. Metabolism was associated with tumorigenesis and cancer development. Metabolic-related genes may be important biomarkers and metabolic therapeutic targets for LUAD.

Materials and Methods

In this study, the gleaned cohort included LUAD RNA-SEQ data from the Cancer Genome Atlas (TCGA) and corresponding clinical data (n = 445). The training cohort was utilized to model construction, and data from the Gene Expression Omnibus (GEO, GSE30219 cohort, n = 83; GEO, GSE72094, n = 393) were regarded as a testing cohort and utilized for validation. First, we used a lasso-penalized Cox regression analysis to build a new metabolic-related signature for predicting the prognosis of LUAD patients. Next, we verified the metabolic gene model by survival analysis, C-index, receiver operating characteristic (ROC) analysis. Univariate and multivariate Cox regression analyses were utilized to verify the gene signature as an independent prognostic factor. Finally, we constructed a nomogram and performed gene set enrichment analysis to facilitate subsequent clinical applications and molecular mechanism analysis.

Result

Patients with higher risk scores showed significantly associated with poorer survival. We also verified the signature can work as an independent prognostic factor for LUAD survival. The nomogram showed better clinical application performance for LUAD patient prognostic prediction. Finally, KEGG and GO pathways enrichment analyses suggested several especially enriched pathways, which may be helpful for us investigative the underlying mechanisms.

Methylation-Induced Silencing of ALDH2 Facilitates Lung Adenocarcinoma Bone Metastasis by Activating the MAPK Pathway

Bone metastasis (BM) dramatically reduces the quality of life and life expectancy in lung adenocarcinoma (LUAD) patients. There is an urgent need to identify potential biomarkers for application in the treatment of this deadly disease. We compared patient BM, LUAD, and para-LUAD tissues using proteomic analysis and identified aldehyde dehydrogenase 2 (ALDH2), which can detoxify acetaldehyde to acetic acid, as one of the key regulators in lung tumor metastasis. Both the mRNA and protein levels of ALDH2 were significantly lower in tumor tissues than in normal tissues and were lowest in BM tissues with increased migratory capacity. Also, ALDH2 was upregulated following treatment with 5-azacitidine, a DNA methyltransferase inhibitor, in H1299, H460, and HCC827 cells. Further, we identified a potential methylated CpG island 3, with the longest methylated CpG island area in ALDH2, and performed bisulfite genomic sequencing of these sites. An average of 78.18% of the sites may be methylated in CpG island 3. Knockdown of DNA (cytosine-5)-methyltransferase 3A (DNMT3A) and methylated CpG binding protein 4 (MBD4) upregulated ALDH2 expression. ALDH2 functions as a mitogen-activated protein kinase (MAPK) upstream to inhibit cell proliferation and migration, promote cell apoptosis, and alter the epithelial–mesenchymal transition (EMT) by elevating E-cadherin and attenuating vimentin. Cell proliferation and migration were inhibited after the addition of the JNK inhibitor SP600125. In the multivariate analysis, M stage (p = 0.003), ALDH2 (p = 0.008), and phospho-c-Jun N-terminal kinase (p-JNK) (p = 0.027) expression were independent prognostic factors for overall survival in patients with BM. In vivo experiments also showed that ALDH2 expression could suppress tumor formation. In summary, we found that ALDH2 expression is a prognostic factor for BM in LUAD and that DNMT3A and MBD4 repression of ALDH2 via a MAPK-dependent pathway alters the EMT process, indicating that these proteins could act as potential biomarkers or therapeutic targets for LUAD metastasis.

PTGES/PGE2 signaling links immunosuppression and lung metastasis in Gprc5a-knockout mouse model

Chronic inflammation has been linked to promotion of tumorigenesis and metastasis in lung. However, due to lack of a relevant animal model for characterization, the underlying mechanism remains elusive. Lung tumor suppressor gene Gprc5a-knockout (ko) mice are susceptible to lung inflammation, tumorigenesis and metastasis, which resembles the pathological features in human patients. Here, we showed that PTGES/PGE2 signaling was highly associated with lung tumorigenesis and metastasis in Gprc5a-ko mice. Interestingly, Ptges-knockout in mouse lung tumor cells, although reduced their stemness and EMT-like features, still formed tumors and lung metastasis in immune-deficient nude mice, but not in immune-competent mice. This suggests that the major role of PTGES/PGE2 signaling in tumorigenicity and lung metastasis is through immunosuppression. Mechanistically, PTGES/PGE2 signaling intrinsically endows tumor cells resistant to T-cell cytotoxicity, and induces cytokines extrinsically for MDSC recruitment, which is crucial for suppression of T-cell immunity. Importantly, targeting PGE2 signaling in Gprc5a-ko mice by PTGES inhibitor suppressed MDSC recruitment, restored T cells, and significantly repressed lung metastasis. Thus, PTGES/PGE2 signaling links immunosuppression and metastasis in an inflammatory lung microenvironment of Gprc5a-ko mouse model.