Large-scale proteome quantification of hepatocellular carcinoma tissues by a three-dimensional liquid chromatography strategy integrated with sample preparation

Role of AKR1B10 in inflammatory diseases

Inflammation is an important pathophysiological process in many diseases; it has beneficial and harmful effects. When exposed to various stimuli, the body triggers an inflammatory response to eliminate invaded pathogens and damaged tissues to maintain homeostasis. However, uncontrollable persistent or excessive inflammatory responses may damage tissues and induce various diseases, such as metabolic diseases (e.g. diabetes), autoimmune diseases, nervous system-related diseases, digestive system-related diseases, and even tumours. Aldo-keto reductase 1B10 (AKR1B10) is an important player in the development and progression of multiple diseases, such as tumours and inflammatory diseases. AKR1B10 is upregulated in solid tumours, such as hepatocellular carcinoma (HCC), non-small cell lung carcinoma, and breast cancer, and is a reliable serum marker. However, information on the role of AKR1B10 in inflammation is limited. In this study, we summarized the role of AKR1B10 in inflammatory diseases, including its expression, functional contribution to inflammatory responses, and regulation of signalling pathways related to inflammation. We also discussed the role of AKR1B10 in glucose and lipid metabolism and oxidative stress. This study provides novel information and increases the understanding of clinical inflammatory diseases.

AKR1B10 inhibits the proliferation and metastasis of hepatocellular carcinoma cells by regulating the PI3K/AKT pathway

Hepatocellular carcinoma (HCC) is one of the most frequent and aggressive malignant neoplasms, and is associated with a poor prognosis. Therefore, there is a crucial need to develop novel cancer therapies and identify novel therapeutic targets. Aldo-keto reductase family 1 member B10 (AKR1B10) is expressed in various types of cancer. However, the role of AKR1B10 in the pathological process of HCC and its underlying molecular mechanism is poorly understood. AKR1B10 expression was evaluated pan-cancer and in HCC using the Genomic Data Commons-The Cancer Genome Atlas (GDC-TCGA) and International Cancer Genome Consortium (ICGC) databases. The relationship between elevated AKR1B10 expression and overall survival in HCC patients was analyzed using a Kaplan-Meier plot. The effects of AKR1B10 on the proliferation, migration, and invasion of HCC cells were evaluated. The proliferation of HCC was measured using CCK-8 and colony formation assays. Transwell and wound healing assays were used to assess the migration and invasion of HCC cells. Western blots were used to detect the expression of proliferative and epithelial-mesenchymal transition (EMT) related proteins in HCC cells, including CCND1, E-cadherin, N-cadherin, vimentin, Twist1, PI3K/p-PI3K, and AKT/p-AKT. AKR1B10 expression was significantly upregulated pan-cancer and in liver cancer. Upregulated AKR1B10 expression was associated with a worse overall survival. HCC cell proliferation, migration, and invasion were found to be influenced by AKR1B10 activity, as demonstrated using DepMap analysis. AKR1B10 knockdown in Huh7 cells reduced proliferation, migration, invasion, and EMT. Mechanistically, AKR1B10 increased the expression of proliferative and EMT-related proteins CCND1, E-cadherin, N-cadherin, vimentin, and Twist1. PI3K and AKT phosphorylation levels decreased following AKR1B10 knockdown. In conclusion, AKR1B10 promoted the proliferation, migration, and invasion of HCC cells via the PI3K/AKT signaling pathway, a potential prognostic indicator.

Bottom-Up Proteomics: Advancements in Sample Preparation

Liquid chromatography–tandem mass spectrometry (LC–MS/MS)-based proteomics is a powerful technique for profiling proteomes of cells, tissues, and body fluids. Typical bottom-up proteomic workflows consist of the following three major steps: sample preparation, LC–MS/MS analysis, and data analysis. LC–MS/MS and data analysis techniques have been intensively developed, whereas sample preparation, a laborious process, remains a difficult task and the main challenge in different applications. Sample preparation is a crucial stage that affects the overall efficiency of a proteomic study; however, it is prone to errors and has low reproducibility and throughput. In-solution digestion and filter-aided sample preparation are the typical and widely used methods. In the past decade, novel methods to improve and facilitate the entire sample preparation process or integrate sample preparation and fractionation have been reported to reduce time, increase throughput, and improve reproducibility. In this review, we have outlined the current methods used for sample preparation in proteomics, including on-membrane digestion, bead-based digestion, immobilized enzymatic digestion, and suspension trapping. Additionally, we have summarized and discussed current devices and methods for integrating different steps of sample preparation and peptide fractionation.

Potential Biomarkers for Liver Cancer Diagnosis Based on Multi-Omics Strategy

Liver cancer is the fourth leading cause of cancer-related death worldwide. Hepatocellular carcinoma (HCC) accounts for about 85%-90% of all primary liver malignancies. However, only 20-30% of HCC patients are eligible for curative therapy mainly due to the lack of early-detection strategies, highlighting the significance of reliable and accurate biomarkers. The integration of multi-omics became an important tool for biomarker screening and unique alterations in tumor-associated genes, transcripts, proteins, post-translational modifications and metabolites have been observed. We here summarized the novel biomarkers for HCC diagnosis based on multi-omics technology as well as the clinical significance of these potential biomarkers in the early detection of HCC.

Proteomic Analysis Reveals the Protective Effects of Yiqi Fumai Lyophilized Injection on Chronic Heart Failure by Improving Myocardial Energy Metabolism

Yiqi Fumai lyophilized injection (YQFM) is the recombination of Sheng mai san (SMS).YQFM has been applied clinically to efficaciously and safely treat chronic heart failure (CHF). However, the mechanism of YQFM is still not fully elucidated. The purpose of our study was to investigate the protective mechanism of YQFM against abdominal aortic coarctation (AAC) in rats by proteomic methods. After YQFM treatment, the cardiac function were obviously meliorated. One hundred and fifty-seven important differentially expressed proteins (DEPs) were identified, including 109 in model rat compared with that in control rat (M:C) and 48 in YQFM-treated rat compared with that in model rat (T:M) by iTRAQ technology to analyze the proteomic characteristics of heart tissue. Bioinformatics analysis showed that DEPs was mainly involved in the body’s energy metabolism and was closely related to oxidative phosphorylation. YQFM had also displayed efficient mitochondrial dysfunction alleviation properties in hydrogen peroxide (H₂O₂)-induced cardiomyocyte damage by Transmission Electron Microscope (TEM), Metabolic assay, and Mitotracker staining. What’s more, the levels of total cardiomyocyte apoptosis were markedly reduced following YQFM treatment. Furthermore, Western blot analysis showed that the expressions of peroxisome proliferator activated receptor co-activator-1α(PGC-1α) (p < 0.01 or p < 0.001), perixisome proliferation-activated receptor alpha (PPAR-α) (p < 0.001)and retinoid X receptor alpha (RXR-α) were upregulated (p < 0.001), PGC-1α as well as its downstream effectors were also found to be upregulated in cardiomyocytes after YQFM treatment(p < 0.001).These results provided evidence that YQFM could enhance mitochondrial function of cardiomyocytes to play a role in the treatment of CHF by regulating mitochondrial biogenesis-related proteins.

Regulation Network and Prognostic Significance of Aldo-Keto Reductase (AKR) Superfamily Genes in Hepatocellular Carcinoma

Purpose

The aldo-keto reductase (AKR) superfamily members have been proposed with multiple roles in various tumors. Here, a comprehensive analysis on the integral role of AKR genes was conducted to evaluate the expression profile, regulation network, and prognostic significance in hepatocellular carcinoma (HCC).

Materials and Methods

Transcriptome datasets of HCC were obtained from the Cancer Genome Atlas (TCGA) and Gene Expression Omnibus. Univariate and multivariate Cox regression analyses were used to build a novel risk score model, and then were further used to identify independent prognostic factors for overall survival (OS) of HCC. A prognostic nomogram was developed and validated. The expression of these critical AKR members was also evaluated by quantitative real-time polymerase chain reaction and immunohistochemistry in HCC specimens.

Results

Eight differentially expressed AKR genes were identified in HCC. The dysregulation of most AKR genes was negatively correlated with DNA methylation, and a regulation network with transcription factors (TFs) was also established. Then, three critical AKR genes (AKR1B10, AKR1D1, and AKR7A3) were screened out to build a novel risk score model. Worse OS was observed in high-risk patients. Besides, a prognostic nomogram based on the model was further established and validated in both the TCGA and GSE14520 cohorts, which showed superior performance in predicting the OS of HCC patients. Notably, close correlations were identified between the risk score and tumor immune microenvironment, somatic mutation profiles, and drug susceptibilities of HCC. Finally, the upregulated AKR1B10 and downregulated AKR1D1 and AKR7A3 were further verified in HCC tumor and adjacent tissues from our institution.

Conclusion

The dysregulated AKR genes could be mediated by DNA methylation and TFs in HCC. The risk model established with superior prognostic performance further suggested the significant role of AKR genes involved in the progression of HCC.

Configuration of the ion exchange chromatography, hydrophilic interaction chromatography, and reversed-phase chromatography as off-line three-dimensional chromatography coupled with high-resolution quadrupole-Orbitrap mass spectrometry for the multicomponent characterization of Uncaria sessilifructus

Herbs represent complex chemical systems involving various primary and secondary metabolites that are featured by large spans of acid-base property, polarity, molecular mass, and content, etc., which thus poses great challenges to characterize the metabolites contained. Here, the combination of multiple-mechanism chromatography coupled with improved data-dependent-MS² acquisition (DDA-MS²) is presented as a strategy to support the deep metabolites characterization. Targeting Uncaria sessilifructus, a reputable medicinal herb containing alkaloids and triterpenic acids (TAs) as the main pharmacologically bioactive ingredients, a three-dimensional liquid chromatography (3D-LC) system was established by integrating ion exchange chromatography, hydrophilic interaction chromatography, and reversed-phase chromatography (IEC-HILIC-RPC). The first-dimensional chromatography, configuring a PhenoSphere SCX column eluted by methanol/20 mM ammonium acetate-0.05% formic acid in water, could well fractionate the total extract into two fractions (unretained ingredients and alkaloids). The subsequent HILIC using an XAmide column and RPC by a CSH Phenyl-Hexyl column achieved the sufficient resolution of the total TAs and total alkaloids, respectively. A polarity-switching precursor ions list-including DDA approach by Q-Orbitrap-MS enabled the high-efficiency, coverage-enhanced identification of alkaloids and TAs. This 3D-LC/Q-Orbitrap-MS system was validated as precise (RSD < 5% for intra-day/inter-day precision), Up to 308 components were separated from U. sessilifructus, and 128 thereof (including 85 alkaloids, 29 TAs, and 14 others) were identified or tentatively characterized, exhibiting superiority over the conventional one-dimensional LC/MS. Conclusively, 3D-LC/MS in an off-line mode can facilitate the flexible configuration of multiple chromatography to accomplish the fit-for-purpose characterization of the metabolites from an herbal extract or a biosample.

Proteomic Profiling of Emiliania huxleyi Using a Three-Dimensional Separation Method Combined with Tandem Mass Spectrometry

Emiliania huxleyi is one of the most abundant marine planktons, and it has a crucial feature in the carbon cycle. However, proteomic analyses of Emiliania huxleyi have not been done extensively. In this study, a three-dimensional liquid chromatography (3D-LC) system consisting of strong cation exchange, high- and low-pH reversed-phase liquid chromatography was established for in-depth proteomic profiling of Emiliania huxleyi. From tryptic proteome digest, 70 fractions were generated and analyzed using liquid chromatography-tandem mass spectrometry. In total, more than 84,000 unique peptides and 10,000 proteins groups were identified with a false discovery rate of ≤0.01. The physicochemical properties of the identified peptides were evaluated. Using ClueGO, approximately 700 gene ontology terms and 15 pathways were defined from the identified protein groups with p-value ≤0.05, covering a wide range of biological processes, cellular components, and molecular functions. Many biological processes associated with CO₂ fixation, photosynthesis, biosynthesis, and metabolic process were identified. Various molecular functions relating to protein binding and enzyme activities were also found. The 3D-LC strategy is a powerful approach for comparative proteomic studies on Emiliania huxleyi to reveal changes in its protein level and related mechanism.

Dimethyl Labeling-Based Quantitative Proteomics of Recalcitrant Cocoa Pod Tissue

Dimethyl labeling is a type of stable-isotope labeling suitable for creating isotopic variants of peptides and thus be utilized for quantitative proteomics experiments. Labeling is achieved through a reductive amination/alkylation reaction using the low-cost reagents formaldehyde and cyanoborohydride, resulting in dimethylation of free amine groups of Lys and N-termini. Availability of isotopomeric forms of these reagents allows for the generation of up to six different isotopic variants. Here we describe the application of dimethylation to create two isotopic variants, light and heavy, differing in 4 Da, to label the total tryptic digest peptides of cocoa pod extracted from healthy pods from cultivars susceptible and resistant to the fungal disease called "frosty pod" caused by Moniliophthora roreri.

Comprehensive analysis reveals a metabolic ten-gene signature in hepatocellular carcinoma

Background

Due to the complicated molecular and cellular heterogeneity in hepatocellular carcinoma (HCC), the morbidity and mortality still remains high level in the world. However, the number of novel metabolic biomarkers and prognostic models could be applied to predict the survival of HCC patients is still small. In this study, we constructed a metabolic gene signature by systematically analyzing the data from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO) and International Cancer Genome Consortium (ICGC).

Methods

Differentially expressed genes (DEGs) between tumors and paired non-tumor samples of 50 patients from TCGA dataset were calculated for subsequent analysis. Univariate cox proportional hazard regression and LASSO analysis were performed to construct a gene signature. The Kaplan–Meier analysis, time-dependent receiver operating characteristic (ROC), Univariate and Multivariate Cox regression analysis, stratification analysis were used to assess the prognostic value of the gene signature. Furthermore, the reliability and validity were validated in four types of testing cohorts. Moreover, the diagnostic capability of the gene signature was investigated to further explore the clinical significance. Finally, Go enrichment analysis and Gene Set Enrichment Analysis (GSEA) have been performed to reveal the different biological processes and signaling pathways which were active in high risk or low risk group.

Results

Ten prognostic genes were identified and a gene signature were constructed to predict overall survival (OS). The gene signature has demonstrated an excellent ability for predicting survival prognosis. Univariate and Multivariate analysis revealed the gene signature was an independent prognostic factor. Furthermore, stratification analysis indicated the model was a clinically and statistically significant for all subgroups. Moreover, the gene signature demonstrated a high diagnostic capability in differentiating normal tissue and HCC. Finally, several significant biological processes and pathways have been identified to provide new insights into the development of HCC.

Conclusion

The study have identified ten metabolic prognostic genes and developed a prognostic gene signature to provide more powerful prognostic information and improve the survival prediction for HCC.

Proteomic analysis reveals the protective effects of emodin on severe acute pancreatitis induced lung injury by inhibiting neutrophil proteases activity

Acute lung injury (ALI) is the most common remote organ complication induced by severe acute pancreatitis (SAP). Almost 60-70% SAP-induced deaths are caused by ALI. Efficient clinical therapeutic strategy for SAP-induced ALI is still lacking. In this study, we demonstrate that Emodin (EMO) can significantly alleviate SAP-induced ALI. We investigate the therapeutic mechanisms of EMO by proteomic analysis, which indicates that EMO protects lung tissue against SAP-ALI by negative regulation of endopeptidase activity and inhibition of collagen-containing extracellular matrix degradation. Protein-protein interaction analysis showed Lamc2, Serpina1 and Serpinb1 play important roles in the above pathways. This study elucidates the possible mechanism and suggests the candidacy of EMO in the clinical treatment of SAP-ALI. SIGNIFICANCE: ALI is a major leading cause of death in SAP. DEX is the standard of care drug for treatment of SAP-ALI, but often associated with inevitable side effects. In the present study, EMO was demonstrated to greatly alleviate the lung injury induced by SAP. Through proteomic analysis, the recovered protein profiles in response to EMO treatment in SAP-ALI rat models was obtained, among which Lamc2, Serpina1 and Serpinb1 were discovered as crucial regulatory proteins in SAP-ALI disease. Our study provides the underlying mechanisms and novel targets of EMO protective effect against SAP-ALI.

Review of Three-Dimensional Liquid Chromatography Platforms for Bottom-Up Proteomics

Proteomics is a large-scale study of proteins, aiming at the description and characterization of all expressed proteins in biological systems. The expressed proteins are typically highly complex and large in abundance range. To fulfill high accuracy and sensitivity of proteome analysis, the hybrid platforms of multidimensional (MD) separations and mass spectrometry have provided the most powerful solution. Multidimensional separations provide enhanced peak capacity and reduce sample complexity, which enables mass spectrometry to analyze more proteins with high sensitivity. Although two-dimensional (2D) separations have been widely used since the early period of proteomics, three-dimensional (3D) separation was barely used by low reproducibility of separation, increased analysis time in mass spectrometry. With developments of novel microscale techniques such as nano-UPLC and improvements of mass spectrometry, the 3D separation becomes a reliable and practical selection. This review summarizes existing offline and online 3D-LC platforms developed for proteomics and their applications. In detail, setups and implementation of those systems as well as their advances are outlined. The performance of those platforms is also discussed and compared with the state-of-the-art 2D-LC. In addition, we provide some perspectives on the future developments and applications of 3D-LC in proteomics.

Diagnostic and Prognostic Potential of AKR1B10 in Human Hepatocellular Carcinoma

Hepatocellular carcinoma (HCC) is a leading cause of cancer-related death worldwide. Although diagnostic measures and surgical interventions have improved in recent years, the five-year survival rate for patients with advanced HCC remains bleak-a reality that is largely attributable to an absence of early stage symptoms, lack of adequate diagnostic and prognostic biomarkers, and the common occurrence of acquired resistance to chemotherapeutic agents during HCC treatment. A limited understanding of the molecular mechanisms underlying HCC pathogenesis also presents a challenge for the development of specific and efficacious pharmacological strategies to treat, halt, or prevent progression to advanced stages. Over the past decade, aldo-keto reductase family 1 member 10 (AKR1B10) has emerged as a potential biomarker for the diagnosis and prognosis of HCC, and experimental studies have demonstrated roles for this enzyme in biological pathways underlying the development and progression of HCC and acquired resistance to chemotherapeutic agents used in the treatment of HCC. Here we provide an overview of studies supporting the diagnostic and prognostic utility of AKR1B10, summarize the experimental evidence linking AKR1B10 with HCC and the induction of chemoresistance, and discuss the clinical value of AKR1B10 as a potential target for HCC-directed drug development. We conclude that AKR1B10-based therapies in the clinical management of specific HCC subtypes warrant further investigation.

Screening therapeutic targets of ribavirin in hepatocellular carcinoma

The objective of the present study was to screen the key genes of ribavirin in hepatocellular carcinoma (HCC) and provide novel therapeutic targets for HCC treatment. The mRNA expression datasets of GSE23031 and GSE74656, as well as the microRNA (miRNA) expression dataset of GSE22058 were downloaded from the Gene Expressed Omnibus database. In the GSE23031 dataset, there were three HCC cell lines treated with PBS and three HCC cell lines treated with ribavirin. In the GSE74656 dataset, five HCC tissues and five carcinoma adjacent tissues were selected. In the GSE22058 dataset, 96 HCC tissues and 96 carcinoma adjacent tissues were selected. The differentially expressed genes (DEGs) and differentially expressed miRNAs were identified via the limma package of R. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis was performed with the Database for Annotation, Visualization and Integrated Discovery. The target mRNAs of DEMs were obtained with TargetScan. A total of 559 DEGs (designated DEG-Ribavirin) were identified in HCC cells treated with ribavirin compared with PBS and 632 DEGs (designated DEG-Tumor) were identified in HCC tissues compared with carcinoma adjacent tissues. A total of 220 differentially expressed miRNAs were identified in HCC tissues compared with carcinoma adjacent tissues. In addition, 121 GO terms and three KEGG pathways of DEG-Ribavirin were obtained, and 383 GO terms and 25 KEGG pathways of DEG-Tumor were obtained. A total of five key miRNA-mRNA regulated pairs were identified, namely miR-183→CCNB1, miR-96→DEPDC1, miR-96→NTN4, miR-183→NTN4 and miR-145→NTN4. The present study indicated that certain miRNAs (including miR-96, miR-145 and miR-183) and mRNAs (including NAT2, FBXO5, CCNB1, DEPDC1 and NTN4) may be associated with the effects of ribavirin on HCC. Furthermore, they may provide novel therapeutic targets for HCC treatment.

Quantitative proteomics by SWATH-MS reveals sophisticated metabolic reprogramming in hepatocellular carcinoma tissues

Hepatocellular carcinoma (HCC) is one of the most common cancers worldwide, and understanding its molecular pathogenesis is pivotal to managing this disease. Sequential window acquisition of all theoretical mass spectra (SWATH-MS) is an optimal proteomic strategy to seek crucial proteins involved in HCC development and progression. In this study, a quantitative proteomic study of tumour and adjacent non-tumour liver tissues was performed using a SWATH-MS strategy. In total, 4,216 proteins were reliably quantified, and 338 were differentially expressed, with 191 proteins up-regulated and 147 down-regulated in HCC tissues compared with adjacent non-tumourous tissues. Functional analysis revealed distinct pathway enrichment of up- and down-regulated proteins. The most significantly down-regulated proteins were involved in metabolic pathways. Notably, our study revealed sophisticated metabolic reprogramming in HCC, including alteration of the pentose phosphate pathway; serine, glycine and sarcosine biosynthesis/metabolism; glycolysis; gluconeogenesis; fatty acid biosynthesis; and fatty acid β-oxidation. Twenty-seven metabolic enzymes, including PCK2, PDH and G6PD, were significantly changed in this study. To our knowledge, this study presents the most complete view of tissue-specific metabolic reprogramming in HCC, identifying hundreds of differentially expressed proteins, which together form a rich resource for novel drug targets or diagnostic biomarker discovery.

Stable isotope dimethyl labelling for quantitative proteomics and beyond

Stable-isotope reductive dimethylation, a cost-effective, simple, robust, reliable and easy-to- multiplex labelling method, is widely applied to quantitative proteomics using liquid chromatography-mass spectrometry. This review focuses on biological applications of stable-isotope dimethyl labelling for a large-scale comparative analysis of protein expression and post-translational modifications based on its unique properties of the labelling chemistry. Some other applications of the labelling method for sample preparation and mass spectrometry-based protein identification and characterization are also summarized.This article is part of the themed issue 'Quantitative mass spectrometry'.

Quantitative proteomics and phosphoproteomics on serial tumor biopsies from a sorafenib-treated HCC patient

Compensatory signaling pathways in tumors confer resistance to targeted therapy, but the pathways and their mechanisms of activation remain largely unknown. We describe a procedure for quantitative proteomics and phosphoproteomics on snap-frozen biopsies of hepatocellular carcinoma (HCC) and matched nontumor liver tissue. We applied this procedure to monitor signaling pathways in serial biopsies taken from an HCC patient before and during treatment with the multikinase inhibitor sorafenib. At diagnosis, the patient had an advanced HCC. At the time of the second biopsy, abdominal imaging revealed progressive disease despite sorafenib treatment. Sorafenib was confirmed to inhibit MAPK signaling in the tumor, as measured by reduced ribosomal protein S6 kinase phosphorylation. Hierarchical clustering and enrichment analysis revealed pathways broadly implicated in tumor progression and resistance, such as epithelial-to-mesenchymal transition and cell adhesion pathways. Thus, we describe a protocol for quantitative analysis of oncogenic pathways in HCC biopsies and obtained first insights into the effect of sorafenib in vivo. This protocol will allow elucidation of mechanisms of resistance and enable precision medicine.

Liver transplantation for hepatocellular carcinoma - factors influencing outcome and disease-free survival

Hepatocellular carcinoma is one of the leading causes of cancer-related death worldwide. Liver transplantation can be a curative treatment in selected patients. However, there are several factors that influence disease-free survival after transplantation. This review addresses the pre-, intra- and postoperative factors that influence the risk of tumor recurrence after liver transplantation.