Integrated proteogenomic approach identifying a protein signature of COPD and a new splice variant of SORBS1

Alternative Splicing Is a Major Factor Shaping Transcriptome Diversity in Mild and Severe Chronic Obstructive Pulmonary Disease

The role of alternative splicing in chronic obstructive pulmonary disease (COPD) is still largely unknown. We aimed to investigate the differences in alternatively splicing events between patients with mild-to-moderate and severe COPD compared with non-COPD control subjects and to identify splicing factors associated with aberrant alternative splicing in COPD. For this purpose, we performed genome-wide RNA-sequencing analysis of bronchial brushings from 23 patients with mild-to-moderate COPD, 121 with severe COPD, and 23 non-COPD control subjects. We found a significant difference in the frequency of alternative splicing events in patients with mild-to-moderate and severe COPD compared with non-COPD control subjects. There were from two to eight times (depending on event type) more differential alternative splicing events in the severe than in the mild-to-moderate stage. The severe COPD samples showed less intron retention and more exon skipping. It is interesting that the transcript levels of the top 10 differentially expressed splicing factors were significantly correlated with the percentage of many alternatively spliced transcripts in severe COPD. The aberrant alternative splicing in severe COPD was predicted to increase the overall protein-coding capacity of gene products. In conclusion, we observed large and significant differences in alternative splicing between bronchial samples of patients with COPD and control subjects, with more events observed in severe than in mild-to-moderate COPD. The changes in the expression of several splicing factors correlated with prevalence of alternative splicing in severe COPD. Alternative splicing can indirectly impact gene expression by changing the relative abundance of protein-coding isoforms potentially influencing pathophysiological changes. The results provide a better understanding of COPD-related alternative splicing changes.

Tandem Mass Tag-Based Proteomic Profiling Identifies Biomarkers in Drainage Fluid for Early Detection of Anastomotic Leakage after Rectal Cancer Resection

Anastomotic leakage (AL), one of the most severe complications in rectal surgery, is often diagnosed late because of the low specificity of the clinical symptoms and limitations of current clinical investigations. Identification of patients with early AL remains challenging. Here, we explored the protein expression profiles of AL patients to provide potential biomarkers to identify AL in patients who undergo surgery for rectal cancer. We screened differentially expressed proteins (DEPs) in drainage fluid from AL and non-AL patients using a tandem mass tag method. A total of 248 DEPs, including 98 upregulated and 150 downregulated proteins, were identified between AL and non-AL groups. Gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses suggested that DEPs were enriched in neutrophil degranulation, bacterial infection, proteolysis, hemostasis, and complement and coagulation cascades. The results of enzyme-linked immunosorbent assay validated that the expression of the top three upregulated DEPs, AMY2A, RETN, and CELA3A, was significantly increased in the drainage fluid of AL patients, compared with that of non-AL patients (AMY2A, P = 0.001; RETN, P < 0.0001; and CELA3A, P = 0.023). Thus, our findings provide several potential biomarkers for the early diagnosis of AL after rectal cancer resection.

Evaluation of common protein biomarkers involved in the pathogenesis of respiratory diseases with proteomic methods: A systematic review

AIM

Respiratory disease (RD) is one of the most common diseases characterized by lung dysfunction. Many diagnostic mechanisms have been used to identify the pathogenic agents of responsible for RD. Among these, proteomics emerges as a valuable diagnostic method for pinpointing the specific proteins involved in RD pathogenesis. Therefore, in this study, for the first time, we examined the protein markers involved in the pathogenesis of chronic obstructive pulmonary disease (COPD), idiopathic pulmonary fibrosis (IPF), asthma, bronchiolitis obliterans (BO), and chemical warfare victims exposed to mustard gas, using the proteomics method as a systematic study.

MATERIALS AND METHODS

A systematic search was performed up to September 2023 on several databases, including PubMed, Scopus, ISI Web of Science, and Cochrane. In total, selected 4246 articles were for evaluation according to the criteria. Finally, 119 studies were selected for this systematic review.

RESULTS

A total of 13,806 proteins were identified, 6471 in COPD, 1603 in Asthma, 5638 in IPF, three in BO, and 91 in mustard gas exposed victims. Alterations in the expression of these proteins were observed in the respective diseases. After evaluation, the results showed that 31 proteins were found to be shared among all five diseases.

CONCLUSION

Although these 31 proteins regulate different factors and molecular pathways in all five diseases, they ultimately lead to the regulation of inflammatory pathways. In other words, the expression of some proteins in COPD and mustard-exposed patients increases inflammatory reactions, while in IPF, they cause lung fibrosis. Asthma, causes allergic reactions due to T-cell differentiation toward Th2.

Age-associated differences in the human lung extracellular matrix

Extracellular matrix (ECM) remodeling has been associated with chronic lung diseases. However, information about specific age-associated differences in lung ECM is currently limited. In this study, we aimed to identify and localize age-associated ECM differences in human lungs using comprehensive transcriptomic, proteomic, and immunohistochemical analyses. Our previously identified age-associated gene expression signature of the lung was re-analyzed limiting it to an aging signature based on 270 control patients (37-80 years) and focused on the Matrisome core geneset using geneset enrichment analysis. To validate the age-associated transcriptomic differences on protein level, we compared the age-associated ECM genes (false discovery rate, FDR < 0.05) with a profile of age-associated proteins identified from a lung tissue proteomics dataset from nine control patients (49-76 years) (FDR < 0.05). Extensive immunohistochemical analysis was used to localize and semi-quantify the age-associated ECM differences in lung tissues from 62 control patients (18-82 years). Comparative analysis of transcriptomic and proteomic data identified seven ECM proteins with higher expression with age at both gene and protein levels: COL1A1, COL6A1, COL6A2, COL14A1, FBLN2, LTBP4, and LUM. With immunohistochemistry, we demonstrated higher protein levels with age for COL6A2 in whole tissue, parenchyma, airway wall, and blood vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in lung parenchyma. Our study revealed that higher age is associated with lung ECM remodeling, with specific differences occurring in defined regions within the lung. These differences may affect lung structure and physiology with aging and as such may increase susceptibility to developing chronic lung diseases.NEW & NOTEWORTHY We identified seven age-associated extracellular matrix (ECM) proteins, i.e., COL1A1, COL6A1, COL6A2 COL14A1, FBLN2, LTBP4, and LUM with higher transcript and protein levels in human lung tissue with age. Extensive immunohistochemical analysis revealed significant age-associated differences for COL6A2 in whole tissue, parenchyma, airway wall, and vessel, for COL14A1 and LUM in bronchial epithelium, and COL1A1 in parenchyma. Our findings lay a new foundation for the investigation of ECM differences in age-associated chronic lung diseases.

Gene expression profiles and bioinformatics analysis in lung samples from ovalbumin-induced asthmatic mice

BACKGROUND

Asthma is characterized by chronic inflammation and airway remodeling. However, limited study is conducted on the gene expression profiles of ovalbumin (OVA) induced asthma in mice. Here, we explored the gene expression profiles in lung tissues from mice with OVA-induced asthma using microarray and bioinformatics analysis.

METHODS

For establishment of OVA-induced asthma model, mice first received intraperitoneal sensitization with OVA on day 0, 7 and 14, followed by atomizing inhalation of OVA 3 times a week for 8 weeks. The lung tissues were collected and subjected to microarray analysis, bioinformatics analysis and expression validation.

RESULTS

Microarray data of lung tissues suggested that 3754 lncRNAs and 2976 mRNAs were differentially expressed in lung tissues between control and asthmatic mice, including 1647 up-regulated and 2106 down-regulated lncRNAs, and 1201 up-regulated and 1766 down-regulated mRNAs. GO analysis displayed that the up-regulated genes were enriched in inflammatory response, leukocyte migration involved in inflammatory response, and Notch signaling pathway. KEGG pathway analysis indicated that the enriched pathway terms of the up-regulated gene included Toll-like receptor signaling pathway and Th17 cell differentiation signaling pathway. Additionally, based on the previously published literatures on asthma and inflammation, we screened out down-regulated genes, such as Smg7, Sumo2, and Stat5a, and up-regulated genes, such as Myl9, Fos and Tlr4. According to the mRNA-lncRNA co-expression network, we selected lncRNAs associated with above genes, including the down-regulated lncRNAs of NONMMUT032848, NONMMUT008873, NONMMUT009478, and NONMMUT006807, and the up-regulated lncRNAs of NONMMUT052633, NONMMUT05340 and NONMMUT042325. The expression changes of the above genes were validated in lung tissues by real-time quantitaive PCR and Western blot.

CONCLUSIONS

Overall, we performed gene microarray on lung samples from OVA-induced asthmatic mice and summarized core mRNAs and their related lncRNAs. This study may provide evidence for further research on the therapeutic targets of asthma.

Development and Validation of a Prognostic Classifier Based on Lipid Metabolism-Related Genes for Breast Cancer

Background

The changes of lipid metabolism have been implicated in the development of many tumors, but its role in breast invasive carcinoma (BRCA) remains to be fully established. Here, we attempted to ascertain the prognostic value of lipid metabolism-related genes in BRCA.

Methods

We obtained RNA expression data and clinical information for BRCA and normal samples from public databases and downloaded a lipid metabolism-related gene set. Ingenuity Pathway Analysis (IPA) was applied to identify the potential pathways and functions of Differentially Expressed Genes (DEGs) related to lipid metabolism. Subsequently, univariate and multivariate Cox regression analyses were utilized to construct the prognostic gene signature. Functional enrichment analysis of prognostic genes was achieved by the Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG). Kaplan-Meier analysis, Receiver Operating Characteristic (ROC) curves, clinical follow-up results were employed to assess the prognostic potency. Potential compounds targeting prognostic genes were screened by Connectivity Map (CMap) database and a prognostic gene-drug interaction network was constructed using Comparative Toxicogenomics Database (CTD). Furthermore, we separately validated the selected marker genes in BRCA samples and human breast cancer cell lines (MCF-7, MDA-MB-231).

Results

IPA and functional enrichment analysis demonstrated that the 162 lipid metabolism-related DEGs we obtained were involved in many lipid metabolism and BRCA pathological signatures. The prognostic classifier we constructed comprising SDC1 and SORBS1 can serve as an independent prognostic marker for BRCA. CMap filtered 37 potential compounds against prognostic genes, of which 16 compounds could target both two prognostic genes were identified by CTD. The functions of the two prognostic genes in breast cancer cells were verified by cell function experiments.

Conclusion

Within this study, we identified a novel prognostic classifier based on two lipid metabolism-related genes: SDC1 and SORBS1. This result highlighted a new perspective on the metabolic exploration of BRCA.

Proteomic characterization of the natural history of chronic HBV infection revealed by tandem mass tag-based quantitative proteomics approach

Currently, determining when to start antiviral therapy in patients with chronic HBV infection is a controversial issue. One crucial reason is that biomarkers for distinguishing the natural history of chronic HBV infection are unmet needs. In this study, we aimed to explore novel biomarkers and therapeutic targets for the diagnosis and treatment of chronic HBV infection by using tandem mass tag (TMT)-based quantitative proteomics approach. Here, we firstly revealed the serum proteomic characterization of the natural history of chronic HBV infection using multiplex TMT labeling coupled with liquid chromatography-mass spectrometry. Then, we verified the levels of differentially expressed proteins (DEPs) across a large number of clinical samples by enzyme-linked immunosorbent assay (ELISA). We found that DEPs over the different phases of chronic HBV infection were primarily involved in the biological process of leukocyte-mediated immunity. Patients with chronic hepatitis were characterized as having an up-regulated proteasome pathway, including upregulation of proteasome activator subunit 1 (PSME1) and proteasome subunit alpha type 7 (PSMA7) levels. In addition, immune tolerant phase patients were characterized by having the lowest ephrin-B2 (EFNB2) levels and highest heat responsive protein 12 (HRSP12) levels. Moreover, inactive HBV carrier state patients were characterized by having a down-regulated glycolysis/gluconeogenesis pathway, with especially low expression of related enzymes alpha-enolase (ENO1) and fructose-1,6-bisphosphatase 1 (FBP1). What's more, HBeAg-negative chronic hepatitis patients were characterized as having the highest interleukin 18 binding protein (IL-18BP) levels. Thus, our results provide several potential diagnostic biomarkers for distinguishing the natural history of chronic HBV infection, such as PSME1, PSMA7, EFNB2, ENO1, and IL-18BP, and also present potential therapeutic interventions for chronic hepatitis B patients, such as targeting the proteasome or glycolysis/gluconeogenesis pathways. Our findings shed new light on the development of novel diagnostic biomarkers and therapeutic targets for the diagnosis and treatment of chronic HBV infection.

Lung proteomic biomarkers associated with chronic obstructive pulmonary disease

Identifying protein biomarkers for chronic obstructive pulmonary disease (COPD) has been challenging. Most previous studies have used individual proteins or preselected protein panels measured in blood samples. Mass spectrometry proteomic studies of lung tissue have been based on small sample sizes. We used mass spectrometry proteomic approaches to discover protein biomarkers from 150 lung tissue samples representing COPD cases and controls. Top COPD-associated proteins were identified based on multiple linear regression analysis with false discovery rate (FDR) < 0.05. Correlations between pairs of COPD-associated proteins were examined. Machine learning models were also evaluated to identify potential combinations of protein biomarkers related to COPD. We identified 4,407 proteins passing quality controls. Twenty-five proteins were significantly associated with COPD at FDR < 0.05, including interleukin 33, ferritin (light chain and heavy chain), and two proteins related to caveolae (CAV1 and CAVIN1). Multiple previously reported plasma protein biomarkers for COPD were not significantly associated with proteomic analysis of COPD in lung tissue, although RAGE was borderline significant. Eleven pairs of top significant proteins were highly correlated (r > 0.8), including several strongly correlated with RAGE (EHD2 and CAVIN1). Machine learning models using Random Forests with the top 5% of protein biomarkers demonstrated reasonable accuracy (0.707) and area under the curve (0.714) for COPD prediction. Mass spectrometry-based proteomic analysis of lung tissue is a promising approach for the identification of biomarkers for COPD.

Chromatin-mediated alternative splicing regulates cocaine-reward behavior

Neuronal alternative splicing is a key gene regulatory mechanism in the brain. However, the spliceosome machinery is insufficient to fully specify splicing complexity. In considering the role of the epigenome in activity-dependent alternative splicing, we and others find the histone modification H3K36me3 to be a putative splicing regulator. In this study, we found that mouse cocaine self-administration caused widespread differential alternative splicing, concomitant with the enrichment of H3K36me3 at differentially spliced junctions. Importantly, only targeted epigenetic editing can distinguish between a direct role of H3K36me3 in splicing and an indirect role via regulation of splice factor expression elsewhere on the genome. We targeted Srsf11, which was both alternatively spliced and H3K36me3 enriched in the brain following cocaine self-administration. Epigenetic editing of H3K36me3 at Srsf11 was sufficient to drive its alternative splicing and enhanced cocaine self-administration, establishing the direct causal relevance of H3K36me3 to alternative splicing of Srsf11 and to reward behavior.

Identification of differentially expressed genes-related prognostic risk model for survival prediction in breast carcinoma patients

Since the imbalance of gene expression has been demonstrated to tightly related to breast cancer (BRCA) genesis and growth, common genes expressed of BRCA were screened to explore the essence in-between. In current work, most common differentially expressed genes (DEGs) in various subtypes of BRCA were identified. Functional enrichment analysis illustrated the driving factor of deactivation of the cell cycle and the oocyte meiosis, which critically triggers the development of BRCA. Herein, we constructed a 12-gene prognostic risk model relative to differential gene expression. Subsequently, the K-M curves, analysis on time-ROC curve and Cox regression were performed to assess this risk model by determining the respective prognostic value, and the prediction performance were ascertained for both training and validation cohorts. In addition, multivariate Cox regression was analysed to reveal the independence between risk score and prognostic stage, and the accuracy and sensitivity of prognosis are particularly improved after clinical indicators are included into the analysis. In summary, this study offers novel insights into the imbalance of gene expression within BRCA, and highlights 12 selected genes associated with patient prognosis. The risk model can help individualize treatment for patients at different risks, and propose precise strategies and treatments for BRCA therapy.

miR-223: A Key Regulator in the Innate Immune Response in Asthma and COPD

Asthma and Chronic Obstructive Pulmonary Disease (COPD) are chronic obstructive respiratory diseases characterized by airway obstruction, inflammation, and remodeling. Recent findings indicate the importance of microRNAs (miRNAs) in the regulation of pathological processes involved in both diseases. MiRNAs have been implicated in a wide array of biological processes, such as inflammation, cell proliferation, differentiation, and death. MiR-223 is one of the miRNAs that is thought to play a role in obstructive lung disease as altered expression levels have been observed in both asthma and COPD. MiR-223 is a hematopoietic cell–derived miRNA that plays a role in regulation of monocyte-macrophage differentiation, neutrophil recruitment, and pro-inflammatory responses and that can be transferred to non-myeloid cells via extracellular vesicles or lipoproteins. In this translational review, we highlight the role of miR-223 in obstructive respiratory diseases, focusing on expression data in clinical samples of asthma and COPD, in vivo experiments in mouse models and in vitro functional studies. Furthermore, we provide an overview of the mechanisms by which miR-223 regulates gene expression. We specifically focus on immune cell development and activation and involvement in immune responses, which are important in asthma and COPD. Collectively, this review demonstrates the importance of miR-223 in obstructive respiratory diseases and explores its therapeutic potential in the pathogenesis of asthma and COPD.