Co-expression Network Analysis Identified Key Proteins in Association With Hepatic Metastatic Colorectal Cancer

Identification and analysis of the molecular targets of statins in colorectal cancer

Colorectal cancer (CRC) is the third most common cancer in the world. According to several types of research, statins may impact the development and treatment of CRC. This work aimed to use bioinformatics to discover the relationship between statin targets and differentially expressed genes (DEGs) in CRC patients and determine the possible molecular effect of statins on CRC suppression. We used CRC datasets from the GEO database to select CRC-related DEGs. DGIdb and STITCH databases were used to identify gene targets of subtypes of statin. Further, we identified the statin target of CRC DEGs hub genes by using a Venn diagram of CRC DEGs and statin targets. Funrich and enrichr databases were carried out for the KEGG pathway and gene ontology (GO) enrichment analysis, respectively. GSE74604 and GSE10950 were used to identify CRC DEGs. After analyzing datasets,1370 genes were identified as CRC DEGs, and 345 targets were found for statins. We found that 35 genes are CRC DEGs statin targets. We found that statin targets in CRC were enriched in the receptor and metallopeptidase activity for molecular function, cytoplasm and plasma membrane for cellular component, signal transduction, and cell communication for biological process genes were substantially enriched based on FunRich enrichment. Analysis of the KEGG pathways revealed that the overexpressed DEGs were enriched in the IL-17, PPAR, and Toll-like receptor signaling pathways. Finally, CCNB1, DNMT1, AURKB, RAC1, PPARGC1A, CDKN1A, CAV1, IL1B, and HSPD1 were identified as hub CRC DEGs statin targets. The genetic and molecular aspects of our findings reveal that statins might have a therapeutic effect on CRC.

Identification of exosome protein panels as predictive biomarkers for non-small cell lung cancer

BACKGROUND

Non-small cell lung cancer (NSCLC) remains a leading cause of cancer-related deaths worldwide, primarily due to its propensity for metastasis. Patients diagnosed with localized primary cancer have higher survival rates than those with metastasis. Thus, it is imperative to discover biomarkers for the early detection of NSCLC and the timely prediction of tumor metastasis to improve patient outcomes.

METHODS

Here, we utilized an integrated approach to isolate and characterize plasma exosomes from NSCLC patients as well as healthy individuals. We then conducted proteomics analysis and parallel reaction monitoring to identify and validate the top-ranked proteins of plasma exosomes.

RESULTS

Our study revealed that the proteome in exosomes from NSCLC patients with metastasis was distinctly different from that from healthy individuals. The former had larger diameters and lower concentrations of exosomes than the latter. Furthermore, among the 1220 identified exosomal proteins, we identified two distinct panels of biomarkers. The first panel of biomarkers (FGB, FGG, and VWF) showed potential for early NSCLC diagnosis and demonstrated a direct correlation with the survival duration of NSCLC patients. The second panel of biomarkers (CFHR5, C9, and MBL2) emerged as potential biomarkers for assessing NSCLC metastasis, of which CFHR5 alone was significantly associated with the overall survival of NSCLC patients.

CONCLUSIONS

These findings underscore the potential of plasma exosomal biomarkers for early NSCLC diagnosis and metastasis prediction. Notably, CFHR5 stands out as a promising prognostic indicator for NSCLC patients. The clinical utility of exosomal biomarkers offers the potential to enhance the management of NSCLC.

Proteome profiling of endogenous and potential S-nitrosylation in colorectal cancer

Background

As a common cancer with high incidence rate and mortality, colorectal cancer (CRC) is seriously threatening human health. S-nitrosylation (SNO) proteins mediated by nitric oxide (NO) has important implications in the genesis, progression, and apoptosis of CRC. It's worth noting that the SNO proteins also play an important role in the tumor endocrine and metabolic pathways of CRC.

Materials and methods

In this study, the protein extracts of human tissues and cell lines were treated by biotin switch technology and magnetic beads enrichment. The proteomic results of endogenous and potential SNO proteins were analyzed by mass spectrometry (MS). Through the comparison and analysis of MS results, Gene Ontology (GO) analysis, and literatures, some endogenous and potential SNO proteins were identified in CRC, which were closely related to the tumor endocrine and metabolic pathways, the apoptotic signaling pathways, protein maturation, and other biological processes of the proliferation and apoptosis of CRC cells.

Results

A total of 19 proteins containing potential or endogenous SNO sites were detected in both human cancer tissue and SW 480 cells. Through the cross validation of MS results, GO analysis, and literatures, several SNO proteins were identified frequently in CRC, such as the actin, cytoplasmic 1 (ACTB), peroxiredoxin-4 (PRDX4), protein S100A8 (S100A8), pyruvate kinase PKM (PKM), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), which were closely related to the tumor endocrine and metabolic pathways and the apoptotic signaling pathways of CRC.

Conclusion

Different CRC cells and tissues contained potential and endogenous SNO modified proteins. In addition, some SNO proteins could participate in the proliferation, metastasis and apoptosis of CRC by regulating the tumor endocrine and metabolic pathways.

Advancements in Oncoproteomics Technologies: Treading toward Translation into Clinical Practice

Proteomics continues to forge significant strides in the discovery of essential biological processes, uncovering valuable information on the identity, global protein abundance, protein modifications, proteoform levels, and signal transduction pathways. Cancer is a complicated and heterogeneous disease, and the onset and progression involve multiple dysregulated proteoforms and their downstream signaling pathways. These are modulated by various factors such as molecular, genetic, tissue, cellular, ethnic/racial, socioeconomic status, environmental, and demographic differences that vary with time. The knowledge of cancer has improved the treatment and clinical management; however, the survival rates have not increased significantly, and cancer remains a major cause of mortality. Oncoproteomics studies help to develop and validate proteomics technologies for routine application in clinical laboratories for (1) diagnostic and prognostic categorization of cancer, (2) real-time monitoring of treatment, (3) assessing drug efficacy and toxicity, (4) therapeutic modulations based on the changes with prognosis and drug resistance, and (5) personalized medication. Investigation of tumor-specific proteomic profiles in conjunction with healthy controls provides crucial information in mechanistic studies on tumorigenesis, metastasis, and drug resistance. This review provides an overview of proteomics technologies that assist the discovery of novel drug targets, biomarkers for early detection, surveillance, prognosis, drug monitoring, and tailoring therapy to the cancer patient. The information gained from such technologies has drastically improved cancer research. We further provide exemplars from recent oncoproteomics applications in the discovery of biomarkers in various cancers, drug discovery, and clinical treatment. Overall, the future of oncoproteomics holds enormous potential for translating technologies from the bench to the bedside.

Construction of 2DE Patterns of Plasma Proteins: Aspect of Potential Tumor Markers

The use of tumor markers aids in the early detection of cancer recurrence and prognosis. There is a hope that they might also be useful in screening tests for the early detection of cancer. Here, the question of finding ideal tumor markers, which should be sensitive, specific, and reliable, is an acute issue. Human plasma is one of the most popular samples as it is commonly collected in the clinic and provides noninvasive, rapid analysis for any type of disease including cancer. Many efforts have been applied in searching for “ideal” tumor markers, digging very deep into plasma proteomes. The situation in this area can be improved in two ways—by attempting to find an ideal single tumor marker or by generating panels of different markers. In both cases, proteomics certainly plays a major role. There is a line of evidence that the most abundant, so-called “classical plasma proteins”, may be used to generate a tumor biomarker profile. To be comprehensive these profiles should have information not only about protein levels but also proteoform distribution for each protein. Initially, the profile of these proteins in norm should be generated. In our work, we collected bibliographic information about the connection of cancers with levels of “classical plasma proteins”. Additionally, we presented the proteoform profiles (2DE patterns) of these proteins in norm generated by two-dimensional electrophoresis with mass spectrometry and immunodetection. As a next step, similar profiles representing protein perturbations in plasma produced in the case of different cancers will be generated. Additionally, based on this information, different test systems can be developed.

Proteomic Profiling and Biomarker Discovery in Colorectal Liver Metastases

Colorectal liver metastases (CRLM) are the leading cause of death among patients with metastatic colorectal cancer (CRC). As part of multimodal therapy, liver resection is the mainstay of curative-intent treatment for select patients with CRLM. However, effective treatment of CRLM remains challenging as recurrence occurs in most patients after liver resection. Proposed clinicopathologic factors for predicting recurrence are inconsistent and lose prognostic significance over time. The rapid development of next-generation sequencing technologies and decreasing DNA sequencing costs have accelerated the genomic profiling of various cancers. The characterisation of genomic alterations in CRC has significantly improved our understanding of its carcinogenesis. However, the functional context at the protein level has not been established for most of this genomic information. Furthermore, genomic alterations do not always result in predicted changes in the corresponding proteins and cancer phenotype, while post-transcriptional and post-translational regulation may alter synthesised protein levels, affecting phenotypes. More recent advancements in mass spectrometry-based technology enable accurate protein quantitation and comprehensive proteomic profiling of cancers. Several studies have explored proteomic biomarkers for predicting CRLM after oncologic resection of primary CRC and recurrence after curative-intent resection of CRLM. The current review aims to rationalise the proteomic complexity of CRC and explore the potential applications of proteomic biomarkers in CRLM.

Proteomics of post-translational modifications in colorectal cancer: Discovery of new biomarkers

Colorectal cancer (CRC) is one of the costliest health problems and ranks second in cancer-related mortality in developed countries. With the aid of proteomics, many protein biomarkers for the diagnosis, prognosis, and precise management of CRC have been identified. Furthermore, some protein biomarkers exhibit structural diversity after modifications. Post-translational modifications (PTMs), most of which are catalyzed by a variety of enzymes, extensively increase protein diversity and are involved in many complex and dynamic cellular processes through the regulation of protein function. Accumulating evidence suggests that abnormal PTM events are associated with a variety of human diseases, such as CRC, thus highlighting the need for studying PTMs to discover both the molecular mechanisms and therapeutic targets of CRC. In this review, we begin with a brief overview of the importance of protein PTMs, discuss the general strategies for proteomic profiling of several key PTMs (including phosphorylation, acetylation, glycosylation, ubiquitination, methylation, and citrullination), shift the emphasis to describing the specific methods used for delineating the global landscapes of each of these PTMs, and summarize the recent applications of these methods to explore the potential roles of the PTMs in CRC. Finally, we discuss the current status of PTM research on CRC and provide future perspectives on how PTM regulation can play an essential role in translational medicine for early diagnosis, prognosis stratification, and therapeutic intervention in CRC.

C8B in Complement and Coagulation Cascades Signaling Pathway is a predictor for Survival in HBV-Related Hepatocellular Carcinoma Patients

OBJECTIVE

The role of the complement and coagulation cascades signaling pathway in the pathogenesis of cancers remains uncertain. This study aimed to investigate the associations between enriched differentially expressed genes (DEGs) in this pathway and hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) patients.

MATERIALS AND METHODS

Clinical and gene expression data of the Gene Expression Omnibus (GEO) series profile GSE14520 were downloaded. The "Limma" package was used to screen the DEGs and the "clusterProfiler" package was used to identify the complement and coagulation cascades pathway and enriched significant genes. Cox regression analysis, the Kaplan-Meier method, and the nomogram model were used to address the correlations between significantly enriched DEGs in the complement and coagulation cascades pathway and HCC survival.

RESULTS

A total of 220 HBV-related HCC patients were enrolled in this study. The complement and coagulation cascades pathway was significantly enriched by 37 DEGs (p-value < 0.05 and adjusted p-value < 0.05). Complement 8 beta chain (C8B) expression levels had protective effects on overall survival (OS) and recurrence-free survival (RFS) in HBV-related HCC patients. High levels of C8B contributed to favorable OS and RFS in this population (both p < 0.01), even after adjustment of clinicopathological characteristics including tumor node metastasis (TNM) staging, Barcelona Clinic liver cancer (BCLC) staging, gender, and fibrinogen beta chain (FGB) expression (all p < 0.05).

CONCLUSION

C8B in the complement and coagulation cascades signaling pathway serves as a predictive candidate for survival in HBV-related HCC patients.

Construction of gene-classifier and co-expression network analysis of genes in association with major depressive disorder

Because the pathogenesis of major depressive disorder (MDD) is still unclear and the accurate diagnosis remains unavailable, we aimed to analyze its molecular mechanisms and develop a gene classifier to improve diagnostic accuracy. We extracted differentially expressed genes from two datasets, GSE45642 (from brain tissue samples) and GSE98793 (from blood samples), and found three key modules to have a significant correlation with MDD traits by weighted gene coexpression network analysis. Hub genes were identified from the key modules according to the connectivity degree in the network and subjected to least absolute shrinkage and selection operator regression analysis. A total of eighty-five hub genes were selected to construct the gene classifier, which had considerable ability to recognize MDD patients in the training set and test set. In addition, the relationship between the key MDD modules and brain tissues indicated that the anterior cingulate should be a notable region in the study of MDD pathogenesis. The results of Gene Ontology (GO) and pathway enrichment analyses reiterate the relationship between depression and immunity. Therefore we identified MDD hub genes in the InnateDB database, and found 14 genes involved in both MDD and the inflammatory response.

Comprehensive analysis of location-specific hub genes related to the pathogenesis of colon cancer

The molecular mechanisms underlying colon cancer lesions at different sites are not entirely clear. Herein, we aimed to explore location-specific gene profiles related to the pathogenesis of colon cancer and to identify their function. The robust rank aggregation (RRA) method was used to integrate colon cancer microarray datasets and screen differentially expressed gene (DEG) profiles between left- and right-sided colon cancers. Then, weighted gene co-expression network analysis (WGCNA) was performed to cluster the DEGs into modules and identify hub genes. The selected hub genes were validated using The Cancer Genome Atlas dataset and clinical tissues. We assessed the association of selected hub genes with the methylation status in immune cells. In total, 905 DEGs were identified by RRA; five gene modules and 18 hub genes were related to the clinical traits of colon cancer by WGCNA. Four hub genes were selected and shown to be associated with colon cancers on different sides and distant metastasis in the validation analysis. The four hub genes showed a low methylation status, and their expression was significantly associated with methylation status. Positive correlations were observed between the four hub genes and tumor purity and among the four types of immune cells. Gene set enrichment analysis revealed that the four hub genes were mainly involved in two cancer-related pathways. In conclusion, this study identified a set of location-specific genes related to the pathogenesis of colon cancer. These four hub genes may act as novel candidate targets for the treatment of colon cancer.

Non-translational Connections of eEF1B in the Cytoplasm and Nucleus of Cancer Cells

The human translation machinery includes three types of supramolecular complexes involved in elongation of the polypeptide chain: the ribosome, complex of elongation factors eEF1B and multienzyme aminoacyl-tRNA synthetase complex. Of the above, eEF1B is the least investigated assembly. Recently, a number of studies provided some insights into the structure of different eEF1B subunits and changes in their expression in cancer and other diseases. There is increasing agreement that possible disease-related functions of eEF1B are not necessarily related to its role in translation. This mini-review focuses on structural and functional features of the eEF1B complex while paying special attention to possible non-canonical functions of its subunits in cancer cells.