Construction of a robust prognostic model for adult adrenocortical carcinoma: Results from bioinformatics and real-world data

This study aims to construct a robust prognostic model for adult adrenocortical carcinoma (ACC) by large-scale multiomics analysis and real-world data. The RPPA data, gene expression profiles and clinical information of adult ACC patients were obtained from The Cancer Proteome Atlas (TCPA), Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA). Integrated prognosis-related proteins (IPRPs) model was constructed. Immunohistochemistry was used to validate the prognostic value of the IPRPs model in Fudan University Shanghai Cancer Center (FUSCC) cohort. 76 ACC cases from TCGA and 22 ACC cases from GSE10927 in NCBI’s GEO database with full data for clinical information and gene expression were utilized to validate the effectiveness of the IPRPs model. Higher FASN (P = .039), FIBRONECTIN (P < .001), TFRC (P < .001), TSC1 (P < .001) expression indicated significantly worse overall survival for adult ACC patients. Risk assessment suggested significantly a strong predictive capacity of IPRPs model for poor overall survival (P < .05). IPRPs model showed a little stronger ability for predicting prognosis than Ki-67 protein in FUSCC cohort (P = .003, HR = 3.947; P = .005, HR = 3.787). In external validation of IPRPs model using gene expression data, IPRPs model showed strong ability for predicting prognosis in TCGA cohort (P = .005, HR = 3.061) and it exhibited best ability for predicting prognosis in GSE10927 cohort (P = .0898, HR = 2.318). This research constructed IPRPs model for predicting adult ACC patients’ prognosis using proteomic data, gene expression data and real-world data and this prognostic model showed stronger predictive value than other biomarkers (Ki-67, Beta-catenin, etc) in multi-cohorts.     

Antifungal activity of nanoemulsion from Cleome viscosa essential oil against food-borne pathogenic Candida albicans

Pathogenic and spoilage fungi cause enormous challenges to food related fatal infections. Plant essential oil based classical emulsions can functions as antifungal agents. To investigate the antifungal spectrum, that is the scope of the nanoemulsion composed of Cleome viscosa essential oil and Triton-x-100 fabricated by ultrasonication method. Minimum inhibitory and fungicidal concentration of essential oil nanoemulsion (EONE) was tested against food borne pathogenic C. albicans. The MIC and MFC values ranged from 16.5 to 33 µl/ml with significant reduction on biofilm of C. albicans isolates. The alteration of molecular fingerprints was confirmed by Fourier transformed infrared spectroscopy and subsequent reduction of chitin levels in cell walls was noted by spectroscopic analysis. The EONE and their bioactive compounds cause collateral damage on C. albicans cells.     

Carbon utilization and growth-inhibition of citrus-colonizing Phyllosticta species

The genus Phyllosticta includes both endophytic and phytopathogenic species that occur on a broad range of plant hosts, including Citrus. Some pathogenic species cause severe disease, such as Phyllosticta citricarpa, the causal agent of Citrus Black Spot (CBS). In contrast, other species, such as Phyllosticta capitalensis, have an endophytic lifestyle in numerous plant hosts. Carbon utilization capabilities are hypothesized to influence both host range and lifestyle, and are in part determined by the set of Carbohydrate Active Enzyme (CAZyme) encoding genes of a species. In this study, carbon utilization capabilities of five Phyllosticta species were determined, as well as the CAZyme repertoire (CAZome) encoded in their genomes. Little variation was found among species in terms of carbon utilization capabilities and CAZome. However, one of the tested carbon sources, sugar beet pulp (SBP), inhibited growth of the plant pathogens, also when combined with another carbon source, while endophytic species remained unaffected.     

Comparative proteomic analysis of cysteine oxidation in colorectal cancer patients

Oxidative stress promotes damage to cellular proteins, lipids, membranes and DNA, and plays a key role in the development of cancer. Reactive oxygen species disrupt redox homeostasis and promote tumor formation by initiating aberrant activation of signaling pathways that lead to tumorigenesis. We used shotgun proteomics to identify proteins containing oxidation-sensitive cysteines in tissue specimens from colorectal cancer patients. We then compared the patterns of cysteine oxidation in the membrane fractions between the tumor and non-tumor tissues. Using nano-UPLC-MS^E proteomics, we identified 31 proteins containing 37 oxidation-sensitive cysteines. These proteins were observed with IAM-binding cysteines in non-tumoral region more than tumoral region of CRC patients. Then using the Ingenuity pathway program, we evaluated the cellular canonical networks connecting those proteins. Within the networks, proteins with multiple connections were related with organ morphology, cellular metabolism, and various disorders. We have thus identified networks of proteins whose redox status is altered by oxidative stress, perhaps leading to changes in cellular functionality that promotes tumorigenesis.     

Constitutive heat shock protein 70 interacts with α-enolase and protects cardiomyocytes against oxidative stress

Abstract

Constitutive heat shock protein 70 (Hsc70) is a molecular chaperone that has been shown to protect cardiomyocytes against oxidative stress. However, the molecular mechanism responsible for this protection remains uncertain. To understand the mechanism associated with the myocardial protective role of Hsc70, we have embarked upon a systematic search for Hsc70-interacting proteins. Using adenosine diphosphate (ADP) affinity chromatography and mass spectrometry, we have identified α-enolase, a rate-limiting enzyme in glycolysis, as a novel Hsc70-interacting protein in the myocardium of both sham and myocardial ischemia-reperfused Sprague–Dawley rat hearts. This interaction was confirmed by co-immunoprecipitation (IP) assays in the myocardial tissues and H9c2 cardiomyocytes and protein overlay assay (POA). It was further shown that Hsc70-overexpression alleviated the H₂O₂-induced decrease of α-enolase activity and cell damage, and Hsc70 deficiency aggravated the decrease of α-enolase activity and cell damage in H₂O₂ treated H9c2 cells. Our research suggests that the protective effect of Hsc70 on the cardiomyocytes against oxidative stress is partly associated with its interaction with α-enolase.     

2D-LC/MS techniques for the identification of proteins in highly complex mixtures

Today, 2D online or offline liquid chromatography/mass spectrometry is state of the art for the identification of proteins from complex proteome samples in many laboratories. Both 2D liquid chromatography methods use two orthogonal liquid chromatography separation techniques. The most commonly used techniques are strong cation exchange chromatography for the first dimension and reversed phase separation for the second dimension. In order to improve sensitivity the reversed phase separation is usually performed in the nanoflow scale and mass spectrometry is used as the final detection method. The high-performance liquid chromatography techniques complement the 2D-gel techniques supporting their weaknesses. This is especially true for the gel separation of hydrophobic membrane proteins, which play an important role in living cells as well as being important targets for future pharmaceutical drugs.     

Role of oncoproteomics in the personalized management of cancer

Oncoproteomics is the term used to describe the application of proteomic technologies in oncology and parallels the related field of oncogenomics. It is now contributing to the development of personalized management of cancer. Proteomic technologies are used for the identification of biomarkers in cancer, which will facilitate the integration of diagnosis and therapy of cancer. Molecular diagnostics, laser capture microdissection and protein biochips are among the technologies that are having an important impact on oncoproteomics. The discovery of protein patterns developed by the US Food and Drug Administration/National Cancer Institute Clinical Proteomics Program is capable of distinguishing cancer and disease-free states with high sensitivity and specificity and will also facilitate the development of personalized therapy of cancer. Examples of application are given for breast and prostate cancer and a selection of companies and their collaborations that are developing application of proteomics to personalized treatment of cancer are discussed. Continued refinement of techniques and methods to determine the abundance and status of proteins in vivo holds great promise for the future study of normal cells and the pathology of associated neoplasms. Personalized cancer therapy is expected to be in the clinic by the end of the first decade of the 21st century.     

Proteomic study of skeletal muscle in obesity and type 2 diabetes: progress and potential

ABSTRACT

Introduction: Skeletal muscle is the major site of insulin-stimulated glucose uptake and imparts the beneficial effects of exercise, and hence is an important site of insulin resistance in obesity and type 2 diabetes (T2D). Despite extensive molecular biology-oriented research the molecular mechanisms underlying insulin resistance in skeletal muscle remain to be established.

Areas covered: The proteomic capabilities have greatly improved over the last decades. This review summarizes the technical challenges in skeletal muscle proteomics studies as well as the results of quantitative proteomic studies of skeletal muscle in relation to obesity, T2D, and exercise.

Expert commentary: Current available proteomic studies contribute to the view that insulin resistance in obesity and T2D is associated with increased glycolysis and reduced mitochondrial oxidative metabolism in skeletal muscle, and that the latter can be improved by exercise. Future proteomics studies should be designed to markedly intensify the identification of abnormalities in metabolic and signaling pathways in skeletal muscle of insulin-resistant individuals to increase the understanding of the pathogenesis of T2D, but more importantly to identify multiple novel targets of treatment of which at least some can be safely targeted by novel drugs to treat and prevent T2D and reduce risk of cardiovascular disease.     

Oncoproteomics: current trends and future perspectives

Oncoproteomics is the application of proteomics technologies in oncology. Functional proteomics is a promising technique for the rational identification of biomarkers and novel therapeutic targets for cancers. Recent progress in proteomics has opened new avenues for tumor-associated biomarker discovery. With the advent of new and improved proteomics technologies, such as the development of quantitative proteomic methods, high-resolution, -speed and -sensitivity mass spectrometry and protein arrays, as well as advanced bioinformatics for data handling and interpretation, it is now possible to discover biomarkers that can reliably and accurately predict outcomes during cancer management and treatment. However, there are several difficulties in the study of proteins/peptides that are not inherent in the study of nucleic acids. New challenges arise in large-scale proteomic profiling when dealing with complex biological mixtures. Nevertheless, oncoproteomics offers great promise for unveiling the complex molecular events of tumorigenesis, as well as those that control clinically important tumor behaviors, such as metastasis, invasion and resistance to therapy. In this review, the development and advancement of oncoproteomics technologies for cancer research in recent years are expounded.     

Postgenomics of Neisseria meningitidis for vaccines development

Meningococcal disease is a global problem. Multivalent (A, C, Y, W135) conjugate vaccines have been developed and licensed; however, an effective vaccine against serogroup B has not yet become available. Outer membrane vesicle (OMV) vaccines have been used to disrupt serogroup B epidemics and outbreaks. Postgenomic technologies have been useful in aiding the discovery of new protein vaccine candidates. Moreover, proteomic technologies enable large-scale identification of membrane and surface-associated proteins, and provide suitable methods to characterize and standardize the antigen composition of OMV-based vaccines.