Discovery and validation of an INflammatory PROtein-driven GAstric cancer Signature (INPROGAS) using antibody microarray-based oncoproteomics

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.

Role of serum matrix metalloproteinase in the diagnosis of gastric cancer

Objective

To determine the clinical value of a matrix metalloproteinase (MMP) antibody array in diagnosing gastric cancer (GC).

Methods

In this prospective study, serum samples of patients with GC (n=66) and non-neoplastic gastric disease (NGD; n=34) were collected between November 2017 and July 2018. The quantitative measurement of 10 MMP-related proteins was done using MMP arrays and compared between the two groups.

Results

The serum levels of MMPs 3, 8, 9 and tissue inhibitor of metalloproteinases (TIMPs) 1 and 2 were significantly higher in the GC group than in the NGD group (p<0.05). The area under curve (AUC) of the 10 MMP proteins for the diagnosis of GC varied between 0.500 and 0.658. The total AUC of all MMPs was 0.897 (95% CI: 0.837-0.957). The total AUC of the five MMPs (MMPs 3, 8, 9, and TIMPs 1 and 2) was 0.821 (95% CI: 0.733-0.909) for diagnosing GC. Also, the 10-factor and 5-factor predictive models had good diagnostic ability for early GC with an AUC of 0.865 (95% CI: 0.753-0.977) and 0.749 (95% CI: 0.600-0.898), respectively.

Conclusions

The detection of multiple serum MMPs with protein biochip technology is promising to be used as a novel non-invasive tool for facilitating early diagnosis or screening of GC.

Current applications of antibody microarrays

The concept of antibody microarrays is one of the most versatile approaches within multiplexed immunoassay technologies. These types of arrays have increasingly become an attractive tool for the exploratory detection and study of protein abundance, function, pathways, and potential drug targets. Due to the properties of the antibody microarrays and their potential use in basic research and clinical analytics, various types of antibody microarrays have already been developed. In spite of the growing number of studies utilizing this technique, few reviews about antibody microarray technology have been presented to reflect the quality and future uses of the generated data. In this review, we provide a summary of the recent applications of antibody microarray techniques in basic biology and clinical studies, providing insights into the current trends and future of protein analysis.

Expression profile of cytokines in gastric cancer patients using proteomic antibody microarray

Gastric cancer (GC) is often a deadly disease due to the late diagnosis and chemoresistance that characterizes many cases of this disease. The aim of this study was to explore a panel of candidate cytokines as diagnostic and predictive biomarkers for GC. Sixteen tissue samples of GC and adjacent noncancerous mucosa were selected from GC patients (n=8) for antibody microarray analysis. Proteomic chip-based analysis was performed to simultaneously identify 507 cytokines using a cytokine antibody array in the gastric tissues to screen for differential proteins related in cases of GC. Fold changes of protein expression >2.0 or <0.5 were considered significant. The proteins that showed significant differences in levels between the cancerous and non-cancerous samples were analyzed using bioinformatics analysis. One hundred and five cytokines that were significantly different (p<0.05) between GC tissues and normal gastric mucosa were identified. Gene Ontology (GO) enrichment analysis showed that these differentially expressed proteins are involved in many biological and immunological processes, mainly in response to stress, chloroplast thylakoid membrane, vacuole, photosynthesis, aspartic-type endopeptidase activity and flavin adenine dinucleotide binding. Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis indicated that these proteins mainly were involved in the process of cytokine-cytokine receptor interaction, transforming growth factor-β (TGF-β) signaling pathway, pathways in cancer, tumor necrosis factor (TNF) signaling pathway, and mitogen-activated protein kinase (MAPK) signaling pathway. These findings suggest that the differentially expressed proteins could be associated with GC in patients. Further study of these cytokines may provide a promising approach for diagnosis, classification and prognosis of GC.

Comprehensive analysis of a novel four-lncRNA signature as a prognostic biomarker for human gastric cancer

Emerging evidence indicates that long non-coding RNAs (lncRNAs) play a crucial role in predicting survival for gastric cancer (GC) patients. This study aims to identify a lncRNA-related signature for evaluating the overall survival of 379 GC patients from The Cancer Genome Atlas (TCGA) database. The associations between survival outcome and the expression of lncRNAs were evaluated by the univariate and multivariate Cox proportional hazards regression analyses. Four lncRNAs (LINC01018, LOC553137, MIR4435-2HG, and TTTY14) were identified as significantly correlated with overall survival. These four lncRNAs were gathered as a single prognostic signature. There was a significant positive correlation between GC patients with low-risk scores and overall survival (P = 0.001). Further analysis suggested that the prognostic value of this four-lncRNA signature was independent in clinical features. Gene set enrichment analysis found that these four lncRNAs were correlated with several molecular pathways of the tumor. Our study indicates that this novel lncRNA expression signature may be a useful biomarker of the prognosis for GC patients, based on bioinformatics analysis.

Simple and effective label-free electrochemical immunoassay for carbohydrate antigen 19-9 based on polythionine-Au composites as enhanced sensing signals for detecting different clinical samples

Carbohydrate antigen 19-9 (CA19-9) is an important biomarker for the early diagnosis and clinical monitoring of pancreatic cancer. Reliable, simple, and accurate methods for the detection of CA19-9 are still urgently needed. In this study, polythionine-Au composites (AuNPs@ PThi) were designed and prepared through one-pot reaction using HAuCl₄ as the co-oxidant and raw material in thionine solution containing FeCl₃ as the oxidant. AuNPs@PThi-immobilized glassy carbon electrode was used as a sensitive redox probe for electrochemical interface. AuNPs@PThi not only favored the amplification of electrochemical signals but also facilitated excellent environmental friendliness for bioassay. Maximizing the electrochemical properties of AuNPs@PThi, an effective label-free electrochemical immunoassay for the ultrasensitive and reliable detection of CA19-9 was developed. Under optimal conditions, the linear range of the proposed immunosensor was estimated to range from 6.5 to 520 U/mL, with a detection limit of 0.26 U/mL at a signal-to-noise ratio of 3. The prepared immunosensor for CA19-9 detection showed high sensitivity, stability, and reproducibility. Furthermore, the fabricated immunosensor based on AuNPs@PThi can effectively detect and distinguish clinical serum samples of pancreatic cancer and normal control with accuracy and convenience.

Progress and prospects for the discovery of biomarkers for gastric cancer: a focus on proteomics

INTRODUCTION

Patient outcomes from gastric cancer vary due to the complexity of stomach carcinogenesis. Recent research using proteomic technologies has targeted components of all of these systems in order to develop biomarkers to aid the early diagnosis of gastric cancer and to assist in prognostic stratification. Areas covered: This review is comprised of evidence obtained from literature searches from PubMed. It covers the evidence of diagnostic, prognostic, and predictive biomarkers for gastric cancer using proteomic technologies, and provides up-to-date references. Expert commentary: The proteomic technologies have not only enabled the screening of a large number of samples, but also enabled the identification of diagnostic, prognostic and predictive biomarkers for gastric cancer. While major challenges still remain, to date, proteomic studies in gastric cancer have provided a wealth of information in revealing proteome alterations associated with the disease.

Epigenetics and nutrition-related epidemics of metabolic diseases: Current perspectives and challenges

We live in a world fascinated by the relationship between disease and nutritional disequilibrium. The subtle and slow effects of chronic nutrient toxicity are a major public health concern. Since food is potentially important for the development of "metabolic memory", there is a need for more information on the type of nutrients causing adverse or toxic effects. We now know that metabolic alterations produced by excessive intake of some nutrients, drugs and chemicals directly impact epigenetic regulation. We envision that understanding how metabolic pathways are coordinated by environmental and genetic factors will provide novel insights for the treatment of metabolic diseases. New methods will enable the assembly and analysis of large sets of complex molecular and clinical data for understanding how inflammation and mitochondria affect bioenergetics, epigenetics and health. Collectively, the observations we highlight indicate that energy utilization and disease are intimately connected by epigenetics. The challenge is to incorporate metabolo-epigenetic data in better interpretations of disease, to expedite therapeutic targeting of key pathways linking nutritional toxicity and metabolism. An additional concern is that changes in the parental phenotype are detectable in the methylome of subsequent offspring. The effect might create a menace to future generations and preconceptional considerations.

Proteomic Approaches for Biomarker Panels in Cancer

Proteomic technologies remain the main backbone of biomarkers discovery in cancer. The continuous development of proteomic technologies also enlarges the bioinformatics domain, thus founding the main pillars of cancer therapy. The main source for diagnostic/prognostic/therapy monitoring biomarker panels are molecules that have a dual role, being both indicators of disease development and therapy targets. Proteomic technologies, such as mass-spectrometry approaches and protein array technologies, represent the main technologies that can depict these biomarkers. Herein, we will illustrate some of the most recent strategies for biomarker discovery in cancer, including the development of immune-markers and the use of cancer stem cells as target therapy. The challenges of proteomic biomarker discovery need new forms of cross-disciplinary conglomerates that will result in increased and tailored access to treatments for patients; diagnostic companies would benefit from the enhanced co-development of companion diagnostics and pharmaceutical companies. In the technology optimization in biomarkers, immune assays are the leaders of discovery machinery.