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

Comparison of blocking reagents for antibody microarray-based immunoassays on glass and paper membrane substrates

Background noise due to nonspecific binding of biomolecules on the assay substrates is one of the most common challenges that limits the sensitivity of microarray-based immunoassays. Background signal intensity usually increases when complex biological fluids are used because they have a combination of molecules and vesicles that can adsorb onto substrate surfaces. Blocking strategies coupled with surface chemistries can reduce such nonspecific binding and improve assay sensitivity. In this paper, we conducted a systematic optimization of blocking strategies on a variety of commonly used substrates for protein measurement in complex biofluids. Four blocking strategies (BSA, non-fat milk, PEG, and a protein-free solution) coupled with four surface chemistries (3-glycidoxypropyltrimethoxysilane (GPS), poly-L-lysine (PLL), aminoalkylsilane (AAS), and nitrocellulose (NC)) were studied for their effect on background, microspot, and net signal intensities. We have also explored the effect that these blocking strategies have when proteins in complex samples (plasma, serum, cell culture media, and EV lysate) are measured. Irregular spot morphology could affect signal extraction using automated software. We found that the microspots with the best morphology were the ones printed on GPS glass surfaces for all immunoassays. On NC membrane, the protein-based blocking strategies yielded the highest net fluorescent intensity with the antigen contained in PBS, plasma, serum, and serum-free cell culture media. Differently, with EV lysate samples, Pierce™ protein-free blocker yielded the best net signal intensity on both GPS and NC surfaces. The choice of blocking strategies highly depends on the substrate. Moreover, the findings discovered in this study are not limited to microarray-based immunoassays but can provide insights for other assay formats.

Digesting the Role of JAK-STAT and Cytokine Signaling in Oral and Gastric Cancers

When small proteins such as cytokines bind to their associated receptors on the plasma membrane, they can activate multiple internal signaling cascades allowing information from one cell to affect another. Frequently the signaling cascade leads to a change in gene expression that can affect cell functions such as proliferation, differentiation and homeostasis. The Janus kinase-signal transducer and activator of transcription (JAK-STAT) and the tumor necrosis factor receptor (TNFR) are the pivotal mechanisms employed for such communication. When deregulated, the JAK-STAT and the TNF receptor signaling pathways can induce chronic inflammatory phenotypes by promoting more cytokine production. Furthermore, these signaling pathways can promote replication, survival and metastasis of cancer cells. This review will summarize the essentials of the JAK/STAT and TNF signaling pathways and their regulation and the molecular mechanisms that lead to the dysregulation of the JAK-STAT pathway. The consequences of dysregulation, as ascertained from founding work in haematopoietic malignancies to more recent research in solid oral-gastrointestinal cancers, will also be discussed. Finally, this review will highlight the development and future of therapeutic applications which modulate the JAK-STAT or the TNF signaling pathways in cancers.

Development and Validation of a Three-Gene Prognostic Signature Based on Tumor Microenvironment for Gastric Cancer

Gastric cancer (GC), which has high morbidity and low survival rate, is one of the most common malignant tumors in the world. The increasing evidences show that the tumor microenvironment (TME) is related to the occurrence and progression of tumors and the prognosis of patients. In this study, we aimed to develop a TME-based prognostic signature for GC. We first identified the differentially expressed genes (DEGs) related to the TME using the Wilcoxon rank-sum test in a training set of GC. Univariate Cox regression analysis was used to identify prognostic-related DEGs. To decrease the overfitting, we performed the least absolute shrinkage and selection operator (LASSO) regression to reduce the number of signature genes and obtained three genes (LPPR4, ADAM12, NOX4). Next, the multivariate Cox regression was performed to construct the risk score model, and a three-gene prognostic signature was developed. According to the signature, patients were classified into high-risk and low-risk groups with significantly different survival. The signature was then applied to three independent validated sets and obtained the same results. We conducted the time-dependent Receiver Operating Characteristic (ROC) curve analysis to evaluate our signature. We further evaluated the differential immune characters between high-risk and low-risk patients to reveal the potential immune mechanism of the impact on the prognosis of the model. Overall, we identified a three-gene prognostic signature based on TME to predict the prognosis of patients with GC and facilitate the development of a precise treatment strategy.

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.

Local and Systemic IL-7 Concentration in Gastrointestinal-Tract Cancers

Background and objectives: Interleukin-7 (IL-7) is exploited in cancer immunotherapies although its status in solid tumors is largely unknown. We aimed to determine its systemic and local concentrations in esophageal (EC), gastric (GC), and colorectal (CRC) cancers. Materials and Methods: IL-7 was immunoenzymatically measured in paired surgical specimens of tumors and tumor-adjacent tissue (n = 48), and in the sera of 170 individuals (54 controls and 116 cancer patients). Results: IL-7 was higher in tumors as compared to noncancerous tissue in all cancers (mean difference: 29.5 pg/g). The expression ratio (tumor to normal) was 4.4-fold in GC, 2.2-fold in EC, and 1.7-fold in CRC. However, when absolute concentrations were compared, the highest IL-7 concentrations were in CRC, both when tumor and noncancerous tissue were analyzed. In CRC tumors, IL-7 was 2 and 1.5 times higher than in EC and GC tumors. In noncancerous CRC tissue, IL-7 was 2.3- and 2.8-fold higher than in EC and GC. IL-7 overexpression was more pronounced in Stage 3/4 and N1 cancers as a result of decreased cytokine expression in noncancerous tissue. Tumor location was a key factor in determining both local and systemic IL-7 concentrations. Serum IL-7 in CRC and EC was higher than in controls, GC, and patients with adenocarcinoma of gastric cardia (CC), but no significant correlation with the disease advancement could be observed. Conclusions: IL-7 protein is overexpressed in EC, GC, and CRC, but concentrations differ both in tumor and tumor-adjacent tissue with respect to tumor location. More advanced cancers have lower IL-7 concentrations in the immediate environment of the tumor. At the systemic level, IL-7 is elevated in CRC and EC, but not CC or GC. IL-7 dependence on the location of the primary tumor should be taken into account in future IL-7-based immunotherapies. Functional studies explaining a role of IL-7 in gastrointestinal cancers are needed.