Tumor-associated antigens and their antibodies in the screening, diagnosis, and monitoring of esophageal cancers

Diagnostic performance of anti-MAGEA family protein autoantibodies in esophageal squamous cell carcinoma

MAGEA family proteins are immunogenic and can produce corresponding autoantibodies, and we aim to evaluate the diagnostic value of anti-MAGEA family protein autoantibodies in esophageal squamous cell carcinoma (ESCC). Protein chip was used to detect the expression level of anti-MAGEA autoantibodies (IgG and IgM) in 20 mixed serum samples. Enzyme linked immunosorbent assay was adopted to determine the expression level of autoantibodies in 1019 serum samples (423 ESCC, 423 healthy control (HC), 173 benign esophageal disease (BED)), and stepwise logistic regression analysis was used for developing a diagnostic model. Eight anti-MAGEA autoantibodies were screened out based on the protein chip. The levels of 7 autoantibodies (MAGEA1-IgG, MAGEA3-IgG, MAGEA3-IgM, MAGEA4-IgG, MAGEA6-IgG, MAGEA10-IgG, MAGEA12-IgG) in ESCC were significantly higher than that in HC, and the levels of anti-MAGEA1 IgG, anti-MAGEA3-IgG, anti-MAGEA4-IgG, anti-MAGEA10-IgG and anti-MAGEA12-IgG autoantibodies in ESCC group were significantly higher than those in BED group. The area under curve (AUC), sensitivity and specificity of the logistic regression model (MAGEA1-IgG, MAGEA4-IgG, MAGEA6-IgG, MAGEA12-IgG) in the training set and the validation set were 0.725 and 0.698, 55.2% and 51.8%, 80.4% and 84.5%, respectively, in distinguishing ESCC and HC. The model also could distinguish between ESCC and BED, with the AUC of 0.743, sensitivity of 55.4% and specificity of 89.0%. The positive rate of the model combined with cytokeratin 19 fragment to diagnose ESCC reached 78.0%. The study identified anti-MAGEA autoantibodies with potential diagnostic value for ESCC, which may provide new promising for the detection of the disease.

Emerging concepts regarding pro- and anti tumor properties of B cells in tumor immunity

Controversial views regarding the roles of B cells in tumor immunity have existed for several decades. However, more recent studies have focused on its positive properties in antitumor immunity. Many studies have demonstrated a close association of the higher density of intratumoral B cells with favorable outcomes in cancer patients. B cells can interact with T cells as well as follicular dendritic cells within tertiary lymphoid structures, where they undergo a series of biological events, including clonal expansion, somatic hypermutation, class switching, and tumor-specific antibody production, which may trigger antitumor humoral responses. After activation, B cells can function as effector cells via direct tumor-killing, antigen-presenting activity, and production of tumor-specific antibodies. At the other extreme, B cells can obtain inhibitory functions by relevant stimuli, converting to regulatory B cells, which serve as an immunosuppressive arm to tumor immunity. Here we summarize our current understanding of the bipolar properties of B cells within the tumor immune microenvironment and propose potential B cell-based immunotherapeutic strategies, which may help promote cancer immunotherapy.

Survival Risk Prediction of Esophageal Squamous Cell Carcinoma Based on BES-LSSVM

Esophageal squamous cell carcinoma (ESCC) is one of the highest incidence and mortality cancers in the world. An effective survival prediction model can improve the quality of patients’ survival. In this study, ten indicators related to the survival of patients with ESCC are founded using genetic algorithm feature selection. The prognostic index (PI) for ESCC is established using the binary logistic regression. PI is divided into four stages, and each stage can reasonably reflect the survival status of different patients. By plotting the ROC curve, the critical threshold of patients’ age could be found, and patients are divided into the high-age groups and the low-age groups. PI and ten survival-related indicators are used as independent variables, based on the bald eagle search (BES) and least-squares support vector machine (LSSVM), and a survival prediction model for patients with ESCC is established. The results show that five-year survival rates of patients are well predicted by the bald eagle search-least-squares support vector machine (BES-LSSVM). BES-LSSVM has higher prediction accuracy than the existing particle swarm optimization-least-squares support vector machine (PSO-LSSVM), grasshopper optimization algorithm-least-squares support vector machine (GOA-LSSVM), differential evolution-least-squares support vector machine (DE-LSSVM), sparrow search algorithm-least-squares support vector machine (SSA-LSSVM), bald eagle search-back propagation neural network (BES-BPNN), and bald eagle search-extreme learning machine (BES-ELM).

Emerging Role of Fascin-1 in the Pathogenesis, Diagnosis, and Treatment of the Gastrointestinal Cancers

Simple Summary

Gastrointestinal (GI) cancers, including esophageal, gastric, colorectal, liver, and pancreatic cancers, remain as one of the leading causes of death worldwide, with a large proportion accounting for fatalities related to metastatic disease. The active involvement of fascin-1 in forming membrane protrusions crucial for cellular movement has been identified as an important molecular mechanism behind the phenotypic switch from the localized to the metastatic tumor. Thus, fascin-1 expression status in the malignant tissue has been utilized as an important component in determining the patient’s clinicopathological outcomes. In this review, we provide an up-to-date literature review of the role of fascin-1 in the initiation and metastatic progression of GI tract cancers, its involvement in patients’ clinical outcomes, and its potential as a therapeutic target.

Abstract

Gastrointestinal (GI) cancers, including esophageal, gastric, colorectal, liver, and pancreatic cancers, remain as one of the leading causes of death worldwide, with a large proportion accounting for fatalities related to metastatic disease. Invasion of primary cancer occurs by the actin cytoskeleton remodeling, including the formation of the filopodia, stereocilia, and other finger-like membrane protrusions. The crucial step of actin remodeling in the malignant cells is mediated by the fascin protein family, with fascin-1 being the most active. Fascin-1 is an actin-binding protein that cross-links filamentous actin into tightly packed parallel bundles, giving rise to finger-like cell protrusions, thus equipping the cell with the machinery necessary for adhesion, motility, and invasion. Thus, fascin-1 has been noted to be a key component for determining patient diagnosis and treatment plan. Indeed, the overexpression of fascin-1 in GI tract cancers has been associated with a poor clinical prognosis and metastatic progression. Moreover, fascin-1 has received attention as a potential therapeutic target for metastatic GI tract cancers. In this review, we provide an up-to-date literature review of the role of fascin-1 in the initiation of GI tract cancers, metastatic progression, and patients’ clinical outcomes.

Anti-Cancer Auto-Antibodies: Roles, Applications and Open Issues

Auto-antibodies are classically associated with autoimmune diseases, where they are an integral part of diagnostic panels. However, recent evidence is accumulating on the presence of auto-antibodies against single or selected panels of auto-antigens in many types of cancer. Auto-antibodies might initially represent an epiphenomenon derived from the inflammatory environment induced by the tumor. However, their effect on tumor evolution can be crucial, as is discussed in this paper. It has been demonstrated that some of these auto-antibodies can be used for early detection and cancer staging, as well as for monitoring of cancer regression during treatment and follow up. Interestingly, certain auto-antibodies were found to promote cancer progression and metastasis, while others contribute to the body's defense against it. Moreover, auto-antibodies are of a polyclonal nature, which means that often several antibodies are involved in the response to a single tumor antigen. Dissection of these antibody specificities is now possible, allowing their identification at the genetic, structural, and epitope levels. In this review, we report the evidence available on the presence of auto-antibodies in the main cancer types and discuss some of the open issues that still need to be addressed by the research community.