Characterization of lectins and their specificity in carcinomas—An appraisal

Abstract

Lectins, a group of specific glycoproteins present in animal as well as plant cells, are used as differentiating markers to study cancers and metastatic cell lines. This property of lectins depends on the process of cellular glycosylation. Glycosylation of some of the extracellular membrane proteins and lipids maintains the cell/cell and cell/matrix interactions. Chemical alterations in glycosylation play an important role in the metastatic behavior of tumor cells. Carbohydrate residues of the membrane glycoproteins can be detected using lectins due to their binding specificity to carbohydrates. Lectins, therefore have gained an importance in the field of cancer research. Galectins, a specialized group of lectin like proteins that are Ca+ independent and galactoside binding, are also considered as differentiation markers in some specific cancers like the carcinomas of thyroid.Thus the use of lectins and galectins to identify specific carbohydrates present on cell surface help in invasion and metastasis processes.

Lectin Isolated from Japanese Red Sword Beans (Canavalia gladiata) as a Potential Cancer Chemopreventive Agent

“…NK cells are effector lymphocytes of the innate immune system that control several types of tumors and microbial infections by limiting their spread and preventing subsequent tissue damage (Vivier, Tomasello, Baratin, Walzer, & Ugolini, ). Notably, a nontoxic concentration of Con A was shown to inhibit the hepatic metastasis of Colon‐26 colon cancer cells through an NK‐mediated mechanism (Sherwani, Mohmood, Khan, Khan, & Azfer, ). Similarly, Yoon et al.…”

Unveiling the Role of Concanavalin A in a Rodent Model of Chemical-Induced Hepatocellular Carcinoma: A Promising Guide in Understanding Liver Cancer Development

“…Hepatic carcinoma cells often exhibit changes in glycosylation patterns on the cell surface. Con-A can be used to detect and characterize these alterations [22,23]. In this study, we assessed the hepatic alteration of the Con-A expression (intensity and spatial location) in a murine model of hepatocellular carcinoma induced by DEN using lectin histochemistry.…”

Identification of cancerlectin proteins using hyperparameter optimization in deep learning and DDE profiles

“…We have been motivated to integrate various classifiers and extractors for improving prediction accuracy by sophisticated applications of machine learning that demonstrate excellent results for cancer identification [11,12]. After contrasting their effectiveness and acceptance, classification algorithms are chosen to show how machine learning affects cancer detection [13].…”