Lambda-Carrageenan Enhances the Effects of Radiation Therapy in Cancer Treatment by Suppressing Cancer Cell Invasion and Metastasis through Racgap1 Inhibition

A Screening Approach to Assess the Impact of Various Commercial Sources of Crude Marine λ-Carrageenan on the Production of Oligosaccharides with Anti-heparanase and Anti-migratory Activities

Oligosaccharides derived from λ-carrageenan (λ-COs) are gaining interest in the cancer field. They have been recently reported to regulate heparanase (HPSE) activity, a protumor enzyme involved in cancer cell migration and invasion, making them very promising molecules for new therapeutic applications. However, one of the specific features of commercial λ-carrageenan (λ-CAR) is that they are heterogeneous mixtures of different CAR families, and are named according to the thickening-purpose final-product viscosity which does not reflect the real composition. Consequently, this can limit their use in a clinical applications. To address this issue, six commercial λ-CARs were compared and differences in their physiochemical properties were analyzed and shown. Then, a H₂O₂-assisted depolymerization was applied to each commercial source, and number- and weight-averaged molar masses (M_n and M_w) and sulfation degree (DS) of the λ-COs produced over time were determined. By adjusting the depolymerization time for each product, almost comparable λ-CO formulations could be obtained in terms of molar masses and DS, which ranged within previously reported values suitable for antitumor properties. However, when the anti-HPSE activity of these new λ-COs was screened, small changes that could not be attributed only to their small length or DS changes between them were found, suggesting a role of other features, such as differences in the initial mixture composition. Further structural MS and NMR analysis revealed qualitative and semi-quantitative differences between the molecular species, especially in the proportion of the anti-HPSE λ-type, other CARs types and adjuvants, and it also showed that H₂O₂-based hydrolysis induced sugar degradation. Finally, when the effects of λ-COs were assessed in an in vitro migration cell-based model, they seemed more related to the proportion of other CAR types in the formulation than to their λ-type-dependent anti-HPSE activity.

Recent advances in exploiting carrageenans as a versatile functional material for promising biomedical applications

Carrageenans are a group of biopolymers widely found in red seaweeds. Commercial carrageenans have been traditionally used as emulsifiers, stabilizers, and thickening and gelling agents in food products. Carrageenans are regarded as bioactive polysaccharides with disease-modifying and microbiota-modulating activities. Novel biomedical applications of carrageenans as biocompatible functional materials for fabricating hydrogels and nanostructures, including carbon dots, nanoparticles, and nanofibers, have been increasingly exploited. In this review, we describe the unique structural characteristics of carrageenans and their functional relevance. We summarize salient physicochemical features, including thixotropic and shear-thinning properties, of carrageenans. Recent results from clinical trials in which carrageenans were applied as both antiviral and antitumor agents and functional materials are discussed. We also highlight the most recent advances in the development of carrageenan-based targeted drug delivery systems with various pharmaceutical formulations. Promising applications of carrageenans as a bioink material for 3D printing in tissue engineering and regenerative medicine are systematically evaluated. We envisage some key hurdles and challenges in the commercialization of carrageenans as a versatile material for clinical practice. This comprehensive review of the intimate relationships among the structural features, unique rheological properties, and biofunctionality of carrageenans will provide novel insights into their biomedicine application potential.

ELIMINATOR: essentiality analysis using multisystem networks and integer programming

A gene is considered as essential when it is indispensable for cells to grow and replicate in a certain environment. However, gene essentiality is not a structural property but rather a contextual one, which depends on the specific biological conditions affecting the cell. This circumstantial essentiality of genes is what brings the attention of scientist since we can identify genes essential for cancer cells but not essential for healthy cells. This same contextuality makes their identification extremely challenging. Huge experimental efforts such as Project Achilles where the essentiality of thousands of genes is measured together with a plethora of molecular data (transcriptomics, copy number, mutations, etc.) in over one thousand cell lines can shed light on the causality behind the essentiality of a gene in a given environment. Here, we present an in-silico method for the identification of patient-specific essential genes using constraint-based modelling (CBM). Our method expands the ideas behind traditional CBM to accommodate multisystem networks. In essence, it first calculates the minimum number of lowly expressed genes required to be activated by the cell to sustain life as defined by a set of requirements; and second, it performs an exhaustive in-silico gene knockout to find those that lead to the need of activating additional lowly expressed genes. We validated the proposed methodology using a set of 452 cancer cell lines derived from the Cancer Cell Line Encyclopedia where an exhaustive experimental large-scale gene knockout study using CRISPR (Achilles Project) evaluates the impact of each removal. We also show that the integration of different essentiality predictions per gene, what we called Essentiality Congruity Score, reduces the number of false positives. Finally, we explored our method in a breast cancer patient dataset, and our results showed high concordance with previous publications. These findings suggest that identifying genes whose activity is fundamental to sustain cellular life in a patient-specific manner is feasible using in-silico methods. The patient-level gene essentiality predictions can pave the way for precision medicine by identifying potential drug targets whose deletion can induce death in tumour cells.

Up-Regulation of RACGAP1 Promotes Progressions of Hepatocellular Carcinoma Regulated by GABPA via PI3K/AKT Pathway

Hepatocellular carcinoma (HCC) is one of the dominating tumors causing death due to lack of timely discovery and valid treatment. Abnormal increase of Rac GTPase activating protein 1 (RACGAP1) has been verified to be an oncogene in plenty tumors. The profound mechanism of RACGAP1 was rarely reported in HCC. In this study, we explored the function and mechanism of RACGAP1 in HCC through multiple analysis and experiments. RACGAP1 expression was up-regulated in HCC samples and the high expression of RACGAP1 was an independent prognostic risk factor for HCC patients. Meanwhile, RACGAP1 promoted developments of HCC both in vitro and in vivo. We verified that RACGAP1 promoted proliferation of HCC via PI3K/AKT/CDK2 and PI3K/AKT/GSK3β/Cyclin D1 signaling pathway. RACGAP1 accelerated the invasion and metastasis of HCC via phosphorylation of GSK3β and nuclear translocation of β-catenin. Furthermore, by luciferase reporter assay and Chromatin immunoprecipitation (ChIP) assay, we confirmed Recombinant GA Binding Protein Transcription Factor Alpha (GABPA) regulated the transcription of RACGAP1. All these findings revealed that RACGAP1 promotes the progression of HCC through a novel mechanism, which might be a new therapeutic target for HCC patients.

Comprehensive analysis of transcriptome data stemness indices identifies key genes for controlling cancer stem cell characteristics in gastric cancer

BACKGROUND

Cancer stem cells (CSCs) are the tumor cell of origin with self-renewing ability and multi-differentiation potency. CSCs can play vital roles in gastric cancer (GC) metastasis and relapse. However, the genes that regulate the stemness maintenance of CSCs in GC patients remain largely unknown. In the present study, we sought to determine the key genes associated with stemness in GC patients.

METHODS

mRNA expression-based stemness index (mRNA SI) was analyzed with regard to the differential expression levels between normal and GC tissues, as well as clinical features and survival outcomes. Weighted gene co-expression network analysis (WGCNA) was performed to identify modules of interest and key genes. The differences in mRNA expression of key genes between normal and GC tissues were calculated by "ggpubr" package in R. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) analysis were carried out to annotate the function of key genes. Protein-protein interaction (PPI) and gene co-expression analyses were conducted using STRING and "corrplot" package in R, respectively.

RESULTS

mRNA SI score was markedly increased in GC tumor compared to normal tissues. High mRNA SI score was remarkably associated with more advanced tumor stage and higher pathologic grade, but longer survival times. Based on the results of WGCNA, 19 key genes (i.e., BUB1, BUB1B, KIF14, NCAPH, RACGAP1, KIF15, CENPF, TPX2, RAD54L, KIF18B, TTX, KIF4A, SGO2, PLK4, ARHGAP11A, XRCC2, C1orf112, NCAPG, ORC6) were identified. GO and KEGG functional analyses revealed that these 19 key genes were mainly related to cell proliferation. From PPI and gene co-expression analyses, these 19 key genes were discovered to be intensively associated with each other at both protein and transcription levels.

CONCLUSIONS

our study identified 19 key genes that play vital roles in the stemness maintenance of CSCs in GC patients. Targeting these key genes may help to control CSC characteristics in GC.

Role of Natural Bioactive Compounds in the Rise and Fall of Cancers

Recent years have seen the idea of a close association between nutrition and the modulation of cancer development/progression reinforced [...].