IL-1α and colorectal cancer pathogenesis: Enthralling candidate for anti-cancer therapy

The construction of a prognostic model by apoptosis-related genes to predict survival, immune landscape, and medication in cholangiocarcinoma

BACKGROUND

Cholangiocarcinoma (CCA) is a highly aggressive and invasive malignant tumor of the bile duct, with a poor prognosis and a high mortality rate. Currently, there is a lack of effective targeted treatment methods and reliable biomarkers for prognosis.

METHODS

We downloaded RNA-seq and clinical data of CCA from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) databases as training and test sets. The apoptosis-related genes were obtained from the Molecular Signatures Database (MsigDB) database. We used univariate/multivariate Cox regression and Lasso regression analyses to construct a riskscore prognostic model. Based on the median riskscore, we clustered the patients into high-risk (HR) and low-risk (LR) groups. We carried out Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially expressed genes (DEGs) in HR and LR groups. The single sample gene set enrichment analysis (ssGSEA) was employed to analyze the immune infiltration of the HR and LR groups. The CellMiner database was utilized to predict drugs and perform molecular docking on drugs and target proteins.

RESULTS

We identified 8 genes with prognostic significance to construct a prognostic model. Results of GO and KEGG demonstrated that DEGs were mainly enriched in biological functions such as fatty acid metabolic processes and pathways such as the cAMP signaling pathway. Results of ssGSEA uncovered that immune cells such as DCs and Macrophages in the HR group, as well as immune functions such as Check-point and Parainflammation, were considerably higher than those in the LR group. Drug sensitivity prediction and results of molecular docking revealed that Rigosertib targeted the prognostic genes MAP3K1. HYPOTHEMYCIN and AMG900 effectively targeted JUN.

CONCLUSION

Our project suggested that the prognostic model with apoptotic features can effectively predict prognosis in CCA patients, proffering prognostic biomarkers and potential therapeutic targets for CCA patients.

Anti-angiogenesis in colorectal cancer therapy

The morbidity of colorectal cancer (CRC) has risen to third place among malignant tumors worldwide. In addition, CRC is a common cancer in China whose incidence increases annually. Angiogenesis plays an important role in the development of tumors because it can bring the nutrients that cancer cells need and take away metabolic waste. Various mechanisms are involved in the formation of neovascularization, and vascular endothelial growth factor is a key mediator. Meanwhile, angiogenesis inhibitors and drug resistance (DR) are challenges to consider when formulating treatment strategies for patients with different conditions. Thus, this review will discuss the molecules, signaling pathways, microenvironment, treatment, and DR of angiogenesis in CRC.

The multifaceted roles of COL4A4 in lung adenocarcinoma: An integrated bioinformatics and experimental study

BACKGROUND

Abnormal expression of collagen IV subunits has been reported in cancers, but the significance is not clear. No study has reported the significance of COL4A4 in lung adenocarcinoma (LUAD).

METHODS

COL4A4 expression data, single-cell sequencing data and clinical data were downloaded from public databases. A range of bioinformatics and experimental methods were adopted to analyze the association of COL4A4 expression with clinical parameters, tumor microenvironment (TME), drug resistance and immunotherapy response, and to investigate the roles and underlying mechanism of COL4A4 in LUAD.

RESULTS

COL4A4 is differentially expressed in most of cancers analyzed, being associated with prognosis, tumor stemness, immune checkpoint gene expression and TME parameters. In LUAD, COL4A4 expression is down-regulated and associated with various TME parameters, response to immunotherapy and drug resistance. LUAD patients with lower COL4A4 have worse prognosis. Knockdown of COL4A4 significantly inhibited the expression of cell-cycle associated genes, and the expression and activation of signaling pathways including JAK/STAT3, p38, and ERK pathways, and induced quiescence in LUAD cells. Besides, it significantly induced the expression of a range of bioactive molecule genes that have been shown to have critical roles in TME remodeling and immune regulation.

CONCLUSIONS

COL4A4 is implicated in the pathogenesis of cancers including LUAD. Its function may be multifaceted. It can modulate the activity of LUAD cells, TME remodeling and tumor stemness, thus affecting the pathological process of LUAD. COL4A4 may be a prognostic molecular marker and a potential therapeutic target.

Relevance of pyroptosis-associated genes in nasopharyngeal carcinoma diagnosis and subtype classification

BACKGROUND

Nasopharyngeal carcinoma (NPC) is a highly aggressive and metastatic malignancy originating in the nasopharyngeal tissue. Pyroptosis is a relatively newly discovered, regulated form of necrotic cell death induced by inflammatory caspases that is associated with a variety of diseases. However, the role and mechanism of pyroptosis in NPC are not fully understood.

METHODS

We analyzed the differential expression of pyroptosis-related genes (PRGs) between patients with and without NPC from the GSE53819 and GSE64634 datasets of the Gene Expression Omnibus (GEO) database. We mapped receptor operating characteristic profiles for these key PRGs to assess the accuracy of the genes for disease diagnosis and prediction of patient prognosis. In addition, we constructed a nomogram based on these key PRGs and carried out a decision curve analysis. The NPC patients were classified into different pyroptosis gene clusters by the consensus clustering method based on key PRGs, whereas the expression profiles of the key PRGs were analyzed by applying principal component analysis. We also analyzed the differences in key PRGs, immune cell infiltration and NPC-related genes between the clusters. Finally, we performed differential expression analysis for pyroptosis clusters and obtained differentially expressed genes (DEGs) and performed Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses.

RESULTS

We obtained 14 differentially expressed PRGs from GEO database. Based on these 14 differentially expressed PRGs, we applied least absolute shrinkage and selection operator analysis and the random forest algorithm to obtain four key PRGs (CHMP7, IL1A, TP63 and GSDMB). We completely distinguished the NPC patients into two pyroptosis gene clusters (pyroptosis clusters A and B) based on four key PRGs. Furthermore, we determined the immune cell abundance of each NPC sample, estimated the association between the four PRGs and immune cells, and determined the difference in immune cell infiltration between the two pyroptosis gene clusters. Finally, we obtained and functional enrichment analyses 259 DEGs by differential expression analysis for both pyroptosis clusters.

CONCLUSIONS

PRGs are critical in the development of NPC, and our research on the pyroptosis gene cluster may help direct future NPC therapeutic approaches.

Interleukin-1 receptor antagonist: An alternative therapy for cancer treatment

The interleukin-1 receptor antagonist (IL-1Ra) is an anti-inflammatory cytokine and a naturally occurring antagonist of the IL-1 receptor. It effectively counteracts the IL-1 signaling pathway mediated by IL-1α/β. Over the past few decades, accumulating evidence has suggested that IL-1 signaling plays an essential role in tumor formation, growth, and metastasis. Significantly, anakinra, the first United States Food and Drug Administration (FDA)-approved IL-1Ra drug, has demonstrated promising antitumor effects in animal studies. Numerous clinical trials have subsequently incorporated anakinra into their cancer treatment protocols. In this review, we comprehensively discuss the research progress on the role of IL-1 in tumors and summarize the significant contribution of IL-1Ra (anakinra) to tumor immunity. Additionally, we analyze the potential value of IL-1Ra as a biomarker from a clinical perspective. This review is aimed to highlight the important link between inflammation and cancer and provide potential drug targets for future cancer therapy.

Fusobacterium nucleatum infection activates the noncanonical inflammasome and exacerbates inflammatory response in DSS-induced colitis

Caspase activation results in pyroptosis, an inflammatory cell death that contributes to several inflammatory diseases by releasing inflammatory cytokines and cellular contents. Fusobacterium nucleatum is a periodontal pathogen frequently detected in human cancer and inflammatory bowel diseases. Studies have reported that F. nucleatum infection leads to NLRP3 activation and pyroptosis, but the precise activation process and disease association remain poorly understood. This study demonstrated that F. nucleatum infection exacerbates acute colitis in mice and activates pyroptosis through caspase-11-mediated gasdermin D cleavage in macrophages. Furthermore, F. nucleatum infection in colitis mice induces the enhancement of IL-1⍺ secretion from the colon, affecting weight loss and severe disease activities. Neutralization of IL-1⍺ protects F. nucleatum infected mice from severe colitis. Therefore, F. nucleatum infection facilitates inflammation in acute colitis with IL-1⍺ from colon tissue by activating noncanonical inflammasome through gasdermin D cleavage.

Interleukins (Cytokines) as Biomarkers in Colorectal Cancer: Progression, Detection, and Monitoring

Cancer is the primary cause of death in economically developed countries and the second leading cause in developing countries. Colorectal cancer (CRC) is the third most common cause of cancer-related deaths worldwide. Risk factors for CRC include obesity, a diet low in fruits and vegetables, physical inactivity, and smoking. CRC has a poor prognosis, and there is a critical need for new diagnostic and prognostic biomarkers to reduce related deaths. Recently, studies have focused more on molecular testing to guide targeted treatments for CRC patients. The most crucial feature of activated immune cells is the production and release of growth factors and cytokines that modulate the inflammatory conditions in tumor tissues. The cytokine network is valuable for the prognosis and pathogenesis of colorectal cancer as they can aid in the cost-effective and non-invasive detection of cancer. A large number of interleukins (IL) released by the immune system at various stages of CRC can act as "biomarkers". They play diverse functions in colorectal cancer, and include IL-4, IL-6, IL-8, IL-11, IL-17A, IL-22, IL-23, IL-33, TNF, TGF-β, and vascular endothelial growth factor (VEGF), which are pro-tumorigenic genes. However, there are an inadequate number of studies in this area considering its correlation with cytokine profiles that are clinically useful in diagnosing cancer. A better understanding of cytokine levels to establish diagnostic pathways entails an understanding of cytokine interactions and the regulation of their various biochemical signaling pathways in healthy individuals. This review provides a comprehensive summary of some interleukins as immunological biomarkers of CRC.

Interleukin-1 alpha and high mobility group box-1 secretion in polyinosinic:polycytidylic-induced colorectal cancer cells occur via RIPK1-dependent mechanism and participate in tumourigenesis

Pathogenic infections have significant roles in the pathogenesis of colorectal cancer (CRC). These infections induce the secretion of various damage-associated molecular patterns (DAMPs) including interleukin-1 alpha (IL-1α) and high mobility group box-1 (HMGB1). Despite their implication in CRC pathogenesis, the mechanism(s) that modulate the secretion of IL-1α and HMGB1, along with their roles in promoting CRC tumourigenesis remain poorly understood. To understand the secretory mechanism, HT-29 and SW480 cells were stimulated with infectious mimetics; polyinosinic:polycytidylic acid [Poly(I:C)], lipopolysaccharide (LPS) and pro-inflammatory stimuli; tumour necrosis factor-alpha (TNF-α). IL-1α and HMGB1 secretion levels upon stimulation were determined via ELISA. Mechanism(s) mediating IL-1α and HMGB1 secretion in CRC cells were characterized using pharmacological inhibitors and CRISPR-Cas9 gene editing targeting relevant pathways. Recombinant IL-1α and HMGB1 were utilized to determine their impact in modulating pro-tumourigenic properties of CRC cells. Pharmacological inhibition showed that Poly(I:C)-induced IL-1α secretion was mediated through endoplasmic reticulum (ER) stress and RIPK1 signalling pathway. The secretion of HMGB1 was RIPK1-dependent but independent of ER stress. RIPK1-targeted CRC cell pools exhibited decreased cell viability upon Poly(I:C) stimulation, suggesting a potential role of RIPK1 in CRC cells survival. IL-1α has both growth-promoting capabilities and stimulates the production of pro-metastatic mediators, while HMGB1 only exhibits the latter; with its redox status having influence. We demonstrated a potential role of RIPK1-dependent signalling pathway in mediating the secretion of IL-1α and HMGB1 in CRC cells, which in turn enhances CRC tumorigenesis. RIPK1, IL-1α and HMGB1 may serve as potential therapeutic targets to mitigate CRC progression.

Identifying and Validating Networks of Oncology Biomarkers Mined From the Scientific Literature

Biomarkers, as measurements of defined biological characteristics, can play a pivotal role in estimations of disease risk, early detection, differential diagnosis, assessment of disease progression and outcomes prediction. Studies of cancer biomarkers are published daily; some are well characterized, while others are of growing interest. Managing this flow of information is challenging for scientists and clinicians. We sought to develop a novel text-mining method employing biomarker co-occurrence processing applied to a deeply indexed full-text database to generate time-interval–delimited biomarker co-occurrence networks. Biomarkers across 6 cancer sites and a cancer-agnostic network were successfully characterized in terms of their emergence in the published literature and the context in which they are described. Our approach, which enables us to find publications based on biomarker relationships, identified biomarker relationships not known to existing interaction networks. This search method finds relevant literature that could be missed with keyword searches, even if full text is available. It enables users to extract relevant biological information and may provide new biological insights that could not be achieved by individual review of papers.