Identification of CXCL10 as a Prognostic Biomarker for Clear Cell Renal Cell Carcinoma

Immune analysis of urine and plasma samples from patients with clear cell renal cell carcinoma

Clear cell renal cell carcinoma (ccRCC) is the third most common type of urological malignancy worldwide, and it is associated with a silent progression and late manifestation. Patients with a metastatic form of ccRCC have a poor prognosis; however, when the disease is diagnosed early, it is largely curable. Currently, there are no biomarkers available in clinical practice for ccRCC. Thus, the aim of the present study was to measure 27 biologically relevant cytokines in preoperative and postoperative urine samples, and in preoperative plasma samples from 34 patients with ccRCC, and to evaluate their diagnostic significance. The concentrations of cytokines were assessed by multiplex immune assay. The results showed significantly higher levels of IL-1 receptor antagonist, IL-6, IL-15, chemokine (C-C motif) ligand (CCL)2, CCL3, CCL4, C-X-C motif ligand (CXCL)10, granulocyte-macrophage colony stimulating factor (GM-CSF) and platelet-derived growth factor-BB (PDGF-BB), and lower levels of granulocyte colony stimulating factor (G-CSF) in urine samples from patients prior to surgery compared with those in the controls. Notably, the urine levels of G-CSF, IL-5 and vascular endothelial growth factor differed following tumor removal compared with the preoperative urine levels. In addition, urinary G-CSF, GM-CSF, IL-6, CXCL10, CCL5 and PDGF-BB appeared to be potential markers of tumor grade. Plasma from patients with ccRCC contained significantly higher levels of IL-6 and lower levels of CCL2 than control plasma. In conclusion, the present findings indicated that urinary and circulating cytokines may represent a promising novel tool for the early diagnosis of ccRCC and/or prediction of tumor grade.

Predictive value of CXCL10 for the occurrence of immune-related adverse events in patient with renal cell carcinoma

Immune checkpoint inhibitors (ICIs) have recently improved the prognosis of various cancers. By contrast, some immune-related adverse events (irAEs) caused by ICIs are fatal and have become problematic. The pathogenesis of irAEs remains unknown and must be elucidated to establish biomarkers. This study investigated plasma cytokine, chemokine, and anti-CD74 autoantibody levels in patients with renal cell carcinoma (RCC) and analyzed their association with irAEs. In a discovery cohort of 13 patients, plasma levels of chemokine (C-X-C motif) ligand (CXCL) 1, IL-17A, IL-1β, IL-6, IL-8, CXCL10, MCP-1, and TNFα were measured at baseline and post-dose 1. Only CXCL10, at post-dose 1 but not at baseline, was significantly associated with grade 2 or higher irAEs (P = 0.0413). Plasma CXCL10 levels were then measured at baseline and post-dose 1 in an extended cohort of 43 patients with RCC who received ICI-based treatment. Higher plasma CXCL10 levels both at baseline and post-dose1 were significantly associated with the occurrence of grade 2 or higher irAEs (P = 0.0246 and 0.0137, respectively). Plasma CXCL13 levels, which we measured in a previous study, were significantly higher in patients with grade 2 or higher irAEs at baseline but not at post-dose 1 (P = 0.0037 and 0.052, respectively). No significant association between plasma anti-CD74 autoantibody level and both irAE pneumonitis and any grade 2 or higher irAE was observed. In conclusion, plasma CXCL10 is significantly associated with the occurrence of irAEs in patients with RCC treated with ICIs. CXCL10 is a potential predictive and on-treatment biomarker for irAEs.

A novel prognostic signature of chemokines for survival and immune infiltration in kidney renal clear cell carcinoma

Objective: Studies have revealed the alteration of chemokines in the tumour microenvironment in renal clear cell carcinoma (KIRC), which is closely related with immune infiltration and the prognosis of patients with KIRC. This research aims to comprehensively clarify the signature of chemokines in KIRC and the correlation between chemokines and immune infiltration in the TME of KIRC. Methods: The chemokine expression in KIRC were investigated by using multiple multiomics and bioinformatics tools. Hub-chemokines that were significantly related with the cancer stage and survival were identified. The role of hub-chemokines in the tumor microenvironment of KIRC was further assessed by using enrichment analysis, cancer-related pathway and immune infiltration analysis. Results: A total of 20 chemokines were significantly elevated in KIRC. Based on the correlation with KIRC stages and survival, 13 hub-chemokines were identified. Among the hub-chemokines, the high expression of CXCL2, CXCL5 and CXCL13 were related with worse survival of KIRC patients. The hub-chemokines were associated with the activation of multiple cancer-related signaling pathways. The functions of hub-chemokines were mainly enriched in chemokine-mediated signaling pathway, immunocytes chemotaxis and chemokine activity. CCL4, CCL5, CXCL9, CXCL10 and CXCL11 were related with various types immune infiltration such as CD8⁺T cell, neutrophil, B cell and dendritic cell. Using the hub-chemokine CXCL10, multiple immune checkpoints including LAG3, CTLA-4 and PD-1 were identified. Conclusion: Our research sheds light on the chemokines and their important role in promoting the tumor microenvironment of KIRC. The findings could provide more data about the prognosis prediction and treatment targets for KIRC.

Ionizing Radiation Selectively Increases CXC Ligand 10 Level via the DNA-Damage-Induced p38 MAPK-STAT1 Pathway in Murine J774A.1 Macrophages

Ionizing radiation (IR) is an important means of tumor treatment in addition to surgery and drugs. Attempts have been made to improve the efficiency of radiotherapy by identifying the various biological effects of IR on cells. Components of the tumor microenvironment, such as macrophages, fibroblasts, and vascular endothelial cells, influence cancer treatment outcomes through communication with tumor cells. In this study, we found that IR selectively increased the production of CXC motif chemokine ligand 10 (CXCL10), which is emerging as an important biomarker for determining the prognosis of anticancer treatments, without changing the levels of CXCL9 and CXCL11 in murine J774A.1 macrophages. Pretreatment with KU55933, an ataxia telangiectasia mutated (ATM) kinase inhibitor, significantly inhibited IR-induced CXCL10 production. In contrast, pretreatment with N-acetyl-cysteine or glutathione, a reactive oxygen species scavenger, did not inhibit IR-induced CXCL10 production. Further, we attempted to identify the intracellular molecular target associated with the IR-induced increase in CXCL10 secretion by J774A.1 macrophages. IR phosphorylated p38 mitogen-activated protein kinase (MAPK) and signal transducer and activator of transcription 1 (STAT1) in J774A.1 macrophages, and p38 MAPK and STAT1 were involved in CXCL10 via IR using pharmacological inhibitors (SB203580 and fludarabine, respectively) and the siRNA technique.

Prognostic and predictive biomarkers for immunotherapy in advanced renal cell carcinoma

The therapeutic algorithm of renal cell carcinoma has been revolutionized by the approval of immunotherapy agents by regulatory agencies. However, objective and durable responses are still not observed in a large number of patients, and prognostic and predictive biomarkers for immunotherapy response are urgently needed. Prognostic models used in clinical practice are based on clinical and laboratory factors (such as hypercalcaemia, neutrophil count or Karnofsky Performance Status), but, with progress in molecular biology and genome sequencing techniques, new renal cell carcinoma molecular features that might improve disease course and outcomes prediction have been highlighted. An implementation of current models is needed to improve the accuracy of prognosis in the immuno-oncology era. Moreover, several potential biomarkers are currently under evaluation, but effective markers to select patients who might benefit from immunotherapy and to guide therapeutic strategies are still far from validation.

Clear Cell Renal Cell Carcinoma: A Comprehensive in silico Study in Searching for Therapeutic Targets

INTRODUCTION

Clear cell renal cell carcinoma (ccRCC) is recognized as one of the leading causes of illness and death worldwide. Understanding the molecular mechanisms in ccRCC pathogenesis is crucial for discovering novel therapeutic targets and developing efficient drugs. With the application of a comprehensive in silico analysis of the ccRCC-related array sets, the main objective of this study was to discover the top molecules and pathways in the pathogenesis of this cancer.

METHODS

ccRCC microarray datasets were downloaded from the Gene Expression Omnibus database, and after quality checking, normalization, and analysis using the Limma algorithm, differentially expressed genes (DEGs) were identified, considering the adjusted p value <0.049. The intensity values of the identified DEGs were introduced to the Weighted Gene Co-Expression Network Analysis (WGCNA) algorithm to construct co-expression modules. Functional enrichment analyses were performed using the DEGs in the disease-correlated module, and hub genes were identified among the top genes in a protein-protein interaction network and the disease most correlated module. The expression analysis of hub genes was done by utilizing GEPIA, and the GSCA server was used to compare the expression patterns of hub genes in ccRCC and other cancers. DGIdb database was utilized to identify the hub gene-related drugs.

RESULTS

Three datasets, including GSE11151, GSE12606, and GSE36897, were retrieved, merged, normalized, and analyzed. Using WGCNA, the DEGs were clustered into eight different modules. Translocation of ZAP-70 to immunological synapse, endosomal/vacuolar pathway, cell surface interactions at the vascular wall, and immune-related pathways were the topmost enriched terms for the ccRCC-correlated DEGs. Twelve genes including PTPRC, ITGAM, TLR2, CD86, PLEK, TYROBP, ITGB2, RAC2, CSF1R, CCR5, CCL5, and LCP2 were introduced as hub genes. All the 12 hub genes were upregulated in ccRCC samples and showed a positive correlation with the infiltration of different immune cells. According to the DGIdb database, 127 drugs, including tyrosine kinase inhibitors, glucocorticoids, and chemotaxis targeting molecules, were identified to interact with the hub genes.

CONCLUSION

By utilizing an integrative bioinformatics approach, this experiment shed light on the underlying pathways in the pathogenesis of ccRCC and introduced several potential therapeutic targets for repurposing or developing novel drugs for an efficient treatment of this cancer. Our next step would be to assess the gene expression profiles of the identified hubs in different cell populations in the tumor microenvironment.

Oncogenic roles of LINC01234 in various forms of human cancer

Abnormal expression of long non-coding RNAs (lncRNAs) plays an essential role in various malignant neoplasia. As a newly identified lncRNA, LINC01234 is abnormally expressed in several types of cancers and promotes the development of cancers. Accumulating evidence indicates that overexpression of LINC01234 is associated with poor clinical outcomes. Moreover, LINC01234 modulates many cellular events as a putative proto-oncogene, including proliferation, migration, invasion, apoptosis, cell cycle progression, and EMT. In terms of molecular mechanism, LINC01234 regulates gene expression by acting as ceRNA, participating in signaling pathways, interacting with proteins and other molecules, and encoding polypeptide. It reveals that LINC01234 may serve as a potential biomarker for cancer diagnosis, treatment, and prognosis. This review summarizes the expression pattern, biological function, and molecular mechanism of LINC01234 in human cancer and discusses its potential clinical utility.