GBP2 promotes clear cell renal cell carcinoma progression through immune infiltration and regulation of PD‑L1 expression via STAT1 signaling

Crosstalk between GBP2 and M2 macrophage promotes the ccRCC progression

Clear cell renal cell carcinoma (ccRCC) represents a highly heterogeneous kidney malignancy associated with the poorest prognosis. The metastatic potential of advanced ccRCC tumors is notably high, posing significant clinical challenges. There is an urgent imperative to develop novel therapeutic approaches to address ccRCC metastasis. Recent investigations indicated a potential association between GBP2 and tumor immunity. However, the precise functional role of GBP2 in the progression of ccRCC remains poorly understood. The present study revealed a strong correlation between GBP2 and M2 macrophages. Specifically, our findings demonstrated that the inhibition of GBP2 significantly impedes the migratory and invasive capabilities of ccRCC cells. We observed that the presence of M2 macrophages can reverse the effects of GBP2 knockdown on tumor cell migration and invasion. Mechanistically, we demonstrated that M2 macrophages promote the expression of the GBP2/p-STAT3 and p-ERK axis in tumor cells through the secretion of interleukin-10 (IL-10) and transforming growth factor-β (TGF-β), thereby substantially enhancing the migratory and invasive capacities of the tumor cells. Simultaneously, we have identified that GBP2 promotes the polarization of macrophages to the M2 phenotype by stimulating the secretion of interleukin-18 (IL-18). In summary, our investigation anticipates that the GBP2/IL-18/M2 macrophages/IL-10 and the TGF-β/GBP2, p-STAT3, p-ERK loop plays a crucial role in ccRCC metastasis. The collective findings from our research underscore the significant role of GBP2 in tumor immunity and emphasize the potential for modulating GBP2 as a promising therapeutic strategy for targeting ccRCC metastasis.

Explore Key Genes and Mechanisms Involved in Colon Cancer Progression Based on Bioinformatics Analysis

To explore underlying mechanisms related to the progression of colon cancer and identify hub genes associated with the prognosis of patients with colon cancer. GSE10950 and GSE62932 were downloaded from the Gene Expression Omnibus (GEO) database. GEO2R was utilized to screen out the differentially expressed genes (DEGs). Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis were conducted on DEGs. Moreover, STRING and Cytoscape software were utilized for establishing the network of protein-protein interaction (PPI) and identifying hub genes. Afterward, data from The Cancer Genome Atlas (TCGA) was utilized for identifying prognosis-related hub genes by Kaplan-Meier survival analysis. Colon cancer cell line LOVO and human normal intestinal epithelial cell line NCM-460 were exploited to demonstrate the differential expression of selected hub genes through RT-qPCR and western blot. The LOVO cells were transfected to regulate expressions of prognosis-associated genes, followed by exploring the effects of those genes on prognosis by Cell Counting Kit-8 assay and colony-forming assay for cancer cell proliferation, cell scratch test and transwell migration assay for cancer cell migration and Annexin V-PE/7-AAD double staining as well as flow cytometry for cancer cell apoptosis. In this study, 266 common DEGs were obtained from the intersection of two datasets. The GO analysis suggested the common DEGs mainly participated in the one-carbon metabolic process, cell cycle G2/M phase transition, organelle fission, cell cycle phase transition regulation, and regulation of mitotic cell cycle phase transition. The KEGG analysis demonstrated the common DEGs were related to the p53 signaling pathway, nitrogen metabolism, mineral absorption, and cell cycle. 10 hub genes including CCNB1, KIF4A, TPX2, MT1F, PRC1, PLK4, CALD1, MMP9, CLCA1, and MMP1 were identified and CCNB1, CLCA1, and PLK4 were prognosis-related. Increased expression of CCNB1, CLCA1, and PLK4 restrained proliferation as well as migration of cancer cells and induced apoptosis of cancer cells. CCNB1, KIF4A, TPX2, MT1F, PRC1, PLK4, CALD1, MMP9, CLCA1, and MMP1 were identified as hub genes and CCNB1, CLCA1, and PLK4 could inhibit the progression of colon cancer through inhibiting proliferation as well as migration of the cancer cell and promoting apoptosis of cancer cell.

DNA hypo-methylation and expression of GBP4 induces T cell exhaustion in pancreatic cancer

Immunotherapy for pancreatic ductal carcinoma (PDAC) remains disappointing due to the repressive tumor microenvironment and T cell exhaustion, in which the roles of interferon-stimulated genes were largely unknown. Here, we focused on a typical interferon-stimulated gene, GBP4, and investigated its potential diagnostic and therapeutic value in pancreatic cancer. Expression analysis on both local samples and public databases indicated that GBP4 was one of the most dominant GBP family members present in the PDAC microenvironment, and the expression level of GBP4 was negatively associated with patient survival. We then identified DNA hypo-methylation in regulatory regions of GBP4 in PDAC, and validated its regulatory role on GBP4 expression via performing targeted methylation using dCas9-SunTag-DNMAT3A-sgRNA-targeted methylation system on selected DNA locus. After that, we investigated the downstream functions of GBP4, and chemotaxis assays indicated that GBP4 overexpression significantly improved the infiltration of CD8+T cells, but also induced upregulation of immune checkpoint genes and T cell exhaustion. Lastly, in vitro T cell killing assays using primary organoids suggested that the PDAC samples with high level of GBP4 expression displayed significantly higher sensitivity to anti-PD-1 treatment. Taken together, our studies revealed the expression patterns and epigenetic regulatory mechanisms of GBP4 in pancreatic cancer and clarified the effects of GBP4 on T cell exhaustion and antitumor immunology.

Interaction between microglial cells and CD1C+ B dendritic cells leads to CD8+ T cells depletion during the early stages of renal clear cell carcinoma

Renal clear cell carcinoma (RCC) is a type of malignant tumor, which, in addition to surgical resection, radiotherapy, and chemotherapy, has been widely treated through immunotherapy recently. However, the influence of the tumor microenvironment and the infiltrating immune cells within it on immunotherapy remains unclear. It is imperative to study the interactions between various immune cells of RCC. The scRNA-seq dataset from GEO's database was used to analyze the immune cells present in tumor tissue and peripheral blood samples. Through quality control, clustering, and identification, the types and proportions of infiltrating immune cells were determined. The cellular differences were determined, and gene expression levels of the differentially present cells were investigated. A protein-protein interaction network analysis was performed using string. KEGG and GO analyses were performed to investigate abnormal activities. The microglia marker CD68 and CD1C+ B dendritic cells marker CD11C were detected using multiplex immunofluorescence staining. Many depleted CD8+ T cells (exhausted CD8+ T cells) appeared in tumor tissues as well as microglia. CD1C+ B dendritic cells did not infiltrate tumor tissues. HSPA1A was correlated with DNAJB1 in microglia. Compared with Paracancer tissues, microglia increased while CD1C+ B dendritic cells decreased in pathological stages I and I-II in cancerous tissues. An altered tumor microenvironment caused by increases in microglia in RCC in the early stage resulted in an inability of CD1C+ B dendritic cells to infiltrate, resulting in CD8+ T cells being unable to receive the antigens presented by them, and in turn being depleted in large quantities.

PD1/PD-L1 blockade in clear cell renal cell carcinoma: mechanistic insights, clinical efficacy, and future perspectives

The advent of PD1/PD-L1 inhibitors has significantly transformed the therapeutic landscape for clear cell renal cell carcinoma (ccRCC). This review provides an in-depth analysis of the biological functions and regulatory mechanisms of PD1 and PD-L1 in ccRCC, emphasizing their role in tumor immune evasion. We comprehensively evaluate the clinical efficacy and safety profiles of PD1/PD-L1 inhibitors, such as Nivolumab and Pembrolizumab, through a critical examination of recent clinical trial data. Furthermore, we discuss the challenges posed by resistance mechanisms to these therapies and potential strategies to overcome them. We also explores the synergistic potential of combination therapies, integrating PD1/PD-L1 inhibitors with other immunotherapies, targeted therapies, and conventional modalities such as chemotherapy and radiotherapy. In addition, we examine emerging predictive biomarkers for response to PD1/PD-L1 blockade and biomarkers indicative of resistance, providing a foundation for personalized therapeutic approaches. Finally, we outline future research directions, highlighting the need for novel therapeutic strategies, deeper mechanistic insights, and the development of individualized treatment regimens. Our work summarizes the latest knowledge and progress in this field, aiming to provide a valuable reference for improving clinical efficacy and guiding future research on the application of PD1/PD-L1 inhibitors in ccRCC.

GBP2 inhibits pathological angiogenesis in the retina via the AKT/mTOR/VEGFA axis

Pathological retinal angiogenesis is not only the hallmark of retinopathies, but also a major cause of blindness. Guanylate binding protein 2 (GBP2) has been reported to be associated with retinal diseases such as diabetic retinopathy and hypoxic retinopathy. However, GBP2-mediated pathological retinal angiogenesis remains largely unknown. The present study aimed to investigate the role of GBP2 in pathological retinal angiogenesis and its underlying molecular mechanism. In this study, we established oxygen-induced retinopathy (OIR) mice model for in vivo study and hypoxia-induced angiogenesis in ARPE-19 cells for in vitro study. We demonstrated that GBP2 expression was markedly downregulated in the retina of mice with OIR and ARPE-19 cells treated with hypoxia, which was associated with pathological retinal angiogenesis. The regulatory mechanism of GBP2 in ARPE-19 cells was studied by GBP2 silencing and overexpression. The regulatory mechanism of GBP2 in the retina was investigated by overexpressing GBP2 in the retina of OIR mice. Mechanistically, GBP2 downregulated the expression and secretion of vascular endothelial growth factor (VEGFA) in ARPE-19 cells and retina of OIR mice. Interestingly, overexpression of GBP2 significantly inhibited neovascularization in OIR mice, conditioned medium of GBP2 overexpressing ARPE-19 cells inhibited angiogenesis in human umbilical vein endothelial cells (HUVECs). Furthermore, we confirmed that GBP2 downregulated VEGFA expression and angiogenesis by inhibiting the AKT/mTOR signaling pathway. Taken together, we concluded that GBP2 inhibited pathological retinal angiogenesis via the AKT/mTOR/VEGFA axis, thereby suggesting that GBP2 may be a therapeutic target for pathological retinal angiogenesis.

GBP2 enhances paclitaxel sensitivity in triple‑negative breast cancer by promoting autophagy in combination with ATG2 and inhibiting the PI3K/AKT/mTOR pathway

Chemoresistance is a major challenge in treating triple‑negative breast cancer (TNBC); chemotherapy remains the primary approach. The present study aimed to elucidate the role of guanylate‑binding protein 2 (GBP2) in activating autophagy in TNBC and its impact on the sensitivity of TNBC cells to paclitaxel (PTX). Transfection with lentivirus was performed to establish TNBC cell lines with stable, high GBP2 expression. The mRNA and protein levels of GBP2 expression were evaluated utilizing reverse transcription‑quantitative PCR and western blotting, respectively. Autophagy in TNBC cells was evaluated using immunoblotting, transmission electron microscopy and fluorescence microscopy. The PI3K/AKT/mTOR pathway proteins and their phosphorylation were detected by immunoblotting, and fluorescence co‑localization analysis was performed to evaluate the association between GBP2 and autophagy‑related protein 2 (ATG2). BALB/c NUDE mice were subcutaneously injected with GBP2 wild‑type/overexpressing MDA‑MB‑231 cells. Low GBP2 expression was detected in TNBC, which was associated with a poor prognosis. Overexpression of GBP2 suppressed cell growth, and especially enhanced autophagy in TNBC. Forced expression of GBP2 significantly increased the PTX sensitivity of TNBC cells, and the addition of autophagy inhibitors reversed this effect. GBP2 serves as a prognostic marker and exerts a notable inhibitory impact on TNBC. It functions as a critical regulator of activated autophagy by co‑acting with ATG2 and inhibiting the PI3K/AKT/mTOR pathway, which contributes to increasing sensitivity of TNBC cells to PTX. Therefore, GBP2 is a promising therapeutic target for enhancing TNBC treatment.

Inflammation and Immunity Gene Expression Patterns and Machine Learning Approaches in Association with Response to Immune-Checkpoint Inhibitors-Based Treatments in Clear-Cell Renal Carcinoma

Clear cell renal cell carcinoma (ccRCC) is the most common renal cancer. Despite the rapid evolution of targeted therapies, immunotherapy with checkpoint inhibition (ICI) as well as combination therapies, the cure of metastatic ccRCC (mccRCC) is infrequent, while the optimal use of the various novel agents has not been fully clarified. With the different treatment options, there is an essential need to identify biomarkers to predict therapeutic efficacy and thus optimize therapeutic approaches. This study seeks to explore the diversity in mRNA expression profiles of inflammation and immunity-related circulating genes for the development of biomarkers that could predict the effectiveness of immunotherapy-based treatments using ICIs for individuals with mccRCC. Gene mRNA expression was tested by the RT2 profiler PCR Array on a human cancer inflammation and immunity crosstalk kit and analyzed for differential gene expression along with a machine learning approach for sample classification. A number of mRNAs were found to be differentially expressed in mccRCC with a clinical benefit from treatment compared to those who progressed. Our results indicate that gene expression can classify these samples with high accuracy and specificity.

TTC13 expression and STAT3 activation may form a positive feedback loop to promote ccRCC progression

Background

Renal cell carcinoma (RCC) originates from renal tubular epithelial cells and is mainly classified into three histological types, including clear cell renal cell carcinoma (ccRCC) which accounts for about 75% of all kidney cancers and is characterized by its strong invasiveness and poor prognosis. Hence, it is imperative to understand the mechanisms underlying the occurrence and progression of ccRCC to identify effective biomarkers for the early diagnosis and the prognosis prediction.

Methods

The mRNA level of TTC13 was quantified by RT-PCR, while the protein level was determined by western blot and immunohistochemistry (IHC) staining. Cell proliferation was measured by cck-8, and cell apoptosis was detected by flow cytometry. The binding of STAT3 to the promoter region of TTC13 was determined by the luciferase reporter assay and chip experiments. STAT3 nuclear translocation was assessed by immunofluorescence staining.

Results

We found that TTC13 was up-regulated in ccRCC, and TTC13 promoted cell proliferation as well as inhibited cell apoptosis and autophagy of ccRCC through wnt/β-catenin and IL6-JAK-STAT3 signaling pathways. Furthermore, TTC13 might play a role in the immune infiltration and immunotherapy of ccRCC. Mechanistically, STAT3 activated the transcription of TTC13 gene.

Conclusions

STAT3 directly regulated TTC13 expression through a positive feedback loop mechanism to promote ccRCC cell proliferation as well as reduce cell apoptosis and autophagy. These findings suggested new and effective therapeutic targets for more accurate and personalized treatment strategies.

GBP2 is a prognostic biomarker and associated with immunotherapeutic responses in gastric cancer

BACKGROUND

The interferon-induced protein known as guanylate-binding protein 2 (GBP2) has been linked to multiple different cancer types as an oncogenic gene. Although the role of GBP2 in cancer has been preliminarily explored, it is unclear how this protein interacts with tumor immunity in gastric cancer.

METHODS

The expression, prognostic value, immune-correlations of GBP2 in gastric cancer was explored in multiple public and in-house cohorts. In addition, the pan-cancer analysis was performed to investigate the immunological role of GBP2 based on The Cancer Genome Atlas (TCGA) dataset, and the predictive value of GBP2 for immunotherapy was also examined in multiple public cohorts.

RESULTS

GBP2 was highly expressed in tumor tissues and associated with poor prognosis in gastric cancer. In addition, GBP2 was associated with the immune-hot phenotype. To be more specific, GBP2 was positively related to immuno-modulators, tumor-infiltrating immune cells (TIICs), immunotherapy biomarkers, and even well immunotherapeutic response. In addition to gastric cancer, GBP2 was expected to be an indicator of high immunogenicity in most cancer types. Importantly, GBP2 could predict the immunotherapeutic responses in at least four different cancer types, including melanoma, urothelial carcinoma, non-small cell lung cancer, and breast cancer.

CONCLUSIONS

To sum up, GBP2 expression is a promising pan-cancer biomarker for estimating the immunological characteristics of tumors and may be utilized to detect immuno-hot tumors in gastric cancer.

Multi-Organ Nutrigenomic Effects of Dietary Grapes in a Mouse Model

As a whole food, the potential health benefits of table grapes have been widely studied. Some individual constituents have garnered great attention, particularly resveratrol, but normal quantities in the diet are meniscal. On the other hand, the grape contains hundreds of compounds, many of which have antioxidant potential. Nonetheless, the achievement of serum or tissue concentrations of grape antioxidants sufficient to mediate a direct quenching effect is not likely, which supports the idea of biological responses being mediated by an indirect catalytic-type response. We demonstrate herein with Hsd:ICR (CD-1® Outbred, 18-24 g, 3-4 weeks old, female) mice that supplementation of a semi-synthetic diet with a grape surrogate, equivalent to the human consumption of 2.5 servings per day for 12 months, modulates gene expression in the liver, kidney, colon, and ovary. As might be expected when sampling changes in a pool of over 35,000 genes, there are numerous functional implications. Analysis of some specific differentially expressed genes suggests the potential of grape consumption to bolster metabolic detoxification and regulation of reactive oxygen species in the liver, cellular metabolism, and anti-inflammatory activity in the ovary and kidney. In the colon, the data suggest anti-inflammatory activity, suppression of mitochondrial dysfunction, and maintaining homeostasis. Pathway analysis reveals a combination of up- and down-regulation in the target tissues, primarily up-regulated in the kidney and down-regulated in the ovary. More broadly, based on these data, it seems logical to conclude that grape consumption leads to modulation of gene expression throughout the body, the consequence of which may help to explain the broad array of activities demonstrated in diverse tissues such as the brain, heart, eye, bladder, and colon. In addition, this work further supports the profound impact of nutrigenomics on mammalian phenotypic expression.

Recent Advances in the Management of Clear Cell Renal Cell Carcinoma: Novel Biomarkers and Targeted Therapies

Renal cell carcinoma (RCC) belongs to a heterogenous cancer group arising from renal tubular epithelial cells. Among RCC subtypes, clear cell renal cell carcinoma (ccRCC) is the most common variant, characterized by high aggressiveness, invasiveness and metastatic potential, features that lead to poor prognosis and high mortality rate. In addition, diagnosis of kidney cancer is incidental in the majority of cases, and this results in a late diagnosis, when the stage of the disease is advanced and the tumor has already metastasized. Furthermore, ccRCC treatment is complicated by its strong resistance to chemo- and radiotherapy. Therefore, there is active ongoing research focused on identifying novel biomarkers which could be useful for assessing a better prognosis, as well as new molecules which could be used for targeted therapy. In this light, several novel targeted therapies have been shown to be effective in prolonging the overall survival of ccRCC patients. Thus, the aim of this review is to analyze the actual state-of-the-art on ccRCC diagnosis, prognosis and therapeutic options, while also reporting the recent advances in novel biomarker discoveries, which could be exploited for a better prognosis or for targeted therapy.

Establishment of a new prognostic risk model of MAPK pathway-related molecules in kidney renal clear cell carcinoma based on genomes and transcriptomes analysis

PURPOSE

The mitogen-activated protein kinase (MAPK) signaling pathway is often studied in oncology as the most easily mentioned signaling pathway. This study aims to establish a new prognostic risk model of MAPK pathway related molecules in kidney renal clear cell carcinoma (KIRC) based on genome and transcriptome analysis.

METHODS

In our study, RNA-seq data were acquired from the KIRC dataset of The Cancer Genome Atlas (TCGA) database. MAPK signaling pathway-related genes were obtained from the gene enrichment analysis (GSEA) database. We used "glmnet" and the "survival" extension package for LASSO (Least absolute shrinkage and selection operator) regression curve analysis and constructed a prognosis-related risk model. The survival curve and the COX regression analysis were used the "survival" expansion packages. The ROC curve was plotted using the "survival ROC" extension package. We then used the "rms" expansion package to construct a nomogram plot. We performed a pan-cancer analysis of CNV (copy number variation), SNV (single nucleotide variant), drug sensitivity, immune infiltration, and overall survival (OS) of 14 MAPK signaling pathway-related genes using several analysis websites, such as GEPIA website and TIMER database. Besides, the immunohistochemistry and pathway enrichment analysis used The Human Protein Atlas (THPA) database and the GSEA method. Finally, the mRNA expression of risk model genes in clinical renal cancer tissues versus adjacent normal tissues was further verified by real-time quantitative reverse transcription (qRT-PCR).

RESULTS

We performed Lasso regression analysis using 14 genes and created a new KIRC prognosis-related risk model. High-risk scores suggested that KIRC patients with lower-risk scores had a significantly worse prognosis. Based on the multivariate Cox analysis, we found that the risk score of this model could serve as an independent risk factor for KIRC patients. In addition, we used the THPA database to verify the differential expression of proteins between normal kidney tissues and KIRC tumor tissues. Finally, the results of qRT-PCR experiments suggested large differences in the mRNA expression of risk model genes.

CONCLUSIONS

This study constructs a KIRC prognosis prediction model involving 14 MAPK signaling pathway-related genes, which is essential for exploring potential biomarkers for KIRC diagnosis.