System analysis of VEGFA in renal cell carcinoma: The expression, prognosis, gene regulation network and regulation targets

The Necroptotic Process-related Signature Predicts Immune Infiltration and Drug Sensitivity in Kidney Renal Papillary Cell Carcinoma

BACKGROUND

It remains controversial whether the current subtypes of kidney renal papillary cell carcinoma (KIRP) can be used to predict the prognosis independently.

OBJECTIVE

This observational study aimed to identify a risk signature based on necroptotic process- related genes (NPRGs) in KIRP.

METHODS

In the training cohort, LASSO regression was applied to construct the risk signature from 158 NPRGs, followed by the analysis of Overall Survival (OS) using the Kaplan-Meier method. The signature accuracy was evaluated by the Receiver Operating Characteristic (ROC) curve, which was further validated by the test cohort. Wilcoxon test was used to compare the expressions of immune-related genes, neoantigen genes, and immune infiltration between different risk groups, while the correlation test was performed between NPRGs expressions and drug sensitivity. Gene set enrichment analysis was used to investigate the NPRGs' signature's biological functions.

RESULTS

We finally screened out 4-NPRGs (BIRC3, CAMK2B, PYGM, and TRADD) for constructing the risk signature with the area under the ROC curve (AUC) reaching about 0.8. The risk score could be used as an independent OS predictor. Consistent with the enriched signaling, the NPRGs signature was found to be closely associated with neoantigen, immune cell infiltration, and immune-related functions. Based on NPRGs expressions, we also predicted multiple drugs potentially sensitive or resistant to treatment.

CONCLUSION

The novel 4-NPRGs risk signature can predict the prognosis, immune infiltration, and therapeutic sensitivity of KIRP.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear-cell renal-cell carcinoma tumor microenvironment

BACKGROUND

Immunotherapy has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with immunotherapy naïve and exposed primary ccRCC tumors to better understand immunotherapy resistance.

RESULTS

Spatial molecular imaging of tumor and adjacent stroma samples from 21 tumors suggests that viable tumors following immunotherapy harbor more stromal CD8 + T cells and neutrophils than immunotherapy naïve tumors. YES1 is significantly upregulated in immunotherapy exposed tumor cells. Spatial GSEA shows that the epithelial-mesenchymal transition pathway is spatially enriched and the associated ligand-receptor transcript pair COL4A1-ITGAV has significantly higher autocorrelation in the stroma after exposure to immunotherapy. More integrin αV + cells are observed in immunotherapy exposed stroma on multiplex immunofluorescence validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. Assessing bulk RNA expression and proteomic correlates in CPTAC databases reveals that collagen IV protein is more abundant in advanced stages of disease.

CONCLUSIONS

Spatial transcriptomics of samples of 3 patient cohorts with cRCC tumors indicates that COL4A1 and ITGAV are more autocorrelated in immunotherapy-exposed stroma compared to immunotherapy-naïve tumors, with high expression among fibroblasts, tumor cells, and endothelium. Further research is needed to understand changes in the ccRCC tumor immune microenvironment and explore potential therapeutic role of integrin after immunotherapy treatment.

Deubiquitinase UCHL1 stabilizes KDM4B to augment VEGF signaling and confer bevacizumab resistance in clear cell renal cell carcinoma

BACKGROUND

Bevacizumab resistance poses barriers to targeted therapy in clear cell renal cell carcinoma (ccRCC). Whether there exist epigenetic targets that modulate bevacizumab sensitivity in ccRCC remains indefinite. The focus of this study is to explore the role of UCHL1 in ccRCC.

METHODS

Both in vitro and in vivo experiments were utilized to investigate the roles of UCHL1 in ccRCC. In vivo ubiquitination assays were performed to validate the posttranslational modification of KDM4B by UCHL1. Luciferase reporter and chromatin immunoprecipitation (ChIP) assays were utilized to explore KDM4B/VEGFA epigenetic regulations.

RESULTS

UCHL1 was increased in ccRCC and associated with unfavorable survival outcomes in patients. UCHL1 was required for ccRCC growth and migration. Mechanistically, the wild-type UCHL1, but not C90A mutant, mediated the deubiquitination of KDM4B and thereby stabilized its proteins. KDM4B was up-regulated in ccRCC and potentiated cell growth. UCHL1 depended on KDM4B to augment ccRCC malignancies. Targeting UCHL1 suppressed tumor growth, colony formation, and migration abilities, which could be rescued by KDM4B. Furthermore, KDM4B was directly bound to the promoter region of VEGFA, abolishing repressive H3K9me3 modifications. KDM4B coordinated with HIF2α to activate VEGFA transcriptional levels. UCHL1-KDM4B axis governs VEGFA levels to sustain the angiogenesis phenotypes. Finally, a specific small-molecule inhibitor (6RK73) targeting UCHL1 remarkably inhibited ccRCC progression and further sensitized ccRCC to bevacizumab treatment.

CONCLUSION

Overall, this study defined an epigenetic mechanism of UCHL1/KDM4B in activating VEGF signaling. The UCHL1-KDM4B axis represents a novel target for treating ccRCC and improving the efficacy of anti-angiogenesis therapy.

Identification of key genes and signalling pathways in clear cell renal cell carcinoma: An integrated bioinformatics approach

BACKGROUND

Clear cell Renal Cell Carcinoma (ccRCC) is one of the most prevalent types of kidney cancer. Unravelling the genes responsible for driving cellular changes and the transformation of cells in ccRCC pathogenesis is a complex process.

OBJECTIVE

In this study, twelve microarray ccRCC datasets were chosen from the gene expression omnibus (GEO) database and subjected to integrated analysis.

METHODS

Through GEO2R analysis, 179 common differentially expressed genes (DEGs) were identified among the datasets. The common DEGs were subjected to functional enrichment analysis using ToppFun followed by construction of protein-protein interaction network (PPIN) using Cytoscape. Clusters within the DEGs PPIN were identified using the Molecular Complex Detection (MCODE) Cytoscape plugin. To identify the hub genes, the centrality parameters degree, betweenness, and closeness scores were calculated for each DEGs in the PPIN. Additionally, Gene Expression Profiling Interactive Analysis (GEPIA) was utilized to validate the relative expression levels of hub genes in the normal and ccRCC tissues.

RESULTS

The common DEGs were highly enriched in Hypoxia-inducible factor (HIF) signalling and metabolic reprogramming pathways. VEGFA, CAV1, LOX, CCND1, PLG, EGF, SLC2A1, and ENO2 were identified as hub genes.

CONCLUSION

Among 8 hub genes, only the expression levels of VEGFA, LOX, CCND1, and EGF showed a unique expression pattern exclusively in ccRCC on compared to other type of cancers.

[Peculiarities of angiogenesis in clear cell renal cancer]

A literature search was conducted to review papers on the results of studies of clear cell renal cancer (CCRC) vascularization. Numerous data on the relationship between tumor pathogenesis and its vascularization have been revealed, which indicates the multifactorial nature of CCRC development and the significant role of angiogenesis in this process. It should be taken into account that patients with CCRC may have impaired vessel formation even before tumor development. To evaluate normal and pathologic angiogenesis, a pathohistologic study using immunohistochemistry is certainly necessary. Due to the significant role of angiogenesis in the development and course of CCRC, the use of drugs that suppress the formation of the vascular network in the tumor is relevant and advisable. To date, many drugs have been developed and introduced into clinical practice to inhibit angiogenesis. However, such drugs have not lived up to the expectations placed due to the frequent and rapidly developing drug resistance. Timely detection of pre-tumor and tumor processes, as well as effective treatment of cancer, including CCRC, is possible only with close cooperation between pathomorphologists and oncologists.

Differential expression of HIF1A and its downstream target VEGFA in the main subtypes of renal cell carcinoma and their impact on patient survival

Renal cell carcinoma (RCC) represents around 3% of all cancers, with the most frequent histological types being clear-cell RCC (ccRCC), followed by papillary (pRCC) and chromophobe (chRCC). Hypoxia-inducible factors (HIFs), which promote the expression of various target genes, including vascular endothelial growth factor (VEGF) and the high- affinity glucose transporter 1, have an important role in the pathogenesis of RCC. This study investigated the immunohistochemical expression of HIF-1α and VEGF-A, showing significantly higher HIF-1α nuclear expression in pRCC compared to ccRCC, while there was no significant difference in VEGF-A protein expression between the analyzed histological RCC subtypes. The quantitative reverse transcription polymerase chain reaction for HIF1A showed no statistical difference between histological types. Data from publicly available RNA sequencing databases were analyzed and showed that, compared to healthy kidney tissue, VEGFA was significantly up-regulated in ccRCC and significantly down-regulated in pRCC. The comparison between histological subtypes of RCC revealed that VEGFA was significantly up-regulated in ccRCC compared to both pRCC and chRCC. There was no statistically significant difference in survival time between HIF1A high- and low-expression groups of patients. As for VEGFA expression, pRCC patients with low expression had a significantly higher survival rate compared to patients with high VEGFA expression.

Increased spatial coupling of integrin and collagen IV in the immunoresistant clear cell renal cell carcinoma tumor microenvironment

Background

Immunotherapy (IO) has improved survival for patients with advanced clear cell renal cell carcinoma (ccRCC), but resistance to therapy develops in most patients. We use cellular-resolution spatial transcriptomics in patients with IO naïve and IO exposed primary ccRCC tumors to better understand IO resistance. Spatial molecular imaging (SMI) was obtained for tumor and adjacent stroma samples. Spatial gene set enrichment analysis (GSEA) and autocorrelation (coupling with high expression) of ligand-receptor transcript pairs were assessed. Multiplex immunofluorescence (mIF) validation was used for significant autocorrelative findings and the cancer genome atlas (TCGA) and the clinical proteomic tumor analysis consortium (CPTAC) databases were queried to assess bulk RNA expression and proteomic correlates.

Results

21 patient samples underwent SMI. Viable tumors following IO harbored more stromal CD8+ T cells and neutrophils than IO naïve tumors. YES1 was significantly upregulated in IO exposed tumor cells. The epithelial-mesenchymal transition pathway was enriched on spatial GSEA and the associated transcript pair COL4A1-ITGAV had significantly higher autocorrelation in the stroma. Fibroblasts, tumor cells, and endothelium had the relative highest expression. More integrin αV+ cells were seen in IO exposed stroma on mIF validation. Compared to other cancers in TCGA, ccRCC tumors have the highest expression of both COL4A1 and ITGAV. In CPTAC, collagen IV protein was more abundant in advanced stages of disease.

Conclusions

On spatial transcriptomics, COL4A1 and ITGAV were more autocorrelated in IO-exposed stroma compared to IO-naïve tumors, with high expression amongst fibroblasts, tumor cells, and endothelium. Integrin represents a potential therapeutic target in IO treated ccRCC.

Mathematical and Machine Learning Models of Renal Cell Carcinoma: A Review

This review explores the multifaceted landscape of renal cell carcinoma (RCC) by delving into both mechanistic and machine learning models. While machine learning models leverage patients' gene expression and clinical data through a variety of techniques to predict patients' outcomes, mechanistic models focus on investigating cells' and molecules' interactions within RCC tumors. These interactions are notably centered around immune cells, cytokines, tumor cells, and the development of lung metastases. The insights gained from both machine learning and mechanistic models encompass critical aspects such as signature gene identification, sensitive interactions in the tumors' microenvironments, metastasis development in other organs, and the assessment of survival probabilities. By reviewing the models of RCC, this study aims to shed light on opportunities for the integration of machine learning and mechanistic modeling approaches for treatment optimization and the identification of specific targets, all of which are essential for enhancing patient outcomes.

The immunoreactivity of GLI1 and VEGFA is a potential prognostic factor in kidney renal clear cell carcinoma

Kidney renal clear cell carcinoma (KIRC) is the most common type of kidney cancer and its pathogenesis is strongly associated with VHL-HIF-VEGF signaling. SHH ligand is the upstream SHH pathway regulator, while GLI1 is its major effector that stimulates as a transcription factor, i.a. expression of VEGFA gene. The aim of present study was to assess the prognostic significance of SHH, GLI1 and VEGFA immunoreactivity in KIRC tissues. The analysis included paired tumor and normal samples from 34 patients with KIRC. The immunoreactivity of SHH, GLI1 and VEGFA proteins was determined by immunohistochemical (IHC) renal tissues staining. The IHC staining results were assessed using the immunoreactive score (IRS) method which takes into account the number of cells showing a positive reaction and the intensity of the reaction. Increased GLI1 protein immunoreactivity was observed in KIRC tissues, especially in early-stage tumors, according to the TNM classification. Elevated expression of the VEGFA protein was noted primarily in high-grade KIRC samples according to the Fuhrman/WHO/ISUP scale. Moreover, a directly proportional correlation was observed between SHH and VEGFA immunoreactivity in TNM 3 + 4 and Fuhrman/ISUP/WHO 3 + 4 tumor tissues as well as in samples of patients with shorter survival. We also observed an association between shorter patient survival as well as increased and decreased immunoreactivity, of the VEGFA and GLI1, respectively. The aforementioned findings suggest that the expression pattern of SHH, GLI1 and VEGFA demonstrates prognostic potential in KIRC.

Exploring oncogenes for renal clear cell carcinoma based on G protein-coupled receptor-associated genes

G protein-coupled receptors (GPCRs) are a class of receptors on cell membranes that regulate various biological processes in cells, such as cell proliferation, differentiation, migration, apoptosis, and metabolism, by interacting with G proteins. However, the role of G protein-coupled receptors in predicting the prognosis of renal clear cell carcinoma is still unknown. The transcriptome data and clinical profiles of renal clear cell carcinoma patients, were downloaded from TCGA databases, and the validation group data were downloaded from number GSE167573, including 63 tumor samples and 14 normal samples. Single-cell RNA sequencing data were downloaded from the GEO database, No. GSE152938 and selected samples were used for GSEA enrichment analysis, WGCNA subgroup analysis, single-cell data analysis, and mutation analysis to explore the role of G protein-coupled receptor-related genes in the diagnosis and prognosis of renal clear cell carcinoma and to verify their reliability with cellular experiments. Finally, this study establishes a disease model based on G protein-coupled receptor-related genes, which may help to propose targeted therapeutic regimens in different strata of renal cell carcinoma patients.Author names: Please confirm if the author names are presented accurately and in the correct sequence (given name, middle name/initial, family name). Author: Given name [Lisa Jia] Last name [Tran].It's ok!

HNRNPC promotes collagen fiber alignment and immune evasion in breast cancer via activation of the VIRMA-mediated TFAP2A/DDR1 axis

BACKGROUND

Cancers aggressively reorganize collagen in their microenvironment, leading to the evasion of tumor cells from immune surveillance. However, the biological significance and molecular mechanism of collagen alignment in breast cancer (BC) have not been well established.

METHODS

In this study, BC-related RNA-Seq data were obtained from the TCGA database to analyze the correlation between DDR1 and immune cells. Mouse BC cells EO771 were selected for in vitro validation, and dual-luciferase experiments were conducted to examine the effect of TFAP2A on DDR1 promoter transcription activity. ChIP experiments were performed to assess TFAP2A enrichment on the DDR1 promoter, while Me-RIP experiments were conducted to detect TFAP2A mRNA m6A modification levels, and PAR-CLIP experiments were conducted to determine VIRMA's binding to TFAP2A mRNA and RIP experiments to investigate HNRNPC's recognition of m6A modification on TFAP2A mRNA. Additionally, an in vivo mouse BC transplant model and the micro-physiological system was constructed for validation, and Masson staining was used to assess collagen fiber arrangement. Immunohistochemistry was conducted to identify the number of CD8-positive cells in mouse BC tumors and Collagen IV content in ECM, while CD8 + T cell migration experiments were performed to measure CD8 + T cell migration.

RESULTS

Bioinformatics analysis showed that DDR1 was highly expressed in BC and negatively correlated with the proportion of anti-tumor immune cell infiltration. In vitro cell experiments indicated that VIRMA, HNRNPC, TFAP2A, and DDR1 were highly expressed in BC cells. In addition, HNRNPC promoted TFAP2A expression and, therefore, DDR1 transcription by recognizing the m6A modification of TFAP2A mRNA by VIRMA. In vivo animal experiments further confirmed that VIRMA and HNRNPC enhanced the TFAP2A/DDR1 axis, promoting collagen fiber alignment, reducing anti-tumor immune cell infiltration, and promoting immune escape in BC.

CONCLUSION

This study demonstrated that HNRNPC promoted DDR1 transcription by recognizing VIRMA-unveiled m6A modification of TFAP2A mRNA, which enhanced collagen fiber alignment and ultimately resulted in the reduction of anti-tumor immune cell infiltration and promotion of immune escape in BC.

Overview of miR-106a Regulatory Roles: from Cancer to Aging

MicroRNAs (miRNAs) comprise a class of non-coding RNA with extensive regulatory functions within cells. MiR-106a is recognized for its super-regulatory roles in vital processes. Hence, the analysis of its expression in association with diseases has attracted considerable attention for molecular diagnosis and drug development. Numerous studies have investigated miR-106 target genes and shown that this miRNA regulates the expression of some critical cell cycle and apoptosis factors, suggesting miR-106a as an ideal diagnostic and prognostic biomarker with therapeutic potential. Furthermore, the reported correlation between miR-106a expression level and cancer drug resistance has demonstrated the complexity of its functions within different tissues. In this study, we have conducted a comprehensive review on the expression levels of miR-106a in various cancers and other diseases, emphasizing its target genes. The promising findings surrounding miR-106a suggest its potential as a valuable biomolecule. However, further validation assessments and overcoming existing limitations are crucial steps before its clinical implementation can be realized.

GPR68 limits the severity of chemical-induced oral epithelial dysplasia

Head and neck cancer is the sixth most common malignancy, and there is an urgent need to identify physiological processes contributing to tumorigenesis. Extracellular acidification caused by aerobic glycolysis within tumor microenvironments can stimulate proton-sensing receptors. GPR68, or ovarian cancer G protein-coupled receptor 1, responds to extracellular acidity and is highly expressed in head and neck squamous cell carcinoma (HNSCC) as well as normal esophageal tissue. To study the role of GPR68 in oral dysplasia, wild-type and GPR68^-/- mice were treated with 4-Nitroquinoline N-oxide (4NQO) in drinking water for 11-13 weeks, followed by normal water for 11-12 weeks. 4NQO treatment resulted in 45 percent of GPR68^-/- mice developing severe dysplasia or squamous cell carcinoma compared to only 10.5 percent of GPR68^+/+ mice. This correlated with increased frequencies of regulatory T cells in the spleens of male GPR68^-/- mice. Dysplastic regions of the tongue had increased CD31 staining compared to normal regions in both GPR68^-/- and GPR68^+/+ mice, suggesting that angiogenesis was GPR68-independent. RNA knockdown studies using HNSCC cell lines demonstrated no direct effect of GPR68 on survival or growth. Overall, we demonstrate that GPR68-deficiency worsens the severity of chemical-induced oral dysplasia, suggesting a protective role for this gene in tumorigenesis.

Systematic analysis of the BET family in adrenocortical carcinoma: The expression, prognosis, gene regulation network, and regulation targets

BACKGROUND

Bromodomain and extracellular terminal (BET) family (including BRD2, BRD3, and BRD4) is considered to be a major driver of cancer cell growth and a new target for cancer therapy. Currently, more than 30 targeted inhibitors have shown significant inhibitory effects against various tumors in preclinical and clinical trials. However, the expression levels, gene regulatory networks, prognostic value, and target prediction of BRD2, BRD3, and BRD4 in adrenocortical carcinoma (ACC) have not been fully elucidated. Therefore, this study aimed to systematically analyze the expression, gene regulatory network, prognostic value, and target prediction of BRD2, BRD3, and BRD4 in patients with ACC, and elucidated the association between BET family expression and ACC. We also provided useful information on BRD2, BRD3, and BRD4 and potential new targets for the clinical treatment of ACC.

METHODS

We systematically analyzed the expression, prognosis, gene regulatory network, and regulatory targets of BRD2, BRD3, and BRD4 in ACC using multiple online databases, including cBioPortal, TRRUST, GeneMANIA, GEPIA, Metascape, UALCAN, LinkedOmics, and TIMER.

RESULTS

The expression levels of BRD3 and BRD4 were significantly upregulated in ACC patients at different cancer stages. Moreover, the expression of BRD4 was significantly correlated with the pathological stage of ACC. ACC patients with low BRD2, BRD3, and BRD4 expressions had longer survival than patients with high BRD2, BRD3, and BRD4 expressions. The expression of BRD2, BRD3, and BRD4 was altered by 5%, 5%, and 12% in 75 ACC patients, respectively. The frequency of gene alterations in the 50 most frequently altered BRD2, BRD3, and BRD4 neighboring genes in these ACC patients were ≥25.00%, ≥25.00%, and ≥44.44%, respectively. BRD2, BRD3, and BRD4 and their neighboring genes form a complex network of interactions mainly through co-expression, physical interactions, and shared protein domains. Molecular functions related to BRD2, BRD3, and BRD4 and their neighboring genes mainly include protein-macromolecule adaptor activity, cell adhesion molecule binding, and aromatase activity. Chemokine signaling pathway, thiamine metabolism, and olfactory transduction were found to be enriched as per the KEGG pathway analysis. SP1, NPM1, STAT3, and TP53 are key transcription factors for BRD2, BRD4, and their neighboring genes. MiR-142-3P, miR-484, and miR-519C were the main miRNA targets of BRD2, BRD3, BRD4, and their neighboring genes. We analyzed the mRNA sequencing data from 79 patients with ACC and found that ZSCAN12, DHX16, PRPF4B, EHMT1, CDK5RAP2, POMT1, WIZ, ZNF543, and AKAP8 were the top nine genes whose expression were positively associated with BRD2, BRD3, and BRD4 expression. The expression level of BRD2, BRD3, and BRD4 positively correlated with B cell and dendritic cell infiltration levels. BRD4-targeted drug PFI-1 and (BRD2, BRD3, and BRD4)-targeted drug I-BET-151 may have good inhibitory effects on the SW13 cell line.

CONCLUSIONS

The findings of this study provide a partial basis for the role of BRD2, BRD3, and BRD4 in the occurrence and development of ACC. In addition, this study also provides new potential therapeutic targets for ACC, which can serve as a reference for future basic and clinical research.

Comprehensive analysis of a glycolysis and cholesterol synthesis-related genes signature for predicting prognosis and immune landscape in osteosarcoma

Background

Glycolysis and cholesterol synthesis are crucial in cancer metabolic reprogramming. The aim of this study was to identify a glycolysis and cholesterol synthesis-related genes (GCSRGs) signature for effective prognostic assessments of osteosarcoma patients.

Methods

Gene expression data and clinical information were obtained from GSE21257 and TARGET-OS datasets. Consistent clustering method was used to identify the GCSRGs-related subtypes. Univariate Cox regression and LASSO Cox regression analyses were used to construct the GCSRGs signature. The ssGSEA method was used to analyze the differences in immune cells infiltration. The pRRophetic R package was utilized to assess the drug sensitivity of different groups. Western blotting, cell viability assay, scratch assay and Transwell assay were used to perform cytological validation.

Results

Through bioinformatics analysis, patients diagnosed with osteosarcoma were classified into one of 4 subtypes (quiescent, glycolysis, cholesterol, and mixed subtypes), which differed significantly in terms of prognosis and tumor microenvironment. Weighted gene co-expression network analysis revealed that the modules strongly correlated with glycolysis and cholesterol synthesis were the midnight blue and the yellow modules, respectively. Both univariate and LASSO Cox regression analyses were conducted on screened module genes to identify 5 GCSRGs (RPS28, MCAM, EN1, TRAM2, and VEGFA) constituting a prognostic signature for osteosarcoma patients. The signature was an effective prognostic predictor, independent of clinical characteristics, as verified further via Kaplan-Meier analysis, ROC curve analysis, univariate and multivariate Cox regression analysis. Additionally, GCSRGs signature had strong correlation with drug sensitivity, immune checkpoints and immune cells infiltration. In cytological experiments, we selected TRAM2 as a representative gene to validate the validity of GCSRGs signature, which found that TRAM2 promoted the progression of osteosarcoma cells. Finally, at the pan-cancer level, TRAM2 had been correlated with overall survival, progression free survival, disease specific survival, tumor mutational burden, microsatellite instability, immune checkpoints and immune cells infiltration.

Conclusion

Therefore, we constructed a GCSRGs signature that efficiently predicted osteosarcoma patient prognosis and guided therapy.

Systematic Analysis of CXC Chemokine-Vascular Endothelial Growth Factor A Network in Colonic Adenocarcinoma from the Perspective of Angiogenesis

Background

Tumor angiogenesis plays a vital role in tumorigenesis, proliferation, and metastasis. Recently, vascular endothelial growth factor A (VEGFA) and CXC chemokines have been shown to play vital roles in angiogenesis. Exploring the expression level, gene regulatory network, prognostic value, and target prediction of the CXC chemokine-VEGFA network in colon adenocarcinoma (COAD) is crucial from the perspective of tumor angiogenesis.

Methods

In this study, we analyzed gene expression and regulation, prognostic value, target prediction, and immune infiltrates related to the CXC chemokine-VEGFA network in patients with COAD using multiple databases (cBioPortal, UALCAN, Human Protein Atlas, GeneMANIA, GEPIA, TIMER (version 2.0), TRRUST (version 2), LinkedOmics, and Metascape).

Results

Our results showed that CXCL1/2/3/5/6/8/11/16/17 and VEGFA were markedly overexpressed, while CXCL12/13/14 were underexpressed in patients with COAD. Moreover, genetic alterations in the CXC chemokine-VEGFA network found at varying rates in patients with COAD were as follows: CXCL1/2/17 (2.1%), CXCL3/16 (2.6%), CXCL5/14 (2.4%), CXCL6 (3%), CXCL8 (0.8%), CXCL11/13 (1.9%), CXCL12 (0.6%), and VEGFA (1.3%). Promoter methylation of CXCL1/2/3/11/13/17 was considerably lower in patients with COAD, whereas methylation of CXCL5/6/12/14 and VEGFA was considerably higher. Furthermore, CXCL9/10/11 and VEGFA expression was notably correlated with the pathological stages of COAD. In addition, patients with COAD with high CXCL8/11/14 or low VEGFA expression levels survived longer than patients with dissimilar expression levels. CXC chemokines and VEGFA form a complex regulatory network through coexpression, colocalization, and genetic interactions. Moreover, many transcription factor targets of the CXC chemokine-VEGFA network in patients with COAD were identified: RELA, NFKB1, ZFP36, XBP1, HDAC2, SP1, ATF4, EP300, BRCA1, ESR1, HIF1A, EGR1, STAT3, and JUN. We further identified the top three miRNAs involved in regulating each CXC chemokine within the network: miR-518C, miR-369-3P, and miR-448 regulated CXCL1; miR-518C, miR-218, and miR-493 regulated CXCL2; miR-448, miR-369-3P, and miR-221 regulated CXCL3; miR-423 regulated CXCL13; miR-378, miR-381, and miR-210 regulated CXCL14; miR-369-3P, miR-382, and miR-208 regulated CXCL17; miR-486 and miR-199A regulated VEGFA. Furthermore, the CXC chemokine-VEGFA network in patients with COAD was notably associated with immune infiltration.

Conclusions

This study revealed that the CXC chemokine-VEGFA network might act as a prognostic biomarker for patients with COAD. Moreover, our study provides new therapeutic targets for COAD, serving as a reference for further research in the future.