Identification Of Genes Research Articles

The potential therapeutic applications of CRISPR/Cas9 in colorectal cancer.

The application of the CRISPR-associated nuclease 9 (Cas9) system in tumor studies has led to the discovery of several new treatment strategies for colorectal cancer (CRC), including the recognition of novel target genes, the construction of animal mass models, and the identification of genes related to chemotherapy resistance. CRISPR/Cas9 can be applied to genome therapy for CRC, particularly regarding molecular-targeted medicines and suppressors. This review summarizes some aspects of using CRISPR/Cas9 in treating CRC. Further in-depth and systematic research is required to fully realize the potential of CRISPR/Cas9 in CRC treatment and integrate it into clinical practice.

Identification and Characterization of Key Genes Associated with Amelogenesis

Abstract Objectives The identification of key genes associated with amelogenesis would be helpful in finding solutions to genetic disorders in oral biology. The study aimed to use in silico analysis to identify the key genes involved in tooth development associated with preameloblasts (PABs) and secretory ameloblasts (SABs). Material and Methods The data was subjected to quality analysis and uniform manifold approximation and projection analysis. To examine the distribution of the genes and identify important upregulated loci, a p-value histogram, a quantile plot, a mean difference and mean-variance plot, and a volcano plot were generated. Finally, protein-protein interaction and gene enrichment analyses were performed to determine the ontology, relevant biological processes, and molecular functions of selected genes. Results A total of 157 genes were found to be significant in the PAB versus SAB comparison. HIST1H31 revealed strong interaction with HIST1H2BM, and EXO1, ASPM, SPC25, and TTK showed strong interactions with one other. The STRING database revealed that NCAPG, CENPU, NUSAP1, HIST1H2BM, and HIST1H31 are involved in biological processes. NCAPG, CENPU, SPC25, ETV5, TTK, ETV1, FAM9A, NUSAP1, HIST1H2BM, and HIST1H31 are involved in cellular components. Conclusion The TTK, NUSAP1, CENPU, NCAPG, FAM9A, ASPM, SPC25, and HIST1H31 genes demonstrate functions in cell division. These genes might play a role in ameloblast development. These results will be useful in developing new methods to stimulate ameloblast development, which is essential for tooth regeneration and tissue engineering. However, more research is required to validate the functions of these genes and the genes with which they interact. A wide variety of genetic, epigenetic, and exogenous signaling factors regulate these genes and pathways throughout development and differentiation, cell fate, and behavior.

Identification and validation of hub differential genes in pulmonary sarcoidosis

A total of 138 cDEGs were screened from mediastinal lymph nodes and peripheral whole blood. Among them, 6 hub cDEGs including CTSS, CYBB, FPR2, MNDA, TLR1 and TLR8 with elevated degree and betweenness levels were illustrated in protein-protein interaction network. In comparison to healthy controls, CTSS (1.61 vs. 1.05), CYBB (1.68 vs. 1.07), FPR2 (2.77 vs. 0.96), MNDA (2.14 vs. 1.23), TLR1 (1.56 vs. 1.09), and TLR8 (2.14 vs. 0.98) displayed notably elevated expression levels within pulmonary sarcoidosis PBMC samples (P < 0.0001 for FPR2 and P < 0.05 for others), echoing with prior mRNA microarray findings. The most significant functional pathways were immune response, inflammatory response, plasma membrane and extracellular exosome, with 6 hub cDEGs distributing along these pathways. CTSS, CYBB, FPR2, MNDA, TLR1, and TLR8 could be conducive to improving the diagnostic process and understanding the underlying mechanisms of pulmonary sarcoidosis.

Identification of Ascorbate Oxidase Genes and Their Response to Cold Stress in Citrus sinensis

Identification of Ascorbate Oxidase Genes and Their Response to Cold Stress in Citrus sinensis

The Transcriptome Characterization of the Hypothalamus and the Identification of Key Genes during Sexual Maturation in Goats

Sexual maturation in goats is a dynamic process regulated precisely by the hypothalamic–pituitary–gonadal axis and is essential for reproduction. The hypothalamus plays a crucial role in this process and is the control center of the reproductive activity. It is significant to study the molecular mechanisms in the hypothalamus regulating sexual maturation in goats. We analyzed the serum hormone profiles and hypothalamic mRNA expression profiles of female goats during sexual development (1 day old (neonatal, D1, n = 5), 2 months old (prepuberty, M2, n = 5), 4 months old (sexual maturity, M4, n = 5), and 6 months old (breeding period, M6, n = 5)). The results indicated that from D1 to M6, serum hormone levels, including FSH, LH, progesterone, estradiol, IGF1, and leptin, exhibited an initial increase followed by a decline, peaking at M4. Furthermore, we identified a total of 508 differentially expressed genes in the hypothalamus, with a total of four distinct expression patterns. Nuclear receptor subfamily 1, group D, member 1 (NR1D1), glucagon-like peptide 1 receptor (GLP1R), and gonadotropin-releasing hormone 1 (GnRH-1) may contribute to hormone secretion, energy metabolism, and signal transduction during goat sexual maturation via circadian rhythm regulation, ECM receptor interactions, neuroactive ligand–receptor interactions, and Wnt signaling pathways. This investigation offers novel insights into the molecular mechanisms governing the hypothalamic regulation of goat sexual maturation.

Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnostic model

PurposeThis study aims to utilize bioinformatics methods to systematically screen and identify susceptibility genes for cervical cancer, as well as to construct and validate an mitophagy-related genes (MRGs) diagnostic model. The objective is to increase the understanding of the disease’s pathogenesis and improve early diagnosis and treatment.MethodWe initially collected a large amount of genomic data, including gene expression profile and single nucleotide polymorphism (SNP) data, from the control group and Cervical cancer (CC) patients. Through bioinformatics analysis, which employs methods such as differential gene expression analysis and pathway enrichment analysis, we identified a set of candidate susceptibility genes associated with cervical cancer.ResultsMRGs were extracted from single-cell RNA sequencing data, and a network graph was constructed on the basis of intercellular interaction data. Furthermore, using machine learning algorithms, we constructed a clinical prognostic model and validated and optimized it via extensive clinical data. Through bioinformatics analysis, we successfully identified a group of genes whose expression significantly differed during the development of CC and revealed the biological pathways in which these genes are involved. Moreover, our constructed clinical prognostic model demonstrated excellent performance in the validation phase, accurately predicting the clinical prognosis of patients.ConclusionThis study delves into the susceptibility genes of cervical cancer through bioinformatics approaches and successfully builds a reliable clinical prognostic model. This study not only helps uncover potential pathogenic mechanisms of cervical cancer but also provides new directions for early diagnosis and treatment of the disease.

Screening and identification of the hub genes in severe acute pancreatitis and sepsis

BackgroundSevere acute pancreatitis (SAP) is accompanied with acute onset, rapid progression, and complicated condition. Sepsis is a common complication of SAP with a high mortality rate. This research aimed to identify the shared hub genes and key pathways of SAP and sepsis, and to explore their functions, molecular mechanism, and clinical value.MethodsWe obtained SAP and sepsis datasets from the Gene Expression Omnibus (GEO) database and employed differential expression analysis and weighted gene co-expression network analysis (WGCNA) to identify the shared differentially expressed genes (DEGs). Functional enrichment analysis and protein–protein interaction (PPI) was used on shared DEGs to reveal underlying mechanisms in SAP-associated sepsis. Machine learning methods including random forest (RF), least absolute shrinkage and selection operator (LASSO) and support vector machine recursive feature elimination (SVM-RFE) were adopted for screening hub genes. Then, receiver operating characteristic (ROC) curve and nomogram were applied to evaluate the diagnostic performance. Finally, immune cell infiltration analysis was conducted to go deeply into the immunological landscape of sepsis.ResultWe obtained a total of 123 DEGs through cross analysis between Differential expression analysis and WGCNA important module. The Gene Ontology (GO) analysis uncovered the shared genes exhibited a significant enrichment in regulation of inflammatory response. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that the shared genes were primarily involved in immunoregulation by conducting NOD-like receptor (NLR) signaling pathway. Three machine learning results revealed that two overlapping genes (ARG1, HP) were identified as shared hub genes for SAP and sepsis. The immune infiltration results showed that immune cells played crucial part in the pathogenesis of sepsis and the two hub genes were substantially associated with immune cells, which may be a therapy target.ConclusionARG1 and HP may affect SAP and sepsis by regulating inflammation and immune responses, shedding light on potential future diagnostic and therapeutic approaches for SAP-associated sepsis.

Multicenter cohort analysis of anoikis and EMT: implications for prognosis and therapy in lung adenocarcinoma

BackgroundAnoikis and epithelial-mesenchymal transition (EMT) are pivotal in the distant metastasis of lung adenocarcinoma (LUAD). A detailed understanding of their interplay and the identification of key genes is vital for effective therapeutic strategies against LUAD metastasis.MethodsKey prognostic genes related to anoikis and EMT were identified through univariate Cox regression analysis. We utilized ten machine learning algorithms to develop the Anoikis and EMT-Related Optimal Model (AEOM). The TCGA-LUAD dataset served as the training cohort, while six additional international multicenter LUAD datasets were employed as validation cohorts. The average concordance index (c-index) was used to evaluate model performance and identify the most effective model. Subsequent multi-omics analyses were conducted to explore differences in pathway enrichment, immune infiltration, and mutation landscapes between high and low AEOM groups. Experimental validation demonstrated that RHPN2, a key biomarker within the model, acts as an oncogene facilitating LUAD progression.ResultsThe AEOM displayed superior prognostic predictive performance for LUAD patients, outperforming numerous previously published LUAD signatures. Biologically, the AEOM was notably associated with immune features; the high AEOM group exhibited decreased immune activity and a tendency towards immune-cold tumors, as well as a higher tumor mutational burden (TMB). Subgroup analysis revealed that the low AEOM + high TMB group had the most favorable prognosis. The high AEOM group was primarily enriched in cell cycle-related pathways, promoting cancer cell proliferation. RHPN2, a crucial gene within the AEOM (correlation = 0.85, P < 0.05), was linked to poorer prognosis in LUAD patients with elevated RHPN2 expression. Further in vitro experiments showed that RHPN2 modulates LUAD cell proliferation and invasion.ConclusionThe AEOM provides a robust prognostic model for LUAD, uncovering critical immune and biological pathways, with RHPN2 identified as a key oncogenic driver. These findings offer valuable insights for targeted therapies and enhanced patient outcomes.

Identification of genes supporting cold resistance of mammalian cells: lessons from a hibernator

Susceptibility of human cells to cold stress restricts the use of therapeutic hypothermia and long-term preservation of organs at low temperatures. In contrast, cells of mammalian hibernators possess remarkable cold resistance, but little is known about the molecular mechanisms underlying this phenomenon. In this study, we conducted a gain-of-function screening of genes that confer cold resistance to cold-vulnerable human cells using a cDNA library constructed from the Syrian hamster, a mammalian hibernator, and identified Gpx4 as a potent suppressor of cold-induced cell death. Additionally, genetic deletion of or pharmacological inhibition of Gpx4 revealed that Gpx4 is necessary for suppressing lipid peroxidation specifically under cold in hamster cell lines. Genetic disruption of other ferroptosis-suppressing pathways, namely biopterin synthesis and mitochondrial or plasma membrane CoQ reduction pathways, also accelerated cold-induced cell death under Gpx4 dysfunction. Collectively, ferroptosis-suppressing pathways protect the cells of a mammalian hibernator from cold-induced cell death and the augmentation of these pathways renders cold resistance to cells of non-hibernators, including humans.

CELEBRIMBOR: Core and accessory genes from metagenomes

Abstract Motivation Metagenome-Assembled Genomes (MAGs) or Single-cell Amplified Genomes (SAGs) are often incomplete, with sequences missing due to errors in assembly or low coverage. This presents a particular challenge for the identification of true gene frequencies within a microbial population, as core genes missing in only a few assemblies will be mischaracterized by current pangenome approaches. Results Here, we present CELEBRIMBOR, a Snakemake pangenome analysis pipeline which uses a measure of genome completeness to automatically adjust the frequency threshold at which core genes are identified, enabling accurate core gene identification in MAGs and SAGs. Availability CELEBRIMBOR is published under open source Apache 2.0 licence at https://github.com/bacpop/CELEBRIMBOR and is available as a Docker container from this repository. Supplementary material is available in the online version of the article. Supplementary information Supplementary data are available at Bioinformatics online.

Genome-wide identification of carotenoid cleavage oxygenase genes in Orah mandarin and the mechanism by which CrCCD4b1 affects peel color

Genome-wide identification of carotenoid cleavage oxygenase genes in Orah mandarin and the mechanism by which CrCCD4b1 affects peel color

Identification of potential characteristic genes in chronic skin infections through RNA sequencing and immunohistochemical analysis

Identification of potential characteristic genes in chronic skin infections through RNA sequencing and immunohistochemical analysis

Identification of Hotspot Regions for Candidate Genes Associated with Peanut (Arachis hypogaea L.) Pod and Seed Size on Chromosome A05

The size of peanut pods and seeds, which directly affects yield and quality, also has significant implications for mechanized production and market efficiency. Identifying relevant loci and mining candidate genes is crucial for cultivating high-yield peanut varieties. In this study, we employed advanced generation recombinant inbred lines developed by crossbreeding Huayu 44 and DF12 as the experimental material. Quantitative trait locus (QTL) mapping for traits related to pod and seed size was conducted across six environments. A total of 44 QTLs were detected, distributed on chromosomes A02, A05, B04, B08, and B10. An enrichment region for multiple QTLs was also identified on chromosome A05 (19.28~52.32 cm). In this region, 10 KASP markers were developed, narrowing the enrichment area to two candidate gene hotspot regions of 600.9 kb and 721.2 kb. By combining gene prediction and functional annotation within the intervals, 10 candidate genes, including those encoding cytochrome P450 protein, polyamine synthase, mannose-1-phosphate guanylyltransferase, pentatricopeptide repeat protein, and E2F transcription factor, were identified as regulators of pod and seed size. This study provides technical support for the genetic improvement and key gene identification of peanut pod and seed size.

Single-Cell Transcriptomics Applied in Plants

Single-cell RNA sequencing (scRNA-seq) is a high-tech method for characterizing the expression patterns of heterogeneous cells in the same tissue and has changed our evaluation of biological systems by increasing the number of individual cells analyzed. However, the full potential of scRNA-seq, particularly in plant science, has not yet been elucidated. To explore the utilization of scRNA-seq technology in plants, we firstly conducted a comprehensive review of significant scRNA-seq findings in the past few years. Secondly, we introduced the research and applications of scRNA-seq technology to plant tissues in recent years, primarily focusing on model plants, crops, and wood. We then offered five databases that could facilitate the identification of distinct expression marker genes for various cell types. Finally, we analyzed the potential problems, challenges, and directions for applying scRNA-seq in plants, with the aim of providing a theoretical foundation for the better use of this technique in future plant research.

Culture and amplification-free nanopore sequencing for rapid detection of pathogens and antimicrobial resistance genes from urine.

Urinary Tract Infections (UTIs) are among the most prevalent infections globally. Every year, approximately 150million people are diagnosed with UTIs worldwide. The current state-of-the-art diagnostic methods are culture-based and have a turnaround time of 2-4 days for pathogen identification and susceptibility testing. This study first establishes an optical density culture-based method for spiking healthy urine samples with the six most prevalent uropathogens. Urine samples were spiked at clinically significant concentrations of 103-105 CFU/ml. Three DNA extraction kits (BioStic, PowerFood, and Blood and Tissue) were investigated based on the DNA yield, average processing time, elution volume, and the average cost incurred per extraction. After DNA extraction, the samples were sequenced using MinION and Flongle flow cells. The Blood and Tissue kit outperformed the other kits based on the investigated parameters. Using nanopore sequencing, all the pathogens and corresponding genes were only identified at a spike concentration of 105 CFU/ml, achieved after 10min and 3 hours of sequencing, respectively. However, some pathogens and antibiotic-resistance genes (ARG) could be identified from spikes at 103 colony formation units (CFU/mL). The overall turnaround time was five hours, from sample preparation to sequencing-based identification of pathogen ID and antimicrobial resistance genes. This study demonstrates excellent promise in reducing the time required for informed antibiotic administration from 48 to 72h to five hours, thereby reducing the number of empirical doses and increasing the chance of saving lives.

Research Progress on Photoperiod Gene Regulation of Heading Date in Rice

Heading date is a critical physiological process in rice that is influenced by both genetic and environmental factors. The photoperiodic pathway is a primary regulatory mechanism for rice heading, with key florigen genes Hd3a (Heading date 3a) and RFT1 (RICE FLOWERING LOCUS T1) playing central roles. Upstream regulatory pathways, including Hd1 and Ehd1, also significantly impact this process. This review aims to provide a comprehensive examination of the localization, cloning, and functional roles of photoperiodic pathway-related genes in rice, and to explore the interactions among these genes as well as their pleiotropic effects on heading date. We systematically review recent advancements in the identification and functional analysis of genes involved in the photoperiodic pathway. We also discuss the molecular mechanisms underlying rice heading date variation and highlight the intricate interactions between key regulatory genes. Significant progress has been made in understanding the molecular mechanisms of heading date regulation through the cloning and functional analysis of photoperiod-regulating genes. However, the regulation of heading date remains complex, and many underlying mechanisms are not yet fully elucidated. This review consolidates current knowledge on the photoperiodic regulation of heading date in rice, emphasizing novel findings and gaps in the research. It highlights the need for further exploration of the interactions among flowering-related genes and their response to environmental signals. Despite advances, the full regulatory network of heading date remains unclear. Further research is needed to elucidate the intricate gene interactions, transcriptional and post-transcriptional regulatory mechanisms, and the role of epigenetic factors such as histone methylation in flowering time regulation. This review provides a detailed overview of the current understanding of photoperiodic pathway genes in rice, setting the stage for future research to address existing gaps and improve our knowledge of rice flowering regulation.

Identification and validation of endoplasmic reticulum stress-related genes in patients with steroid-induced osteonecrosis of the femoral head

Steroid-induced osteonecrosis of the femoral head (SONFH) is a debilitating condition caused by long-term corticosteroid use, leading to impaired blood flow and bone cell death. The disruption of cellular processes and promotion of apoptosis by endoplasmic reticulum stress (ERS) is implicated in the pathogenesis of SONFH. We identified ERS-associated genes in SONFH and investigated their potential as therapeutic targets. We analysed the GSE123568 GEO dataset to identify differentially expressed genes (DEGs) related to ERS in SONFH. We conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses, identified hub genes by protein-protein interaction (PPI) analyses, and evaluated their functions by gene set enrichment analysis (GSEA). We constructed mRNA–miRNA networks, identified potential therapeutics, and assessed immune cell infiltration. We performed cross-validation using the GEO dataset GSE74089, qRT-PCR on clinical samples from patients with SONFH and controls, and a receiver operating characteristic (ROC) curve analysis to assess the diagnostic performance of the hub genes. We identified 195 ERS-related genes in SONFH, which were primarily involved in oxidative stress, immune responses, and metabolic pathways. The PPI network suggested CXCL8, STAT3, IL1B, TLR4, PTGS2, TLR2, CASP1, CYBB, CAT, and HOMX1 to be key hub genes, which were shown by GSEA to be involved in biological pathways related to metabolism, immune modulation, and cellular integrity. We also identified 261 microRNAs (miRNAs) as well as drugs such as dibenziodolium and N-acetyl-L-cysteine that modulated inflammatory responses in SONFH. Twenty-two immune cell subtypes showed significant correlations, such as a positive correlation between activated mast cells and Tregs, and patients with SONFH had fewer dendritic cells than controls. The hub genes CYBB and TLR4 showed significant correlations with M1 macrophages and CD8 T cells, respectively. Cross-validation and qRT-PCR confirmed the upregulation of STAT3, IL1B, TLR2, and CASP1 in patients with SONFH, validating the bioinformatics findings. An ROC curve analysis confirmed the diagnostic potential of the hub genes. The top 10 hub genes show promise as ERS-related diagnostic biomarkers for SONFH. We discovered that 261 miRNAs, including hsa-miR-23, influence these genes and identified potential therapeutics such as dibenziodolium and simvastatin. Immune profiling indicated altered immune functions in SONFH, with significant correlations among immune cell types. Validation confirmed the upregulation of STAT3, IL1B, TLR2 and CASP1, which had diagnostic potential. The findings suggest potential diagnostic markers and therapeutic targets for SONFH.

Exogenous interactome analysis of bovine viral diarrhea virus-host using network based-approach and identification of hub genes and important pathways involved in virus pathogenesis

Bovine viral diarrhea (BVD) is one of the most important diseases in livestock, caused by BVD virus (BVDV). During the pathogenesis of the virus, many interactions occur between host and viral proteins. Studying these interactions can help better understand the pathogenesis of the virus, identify putative functional proteins, and find new treatment and prevention strategies. To this aim, a BVDV-host protein-protein interaction (PPI) network map was constructed using Cytoscape and analyzed with cytoHubba, Kyoto Encyclopedia of Genes and Genomics (KEGG), Gene Ontology (GO), and Protein Analysis Through Evolutionary Relationships (PANTHER). Npro with 125 connections had the greatest number of interactions with host proteins. CD46, EEF-2, and TXN genes were detected as hub genes using different ranking algorithms in cytoHubba. BVDV interactions with its host mainly focus on targeting translation, protein synthesis, and cellular metabolism pathways. Different classes of proteins including translational proteins, nucleic acid metabolism proteins, metabolite interconversion enzymes, and protein-modifying enzymes are affected by BVDV. These findings improve our understanding of the effects of the virus on the cell. Hub genes and key pathways identified in the present study can serve as targets for novel BVDV prevention or treatment strategies.

Identification of MYC genes in four Cucurbitaceae species and their roles in the response to temperature stress

BackgroundMyelocytomatosis (MYC) transcription factors are crucial mediators of the response of plants to environmental stresses through via binding to DNA regulatory regions. However, few systematic characterizations of MYC genes are available in Cucurbitaceae species.ResultsIn this study, we identified 10, 8, 12, and 10 MYC genes in Cucumis sativus, Cucumis melo, Citrullus lanatus, and Benincasa hispida, respectively. Characterization revealed that all of the MYC proteins contain a highly conserved H4-V5-E6-E8-R9-R11-R12 sequence, which is essential for the binding of DNA regulatory regions. Evolutionary analysis enabled us to categorize 40 predicted MYC proteins from seven species into five distinct groups and revealed that the expansion of the MYC genes occurred before the divergence of monocots and dicots. The upstream promoter regions of the MYC genes contain a variety of developmental, stress, and hormone-responsive regulatory elements. The expression of cucumber MYC genes varies significantly across organs, with particularly high expression of CsaV3_3G001710 observed across all organs. Transcriptomic analysis revealed that certain cucumber MYC genes undergo specific upregulation or downregulation in response to both biotic and abiotic stressors. In particular, under temperature stress, the cucumber genes CsaV3_3G007980 and CsaV3_3G001710 were significantly upregulated. Interestingly, the homologs of these two genes in C. lanatus presented a similar expression pattern to that in C. sativus, whereas in B. hispida, they presented the opposite pattern, i.e., significant downregulation. These findings indicated that these two genes indeed respond to temperature stress but with different expression patterns, highlighting the divergent functions of homologous genes across different species.ConclusionsThis study analyzed the size and composition of the MYC gene family in four Cucurbitaceae species and investigated stress-responsive expression profiles, especially under temperature stress. All the results showed that MYC genes play important roles in development and stress responses, laying a theoretical foundation for further investigations of these response mechanisms.

A systematic investigation of clear cell renal cell carcinoma using meta-analysis and systems biology approaches.

Renal cell carcinoma with clear cells (ccRCC) is the most frequent kind; it accounts for almost 70% of all kidney cancers. A primary objective of current research was to find genes that may be used in ccRCC gene therapy to understand better the molecular pathways underlying the disease. Based on PubMed microarray searches and meta-analyses, we compared overall survival and recurrence-free survival rates in ccRCC patients with those in healthy samples. The technique was followed by a KEGG pathway and Gene Ontology (GO) function analyses, both performed in conjunction with the approach. Tumor immune estimate and multi-gene biomarkers validation for clinical outcomes were performed at the molecular and clinical cohort levels. Our analysis included fourteen GEO datasets based on inclusion and exclusion criteria. A meta-analysis procedure, network construction using PPIs, and four significant gene identification standard algorithms indicated that 11 genes had the most important differences. Ten genes were upregulated, and one was downregulated in the study. In order to analyze RFS and OS survival rates, 11 genes expressed in the GEPIA2 database were examined. Nearly nine of eleven significant genes have been found to beinvolved in tumor immunity. Furthermore, it was found that mRNA expression levels of these genes were significantly correlated with experimental literature studies on ccRCCs, which explained these findings. This study identified eleven gene panels associated with ccRCC growth and metastasis, as well as their immune system infiltration.