Identification of Crotonylation Metabolism Signature Predicting Overall Survival for Clear Cell Renal Cell Carcinoma

Background Immunotherapy shows promise in treating cancer by leveraging the immune system to combat cancer cells. However, the influence of crotonylation metabolism on the prognosis and tumor environment in ccRCC patients is not fully understood. Methods We conducted various systematic analyses, including prognosis and cluster analyses, to investigate the role of KAT2A in immunotherapy. We used qRT-PCR to compare KAT2A expression in cancer and adjacent tissues and among different cell lines. Additionally, we employed Cell Counting Kit-8, wound healing, and Transwell chamber assays to assess changes in the proliferative and metastatic ability of A498 and 786-O cells. Results We identified three clusters related to crotonylation metabolism, each with distinct prognosis and immune characteristics in ccRCC. We categorized CT1 as immune-inflamed, CT2 as immune-excluded, and CR3 as immune-desert. A new system, CRS, emerged as an effective predictor of patient outcomes with differing immune characteristics. Moreover, qRT-PCR revealed elevated KAT2A levels in ccRCC tissues and cell lines. KAT2A was found to promote ccRCC and correlate significantly with immunosuppressive elements and checkpoints. Reducing KAT2A expression hindered ccRCC cell growth and metastasis. Conclusion Our study highlights the critical role of crotonylation metabolism in cancer development and progression, particularly its link to poor prognosis. CRS proves to be an accurate predictor of patient outcomes and immune features in ccRCC. KAT2A shows strong associations with clinical factors and the immunosuppressive environment, suggesting potential for innovative immunotherapies in ccRCC treatment.


Introduction
Post-translational modifcation (PTM) of proteins encompasses chemical alterations that occur after the translation process.Tese modifcations wield substantial infuence over intracellular signal transduction, metabolism, and gene regulatory networks by orchestrating changes in protein stability, activity, localization, and interactions with other biological macromolecules, such as proteins, nucleic acids, and lipids [1][2][3].Consequently, they hold sway over a wide array of cellular functions.In normal cells, PTMs play a pivotal role in precisely and swiftly regulating cell proliferation, thereby dictating the cell's state-be it quiescence or proliferation.In contrast, in cancer cells, PTMs can foster abnormal proliferation by steering cell cycle-related efector proteins and perpetuating proliferation signals [4][5][6].Te vast spectrum of PTMs, numbering in the hundreds, encompasses forms like phosphorylation, glycosylation, acetylation, ubiquitination, and acylation [7].Among them, protein acylation stands out as a pivotal post-translational modifcation.Lipidated proteins often share an intimate association with non-polar structures like lipid bilayers, greatly elevating their hydrophobicity and, in turn, modulating their conformation, membrane afnity, localization, and mobility [8].Consequently, protein acylation plays a pivotal role in regulating cell proliferation and metabolism, regardless of whether the context is normal or cancerous.
Histone crotonylation, a conservative and non-acetylated histone lysine acylation modifcation, occupies a prominent niche in transcriptional regulation and disease progression [9,10].Lysine crotonylation (Kcr), a subtype of histone lysine acylation, primarily unfolds at the ε-amino group of histone lysines [11].Te mechanisms behind histone crotonylation's establishment, removal, and recognition are orchestrated by well-known enzymes involved in histone acetylation [12].Furthermore, localized shifts in histone crotonylation levels can precipitate corresponding changes in gene expression [13].Importantly, histone crotonylation exerts distinctive biological functions, impacting cell metabolism, the cell cycle, tissue development, and other vital processes [14][15][16].Nonetheless, the prognostic implications and underlying biological mechanisms of Kcr in clear cell renal cell carcinoma (ccRCC) remain veiled.
Tis study embarks on a systematic exploration of the prognostic signifcance and immune signatures associated with Kcr-related genes in ccRCC.We also construct Kcr-related clusters distinguished by their varying prognostic and immune characteristics.Leveraging data from the Cancer Genome Atlas (TCGA) and the E-MATB-1980 dataset, we construct and validate a Kcr-based prognostic model to predict the fate of ccRCC patients.Additionally, we delve into the clinical attributes, biological pathways, and immune properties of KAT2A, a pivotal gene in Kcr modifcation.

Data Acquisition and Processing.
Transcriptome data and clinical information of ccRCC patients were obtained from TCGA and Gene Expression Omnibus (GEO) databases.A set of 17 crotonylation-related genes (CRGs) were curated from pertinent literature sources [17,18].Te GSE22541 dataset was utilized as external validation datasets, while the GSE36895 and GSE73731 datasets were utilized to evaluate the clinical features of the model genes.

Construction of Crotonylation-Related Clusters.
To evaluate the role of CRGs in tumor progression, we adopted the non-negative matrix factorization (NMF) algorithm to classify patients.Survival diferences between crotonylationrelated clusters were evaluated using Kaplan-Meier (KM) analysis.To further delve into the diferences of biological pathways among the clusters, we identifed diferentially expressed genes (DEGs) according to the criteria of | log-Fold Change (logFC) > 1.5 | and adjusted p value <0.01.We then conducted Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses to unravel the underlying mechanisms of these DEGs.Gene set variation analysis (GSVA) was employed to explore variations in pathway enrichment among the clusters.

Establishment of the Crotonylation-Related Signature.
Firstly, we performed the Wilcoxon test to discern the differential expression of 17 CRGs between cancer and adjacent tumors tissues.Subsequently, we subjected the diferentially expressed CRGs to univariate Cox regression analysis to identify CRGs associated with prognosis.Utilizing the expression profle of prognostic related CRGs, we further constructed a prognostic model using the least absolute shrinkage and selector operation (LASSO) analysis.Te crotonylation-related signature (CRS) was obtained by linear combination of gene expression weighted regression coefcients.Te algorithm was as follows: CRS � Coef A * Gene A expression + Coef B * Gene B expression + Coef C * Gene C expression+. ... ..Coef N * Gene N expression, with Coef referring to the coefcient calculated by LASSO and gene expression referring to the expression of CRGs.According to the ratio of 1 : 1, the patients were classifed into training and test group.Te survival diferences in overall survival (OS, overall survival is a measure of the length of time individuals or patients survive from a defned starting point (such as diagnosis or treatment initiation) until death from any cause) were analyzed between the high and low groups.Te timedependent receiver operating characteristic (ROC) curve and univariate and multivariate analyses were adopted to assess the stability and accuracy of the model.Te GSE22541 dataset was used for external validation of the model.

Evaluation of the Immunogenomic Landscape.
Multiple algorithms were exploited to investigate immune infltration characteristics of ccRCC samples.Te Spearman algorithm was employed to analyze the correlation between CRS and immunoinfltrating cells.Te anticancer immune response (cancer immune cycle) in the tumor microenvironment (TME) had seven steps.Te immune activity scores on ccRCC samples were collected from the Tracking Tumor Immunophenotype (TIP, https://biocc.hrbmu.edu.cn/TIP/).Tumor microenvironment (TME) may afect the occurrence and development of cancer, so we employed the ESTIMATE algorithm to evaluate the TME score (ImmuneScore, StromalScore, and tumor purity) of ccRCC samples.Additionally, the single-sample gene set enrichment analysis (ssGSEA) algorithm was applied to assess immune function pathway scores in ccRCC samples.

Screening and Validation of Hub Crotonylation-Related
Genes.On the basis of modeled genes expression, the recursive feature elimination-(RFE-) support vector machine (SVM) algorithm was utilized to further screen the hub crotonylation-related genes.Ten, the KM survival curve and ROC curve were adopted to evaluate the prognostic characteristics of hub genes.We further exploited the correlation between hub genes and clinicopathological variables.Ten, the real-time quantitative PCR (RT-qPCR) was utilized to evaluate the diferential expression of modeling genes between ccRCC and normal tissues.Protein expression data for KAT2A between cancer and paracancer tissues were retrieved from the Human Protein Atlas (HPA) database.

Cell Culture and Cell
Transfection.Two human ccRCC cell lines (A498 and 786-O) were purchased from the cell bank of the Chinese Academy of Sciences (Shanghai, China).All cells were cultured in RPMI 1640 medium (Termo Fisher Scientifc, Inc.) supplemented with 10% fetal bovine serum (FBS; Termo Fisher Scientifc, Inc.) at a constant temperature of 37 °C in a humidifed atmosphere containing 5% CO 2 .

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International Journal of Clinical Practice Lentiviral shRNA plasmids that target KAT2A together with the nonspecifc control shRNA were obtained from Dharmacon (Shanghai, China).Transfection of plasmid and shRNA was performed with Lipo3000 following the manufacturer's instructions.
2.8.Transwell Assay.A498 and 786-O cells (with an cubation density of 2 × 10 5 ) were incubated in the upper chambers (Corning).For the invasion assay, the upper chambers were precoated with Matrigel (BD Biosciences).Culture medium without and with 10% FBS was added into the upper and lower chambers, respectively.After 12 h, nonmigrated cells were wiped out while migrated or invaded CRC cells were fxed, stained, and counted using an inverted microscope.
2.9.Wound Healing Assay.Cell migration was assessed by performing a wound healing assay.In brief, A498 and 786-O cells were transfected with KAT2A.Approximately 2 × 10 6 cells were seeded into 6-well plates and cultured for 24 h.Ten, a yellow plastic pipette tip was used to create a wound by scraping the cells.Cell migration was monitored under a Nikon Eclipse microscope and photographed at 100×.

Establishment of the Crotonylation-Related Clusters and
Functional Enrichment Analysis.We utilized the NMF algorithm to establish three disparate crotonylation metabolism-related clusters (CT1, CT2, and CT3) according to 17 CRG expressions (Figure 1(a)).Te heatmap illustrated the distribution of the clinical variables and CRG expression (Figure 1(b)).Te KM curve indicated that CT1 patients had the best prognosis (Figure 1(c)).To delve into diference of pathway enrichment among the clusters, we screened the DRGs according to the criteria of | logFC| ≥ 1.5 and adjusted p value <0.01.Venn diagram demonstrated that 788 DEGs were common among the three distinct crotonylation metabolismrelated clusters (Figure 1(d)).GO analysis revealed that DEGs were mainly enriched in cadherin binding, cell adhesion molecule binding, cell-substrate junction, and protein catabolic process (Figure 1(e)).KEGG analysis suggested that DEGs were focused on the immune-related pathway, oncogenic pathway, and angiogenesis pathway (Figure 1(f)).Additionally, GSVA analysis unveiled that CT1 was signifcantly related to the enrichment pathway related to immune activation, matrix and carcinogenic activation pathway were signifcantly enriched in CT2, and CT3 was obviously associated with the biological process of immunosuppression (Figures 1(g) and 1(h)).

Immune Infltration Characteristics of Crotonylation-Related Clusters.
To further explore causes of survival differences among crotonylation metabolism-related clusters, we analyzed characteristics of immune infltration.Initially, we analyzed diferences of immune function pathways among the clusters, fnding that the expression of multiple immune function pathways was highest in CT1 and lowest in CT3 (Figure 2(a)).Immunosuppression checkpoints were diferentially expressed among crotonylation metabolismrelated clusters, and the highest expression was found in CT3 (Figure 2(b)).Te TME scores showed signifcant diferences among various groups, with CT1 exhibiting the highest expression in StromalScore and ESTIMATEScore, while displaying the lowest expression in tumor purity (Figures 2(c)-2(f )).Heatmap presented the distribution of immune infltrating cells and TME scores among crotonylation metabolism-related clusters (Figure 2(g)).Additionally, the expression of immune infltrating cells was the highest in CT1 and the lowest in CT3 (Figure 2(h)).

Establishment of the Crotonylation-Related Signature and
Prognosis Analysis.To explore the role of CRGs in ccRCC, we explored diferential expression of CRGs between cancer and paracancerous tissues.Except for EP300 and SIRT1, the expression of other 15 CRGs was signifcantly diferent between ccRCC and paracancer tissues (Figure 3(a)).Subsequently, we identifed eight prognostic related CRGs through univariate Cox regression analysis (Figure 3(b)).After performing LASSO regression analysis on these 8 genes, we selected 4 genes to establish the crotonylationrelated signature (Figure 3(c)).Patients were randomly divided into training group and test group on a 1 : 1 ratio.Heatmap illustrated the distribution of four modeled genes and clinical variables in allrisk group (Figure 3(d)).KM curve and survival status distribution suggested that patients in the high CRS group had a worse prognosis in the allrisk group (Figures 3(e) and 3(f )).ROC curves about CRS in one, two, and tree years in the allrisk group were 0.735, 0.685, and 0.697 (Figure 3(g)).Univariate and multivariate Cox analysis suggested that CRS had strong predictive accuracy for the prognosis of ccRCC patients (Figures 3(h) and 3(i)).GSE22541 served as an external validation dataset to verify stability of CRS.Te KM curve and survival status distribution in the GSE22541 showed that CRS was associated with poor prognosis (Figures 3(j) and 3(k)).ROC curves about CRS in 1, 2, and 3 years in the GSE22541 dataset were 0.683, 0.699, and 0.680 (Figure 3(l)).Similar results were obtained in the training and test risk groups (Figure S1).Tese results corroborated the association between higher CRS expression and worse patient prognosis.(a)  .Te high CRS group exhibited higher expression levels in immune functional pathways such as the checkpoint, cytoolytic activity, CCR, and infammationpromoting pathway (Figure 5(i)).In order to further assess the relevance of CRS to immune typing, we then analyzed the relation between CRS and previously reported pan-cancer immune subtypes.Te expression of CRS was higher in C1, C2, and C6 and lowest in C3 (Figure 5(j)).Given that C6 was correlated with a poor prognosis and C3 was linked to a better prognosis, these results suggested a unique characteristic of the ccRCC immune microenvironment.Most immunosuppressive checkpoints were signifcantly overexpressed in the high CRS group (Figure 5(k)).Antitumor immunity must efectively eliminate cancer cells through a gradual process.To further analyze function of immune cells in progression of ccRCC, we obtained immune activity score of each step in ccRCC sample from TIP. Antitumor immune cells were signifcantly overexpressed in high CRS group (Figure 5(l)).

Identifcation of Prognostic Characteristics of Hub
Crotonylation-Related Genes.In order to identify the most representative prognostic genes related to crotonylation modifcation in RCC, we employed the SVM-RFE method to screen three genes (KAT2A, KAT6A, and SIRT3) (Figure 6(a)).Te AUC of ROC was used for evaluation of the ability to predict the prognosis of patients with ccRCC on the basis of gene expression.Te AUC values of KAT2A, KAT6A, and SIRT3 were 0.811, 0.618, and 0.572, respectively (Figure 6(b)).KM analysis showed that KAT2A was associated with a poor prognosis, while KAT6A and SIRT3 displayed an inverse association (Figures 6(c)-6(e)).Furthermore, KAT2A expression was higher in advanced clinical variables, while KAT6A and SIRT3 were opposite (Figures 6(f)-6(m)).

Identifcation of Immune Characteristics of KAT2A.
Ten, we further analyzed immune characteristics of KAT2A.
Patients were grouped into high and low KAT2A expression groups based on the average expression of KAT2A.In the low KAT2A group, most immune cells were markedly upregulated (Figure 7(a)).Figure 7(b) shows a signifcant negative correlation between KAT2A and a variety of immune cells.Moreover, KAT2A was positively correlated with multiple immunosuppressive checkpoints, with most of these checkpoints being markedly overexpressed in the high KAT2A group (Figures 7(c) and 7(d)).

KAT2A Knockdown Suppressed Proliferation, Migration, and Invasion in A498 and 786-O Cells.
In addition, 18 pairs of ccRCC tissues, tree ccRCC cell lines, and 1 normal renal cell line were detected by RT-qPCR.KAT2A was markedly upregulated in tumor tissues.Furthermore, KAT2A was markedly upregulated in ccRCC cell lines and was highest in A498 cell line in comparison to normal kidney cell lines (Figure 8(a)).In the KAT2A knockdown group, mRNA and protein expression of KAT2A were dramatically downregulated (Figure 8

Discussion
Renal cell carcinoma (RCC) is an extremely complex tumor originating from epithelial cells, of which ccRCC is the most common subtype [19,20].Te incidence and mortality of ccRCC were increasing year by year, accounting for about two to tree percent of adult malignancies [21][22][23].Since ccRCC was insensitive to targeted and immunosuppressive agents, surgical treatment remains the main and most effective treatment [23,24].Despite signifcant progress in early screening and diagnosis, about one-third of patients already metastasized when diagnosed and about 25% have metastases after surgical treatment [25,26].Lysine crotonylation takes part in many biological processes, including translation initiation, RNA splicing, DNA damage and repair, cell cycle, and amino acid metabolism.Tis study focuses on understanding the potential role of crotonylation modifcation in ccRCC, as Kcr has been implicated in various cellular processes, including those related to cancer.International Journal of Clinical Practice Immunotherapy has emerged as a promising approach for the treatment of cancer, ofering several advantages over traditional therapies such as chemotherapy and radiation [27].Its design is centered on the specifc targeting of cancer cells while preserving healthy cells.Unlike conventional treatments that often harm both cancerous and healthy cells, immunotherapy is designed to target specifc molecules or cells involved in the immune response against cancer.Tis targeted approach minimizes of-target toxicity and reduces the risk of side efects.Immunotherapy can reactivate the immune system, which can be particularly efective when cancer cells develop resistance to traditional treatments.Immune checkpoint inhibitors, for example, have shown success in blocking interactions that hinder immune responses, allowing immune cells to attack cancer cells more efectively.
In this study, based on the 17 CRG expressions, we employed the NMF algorithm to construct three crotonylationmodifed clusters with diferent prognostic and immune characteristics.By analyzing the diferences of immune and biological pathways between the three clusters, three crotonoylation modifcation clusters have markedly diferent TME cell infltration characteristics.We speculated that a large number of immune cell infltration and immune-related pathways were enriched in CT1, which was considered to be an immune-infammatory type; a large number of innate immune cell infltration and cancer-promoting activation-related pathways were enriched in CT2, and CT2 was considered an immune excluded type; there was a lack of immune cell infltration in CT3, which was considered an immune desert type.However, CT2 was signifcantly enriched in innate immune cells but had a poorer prognosis.It has been shown that immune-excluded tumors were infltrated by immune cells, but these immune cells were only present in the stroma surrounding the tumor cells.Terefore, activation of the stroma in the tumor microenvironment was considered to be T cell suppression [28].In addition, matrix activation pathways were clearly enriched in CT2.Tese pathways include ECM receptor interaction, TGF-β signal pathway, and cell adhesion.Tus, we hypothesized that the antitumor efects of immune cells were suppressed by the activation of intermediates in the CT2 cluster.Subsequently, the univariate cox and Lasso analyses were utilized to structure the Crotonacylation modifcation-related prognosis model and verifed the stability of this model in predicting patient prognosis with univariate and multivariate independent prognostic analysis and E-MATB-1980 datasets.In TME, invasive immune cells had key function in tumor proliferation, migration, invasion, and regulation of anticancer immunity and were extremely important therapeutic targets [29].In high CRS group, tumor microenvironment score and proportion of immunosuppressive cell infltration were higher, and the prognosis was worse.In conclusion, the crotonylation modifcation-related prognosis model was an important indicator for evaluating patients' prognosis and immune response, which was helpful for the formulation and development of personalized therapy for patients with ccRCC.
Kcr is not only a plentiful, evolutionally conservative, and physiologically related PTM but also signifcantly associated with the occurrence and progression of tumors.A quantitative proteomics study indicated that Kcr substrates targeted by P300 may be linked to cancer [30].Besides, crotonylation modifcation was expressed diferently in various cancers, such as high expression in thyroid, esophagus, colon, pancreas, and lung carcinomas, but low expression in liver and stomach carcinomas [31].At the same time, in hepatocellular carcinoma (HCC), Kcr was correlated to tumor, lymph node, and metastasis (TMN) staging [14].Besides histone crotonylation, many non-histone proteins also participate in carcinogenesis.In lung adenocarcinoma, many non-histone proteins were modifed by crotonylation, and these proteins were signifcantly enriched in subcellular localization, cell composition, molecular function, and many important cellular pathways [32].
As the frst writers, KAT2A (General control nondepressible 5 (GCN5)) has been shown to have acetyltransferase, succinyltransferase, and crotonyltransferase activities on histones [32][33][34].KAT2A regulated multiple biological events and played a vital role in tumor initiation and progression [34].KAT2A was highly expressed in nonsmall-cell radiation-induced lung cancer and may promote tumor progression by upregulating E2F1 and cyclin d1 [35].GCN5 was overexpressed in HCC, and downregulation of KAT2A inhibits HCC cell and xenograft tumor proliferation [36].KAT2A is markedly overexpressed in urothelial carcinoma, and KAT2A knockdown can inhibit the progression of urothelial carcinoma [37].Our study revealed that KAT2A was markedly upregulated in ccRCC, and this conclusion was further verifed by RT-qPCR assay and HPA dataset.At the same time, KAT2A was negatively associated with most immune cells and signifcantly positively correlated with immunosuppression checkpoints.We speculated that KAT2A might promote tumor metastasis and proliferation by participating in the establishment of an immunosuppressive tumor microenvironment.
Despite the valuable insights gained from this study, it has some limitations.Tese include the use of traditional univariate and Lasso regression analyses to construct the crotonylationrelated prognosis model, which may beneft from more advanced methodologies.Additionally, the study's reliance on clinical information from the TCGA database, which may lack comprehensive data, could be complemented with additional parameters such as imaging data.Future research could focus on further elucidating the mechanisms through which crotonylation modifcation afects ccRCC progression and exploring the potential of targeted therapies, including immunotherapies, based on these fndings.Moreover, clinical studies could be conducted to validate the prognostic and predictive value of the crotonylation-related signature in ccRCC patients, ultimately leading to more personalized treatment approaches for this challenging cancer subtype.

Conclusion
In brief, we classifed ccRCC patients into three crotonylation metabolism-related clusters with diferent prognosis and immune cell infltration characteristics.Moreover, the crotonylation metabolism-related prognostic model was constructed in ccRCC patients, which may be a marker to predict International Journal of Clinical Practice the prognosis and immune response of ccRCC patients.Meanwhile, KAT2A may contribute to the construction of an immunosuppressive tumor microenvironment, which may become a target for immunotherapy to further guide clinical treatment decisions.

Figure 2 :
Figure 2: Immune infltration characteristics of crotonylation metabolism-related clusters.(a) Diferential expression of immune function score among diferent crotonylation metabolism-related clusters.(b) Diferences in immunosuppressive checkpoint expression among crotonylation metabolism clusters.(c-f ) Diferences in tumor microenvironment scores among crotonylation metabolism-related clusters.(g) Distribution of immune cell and tumor microenvironment scores among crotonylation metabolism clusters.(h) Diferences in immune infating cells among crotonylation metabolism-related clusters.

Figure 3 :Figure 4 : Continued. 8 International
Figure 3: Construction and validation of the crotonylation metabolism-related signature.(a) Diferences in crotonylation metabolismrelated genes expression between ccRCC and normal tissues.(b) Results of univariate Cox regression analysis.(c) LASSO regression identifed 4 crotonylation metabolism-related genes.(d) Distribution of modeled genes and clinicopathologic features between crotonylation metabolism signatures.(e) Te risk curve of each sample reordered by crotonylation metabolism-related signature and the distribution of survival states.(f ) Survival analysis of the crotonylation metabolism signature.(g) ROC curves about crotonylation metabolism-related signature in 1-3 years.(h, i) Te results of univariate and multivariate Cox analysis of crotonylation metabolism-related signature.(j) Risk curve of each sample reordered by crotonylation metabolism signature and the distribution of survival states in GSE22541.(k) Survival analysis of the crotonylation metabolism signature in GSE22541.(l) ROC curves about crotonylation metabolism signature in 1-3 years in GSE22541.

Figure 4 :Figure 5 :
Figure 4: Correlation analysis between crotonylation metabolism signature and clinicopathological stages.(a-f ) Diferences in crotonylation metabolism signature among clinicopathological variables.(g-l) Te histogram showing the proportion of clinicopathological variables in crotonylation metabolism signature groups.(m-q) Survival analysis of palmitoylation metabolism-related signature in diferent clinicopathological variables.

Figure 5 :Figure 6 Figure 6 :
Figure 5: Identifcation of the immune characteristics of the crotonylation metabolism signature.(a) Heatmap representing expression of immune cells in crotonylation metabolism-related signature groups under various algorithms.(b) Correlation analysis of immune cells and crotonylation metabolism signature under multiple algorithms.(c-e) Expression diference of immunosuppressive cells in crotonylation metabolism-related signature groups.(f-h) Expression diference of tumor microenvironment scores in crotonylation metabolism-related signature groups.(i) Diference of immune function scores in crotonylation metabolism-related signature groups.(j) Diferential expression of crotonylation metabolism signature among immune subtypes.(k) Expression diference of immunosuppressive checkpoints in crotonylation metabolism-related signature groups.(l) Diferential expression of crotonylation metabolism signature in tracking tumor immunophenotypes.

Figure 8 :
Figure 8: Downregulation of KAT2A suppressed the progression of ccRCC in vitro.(a) mRNA diferential expression of KAT2A in ccRCC tissues and cell lines.(b) Te expression of KAT2A in A498 and 786-O cells was detected by RT-qPCR.(c) KAT2A knockdown suppressed ccRCC cell proliferation in A498 and 786-O cells.(d) KAT2A knockdown suppressed ccRCC cell metastasis in A498 and 786-O cells.(e) Wound healing tests demonstrated changes in ccRCC cell migration.