Integrative analysis of histone acetyltransferase KAT2A in human cancer

Abstract

The high incidence of mutations and the crucial roles of KAT2A in cancer development have received increased attention. Nevertheless, a systematic comparison of the heterogeneity and dynamics across different cancer types has not been conducted. Hence, a deep analysis using public databases was performed to clarify the contributions of KAT2A and its correlation with tumorigenesis. The raw data regarding KAT2A expression in cancer patients and healthy controls were obtained from The Cancer Genome Atlas (TCGA). Sexually dimorphic manner, genomic alterations, and expression pattern of KAT2A, as well as the association of the KAT2A with survival, were retrieved from UALCAN, cBioportal, and TISIDB databases. Additionally, the Protein-Protein Interaction (PPI) analysis was conducted using the STRING database. The human protein atlas was used to obtain the staining results of protein levels in cancer and normal samples. The correlation between KAT2A and its potential target drugs was determined using TISIDB and HISTome2. Compared to the normal tissues, CHOL and TGCT tumors presented significantly high KAT2A expression, which was positively correlated with BLCA, BRCA, CESC, CHOL, COAD, ESCA, HNSC, KICH, KIRP, LIHC, LUAD, LUSC, READ, STAD, and THCA. However, no significant difference was detected between normal and tumor tissues for the sex difference pattern of KAT2A expression. The PPI analysis indicated that TADA3, CCDC101, TRRAP, SUPT3H, MYC, TADA2A, and USP22 levels were positively correlated with KAT2A expression, while TADA2B and ATXN7 were negatively correlated. A positive link of KAT2A with cancer isotypes and significant connections of the KAT2A expression to poor overall and disease-free survival were also observed. Further validation was conducted using immunohistochemistry (IHC) staining, qPCR, and Western blot. Some potential HAT inhibitory drugs of KAT2A were also determined, but more work and clinical trials are required before their application.

1. Introduction

Historically, cancer remains the leading cause of death, posing a significant threat to human health and lifespan on a global scale. According to World Cancer Research Fund International data, there were an estimated 18.1 million cancer cases worldwide in 2020; breast and lung cancers were the most common, contributing 12.5 and 12.2% of the total number of new cases diagnosed [1]. Generally, the young population has a relatively lower cancer incidence than older people, and cancer incidence rises dramatically with age [2].

Lysine acetyltransferase 2A (KAT2A), or General control nonderepressible-5 (GCN5), is a histone acetyltransferase (HAT) that primarily functions as a transcriptional activator. Its complex belongs to the GNAT (Gcn5-related N-acetyltransferase) family of acetyltransferases and are transcription co-activators [3]. KAT2A also functions as a repressor of NF-$\kappa$-B by promoting ubiquitination of the NF-$\kappa$-B subunit RELA in a HAT-independent manner [4]. Additionally, as a subunit of the SAGA (Spt-Ada-Gcn5 acetyltransferase) and ATAC (Ada two A containing) complexes, KAT2A can acetylate the acetyl group from acetyl-CoA to the core histones [5]. The acetylation of histone H3K9/K14 at the promoter and upstream region of TNFRSF10A/B genes recruits the KAT2A complex and mediates the endoplasmic reticulum (ER) stress-triggered apoptosis in human lung cancer cells [6]. KAT2A is also required for the growth and differentiation of craniofacial cartilage and bone by regulating the acetylation of histone H3K9 in zebrafish and mice [7]. H3K79 is also reported as a target of KAT2A, with a maximum frequency around the transcription start sites of genes [8]. Moreover, histone variants are also substrates of KAT2A, which is recruited by the XPC (Xeroderma pigmentosum, complementation group C) complex at promoter sites and activates the expression of target genes [9, 10]. However, by mediating the acetylation of PLK4 (Polo-like kinase), negative KAT2A regulation also occurs on centrosome amplification [11].

Histone acetylation by HAT gives a specific tag for epigenetic transcription activation [8] and further destabilizes nucleosomes by promoting the dissociation of H2A-H2B dimers from nucleosomes for nucleosome assembly, DNA damage repair, and transcriptional regulation [12]. Accordingly, KAT2A also participates in the regulation of post-translational modifications by the acetylation of nonhistone proteins, such as CEBPB (CCAAT/enhancer binding protein beta), PLK4, and TBX5 (T-box transcription factor) [13]. Emerging evidence suggests that KAT2A is differentially expressed in metabolic disorders and is crucial in multiple human diseases, including cancers [14, 15]. KAT2A protein levels are significantly upregulated in urothelial cancer cell lines and human colon cancer tissues compared to normal controls [16, 17]. Recently, a research group in MD Anderson Cancer Center has identified KAT2A as a critical coactivator of cell-cycle gene expression driven by MYC overexpression, with significant implications for B-cell lymphomagenesis. The depletion of the GCN5 gene is notably associated with MYC-derived B-cell lymphoma, highlighting the potential therapeutic value of targeting KAT2A as a viable drug option in cancer treatment [18]. Hu et al. suggested that GCN5 and PCAF mediated acetylation of RAE-1 protein can activate NKG2D-dependent immune surveillance within HEK 293 cells and GCN5 and PCAF knockdown in osteosarcoma and lung cancer result in impaired induction of the natural killer group 2D (NKG2D) ligand Rae-1 [19, 20]. In head and neck squamous cell carcinoma, H3K27 acetylation, a GCN5 target, activates PD-L1 and galectin-9 transcription to evade tumor immunity [21].

Some studies have explored the role of KAT2A in malignancies. However, the effect of KAT2A expression and its association with tumorigenesis remains unknown. Cancer immunotherapy, especially immune checkpoint blocking (ICB), has emerged as a prominent approach in cancer treatment. The identification of immunotherapy targets can be achieved via pan-cancer expression analysis. Therefore, exploring the correlation between target genes, clinical prognosis, and associated signaling pathways using public databases is of great interest. Given the intricacy of tumorigenesis, investigating the expression of potential target genes and the underlying molecular mechanisms in various cancers is crucial. Therefore, our main objective is to offer a comprehensive understanding of KAT2A gene expression and its correlations across different tumors. Additionally, we aim to explore the potential therapeutic value of KAT2A as a promising drug target for these cancers.

2. Material and methods

2.1. Human tissue source and ethical statement

This study was approved by the clinical trial ethical committee of the Shanghai Pulmonary Hospital, Tongji University School of Medicine. After the approval of the ethical committee, all methods and information collection in this study were performed according to relevant guidelines and regulations. This research complies with all relevant ethical principles. Samples were sent to Tongji University School of Medicine for further pathological analysis. All patient samples were collected following local regulations and after obtaining the informed consent approved by the institutional review board (IRB). This commitment to ethical guidelines ensures that the research respects the rights and well-being of the study participants. Details regarding the human tissues collected for this study are presented in Table 1.

Table 1.

Summary of human tissues used in the study

Human tissues	Clinical diagnosis	Gender	Age	Study used for
Colon	Heart failure, asthma	Male	84	qPCR, IHC, and Western
Spinal cord	Diabetes	Male	79	qPCR, IHC, and Western
Kidney	Unknown	Female	85	qPCR, IHC, and Western
Liver	Unknown	Male	92	qPCR, IHC, and Western
Pancreas	Diabetes, asthma	Male	90	qPCR, IHC, and Western
Stomach	Diabetes	Female	82	qPCR, IHC, and Western
Normal	Unknown	Female	76	qPCR, IHC, and Western

2.2. Quantitative RT-PCR (qPCR)

RNA isolation (#74004, RNeasy Micro Kit, QIAGEN) and cDNA preparation (#QP057, SureScript™ First-Strand cDNA Synthesis Kit, GeneCopoeia) were conducted following the manufacturer’s instructions. The qPCR using PowerUp™ SYBR™ Green Master Mix (#A25742, Thermo Fisher, Carlsbad, CA, USA) was carried out on the Bio-Rad CFX96 system (#3600037, Bio-Rad Laboratories). Results were normalized by the GAPDH gene and the mRNA levels of KAT2A were calculated versus GAPDH (2${}^{-\mathrm{\Delta }\mathrm{\Delta }Ct}$). The primers used were: KAT2A Fwd (forward): GAGGTCATGCTGACCATCACTG, Rev (reverse): CAGTGAGTTGCCGATGACATGG; GAPDH Fwd: GTCTCCTCTGACTTCAACAGCG, Rev: ACCACCCTGTTGCTGTAGCCAA.

2.3. Western blot

Protein extraction, quantification, and Western blot analysis were conducted following the manufacturer’s instructions. Briefly, tissue protein was mechanically dissociated using Dounce Tissue Grinders (D8938, Sigma-Aldrich, USA) and disrupters (TissueLyser LT, Cat. No.: 85600, QIGEN) at 4${}^{\circ }$C. The homogenates were centrifuged at 15,000 rpm for 20 min at 4${}^{\circ }$C, and supernatants were removed and stored in aliquots at -80${}^{\circ }$C for downstream experiments. Total protein was quantified using the PierceTM BCA Protein Assay kit (#23225, Thermo Scientific, IL, USA). Equal amounts of total protein (50 $\mu$g) were loaded into each protein lane. After electrophoresis, the gel was electrophoretically transferred to a polyvinylidene fluoride (PVDF) membrane at a constant current of 150 mA. Western blot analyses were performed using antibodies against KAT2A (ab153903, Abcam, rabbit, 1:1000) and GAPDH (#8884S, Cell Signaling Technology, rabbit, 1:1500). Blots were visualized using an enhanced chemiluminescence assay kit (#32106, Thermo Scientific, IL). Quantity One®1-D analysis software (Bio-Rad Laboratories, Inc) calculated the densitometric analysis from three independent experiments.

2.4. Immunohistochemistry (IHC)

Samples were fixed in formalin and embedded in paraffin. The staining process was performed following the manufacturer’s instructions. Briefly, after antigen retrieval, the sections were treated with 3% H${}_2$O${}_2$ for 5 min and blocked with 3% BSA for 60 min at room temperature (RT). Sections were exposed to primary rabbit anti-KAT2A antibodies (1:300, ab217876, Abcam) overnight at 4${}^{\circ }$C, followed by secondary antibodies for 60 min at RT. Antibodies were labeled with horseradish peroxidase, and rabbit antibodies were labeled with alkaline phosphatase according to the instructions (ADI-950-100-0001, Enzo). Two investigators quantified the slides blindly.

2.5. Data source

UCSC Xena. The RNA sequencing (RNA-seq) expression profile and survival data regarding pan-cancer (33 cancer types) were downloaded from the University of California SANTA CRUZ database (UCSC Xena https://xenabrowser.net/) [22], as well as the clinical characteristics (e.g., sex, age, tumor stage, and survival time). Cancer names and abbreviations are presented in Table 2.

Table 2.

Name and abbreviation of the cancers analyzed in this study

Study abbreviation	Study name
LAML	Acute Myeloid Leukemia
ACC	Adrenocortical carcinoma
BLCA	Bladder Urothelial Carcinoma
LGG	Brain Lower Grade Glioma
BRCA	Breast invasive carcinoma
CESC	Cervical squamous cell carcinoma and endocervical adenocarcinoma
CHOL	Cholangiocarcinoma
LCML	Chronic Myelogenous Leukemia
COAD	Colon adenocarcinoma
CNTL	Controls
ESCA	Esophageal carcinoma
FPPP	FFPE Pilot Phase II
GBM	Glioblastoma multiforme
HNSC	Head and Neck squamous cell carcinoma
KICH	Kidney Chromophobe
KIRC	Kidney renal clear cell carcinoma
KIRP	Kidney renal papillary cell carcinoma
LIHC	Liver hepatocellular carcinoma
LUAD	Lung adenocarcinoma
LUSC	Lung squamous cell carcinoma
DLBC	Lymphoid Neoplasm Diffuse Large B-cell Lymphoma
MESO	Mesothelioma
MISC	Miscellaneous
OV	Ovarian serous cystadenocarcinoma
PAAD	Pancreatic adenocarcinoma
PCPG	Pheochromocytoma and Paraganglioma
PRAD	Prostate adenocarcinoma
READ	Rectum adenocarcinoma
SARC	Sarcoma
SKCM	Skin Cutaneous Melanoma
STAD	Stomach adenocarcinoma
TGCT	Testicular Germ Cell Tumors
THYM	Thymoma
THCA	Thyroid carcinoma
UCS	Uterine Carcinosarcoma
UCEC	Uterine Corpus Endometrial Carcinoma
UVM	Uveal Melanoma

Data source: https://gdc.cancer.gov/resources-tcga-users/tcga-code-tables/tcga-study- abbreviations.

TISIDB database. TISIDB (http://cis.hku.hk/TISIDB /index.php) is an online website focused on the interactions between cancer and the immune system and contains multiple heterogeneous data types [23]. This study used TISIDB to construct the heatmap of KAT2A expression in different immune subtypes, the stages of different cancers from The Cancer Genome Atlas (TCGA), and the drugs targeting KAT2A.

cBioPortal. The cBioPortal (https://www.cbioportal. org/) is a widely used open-access website containing over 5,000 tumor samples from 20 cancer studies [24, 25]. The summarized results of KAT2A in the ‘Cancer Types Summary’ module were obtained for this study, and detailed KAT2A mutated information is presented in the diagram.

UALCAN. The UALCAN (http://ualcan.path.uab. edu/index.html) database is an interactive web portal for in-depth analyses of TCGA gene expression data [26]. Herein, the differences in the KAT2A expression between the gender of patients and cancer stages of individuals were compared using UALCAN.

STRING. The STRING database (http://string-db. org) is an online server that focuses on protein-protein interactions (PPIs) and functional protein networks [27]. The STRING database was used to explore KAT2A interaction networks.

Human protein atlas (HPA). The HPA (https://www. protei natlas.org/) is a database of proteins in human organs, tissues, and cells based on multiple omics approaches [28, 29].

HISTome2. The HISTome Infobase (http://www.actrec.gov.in/histome2/index.php) has information on histone proteins, modifiers for multiple organisms with drugs [30, 31], and was created by researchers from Advanced Center for Treatment, Research and Education in Cancer, Navi Mumbai. Potential HAT inhibitory drugs of KAT2A were downloaded from HISTome2.

2.6. Statistical analysis

Data from individual experiments are presented as means $\pm$ S.D., and differences were assessed by Student’s t-test, one-way or two-way analysis of variance (ANOVA) with Tukey post hoc test for multiple comparisons (GraphPad Prism Software Inc, San Diego, CA, USA). The Pearson correlation coefficient was used for pan-cancer and correlation analysis. R (version 4.0.2) was used for statistical analyses and image plots. Statistical significance was defined as 0.05, 0.01, 0.001.

3. Results

3.1. Transcriptional level analysis of KAT2A among human cancers

To determine the KAT2A gene expression in different cancers, we analyzed 11,014 samples (9,675 primary tumors, 719 solid tissue normal, 394 metastatic tumors, 173 primary blood-derived cancers, 42 recurrent tumors, 10 additional new primary tumors, and one additional metastatic tumor) spanning 32 different human tumors (Tables 2 and 3). We explored KAT2A mRNA levels using the UCSC Xena database (http://xena.ucsc.edu/). KAT2A mRNA levels varied greatly among these cancer samples. CHOL and TGCT exhibited the highest KAT2A expression, while KICH presented a relatively low expression (Fig. 1A and B). Next, to examine the distribution of KAT2A transcripts in different sample types, we compared the expression of KAT2A in primary tumors, solid tissue normal, and metastatic groups. Using the available clinical information, we compared the primary tumors with their corresponding solid tissue normals in each of the 32 cancers. Since the number of normal samples was limited for some cancer types, we filtered the comparisons of differentially expressed genes (DEGs) using a cutoff value of $N>$ 50 and 0.000001 in the Student’s $t$-test. BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA presented significantly different KAT2A expressions from solid tissue normal controls (Fig. 1C and D). Further, we selected BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA and compared KAT2A levels for each sample using a Jitter plot (Fig. 1D-J). These results indicated that KAT2A expression significantly increased in multiple cancer types, including BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA, compared to normal tissues.

Table 3.

Sample numbers of all cancer types

Sample types	Sample number
Additional – New Primary	10
Metastatic	394
Primary Tumor	9675
Solid Tissue Normal	719
Additional Metastatic	1
Primary Blood-Derived Cancer – Peripheral Blood	173
Recurrent Tumor	42

Figure 1.

Pan-cancer analysis of KAT2A gene expression. A. KAT2A expression in different cancer types from TCGA database. B. Radar map of KAT2A expression. C. KAT2A expression in various cancers compared to normal tissues. D–J. KAT2A expression decreases in BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA. X-axis, sample types. Y-axis, transcript per million [log${}_2$(TPM $+$ 1)]. 0.05, 0.01, and 0.001.

3.2. KAT2A gene expression showed gender bias across different cancers

Cancer incidence has a sexually dimorphic pattern, making the underlying mechanisms a crucial issue in cancer research and the development of precision medicine [32]. This sexual dimorphism might result from biological sex differences (e.g., hormone discrepancies and/or chromosomal homo/heterogeneity) [33, 34], as well as lifestyle and habit, which are also connected to the incidence of cancers [35]. Therefore, precision medicine based on gender is an important modality [36, 37]. Furthermore, the National Institutes of Health (NIH) emphasizes studying male and female vertebrate animals and humans. In this study, we investigated whether KAT2A expression has a sex-specific pattern. First, we conducted a side-by-side analysis of the KAT2A mRNA levels in males and females using samples of additional new primary tumor, additional metastatic tumor, metastatic tumor, primary blood-derived cancer, primary tumor, recurrent tumor, and solid tissue normal. However, we did not detect significant differences between males and females (Fig. 2A). Then, we evaluated the sex difference expression pattern of KAT2A in normal (Fig. 2B) and tumor tissues (Fig. 2C) separately and did not detect significant differences. To gain further insights into KAT2A expression, we selected the top 5 cancers according to the $p$-value (READ, $p=$ 0.521; COAD, $p=$ 0.528; ESCA, $p=$ 0.540; MESO, $p=$ 0.569; and THYM, $p=$ 0.573) to confirm the accuracy of our analysis and compared KAT2A expression in males, females, and normal tissues using data from another database (http://ualcan.path.uab.edu/analysis.html). KAT2A expression increased in both males and females compared to normal tissues for READ (Normal-vs-Male, $p=$ 1.624E-12; Normal-vs-Female, $p=$ 1.624E-12) (Fig. 2D), COAD (Normal-vs-Male, $p=$ 1.624E-12; Normal-vs-Female, $p=$ 1.624E-12) (Fig. 2E), and ESCA (Normal-vs-Male, $p=$ 1. 1.749E-12; Normal-vs-Female, $p=$ 1.00729E-12) (Fig. 2F). However, KAT2A expression did not differ between males and females for READ ($p=$ 0.856; Fig. 2D), COAD ($p=$ 0.664; Fig. 2E), ESCA ($p=$ 0.947; Fig. 2F), MESO ($p=$ 0.232; Fig. 2G), and THYM ($p=$ 0.509; Fig. 2H). The results using data from UCSC Xena were consistent with the UALCAN database, despite the different sample numbers due to the varying sample resources. Hence, these results indicated that KAT2A gene expression did not have a sexually dimorphic pattern in normal and cancer samples.

Figure 2.

KAT2A gene expression gender bias across different cancers. A. Expression profile of the KAT2A gene between males and females based on sample types. B–C. Sex difference expression pattern of KAT2A in normal (B) and tumor tissues (C). D–H. KAT2A gene expression in READ ($p=$ 0.521), COAD ($p=$ 0.528), ESCA ($p=$ 0.540), MESO ($p=$ 0.569), and THYM ($p=$ 0.573) dependent on the patient’s gender. X-axis, sample type and numbers. Y-axis, transcript per million [log${}_2$(TPM $+$ 1)]. 0.0001 compared to the normal group.

3.3. Relationship of KAT2A expression and cancer pathological stages

To assess the clinical relevance of KAT2A expression in pan-cancer, we investigated its correlation with cancer pathological stages. KAT2A expression was significantly correlated with pathological stages for BLCA (Fig. 3A), BRCA (Fig. 3B), CESC (Fig. 3C), CHOL (Fig. 3D), COAD (Fig. 3E), ESCA (Fig. 3F), HNSC (Fig. 3J), KICH (Fig. 3H), KIRP (Fig. 3I), LIHC (Fig. 3G), LUAD (Fig. 3K), LUSC (Fig. 3L), READ (Fig. 3M), STAD (Fig. 3N), and THCA (Fig. 3O) ( 0.05 for Normal vs. all stages). However, KAT2A expression did not differ among stages in most tumors except for BLCA (Stage 2 vs. Stage 4, $p=$ 0.0353) (Fig. 3B), HNSC (Stage 1 vs. Stage 2, $p=$ 0.00464; Stage 1 vs. Stage 3, $p=$ 0.000199; Stage 1 vs. Stage 4, $p=$ 1. 556E-06) (Fig. 3J), KICH (Stage 1 vs. Stage 2, $p=$ 0.00200; Stage 2 vs. Stage 3, $p=$ 1. 921E-03) (Fig. 3H), KIRP (Stage1 vs. Stage 3, $p=$ 0.00458), LIHC (Stage 1 vs. S tage3, $p=$ 0.00261) (Fig. 3I), LUSC (Stage 1 vs. Stage 2, $p=$ 1. 284E-03) (Fig. 3L), and READ (Stage 2 vs. Stage 4, $p=$ 0.0467; Stage 3 vs. Stage 4, $p=$ 4.061E-03) (Fig. 3M). Therefore, the expression of KAT2A was significantly associated with tumor stage in BLCA, HNSC, KICH, KIRP, LIHC, LUSC, and READ cancer samples.

Figure 3.

Expression of KAT2A gene based on individual pathological stages. A–O. KAT2A expression in different pathological stages (stages I-IV) of BLCA, BRCA, CESC, CHOL, COAD, ESCA, LIHC, KICH, KIRP, HNSC, LUAD, LUSC, READ, STAD, and THCA based on the UALCAN database. 0.05, 0.01, 0.001, 0.0001 vs. Normal group. 0.05, 0.01, 0,001, and 0.0001 vs. Stage I. † 0.05, †† 0.01, ††† 0.001, and †††† 0.0001 vs. Stage II. ‡ 0.05, ‡‡ 0.01, ‡‡‡ 0.001, and ‡‡‡‡ 0.0001 vs. Stage III.

3.4. PPI correlation analysis of KAT2A

KAT2A is a subunit of the HAT module, which belongs to two distinct macromolecular complexes: the Human SAGA complex [38] and ATAC [39]. Thus, KAT2A is involved in a network that correlates with pathological tumor development. Thus, we evaluated the connections among the genes in this network using the STRING online database. The PPI network presented 10 nodes (TADA3, CCDC101, TRRAP, SUPT3H, MYC, TADA2A, USP22, TADA2B, ATXN7, and TAF10) involved in the functional interactions with KAT2A (Fig. 4A). Moreover, eight genes – USP22 (Fig. 4B), CCDC101 (Fig. 4C), MYC (Fig. 4D), SUPT3H (Fig. 4E), TADA2A (Fig. 4F), TADA3 (Fig. 4G), TRRAP (Fig. 4I), and TAF10 (Fig. 4H) were positively correlated with KAT2A. The remaining two genes, TADA2B (Fig. 4J) and ATXN7 (Fig. 4K) were negatively correlated with KAT2A. The function of these KAT2A-related proteins is summarized in Table 4.

Figure 4.

KAT2A gene interaction networks and correlation. A. Protein–protein interaction (PPI) network of the KAT2A-interacted proteins from the STRING website. B–K. Correlation between the expression of KAT2A and its related genes including USP22, CCDC101, MYC, SUPT3H, TADA2A, TADA3, TAF10, TRRAP, TADA2B, and ATXN7.

Table 4.

Role of KAT2A-associated proteins in cancer development

KAT2A-associated proteins	Roles in cancer development	Score
USP22	Recruited to specific gene promoters by activators such as MYC, where it is required for transcription.	0.999
TRRAP	Required for p53/TP53-, E2F1- and E2F4-mediated transcription activation.	0.999
MYC	Myc proto-oncogene protein; Binds to the VEGFA promoter, promoting VEGFA production and subsequent sprouting angiogenesis.	0.999
TADA2A	Can promote TP53/p53 ’Lys-321’ acetylation, reducing TP53 stability and transcriptional activity.	0.999
SUPT3H	Transcription initiation protein SPT3 homolog.	0.999
TAF10	Plays a central role in mediating promoter responses to various activators and repressors.	0.999
CCDC101(SGF29) ATXN7	Involved in the response to endoplasmic reticulum (ER) stress. Mediates the interaction of the STAGA complex with the CRX and is involved in CRX-dependent gene activation.	0.998 0.998
TADA3	Coactivator for p53/TP53-dependent transcriptional activation.	0.998
TADA2B	Coactivates PAX5-dependent transcription with either SMARCA4 or GCN5L2.	0.997

3.5. Mutation of KAT2A gene across TCGA

Genomic mutation is closely associated with tumorigenesis [40, 41]. Thus, to identify mutation sites in KAT2A genes, we assessed 10,967 samples from 10,953 patients. As the lollipop plot depicted (Fig. 5A, post-translational modification (PTM) sites were frequently found in the p300/CBP-associated factor (PCAF) domain (86-337), Acetyltransferase domain (547-628), and bromodomain (738-818). The PCAF, acetyltransferase, and bromodomain in KAT2A are highly conserved across species [7, 42]. The types and sites of KAT2A genetic alterations are presented in Fig. 5A. We detected eight phosphorylation sites, six acetylation sites, one ubiquitination site, two methylation sites, and three SUMOylation sites for all 837 amino acids. The mutation sites contained 114 missenses, 16 truncating, five inframe, and four fusion mutations; R783Q was the most frequent (Fig. 5A).

Figure 5.

KAT2A gene mutation across TCGA. A. Mutation site of KAT2A in different cancer types across protein domains. B. The alteration frequency of KAT2A in pan-cancer datasets according to the cBioPortal database. C. Mutation count of KAT2A across TCGA.

Next, we conducted a comparative analysis to determine the genetic alteration recurrence of the KAT2A gene in cancers. Then, we checked the genetic alterations of the KAT2A gene in cancer patients using the cBioPortal database. The frequency of KAT2A alteration significantly fluctuated across different cancers. The genetic alteration profiling of KAT2A showed that its mutation was one of the most important single factors for alteration in UCEC and SKCM. Also, we found the highest amplification frequencies of KAT2A in ESCA, STAD, PAAD, MESO, and PCPD (Fig. 5B).

Additionally, we analyzed the copy number alterations of the KAT2A gene among these cancers. We determined the highest amplification and the lowest deep deletion levels based on the batch normalized from Illumina HiSeq analysis, indicating a relatively rare frequency (Fig. 5C). Hence, various genetic alterations were implicated in KAT2A and might contribute to cancer development.

3.6. Immune correlation analysis of KAT2A in pan-cancer

As a significant part of the complex microenvironment, the KAT2A-contained SAGA complex is significantly connected to the development and progression of various cancers [43, 44]. The quantity and activity status of tumor-infiltrating lymphocytes are important predictive criteria for cancer survival times [45, 46]. Cytotoxic CD8${}^{+}$ T cells (CTLs) are crucial in cancer initiation, progression, and metastasis [47, 48]. Herein, we explored the correlation between immune cell infiltration and KAT2A expression in various cancers based on CD8${}^{+}$ T cell levels using the TIMER database. We first compared KAT2A expression with the abundance of immunomodulators (Fig. 6A). KAT2A expression was significantly positively correlated with the infiltration of CD56-expressing cells (both bright and dim) in BLCA, CHOL, KIKC, KIRC, PAAD, PCPG, PRAD, READ, STAD, TGCT, and THCA. Furthermore, KAT2A expression was also negatively correlated with other infiltrated immune cells, such as cytotoxic CD8${}^{+}$ T cells (Fig. 6A). We selected BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA to perform the correlation analysis between KAT2A expression and CD8 T cells abundances. KAT2A expression was negatively correlated with the abundances of active CD8 T cells in BRCA (rho $=$$-$0.025), LIHC (rho $=$$-$0.059), LUAD (rho $=$$-$0.05), and LUSC (rho $=$$-$0.152), and positively correlated with active CD8${}^{+}$ T cell abundances in KIRC (rho $=$ 0.043), PRAD (rho $=$ 0.035), and THCA (rho $=$ 0.108) (Fig. 6B-H).

Figure 6.

Immune correlation analysis of KAT2A across TCGA. A. Correlation of KAT2A expression with immune infiltrating cells in the TISIDB database. B–H. Correlation of KAT2A expression in BRCA, KIRC, LIHC, LUAD, LUSC, PRAD, and THCA with infiltrating levels of act_CD8+ T cell. 0.05, 0.01, and 0.001.

3.7. Associations between KAT2A expression and immune subtypes in pan-cancer

Our analysis using TCGA data showed that compared to the normal control tissues, BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA tissues have significantly elevated KAT2A expression and that KAT2A expression is correlated with the infiltration of CD8 T cell abundances (Fig. 6A). Additionally, we explored the associations of KAT2A expression across immune and molecular subtypes (Fig. 7A). The top 5 KAT2A expression was PRAD, TGCT, STAD, BRCA, and LIHC. Then, we focused on these five cancer and assessed the expression of six immune and molecular subtypes. The main clinical and molecular characteristics were depicted as C1 (wound healing); C2 (IFN-gamma dominant); C3 (inflammatory); C4 (lymphocyte depleted); C5 (immunologically quiet); C6 (TGF-b dominant). KAT2A gene expression was similar in BRCA (Fig. 7B), PRAD (Fig. 7D), and STAD (Fig. 7E) within five immune and molecular subtypes. KAT2A expression decreased in C6 (LIHC) and C3/C4 (TGCT) in LIHC (Fig. 7C) and TGCT (Fig. 7F).

Figure 7.

Associations between KAT2A expression and immune subtypes across human cancers. A. Associations of KAT2A expression across immune cells in the TISIDB database. B–F. Correlation of KAT2A expression in BRCA, LIHC, PRAD, STAD, and TGCT within immune subtypes. C1 (wound healing); C2 (IFN-gamma dominant); C3 (inflammatory); C4 (lymphocyte depleted); C5 (immunologically quiet); C6 (TGF-b dominant). 0.05, 0.01, 0.001, 0.0001 vs. C1 group. # 0.05, ## 0.01, ### 0,001, and #### 0.0001 vs. C2 group. † 0.05, †† 0.01, ††† 0.001, and †††† 0.0001 vs. C3 group. ‡ 0.05, ‡‡ 0.01, ‡‡‡ 0.001, and ‡‡‡‡ 0.0001 vs. C4 group.

3.8. Survival prognosis analysis of the KAT2A gene

Furthermore, we assessed the associations of overall survival with KAT2A expression across human cancers. We determined the relationship between longer, shorter, and NS (no significant) overall survival rates with KAT2A expression among 30 cancer (Fig. 8A). Shorter overall survival rate was significantly correlated with elevated KAT2A expression in KIRC. Low KAT2A expression was significantly correlated with a longer overall survival rate in PAAD (Fig. 8A). We also analyzed the connections between overall survival rate and KAT2A expression in KIRC, PAAD, STAD, and LGG using Kaplan-Meier curves. A higher KAT2A expression indicates a shorter survival rate within 12 years ($p=$ 6.38E-11) in KIRC (Fig. 8B), while a higher KAT2A expression indicates longer survival in PAAD ($p=$ 0.0195) (Fig. 8C). However, KAT2A expression was not associated with the overall survival rate in STAD and LGG (Fig. 8D and E). These results indicated suggested that KAT2A expression was a great factor affecting the survival of KIRC and PAAD.

Figure 8.

KAT2A gene expression level and overall survival. A. Associations of overall survival with KAT2A expression across human cancers. B–E. Kaplan–Meier survival curves comparing high and low KAT2A expression in KIRC, PAAD, STAD, and LGG. High KAT2A expression was related to unfavorable OS in KIRC and better survival in PAAD, STAD, and LGG. Thus, KIRC patients with high KAT2A expression have a risk factor affecting survival.

3.9. KAT2A expression in human normal and tumor tissues

Dysregulation of transcriptomes is closely associated with cancer, leading to alterations in specific genes or pathways that contribute to uncontrolled tumor growth [49]. Over 500 genes have been identified as strongly implicated in transforming normal cells into cancer cells [50]. However, tracking total mRNA levels is insufficient for the major feature of KAT2A expression and cancers. Translation and (or) translocation of mRNAs encoding proteins that govern cancer cell plasticity play a central role in tumor cell differentiation [51, 52]. Thus, to provide a comprehensive view of KAT2A expression and cancers, we examined the KAT2A protein and mRNA level patterns in human cancer tissues. KAT2A protein was mainly located intracellularly and expressed with low tissue specificity. To validate the KAT2A expression in these organs, we used colon, spinal cord, kidney, liver, pancreas, and stomach tumors and normal human tissue sections to analyze pathological KAT2A levels with IHC staining. In the tumor cores, colon, spinal cord, kidney, liver, pancreas, and stomach cancer cells and tumor stroma were positive for KAT2A (Fig. 9A, lower panel). Different tumor organs demonstrated a range of KAT2A intensity. The normal human colon, spinal cord, kidney, liver, pancreas, and stomach organs were also positive for KAT2A (Fig. 9A, upper panel). Next, we evaluated KAT2A levels among these organs. KAT2A mRNA levels greatly increased in tumor organs compared to normal ones by qPCR (Fig. 9B), 2-4 folds compared to their respective control tissues. Finally, we performed a Western blot assay with KAT2A and GAPDH antibodies and observed higher KAT2A protein levels in tumors than their respective control organs (Fig. 9C). Accordingly, the quantification data showed a similar higher KAT2A protein level using the GAPDH housekeeping gene for normalization (Fig. 9D). Therefore, KAT2A expression in tumors presented a comprehensive range compared to normal samples, consistent with the database analysis (Fig. 1).

Figure 9.

KAT2A expression in normal and cancer tissues. A. Representative immunohistochemistry (IHC) staining of KAT2A in human normal and tumor colon, spinal cord, kidney, liver, pancreas, and stomach tissues with KAT2A antibody. Scale bar $=$ 100 $\mu$m. B. KAT2A gene mRNA levels by RT-PCR in normal and tumor tissues. C. Western blots of KAT2A and GAPDH protein levels in human colon, spinal cord, kidney, liver, pancreas, and stomach tissues. GAPDH was used as a loading control. D. Optical density of KAT2A bands normalized to the loading control. Data are means from three to four independent experiments. $n=$ 3, 0.05; 0.01; 0.001.

3.10. Potential anticancer drugs of KAT2A

Pathologically, dysregulation of epigenetic events can lead to cancer. Consequently, identifying drugs that can modify these epigenetic changes holds great clinical potential. As described, KAT2A-mediated lysine acetylation is a reversible post-translational modification involved in tumor genesis [53]. Small molecules or inhibitors that can modulate the HAT or its competence, such as HDACs (histone deacetylases), can be potential therapeutics for various diseases [54, 55]. Hence, to explore the potential mechanisms in which KAT2A participates in carcinogenesis, we used the TISIDB online tool to predict the drugs targeting KAT2A collected from the DrugBank database (Fig. 10A. DB01992 has a direct interaction with KAT2A and is targeted by other modules. DB01992 is a small molecule of Coenzyme A (Fig. 10B) known for its role in the synthesis and oxidation of fatty acids and pyruvate in the citric acid cycle. Furthermore, we searched the HISTome2 database for more information on HAT inhibitors. Gallic acid, Garcinol, Anacardic acid, Procyanidin, MB-3, CTK7A, Plumbagin, and Embelin were predicted to interact with KAT2A directly (Fig. 10C-J) [56, 57]. Overall, these results might accelerate drug understanding and future development.

Figure 10.

Drug targeting KAT2A in the DrugBank database. Prediction of drugs targeting KAT2A in the DrugBank database. B. Structure of Coenzyme A DB01992. C–J. Structures of HAT inhibitors: Gallic acid (C), Garcinol (D), Anacardic acid (E), Procyanidin (F), MB-3 (G), CTK7A (H), Plumbagin (I), and Embelin (J) from the HISTome2 database.

4. Discussion

Aberrant epigenetic modifications are closely associated with the risk of numerous human cancers. Changes in the epigenome have significant consequences on the regulation of tumorigenesis, invasiveness, and metastasis. Emerging evidence suggests that KAT2A is differentially expressed in metabolic disorders and is critical in multiple human cancers. However, the mechanism by which the histone-modifying complex rewrites and influences global epigenome levels in pan-cancer remains incomplete.

Herein, we conducted a pan-cancer analysis of KAT2A expression profiles encompassing 33 tumor types. We explored the role of KAT2A, including its expression profile, sexually dimorphic characteristics, correlation with pathological stages, overall survival analysis, immune landscape, and potential drugs. Notably, KAT2A expression was upregulated in seven cancer types: BRCA, KIRC, LIHC, LUAC, LUSC, PRAD, and THCA (Fig. 1). However, we did not found sex difference patterns in normal or cancer samples, indicating that sexually dimorphic patterns in most cancer types are not caused by KAT2A (Fig. 2). Since high KAT2A levels were correlated with elevated tumor risk, we evaluated whether KAT2A expression was correlated with poor patient prognosis in different cancer stages. KAT2A expression was significantly associated with tumor stage in BLCA, HNSC, KICH, KIRP, LIHC, LUSC, and READ cancer samples (Fig. 3), which is partially consistent with the conclusion from Fig. 1; for example, LIHC and LUSC showed increased KAT2A levels, KAT2A upregulation was positively correlated with unfavorable prognosis, and KAT2A was correlated with cancer infiltration levels in LIHC and LUSC.

Genes seldom operate in isolation within cellular processes, while KAT2A is a subunit of two distinct macromolecular complexes (SAGA and ATAC) that drive histone acetylation in the promoter region of target genes. To understand the properties and functions of the KAT2A gene, we used the STRING database to estimate regulatory relationships between KAT2A and its interacting partners based on Pearson’s correlation coefficient. KAT2A was positively correlated with TADA3, CCDC101, TRRAP, SUPT3H, MYC, TADA2A, and USP22, while negatively correlated with TADA2B and ATXN7 (Fig. 4). Additionally, we explored KAT2A gene alterations that are associated with various genomic mutations across cancers. Notably, mutations were among the most significant single factors for alteration in UCEC and SKCM. Also, KAT2A amplification frequencies were elevated in ESCA, STAD, PAAD, MESO, and PCPD (Fig. 5), indicating that various genetic alterations were assembled in KAT2A that led to cancer development. One relevant pathway of KAT2A gene rewiring and epigenetic landscape is histone acetylation, which plays a critical role in regulating chromatin structure and participating in specific gene regulation, affecting the development and progression of diverse cancers. We also investigated the correlation between KAT2A and immune infiltration, as well as immune checkpoints, using the TIMER database. KAT2A expression was negatively correlated with the abundance of active CD8${}^{+}$ T cells in BRCA, LIHC, LUAD, and LUSC while positively correlated in KIRC, PRAD, and THCA (Fig. 6). Furthermore, KAT2A gene expression had a considerable positive link to the immune and molecular subtypes in these cancers (Fig. 7). To comprehend the factors influencing survival rates, we used Kaplan-Meier curve analysis to examine the correlation between KAT2A expression and survival outcomes across various human cancers. The KAT2Aexpression level was a great factor affecting cancer survival, depending on tumor types (Fig. 8). We also validated KAT2A expression using IHC staining data obtained from human organ tissues, which was consistent with the public database analysis (Fig. 9). Finally, we analyzed the correlation between KAT2A and potential target drugs (Fig. 10).

Generally, KAT2A contributes to cancer development via transcriptional activity control. Namely, KAT2A regulates E2F and MYC transcriptional targets through histone acetylation-mediated co-activation. Enhanced KAT2A is associated with a bad prognosis in breast cancer [58, 59], Non-Small Cell Lung Carcinoma [60, 61], and Colon [15, 62]. Recently, the nonhistone substrates of KAT2A have been reported in cancer biology, as well as their potential roles in the development and progression of cancer [63, 64]. KAT2A can regulate the activity of Peroxisome Proliferator-Activated Receptor Gamma-Coactivator-1$\alpha$ and B via acetylation in AML (Acute Myeloid Leukemia) [65]. Furthermore, the key regulator of centrosome duplication, polo-like kinase 4 (PLK4), can also be acetylated by KAT2A in HeLa cell lines, further contributing to tumor progression [11, 66, 67, 68]. Elevated KAT2A expression was observed in patients with prostate cancer who exhibited high-grade disease or experienced biochemical recurrence after radical prostatectomy. Higher KAT2A expression was also associated with poorer clinical survival outcomes in these patients [69]. Our analysis supports that KAT2A participates in cancer biology with oncogene-like and tumor-suppressor roles. KAT2A overexpression contributes to the dysfunction of histone acetylation in cancer and works as a potential drug target.

However, although we investigated and integrated KAT2A’s role in these cancers with different databases and bioinformatics analyses, our study also has some limitations. First, it is a reanalysis study with the public data; only modern bioinformatics methods were employed to explore the relations. We have few original data to reproduce the results with the new criteria and algorithm, and further validation might support our conclusions. Second, due to the small number of samples, we could not distinguish KAT2A expression patterns between groups for the human sample’s validation data. Thus, this result is not comprehensive without sufficient sample size and clarification by pharmacodynamic and molecular biological experiments data. Moreover, KAT2A-mediated histone acetylation is only one part of the epigenetic modification. The intracellular signal transduction and regulatory factor activity are complex and fluctuate irregularly, and it was still unclear how KAT2A affected clinical survival via the immune pathway.

5. Conclusion

In summary, we explored the correlation and the prognostic significance of KAT2A expression in diverse human cancers. KAT2A was a predictive cancer factor upregulated in BRCA, KIRC, LIHC, LUAD, LUSC, PRAD, and THCA and correlated with prognosis in KIRC, PAAD, STAD, and LGG. Therefore, we shed some light on a better understanding of the underlying molecular mechanisms and crucial molecular players of KAT2A and provide a new viewpoint for researchers to target the causes of cancers.

Abbreviation list

KAT2A:	Lysine acetyltransferase 2A
GCN5:	General control nonderepressible-5
HAT:	Histone acetyltransferase
GNAT:	Gcn5-related N-acetyltransferase
SAGA:	Spt-Ada-Gcn5 acetyltransferase
ATAC:	Ada two A containing
XPC:	Xeroderma pigmentosum, complementation group C
PLK4:	Polo-like kinase 4
CEBPB:	CCAAT/enhancer binding protein beta
TBX5:	T-box transcription factor
TADA3:	Transcriptional adapter 3
CCDC101:	Coiled-coil domain containing 101 (SGF29)
TRRAP:	Transformation/transcription domain-associated protein
SUPT3H:	Transcription initiation protein SPT3 homolog
MYC:	Myc proto-oncogene protein
TADA2A:	Transcriptional adapter 2-alpha
USP22:	Ubiquitin carboxyl-terminal hydrolase 22

TADA2B:	Transcriptional adapter 2-beta
ATXN7:	Ataxin-7
TAF10:	Transcription initiation factor TFIID subunit 10
PTM:	Post-translational modification
HDACs:	Histone deacetylases

Ethics approval and consent to participate

This study was approved by the clinical trial ethical committee of the Shanghai Pulmonary Hospital, Tongji University School of Medicine. After approval of the ethical committee, all methods and information collection in this study were performed according to the relevant guidelines and regulations.

Consent for publication

Not applicable.

Availability of data and materials

The datasets used and/or analyzed during the present study are available from the authors at reasonable request. The code used throughout this study is available upon reasonable request from the corresponding authors.

The datasets presented in this study can be found in the following databases: UCSC Xena (https://xenabro wser.net/), TISIDB (http://cis.hku.hk/TISIDB/index. php), cBioPortal (https://www.cbioportal.org/), STRING (http://string-db.org), and HISTome 2 (http://www.actrec.gov.in/histome2/index.php).

Competing interests

The authors declare that they have no competing interests.

Funding

None.

Authors’ contributions

Conception: Lu-zong Yang and Ji Liu.

Interpretation or analysis of data: Hua Li, Chun Li, and Ji Liu.

Preparation of the manuscript: Chun Li, Ji Liu, and Hua Li.

Revision for important intellectual content: Ji Liu and Hua Li.

Supervision: Ji Liu.

All authors read and approved the final version of the manuscript.