Pan-cancer analysis of the prognostic and immunotherapeutic values of exostosin-1

doi:10.21203/rs.3.rs-2830689/v1

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Pan-cancer analysis of the prognostic and immunotherapeutic values of exostosin-1

https://doi.org/10.21203/rs.3.rs-2830689/v1

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Background

Exostosin-1 (EXT1) is associated with the spread and metastasis of cancer cells. In this study, we investigate the prognostic value and immunological relevance of EXT1 in various cancers.

Methods

The expression profiles and clinical data of 33 different cancers were collected. The differences of EXT1 expression between tumor and normal tissues were analyzed using a t-test and paired t-test. Univariate Cox regression analysis was performed, and survival curves were plotted to evaluate the prognostic value of EXT1. The molecular mechanisms of EXT1 were determined, and a drug sensitivity analysis was conducted. Finally, the expression and function of EXT1 was verified in endocervical adenocarcinoma (CESC) cells.

Results

The Cancer Genome Atlas and Genotype-Tissue Expression databases showed that EXT1 expression was higher in CESC, cholangiocarcinoma, head and neck squamous cell carcinoma, esophageal carcinoma, kidney renal papillary cell carcinoma, liver hepatocellular carcinoma, lung squamous cell carcinoma, and stomach adenocarcinoma specimens than in normal specimens. Additionally, EXT1 expression correlated with survival time, including overall survival, disease-specific survival, disease-free interval, and progression-free interval, in multiple cancers. Functional enrichment analysis revealed that EXT1 is associated with immunity-, tumorigenesis-, and development-related pathways. Immunocorrelation analysis showed that EXT1 is related to the immune response, tumor microenvironment, and immunotherapeutic response in various cancers. Drug sensitivity analysis revealed that 152 drugs exhibited remarkably different sensitivities between the high- and low-EXT1 expression groups. Cell experiments showed that EXT1 expression was related to the proliferation, migration, and invasion of CESC tumor cells.

Conclusion

EXT1 is a potential target gene for immune infiltration and has prognostic value in multiple cancers; thus, it may provide new insights into cancer treatment.

Exostosin-1

pan-cancer

prognostic value

biomarkers

immune microenvironment

Cancer is one of the leading causes of morbidity and mortality worldwide. According to the World Cancer Report 2014 by the World Health Organization, 8.2 million cancer-related deaths occurred worldwide in 2012, with this number expected to increase to 22 million by 2035 [1]. The morbidity and mortality rates of cancer have been increasing annually. Consequently, researchers worldwide are committed to discovering more effective, rapid methods to diagnose and treat cancer. Currently, the most traditional cancer treatments include chemotherapy, radiotherapy, and surgery; however, patients often experience unsatisfactory therapeutic outcomes and severe side effects. Thus, it is imperative to identify tumor-related diagnostic markers and drug targets for the early diagnosis of cancerous lesions.

The exostosin (EXT) family of glycosyltransferases, including EXT1 and EXT2, encode exogenous phytate glycosyltransferases that exhibit tumor-suppressive properties [2, 3]. EXT1 is located on chromosome 8 and encodes an endoplasmic reticulum-resident type II transmembrane glycosyltransferase, which is involved in the chain elongation step of heparan sulfate biosynthesis. Mutations in EXT1 cause type 1 hereditary exostosis multiplex, an autosomal dominant disorder characterized by benign bone tumors in areas of active bone growth [4, 5], highlighting its role as a tumor suppressor. Although EXT1 is a well-known tumor suppressor gene, its elevated expression has been observed in human cholangiocarcinoma (CHOL) plasma [6]. Furthermore, heparan sulfate chains are critical in the growth of multiple myeloma cells [7]. In vivo knockdown of EXT1 inhibits multiple myeloma cell growth, suggesting that EXT1 plays a part in carcinogenesis [8]. Additionally, the inhibition of EXT1 expression suppresses epithelial–mesenchymal transition markers and migratory behavior [9]. EXT1 promoter hypermethylation has been detected in a variety of cancers, including non-melanoma skin cancer and leukemia [10]. However, this has been demonstrated in only a small number of tumor types, and no systematic pan-cancer analysis of the function of EXT1 has been conducted.

Herein, we executed a comprehensive pan-cancer analysis of the EXT1 function in 33 cancer types using transcriptomic data from The Cancer Genome Atlas (TCGA) database to elucidate its expression, mutation status, association with features of interest, and correlation with the immune microenvironment. Collectively, our results show that EXT1 is a potential target for cancer treatment.

Data collection

Expression profiles and clinical information for 33 cancers from TCGA, Genotype Tissue Expression (GTEx), and Cancer Cell Line Encyclopedia (CCLE) databases were obtained from UCSC Xena (https://xenabrowser.net).

Differential expression of EXT1

Differences in EXT1 expression between tumor and normal tissues were determined via t-tests and paired t-tests. Differences in EXT1 expression among tumor stages I, II, III, and IV and between tissues and cells were assessed established on the expression data gained from TCGA, GTEx, and CCLE databases.

Prognostic value of EXT1

The connection between EXT1 expression and patient prognosis (overall survival [OS], disease-specific survival [DSS], disease-free interval, and progression-free interval [PFI]) in multiple cancers was determined via univariate Cox regression analysis (p < 0.05). Tumor specimens were categorized into high- and low-expression groups according to the median EXT1 expression value, and the Survminer package was used to draw Kaplan–Meier curves to estimate the survival rate between the two groups [11]. The ability of EXT1 to discriminate between normal and tumor specimens was estimated by plotting receiver operating characteristic curves using the pROC package [12].

Gene set enrichment analysis

Gene set enrichment analysis (GSEA) was executed using the clusterProfiler package [13] to explore the pathways enriched by EXT1 in multiple cancers based on the Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and Reactome databases.

Immune and tumor microenvironment analysis

The infiltration data for 24 immune cell types were obtained from the ImmuCellAI database (http://bioinfo.life.hust.edu.cn/web/ImmuCellAI/). The association between EXT1 expression and the infiltration of 24 immune cell types in 32 cancers (excluding acute myeloid leukemia [LAML]) was determined. To identify differential immune cells, tumor specimens were categorized into two expression groups based on the median EXT1 expression value. The relationships between EXT1 expression and the major histocompatibility complex, chemokines and receptors, immunoinhibitors, immunostimulators, N6-methyladenosine (m⁶A) genes, ferroptosis-related genes (FRGs), tumor mutational burden (TMB), and microsatellite instability have been explored [14]. Mutation data from the Genomic Data Commons TCGA cohort were obtained from the UCSC Xena Browser. The associations between EXT1 expression, copy number alterations, and methylation were determined using Pearson’s correlation analysis. Copy number alterations and methylation data were obtained from cBioPortal (http://www.cbioportal.org/). Subsequently, survival discrepancies between the high and low EXT1-methylated groups were investigated. The relationship between EXT1 expression, gene mutation status, and the tumor microenvironment (TME) [15] was investigated. Gene mutation data were gained from the UCSC Xena Browser, and the mutation waterfall plot was fitted using the maftools package [16].

Drug sensitivity analysis

The half-maximal inhibitory concentrations (IC₅₀) of 192 drugs were gained from the GDSC2 database (https://www.cancerrxgene.org/), and their relationships with EXT1 expression were determined using Spearman’s correlation analysis.

Cell culture

The human cervical cancer cell lines SiHa and CaSki, which were kindly donated by Qilu Hospital of Shandong University (Shandong, China), were cultured in 10% high-glucose Dulbecco's Modified Eagle Medium (DMEM) and incubated at 37°C with 5% CO₂.

Cell transfection

Small interfering RNAs (siRNAs) targeting different EXT1 loci and a pcDNA3.1 plasmid carrying full-length EXT1 were designed and constructed by RiboBio (Guangzhou, China). SiRNA transfection was executed using riboFECT^TMCP (RiboBio) based on the manufacturer’s protocol. Scrambled siRNA was used as a negative control.

The EXT1 siRNA sequences were:

EXT1_001: GAACCAAGCTGCCGTCATA

EXT1_002 CTACCACAGTATTCATCTT

EXT1_003: GCTTCAAAGTCTACGTATA

Reverse transcription quantitative polymerase chain reaction (RT-qPCR)

Total RNA was extracted using TRIzol (Accurate Biology, Hunan, China), and 1 µg of RNA was reverse transcribed into cDNA using SPARKscript II All-in-one RT SuperMix for qPCR (Sparkjade Biotechnology Co.,Ltd. Shandong, China) according to the manufacturers’ protocols. RT-qPCR was performed to detect and quantify EXT1 mRNA using the 2^−ΔΔCt method. The experiment was performed in triplicate for each sample. Actin was used as the internal control.

5-ethynyl-2′-deoxyuridine (EDU) assay

The effect of EXT1 overexpression or interference on cervical cancer cell proliferation was analyzed using the EDU assay. Cervical cancer cells were seeded in 6-well plates for 24 h, transfected with EXT1 plasmids or siRNA, and incubated at 37°C for 24 h. Proliferation was detected in vitro using the EdU Cell Proliferation and Alexa Fluor 555 kits (CellorLab, Shanghai, China) based on the manufacturer’s protocol.

Transwell migration/invasion assay

After 24 h, the transfected cells were trypsinized, resuspended in high-glucose DMEM containing 1% fetal bovine serum (FBS), and counted. The suspended cells (150 µL; 5 × 10⁴ cells) and medium containing 20% FBS (650 µL) were added to the upper and lower chambers of the Transwell plates, respectively. After 24 h, the cells were fixed, stained, and then photographed under a microscope (EVOS M7000, Invitrogen, USA). Invasion was detected using BD Biocoat Matrigel (BD Biosciences, Bedford, MA, USA). The Matrigel and FBS-free medium were mixed at a ratio of 1:4 and added to the chamber, then incubation at 37°C for 30 min to facilitate solidification. The remaining steps were identical to those used for the migration assay.

Statistical analysis

All open databases and R software were utilized to analyze and visualize in this study. A heat map was drawn using the pheatmap package [17]. A p value < 0.05 was considered statistically significant unless otherwise stated.

Differential EXT1 expression in tumor and normal samples

In TCGA database, EXT1 was expressed in all 33 cancer types investigated herein; its expression was higher in CHOL, head and neck squamous cell carcinoma (HNSC), and esophageal carcinoma (ESCA) than in other cancers (Fig. 1A, B). Moreover, EXT1 expression was notably different in 17 of the cancer types; it was expressed higher in CESC, CHOL, HNSC, ESCA, kidney renal papillary cell carcinoma (KIRP), liver hepatocellular carcinoma (LIHC), lung squamous cell carcinoma (LUSC), sarcoma, and stomach adenocarcinoma (STAD) (Fig. 1C). Paired t-test results revealed that EXT1 expression was remarkably different among 10 of the cancer types; notably, its expression was high in CHOL, HNSC, ESCA, LIHC, LUSC, and STAD (Fig. 1D). In the combined analysis of TCGA and GTEx databases, EXT1 expression was remarkably different in 26 cancer types. Notably, its expression was high in breast invasive carcinoma (BRCA), CESC, CHOL, colon adenocarcinoma (COAD), lymphoid neoplasm diffuse large B-cell lymphoma, ESCA, glioblastoma multiforme (GBM), HNSC, KIRP, LAML, brain lower grade glioma (LGG), LIHC, LUSC, ovarian serous cystadenocarcinoma (OV), pancreatic adenocarcinoma (PAAD), rectum adenocarcinoma (READ), STAD, testicular germ cell tumor, thymoma (THYM), and uterine carcinosarcoma (UCS) (Fig. 1E). EXT1 expression in kidney renal clear cell carcinoma (KIRC), mesothelioma (MESO), adrenocortical carcinoma (ACC), skin cutaneous melanoma, bladder urothelial carcinoma, colon adenocarcinoma, KIRP, and LUSC varied according to the tumor stage (Fig. 2A). These results indicate that EXT1 expression varies in different cancers.

Differential EXT1 expression in tissues and cells

Analysis of the GTEx database showed that EXT1 expression was low in the muscle, brain, and bone marrow and high in the lungs and blood vessels (Fig. 2B, C). Cellular analysis of the data from the CCLE database indicated that EXT1 expression was high in MESO, thyroid cancer (THCA), and HNSC tumor cells and low in LAML, acute lymphoblastic leukemia, and chronic myelogenous leukemia (LCML) tumor cells (Fig. 2D, E).

Survival discrepancies between different EXT1 -expression groups

Pan-cancer survival assay and univariate Cox analysis results indicated that EXT1 expression was connected with the OS of patients with ACC, BRCA, CESC, KIRC, LGG, lung adenocarcinoma (LUAD), and PAAD (Fig. 3A). The high-expression group had a lower survival probability in LGG, LUAD, LUSC, and THCA; however, the opposite was observed in KIRC (Fig. 3B). Moreover, EXT1 expression was connected with DSS in KIRC, ACC, LGG, LUAD, PAAD, and uveal melanoma (UVM) (Fig. 3C). The high-expression group had shorter DSS in kidney chromophobe (KICH), LGG, LUAD, and THCA, whereas the opposite effect was observed in KIRC (Fig. 3D). EXT1 expression was associated with the disease-free interval of ACC and PAAD; the high-expression group had shorter disease-free interval in KIRP and PAAD (Fig. 3E, F). EXT1 expression correlated with the PFI of ACC, KIRC, LGG, OV, PAAD, and UVM (Fig. 3G). The high-expression group had shorter PFIs in the ACC, LGG, and UVM and longer PFIs in KIRC and THCA (Fig. 3H). The AUC values of LUAD, rectum adenocarcinoma, prostate adenocarcinoma (PRAD), testicular germ cell tumor, and THYM were > 0.6, indicating that EXT1 could effectively distinguish between tumor and normal samples (Fig. 3I).

Potential molecular mechanisms of EXT1

GO analysis revealed that EXT1 was related to the ubiquitin ligase complex, RNA splicing, chromosomes, cell division, and protein transport-related pathways, such as the G1/S transition of the mitotic cell cycle, via transesterification reactions (Fig. 4A, Supplementary Fig. 1). KEGG analysis revealed that signaling pathways associated with tumorigenesis and development (such as MAPK, mTOR, and PI3K-Akt signaling pathways) and pathways related to immunity (such as T-cell receptor and PD-L1 expression pathways) were notably enriched by EXT1(Fig. 4B, Supplementary Fig. 2). Therefore, EXT1 may be involved in the growth of various cancers.

Relationship between EXT1 and immune and TMEs

The tumor immune microenvironment (TIME) is strongly associated with tumor prognosis; hence, we investigated its association with EXT1 expression in 32 cancer types, excluding LAML. EXT1 expression correlated with the infiltration of most of the 24 immune cells (Fig. 4C, Supplementary Fig. 3). It was positively associated with induced regulatory T (iTreg) cells, central memory T (T_CM) cells, naturally occurring regulatory T (nTreg) cells, type 1 regulatory (Tr1) cell, T helper 17 (T_h17) cells, dendritic cells (DCs), monocytes, macrophages, and neutrophil infiltration, and negatively associated with CD8 T, gamma delta T (Tgd), B-, natural killer (NK), effector memory T (T_EM), exhausted CD8 T (T_ex), T follicular helper (T_fh), and cytotoxic T (T_c) cells, as well as mucosal-associated invariant T (MAIT) cell infiltration (Fig. 4D). In most cancers, the abundance of monocytes, neutrophils, CD8 T, iTregs, Tgd, and T_CM cells differed between the two EXT1-expression groups (Fig. 4E, Supplementary Fig. 4). Most major histocompatibility complex molecules, chemokines, chemokine receptors, immunoinhibitors, immunostimulators, m6A genes, and FRGs had a positive correlation with EXT1 expression in most cancers (Fig. 5A–G). EXT1 expression in THCA and STAD was negatively associated with the TMB (Fig. 5H), and, in diffuse large B-cell lymphoma, UCS, THCA, PRAD, and HNSC, it had a negative association with microsatellite instability and a considerable positive association with testicular germ cell tumor (Fig. 5I). Copy number alterations positively connected with EXT1 expression in most cancers, including BRCA, OV, and UVM (Fig. 5J). Moreover, in most of the cancer types, including diffuse large B-cell lymphoma, THYM, and UVM, EXT1 expression negatively correlated with methylation (Fig. 5K). The patients’ OS were differed between the high- and low-methylation groups in KIRP, LIHC, LUAD, MESO, THYM, and UVM, and the survival rate of the high-methylation group was better than that of the low-methylation group (Fig. 6A). DSS differed between the two methylation groups in KIRP, LGG, LUAD, THYM, and UVM, and the survival rate of the high-methylation group was better than that of the low-methylation group(Fig. 6B). Similarly, PFI differed between the two methylation groups in KIRP, LUAD, and MESO, and the survival rate of the high-methylation group was better than that of the low-methylation group (Fig. 6C). Therefore, EXT1 methylation may be related with patient survival in various cancer types.

Gene mutations are critical in tumor formation; hence, the relationship between EXT1 expression, gene mutations, and TIME was assessed. The high-EXT1 expression group had a higher mutation frequency than the low-EXT1 expression group in most cancers, and missense mutations were dominant in both groups (Fig. 6D, Supplementary Fig. 5). The gene mutations in ACC and bladder urothelial carcinoma are shown in Fig. 6E, and other mutations are shown in Supplementary Fig. 6. EXT1 expression is negatively associated with the TMB score and positively associated with other factors, including DNA replication and immune checkpoints, in several cancer types. Thus, EXT1 expression may be related to TIME and immunotherapeutic response in several cancer types (Fig. 6F).

Discrepancies in the sensitivity of common drugs

Spearman’s correlation analysis indicated that EXT1 expression positively connected with the IC₅₀ of 160 different treatment drugs (Supplementary Table 1). The IC₅₀ values of 152 drugs were notably different between the two EXT1-expression groups. Ten commonly used drugs showed remarkable differences in sensitivity between the high- and low-expression groups (Fig. 7). Therefore, EXT1 expression can be used to predict the sensitivity of these drugs in several cancer types.

Validation of EXT1 expression and function in CESC

Immunohistochemistry indicated that EXT1 expression in tumor tissues was notably higher than that in normal tissues, which was compatible with the transcriptomic data from TCGA and GTEx databases (Fig. 8A). Among the four CESC cell lines (C33A, CaSki, SiHa, and HeLa), EXT1 expression was the lowest and highest in SiHa and C33A cells, respectively (Fig. 8B). EXT1 was successfully overexpressed and silenced using siEXT1-1(Fig. 8C, D). The western blot results were compatible with those of the RT-qPCR (Fig. 8E). Moreover, EXT1 overexpression enhanced SiHa cell proliferation, whereas EXT1 inhibition reduced CaSki cell proliferation (Fig. 8F). The migration and invasion assays revealed that EXT1 overexpression enhanced the migration and invasion of CESC, whereas EXT1 inhibition had the opposite effect (Fig. 8G).

The tumor suppressor gene EXT1 has been extensively studied in multiple myeloma [18]. However, numerous recent studies have shown increased expression of EXT1 in various cancers, including adult acute lymphoblastic leukemia [9], hepatocellular carcinoma [19], and breast cancer [10]. These studies suggest that, besides being a tumor suppressor gene, EXT1 is also critical in tumor development. However, the mechanism of EXT1 in various cancer types has not yet been reported.

Herein, we assessed EXT1 expression levels in 33 different cancer types using independent TCGA, GTEx, and CCLE databases, and the results indicated that EXT1 expression was remarkably different between tumor and normal tissues. In the GTEx database, EXT1 expression was lower in the muscles, brain, and bone marrow and higher in the lungs and blood vessels than in other tissues. In TCGA dataset, EXT1 was expressed in all the 33 cancer types, particularly CHOL, HNSC, and ESCA, and it was relatively higher expressed in these cancers than in normal tissues. EXT1 was markedly differentially expressed among the 17 cancer types in several datasets and was highly expressed in CESC, CHOL, HNSC, ESCA, KIRP, LIHC, LUSC, sarcoma, and STAD in TCGA database. Therefore, EXT1 plays an oncogenic part in tumor progression. EXT1 is a potential prognostic marker for LUSC [20, 22] and a promising new target for inhibiting the stemness of cancer cells [10].

The EXT1 high-expression group had a lower survival probability in LGG, LUAD, LUSC, and THCA. EXT1 expression was closely connected with m⁶A methylation genes. In most cancers, EXT1 exhibited a strong correlation with methylation, and the OS of patients in the EXT1-hypermethylated group was substantially different from that of patients in the hypomethylated group. Therefore, the level of EXT1 methylation could be a critical indicator for the prognosis of various cancers. EXT1 methylation can affect cell proliferation and migration via the Wnt pathway, regulate gene expression, and predict poor prognosis in non-small cell lung carcinoma [20]. TMB is a predictive biomarker of immune checkpoint inhibitors. In general, the higher the TMB, the more the patients will benefit from immunotherapy. Additionally, studies have reported that TMB can predict immune-related survival outcomes in patients with breast cancer [21]. Herein, we examined the efficacy of immunotherapy by detecting the expression of EXT1. Our results could be used to develop EXT1-targeted therapeutic drugs that can be combined with clinical immunotherapies for improved efficacy. Our results indicated that EXT1 is a valuable prognostic marker in various tumor types.

We also observed a correlation between EXT1 and TIME. Tumors are closely related to TME, particularly the TIME, which affects their development and prognosis [23, 24]. TME prediction plays a critical part in cancer prognosis and treatment response [25]. Immune cells can be divided into effector (CD8 T) and suppressor (Treg) cells. The greater the infiltration of effector cells, the greater the possibility of clinical benefits and vice versa. In this study, EXT1 expression was associated with the infiltration of most of the 24 immune cell types in 32 cancer types, excluding LAML. EXT1 positively correlated with iTreg cells, T_CM cells, nTreg cells, and monocytes and negatively correlated with CD8 T cells, Tgd cells, B-cells, and NK cells. This indicates that high EXT1 expression represents an immunosuppressive state, which allows for tumor cells to escape immune surveillance and promotes the malignant progression of tumors.

We assessed the association between EXT1 and immune-related genes and the roles of these genes in most cancer types. EXT1 expression positively correlated with that of TGFB1, PD-L1, IL-10, and other immunosuppressive genes. The critical role of EXT1 in TIME and macrophage polarization was further confirmed. TGFB1 is a crucial immunosuppressive molecule in TME [26], and tumor cells secrete great amounts of TGFB1. Increased TGFB1 expression can inhibit the activation and differentiation of T/B lymphocytes and NK cells, thereby causing immune dysfunction and promoting the immune escape of tumor cells [26]. Increased PD-L1 expression is commonly found in tumor cells. PD-L1 binds to PD-1 on T cells, which leads to T-cell exhaustion and effectively prevents cytotoxic T cells from targeting tumor cells, thereby suppressing anti-tumor immunity [27]. Moreover, KEGG pathway enrichment analysis indicated that signaling pathways associated with tumorigenesis and development (including MAPK, mTOR, and PI3K-Akt signaling pathways) and immune-related pathways (including T-cell receptor and PD-L1 expression) were notably enriched with EXT1. EXT1 promotes apoptosis via the ERK1/2 signaling pathway under the regulation of MiR-665 in acute lymphoblastic leukemia [28]. Additionally, EXT1 can affect chondrogenic differentiation of precursor cells by altering Wnt/β-catenin signaling activity [29]. These results indicate that EXT1 acts via various pathways in different tumors. Research on EXT1 is limited; however, we believe that future studies will reveal more functions of EXT1.

Anti-tumor drug resistance analysis indicated that EXT1 expression showed a remarkable positive connection with the IC₅₀ values of 160 drugs. The IC₅₀ values of 10 commonly used clinical drugs (including fluorouracil, ABT737, alisertib, bortezomib, and carmustine) were considerably different between the high- and low-expression groups. Therefore, patients with high EXT1 expression levels are prone to developing drug resistance. Patients with low EXT1 expression were more sensitive to the conventional anticancer drugs cisplatin, cytarabine, and nilotinib, and less likely to develop drug resistance. However, this was the result of bioinformatics analysis; hence, there is a need for clinical confirmation.This was a limitation of our study. The potential mechanisms underlying the role of EXT1 in drug resistance require further investigation. In summary, EXT1 may be involved in immune regulation in various cancers. Elevated EXT1 expression inhibits TIME, indicating that EXT1 is a potential target for tumor immunotherapy.

To our knowledge, this is the first study to concentrate on the pan-cancer analysis of the role of EXT1. Our research provides theoretical support for the analysis and determination of differential expression and clinical significance of EXT1 in various tumors. EXT1 expression was elevated in most tumors, most of which indicated poor prognosis; nonetheless, the prognosis of KIRC showed a good trend. The different survival analysis results may provide clinical significance and a theoretical basis for future research on specific tumors. Owing to the potential tumorigenicity of EXT1 in various cancers, including CESC, we performed experiments to verify the oncogenicity of EXT1 in CESC. In CESC tissue sections, the EXT1 expression was notably higher than in the normal controls, and the downregulation of EXT1 could significantly reduce the proliferation, migration, and invasion abilities of CaSki cells. However, EXT1 overexpression had the opposite effect in SiHa cells, confirming the accuracy of the pan-cancer bioinformatics analysis results. In future, we will perform more studies on other cancer types to provide potentially useful data for the development of cancer treatment strategies.

Using public databases, we explored the prognostic value and immune correlation of EXT1 in various cancers, thereby providing a basis for further understanding of the molecular mechanisms of these cancers. Our findings provide potential targets for the clinical diagnosis and immunotherapy of various cancers. Nevertheless, this study had some major limitations because it was primarily based on bioinformatics. First, this retrospective study was based on data from public databases, and the results must be supported and verified using clinical samples and data. Second, the mechanism by which EXT1 influences tumors differs among various tumors and requires further research and verification. Finally, the application of the predicted drug targets requires clinical trials and data.

ACC Adrenocortical carcinoma

BRCA Breast invasive carcinoma

CCLE Cancer Cell Line Encyclopedia

CESC Endocervical adenocarcinoma

CHOL Cholangiocarcinoma

CNA Copy number alterations

COAD Colon adenocarcinoma

DFI Disease-free interval

DMEM Dulbecco's Modified Eagle Medium

DSS Disease-specific survival

ESCA Esophageal carcinoma

FBS Fetal bovine serum

FRGs Ferroptosis-related genes

GO Gene Ontology

GBM Glioblastoma multiforme

GSEA Gene Set Enrichment Analysis

GTEx Genotype Tissue Expression

HNSC Head and neck squamous cell carcinoma

KEGG Kyoto Encyclopedia of Genes and Genomes

KICH Kidney chromophobe

KIRC Kidney renal clear cell carcinoma

KIRP Kidney renal papillary cell carcinoma

LAML Acute myeloid leukemia

LCML Chronic myelogenous leukemia

LGG Brain lower grade glioma

LIHC Liver hepatocellular carcinoma

LUAD Lung adenocarcinoma

LUSC Lung squamous cell carcinoma

MESO Mesothelioma

MHC Major histocompatibility complex

MSI Microsatellite instability

MM Multiple myeloma

NC Negative control

NK Natural killer

OS Overall survival

OV Ovarian serous cystadenocarcinoma

PAAD Pancreatic adenocarcinoma

PFI Progression-free interval

PRAD Prostate adenocarcinoma

READ Rectum adenocarcinoma

ROC Receiver operating characteristic

SKCM Skin cutaneous melanoma

STAD Stomach adenocarcinoma

TCGA The Cancer Genome Atlas

TGCT Testicular germ cell tumor

THCA Thyroid cancer

THYM Thymoma

TIME The tumor immune microenvironment

TMB Tumor mutational burden

TME The tumor microenvironment

UCS Uterine carcinosarcoma

UVM Uveal melanoma

Ethics approval and consent to participate

The studies involving human participants were reviewed and approved by the Ethical Review Committee of the Provincial Hospital Affiliated to Shandong First Medical University(certifcation no. 2022-421).The processing of clinical tissue samples is in strict compliance with the ethical standards of the Declaration of Helsinki. All methods were carried out in accordance with relevant guidelines and regulations. The patients/participants provided their written informed consent to participate in this study.

Consent for publication

Not applicable

Availability of data and materials

The data generated and analysed during the current study are available in the UCSC Xena (https://xenabrowser.net).

Competing interests

The authors declare that they have no competing interests

Funding

The authors declare that no fund, grant, or other support was received during the preparation of this manuscript.

Authors' contributions

All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Yuqiu Liu, LiLi and Hongqing Wang. The first draft of the manuscript was written by Yuqiu Liu, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Acknowledgements

The authors thank the reviewers for their helpful comments on the manuscript.

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No competing interests reported.

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Pan-cancer analysis of the prognostic and immunotherapeutic values of exostosin-1

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Abstract

Figures

Background

Materials and Methods

Data collection

Differential expression of EXT1

Prognostic value of EXT1

Gene set enrichment analysis

Immune and tumor microenvironment analysis

Drug sensitivity analysis

Cell culture

Cell transfection

Reverse transcription quantitative polymerase chain reaction (RT-qPCR)

5-ethynyl-2′-deoxyuridine (EDU) assay

Transwell migration/invasion assay

Statistical analysis

Results

Discussion

List of Abbreviations

Declarations

References

Additional Declarations

Supplementary Files

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