An integrated pan-cancer analysis of ALKBH5 as an immunological and prognostic biomarker Running title: ALKBH5 as a biomarker in pan-cancer

doi:10.21203/rs.3.rs-1638245/v1

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An integrated pan-cancer analysis of ALKBH5 as an immunological and prognostic biomarker Running title: ALKBH5 as a biomarker in pan-cancer

https://doi.org/10.21203/rs.3.rs-1638245/v1

This work is licensed under a CC BY 4.0 License

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Background: N6-methyladenosine (m⁶A) is the internal chemical modification of organism mRNA and participates in various biological processes in cancers. Studies have shown that m⁶A can be cleared by ALKBH5 (alkB homolog 5), indicating that it may play important functions. Therefore, we intend to conduct a comprehensive analysis of ALKBH5 from a pan-cancer perspective to clarify its role in cancers.

Methods: Differently expression of ALKBH5 was performed by ‘edger’ package. Cox Univariate and log-rank analysis were used to evaluate the prognosis of ALKBH5. The correlation between ALKBH5 expression and immune cell infiltration, tumor microenvironment, copy number variations, tumor mutational burden, neoantigen, homologous recombination deficiency and microsatellite instability, methyltransferases and stemness scores were analyzed respectively via Pearson or Spearman analysis. ESTIMATE, stromal and immune scores were evaluated through ‘ESTIMATE’ package and tumor mutational burden was calculated by ‘maftools’ package.

Results: We found that ALKBH5 was differentially expressed and important for prognosis in some cancers. Also, we found that the expression of ALKBH5 had a significant correlation with immune cell infiltration, tumor microenvironment, copy number variations, tumor mutational burden, neoantigen, homologous recombination deficiency and microsatellite instability in various common cancers. Further, the ALKBH5 expression significantly correlated with the expression of methyltransferases and stemness scores in various cancers.

Conclusions: Our research showed that ALKBH5 plays a pivotal role in several cancers and can be a novel immunological and prognostic biomarker, indicating its role as a target of immunotherapy.

ALKBH5

immunological biomarker

prognosis

pan-cancer

Cancers have been the main cause of death for people around the world¹. Although with the deepening of people's understanding of cancers and the continuous improvement of treatment methods, the therapeutic effect of cancers has been greatly improved². However, in clinical treatment, some problems have become prominent, such as drug resistance and off-target effects³. In recent years, it has been found that most cancers have changes in the level of molecular biology⁴. These changes include genetic mutations⁵, inhibitory immune cell infiltration⁶, microsatellite instability (MSI)⁷ and changes in DNA and RNA methylation level^8,9, which can affect the therapeutic strategy and efficacy. Thus, finding biomarkers that are associated with these changes may become an important focus of cancer treatment.

There is increasing evidence that m⁶A modification participated in various cellular biological processes by influencing mRNA metabolism¹⁰. Recently, it has been confirmed the disorder of m⁶A modification is associated with human carcinogenesis^11,12 and the study has revealed m⁶A modification has a dual role in cancer⁹. M⁶A modification can be reversible¹³. ALKBH5, as a m6A methylation scavenging protein, affected the biological phenotype of cancer cells through different mechanisms, for example, ALKBH5 could sustain the expression of FOXM1 to maintain tumorigenicity of glioblastoma¹⁴. And overexpression of ALKBH5 could repress the invasion and metastasis of colon cancer¹⁵. In addition, researchers have confirmed that ALKBH5 can inhibit the efficacy of immunotherapy by regulating immune cells in mice with melanoma and colon cancer¹⁶. However, it is not known whether ALKBH5 could regulate immunity and have prognostic value in pan-cancer.

In the current study, we firstly investigated the expression and prognostic value of ALKBH5 in pan-cancer. Then, we calculated the correlation of ALKBH5 expression with immune cell infiltration, tumor microenvironment (TME), neoplastic antigen, copy number variations (CNV), tumor mutational burden (TMB), microsatellite instability (MSI) and homologous recombination deficiency (HRD). Further, we also analyzed the correlation of ALKBH5 with methyltransferases expression in pan-cancer. The study involved in the integration analysis of ALKBH5 in pan-cancer so far, presenting the association between ALKBH5 and prognosis, immune infiltration, cancer mutation and methyltransferases, suggesting that ALKBH5 can be a novel immunological and prognostic biomarker in pan-cancer.

Data Sources

The expression data of ALKBH5 were obtained from The Cancer Genome Atlas (TCGA), Clinical Proteomic Tumor Analysis Consortium (CPTA) portal (http://ualcan.path.uab.edu/analysis-prot.html) and the Genotype-Tissue Expression (GTEx) (https://gtexportal.org/home/) databases. And the copy number variation, single nucleotide polymorphism and clinical data were from the TCGA database. Stemness scores based on DNA methylation (DNAss) were obtained from reference¹⁷.

Survival analysis

The association between ALKBH5 expression and prognostic value including overall survival (OS), disease-specific survival (DSS), disease-free interval (DFI) and progression-free interval (PFI) time were performed by Cox Univariate analysis and visualized by forest plot. OS and disease-free survival (DFS) were tested by log-rank analysis and shown by Kaplan–Meier. The expression groups were divided by median in every type of cancer.

The correlation between expression of ALKBH5 and immune infiltration in pan-cancer

The relationship between ALKBH5 expression and immune cell score was evaluated by Spearman correlation analysis. ESTIMATE, stromal and immune scores were calculated using the ‘ESTIMATE’ package (R Version 3.5.1). The correlation between ALKBH5 expression and immunoregulatory genes were calculated through Pearson correlation analysis. The correlation between ALKBH5 expression and purity were obtained from TIMER2.0 (http://timer.cistrome.org/).

Statistical analysis

Analysis of differential expression of ALKBH5 between normal and cancer tissues was performed by the ‘edger’ package in the R (Version 3.5.1). TMB was calculated by ‘maftools’ package in the R. The relationship between counts of neoantigen, purity, TMB and MSI in each sample and ALKBH5 expression via Spearman correlation analysis. And the relationship between the expression of ALKBH5 and methyltransferase genes was calculated through Pearson correlation analysis.

The expression levels of ALKBH5 in pan-cancer

To determine the role of ALKBH5 in pan-cancer, we first tested the expression levels of ALKBH5 in human cancer and normal tissues. The results showed that ALKBH5 mRNA was higher in ACC (adrenocortical carcinoma), BRCA (breast invasive carcinoma), CESC (cervical squamous cell carcinoma and endocervical adenocarcinoma), CHOL (cholangiocarcinoma), COAD (colon adenocarcinoma), ESCA (esophageal carcinoma), GBM (glioblastoma multiforme), HNSC (head and neck squamous cell carcinoma), KIRC (kidney renal clear cell carcinoma), LAML (acute myeloid leukemia), LGG (brain lower grade glioma), LIHC (liver hepatocellular carcinoma), LUSC (lung squamous cell carcinoma), LUAD (lung adenocarcinoma), OV (ovarian serous cystadenocarcinoma), PAAD (pancreatic adenocarcinoma), PRAD (prostate adenocarcinoma), SKCM (skin cutaneous melanoma), STAD (stomach adenocarcinoma), TGCT (testicular germ cell tumors), THCA (thyroid carcinoma) and UCS (uterine carcinosarcoma) tissues than that in normal tissues, but in KIRP (kidney renal papillary cell carcinoma), READ (rectum adenocarcinoma) and UCEC (uterine corpus endometrial carcinoma) had opposite results (Figure 1A). Moreover, there was no difference between normal and cancer tissues in BLCA (bladder urothelial carcinoma) and KICH (kidney chromophobe) (Figure 1A). Similarly, ALKBH5 protein was higher in breast cancer, OV, KIRC, lung cancer, glioblastoma and liver cancer, whereas lower in UCEC and pancreatic cancer (Figure 1B).

Prognostic value of ALKBH5 in pan-cancer

To explore the prognostic value of ALKBH5 in cancers, we analyzed the relationship between the expression levels of ALKBH5 and OS in 33 cancers and found the higher expression level of ALKBH5 was a risk factor of OS in BLCA, GBM, KICH, LAML and LGG, while a low-risk factor in ESCA, OV and PAAD (Figure 2A). Considering that there may be factors other than tumor-caused death, we also analyzed the correlation between the ALKBH5 expression and DSS. And we found higher ALKBH5 indicated a high risk of DSS in GBM, KICH and LGG and a low risk in OV and KIRC (Figure 2B). Also, higher ALKBH5 showed a high risk of PFI in ACC, KICH, LGG and LUSC, but a low risk in PAAD (Figure 2C). Moreover, higher ALKBH5 showed a high risk of DFI in ACC and LUSC (Figure 2D).

Meanwhile, we also tested the correlation between ALKBH5 expression and OS, and the results showed that the highly expressed ALKBH5 has a shorter OS time in BLCA, KICH, LAML, LGG and UVM, but a longer OS time in CESC (Figure 2E). Moreover, highly expressed ALKBH5 has a shorter DFS time in ACC and LGG (Figure 2F).

Further, we explored the correlation between ALKBH5 expression and clinical features such as pathological stage, T stage and histological type. The results showed that, for pathological stage, the expression of ALKBH5 was significantly downregulated in THCA, KIRC, SKCM, TGCT and OV (Figure 3A). With the increase of T stage, ALKBH5 was upregulated in STAD, while downregulated in THCA and KIRC (Figure 3B). Intriguingly, ALKBH5 expression was higher in endometrioid than serous UCEC. And in THYM, both type A and B have higher ALKBH5 expression compared to type C (Figure 3C).

ALKBH5 Expression is correlated with Immune Infiltration in pan-caner

Immunotherapy as one of the effective treatments for cancers, such as cell immunotherapy and checkpoint treatment strategy has become the focus of researchers¹⁸. Infiltration of immune cells in the cancer environment means that immune cells move from the blood to the cancer tissue and begin to play their roles. These immune cells can be separated and is closely related to the clinical results¹⁹, indicating they may serve as drug targets²⁰. Therefore, we firstly analyzed the correlation between these immune cells and OS. Results showed these immune cells were remarkably associated with OS in various cancers (Table S1). Then, we found ALKBH5 expression was remarkably associated with purity in various cancers (Table 1). Next, the correlation between ALKBH5 expression and B cell, CD4+T cell. CD8+T cell, neutrophil, macrophage, dendritic cell was investigated respectively. Surprisingly, ALKBH5 expression remarkably correlated with these immune cells (Table S2), especially in COAD, KIRC and LGG

Table 1

The relationship between ALKBH5 expression and purity, homologous recombination deficiency (HRD) and stemness scores (DNAss) in pan-cancer.

Cancer type	Purity		HRD		DNAss
Cancer type	Cor	P	Cor	P	Cor	P
ACC	0.310	0.006	0.250	0.030	0.040	0.760
BLCA	-0.020	0.680	0.130	0.010	-0.140	0.005
BRCA	0.160	<0.001	-0.160	<0.001	-0.050	0.140
CESC	0.130	0.030	-0.110	0.070	0.030	0.550
CHOL	-0.020	0.920	-0.110	0.540	0.420	0.010
COAD	-0.310	<0.001	-0.110	0.050	-0.210	<0.001
DLBC	-0.170	0.270	-0.030	0.840	-0.050	0.750
ESCA	0.190	0.020	0.150	0.060	-0.030	0.720
GBM	0.060	0.500	0.040	0.630	-0.010	0.930
HNSC	0.130	0.004	0.190	<0.001	0.070	0.130
KICH	-0.080	0.550	0.370	0.002	-0.170	0.180
KIRC	0.030	0.490	0.100	0.030	0.040	0.510
KIRP	0.090	0.130	-0.140	0.020	-0.100	0.100
LAML	0.010	0.910	-0.200	0.040	0.110	0.160
LGG	-0.070	0.130	0.130	0.003	0.290	<0.001
LIHC	0.110	0.030	0.090	0.080	-0.040	0.480
LUAD	0.110	0.010	0.060	0.220	0.007	0.880
LUSC	0.270	<0.001	0.070	0.130	0.170	0.001
MESO	0.080	0.460	0.080	0.470	-0.010	0.910
OV	0.010	0.770	0.030	0.500	0.500	0.210
PAAD	0.160	0.040	-0.130	0.110	-0.030	0.720
PCPG	-0.090	0.270	0.020	0.830	-0.080	0.300
PRAD	-0.120	0.007	-0.040	0.420	-0.020	0.600
READ	-0.310	0.003	-0.120	0.250	-0.150	0.160
SARC	0.270	<0.001	0.300	<0.001	0.030	0.640
SKCM	0.010	0.900	-0.260	0.010	0.030	0.790
STAD	0.009	0.850	-0.030	0.530	-0.010	0.860
TGCT	-0.020	0.830	-0.400	<0.001	0.110	0.170
THCA	0.140	0.004	0.090	0.060	-0.230	<0.001
THYM	-0.040	0.660	-0.200	0.050	-0.210	0.020
UCEC	0.150	0.040	-0.230	0.002	0.020	0.820
UCS	0.150	0.280	0.070	0.630	0.140	0.300
UVM	-0.390	<0.001	-0.220	0.060	0.200	0.080

In the TME, ESTIMATE algorithm can quantify immune and stromal components in the cancer²¹. We analyzed the correlation between ALKBH5 expression and immune and stromal scores and found that the expression of ALKBH5 was significantly correlated with these three scores (Table S3), especially negatively in THCA and ACC, but positively in COAD and UVM (Figure 5).

As mentioned above, the immunoregulatory gene functions importantly in cancers, including chemokines, receptors, major histocompatibility complex (MHC), immune inhibitors and immune stimulators. Therefore, the correlation between these immunoregulatory genes and ALKBH5 expression in cancers was performed. ALKBH5 showed significantly correlation with immunoregulatory genes in various cancers (Figure 6).

The correlation between ALKBH5 expression and tumor mutation in pan-cancer

Tumor mutation is the pivotal factor affecting tumor prognosis²². We first analyzed the mutation of ALKBH5 in cancers. It was found that ALKBH5 has a missense mutation rate from 0.2% to 1.4% in BLCA, BRCA, CESC, COAD, ESCA, GBM, HNSC, KIRP, LGG, LIHC, LUAD, LUSC, PAAD, PRAD, SARC, STAD and UCEC, however, there was no detected missense mutation in other cancers (Fig 7A). Then, the correlation between ALKBH5 expression and CNV was explored in cancers and the significance was shown in BLCA, BRCA, CESC, ESCA, HNSC, LIHC, LUAD, LUSC, OV, PAAD, PRAD, SARC, STAD, UCEC and UCS (Fig 7B). Mutations in cancer cells can cause TMB, MSI, neoantigen and HRD. Thus, we firstly tested the correlation between ALKBH5 expression and TMB and the remarkable correlation presented in BRCA, COAD, DLBC, ESCA, LGG, PRAD, SARC and THCA (Table 2). As for MSI, the significant correlation existed in COAD, DLBC, KIRC, LUAD, LUSC, PRAD, SARC, STAD and THCA (Table 2). Besides, tumor mutations can also produce new antigens, which in turn affect the patient's prognosis. Intriguingly, ALKBH5 expression was significantly correlated with the count of neoantigens in COAD and UCEC (Table 2). Further, ALKBH5 and HRD showed a significant correlation in ACC, BLCA, BRCA, HNSC, KICH, KIRC, KIRP, LAML, LGG, SARC, SKCM, TGCT and UCEC (Table 1).

Table 2

The relationship between ALKBH5 expression and tumor mutational burden (TMB), microsatellite instability (MSI) and neoantigen in pan-cancer.

Cancer type	TMB		MSI		Neoantigen
Cancer type	Cor	P	Cor	P	Cor	P
ACC	0.150	0.190	-0.030	0.800	0.070	0.590
BLCA	-0.030	0.600	0.050	0.310	0.030	0.590
BRCA	-0.190	<0.001	-0.010	0.710	0.040	0.300
CESC	-0.050	0.380	0.050	0.380	0.080	0.210
CHOL	0.100	0.570	0.190	0.260	-0.190	0.310
COAD	0.340	<0.001	0.360	<0.001	0.340	<0.001
DLBC	-0.340	0.040	-0.500	<0.001	0.002	0.990
ESCA	-0.180	0.010	0.020	0.830	-	-
GBM	0.070	0.420	0.110	0.170	0.040	0.690
HNSC	-0.090	0.050	0.005	0.910	-0.020	0.600
KICH	0.160	0.210	-0.050	0.680	0.070	0.660
KIRC	0.010	0.800	0.120	0.030	0.030	0.620
KIRP	-0.040	0.480	0.030	0.650	-0.020	0.730
LAML	-0.130	0.150	0.010	0.870	-	-
LGG	0.150	<0.001	-0.050	0.280	-0.003	0.950
LIHC	-0.060	0.240	0.020	0.640	0.040	0.470
LUAD	0.020	0.600	0.100	0.020	0.040	0.390
LUSC	-0.060	0.190	0.190	<0.001	0.030	0.520
MESO	0.130	0.240	-0.040	0.730	0.020	0.900
OV	-0.010	0.810	0.030	0.600	-	-
PAAD	-0.210	0.005	-0.030	0.670	0.020	0.850
PCPG	-0.010	0.860	0.130	0.090	-0.070	0.570
PRAD	-0.150	<0.001	-0.090	0.040	-0.060	0.260
READ	-0.090	0.420	0.040	0.700	0.050	0.680
SARC	0.220	<0.001	0.170	0.006	0.020	0.780
SKCM	0.130	0.190	0.120	0.220	0.060	0.600
STAD	0.040	0.410	0.160	0.001	-	-
TGCT	-0.150	0.070	-0.050	0.580	0.090	0.370
THCA	-0.210	<0.001	-0.170	<0.001	-0.100	0.170
THYM	-0.030	0.770	0.005	0.950	-0.090	0.470
UCEC	0.150	0.050	0.120	0.100	0.200	0.010
UCS	0.130	0.350	0.260	0.050	0.180	0.220
UVM	-0.210	0.070	0.150	0.180	-0.070	0.670

The correlation between ALKBH5 expression and methyltransferase in pan-cancer

Methylation is an important way of epigenetic regulation in organisms and can be divided into DNA and RNA methylation. ALKBH5 serves as a demethylation regulator of RNA, thus we analyzed the correlation between ALKBH5 and genes regulating RNA methylation and a significant correlation was found in most cancers (Figure 8A). And DNA methylation can affect m6A modification by modulating m6A demethylase gene expression²³. To further clarify the role of ALKBH5 in cancers, the correlation between ALKBH5 and DNA methyltransferase was performed and there showed a significant correlation between ALKBH5 and DNA methyltransferase in various cancers (Figure 8B). In addition, it is reported that methylation is involved in the regulation of cell stemness, which might regulate immunotherapy²⁴. And we found ALKBH5 expression was correlated with DNAss in BLCA, CHOL, COAD, LGG, LUSC, THCA and THYM (Table 1).

ALKBH5 is a key player in the biological process of m⁶A methylation⁹. So far, researchers have mostly studied the role of ALKBH5 in a single tumor and revealed ALKBH5 might function as a potential target for cancer immunotherapy^25,26, but the prognostic value of ALKBH5 and its association with immune infiltration, tumor mutations and genes of methyltransferase in pan-cancer have not been reported. Here, we investigated these and provided new insights to understand the correlation of ALKBH5 with tumor immunology, mutation, methylation modification and its potential in the treatment of various cancers.

Here, we found ALKBH5 was highly expressed in various cancers, but the opposite was true in KIRP, READ and UCEC, indicating that ALKBH5 might play different roles in different cancers. At the same time, ALKBH5 had different prognostic values in different cancers, which also confirmed this point. ALKBH5 functioned as a suppressor in bladder cancer²⁷, while it promoted the progression of acute myeloid leukemia, gastric cancer, epithelial OV, colon cancer and GBM ^14,28−31. This evidence also indicated the diverse effects of ALKBH5 in cancers. Further, it is very necessary to explore the role of ALKBH5 in every type of cancer.

Our study provided evidence of the correlation between ALKBH5 expression and cancer immunity. Tumor-infiltrating lymphocytes are independent predictors in cancer³². Firstly, we found the expression of ALKBH5 and the infiltration level of 6 immune cells showed a significant correlation. Infiltrating inhibitory lymphocytes cannot kill tumor cells, but can promote tumor progression³³. Further, ALKBH5 expression showed a remarkable correlation with TME in most cancers. At present, immunotherapy of cancers was mainly aimed at specific targets³⁴. And we found ALKBH5 and multiple immunoregulatory genes were significantly correlated in different cancers. The study showed mice lacking Alkbh5 showed innate immune response dependence on virus exposure³⁵. And lung squamous cell carcinoma patients with low level of ALKBH5 showed a better immunotherapy sensitivity ³⁶. These indicated ALKBH5 was a potential target for cancer immunotherapy and the immune correlation of ALKBH5 in different tumors will be explored in the future.

Tumor mutations can produce cancer biomarkers in immunotherapy, including MSI, neoantigen, and HRD. Here, ALKBH5 expression showed a correlation with MSI, neoantigen and HRD in various tumors. In general, the more neoantigens produced by tumor mutations were more likely to cause anti-tumor T cells in the tumor microenvironment and peripheral blood correspondingly increased, and the possibility of responding to tumor immunotherapy was higher³⁷. Clinical trials have found that patients with high MSI respond better to immunotherapy³⁸. Also, abnormal HRD will trigger a series of cancerous phenotypes³⁹. Clinical studies have found that HRD caused by mutations of mismatch responses genes may help to accurately predict the response of patients to PD-1 inhibitors⁴⁰ and is highly related to the sensitivity of platinum-based chemotherapy drugs⁴¹. These findings reinforced the evidence that ALKBH5 was a potential target for cancer immunotherapy.

Finally, ALKBH5, as a regulator of m⁶A methylation, has also been shown to have a significant correlation with genes involved in other RNA methylation and DNA methylation, indicating the important role of ALKBH5 in epigenetic regulation. Studies have shown that the main difference between stem cells and other cells is the epigenetic difference²⁴, and ALKBH5 has been proven to regulate the stemness of cancer stem cells in AML and GBM^14,31. Moreover, stemness is closely related to immunotherapy, for example, studies have shown that enhancing the stemness of T cells could enhance the efficacy of immunotherapy^42,43. Although the current reports on ALKBH5 mainly focus on m⁶A methylation and it is believed that other regulation mechanisms will also be discovered in the future.

Our study analyzed the expression of ALKBH5 in pan-cancer and determined the prognostic value of ALKBH5. Our study provides evidence of the association between ALKBH5 expression and cancer immunity, tumor mutations, and methyltransferase. Our results provide new evidence about the role of ALKBH5 in pan-cancer, as well as new insights into cancer treatment targets.

ACC (adrenocortical carcinoma), BLCA (bladder urothelial carcinoma), BRCA (breast invasive carcinoma), CESC (cervical squamous cell carcinoma and endocervical adenocarcinoma), CHOL (cholangiocarcinoma), COAD (colon adenocarcinoma), ESCA (esophageal carcinoma), 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), LAML (acute myeloid leukemia), LGG (brain lower grade glioma), LIHC (liver hepatocellular carcinoma), LUSC (lung squamous cell carcinoma), LUAD (lung adenocarcinoma), OV (ovarian serous cystadenocarcinoma), PAAD (pancreatic adenocarcinoma), PRAD (prostate adenocarcinoma), READ(rectum adenocarcinoma) SKCM (skin cutaneous melanoma), STAD (stomach adenocarcinoma), TGCT (testicular germ cell tumors), THCA (thyroid carcinoma), UCEC (uterine corpus endometrial carcinoma), UCS (uterine carcinosarcoma), m⁶A (N6-methyladenosine), ALKBH5 (alkB homolog 5), CNV (copy number variation), MSI (microsatellite instability), TCGA (the Cancer Genome Atlas), GTEx (the Genotype-Tissue Expression), OS (overall survival), DSS (disease-specific survival), DFI (disease-free interval), PFI (progression-free survival), DFS (disease-free interval), TMB (tumor mutational burden), TME (tumor microenvironment), HRD (homologous recombination deficiency), DNAss (DNA methylation based stemness scores).

Author contributions

Xiaohong Xiang designed the study and analyzed the data, Doudou Shi downloaded the data and revised the manuscript, Xiaohong Xiang revised the manuscript.

Acknowledgements

Thanks for Hao Lu, Mengru Liu and Pan Liang for checking the spelling of manuscript. Thanks to the Henan Key Laboratory of Digestive Organ Transplantation and Sangerbox 3.0 for supporting this work.

Competing interests

The authors declare that they have no competing interests.

Ethics approval and consent to participate

The present study used secondary data which is available in public domain. The dataset has no identifiable information of the survey participants. All methods are carried out in relevant guidelines and regulations.

Consent for publication

Not applicable.

Availability of data and materials

The raw data involved in this research were available from the Genomic Data Commons Data Portal via gdc-client tool, Clinical Proteomic Tumor Analysis Consortium (CPTA) (http://ualcan.path.uab.edu/), TIMER2.0 (http://timer.cistrome.org/) and the Genotype-Tissue Expression (GTEx) (https://gtexportal.org/home/) databases.

Funding

None.

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An integrated pan-cancer analysis of ALKBH5 as an immunological and prognostic biomarker Running title: ALKBH5 as a biomarker in pan-cancer

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