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www.aging-us.com
AGING 2023, Vol. 15, Advance
Research Paper
N6AMT1 is a novel potential diagnostic, prognostic and
immunotherapy response biomarker in pan-cancer
Mingqi Wang1,2,*
, Jiajie Zhu3,*
, Yingquan Ye1,2,*
, Ping Li1,2
, Weijie Sun4
, Mei Zhang1,2
1
Department of Chinese Integrative Medicine Oncology, The First Affiliated Hospital of Anhui Medical University,
Shushan, Hefei 230022, Anhui, China
2
Department of Integrated Traditional Chinese and Western Medicine, Anhui Medical University, Shushan, Hefei
230022, Anhui, China
3
Department of Gastroenterology, Tongde Hospital of Zhejiang Province, Xihu, Hangzhou 310012, Zhejiang,
China
4
Department of Infectious Diseases, The First Affiliated Hospital of Anhui Medical University, Shushan, Hefei
230022, Anhui, China
*Equal contribution and share first authorship
Correspondence to: Ping Li, Weijie Sun, Mei Zhang; email: liping64@sina.com; swj950128@163.com, https://orcid.org/0000-
0003-0112-0461; zhangmei@ahmu.edu.cn
Keywords: N6AMT1, prognosis, pan-cancer, diagnosis, immunotherapy
Received: April 3, 2023
Accepted: June 15, 2023
Published: July 12, 2023
Copyright: © 2023 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution
License (CC BY 3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original
author and source are credited.
ABSTRACT
Background: The N-6-adenine-specific DNA methyltransferase 1 (N6AMT1) is the only writer responsible for
DNA 6mA modifications. At present, its role in cancer is still unclear, and further systematic pan-cancer analysis
is needed to explore its value in diagnosis, prognosis and immunological function.
Methods: The subcellular localization of N6AMT1 was explored by UniProt and HPA database. The expression
data and prognosis data of N6AMT1 were downloaded from the UCSC (cohort: TCGA pan-cancer), and the
diagnostic and prognostic value of N6AMT1 in pan-cancer was explored. The value of N6AMT1-guided
immunotherapy was explored through three cohorts (GSE168204, GSE67501 and IMvigor210 cohort). The
correlation between N6AMT1 expression and tumor immune microenvironment was explored using CIBERSORT
and ESTIMATE calculation methods, combined with TISIDB database. The biological role of N6AMT1 in specific
tumors was explored by GSEA method. Finally, we explored chemicals affecting N6AMT1 expression through
the CTD.
Results: N6AMT1 is mainly localized in the nucleus and differentially expressed in 9 cancer types. In addition,
N6AMT1 showed early diagnostic value in 7 cancers and showed potential prognostic value in multiple cancer
types. We also demonstrated that N6AMT1 expression was significantly associated with immunomodulator
related molecules, infiltration of lymphocyte subsets, and biomarkers of immunotherapy response.
Furthermore, we show that N6AMT1 is differentially expressed in the immunotherapy cohort. Finally, we
explored 43 chemicals that can affect N6AMT1 expression.
Conclusions: N6AMT1 has shown excellent diagnostic and prognostic capabilities in a variety of cancers, and
it may reshape the tumor microenvironment and contribute to the ability to predict response to immuno
therapy.www.aging-us.com
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INTRODUCTION
Cancer is currently the leading cause of death worldwide,
killing more than 10 million people each year [1]. The
main methods for cancer treatment are surgery,
radiation, chemotherapy, and immunotherapy. However,
although these methods greatly prolong the survival
time of patients, some patients still have a poor
prognosis. Therefore, an in-depth understanding of the
molecular mechanisms underlying the occurrence and
development of cancer will help us to find more
accurate prognostic biomarkers and therapeutic targets,
thereby providing new approaches to the diagnosis and
treatment of cancer.
Recent research has shown that abnormal epigenetic
modifications (DNA methylation, histone modifications,
etc.) are closely related to the occurrence of cancer [2].
Importantly, such epigenetic modifications are tunable;
thus, targeting epigenetic modifications represents a
promising therapeutic approach for cancer. With the
development of deep sequencing, the newly discovered
epigenetic mark DNA N6-methyl-2’-deoxyadenosine
(6mA) methylation has been shown to be widespread
in the human genome [3]. Dysregulation of DNA 6mA
modification is associated with embryogenesis [4],
atherosclerosis [5], hypertension [6], chronic kidney
disease [7], and cancer [3, 8, 9]. The N-6-adenine
specific DNA methyltransferase 1 (N6AMT1), a putative
methyltransferase, was the first writer identified to be
responsible for DNA 6mA modification [3]. Therefore,
we speculate that N6AMT1 may have a crucial role in
the occurrence and development of cancer. Studies have
shown that abnormal expression of N6AMT1 can affect
the progression of triple-negative breast cancer and affect
drug resistance [10, 11]. In addition, increased expression
of N6AMT1 significantly increased the proliferation and
migration of HCC and tongue squamous cell carcinoma
[12, 13]. However, its specific mechanism of action and
its role in other cancers have not yet been studied. Given
the limited reports on the role of N6AMT1 in cancer, it is
difficult to draw any conclusions at this time. Therefore,
a comprehensive analysis of N6AMT1 in different cancer
types is required.
In this study, we determined the differential expression
of N6AMT1 in pan-cancer and screened cancer types
with diagnostic and prognostic values. Furthermore, this
study explored the correlation of N6AMT1 expression
with immunomodulators, lymphocyte subset infiltration,
and immunotherapy biomarkers, and assessed the
potential value of N6AMT1 in immunotherapy in
different cancer types. Finally, we explored the chemicals
that affect N6AMT1 expression. N6AMT1 was found
to be a predictor of diagnosis, prognosis and immuno
therapy response in multiple cancers. This study may
broaden the clinical application of N6AMT1 in various
cancers.
MATERIALS AND METHODS
Data collection
Transcriptomic data and clinical profiles of 33
tumors from The Cancer Genome Atlas (TCGA) were
obtained from the University of California Santa
Cruz (UCSC) Xena resource (cohort: TCGA pan-cancer)
(https:// xena.ucsc.edu/). In addition, somatic mutation
data were obtained from TCGA (https://portal.gdc.
cancer.gov/). Three immunotherapy response cohorts
were from the public Gene Expression Omnibus
database (https://www.ncbi.nlm.nih.gov/geo/). A cohort
from the IMvigor210 trial of atezolizumab-treated
advanced urothelial carcinoma [14]; a cohort of meta
static melanoma patients treated with anti-PD1
(GSE168204); and nivolumab-treated human renal
cell carcinoma samples (GSE67501). Generally, the
indicators used to assess immunotherapy efficacy are
progressive disease (PD), stable disease (SD), partial
response (PR), and complete response (CR). In this
study, PD and SD patients were classified as non
responders, and CR and PR patients were classified as
responders.
Subcellular localization analysis of N6AMT1
The UniProt database (https://www.uniprot.org/) includes
all known protein sequences with a complete
functional annotation compendium [15, 16]. The
Human Protein Atlas (HPA, https://www.proteinatlas.
org/) is a free open database containing various tissue
immunohistochemical (IHC) images and various cell
immunofluorescence (IF) images [17]. We analyzed
the subcellular localization of N6AMT1 using the
UniProt and HPA databases. IF pictures of N6AMT1
cell sublocalization in the human osteosarcoma cell
line U-2 OS and human squamous cell carcinoma cell
line A-431 were obtained from HPA. In addition, the
IHC images of N6AMT1 protein expression in 7 normal
tissues and corresponding tumor tissues were obtained
through the HPA database.
Clinical relevance of N6AMT1 expression and pan
cancer
First, we converted the transcriptome data (log2(FPKM+1))
acquired from UCSC Xena into a transcriptome data
form (FPKM), consistent with the TCGA data. The
limma package was used to analyze whether there was
a difference in N6AMT1 expression between the tumor
group and the normal group. Correlations between www.aging-us.com
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N6AMT1 expression and three clinical parameters (age,
sex, and tumor stage) were also investigated.
Analysis of the diagnostic value of N6AMT1
To evaluate the diagnostic accuracy of N6AMT1 in
pan-cancer, we performed sensitivity- and specificity
based ROC curve analysis using the “Proc” package.
The area under the curve (AUC) ranged from 0.5 - 1.0
[18]. Different AUC values represent different diagnostic
values: no diagnostic value (AUC = 0.5), low diagnostic
value (AUC: 0.5 - 0.7), relative diagnostic accuracy
(AUC: 0.7 - 0.9), high diagnostic value (AUC: 0.9 -1.0),
perfect diagnosis (AUC = 1.0).
Analysis of the prognostic value of N6AMT1
We determined the prognostic value of N6AMT1 in
pan-cancer using the survival and survminer packages
based on several prognostic indicators: overall survival
(OS), disease-free survival (DFS), disease-specific survival
(DSS) and progression-free survival (PFS). For cancer
types where N6AMT1 expression affects prognosis,
we further supplemented Kaplan-Meier survival curve
analysis. p < 0.05 was considered to indicate statistical
significance.
Gene set enrichment analysis (GSEA)
GSEA is a conventional tool for analyzing different
groups based on gene expression data to provide
insights of biological significance [19]. Gene Ontology
(GO) gene set “c5.go.v7.4.symbols.gmt” and signal
pathway gene set “c2.cp.kegg.v7.4.symbols.gmt” are
obtained from GSEA website (https://www.gseamsigdb.
org/gsea/index.jsp). The samples were divided into high
and low expression groups according to the median
N6AMT1 expression value, and then GSEA functional
analysis was performed using the “limma”, “enrichplot”,
“clusterProfiler” and “org.Hs.eg.db” packages. Finally,
the 5 most significantly correlated GO and signaling
pathways are shown.
Association of N6AMT1 expression with immune
related factors
Estimation of STromal and Immune cells in MAlignant
Tumours using Expression data (ESTIMATE) is an
algorithm based on single-sample gene set enrichment
analysis (ssGSEA) that estimates the extent of stromal
and immune cells in the tumor microenvironment
(TME) using tumor expression data [20]. Thus, we
obtained Immunescore and Stromalscore for each
sample. CIBERSORT is an emerging deconvolution
method for characterizing the composition of 22
immune cells based on tumor gene expression data [21].
Therefore, we used the CIBERSORT algorithm to
analyze the proportion of 22 infiltrating lymphocyte
subsets in the sample (perm = 1000, p < 0.05). TISIDB
(http://cis.hku.hk/TISIDB/index.php) is a user-friendly
portal with multi-type data resources integrating tumors
and the immune system [22]. We explored the
association between N6AMT1 and immunomodulators
on a pan-cancer basis using the TISIDB website. The
immunomodulators comprised 24 immunoinhibitors, 45
immunostimulators, and 21 major histocompatibility
complex (MHC) molecules. We analyzed the potential
associations of N6AMT1 with programmed cell death 1
ligand 1 (PDL1) expression, tumor mutational burden
(TMB), microsatellite instability (MSI), and mismatch
repair (MMR), which previous studies have identified
as potential biomarkers for predicting good response to
tumor immunotherapy [23]. TMB represents the number
of nonsynonymous mutations per megabase in somatic
cells [24]. MSI scores were derived from data from
previously published studies [25].
Interaction of N6AMT1 with chemicals
The Comparative Toxicogenomics Database (CTD;
http://ctdbase.org/) is a publicly available large database
linking toxicological information on chemicals, genes,
phenotypes, diseases and exposures in understanding
health [26]. We explored interacting chemicals with
N6AMT1 using the CTD database.
Cell culture, RNA extraction and quantitative real
timePCR (qRT-PCR)
All HCC cell lines HEPG2, BEL7402, HCCLM3
and normal liver cell line LO2 were donated by Dr.
Dai [27]. Cell culture, RNA extraction, and qRT-PCR
were performed as in previous studies [28]. The primer
sequences involved in this study are as follows. β-
actin primer forward sequences: CACCATTGGCAA
TGAGCGGTTC; β-actin primer Reverse sequences:
AGGTCTTTGCGGATGTCCACGT. N6AMT1 primer
forward sequences: GGCTTGCTACCAAGATTGACCG;
N6AMT1 primer Reverse sequences: CCAAGCTGCC
TCTATTCCGTGA.
Statistical analysis
The TMB is obtained by processing the PERL
programming language (version 5.32.1). All statistical
analyses were performed using R software (version
4.1.0). Analyses of differential N6AMT1 gene expression
were performed using Wilcoxon tests. Correlation
analyses were performed using the Spearman correlation
coefficient. p < 0.05 was considered to indicate a
statistically significant difference.www.aging-us.com
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RESULTS
Subcellular localization of N6AMT1 protein
N6AMT1 is a methylase that performs DNA 6mA
modification. We first checked the intracellular
localization of N6AMT1 protein in the UniProt and
HPA databases; the results showed that N6AMT1
protein was mainly distributed in the nucleus (Figure
1A, 1B). Furthermore, IF results showed that N6AMT1
was mainly localized in the nucleus in U-2 OS (Figure
1C) and A-431 cells (Figure 1D). This provides a
physical basis for N6AMT1 to perform DNA 6mA
modification.
Expression of N6AMT1 in 33 cancers
The full names and abbreviations of the 33 cancers
considered in this study are given in Table 1. Compared
with normal tissues, N6AMT1 was differentially
expressed in nine cancer types (CHOL, COAD, KICH,
KIRC, LIHC, LUSC, STAD, THCA and UCEC)
(Figure 2A); specifically, it showed significantly higher
expression in CHOL, COAD, LIHC and STAD and
low expression in KICH, KIRC, LUSC, THCA and
UCEC. In addition, we analyzed and ranked the
expression of N6AMT1 in tumor tissues and found that
it had the highest expression levels in ACC and
the lowest in HNSC (Figure 2B). Furthermore, we
considered the relationship of N6AMT1 expression with
clinical factors including age, gender and tumor
stage; the results showed that N6AMT1 was
differentially expressed in elderly patients aged ≥65
years in the THYM group (Figure 2C). Moreover,
N6AMT1 expression was correlated with patient gender
in the SARC and UVM groups (Figure 2D), with tumor
stage in the BLCA, LUAD and THCA groups (Figure
2E). Furthermore, for the nine cancer types in which
Figure 1. Subcellular localization of N6AMT1 protein. Annotations of N6AMT1 protein in the UniProt (A) and HPA (B) databases.
Immunofluorescence images showing intracellular localization of N6AMT1 in U2-OS (C) and A-431 (D) cells.www.aging-us.com
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Table 1. 33 types of human cancers employed in our research.
Abbreviation
Full name
ACC
Adrenocortical carcinoma
BLCA
Bladder urothelial carcinoma
BRCA
BRCA Breast invasive carcinoma
CESC
Cervical squamous cell carcinoma and endocervical adenocarcinoma
CHOL
Cholangiocarcinoma
COAD
Colon adenocarcinoma
DLBC
Diffuse large B-cell lymphoma
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
LUAD
Lung adenocarcinoma
LUSC
Lung squamous cell carcinoma
MESO
Mesothelioma
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
THCA
Thyroid carcinoma
THYM
Thymoma
UCEC
Uterine corpus endometrial carcinoma
UCS
Uterine carcinosarcoma
UVM
Uveal melanoma
N6AMT1 was differentially expressed, we compared
N6AMT1 protein expression levels between normal and
tumor tissues using data obtained from the HPA
database. The results showed that N6AMT1 was
significantly overexpressed in COAD (Figure 3A), LIHC
(Figure 3B) and STAD (Figure 3C) and significantly
underexpressed in renal adenocarcinoma (KICH and
KIRC) (Figure 3D), LUSC (Figure 3E), THCA (Figure
3F) and UCEC (Figure 3G). These results are consistent
with the difference in mRNA expression.
Pan-cancer diagnostic value of N6AMT1
We further evaluated the diagnostic ability of N6AMT1
in pan-cancer using ROC. Figure 4 shows that N6AMT1
exhibits high diagnostic accuracy in CHOL (AUC =
0.975). Relative diagnostic accuracy was demonstrated
in COAD (AUC = 0.745), KIRC (AUC = 0.740), LIHC
(AUC = 0.882), THCA (AUC = 0.742) and UCEC (AUC
= 0.767). Lower diagnostic accuracy was demonstrated
across 18 cancer types.
Pan-cancer prognostic value of N6AMT1
Next, we explored the relationship between N6AMT1
expression and patient prognosis in 33 cancer types.
Univariate Cox regression analysis was performed; the
results, illustrated by forest plots, showed that N6AMT1
expression was associated with OS in PAAD and PCPG
patients (Figure 5A). Specifically, N6AMT1 was a
protective factor for OS in PAAD patients (hazard ratio
[HR] = 0.711, p = 0.025) and a risk factor for OS in
PCPG patients (HR = 1.659, p = 0.020). However, there
are other important clinical indicators that can reflect
clinical benefit, such as DFS, DSS and PFS. Therefore,
we further analyzed the correlations between N6AMT1
expression and these indicators. The results showed
that N6AMT1 could affect DFS in LIHC and STAD www.aging-us.com
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(Figure 5B); specifically, N6AMT1 was a risk factor for
DFS in LIHC (HR = 1.411, p = 0.021) and a protective
factor for DFS in STAD (HR = 0.473, p = 0.039).
Furthermore, N6AMT1 was a risk factor for DSS in
PCPG (HR = 2.248, p = 0.002) (Figure 5C); a risk
factor for PFS in CESC (HR = 1.383, p= 0.016), LIHC
(HR = 1.474, p = 0.003) and PRAD (HR = 1.396, p =
0.019); and a protective factor in PAAD (HR = 0.699, p
= 0.017) (Figure 5D). Finally, for cancer types where
patient prognosis was affected by N6AMT1, we
supplemented the analysis using Kaplan–Meier survival
curves (Figure 5E–5H). In conclusion, our results
suggest that N6AMT1 is closely related to patient
prognosis, especially in PAAD, PCPG and LIHC.
Correlations between N6AMT1 and the TME
To comprehensively explore the correlation between
N6AMT1 and TME in pan-cancer, first, we analyzed
the correlations between N6AMT1 expression and
ESTIMATE scores, which included Immunescore and
Stromalscore (filter criteria: |correlation coefficient| >
0.4, p < 0.01). The results showed that N6AMT1 expression
was negatively correlated with Immunescore in LGG,
MESO, TGCT and THYM and negatively correlated
with Stromalscore in LGG, MSEO and SARC (Figure
6A). In addition, we explored the correlations between
N6AMT1 expression and degree of immune cell
infiltration using the CIBERSORT algorithm. In DLBC,
N6AMT1 expression was negatively correlated with
macrophages M0; in THYM, N6AMT1 expression was
positively correlated with macrophages M1 and negatively
correlated with regulatory T cells; in UCS, N6AMT1
expression was positively correlated with macrophages
M0 (Figure 6B).
Correlation of N6AMT1 expression with
immunomodulators
We queried TISIDB for correlations between N6AMT1
expression and immunomodulators, including
immunoinhibitors, immunostimulators and MHC
molecules. The correlation analysis of 24 immuno
inhibitors showed that N6AMT1 expression was
associated with most immunosuppressive agents on
a pan-cancer basis: in UVM, N6AMT1 expression
showed the strongest positive correlation with
TGFBR1; and in LGG, N6AMT1 and TGFB1
expression showed the strongest negative correlation
(Figure 7A). In addition, N6AMT1 expression had
pan-cancer correlations with most of the 45 immuno
stimulators: in ACC, N6AMT1 expression showed
the strongest positive correlation with CXCR4; in
UVM, N6AMT1 expression showed the strongest
Figure 2. Differential expression and clinical relevance of N6AMT1 in 33 tumor types. (A) Differential expression of N6AMT1 in
pan-cancer. (B) N6AMT1 expression in pan-cancer order from high to low. Correlations of N6AMT1 expression with patient age (C), gender
(D) and tumor stage (E). *: p < 0.05, **: p < 0.01, ***: p < 0.001. ns: No Significant.www.aging-us.com
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negative correlation with CD276 (Figure 7B). Likewise,
the correlations between 21 MHC molecules and
N6AMT1 expression were analyzed. In PCPG, N6AMT1
expression showed the strongest positive correlation with
TAP2; and in TGCT, N6AMT1 expression showed the
strongest negative correlation with HLA-A (Figure
7C). Considering the strong correlations of N6AMT1
with ACC, LGG, PCPG, TGCT and UVM, GSEA was
performed to investigate the GO and signal pathways
involving N6AMT1 in these cancers. According to the
results, the GO (Figure 8A) and signal pathways (Figure
8B) involving N6AMT1 varied widely in different cancers
but were mostly related to tumor and immunity.
Ability of N6AMT1 to predict response to
immunotherapy
PDL1, TMB, MSI and MMR are currently considered as
biomarkers to predict the response to immunotherapy
[23]. Therefore, we explored the correlations between
N6AMT1 expression and these biomarkers. PDL1 was
positively correlated with N6AMT1 expression in KIRC,
LAML, PCPG, STAD and UVM and negatively
correlated in BLCA, BRCA, CESC, COAD, ESCA,
LGG, MESO, SARC, TGCT and THCA. TMB was
positively correlated with N6AMT1 expression in
ESCA, PRAD and THYM and negatively correlated in
BRCA, LUAD, SARC and THCA. MSI was positively
correlated with N6AMT1 expression in THCA and
negatively correlated with BRCA and COAD (Figure
9A). N6AMT1 expression was positively correlated with
MMR-related genes (including MLH1, MSH2, MSH6,
PMS2 and EPCAM) in most cancer types and was
positively correlated with all MMR-related genes in
CESC, HNSC, KIRP, LAML, LGG, LIHC, PRAD
and THCA (Figure 9B). In addition, we analyzed
three immunotherapy cohorts and found that in the
GSE168204 cohort, N6AMT1 expression was significantly
Figure 3. Representative IHC staining of N6AMT1 in eight normal (left) and tumor (right) tissues of the colon (A), liver (B), stomach (C),
kidney (D), lung (E), thyroid (F) and endometrium (G).www.aging-us.com
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Figure 4. Analysis of the diagnostic value of N6AMT1 in pan-cancer.www.aging-us.com
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Figure 5. Prognostic analysis of N6AMT1 in pan-cancer. Forest plot showing the results of univariate Cox regression analysis of the
correlations between N6AMT1 and OS (A), DFS (B), DSS (C) and PFS (D). (E–H) Kaplan-Meier survival curves of N6AMT1 in cancer types that
affect cancer prognosis. p < 0.05 indicates statistical significance.www.aging-us.com
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lower in the responder group than in the non-responder
group (p = 0.014) (Figure 9C). By contrast, there was no
significant difference in N6AMT1 expression between
the responder and non-responder groups in the GSE67501
and IMvigor210 cohorts (Figure 9C).
N6AMT1 expression verification in LIHC
First, we detected the expression of CTSA in liver
cancer cell lines (BEL7402, HEPG2, HCCLM3) and
normal liver cell lines (LO2), and the results showed
that the expression level of CTSA in liver cancer cell
lines was significantly higher than that in LO2 cells
(Figure 9D). Secondly, we analyzed the expression of
N6AMT1 in LIHC online through GEPIA2.0 (Merged
TCGA and GTEx normal tissue expression data,
http:// gepia2.cancer-pku.cn/), and the results showed
that N6AMT1 was significantly higher in cancer tissues
than in adjacent normal tissues (Figure 9E).
Interacting chemicals of N6AMT1
We explored N6AMT1-related chemicals using the
CTD database. The results showed that a total of 45
chemicals were associated with N6AMT1 (Table 2).
Among them, 19 chemicals can up-regulate N6AMT1
Figure 6. Correlations between N6AMT1 expression and TME scores. (A) Correlations between N6AMT1 and ESTIMATE scores
including Immunescore and Stromalscore. (B) Correlation of N6AMT1 with infiltration of lymphocyte subsets.www.aging-us.com
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Figure 7. Correlations between N6AMT1 expression and immunomodulators: immunoinhibitors (A), immunostimulators (B) and MHC
molecules (C). Red represents positive correlation and blue represents negative correlation. The most positively and negatively correlated
cases are highlighted on the right.www.aging-us.com
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mRNA expression, and 24 chemicals can down-regulate
N6AMT1 mRNA expression. In addition, there are two
chemicals that can affect N6AMT1 mRNA expression,
but the specific role is not clear.
DISCUSSION
Original Research Epigenetic changes are reversible,
heritable processes that affect gene expression without
altering the DNA nucleotide sequence [29]. Abnormal
epigenetic changes are closely associated with many
human diseases, including cancer. Abnormal epigenetic
pathways occur in the early stages of tumorigenesis
and are therefore increasingly recognized as hallmarks
of tumorigenesis [30]. Aberrant DNA methylation
is currently the most widely studied epigenetic
alteration in cancer. DNA methylation modifications
are dynamically regulated by enzymes involved in
Figure 8. N6AMT1-related GO and signal pathways. (A) GO involving N6AMT1 in five tumor types as analyzed by GSEA. (B) Signal
pathways involving N6AMT1 in five tumor types as analyzed by GSEA.www.aging-us.com
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Figure 9. Correlation of N6AMT1 expression with immunotherapy markers and immunotherapy response. (A) Correlations of
N6AMT1 expression with PDL1, MSI and TMB. (B) Correlations of N6AMT1 expression with MMR-related genes. (C) Differences in N6AMT1
expression between responder and non-responder groups in the three immunotherapy cohorts. (D) Differential analysis of mRNA expression
of N6AMT1 in HCC in GEPIA2.0 database. (E) Expression levels of N6AMT1 in normal liver cell lines and HCC cell lines. *: p < 0.05, **: p < 0.01,
***: p < 0.001.www.aging-us.com
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Table 2. Interacting chemicals of N6AMT1 in CTD.
Chemical name
Chemical ID
Interaction actions
Chemical name
Chemical ID
Interaction actions
2,3,7,8-
tetrachlorodibenzof-uran
C014211
Increases expression
(+)-JQ1 compound
C561695
Increases expression
2,6-dinitrotoluene
C023514
Increases expression
Methidathion
C005828
Increases expression
4-(5-benzo (1,3) dioxol-5-
yl-4-pyridin-2-yl-1H
imidazol-2-yl) benzamide
C459179
Decreases expression
Methylmercuric
chloride
C004925
Decreases expression
Abrine
C496492
Increases expression
Monomethylarso
nous acid
C406082
Increases expression
Acetamide
C030686
Decreases expression
Nickel
D009532
Decreases expression
Acetaminophen
D000082
Affects expression
Pentachlorophenol
D010416
Decreases expression
Aristolochic acid I
C000228
Decreases expression
Perfluoro-n
nonanoic acid
C101816
Increases expression
Benzo(a)pyrene
D001564
Increases expression
Pirinixic acid
C006253
Increases expression
Bisphenol A
C006780
Affects expression
Prochloraz
C045362
Increases expression
Cyclosporine
D016572
Decreases expression
Quercetin
D011794
Decreases expression
Cylindrospermopsin
C089595
Increases expression
Resorcinol
C031389
Decreases expression
Dicrotophos
C000944
Decreases expression
S-2-pentyl-4-
pentynoic
hydroxamic acid
C513635
Decreases expression
Dorsomorphin
C516138
Decreases expression
Soman
D012999
Decreases expression
Doxorubicin
D004317
Decreases expression
Sunitinib
D000077210
Increases expression
Endosulfan
D004726
Increases expression
Tetrachlorodiben
zodioxin
D013749
Increases expression
Ethinyl estradiol
D004997
Increases expression
Tetradecanoylph
orbol Acetate
D013755
Increases expression
Ethyl methanesulfonate
D005020
Decreases expression
Tobacco smoke
pollution
D014028
Decreases expression
Fenthion
D005284
Increases expression
Tretinoin
D014212
Decreases expression
Folic acid
D005492
Decreases expression
Trichostatin A
C012589
Decreases expression
Formaldehyde
D005557
Decreases expression
Triptonide
C084079
Decreases expression
Fulvestrant
D000077267
Increases expression
Valproic acid
D014635
Decreases expression
Ionomycin
D015759
Increases expression
Vehicle emissions
D001335
Decreases expression
Ivermectin
D007559
Decreases expression
modification, including DNA methylases and DNA
demethylases, the so-called writers and erasers. In
eukaryotes, methylation at the fifth position of cytosine to
form 5-methylcytosine (5mC) is the most common DNA
methylation modification; in vertebrate somatic cells,
DNA 5mC modifications have been detected in more
than 70% of CpG islands [31] and are often associated
with transcriptional repression by transposable elements
[32]. Recent studies have shown that another DNA
methylation modification, namely the 6mA modification,
which is widely present in the genome of prokaryotes and
involved in the regulation of DNA replication, repair,
transcription and other functions [33], is also widely
present in eukaryotic genomes, including the human
genome [3, 34–36]. The biological role of this ubiquitous
and novel form of DNA methylation in human cancer is
largely unknown.
N6AMT1 is the only writer so far of DNA 6mA methy
lation. It has a potentially huge role in the development
of cancer, but little is known about its role in human
cancer. This study focuses on the potential biological
roles of N6AMT1 in 33 human tumor types. First, we
investigated the subcellular localization of N6AMT1
protein and found that it was mainly localized in the
nucleus, consistent with the functional properties of
N6AMT1 as a DNA methylase. Generally, information
at the protein level more directly reflects the biological
effects of a gene; however, as there is a lack of public
databases related to protein quantification, it is impossible
to perform a comprehensive analysis at the protein level.
Therefore, in this study, we carried out a comprehensive
pan-cancer exploration of N6AMT1 at the transcriptome
level, including early diagnosis, prognostic value, and
immunological role.
We analyzed differences in the expression levels of
N6AMT1 among the 33 tumor types. The results
showed that it was significantly overexpressed in
CHOL, COAD, LIHC and STAD. Consistent with
previous studies, Lin et al. found that N6AMT1 was
highly expressed in LIHC tissues, where it promoted www.aging-us.com
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AGING
proliferation, migration and invasion of LIHC cells
and inhibited apoptosis [12]. We also investigated
the correlations between N6AMT1 and various clinical
parameters. The expression of N6AMT1 was higher in
elderly patients with THYM and lower in male patients
with SARC and UVM. These results may have important
implications for guiding the selection of immunotherapy
regimens for patients in different age and gender groups.
Furthermore, the expression of N6AMT1 was significantly
different at different stages in LUAD and THCA, implying
that N6AMT1 may influence the progression of LUAD
and THCA.
Collectively, these findings confirm the differential
expression of N6AMT1 in a variety of cancers, suggesting
a promising future for N6AMT1 in cancer diagnosis. It
is worth noting that the search for early diagnostic
markers of cancer has essential clinical significance,
which can detect tumors as early as possible and greatly
improve the clinical prognosis of patients. Therefore,
we explored the diagnostic value of N6AMT1 in pan
cancer. The results showed that N6AMT1 showed
excellent diagnostic value in multiple cancer types,
especially in CHOL (AUC = 0.975) and LIHC (AUC =
0.882). In addition, we explored the prognostic value
of N6AMT1 in different cancers by univariate Cox
regression analysis and found that upregulation of
N6AMT1 expression was associated with poor prognosis
in CESC, LIHC, PCPG and PRAD. However, high
expression of N6AMT1 was associated with better
prognosis in PAAD and STAD. These results suggest
that N6AMT1 may have different roles in different
tumors. Taken together, these results clearly demonstrate
that N6AMT1 is a potential novel diagnostic and prognostic
marker in multiple cancer types. Excitingly, we found
that N6AMT1 showed amazing diagnostic value and
prognostic value in LIHC at the same time, which may
mean that N6AMT1 has extremely high research value
in LIHC.
In the past few years, immune checkpoint inhibitors
(ICIs) targeting immune checkpoints have emerged as
promising cancer treatments [37–39]. Future cancer
treatment strategies are likely to aim at increasing the
efficacy of ICIs. Owing to the plasticity of epigenetics,
the development of drugs targeting epigenetic modi
fications has also been the subject of attention. DNA
methyltransferase inhibitors and histone deacetylase
inhibitors are clinical drugs currently in use that mainly
target epigenetic modifications [40, 41]. Accumulating
evidence suggests that tumor cells evade chemotherapy
and host immune surveillance in general through epi
genetic processes [42]. Studies have shown that epigenetic
drugs can effectively reverse the immune evasion of
tumor cells, for instance, by promoting tumor-associated
neoantigen expression, improving immune cell recognition
and regulating immune cell function in the TME [29, 43,
44]. Therefore, an important potential application of
epigenetic drugs is their use in combination with ICIs to
enhance clinical benefit in cancer patients compared with
ICIs alone. Another important finding of this study was
the potential value of N6AMT1 in cancer immunotherapy.
We first investigated the correlation between N6AMT1
and TME. On the one hand, N6AMT1 was negatively
correlated with both Immunescore and Stromalscore
in LGG and MESO, with Stromalscore in SARC
and with Immunescore in TGCT and THYM. On the
other hand, N6AMT1 was negatively correlated with
macrophages M0 in DLBC, positively correlated with
macrophages M0 in UCS, positively correlated with
macrophages M1 in THYM and negatively correlated with
regulatory T cells. Macrophages M1 often indicate a pro
inflammatory phenotype and have anti-tumor associations
[45, 46], whereas regulatory T cells often indicate an
anti-inflammatory phenotype and have tumor-promoting
associations [47]; both can be used as markers to guide
cancer immunotherapy [47–49]. Therefore, N6AMT1
may represent a new target for immunotherapy in THYM
patients.
Overall, N6AMT1 is negatively correlated with immune
infiltration in a variety of cancers and inhibition of
N6AMT1 expression may help to improve immune cell
infiltration in cancer patients. In our study of immuno
suppressants, immune activators and MHC molecules,
most of the modulator-related molecules were inversely
correlated with N6AMT1 (except in GBM and HNSC).
These results support the development of drug combi
nations targeting N6AMT1 and modulator molecules. In
addition, the GO and signal pathways related to
N6AMT1 differed greatly in different tumors, but most
were involved in cancer progression and immune
related directions, suggesting that N6AMT1 may affect
cancer progression via its influence on the TME.
In this study, the associations of N6AMT1 with PDL1,
TMB, MSI and MMR were also explored. PDL1, TMB,
MSI and MMR are currently considered meaningful
biomarkers for predicting ICI response. PDL1 expression
is associated with response to ICI in a variety of cancers,
including non-small-cell lung cancer, advanced gastric
cancer and urothelial cancer [50–52]. Likewise, MMR
systems have shown clinical benefit in immune checkpoint
blockade in multiple cancer types [53]. MMR is an
important DNA repair pathway with a key role in
maintaining the fidelity of DNA replication and defects
of MMR (dMMR) lead to MSI [54]. A recent study
showed that most tumors with MSI-high/dMMR status
exhibited high TMB [55]. A plausible explanation for
this is that MSI-high/dMMR is associated with the
occurrence of mutations. With the accumulation of
mutations, TMB increases, which in turn leads to the www.aging-us.com
16
AGING
formation of neoantigens and activates anti-tumor
immune responses [56, 57]. Here, we investigated the
association of N6AMT1 with PDL1, TMB and MSI in
33 tumor types. N6AMT1 expression was negatively
correlated with PDL1, TMB and MSI in BRCA; with
PDL1 and TMB in SARC; and with PDL1 and MSI in
COAD. These results suggest that low expression of
N6AMT1 may be conducive to the immunotherapy
response in BRCA, SARC and COAD, especially
BRCA. In addition, N6AMT1 and MMR-related genes
were closely related in eight of the 33 cancer types
studied; this provides some insight regarding the
immunotherapeutic value of N6AMT1 in other tumors.
Subsequently, we explored the correlations between
N6AMT1 and immune responses in three immunotherapy
cohorts. N6AMT1 was associated with a difference
in treatment response only in the GSE168204 cohort
representing metastatic melanoma, that is, N6AMT1
expression was lower in the nivolumab-responsive
group of this cohort. These results were consistent with
those of previous analyses. However, our study only
explored three relevant cohorts, which made it difficult
to fully describe the effect of N6AMT1 on immuno
therapy response in cancer patients. Future studies
should focus on basic and clinical studies of N6AMT1
in relation to immunotherapy in various cancers.
Finally, we explored chemicals related to N6AMT1.
A total of 43 chemicals could affect N6AMT1 expression
levels. Some well-known chemicals are included,
including acetaminophen, cyclosporine, doxorubicin,
and folic acid, which increase N6AMT1 expression,
and sunitinib, tretinoin, and triptonide, which reduce
N6AMT1 expression. These results are expected to
provide some clinical guidance for cancer patients with
abnormal N6AMT1 expression.
To date, there have been limited studies on N6AMT1 in
cancer. This study is the first comprehensive analysis
focusing on the role of N6AMT1 in 33 tumor types and
its results demonstrate that N6AMT1 could be regarded
as a potential target for cancer therapy. This study also
provides a valuable basis for the diagnosis, prognosis
and immunological roles of N6AMT1 in pan-cancer,
especially in immunotherapy research provides some
new insights.
However, this study still has some shortcomings. On the
one hand, the main research results of this study come
from the bioinformatics analysis of public databases,
and the research on the biological function of N6AMT1
in specific cancers is lacking. Second, this study did not
use a real-world cohort to validate the diagnostic and
prognostic value of N6AMT1 in pan-cancer, as well as
its predictive ability for immunotherapy. In the future, it
is necessary to focus on the mechanism research and
clinical drug development of N6AMT1 in specific
cancers.
CONCLUSIONS
This study is the first to explore the diagnostic,
prognostic and immunotherapeutic value of N6AMT1
in pan-cancer. These results form part of a theoretical
basis for further basic research and clinical experiments.
AUTHOR CONTRIBUTIONS
Conceptualization, M.Z. and W.-J.S.; methodology, M.-
Q.W., J.-J.Z., and Y.-Q.Y.; software, data curation, Y.-
Q.Y. and P.L.; experiments, P.L.; writing—original
draft preparation, M.-Q.W. and J.-J.Z.; writing—review
and editing, M.Z. and W.-J.S. All authors have read and
agreed to the published version of the manuscript.
CONFLICTS OF INTEREST
All authors declare that the research was conducted in
the absence of any commercial or financial relationships
that could be construed as a potential conflict of interest.
FUNDING
No funding was provided for this study.
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