Medicine ®

OPEN

EMX2OS plays a prognosis-associated enhancer RNA role in gastric cancer

Ge-Xin Liu, MDª, Yu-Zhen Tan, MDª, Guo-Chao He, MDª, Qin-Lin Zhang, MDb, Pan Liu, MDª,*[D

Abstract

Enhancer RNAs (eRNAs), a subclass of lncRNAs, are derived from enhancer regions. The function of eRNAs has been reported by many previous studies. However, the role of eRNAs in gastric cancer, especially the prognosis-associated eRNAs, has not been studied yet.

In this study, we have used a novel approach to screened key eRNAs in gastric cancer. Kaplan-Meier correlation analysis and Co- expression analysis were used to find the most significant survival-associated eRNAs. Enrichment analysis is applied to explore the key functions and pathways of screened eRNAs. The correlation and survival analysis are used to evaluate targeted genes in the pan- cancer analysis

A total of 63 prognostic-associated eRNAs in gastric cancer were identified, the top 6 eRNAs were LINC01714, ZNF192P1, AC079760.2, LINC01645, EMX2OS, and AC114489.2. The correlation analysis demonstrated the top 10 screened eRNAs and their targeted genes. The results demonstrated that EMX2OS was ranked as the top eRNA according to the results of the Kaplan-Meier analysis. The correlation analysis demonstrated that eRNA EMX2OS is correlated with age, grade, stage, and cancer status. The pan-cancer analysis demonstrated that EMX2OS was associated with poor survival outcomes in adrenocortical carcinoma, cervical squamous cell carcinoma and endocervical adenocarcinoma, kidney renal clear cell carcinoma, stomach adenocarcinoma, and uveal melanoma.

In this study, survival-related eRNAs were screened and the correlation between survival-related eRNAs and their targeted genes was demonstrated. EMX2OS plays a prognosis-associated eRNA role in gastric cancer, which might be a novel therapeutic target in clinical practice.

Abbreviations: eRNAs = enhancer RNAs, lncRNAs = long noncoding RNAs.

Keywords: EMX2OS, enhancer RNAs, gastric cancer, survival

1. Introduction

Gastric cancer is one of the most common malignant cancers all around the world, with more than 1 million people newly

Editor: Chien-Feng Li. GXL and YZT contributed equally to this work.

The authors have no funding and conflicts of interest to disclose.

Ethical approval was not necessary, as this article is a bioinformatics analysis, which is based on data downloaded from the published and public database.

Consent for publication is not applicable.

All data generated or analyzed during the present study was downloaded from the UCSC Xena (https://xena.ucsc.edu/).

The datasets generated during and/or analyzed during the current study are publicly available.

ª Department of Emergency, Zhuzhou Central Hospital, Zhuzhou, China, b Department of Neurology, Zhuzhou Central Hospital, Zhuzhou, China.

Correspondence: Pan Liu, Department of Emergency, Zhuzhou Central Hospital, Zhuzhou 412007, China (e-mail: liupan85@126.com).

Copyright @ 2021 the Author(s). Published by Wolters Kluwer Health, Inc. This is an open access article distributed under the Creative Commons Attribution License 4.0 (CCBY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to cite this article: Liu GX, Tan YZ, He GC, Zhang QL, Liu P. EMX2OS plays a prognosis-associated enhancer RNA role in gastric cancer. Medicine 2021;100:41(e27535).

Received: 16 May 2021 / Received in final form: 31 August 2021 / Accepted: 27 September 2021

http://dx.doi.org/10.1097/MD.0000000000027535

diagnosed with gastric cancer every year.[1] In the past 5 decades, although the incidence and mortality have gradually declined, gastric cancer remains the third leading cause of cancer- associated death. The main cause of gastric cancer attributes to the chronic infection with H. pylori.[2] The detection of gastric cancer at an early and curable stage is an effective way to reduce the mortality rate.[3] Besides, H. pylori eradication treatment also plays an important role in preventing gastric cancer.[4]

Long noncoding RNAs (IncRNAs) has proved to be associated with many kinds of human disease,[5,6] especially cancers.[7,8] Enhancer RNAs (eRNAs), as a subclass of lncRNAs transcribed within gene enhancers, play important roles in lots of biological processes.[9-11] The previous study[12] has reported that eRNAs can interact with transcription factors and RNA polymerase II, so that increase the expression of the corresponding downstream gene. Zhao et al[13] has reported that alterations of androgen receptor-regulated eRNAs could lead to enzalutamide resistance in castration-resistant prostate cancer. To the best of our knowledge, there is no research on gastric-associated eRNAs.

In this study, we have screened a series of prognostic eRNAs and their targeted genes in gastric cancer. Kaplan-Meier correlation analysis and Co-expression analysis were used to find the most significant survival-associated eRNAs. The eRNA EMX2OS was selected and found to be associated with overall survival in gastric cancer patients. Enrichment analysis is applied to explore the key functions and pathways of screened eRNAs. The correlation and survival analysis are used to evaluate targeted genes in the pan-cancer analysis.

2. Materials and methods

2.1. Data downloading

The gene expression RNAseq profiles, survival data, and clinicopathological characteristics of 33 tumors in the TCGA database were downloaded from the UCSC Xena (https://xena. ucsc.edu/).

2.2. Data preparing

The ensemble_IDs in the gene expression RNAseq profiles were transferred into gene symbols. The eRNA_IDs were also transferred into gene symbols. The expression profiles of eRNAs of gastric cancer in the TCGA database were extracted. The survival time and status of patients were merged with the expression profiles of eRNAs of gastric cancer.

2.3. Identification of prognostic eRNAs in gastric cancer

We utilized the Kaplan-Meier method to evaluate the prognostic eRNAs in gastric cancer based on the expression level of each eRNAs. The patients were divided into the low-expression group and the high-expression group based on the median expression value.

2.4. Validation of the correlation of eRNAs with their targeted genes

The relationship between eRNAs and their targeted genes was evaluated by correlation analysis in gastric cancer. Only those eRNAs with R>0.4 and P <. 01 were screened and selected for the following analyses. The plots of correlation analyses were generated. The X-axis represents the expression level of eRNA, and the Y-axis represents the expression of its targeted genes.

2.5. Validation of the correlation of the hub eRNA with clinicopathological characteristics

EMX2OS, as one of the most remarkable eRNAs in the Kaplan- Meier analysis and correlation analysis, was selected as the hub eRNA for the following analyses. The correlation of the EMX2OS with clinicopathological characteristics in gastric cancer was performed.

2.6. Co-expression analysis of eRNA EMX2OS in gastric cancer

Co-expression analysis was performed in gastric cancer aimed to identify more targeted genes of eRNA EMX2OS. The screened criteria were set as R>0.4 and P <. 01.

2.7. Enrichment analysis

GO was performed by using the potential targeted genes of eRNA EMX2OS aimed to identify the key functions and pathways in the regulation of gastric cancer.

2.8. Validation of the correlation of EMX2OS with its targeted genes in the pan-cancer analysis

The relationship between eRNAs and their targeted genes was evaluated by correlation analysis in pan-cancer.

2.9. Validation of the survival analysis of EMX2OS in the pan-cancer analysis

We utilized the Kaplan-Meier method to evaluate the prognostic eRNAs in pan-cancer based on the expression level of each eRNAs. The patients were divided into the low-expression group and the high-expression group based on the median expression value.

3. Results

3.1. Identification of prognostic eRNAs in gastric cancer

A total of 63 prognostic associated eRNAs in gastric cancer were identified. The top 10 eRNAs with P <. 01 were demonstrated in Table 1. The KM plots of the top 6 eRNAs with P <. 01 were demonstrated in Figure 1. The results demonstrated that higher expression levels of LINC01714, ZNF192P1, AC079760.2, LINC01645, EMX2OS, and AC114489.2 were significantly associated with the poor survival of gastric cancer patients.

3.2. The correlation of eRNAs with their targeted genes

The relationship between eRNAs and their targeted genes was evaluated by correlation analysis in gastric cancer. Only those eRNAs with R>0.6 and P <. 05 were screened and selected for the following analyses. The correlation between the top 10 screened eRNAs and their targeted genes were presented in Table 2. The correlation between the top 6 screened eRNAs and their targeted genes were presented in Figure 2. The results demonstrated that eRNA EMX2OS with the most significant P-value which was calculated by the Kaplan-Meier analysis was selected to perform the following analyses.

3.3. The correlation of eRNA EMX2OS with clinicopathological characteristics

The clinicopathological characteristics of these patients were demonstrated in Table 3. The clinicopathological characteristics include age, grade, cancer status, and tumor stage. The results demonstrated that eRNA EMX2OS is correlated with the age, grade, stage, and cancer status. eRNA EMX2OS expression in patients with age ≤65 is higher than that in patients with age >65. However, there is no significant difference in terms of gender. In terms of tumor grade, eRNA EMX2OS expression is higher in the G3 grade than those in the G2 grade. For the tumor stage, the results demonstrated that the expression of eRNA EMX2OS is higher in patients with Stage IV than those in Stage I.

Table 1 The list of top 10 survival-related eRNAs screen based on P-value.
geneKM
LINC017140.000164
ZNF192P10.0006
AC079760.20.001022
LINC016450.001267
EMX2OS0.001502
AC114489.20.001884
LINC028450.001905
AL021937.30.00191
AC010457.10.002038
HAGLR0.002276
Figure 1. The survival analysis demonstrating the top 6 eRNAs with a P value <. 01.

LINC01714 level

high

low

ZNF192P1 level

high

low

AC079760.2 level

high

low

1.00

1.00

1.00

Survival probability

0.75

Survival probability

0.75

Survival probability

0.75

0.50

0.50

0.50

0.25

p<0.001

0.25

p<0.001

0.25

p=0.001

0.00

0.00

0.00

A

0

1

2

3

4

5

6

7

8

9

10

B

0

1

2

3

4

5

6

7

8

9

10

C

0

1

2

3

4

5

6

7

8

9

10

LINC01714 level

Time(years)

ZNF192P1 level

Time(years)

AC079760.2 level

Time(years)

high

163

98

37

20

8

4

2

0

0

0

0

high

175

110

42

19

11

6

3

1

1

1

0

high

175

105

41

18

6

2

1

1

1

1

0

low

187

130

63

27

15

10

5

3

3

3

1

low

175

118

58

28

12

8

4

2

2

2

1

low

175

123

59

29

17

12

6

2

2

2

1

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

Time(years)

Time(years)

Time(years)

LINC01645 level

high

low

EMX2OS level

high

low

AC114489.2 level

high

low

1.00-

1.00-

1.00-

Survival probability

0.75

Survival probability

0.75

Survival probability

0.75

0.50

0.50

0.50

0.25

p=0.001

0.25

p=0.002

0.25

p=0.002

0.00

0.00

0.00

D

0

1

2

3

4

5

6

7

8

9

10

E

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

LINCO1645 level

AC114489.2 level TI

Time(years)

Time(years)

Time(years)

EMX2OS level

high

175

106

45

20

10

6

1

1

1

1

1

high

175

109

40

14

6

3

1

1

1

1

0

high

175

107

40

21

10

4

0

0

0

0

2 8

0 1

low

175

122

55

27

13

8

6

2

2

0

low

175

119

60

33

17

11

6

2

2

2

1

low

175

121

60

26

13

10

7

3

3

3

0

1

2

3

4

5

6

7

9

10

0

1

2

3

4

5

6

7

8

9

10

0

1

2

3

4

5

6

7

8

9

10

Time(years)

Time(years)

Time(years)

Also, the expression of eRNA EMX2OS is higher in patients with Stage II than in those with Stage I. The eRNA EMX2OS expression in patients with tumors is higher than those patients with tumor-free (Fig. 3).

3.4. Co-expression analysis of eRNA EMX2OS in gastric cancer

Co-expression analysis was performed in gastric cancer aimed to identify more targeted genes of eRNA EMX2OS. The screened criteria were set as R>0.4 and P <. 01. A total of 2050 targeted genes were identified finally. The top 10 targeted genes of EXM2OS were demonstrated in Table 4 which ranked according to the correlation value.

3.5. Enrichment analysis

GO analyses were performed by using the potential targeted genes of eRNA EMX2OS aimed to identify the key functions in

the regulation of gastric cancer. The results were demonstrated in Figure 4. The top 3 terms enriched in BP are modulation of chemical synaptic transmission, regulation of trans-synaptic signaling, regulation of membrane potential. The top 3 terms enriched in CC were synaptic membrane, collagen-containing extracellular matrix, and presynapse. The top 3 terms enriched in MF were metal ion transmembrane transporter activity, ion channel activity, and substrate-specific channel activity.

3.6. The correlation of eRNA EMX2OS with its targeted genes and survival analyses in pan-cancer

The correlation between eRNA EMX2OS and its targeted genes in pan-cancer was calculated. We utilized the Kaplan-Meier method to evaluate the prognostic eRNAs in pan-cancer based on the expression level of each eRNAs. The patients were divided into the low-expression group and the high-expression group based on the median expression value. Finally, we identified that eRNA EMX2OS also plays important roles in 5 tumors,

Table 2 The correlation between the top 10 screened eRNAs and their targeted genes.
eRNAKMTargetcorcorPval
EMX2OS0.001502EMX20.7619342.31E-72
HAGLR0.002276HOXD10.7586050
RASSF8-AS10.003017RASSF80.881550
NR2F1-AS10.005252NR2F10.8553870
VLDLR-AS10.013156VLDLR0.7742314.22E-76
ZFHX4-AS10.016982ZFHX40.7825029.42E-79
LINC023810.017657HOXC40.6533030
AL445426.10.024848WNT2B0.6050518.14E-39
AC002451.10.035746PDK40.6634476.40E-49
IGFBP7-AS10.041357IGFBP70.7781362.44E-77

3

R= 0.76 , p < 2.2e-16

R=0.76 , p< 2.2e=16

6

R= 0.88 , p < 2.2e-16

1.0

2

EMX2

HOXD1

RASSF8

4

·

0.5

1

2

:

..

0.0

0

0

A

0.0

0.3

0.6

EMX2OS

0.9

B

0

1

2

3

4

C

0

1

2

RASSF8-AS1

3

HAGLR

4

5

6

R =0.86 , p < 2.2e-16

4

4

4

3

NR2F1

VLDLR

R= 0.77 , p <2.2e-16

ZFHX4

R=0.78 , p <2.2e-16

·

2.

:

2

2

1

0

0

D

0.0

0.5

1.0

NR2F1-AS1

1.5

2.0

E

0.0

0.5

VLDLR-AS1

1.0

F

0

1

ZFHX4-AS1

2

3

Figure 2. The correlation between the top 6 screened eRNAs and their targeted genes.

including adrenocortical carcinoma (Fig. 5D, Fig. 6A), cervical squamous cell carcinoma and endocervical adenocarcinoma (Fig. 5C, Fig. 6B), kidney renal clear cell carcinoma (Fig. 5B, Fig. 6C), stomach adenocarcinoma (Fig. 5E, Fig. 6D), and uveal melanoma (Fig. 5A, Fig. 6E). These results mentioned above reflected that eRNA EMX2OS may play critical roles in many

Table 3 The clinicopathological characteristics of patients.
CovariatesTypeTable_Stat
Age≤65164 (43.73%)
>65207 (55.2%)
Unknown4 (1.07%)
GradeG110 (2.67%)
G2137 (36.53%)
G3219 (58.4%)
Unknown9 (2.4%)
Cancer_statusTumor free167 (44.53%)
Unknown136 (36.27%)
With tumor72 (19.2%)
GenderFemale134 (35.73%)
Male241 (64.27%)
StageStage I53 (14.13%)
Stage II111 (29.6%)
Stage III150 (40%)
Stage IV38 (10.13%)
Unknown23 (6.13%)

types of tumors and may have the chance to be regarded as a novel treatment target in the future.

4. Discussion

eRNAs, as a specific subclass of lncRNAs, are derived from gene enhancer regions. eRNAs play an important role in regulating the transcription of the corresponding genes and tumorigenesis.[14] The previous study[15] has reported that eRNAs play an important role in increasing the rate of the transcription of genes. As the evidence began to accumulate, the importance of the role of the eRNAs in tumor development and treatment has been reported by many researchers. For instance, Zhang et al[9] demonstrated that eRNAs can be regarded as a useful tool for eRNA-targeted therapy in cancer. Also, Wang et al[14] showed that WAKMAR2 might be a novel target gene in regulating the breast cancer microenvironment and may function by influencing the expression of immune-related genes. However, the specific role of eRNAs in cell fate determination has not been completely elucidated yet. In this study, we performed a series of assays to identify the prognosis-related eRNAs in gastric cancer. To illustrate the network of eRNAs in gastric cancer, we identified a subset of eRNAs that are significantly associated with the overall survival of gastric cancer. Then, we have identified a subset of eRNAs’ potential target genes. To the best of our knowledge, this is the first study to explore the influence of eRNAs in gastric cancer.

Stage

Stage I

Stage II

Stage III

Stage IV

Gender

female

male

Figure 3. The correlation between eRNA EMX2OS and clinicopathological characteristics.

0.14

1.21

0.69

0.83

0.067

1.5

0.033

0.19

0.9

EMX2OS expression

0.011

EMX2OS expression

1.0

0.6

0.5

0.3

0.0

0.0

A

Stage I

Stage II

Stage III

Stage IV

female

male

Stage

B

Gender

Cancer_status

TUMOR FREE

WITH TUMOR

Age

65

>65

1.2-

0.028

1.2-

0.00053

0.9

0.9

EMX2OS expression

EMX2OS expression

0.6

0.6

0.3

0.3

0.0

0.0

TUMOR FREE

WITH TUMOR

65

>65

C

Cancer_status

D

Age

Grade

G1

G2

G3

0.00045

0.24

0.98

EMX2OS expression

1.0

0.5

0.0

E

G1

G2

G3

Grade

In this study, the top key eRNA candidate in gastric cancer is EMX2OS. EMX2OS, as a IncRNA, has been reported to play an important role in many cancers. Duan et al[16] reported that lncRNA EMX2OS can induce proliferation, invasion, and sphere formation of ovarian cancer cells via regulation of the miR-654- 3p/AKT3/PD-L1 Axis. Also, Gu et al[17] demonstrated that the downregulation of lncRNA EMX2OS can predict shorter recurrence-free survival of thyroid cancer. Plus, a previous

study[18] reported that lncRNA EMX2OS was significantly upregulated in gastric cancer tissues compared with normal tissues, which is consistent with our results. However, the effects and mechanisms of EMX2OS in gastric cancer remain largely unknown.

EMX2OS is located in the enhancer region of the EMX2 gene. EMX2, a protein-coding gene, was reported to be a significant role in many kinds of tumors. Aykut et al[19] demonstrated that

Table 4 The results of co-expression analysis demonstrating the top 10 targeted genes of EMX2OS.
eRNAgenecorP-value
EMX2OSEMX20.7622.31E-72
EMX2OSSLITRK20.71.41E-56
EMX2OSST6GAL20.6911.91E-54
EMX2OSRGS220.6812.43E-52
EMX2OSRNF1650.6788.52E-52
EMX2OSCYP1B1-AS10.6694.89E-50
EMX2OSSCN2B0.6689.86E-50
EMX2OSLINC016380.6652.76E-49
EMX2OSCDO10.6621.26E-48
EMX2OSLRRC4C0.6595.56E-48

EMX2 is down-regulated in colorectal cancer and can be a prognostic marker for disease-free and overall survival of colorectal cancer. Also, Falcone et al[20] demonstrated that EMX2 could be treated as a novel promising tool for the treatment of glioblastoma and prevention of its recurrences.

The results of this study have shown a strong correlation between the expression of EMX2OS and EMX2. Also, EMX2OS has shown the most significant impact on overall survival in gastric cancer among all identified eRNAs. Plus, we have identified co-expression genes of EMX2OS in addition to its targeted gene EMX2. Finally, we have found a total of 2050 genes with a significant expression correlation with EMX2OS. Some studies indicated that the primary function of eRNA was performed in cis, however, several studies stated that eRNAs could also regulate the expression of genes in trans.[21] To determine the function of screened genes with significant expression correlation with EMX2OS, we performed gene ontology enrichment analysis.

Recently, some researchers have reported that the diet, treatment, and heterogeneity of tumors play important roles in affecting the expression of eRNAs. For instance, Klein et al.[22] demonstrated the effect of early-life undernutrition on the induction of the eRNA remodeling in mice liver. They stated that the expression of metabolism-associated genes was regulated by the enhancer activity in early life. In terms of the treatment, Xie et al[23] demonstrated that knockdown enhancer-RNA-P53- bound enhancer regions 2 could reverse the nutlin-3-induced cytotoxic effect in TP53-WT cell lines. Chen et al(24] showed that

Figure 4. The results of GO analysis were conducted by using the potential targeted genes of eRNA EMX2OS.

modulation of chemical synaptic transmission

regulation of trans-synaptic signaling

regulation of membrane potential

axonogenesis

muscle system process

synapse organization

BP

muscle contraction

cell-cell adhesion via plasma-membrane adhesion molecules

multicellular organismal signaling

cardiac conduction

.

Count

synaptic membrane

60

collagen-containing extracellular matrix

80

presynapse

100

postsynaptic membrane

glutamatergic synapse

neuron to neuron synapse

CC

qvalue

contractile fiber

contractile fiber part

5e-07

myofibril

sarcomere

1e-06

metal ion transmembrane transporter activity

ion channel activity

substrate-specific channel activity

actin binding

cation channel activity

ion gated channel activity

MF

gated channel activity

glycosaminoglycan binding

extracellular matrix structural constituent

heparin binding

0.03

0.04

0.05

0.06

0.07

GeneRatio

Cancer: UVM

Cancer: KIRC

Figure 5. Survival analyses of EMX2OS stratified by the relative expression of EMX2OS in pan-cancer, including (D) adrenocortical carcinoma, (C) cervical squamous cell carcinoma, and endocervical adenocarcinoma, (B) kidney renal clear cell carcinoma, (E) stomach adenocarcinoma, and (A) uveal melanoma.

EMX2OS level L

high

1

low

EMX2OS level

4

high

L

low

1.00-

1.00

Survival probability

Survival probability

0.75

0.75

0.50

0.50

0.25

p=0.013

0.25

p<0.001

0.00

0.00

A

0

1

2

3

4

5

6

7

8

B

0

1

2

3

4

5

6

7

8

9

10

11

12

EMX2OS level

Time(years)

EMX2OS level

Time(years)

high

40

40

29

35

21

7

19

3

3

1

NO

0

0

0

high low

265 228

266

196

157

120

83

57

42

36

24

18

9

2

1

low

24

2

1

212

164

134

98

67

26

17

13

4

1

0

0

1

2

3

4

5

6

7

8

0

1

2

3

4

5

6

7

8

9

10

11

12

Time(years)

Time(years)

Cancer: CESC

Cancer: ACC

EMX2OS level L high

L

low

EMX2OS level

4

high

L low

1.00-

1.00-

Survival probability

Survival probability

0.75

0.75

0.50

0.50

0.25

p=0.020

0.25

p=0.002

0.00

0.00

C

0

1

2

3

4

5

6

7

8

9

10

11

12

13

14

15

16

17

18

19

20

Time(years)

D

0

1

2

3

4

5

6

7

8

9

10

11

12

EMX2OS level

EMX2OS level

Time(years)

high

146 2176 46 30 22 17 15 12 10

14710866 46 32 22 18 12 11 9 7 6 6 3 2 1 1 1 0 0 0

S 9 7

0

5

1

1

1

0

high

39

7

low

low

40

35

40

24

18

26

11

3

0

0

O

34

19

1

17

13

2

9

7

7

4

2

00

2

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20

0

1

2

3

4

5

6

7

8

9

10

11

12

Time(years)

Time(years)

Cancer: STAD

EMX2OS level 1

high

+

low

1.00-

Survival probability

0.75

0.50

0.25

p=0.002

0.00

E

0

1

2

3

4

5

6

7

8

9

10

EMX2OS level

Time(years)

high

175

175

109

40

60

14

6

119

33

17

3

1

0

low

11

6

1

1

1

2

2

2

1

0

1

2

3

4

5

6

7

8

9

10

Time(years)

the eRNAs could affect the cancer phenotypes by regulating the intra-tumoral heterogeneity. In summary, the diet, treatment, and heterogeneity of tumors could affect the function of eRNAs.

There are some limitations to this study. Firstly, the number of cases in this study is too small, for not further data could be downloaded from other databases. Secondly, no external data and historic comparisons were used to make the validation of our conclusion. Further study should be made to validate our conclusion, including external data and historic validations.

Third, the effect of diet, treatment, and heterogeneity of tumors on the expression of eRNAs has not been deeply explored in this study. However, we have tried our best to make a literature review in the discussion part of this study.

To conclude, we have identified key eRNAs in gastric cancer. The impact of these eRNAs on overall survival was also demonstrated. The results suggested that eRNA EMX2OS is a prognosis-related gene for gastric cancer. eRNA EMX2OS may be a therapeutic target for patients with gastric cancer.

Figure 6. The correlation between eRNA EMX2OS and its targeted gene EMX2 in pan-cancer, including (A) adrenocortical carcinoma, (B) cervical squamous cell carcinoma, and endocervical adenocarcinoma, (C) kidney renal clear cell carcinoma, (D) stomach adenocarcinoma, and (E) uveal melanoma.

Cancer: ACC

Cancer: CESC

Cancer: KIRC

2.5

6

R=0.81 , p <2.2e-16

6

R=0.95 , p < 2.2e-16

2.0

R =0.84 , p < 2.2e-16

1.5

4

4

EMX2

EMX2

EMX2

1.0

2

2

0.5

0.0

0

0

A

0.0

0.5

1.0

1.5

B

0

1

2

3

4

5

0

1

2

3

4

5

EMX2OS

EMX2OS

C

EMX2OS

Cancer: STAD

Cancer: UVM

0.6

R = 0.81 , p < 2.2e-16

R=0.76 , p< 2.2e=16

1.0

0.4

EMX2

EMX2

0.5

0.2

0.0

0.0

D

0.0

0.3

0.6

EMX2OS

0.9

E

0.0

0.1

EMX2OS

0.2

Acknowledgments

Not applicable.

Author contributions

Conceptualization: GeXin Liu, Pan Liu.

Data curation: GeXin Liu, GuoChao He.

Formal analysis: GuoChao He.

Methodology: Yu-Zhen Tan.

Software: Yu-Zhen Tan.

Supervision: QinLin Zhang, Pan Liu.

Visualization: QinLin Zhang.

Writing - original draft: GeXin Liu, Yu-Zhen Tan.

Writing - review & editing: Pan Liu.

References

[1] Thrift AP, El-Serag HB. Burden of gastric cancer. Clin Gastroenterol Hepatol 2020;18:534-42.

[2] Plummer M, Franceschi S, Vignat J, Forman D, de Martel C. Global burden of gastric cancer attributable to Helicobacter pylori. Int J Cancer 2015;136:487-90.

[3] Matsuzaki J, Tsugawa H, Suzuki H. Precision medicine approaches to prevent gastric cancer. Gut Liver 2020;15:3-12.

[4] Zhang X, Li M, Chen S, et al. Endoscopic screening in Asian countries is associated with reduced gastric cancer mortality: a meta-analysis and systematic review. Gastroenterology 2018;155: 347.e9-54.e9.

[5] Yarani R, Mirza AH, Kaur S, Pociot F. The emerging role of lncRNAs in inflammatory bowel disease. Exp Mol Med 2018;50:1-14.

[6] Wang S, Jin J, Xu Z, Zuo B. Functions and regulatory mechanisms of lncrnas in skeletal myogenesis, muscle disease and meat production. Cells 2019;8: doi: 10.3390/cells8091107.

[7] Li Y, Jiang T, Zhou W, et al. Pan-cancer characterization of immune- related lncRNAs identifies potential oncogenic biomarkers. Nat Commun 2020;11:1000.

[8] Lin W, Zhou Q, Wang CQ, et al. LncRNAs regulate metabolism in cancer. Int J Biol Sci 2020;16:1194-206.

[9] Zhang Z, Lee JH, Ruan H, et al. Transcriptional landscape and clinical utility of enhancer RNAs for eRNA-targeted therapy in cancer. Nat Commun 2019;10:4562.

[10] Melo CA, Drost J, Wijchers PJ, et al. eRNAs are required for p53- dependent enhancer activity and gene transcription. Mol Cell 2013; 49:524-35.

[11] Ding M, Liu Y, Liao X, Zhan H, Liu Y, Huang W. Enhancer RNAs (eRNAs): new insights into gene transcription and disease treatment. J Cancer 2018;9:2334-40.

[12] Chen H, Du G, Song X, Li L. Non-coding transcripts from enhancers: new insights into enhancer activity and gene expression regulation. Genomics Proteomics Bioinformatics 2017;15:201-7.

[13] Zhao J, Zhao Y, Wang L, et al. Alterations of androgen receptor- regulated enhancer RNAs (eRNAs) contribute to enzalutamide resistance in castration-resistant prostate cancer. Oncotarget 2016;7:38551-65.

[14] Wang L, Liu J, Tai J, et al. A prospective study revealing the role of an immune-related eRNA, WAKMAR2, in breast cancer. Sci Rep 2021;11:15328.

[15] Cheng JH, Pan DZ, Tsai ZT, Tsai HK. Genome-wide analysis of enhancer RNA in gene regulation across 12 mouse tissues. Sci Rep 2015;5:12648.

[16] Duan M, Fang M, Wang C, Wang H, Li M. LncRNA EMX2OS induces proliferation, invasion and sphere formation of ovarian cancer cells via regulating the miR-654-3p/AKT3/PD-L1 axis. Cancer Manag Res 2020; 12:2141-54.

[17] Gu Y, Feng C, Liu T, Zhang B, Yang L. The downregulation of IncRNA EMX2OS might independently predict shorter recurrence-free survival of classical papillary thyroid cancer. PLOS One 2018;13:e0209338.

[18] Li H, Yu B, Li J, et al. Characterization of differentially expressed genes involved in pathways associated with gastric cancer. PLoS One 2015;10: e0125013.

[19] Aykut B, Ochs M, Radhakrishnan P, et al. EMX2 gene expression predicts liver metastasis and survival in colorectal cancer. BMC cancer 2017;17:555.

[20] Falcone C, Daga A, Leanza G, Mallamaci A. Emx2 as a novel tool to suppress glioblastoma. Oncotarget 2016;7:41005-16.

[21] Ransohoff JD, Wei Y, Khavari PA. The functions and unique features of long intergenic non-coding RNA. Nat Rev Mol Cell Biol 2018;19: 143-57.

[22] Klein EA, Cooperberg MR, Magi-Galluzzi C, et al. A 17-gene assay to predict prostate cancer aggressiveness in the context of Gleason grade heterogeneity, tumor multifocality, and biopsy undersampling. Eur Urol 2014;66:550-60.

[23] Xie H, Ma K, Zhang K, et al. Cell-cycle arrest and senescence in TP53- wild type renal carcinoma by enhancer RNA-P53-bound enhancer regions 2 (p53BER2) in a p53-dependent pathway. Cell Death Dis 2021;12:1.

[24] Chen H, Liang H. A high-resolution map of human enhancer RNA loci characterizes super-enhancer activities in cancer. Cancer Cell 2020;38: 701.e5-715.e5.