Role of SLC44A3-AS1 Enhancer RNA in Esophageal Cancer Prognosis

By Kai Kang¹, Jingyi Wu², Yajun Mao³, Jindan Kai¹, Si Chen¹, Fei Xiong¹

Affiliations

1. Department of Thoracic Surgery, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China
2. Department of Thoracic Oncology, Hubei Cancer Hospital, Tongji Medical College, Huazhong University of Science and Technology, Hubei, China
3. Operating Room, Shanghai Pulmonary Hospital, Tongji University School of Medicine, Shanghai, China

doi: 10.29271/jcpsp.2023.09.964

ABSTRACT
Objective: To identify key enhancer RNAs (eRNA) in esophageal cancer through a comprehensive analysis and explore its importance in esophageal cancer.
Study Design: An observational study.
Place and Duration of the Study: Department of Thoracic Surgery, Hubei Cancer Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology, Wuhan, Hubei Province, China, from September to October 2022.
Methodology: RNA-sequencing data, survival data, and clinical data for a total of 33 tumours were gathered from TCGA (The Cancer Genome Atlas) datasets. The survival-associated eRNAs were detected by means of Spearman's correlation and Kaplan-Meier survival analyses. Enhancer RNAs linked to survival rate and their target genes in esophageal cancer were screened, and a clinical correlation analysis of key eRNAs was carried out. A functional enrichment analysis was performed and the selected key eRNAs were confirmed in pan-cancer.
Results: The key eRNA was identified as SLC44A3-AS1, and patients with higher expression of SLC44A3-AS1 had worse prognosis than those with low expression. SLC44A3-AS1 expression was significantly associated with many clinical traits, namely tumour status, grade, pathological tumour, node, metastasis (TNM) stage, tumour type, etc. According to KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway enrichment results, SLC44A3 may affect the prognosis of esophageal cancer patients through the herpes simplex virus 1 (HSV1) infection pathway. According to pan-cancer validation results, SLC44A3-AS1 was related to the survival of eight tumours. Correlations were observed between SLC44A3-AS1 and SLC44A3 in 32 types of tumours.
Conclusion: SLC44A3-AS1 plays a key role in esophageal cancer related to prognosis, which may be a new therapeutic target for clinical exploration.

Key Words: SLC44A3-AS1, Enhancer RNA, Esophageal cancer, Prognosis.

INTRODUCTION

Esophageal cancer ranks 8^th in terms of cancer incidence and 6^th in overall death rate.¹ Surgery can be performed to treat esophageal cancer, and about 1/4 of newly diagnosed patients can be treated by surgery.² Chemotherapy, radiotherapy, targeted therapy and combinations, thereof, are considered treatment options for patients whose tumours are too advanced to undergo surgery.³ However, the five-year survival rate of patients with esophageal cancer is still very low, ranging from about 10% to 30% in most countries.^4,5

Long non-coding RNAs (lncRNAs) are related to many diseases in humans, such as cancers.^6-8 Enhancer RNAs (eRNAs), a lncRNA subclass, play important roles in many biological processes.^9,10 There are thousands of eRNAs that have been identified in the human cells, and many of them mediate target gene activation.⁹ eRNAs can regulate the expression of oncogene and tumour suppressors and participate in the regulation of cancer signalling. They also play key roles in tumour progression and tumourigenesis,⁹ such as lung cancer,¹¹ breast cancer,¹² indicating that eRNAs have potential values in cancer diagnosis and prognosis.

SLC44A3-AS1 may be a potential biomarker and therapeutic target for esophageal cancer. This study aimed to identify the prognostic eRNAs involved in esophageal cancer progression and seek their therapeutic targets.

METHODOLOGY

The study was approved by the Institutional Ethics Committee of Hubei Cancer Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology (Ethical Approval Number: LLHBCH2022YN-045). It analysed data on 33 tumour types obtained from the TCGA (The Cancer Genome Atlas) database, from September to October 2022.

The RNA-seq gene expression profiles, clinical data, and survival datasets in this study were from TCGA (The Cancer Genome Atlas) database using the UCSC Xena website.¹³ The gene expression RNAseq (Workflow Type: HTSeq-FPKM), clinical and survival data from GDC TCGA esophageal cancer were all downloaded from TCGA database, and the same approach was applied to the gene expression RNAseq, clinical and survival data for the other 32 types of cancer. All data can be freely downloaded online.

Ensemble IDs in the RNA-seq gene expression profiles were converted to their corresponding gene symbols using gene transfer format (GTF) files for humans. The eRNA IDs were transported into gene symbols using human GTF files. The eRNA expression profiles of esophageal cancer were obtained in the TCGA database. The eRNA expression matrixes were merged with the esophageal cancer survival data by means of the limma package in R software. The clinical data for esophageal cancer were screened, and 9 types of clinical information for analysis were retained, including age, gender, cancer status, grade, smoker/non-smoker, race, stage, tumour centre and type. Age was divided into two groups of <60 and ≥60 years. Tumour stage was classified into four stages as I, Ⅱ, Ⅲ, and Ⅳ, while those without data information were marked as unknown.

The Kaplan-Meier method was used for evaluating the prognostic eRNAs in esophageal cancer, and survival-associated eRNAs were selected with p<0.05 as the standard cut-off values. The patients with esophageal cancer were categorised into high-expression and low-expression groups following the median expression of each eRNA. The survival differences between the two groups were evaluated and the survival curve was drawn, with p<0.05 used as the cut-off value.

The correlation between eRNAs and their target genes was assessed through correlation analysis. eRNAs with r >0.4 and p<0.01 were screened for further analyses, and correlation analysis plots were therefore generated. The x- and y-axis respectively represent the expression levels of eRNAs and eRNAs-targeted genes. The main eRNAs linked to survival and target genes, which play important roles in esophageal cancer, were obtained through Spearman’s correlation analysis. The statistical significance was determined at p <0.001 and r >0.4.

SLC44A3-AS1, as an eRNA with a significant p-value, was not reported in esophageal cancer. Hence, the correlation between SLC44A3-AS1 and clinical traits of esophageal cancer was further analysed.

For the identification of more targeted genes of SLC44A3-AS1 in esophageal cancer, co-expression analysis was performed. The co-expressed genes of SLC44A3-AS1 in esophageal cancer were screened through Spearman’s correlation analysis. Statistical significance was considered at p<0.001 and rank correlation coefficient r >0. The correlation between SLC44A3-AS1 and SLC44A3 in 33 types of tumours was examined.

The org. Hs.eg.db package of R software was used to analyse gene IDs corresponding to the target genes related to the main eRNA. Then, GO [Cellular Component (CC), Biological Process (BP), and Molecular Function (MF)] and KEGG pathway enrichment analyses were made. KEGG pathways and GO terms were considered significantly enriched when the p-value <0.05.

The SLC44A3-AS1 expression data and its target gene SLC44A3 were obtained, while the expression matrix was combined with the survival data of the pan-cancer. According to each eRNA’s median expression value, patients were divided into low-expression and high-expression groups. The Kaplan-Meier method was used to assess the prognostic eRNAs in pan-cancer. The association between eRNAs and their targeted genes was determined by correlation analysis.

All of the statistical analyses were performed using R 3.6.1. The Kaplan-Meier method was employed to analyse the differences between the two groups with high and low expression of SLC44A3-AS1, and spearman correlation analysis was applied to verify the correlation between SLC44A3-AS1 and their target genes. The difference in SLC44A3-AS1 expression was analysed in different clinical traits by Wilcoxon signed-rank test. Pearson correlation analysis was used to find out the genes that were co-expressed with SLC44A3-AS1. Functional enrichment analysis was performed using the clusterprofiler R package. The Kaplan-Meier method was used to assess the prognostic eRNAs in pan-cancer. The association between eRNAs and their targeted genes in pan-cancer was determined by Pearson correlation analysis.

RESULTS

A total of 34 eRNAs were significantly linked to the survival of esophageal cancer patients according to the esophageal cancer-associated RNA-seq expression profiles. The link between eRNAs and their target genes was determined by the means of correlation analysis. The results showed that 11 highly-expressed eRNAs, including AC007255.1, SLC44A3-AS1, FOXP4-AS1, AC025871.2, AL021391.1, AP000696.1, LINC01006, LINC01271, CCDC18-AS1, SPAAR, WDFY3-AS2, were significantly associated with poor survival of patients with esophageal cancer. In order to obtain new prognostic-related genes, eRNA SLC44A3-AS1 was selected for the following analyses because it had the most significant p-value but was not reported in esophageal cancer. Among esophageal cancer patients, the OS time of high expression of SLC44A3-AS1 was worse than that of low expression (p = 0.041, Figure 1a), and the correlation coefficient with the target gene SLC44A3 was 0.83 (p <2.2e-16; Figure 1b).

The clinical traits of these patients are demonstrated in Table I. The eRNA SLC44A3-AS1 expression was related to the cancer status and age of the patients. In Figure 2, eRNA SLC44A3-AS1 expression in tumour patients was higher than those without tumours, while the eRNA SLC44A3-AS1 expression was lower in patients younger than 60 years (Figure 2a). In different grades, the expression of SLC44A3-AS1 in G1 patients was significantly lower compared with G2 and G3 patients (Figure 2c). As observed in Figure 2d, patients with N1 showed significantly higher expression of SLC44A3-AS1 than those with N0. Concerning the races (Figure 2e), white patients showed highly expressed SLC44A3-AS1. In Figure 2f, stage III patients showed significantly higher SLC44A3-AS1 expression than stage II patients. As observed in Figure 2g, the expression of SLC44A3-AS1 was significantly linked to central tumour location. A higher expression of SLC44A3-AS1 was observed in distal esophageal cancer patients than in the middle. Among different tumour types (Figure 2h), the eRNA SLC44A3-AS1 expression in adenocarcinoma patients was significantly higher compared to the other patients’ types.

Figure 1: The risk role of SLC44A3-AS1 for esophageal cancer; (a) Kaplan-Meier overall survival between high SLC44A3-AS1 expression and its low expression in esophageal cancer patients; (b) Spearman correlation analysis between SLC44A3-AS1 and SLC44A3.

Table I: Association between clinical traits of esophageal cancer patients and SLC44A3-AS1 expression.

Covariates	Type	Table Stat
Age	<60	75(46.3%)
	>=60	87(53.7%)
Gender	Female	23(14.2%)
	Male	139(85.8%)
Cancer_status	Tumour free	61(37.65%)
	With tumour	35(21.6%)
	Unknown	66(40.74%)
Grade	G1	16(9.88%)
	G2	66(40.74%)
	G3	44(27.16%)
	Unknown	36(22.22%)
Smoker/ Non Smoker	<20	26(16.05%)
	>=20	60(37.04%)
	Unknown	76(46.91%)
Race	Asian	38(23.46%)
	Black or african american	6(3.7%)
	White	100(61.73%)
	Unknown	18(11.11%)
Stage	I	10(6.17%)
	II	53(32.72%)
	III	51(31.48%)
	IV	14(8.64%)
	Unknown	34(20.99%)
Tumour central	Distal	113(69.75%)
	Mid	42(25.93%)
	Proximal	6(3.7%)
	Unknown	1(0.62%)
Type	Adenocarcinoma	79(48.77%)
	Cystic, Mucinous, and Serous Neoplasms	1(0.62%)
	Squamous Cell Neoplasms	82(50.62%)

In order to find more targeted genes of eRNA SLC44A3-AS1, co-expression analysis in esophageal cancer was performed with r >0.4 and p<0.01. A total of 4383 targeted genes were identified ultimately. Among 4383 target genes, the top 10 genes of SLC44A3-AS1 were ranked and finally determined according to the correlation value, which are SLC44A3, AC006042.1, RAB17, SMPDL3B, ICA1, RAB20, CHN2, LINC01558, SMIM24, AL117382.2.

The GO enrichment analysis displayed that eRNA-related TFs (transcription factors) were enriched in the glycoprotein metabolic and biosynthetic process in the BP group, apical part of cell and plasma membrane in the CC group, as well as anion transmembrane transporter activity in the MF group (Figure 3a). KEGG enrichment analysis showed that eRNA-related TFs were enriched in herpes simplex virus 1 (HSV1) infection, Ras-associated protein 1 (Rap1) signaling pathway, and tight junction (Figure 3b). The colour intensity implies the p-value: the stronger the colour is, the lower the p-value and the more substantial the enrichment will be. In addition, SLC44A3-AS1 was distinctly related to neutrophil-mediated immunity. Ninety-three genes were enriched in the signalling pathway (Table II).

The prognostic role of SLC44A3-AS1 and its association with target genes in pan-cancer were determined by the means of survival and correlation analysis. The evaluation of the prognosis of pan-cancer was based on the expression level of each eRNA, using Kaplan-Meier method. Then, the median expression value of eRNAs was calculated based on which the patients were divided into low-expression and high-expression groups.

Table II: Ninety-three genes associated with SLC44A3-AS1 are enriched in neutrophil-mediated immunity (adjusted p <0.05 and r >0.4).

Gene	Spearman Correlation Coefficient r	Gene	Spearman Correlation Coefficient r	Gene	Spearman Correlation Coefficient r
ENPP4	0.762	MLEC	0.611	PECAM1	0.479
FUCA1	0.735	S100P	0.607	CEACAM6	0.475
SERPINA1	0.732	DNAJC3	0.607	ASAH1	0.471
TMEM63A	0.723	CTSH	0.602	MVP	0.467
CYSTM1	0.715	CYBA	0.601	STBD1	0.466
AOC1	0.712	ORM2	0.601	RAB27A	0.466
PTPRJ	0.702	PRSS3	0.588	ALOX5	0.465
GCA	0.69	GHDC	0.585	ANPEP	0.458
NHLRC3	0.688	SPTAN1	0.584	TCIRG1	0.457
ADGRE5	0.683	TTR	0.583	CAT	0.454
ALDH3B1	0.681	GUSB	0.581	SLC27A2	0.45
APAF1	0.672	MGAM	0.577	FRK	0.448
ATP11A	0.672	COTL1	0.569	CST3	0.446
OLFM4	0.668	CD55	0.569	LRG1	0.445
FUCA2	0.664	VNN1	0.561	SDCBP	0.444
PIGR	0.662	LGALS3	0.554	PRDX4	0.44
LYZ	0.658	SNAP23	0.552	KCNAB2	0.439
SERPINB6	0.652	CTSA	0.545	AGPAT2	0.439
PRSS2	0.648	CANT1	0.543	ACAA1	0.436
ATP8A1	0.643	HEXB	0.538	APEH	0.428
CD63	0.642	LCN2	0.536	CEACAM8	0.421
SVIP	0.64	TRPM2	0.535	PADI2	0.418
RAB37	0.637	RHOF	0.529	DNASE1	0.415
GLB1	0.637	PLAC8	0.527	AP2A2	0.414
IQGAP2	0.635	CTSZ	0.526	CEACAM1	0.413
PTPRB	0.632	CD93	0.512	RHOA	0.412
TNFRSF1B	0.632	ANXA3	0.499	TXNDC5	0.411
CTSS	0.629	PRKCD	0.496	BRI3	0.41
PTPRN2	0.621	DGAT1	0.496	SERPINA3	0.41
RNASET2	0.619	GNS	0.495	CEACAM3	0.404
ORMDL3	0.613	DDOST	0.492	CFP	0.404

Table III: List of 33 types of tumours related to SLC44A3-AS1 and SLC44A3.

eRNA	Target	Cancer Type	cor	corPval
SLC44A3-AS1	SLC44A3	Adrenocortical carcinoma	0.798953	0
SLC44A3-AS1	SLC44A3	Bladder urothelial carcinoma	0.780606	0
SLC44A3-AS1	SLC44A3	Adrenocortical carcinoma	0.627351	0
SLC44A3-AS1	SLC44A3	Cervical squamous cell carcinoma and endocervical adenocarcinoma	0.727385	0
SLC44A3-AS1	SLC44A3	Cholangiocarcinoma	0.857915	1.55E-08
SLC44A3-AS1	SLC44A3	Colon adenocarcinoma	0.580665	0
SLC44A3-AS1	SLC44A3	Lymphoid neoplasm diffuse large B-cell lymphoma	0.801867	7.43E-12
SLC44A3-AS1	SLC44A3	Esophageal cancer	0.830174	0
SLC44A3-AS1	SLC44A3	Glioblastoma multiforme	0.703909	0
SLC44A3-AS1	SLC44A3	Head and neck squamous cell carcinoma	0.535101	1.57E-38
SLC44A3-AS1	SLC44A3	Kidney chromophobe	0.772902	0
SLC44A3-AS1	SLC44A3	Kidney renal clear cell carcinoma	0.371966	0
SLC44A3-AS1	SLC44A3	Kidney renal papillary cell carcinoma	0.677006	0
SLC44A3-AS1	SLC44A3	Acute myeloid leukemia	0.732071	1.28E-26
SLC44A3-AS1	SLC44A3	Brain lower grade glioma	0.853526	2.5E-151
SLC44A3-AS1	SLC44A3	Liver hepatocellular carcinoma	0.722753	1.17E-61
SLC44A3-AS1	SLC44A3	Lung adenocarcinoma	0.605153	0
SLC44A3-AS1	SLC44A3	Lung squamous cell carcinoma	0.708217	0
SLC44A3-AS1	SLC44A3	Mesothelioma	0.732629	0
SLC44A3-AS1	SLC44A3	Ovarian serous cystadenocarcinoma	0.665409	0
SLC44A3-AS1	SLC44A3	Pancreatic adenocarcinoma	0.604594	0
SLC44A3-AS1	SLC44A3	Pheochromocytoma and paraganglioma	0.728468	0
SLC44A3-AS1	SLC44A3	Prostate adenocarcinoma	0.568799	0
SLC44A3-AS1	SLC44A3	Rectum adenocarcinoma	0.641432	0
SLC44A3-AS1	SLC44A3	Sarcoma	0.649646	6.40E-33
SLC44A3-AS1	SLC44A3	Skin cutaneous melanoma	0.733416	0
SLC44A3-AS1	SLC44A3	Stomach adenocarcinoma	0.675076	0
SLC44A3-AS1	SLC44A3	Testicular germ cell tumours	0.916486	3.74E-63
SLC44A3-AS1	SLC44A3	Thyroid carcinoma	0.560261	0
SLC44A3-AS1	SLC44A3	Thymoma	0.86158	0
SLC44A3-AS1	SLC44A3	Uterine corpus endometrial carcinoma	0.717948	0
SLC44A3-AS1	SLC44A3	Uterine carcinoma	0.670267	4.88E-08
SLC44A3-AS1	SLC44A3	Uveal melanoma	0.907103	0

Figure 2: Correlation between SLC44A3-AS1 expression and clinical traits of esophageal cancer; (a) age; (b) cancer status; (c) grade; (d) patho-logical N stage; (e) race; (f) stage; (g) tumour central; (h) type.

Finally, it was found that the eRNA SLC44A3-AS1 also plays an important role in a variety of tumours, including bladder urothelial carcinoma, uveal melanoma, glioblastoma multiforme, brain lower grade glioma, kidney renal clear cell carcinoma, ovarian serous cystadenocarcinoma, rectum adenocarcinoma, and uterine corpus endometrial carcinoma. The survival curves for SLC44A3-AS1 in the 8 types of tumours are presented in Figure 4. In addition, SLC44A3-AS1 and its target genes were related to 32 kinds of tumours (Table III).

DISCUSSION

Non-coding RNA (ncRNA) plays a crucial part in the incidence and expansion of many major human diseases.¹⁰ The role of enhancers attracted widespread attention not only because of its role in gene transcription and enhancer function mediation, but also because it overlaps with no risk loci, which are related to diseases.¹⁴ eRNAs (500-5000 bp), which could produce through enhancer transcription,¹⁵ are crucial cis-regulatory components promoting the eukaryotic gene expression.¹⁶ They can stimulate the downstream gene expression by activating enhancer activity or by combining with other protein factors to promote the enhancer-promoter loop formation.¹⁷ The role of eRNAs in tumour treatment is well understood.^9,18 In this study, the prognosis-related eRNAs in esophageal cancer was explored and examined.

It was found that eRNA SLC44A3-AS1 was up-regulated in esophageal cancer, and patients with high eRNA SLC44A3-AS1 expression had a weaker prognosis. These findings showed that the expression of SLC44A3-AS1 was positively linked to esophageal cancer progression. The up-regulation had an obvious correlation with many clinical characteristics, such as tumour status, tumour centre location, grade, etc. SLC44A3-AS1 may be an important factor in predicting the prognosis of esophageal cancer. According to the KEGG pathway enrichment results, SLC44A3 affected the survival of esophageal cancer patients through the HSV1 infection pathway. The pan-cancer validation results in this study showed that SLC44A3-AS1 was related to survival in 8 types of tumours (bladder urothelial carcinoma, uveal melanoma, Glioblastoma multiforme, renal clear cell carcinoma, low grade glioma, ovarian serous cystadenocarcinoma, rectum adenocarcinoma, and endometrial carcinoma). In this study, the expression of SLC44A3-AS1 was associated with its target gene SLC44A3, which had similar results across 32 tumour types. These results show that SLC44A3-AS1 can serve as an independent predictor of esophageal cancer. 

In esophageal cancer, the SLC44A3-AS1 expression was positively related to the SLC44A3 expression. SLC44A3 may be the target gene of eRNA SLC44A3-AS1. SLC44A3 is a member of the SLC44A1-5 (SLC44 family of solute carriers), which can function as choline transporters.¹⁹ A previous study revealed that SLC44A3 was differently expressed between normal and uveal melanoma.²⁰ Hou et al. proved that a DNA methylation-driven signature (10MeSig) composed of 10 MDPGs containing SLC44A3 is an independent predictive factor for the survival of patients with uveal melanoma.²¹ In this study, SLC44A3-AS1 is involved in esophageal cancer progression by the regulation of SLC44A3. 

To clarify the mechanism by which SLC44A3-AS1 mediates esophageal cancer occurrence, GO and KEGG enrichment analyses were performed.

Figure 3: Biological functions of SLC44A3-AS1; (a) The top 10 GO terms; (b) The top 30 KEGG pathway enrichment analysis results. Figure 4: Kaplan-Meier survival curves for SLC44A3-AS1 in pan-cancer (p<0.05); (a) bladder urothelial carcinoma; (b) uveal melanoma; (c) glio-blastoma multiforme; (d) Kidney renal clear cell carcinoma; (e) brain lower grade glioma; (f) ovarian serous cystadenocarcinoma; (g) rectum adenocarcinoma; (h) uterine corpus endometrial carcinoma.

eRNA-associated TFs were mainly enriched in the HSV1 infection pathway, indicating that eRNAs might regulate the HSV1 infection pathway through eRNA-related TFs and suggesting that eRNAs could regulate the HSV1 infection pathway. It is a potential eRNA target for improving the oncolytic virus therapy effect, providing a potential reason for the reported mechanism of using HSV1 to treat premalignant lesions and hence, delay cancer progression.²²

SLC44A3-AS1 is distinctly related to neutrophil-mediated immunity. lncRNAs are considered important regulators of neutrophils for cancer. lncRNA HOTTIP (homeobox A cluster transcript at the distal tip) stimulates ovarian cancer cells’ immune escape by up-regulating programmed death-ligand 1 (PD-L1) in neutrophils.²³ In this study, SLC44A3-AS1 was strongly associated with tight junction. Tight junction proteins can help maintain cellular integrity.²⁴ The tight junction barrier imbalance can stimulate cancer cell invasion and metastasis.²⁵

CONCLUSION

The eRNA SLC44A3-AS1 expression was up-regulated in esophageal cancer tissues. An overexpression of SLC44A3-AS1 also indicated a poor prognosis in esophageal cancer patients. Significant correlations were observed between SLC44A3-AS1 expression and clinical traits (e.g., central tumour location, cancer status, grade, etc.). Through pan-cancer validation, SLC44A3-AS1 was found to be related to the survival of eight other types of tumours.

ETHICAL APPROVAL:
This study was approved by the Institutional Ethics Committee of Hubei Cancer Hospital affiliated to Tongji Medical College, Huazhong University of Science and Technology, Hubei, China (Ethical Approval Number: LLHBCH2022YN-045).

PATIENTS’ CONSENT
Consent was not obtained as this study analysed data through TCGA data mining, and all patient information was sourced from publicly available databases.

COMPETING INTEREST:
The authors declared no competing interest.

AUTHORS’ CONTRIBUTION:
KK, JW, YM: Collected and analysed data, and wrote the manuscript.
JK, SC: Analysed data, worked on data acquisition.
KK, FX: Worked on conception and design, interpretation, critical revision, and final approval.
All authors have approved the final version of the manuscript to be published.

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