PARGP1, a specific enhancer RNA associated with biochemical recurrence of prostate cancer

Figures & data

Table 1. List of overall survival associated eRNAs derived from enhancers.

			Correlation between eRNA and the Neighboring Target
Symbol	Kaplan–Meier survival analysis and Log-Rank p-Value	Predicted Target	p-value	Correlation coefficient r
ZNF518A	0.001	CCNJ	<0.001	0.644
PARGP1	0.003	AGAP4	<0.001	0.571
CDK6-AS1	0.005	CDK6	<0.001	0.459
AC087672.2	0.023	LY96	<0.001	0.446
AC025539.1	0.032	HS3ST1	<0.001	0.461
LINC02731	0.033	JAM3	<0.001	0.564
AL353764.1	0.035	NFIL3	<0.001	0.533
AC025183.1	0.040	IRX4	<0.001	0.769
AC009950.1	0.043	SP140	<0.001	0.453
AC009950.1	0.043	SP140L	<0.001	0.514
FZD10-AS1	0.046	FZD10	<0.001	0.788
SLC7A11-AS1	0.046	SLC7A11	<0.001	0.638

Figure 1. Impact of eRNA PARGP1 on prostate adenocarcinoma (PRAD). (a) Kaplan–Meier survival curve for patients with PARGP1-high and PARGP1-low expression. (b) Scatterplot showing the association between PARGP1 and AGAP4 levels.

Figure 2. Expression of AGAP4 in tumor and normal prostate tissue.

Figure 3. Impact of eRNA PARGP1 on other cancers. (a) Kaplan–Meier overall survival curve for patients with PARGP1-high and PARGP1-low expression on head and neck squamous cell carcinoma (HNSC). (b) Kaplan–Meier overall survival curve for patients with PARGP1-high and PARGP1-low expression in brain lower grade glioma (LGG). (c) Kaplan–Meier overall survival curve for patients with PARGP1-high and PARGP1-low expression on pheochromocytoma and paraganglioma (PCPG).

Table 2. Kaplan–Meier survival analysis and gene expression correlations for PARGP1 and AGAP4 across 33 cancer types from the Cancer Genome Atlas (TCGA) project.

Tumor Type			PARGP1 and AGAP4
Abbrev-iation	Detail	PARGP1Overall Survival Log-Rank P-Value	Correlation P-Value	Correlation Coefficient r
ACC	Adrenocortical carcinoma	0.073	<0.001	0.597
BLCA	Bladder Urothelial Carcinoma	0.308	<0.001	0.559
BRCA	Breast invasive carcinoma	0.715	<0.001	0.636
CESC	Cervical squamous cell carcinoma and endocervical adenocarcinoma	0.296	<0.001	0.590
CHOL	Cholangiocarcinoma	0.408	0.004	0.473
COAD	Colon adenocarcinoma	0.904	<0.001	0.688
DLBC	Lymphoid Neoplasm Diffuse Large B-cell Lymphoma	0.667	<0.001	0.698
ESCA	Esophageal carcinoma	0.262	<0.001	0.790
GBM	Glioblastoma multiforme	0.394	<0.001	0.665
HNSC	Head and Neck squamous cell carcinoma	≤0.001	<0.001	0.671
KICH	Kidney Chromophobe	0.191	0.001	0.390
KIRC	Kidney renal clear cell carcinoma	0.364	<0.001	0.766
KIRP	Kidney renal papillary cell carcinoma	0.746	<0.001	0.697
LAML	Acute Myeloid Leukemia	0.277	<0.001	0.634
LGG	Brain Lower Grade Glioma	0.003	<0.001	0.720
LIHC	Liver hepatocellular carcinoma	0.072	<0.001	0.677
LUAD	Lung adenocarcinoma	0.203	<0.001	0.731
LUSC	Lung squamous cell carcinoma	0.684	<0.001	0.749
MESO	Mesothelioma	0.357	<0.001	0.519
OV	Ovarian serous cystadenocarcinoma	0.171	<0.001	0.671
PAAD	Pancreatic adenocarcinoma	0.060	<0.001	0.666
PCPG	Pheochromocytoma and Paraganglioma	0.033	<0.001	0.437
PRAD	Prostate adenocarcinoma	0.003	<0.001	0.571
READ	Rectum adenocarcinoma	0.153	<0.001	0.645
SARC	Sarcoma	0.151	<0.001	0.677
SKCM	Skin Cutaneous Melanoma	0.586	<0.001	0.760
STAD	Stomach adenocarcinoma	0.888	<0.001	0.760
TGCT	Testicular Germ Cell Tumors	0.609	<0.001	0.467
THCA	Thyroid carcinoma	0.231	<0.001	0.544
THYM	Thymoma	0.699	<0.001	0.592
UCEC	Uterine Corpus Endometrial Carcinoma	0.202	<0.001	0.447
UCS	Uterine Carcinosarcoma	0.483	<0.001	0.605
UVM	Uveal Melanoma	0.746	<0.001	0.891

Figure 4. Gene expression related to prostate cancer. (a–d) Expression levels of PARGP1 were not related to age in patients with prostate cancer or to the TNM stage of the tumor. (e–f) The difference between the expression level of PARGP1 and the value of PSA. There was a significant difference in PARGP1 expression level for PSA between 0–4 ng/ml and 4–10 ng/ml. (g–h) The expression levels of PARGP1 and AGAP4 were related to biochemical recurrence of prostate cancer (p < 0.05).

Figure 5. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEEG)enrichment analysis of co-expressed genes. The ordinate is the name of the metabolic pathway in GO and KEGG, and the abscissa is the number of genes annotated to the pathway.