Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: Natural Science Foundation of Gansu Province. No. 22JR5RA437.

PROVIDER: PRJNA1222546 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR32334836_1.fastq.gz	Fastqsanger.gz
	SRR32334836_2.fastq.gz	Fastqsanger.gz
	SRR32334837_1.fastq.gz	Fastqsanger.gz
	SRR32334837_2.fastq.gz	Fastqsanger.gz
	SRR32334838_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 18

Similar Datasets

Characteristics of microRNAs Profile in Five Pairs of Early Gastric Cancer Tissues and Matched Adjacent Normal Mucosa Tissues.

Project description:Gastric cancer is one of the most common malignant tumors. Asia has a high incidence of gastric cancer globally. South Korea, Mongolia, Japan and China are the four countries with the highest incidence of gastric cancer in the world. Gansu province in China has the estimated age-standardized incidence rates and mortality rates by Chinese standard population of 62.34/100,000 and 36.94/100,000, respectively, in 2012, which are much higher than the average level of China (22.06/100,000 and 15.16/100,000) in the same year. As a high incidence area of gastric cancer in China, Wuwei city in Gansu province has the prevalence of gastric cancer almost 5 times higher than the average level nationwide. In this study, the cancer tissues and matched adjacent normal mucosa tissues of 5 patients with early gastric cancers who were treated with ESD in Gansu Wuwei Tumor Hospital and the First Hospital of Lanzhou University were collected. All of the patients are from Gansu, China. MicroRNA array was used to find the differences in microRNAs expression profile between the early gastric cancer tissues and the para-cancer normal tissues. It is expected to explore the reasons of the abnormal high incidence of gastric cancer in Gansu Province, China, from the aspect of microRNAs expression profile characteristics.

2021-07-01 | GSE158315 | GEO

Project description:Regional Science Foundation project of National Natural Science Foundation of China (31960381)

| PRJNA780384 | ENA