five

A Qualitative Transcriptional Signature for the Histological Classification of Non-Small Cell Lung Cancer

收藏
NIAID Data Ecosystem2026-03-10 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE121090
下载链接
链接失效反馈
官方服务:
资源简介:
Histological classification by routine pathology assessment with hematoxylin-eosin staining and immunostaining for poorly differentiated tumors, particularly those from small biopsies, is still challenging. In this study, using gene expression profiles of pathologically-determined lung squamous cell carcinomas and adenocarcinomas, denoted as pSCC and pADC respectively, we developed a qualitative transcriptional signature, based on the within-sample relative gene expression orderings (REOs) of gene pairs, to individually distinguish ADC from SCC. The signature was validated in the frozen tissues, FFPE materials, mixed tumors, small biopsy specimens and poorly differentiated samples.In summary, the qualitative signature, independent of the subjective diagnosis of pathologists, would be an effective auxiliary tool in distinguishing ADC from SCC. Total RNA was extracted using Trizol reagent (Invitrogen) according to the manufacture's protocol. The purity and concentration of RNA was determined by Nano Drop ND-1000 spectrophotometer according to OD260/280 reading. Total RNAs were hybridized using mRNA + lncRNA Human Gene Expression Microarray
创建时间:
2018-10-13
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作