Gene Expression Profiles in Cancers and Their Therapeutic Implications

被引:7
|
作者
Creighton, Chad J. [1 ,2 ,3 ,4 ]
机构
[1] Univ Texas MD Anderson Canc Ctr, Dan L Duncan Comprehens Canc Ctr, Human Genome Sequencing Ctr, Div Biostat,Baylor Coll Med, Houston, TX USA
[2] Univ Texas MD Anderson Canc Ctr, Baylor Coll Med, Dept Med, Houston, TX USA
[3] Univ Texas MD Anderson Canc Ctr, Dept Bioinformat & Computat Biol, Houston, TX USA
[4] One Baylor Plaza, MS305, Houston, TX 77030 USA
来源
CANCER JOURNAL | 2023年 / 29卷 / 01期
基金
美国国家卫生研究院;
关键词
cancer; gene expression profiling; proteomics; RNA-seq; transcriptomics; TERT PROMOTER MUTATIONS; MOLECULAR CLASSIFICATION; SIGNALING PATHWAYS; PREDICT RECURRENCE; BREAST-CANCER; SURVIVAL; REVEALS; CHEMOTHERAPY; PATTERNS; GENOMICS;
D O I
10.1097/PPO.0000000000000638
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
The vast amount of gene expression profiling data of bulk tumors and cell lines available in the public domain represents a tremendous resource. For any major cancer type, expression data can identify molecular subtypes, predict patient outcome, identify markers of therapeutic response, determine the functional consequences of somatic mutation, and elucidate the biology of metastatic and advanced cancers. This review provides a broad overview of gene expression profiling in cancer (which may include transcriptome and proteome levels) and the types of findings made using these data. This review also provides specific examples of accessing public cancer gene expression data sets and generating unique views of the data and the resulting genes of interest. These examples involve pan-cancer molecular subtyping, metabolism-associated expression correlates of patient survival involving multiple cancer types, and gene expression correlates of chemotherapy response in breast tumors.
引用
收藏
页码:9 / 14
页数:6
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