Breast cancer PAM50 subtypes

PAM50

PAM50 stands for Prediction Analysis of Microarray 50. It tests a sample of the tumor (removed during a biopsy or surgery) for a group of 50 genes. Along with other factors, the results of the PAM50 test help predict the chance of metastasis (when cancer spreads to other organs). It was proposed by Parker et al. in 2009.

The PAM50 is a RT-qPCR assay that measures the expression of 50 classifier genes and five control genes to identify the intrinsic subtypes known as Luminal A, Luminal B, HER2-enriched and Basal-like. Along with a categorical classification of breast cancer subtype, it also provides quantitative values for proliferation, luminal gene expression, ESR1, PGR and ERBB2.

Gene expression profiling by microarray has given us insight into the complexity of breast tumors and can be used to provide prognostic information beyond standard clinical assessment.

For example:

  • the 21-gene OncotypeDx assay (Genome Health Inc, Redwood City, CA) can be used to risk stratify early-stage estrogen receptor (ER) –positive breast cancer.
  • Another strong predictor of outcome in ER-positive disease is proliferation or genomic grade.
  • the 70-gene MammaPrint (Agendia, Huntington Beach, CA) microarray assay has shown prognostic significance in ER-positive and ER-negative early-stage node-negative breast cancer.

Parker et al (2009) published microarray data (GEO data set GSE10886),数据可以比较方便的下载重现整个思路,只需要测定50个基因的表达量即可。

PAM50 classifier usage

The centroids, gene lists, and R code to produce the classification are all available along with the clinical information for the training set on this page: https://genome.unc.edu/pubsup/breastGEO/

Specifically, the R code and supporting data files are here: https://genome.unc.edu/pubsup/breastGEO/PAM50.zip

And the centroids alone are here: https://genome.unc.edu/pubsup/breastGEO/pam50_centroids.txt

In addition, this document provides additional information regarding classification of the PAM50 plus Claudin-low calls https://genome.unc.edu/pubsup/breastGEO/Guide%20to%20Intrinsic%20Subtyping%209-6-10.pdf

Anyone running PAM50 (or any classifier based on relative measurements such as expression) should understand the concepts in this paper: http://www.breast-cancer-research.com/content/pdf/s13058-015-0520-4.pdf

30个基因的分类效果

2011年一篇文章 提出了Montreal cohort of 87 patients的30个基因,也可以比较好的区分这些亚型:

这两个基因集的交叉,Of these 30 genes, only 7 of the 30 genes overlapped with the PAM50 (FOXA1, MLPH, ESR1, SLC39A6, NAT1, GRB7 and ERBB2) (Parker et al, 2009)

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因为不想遗忘! 在这个信息大爆炸的年代,最重要的是对知识的消化-吸收-重铸。每天学了很多东西,但是理解的多少,以及能够运用多少是日后成功的关键。作为一个PhD,大脑中充斥了太多的东西,同时随着年龄的增长,难免会忘掉很多事情。所以只是为了在众多教程中写一个自己用到的,与自己...… Continue reading