20170321 expr&mut

Current available data

• TCGA Data: CNA, Mutation, Expression(protein/mRNA), clinical output

• Additional
  • pathway commons : to identify neighbors
  • cancer gene: Cancer gene census and uniprot POG/TSG keyword

CNA

Copy Number Alterations(CNA) are alterations of genomic regions. CNAs regions can be as long as chromosome arm or even an entire chromosome, called arm-level CNA; CNAs regions can also be much shorter, termed focal CNAs.

• The frequency of CNAs are inversely proportional to its length. But arm-level CNAs are exceptions.

• CNA affects gene expression levels through permanently add/ remove hard copies of DNA pieces from genome.
  • An example in the nature paper by Beroukhim et al. (2010) :

  ‘We show that cancer cells containing amplifications surrounding the MCL1 and BCL2L1 anti-apoptotic genes depend on the expression of these genes for survival.’

• According to broad institute, it’s calculated using GISTIC 2.0 developed by C. H. Mermel et al. (2011)

• data ? format? how to use?

Mut

Mutations are called from different variant caller algorithms from sequencing. There are three sequencing centers in TCGA project that independently sequence and make mutation calls (although data is not always available from all three centers).

• .maf file format is tabular annotated mutation data. it’s supported by software suites developed in the tcga community.

• However .vcf files might be a more popular format to record mutations outsite TCGA. For example, 1000G project.

• different mutation types might have different accuracy. Indels consist of a heap of false positives. use SNPs only.

Expression

Patient_level data can be downloaded using R/fh_geneexpr.R

CNA & Expression

CNA & Mutation

Mutation & Expression

Reference

Beroukhim, Rameen, Craig H. Mermel, Dale Porter, Guo Wei, Soumya Raychaudhuri, Jerry Donovan, Jordi Barretina, et al. 2010. “The Landscape of Somatic Copy-Number Alteration Across Human Cancers.” Nature 463 (7283): 899–905. doi:10.1038/nature08822.

Mermel, Craig H, Steven E Schumacher, Barbara Hill, Matthew L Meyerson, Rameen Beroukhim, and Gad Getz. 2011. “GISTIC2.0 Facilitates Sensitive and Confident Localization of the Targets of Focal Somatic Copy-Number Alteration in Human Cancers.” Genome Biology 12 (4): R41. doi:10.1186/gb-2011-12-4-r41.