[talks] Pawel Przytycki will present his FPO "Algorithms for deciphering cancer genomes: from differential mutation to differential allele specific expression" on Friday, 8/31/2018 at 11:30 in CS 402.

[Nicki Gotsis]

Pawel Przytycki will present his FPO "Algorithms for deciphering cancer genomes: from differential mutation to differential allele specific expression" on Friday, 8/31/2018 at 11:30 in CS 402. 

The members of his committee are as follows: Mona Singh (adviser); Joshua Akey (LSI) and Olga Troyanskaya (readers); Mona Singh, Ben Raphael, and Yibin Kang (MOL) (examiners). 


All are welcome to attend. A copy of his thesis is available in CS 310. 

The thesis abstract follows below. 




Large-scale cancer genome sequencing consortia have provided a huge influx of somatic 



mutation data across large cohorts of patients. Understanding how these observed 

genetic alterations give rise to specific cancer phenotypes represents a major aim of 

cancer genomics. In this dissertation, I present two methods for utilizing natural 

variation as a background for interpreting cancer genomes. 

In Chapter 2, I introduce di↵erential mutation analysis, a framework for uncovering 

cancer genes that compares the mutational profiles of genes across cancer genomes 

with natural germline variation across healthy individuals. I hypothesize that if a 

gene is less constrained with respect to variation across the healthy population, it 

may also be able to tolerate a greater amount of somatic mutation without experiencing 

a drastic detrimental functional change. I develop a fast and simple approach 

that uncovers genes that are di↵erentially mutated between cancer genomes and the 

genomes of healthy individuals. I demonstrate that my di↵erential mutation approach 

outperforms considerably more sophisticated approaches for discovering cancer genes. 

In Chapter 3, I propose the concept of di↵erential allele-specific expression to 

identify genes within an individual’s cancer whose allele-specific expression (ASE) differs 

from what is found in matched normal tissue, with the overall goal of uncovering 

genes whose regulation is altered via functional noncoding somatic mutations. I reason 

that since specific noncoding mutations usually occur on only one chromosome, 

they are expected to a↵ect only the expression of the allele derived from that chromosome. 

Thus, ASE is a potential avenue towards detecting cis mutations that lead 

to regulatory changes. I present three methods to identify di↵erential ASE in paired 

tumor-normal samples, and apply them to breast cancer tumor samples. I demonstrate 

that di↵erential ASE can detect dysregulation caused by nonsense mediated 

decay and copy number variation, that known cancer-related genes are enriched for 

di↵erential ASE, and that genes with cis noncoding mutations are enriched for difiii 

ferential ASE. Finally, I show that noncoding mutations in cis with genes exhibiting 

di↵erential ASE often disrupt known regulatory mechanisms. I thus conclude that 

di↵erential ASE is a powerful means for characterizing gene dysregulation due to cis 

noncoding mutations. 


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