Every cell present in our bodies is related to every other cell by mitotic division, and the history of each of our somas is a bifurcating cell lineage tree whose root is the zygote. We will use this concept to establish lineage relationships among neoplastic lesions and carcinomas from each of 100 HER2-positive breast cancer cases. We will accomplish this by sequencing the genomes of several distinct tissue samples (normal, neoplastic, carcinoma) from each case and by performing expression profiling. The somatic variation we will identify (single nucleotide variants, structural variants, and aneuploidies) willbe used to build lineage trees that serve as roadmaps to determine when during evolution genomic driver events (HER2 overexpression and/or amplification, aneuploidies, and mutations in key cancer genes) and gene expression changes occurred. Several additional neoplastic samples that are too small for whole-genome sequencing will be identified and typed by targeted PCR and sequencing, for 192 of the identified somatic mutations from each case. These additional samples will substantially broaden the phylogenetic tree and facilitate finer resolution as to which types of mutations and other genomic changes happen first during neoplastic evolution. They will also allow us to determine if there are mutations that recur within the same case. Remarkably, in our previous work we have shown, on the basis of such tree analyses, that H1047R in PIK3CA has arisen multiple times within several patients. We will identify additional such mutations, if they exist. Our proposed work is distinct from other studies of tumor evolution, which have so far focused exclusively on within-tumor subclone evolution or metastatic changes, and which cannot order the earliest driver changes. Our study will distinguish drivers of the initial proliferative phenotype from those that cause a full-blown carcinoma. This can only be done by comparative analyses of early neoplasias with normal tissue and with carcinomas. We note that this concept is well-established in species phylogenetics and evolution, where past events are routinely inferred by comparison among extant species, and which have broadly facilitated insight into both gene function and evolutionary mechanisms. Just like evolving species, cells in our somas are governed by inheritance, change, and divergence, and our understanding of the origins and evolution of neoplasias towards tumors will benefit from a phylogenetic and evolutionary perspective. Our proposed study is one of the first that is dedicated to examining cancer in the light of evolution. We believe that a fuller understanding of mutational mechanisms, the order of driver changes during progression, and the role of hypermutable sites, will be essential for improving diagnostics, prediction, and drug development of this fundamentally evolutionary disease.

Public Health Relevance

Little is known about the genetic events that occur at the beginning of oncogenesis. Using concepts of cellular evolution, we will characterize the mutation and gene expression changes during progression of normal cells to breast cancer. An understanding of these early events in cancer will form the basis for improved diagnostics, prediction, treatment, and prevention strategies.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA183904-02
Application #
9003034
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Johnson, Ronald L
Project Start
2015-03-01
Project End
2019-02-28
Budget Start
2016-03-01
Budget End
2017-02-28
Support Year
2
Fiscal Year
2016
Total Cost
$653,942
Indirect Cost
$241,292
Name
Stanford University
Department
Pathology
Type
Schools of Medicine
DUNS #
009214214
City
Stanford
State
CA
Country
United States
Zip Code
94304
Spies, Noah; Weng, Ziming; Bishara, Alex et al. (2017) Genome-wide reconstruction of complex structural variants using read clouds. Nat Methods 14:915-920
Sidow, Arend; Spies, Noah (2015) Concepts in solid tumor evolution. Trends Genet 31:208-14
Bishara, Alex; Liu, Yuling; Weng, Ziming et al. (2015) Read clouds uncover variation in complex regions of the human genome. Genome Res 25:1570-80