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Directed Kinome Resequencing to Define New Targeted Therapies for “Basal-Like” Breast Cancer
‘Basal-like’ breast tumors often lack estrogen receptor expression and her2 gene amplification, are more refractory to hormonal and non-hormonal chemotherapy, and are more clinically aggressive. Agents that target aberrant kinase activity, when used in combination, could potentially provide effective treatment and improve survival in these patients with minimal toxicity. Effective use of such compounds in breast cancer patients, however, will require a better understanding of the tumor’s corresponding molecular vulnerability. Our hypothesis is that comprehensive but focused DNA resequencing (‘mutational profiling’) of expressed kinases in ‘basal-like’ breast tumors will identify characteristic kinase mutations that can be specifically targeted by existing or newly developed molecular inhibitors. A compendium of breast kinase mutations will serve as a set of important clinical biomarkers to predict disease course and therapeutic response, and will stimulate rationally based Phase I therapeutic trials for breast cancer. In the first aim, we will identify frequently recurring sequence alterations in kinases that are commonly expressed in basal-like breast tumors. We will leverage the unique capabilities of our institution’s Genome Sequencing Center and a pre-existing, robust infrastructure for sample tracking, primer design, bioinformatics, and data visualization to perform high-throughput cDNA sequencing. Kinases that are frequently expressed in basal-like tumors will be identified through analysis of existing expression profile data. The coding region of each of these kinases will be sequenced using cDNAs from a set of 94 basal-like breast tumors. In the second aim, we will identify those sequence alterations that represent true somatic mutations. Tumor sequence alterations will be scored as germline polymorphisms or somatic mutations based upon automated comparison to established polymorphism databases and by sequencing corresponding, patient matched non-malignant genomic DNA. Specific mutations identified will be the target for focused resequencing of additional cDNAs from a larger number of breast tumors of varying molecular classifications. The frequency of specific mutations in relation to clinical stage, pathological grade, and molecular subtype will be determined. The outcome of this proposed research will comprehensively define therapeutic opportunities to use molecular inhibitors directed at mutated kinases as a first step toward evaluating new therapies for breast cancer patients.
Some types of breast cancer (‘basal-like’) are particularly aggressive and do not respond well to conventional therapy. Targeted therapies are designed to attack specific molecular deficits in tumor cells. These agents are often very effective and have limited side effects. To determine which of these new agents might be useful for treating patients with basal-like breast cancer, it will be necessary to determine whether the corresponding molecular deficits are present in breast cancer cells. We propose to analyze the DNA sequence of basal-like breast tumors to identify alterations in cellular molecules called kinases. Kinases are frequently mutated in many types of cancer and are often responsible for a cancer cell’s growth. A number of targeted therapies are currently available or in development that can block the action of these mutated kinases. Therefore, knowing which kinase molecules are mutated in breast cancer cells should allow physicians to choose the best possible agents for treating breast cancer. To accomplish these studies, we will utilize our institution’s Genome Sequencing Center, one of the largest DNA sequencing facilities in the country. We will also use a number of unique resources such as frozen tumor tissue collections, computer databases, and novel data visualization tools that we have already developed to study similar problems in leukemia and prostate cancer. We will use 94 basal-like breast tumors to identify kinase molecules that are commonly altered. Anonymous patient breast tumor samples will be used to isolate tumor DNA. These tumor DNAs will be used to sequence kinase molecules that are present in the tumors. The results of over 27 million DNA sequences will be automatically collected into a database and frequent alterations will be identified using novel software that we have developed. Second, we will determine whether the altered kinase molecules are true tumor mutations or naturally occurring, non-cancer variants. This will be ascertained by automated searching of publicly available databases of DNA sequence from non-cancer populations, and by directly comparing tumor and non-tumor DNAs. We will look for these mutations in a larger number of breast tumors to determine whether they correlate with a specific stage of tumor progression or a specific subtype of tumor. This information could lead to new genetic tests to predict the clinical behavior of breast tumors and will form the basis for future clinical trials, utilizing specific targeted therapies to more effectively treat women with breast cancer.