AND ABSTRACT In the United States, metastatic breast cancer (MBC) accounts for over 40,000 deaths each year. Estrogen receptor-positive (ER+) MBC is present in up to 80% of MBC patients, and is treated by hormone therapy- based regimens. Given the high global prevalence of ER+ breast cancer, hormone therapy has a greater global impact than any other therapy in cancer medicine. However, >50% of ER+ MBC patients will exhibit de novo or acquired resistance to hormone therapy and once this occurs, patient prognosis is much more dismal. Currently, ER+ MBC treatment decisions are mainly based on pathological examinations of tumor tissues or biopsies. However, tissues or biopsies are not always obtainable and can yield inaccurate findings due to intratumoral heterogeneity. Moreover, MBC progression is a highly dynamic process in which the metastatic tumors constantly and rapidly change their genomic fingerprints to evade the attacks from systemic therapies and immune system, leading to drug resistance. To promptly and accurately detect these changes and adjust treatment plans, repeated tumor biopsies would be needed, which is extremely infeasible in real clinical settings. Therefore, it is important to develop novel non-invasive approaches for the prospective prediction and real-time monitoring of treatment responses, which can lead to more precise and timely treatment decisions. In MBC patients, circulating tumor cells (CTCs) are shed into blood by tumors, have extremely high malignant potential, and are arguably the most important subset of tumor cells to monitor and treat. Unlike tissues or biopsies, CTCs can be non-invasively enumerated and characterized in real-time as ?liquid biopsy?. The landmark study by our Co-Investigator, Dr. Massimo Cristofanilli (NEJM. 2004, 351(8)) showed that CTC number independently predicts MBC survival. That finding led to the clearance of CellSearchTM as the only CTC enumeration system approved by the Food and Drug Administration. However, although instrumental in predicting survival, a recent randomized trial (JCO. 2014, 32(31)) showed that treatment changes based on CTC enumeration alone did not prolong patient survival, highlighting the necessity of further in-depth genomic characterizations of single CTCs. Single-CTC analyses are highly challenging both technically and analytically, and would have been impossible in large-scale population studies without the recent emergence of the single- cell next-generation sequencing (NGS) technology. We recently established a pipeline on the enrichment, enumeration, isolation, amplification, and NGS analysis of single CTCs. Based on this pipeline, we propose a study to comprehensively characterize CTC genomes of ER+ MBC patients using a population-based approach. As, to our knowledge, the first population study of single-CTC NGS analysis in MBC patients, the findings of this study will significantly improve the potential of CTCs in the clinical management of MBC, by precisely tailoring treatment to the genomic make-up of individual CTCs from individual patients.

Public Health Relevance

We will use a population-based approach to conduct whole exome sequencing and targeted gene panel sequencing of single and pooled circulating tumor cells (CTCs), in order to identify CTC mutations/genes that are predictive of the survival and treatment response in patients with estrogen receptor-positive metastatic breast cancer (MBC). As, to our knowledge, the first population study of single-CTC next-generation sequencing in MBC patients, the findings of this study will significantly improve the potential of CTCs in the clinical management of MBC, by precisely tailoring treatment to the genomic make-up of individual CTCs from individual patients.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA207468-04
Application #
9987276
Study Section
Cancer, Heart, and Sleep Epidemiology B Study Section (CHSB)
Program Officer
Dey, Sumana Mukherjee
Project Start
2017-08-15
Project End
2022-07-31
Budget Start
2020-08-01
Budget End
2021-07-31
Support Year
4
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Thomas Jefferson University
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
053284659
City
Philadelphia
State
PA
Country
United States
Zip Code
19107