Tumor Heterogeneity and Therapeutic Resistance in Small Cell Lung Cancer (SCLC)
Abstract
Lung cancer is the leading cause of cancer death worldwide. Small cell lung cancer (SCLC) is a particularly aggressive form of lung cancer that is strongly linked to tobacco use and accounts for 14% of all lung cancer diagnoses in the United States. While oncologists have been provided a number of exciting new therapies for other types of lung cancer in the past decade, including much publicized immunotherapies and targeted therapies, treatment options for SCLC are exceedingly limited and have remained largely unchanged for decades. Further complicating the management of SCLC is the fact that resistance to the few available treatments develops rapidly and inevitably. As a result, less than 10% of patients with SCLC are living just 5 years after their initial diagnosis. In order to improve these grim statistics, research focusing on the identification of novel targets for therapies and the mechanisms that underlie resistance to new and existing therapies must be performed. We propose utilizing novel animal models that we have generated using tumor cells collected from SCLC patient blood samples to uncover the causes of treatment resistance in SCLC. This proposal directly addresses the following Lung Cancer Research Program Areas of Emphasis: (1) Understanding predictive and prognostic markers to identify responders and (2) Understanding susceptibility or resistance to treatment. We hypothesize two non-mutually exclusive mechanisms by which once-sensitive tumors may develop resistance to treatment: (1) positive selection of initially low-frequency, inherently resistant populations of cancer cells and/or (2) real-time adaptive alterations in the DNA sequence or RNA and protein expression of cancer cells to adopt more resistant characteristics. We have previously shown that our novel patient-derived mouse models accurately mimic the tumor characteristics and treatment responses of the patients from which they were derived. As a result, we have developed models that consistently demonstrate sensitivity or resistance to standard-of-care treatment options. We propose employing highly innovative DNA, RNA, and protein analyses with both whole tumors and with single-cell resolution to identify large- and/or small-scale adaptations that mediate treatment resistance. These cutting-edge techniques provide us with unparalleled resolution at the single-cell level to identify rare pre-existing populations of resistant cells that precede widespread treatment resistance, as well as the ability to accurately identify even subtle changes in gene and protein expression that occur as a result of treatment. If successful, these experiments have the potential to alter the diagnosis and surveillance of SCLC within 1 to 2 years, potentially supporting the use of minimally invasive blood sampling in lieu of risky and costly invasive biopsy techniques in order to guide the use of existing therapies. Additionally, we believe that our results may reveal novel strategies for combining and sequencing existing therapies, as well as identify targets for the design of new SCLC therapies that could reach clinical trials within a 2- to 3-year window. As SCLC is strongly linked to tobacco use and tobacco use is historically increased in the Veteran population, the development of less morbid and less costly SCLC surveillance strategies that increase the efficiency and effectiveness of treatment delivery offers an obvious benefit not only to Veterans, but to their families and the population at large as well. In short, this could mean fewer invasive procedures, an improved ability to distinguish between useful and futile therapies, and increased therapeutic options, all of which would enhance the quality of both healthcare delivery and, most importantly, Veterans’ lives.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Oct 29, 2018
- Source ID
- W81XWH1810091
Entities
People
- Lauren Byers
Organizations
- United States Army
- University of Texas at Austin