We propose a novel technique to identify and capture circulating tumor cells (CTCs) using engineered adenoviruses and sophisticated flow cytometry. Current techniques for detection of CTCs include reverse transcriptase-polymerase chain reaction (RT-PCR), flow cytometry, fluorescence in situ hybridization, and, more recently, microfluidics. Unfortunately, RT-PCR does not distinguish between viable metastatic CTC versus nucleic acids or cellular fragments originating from the primary tumor. ! Antibody-based techniques cannot be used for detection of all cancers, but only those cancers that express the most common and well- characterized markers. As such, there is a desperate need to develop new diagnostic agents and tools that not only detect and capture CTCs but also quantify their malignant potential and identify 'up-front'the therapies that are most effective in ablating an individual patient's tumor. Despite the complexity and variability of cancers at a genome scale, a unifying theme is their growth deregulation phenotypes, the so-called hallmarks of cancer, which are conferred by mutations in a relatively small number of key pathways. Rather than focus on detecting individual genetic lesions that are numerous and highly variable between tumors, we propose to create diagnostic viruses that incorporate multiple transcriptional and molecular modules in their genomes to infect and detect a patient's tumor, report its molecular 'hallmarks'and its response to different therapies 'up- front'. Using these agents, the molecular lesions and malignant characteristics of any given tumor will be rapidly discerned (within 24 hours) and scored via a standardized automated platform. Furthermore, these agents could also be used as reporters to determine rapidly and directly if a patient's tumor is likely to respond to a particular therapy. Our goal is to develop a standardized automated platform that provides point-of-care diagnostics to inform clinical decisions at a level of molecular sophistication and prognostic power that is not possible with any other detection system, biomarkers or correlative gene expression signatures. To achieve this, we will combine transformative new technological platforms developed at the Salk, UCSD, and NanoSort that label tumor cells in different colors based on their acquisition of molecular lesions that dictate malignant progression and response to therapy, facilitating their detection, quantification and isolation using an integrated 'lab-on a chip'flow cytometer.
To aid in the diagnosis and treatment of cancer, we will specially design adenoviruses that preferentially infect circulating tumor cells (CTCs, cells that have left a tumor and entered the bloodstream), drastically distinguishing these rare cells from the billions of blood cells found in a routine blood sample. This technology also detects the status of the cancer, giving doctors information about how aggressive or treatable a cancer might be. We combine this adenoviral system with a sophisticated new lab-on-a-chip cell-sorting device that passes the virally infected cells along microfluidic channels to be measured and sorted from the blood, and examined for characteristic hallmarks of cancer.