Project 3 Abstract Cancer is an evolutionary process where a single cell grows into a visible tumor after it has acquired multiple driver alterations and has created, or finds itself within, a permissive microenvironment. We will study fundamental parameters of evolution (mutation, drift, selection, MDS), and microenvironmental features to better understand their roles in colorectal cancer (CRC) outcomes. The innovation is that MDS-based microenvironmental-aware biomarkers are direct measures of evolution. Such evolution-based biomarkers reflect fundamental mechanisms for understanding what aspects of evolution most impact survival. To fully characterize tumor evolution it is necessary to measure both how tumor cells evolve and the host ecology.
In Aim 1, mutations detected by whole genome sequencing of 4 regions of 200 stage II and III CRCs with long-term follow-up will be classified as public (clonal) and private (subclonal). CRCs will then be subclassified with newly developed algorithms that can quantify selection (positive, neutral, negative) based on subclonal mutation frequencies, where selection preferentially increases (positive) or decreases (negative) subclonal mutation frequency. The same studies will be performed on small numbers of mouse and elephant tumors to test whether neoplastic MDS parameters differ between species.
In Aim 2, we will scan microscope sections from the exact same regions sequenced in Aim 1, using a unique automated computational image analysis platformthat can identify cells and quantify tumor microenvironments with respect to lymphocytes and stromal cells. In particular, we will quantify potential immunoediting by the host, using lymphocyte colocalization (Morisita index), lymphocyte density and Immunoscore, because prior studies indicate such host responses lead to significantly better outcomes. To determine if host ecological heterogeneity reflects responses to specific tumor subclones, we will overlay private mutation distributions on the same microscope slides. A correlation between a specific subclone with a specific microenvironment is consistent with selection. No correlation between specific ecological niches and tumor subclones is more consistent with neutral evolution, where all subclones are equally well-adapted and subject to the same selection. We will combine tumor evolution and the host reaction into a single evolution-ecology (Evo-Eco) index that summarizes the underlying evolutionary struggle. For example, patients with aggressive tumors (positive selection) and supportive environments are likely to have poorer outcomes relative to patients with tumorsunder negative selection and repressive environments. We will validate any promising Evo-Eco index on a validation cohort of ~100 more CRCs in Aim 3. Data from this Project will be also analyzed in Project 1, and compared with the normal crypts in Project 2 to determine if and how MDS parameters change in neoplasia. If successful, these studies will advance the measurement and understanding of MDS parameters in human cancer, and could yield improved CRC predictive biomarkers.
| Boddy, Amy M; Huang, Weini; Aktipis, Athena (2018) Life History Trade-Offs in Tumors. Curr Pathobiol Rep 6:201-207 |
| Barry, Peter; Vatsiou, Alexandra; Spiteri, Inmaculada et al. (2018) The Spatiotemporal Evolution of Lymph Node Spread in Early Breast Cancer. Clin Cancer Res 24:4763-4770 |
