Cancer is a disease of the genome, governed by principles of Darwinian evolution, whereby a cell acquires successive genetic or epigenetic alterations that lead to malignant transformation. The microenvironment is responsible for the selective pressures acting upon cells, for example immune predation, or resource availability (e.g. oxygen and nutrients provided through vascularization), and can in turn be remodeled by the cancer cell. Ecological interactions between a tumor and its environment are thus increasingly scrutinized to understand carcinogenesis and tumor progression.
The cancer ecology and evolution project of the rare cancers genomics team is a transversal research program led by Dr. Nicolas Alcala that aims to build a theoretical and analytical framework of cancer formation and development. The project makes use of existing mathematical and computational models, as well as development of new methods, applying them to the multi-omic data generated within other team projects (lungNENomics, panNENomics, MESOMICS, and SARCOMICS). We focus on three topics :
Temporal dynamics of tumor clones (colored shapes) in patient-derived tumor organoids (PDTO) of neuroendocrine neoplasms. Clonal complexity and selection (gray: neutrally evolving clones; colors: selected clones) increase with grade (left: low grade; right: high grade). From Dayton, Alcala et al. (Under review) https://www.biorxiv.org/content/10.1101/2022.10.31.514549v1
Malignant pleural mesothelioma phenotypes and associated features. Mesothelioma can be classified into three phenotypes (cell division, tumor-immune interaction, acinar), and each evolved under specific environmental conditions. From Mangiante, Alcala, Sexton-Oates, Di Genova et al., Nature Genetics (In press) https://www.biorxiv.org/content/10.1101/2021.09.27.461908v1
Computer simulations of a measure of differences in genetic composition (ranging from 0 for genetically similar populations to 1 for completely different populations), as a function of the frequency of genes M in two populations. Rows correspond to different rates of migration between the two populations (4Nm) and columns to different mutation rates for the individuals (4Nmu). From Alcala and Rosenberg, Philosophical Transactions of the Royal Society B https://royalsocietypublishing.org/doi/full/10.1098/rstb.2020.0414