Understanding Physical Determinants of Heterogeneity in Renal Cancer Carcinoma
Abstract
Clear cell renal cell carcinoma (ccRCC) is the most common type of kidney cancer and its rates are on the rise worldwide. Metastatic ccRCC, which accounts for about 30%-40% of all cases, is refractory to current treatment options and is therefore incurable. Indeed, only a modest proportion of patients benefit from durable response to treatments with anti-angiogenesis (e.g., anti-VEGF) or immune-checkpoint inhibitors (ICI). There is thus an urgent need to identify, characterize, and target novel drivers of ccRCC progression and resistance to therapies to improve disease outcomes and patient survival. This goal has been hindered by the underlying complexity of ccRCC, a solid tumor that contains cancerous cells along with non-cancerous cell types of the body that support tumor growth, including blood vessels and the matrix onto which the tumor is anchored, and regulatory cells of the immune system that suppress the antitumor function of tumor-infiltrating immune cells. In this proposal we postulate that in renal cell carcinoma the spatial distribution of physical forces and tissue stiffness control the topology of gene expression across the tumor mass, thereby positioning cancer cell subpopulations for distinct phenotypes, growth-initiating potentials, and therapeutic intractability. Indeed, RCC is a paradigm of cellular and molecular heterogeneity and regional diversity, which conceals mechanisms of disease progression, relapse, and therapeutic responses, including poorly understood chemo- and radiation resistance. While large studies have delineated the molecular landscape of RCC, including at the single-cell level, little is known about the spatial determinants of cell positioning and phenotypic diversity across the tumor ecosystem, in spite of the emerging role of mechanosignaling in gene expression and cellular function. We hypothesize that the location of critical tumor microregions, such as position and density of cancer stem-like progenitor cells and their niches, as well as premetastatic, drug resistant, and angiogenic cells is defined by physical force fields and tissue stiffness, which can be therapeutically realigned. We know that gene regulation and transcriptome patterns shape the identity and functionality of cells; however, driving forces that modulate gene regulation, and thereby alter cell function within the ccRCC microenvironment are poorly studied. Importantly, the effects of physical factors, including tissue stiffness that exist within the ccRCC ecosystem on shaping transcriptome patterns and cell behaviors are unknown. This is a challenging question, given the complex nature of the concept, which spans genomics (gene regulation), physics (mechanical cues such as stiffness), and cell biology (cellular behavior). To address this challenge, this project leverages multidisciplinary expertise in genomics, bioengineering, computational science, and cancer biology to enable the measurements of stiffness diversity and spatial transcriptome heterogeneity within the ccRCC microenvironment, and integrate these patterns to elucidate the role of stiffness in modulating the behavior of cancer cells in the ccRCC ecosystem. Achieving this goal will allow us, for the first time, to study the role of the mechanical cues in the development of metastatic ccRCC. Patients suffering from metastatic ccRCC face a largely incurable disease due to limitations of the currently available forms of systemic therapy and severe side effects. Our work will develop unprecedented experimental approaches and computational algorithms that will serve to integrate mechanical and molecular properties of a complex tumor microenvironment, by which we will investigate reciprocal connections between intratumoral physical properties and molecular heterogeneity in ccRCC. Frameworks developed in the proposed study will help the scientific community and researchers to address challenges and questions that could not be examined previously.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Dec 05, 2021
- Source ID
- W81XWH2110579
Entities
People
- Yasser Riazalhosseini
Organizations
- McGill University
- United States Army