Cancer Evolution: A Multifaceted Affair

Abstract

Cancer cells adapt and survive through the acquisition and selection of molecular modifications. This process defines cancer evolution. Building on a theoretical framework based on heritable genetic changes has provided insights into the mechanisms supporting cancer evolution. However, cancer hallmarks also emerge via heritable nongenetic mechanisms, including epigenetic and chromatin topological changes, and interactions between tumor cells and the tumor microenvironment. Recent findings on tumor evolutionary mechanisms draw a multifaceted picture where heterogeneous forces interact and influence each other while shaping tumor progression. A comprehensive characterization of the cancer evolutionary toolkit is required to improve personalized medicine and biomarker discovery.

Significance: Tumor evolution is fueled by multiple enabling mechanisms. Importantly, genetic instability, epigenetic reprogramming, and interactions with the tumor microenvironment are neither alternative nor independent evolutionary mechanisms. As demonstrated by findings highlighted in this perspective, experimental and theoretical approaches must account for multiple evolutionary mechanisms and their interactions to ultimately understand, predict, and steer tumor evolution.

Figure 1.

The many faces of cancer evolution. Enabling characteristics such as genetic instability, epigenetic reprogramming, and interactions between tumor cells and the TME enable cancer evolutionary mechanisms such as the emergence and selection of genetic variants, cancer cell plasticity, and re-education of the TME.

Figure 2.

Emergence and selection of somatic mutations. A, The propagation of DNA lesions that are not resolved into mutations within one cell cycle leads to lesion segregation and multiallelic variation. B, Initiating genetic mutations observed in cancer cells can be found in normal cells at the tumor site allowing us to trace the origin of the tumor. C, Genetic instability during tumor progression leads to the acquisition and selection of tumor-advantageous variants. Variant selection can be studied by modeling the recurrence of somatic mutations across large tumor cohorts, developing machine learning approaches to predict variant oncogenicity, and investigating whether the selection of specific variants depends on either preexisting alterations or the cell of origin of the tumor.

Figure 3.

From somatic mutations to epigenetic reprogramming. A, Somatic mutations targeting CTCF binding sites can impair CTCF binding and insulation between chromatin loops or topologically associating domains (TAD). Loss of insulation leads to aberrant interactions between gene promoters and cis-regulatory elements (CRE). B, Somatic mutations of histone modifiers may lead to altered histone modification (e.g., methylation and acetylation). Aberrant histone marks have been associated with missegregated chromatin compartments and compartment repositioning, as well as the emergence of a state of “phenotypic inertia,” which allows tumor cells to tolerate oncogenic stress and ultimately adapt.

Figure 4.

Cancer cell plasticity and cancer cell states. A, Histone modifications, miRNA, and interactions with the TME induce epigenetic and transcriptional reprogramming that alters cancer cell identity. This process defines cancer cell plasticity transitions among phenotypically heterogeneous cell states that can be inferred from single-cell molecular profiles. B, Examples of such cell state transitions have been reported in skin melanoma, where mesenchymal and stem-like states have been associated with metastatic and tumorigenic capacity, respectively, in lung adenocarcinoma, where disease progression was associated with morphologic differences and transition from an alveolar-type 2-like state (AT2-like) to a dedifferentiated and proliferative cell state; and in breast cancer, where resistance to therapy was shown associated with cell dormancy and random awakening mediated by epigenetic reprogramming.

Figure 5.

Interactions with an evolving TME. A, Along with tumor cells, the surrounding TME also evolves often acquiring protumor features. Examples include reeducation of macrophages in treatment-resistant glioma, phenotypically heterogeneous populations of cancer-associated fibroblasts, treatment-induced generation of a tumor-evasive TME, which is associated with dual resistance to targeted and immunotherapies in melanoma, and interactions between tumor-associated neutrophils (TAN) and lung cancer cells, which toward a less proliferative, but hypoxia responsive cell state. B, Spatially resolved molecular profiles provide a critical tool to investigate tumor–TME interactions.