The complex ecosystem in non small cell lung cancer invasion

Abstract

Many tumors are characterized by genetic instability, producing an assortment of genetic variants of tumor cells called subclones. These tumors and their surrounding environments form complex multi-cellular ecosystems, where subclones compete for resources and cooperate to perform multiple tasks, including cancer invasion. Our recent empirical studies revealed existence of such distinct phenotypes of cancer cells, leaders and followers, in lung cancer. These two cellular subclones exchange a complex array of extracellular signals demonstrating a symbiotic relationship at the cellular level. Here, we develop a computational model of the microenvironment of the lung cancer ecosystem to explore how the interactions between subclones can advance or inhibit invasion. We found that, due to the complexity of the ecosystem, invasion may have very different dynamics characterized by the different levels of aggressiveness. By altering the signaling environment, we could alter the ecological relationship between the cell types and the overall ecosystem development. Competition between leader and follower cell populations (defined by the limited amount of resources), positive feedback within the leader cell population (controlled by the focal adhesion kinase and fibronectin signaling), and impact of the follower cells to the leaders (represented by yet undetermined proliferation signal) all had major effects on the outcome of the collective dynamics. Specifically, our analysis revealed a class of tumors (defined by the strengths of fibronectin signaling and competition) that are particularly sensitive to manipulations of the signaling environment. These tumors can undergo irreversible changes to the tumor ecosystem that outlast the manipulations of feedbacks and have a profound impact on invasive potential. Our study predicts a complex division of labor between cancer cell subclones and suggests new treatment strategies targeting signaling within the tumor ecosystem.

Therapeutic Targeting of Collective Invasion in Ovarian Cancer

“…Three key characteristics defining collective invasion are: (i) the preservation of the physical connections and cell–cell junctions to orchestrate collective movement; (ii) shared cytoskeletal dynamics, allowing groups of cells to proceed as a single unit and develop multicellular polarity; and (iii) interactions with other cells and the ECM along the migratory path [26,27,28]. Collective invasion is a fundamental property of many metastatic tumours in human cancers, particularly epithelial tumours [29,30] including pancreatic cancer [31], colon cancer [32], sebaceous cancer [33], melanoma [34], breast cancer [35,36,37], and lung cancer [38].…”

“…Leader cells may also secrete immune effector molecules, influencing lymphocyte differentiation and polarizing local immune responses towards a suppressive phenotype [49]. Several studies have now demonstrated the importance of leader cells in the progression of epithelial-tumour types including breast, salivary, bladder, prostate, and lung cancers [36,38,49,50,51].…”

A Scribble/Cdep/Rac pathway regulates follower cell crawling and cluster cohesion during collective border cell migration

“…Collective cell migration is a widespread phenomenon that drives much of embryonic development, wound healing, and tumor metastasis. In migrating collectives, there are typically leader cells that extend protrusions outward from the group to steer it (Haney et al, 2018; Khalil and de Rooij, 2019; Theveneau and Linker, 2017; Zhang et al, 2019). The functions of follower cells are less clear (Qin et al, 2021), especially in vivo .…”

Cancer metabolism and carcinogenesis

“…Based on this, targeting invasive leader cells is an active area of research for developing anti-metastatic therapies. By understanding the molecular and cellular mechanisms underlying their invasive behavior, researchers aim to identify specific targets or pathways that can be therapeutically targeted to suppress tumor invasion and metastasis [ 103 , 104 ].…”