Sociobiology meets oncology: unraveling altruistic cooperation in cancer cells and its implications

Abstract

Altruism, an act of benefiting others at a cost to the self, challenges our understanding of evolution. This Perspective delves into the importance of altruism in cancer cells and its implications for therapy. Against the backdrop of existing knowledge on various social organisms found in nature, we explore the mechanisms underlying the manifestation of altruism within breast tumors, revealing a complex interplay of seemingly counteracting cancer signaling pathways and processes that orchestrate the delicate balance between cost and benefit underlying altruistic cooperation. We also discuss how evolutionary game theory, coupled with contemporary molecular tools, may shed light on understudied mechanisms governing the dynamics of altruistic cooperation in cancer cells. Finally, we discuss how molecular insights gleaned from these mechanistic dissections may fuel advancements in our comprehension of altruism among cancer cells, with implications across multiple disciplines, offering innovative prospects for therapeutic strategies, molecular discoveries, and evolutionary investigations. Altruism, or selfless behavior, has puzzled scientists for years, especially in the context of evolution. Traditionally, cancer cells are seen as selfish, growing uncontrollably. However, recent research suggests some cancer cells might act altruistically. They found that certain breast cancer cells produce substances that help neighboring cells survive chemotherapy, even though this slows their own growth. The study used breast cancer cell lines to observe these interactions. Researchers identified a subpopulation of cells with high levels of a molecule called miR-125b. These cells secrete proteins that protect other cells but grow more slowly themselves. This behavior fits the definition of biological altruism, where one organism incurs a cost to benefit others. The findings suggest that understanding these altruistic behaviors in cancer could lead to new treatment strategies. This summary was initially drafted using artificial intelligence, then revised and fact-checked by the author.