In Frontiers in immunology ; h5-index 100.0
The tumor microenvironment is a complex ecosystem almost unique to each patient. Most of available therapies target tumor cells according to their molecular characteristics, angiogenesis or immune cells involved in tumor immune-surveillance. Unfortunately, only a limited number of patients benefit in the long-term of these treatments that are often associated with relapses, in spite of the remarkable progress obtained with the advent of immune checkpoint inhibitors (ICP). The presence of "hot" tumors is a determining parameter for selecting therapies targeting the patient immunity, even though some of them still do not respond to treatment. In human studies, an in-depth analysis of the organization and interactions of tumor-infiltrating immune cells has revealed the presence of an ectopic lymphoid organization termed tertiary lymphoid structures (TLS) in a large number of tumors. Their marked similarity to secondary lymphoid organs has suggested that TLS are an "anti-tumor school" and an "antibody factory" to fight malignant cells. They are effectively associated with long-term survival in most solid tumors, and their presence has been recently shown to predict response to ICP inhibitors. This review discusses the relationship between TLS and the molecular characteristics of tumors and the presence of oncogenic viruses, as well as their role when targeted therapies are used. Also, we present some aspects of TLS biology in non-tumor inflammatory diseases and discuss the putative common characteristics that they share with tumor-associated TLS. A detailed overview of the different pre-clinical models available to investigate TLS function and neogenesis is also presented. Finally, new approaches aimed at a better understanding of the role and function of TLS such as the use of spheroids and organoids and of artificial intelligence algorithms, are also discussed. In conclusion, increasing our knowledge on TLS will undoubtedly improve prognostic prediction and treatment selection in cancer patients with key consequences for the next generation immunotherapy.
Domblides Charlotte, Rochefort Juliette, Riffard Clémence, Panouillot Marylou, Lescaille Géraldine, Teillaud Jean-Luc, Mateo Véronique, Dieu-Nosjean Marie-Caroline
artificial intelligence, biomarker, cancer, lymphoid neogenesis, organoid, tertiary lymphoid structure, therapeutic intervention, tumor model