A mixture-like model for tumor-immune system interactions.

We introduce a mathematical model based on mixture theory intended to describe the tumor-immune system interactions within the tumor microenvironment. The equations account for the geometry of the tumor expansion, and the displacement of the immune cells, driven by diffusion and chemotactic mechanisms. They also take into account the constraints in terms of nutrient and oxygen supply.

Comparative Performance of Four Staging Classifications to Select «High-Risk» Head and Neck Cutaneous Squamous Cell Carcinomas.

Background: Many classifications exist to select patients with "high-risk" head and neck cutaneous squamous cell carcinoma (HNCSCC).

Objective: To compare the performance of the Brigham and Women's Hospital (BWH) classification with the performance of the American Joint Committee on Cancer 8th Edition (AJCC8), the Union for International Cancer Control 8th Edition (UICC8), and the National Comprehensive Cancer Network (NCCN) classifications.

Methods: In this single-center retrospective study, HNCSCC resected in a tertiary care center were classified as "low-risk" or "high-risk" tumors according to the four classifications.

Autofluorescence identifies highly phagocytic tissue-resident macrophages in mouse and human skin and cutaneous squamous cell carcinoma.

Macrophages from human and mouse skin share phenotypic and functional features, but remain to be characterized in pathological skin conditions. Skin-resident macrophages are known to derive from embryonic precursors or from adult hematopoiesis. In this report, we investigated the origins, phenotypes and functions of macrophage subsets in mouse and human skin and in cutaneous squamous cell carcinoma (cSCC) using the spectral flow cytometry technology that enables cell autofluorescence to be considered as a full-fledged parameter.

Analysis of the Equilibrium Phase in Immune-Controlled Tumors Provides Hints for Designing Better Strategies for Cancer Treatment.

When it comes to improving cancer therapies, one challenge is to identify key biological parameters that prevent immune escape and maintain an equilibrium state characterized by a stable subclinical tumor mass, controlled by the immune cells. Based on a space and size structured partial differential equation model, we developed numerical methods that allow us to predict the shape of the equilibrium at low cost, without running simulations of the initial-boundary value problem. In turn, the computation of the equilibrium state allowed us to apply global sensitivity analysis methods that assess which and how parameters influence the residual tumor mass.

LLT1-CD161 Interaction in Cancer: Promises and Challenges.

The success of immune checkpoint therapy in cancer has changed our way of thinking, promoting the design of future cancer treatments that places the immune system at the center stage. The knowledge gained on immune regulation and tolerance helped the identification of promising new clinical immune targets. Among them, the lectin-like transcript 1 (LLT1) is the ligand of CD161 (NKR-P1A) receptor expressed on natural killer cells and T cells.