To date the anatomic extent of tumor (TNM-classification) has been by far the most important factors to predict the prognosis of cancer patients. However, this classification provides limited prognostic information and does not predict response to therapy. 

We redefined cancer by integrating the immune system, to transfer cutting-edge medicine to the patients. We showed that tumors from human colorectal cancer with a high-density of infiltrating memory and effector-memory T-cells (Tem) are less likely to disseminate to lymphovascular and perineural structures and to regional lymph-nodes. We demonstrated the critical tumor-microenvironment parameters determining the dissemination to distant metastasis. We showed that the combination of immune parameters associating the nature, the density, the functional immune orientation and the location of immune cells within the tumor was essential to accurately define the impact of the local host-immune reaction on patients prognosis. We defined these parameters as the “immune contexture”. We characterized the immune landscape within human tumors, and showed the importance of adaptive immune cells including, cytotoxic T-cells, Th1-cells, B-cells and T-follicular-helper (Tfh) cells. We described the immunopenotype and antigenome associated with immune escape mechanisms and demonstrated mechanisms associated with pre-existing and proliferating intratumoral T-cells. 

Based on the immune contexture, a standardized, simple and powerful digital-pathology-based immune stratification-system, termed “Immunoscore”, was delineated having a prognostic power superior to that of the currently used cancer staging-system. Tumor invasion parameters were statistically dependent on the host-immune reaction. A worldwide consortium is validating the prognostic value of Immunoscore, using a standardized-assay. Recent data are supporting the significant role of Immunoscore within lung, liver, and brain metastases and cancer evolution. Thus, tumor progression, invasion and recurrence are dependent on pre-existing immunity and on Immunoscore.

Learning Objectives: 

1. To decipher and understand the complexity of the tumor microenvironment.
2. To demonstrate the need for genomics, immunomics and systems biology to achieve precision medicine.