Tumor Immunology and Tumor Evolution: Intertwined Histories

Cancer is a complex disease whose outcome depends largely on the cross-talk between the tumor and its microenvironment. Here, we review the evolution of the field of tumor immunology and the advances, in lockstep, of our understanding of cancer as a disease. We discuss the involvement of different immune cells at distinct stages of tumor progression and how immune contexture determinants shaping tumor development are being exploited therapeutically. Current clinical stratification schemes focus on the tumor histopathology and the molecular characteristics of the tumor cell. We argue for the importance of revising these stratification systems to include immune parameters so as to address the immediate need for improved prognostic and/or predictive information to guide clinical decisions.

Automated tumour budding quantification by machine learning augments TNM staging in muscle-invasive bladder cancer prognosis

Tumour budding has been described as an independent prognostic feature in several tumour types. We report for the first time the relationship between tumour budding and survival evaluated in patients with muscle invasive bladder cancer. A machine learning-based methodology was applied to accurately quantify tumour buds across immunofluorescence labelled whole slide images from 100 muscle invasive bladder cancer patients. Furthermore, tumour budding was found to be correlated to TNM (p = 0.00089) and pT (p = 0.0078) staging. A novel classification and regression tree model was constructed to stratify all stage II, III, and IV patients into three new staging criteria based on disease specific survival. For the stratification of non-metastatic patients into high or low risk of disease specific death, our decision tree model reported that tumour budding was the most significant feature (HR = 2.59, p = 0.0091), and no clinical feature was utilised to categorise these patients. Our findings demonstrate that tumour budding, quantified using automated image analysis provides prognostic value for muscle invasive bladder cancer patients and a better model fit than TNM staging.