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The body's defence network of cells and molecules that recognises and destroys infected, foreign and abnormal cells. It kills most would-be cancers before they are ever noticed; the ones that survive have learned to hide from it.
The innate arm (macrophages, neutrophils, natural killer cells, dendritic cells) responds fast and generically; the adaptive arm (T cells and B cells) learns specific targets and remembers them. Tumours are recognised because they display mutated proteins and stress signals, but successful tumours evade destruction by displaying 'don't attack me' checkpoint signals, hiding their antigens, recruiting suppressive cells, and walling themselves off; 'avoiding immune destruction' is one of the hallmarks of cancer. Immunotherapy in its many forms (checkpoint inhibitors, engineered T cells, bispecifics, vaccines) works by restoring or engineering the immune system's ability to see and kill the tumour.
TIMER2.0 is one of the most used tools in cancer immunogenomics and its multi-algorithm design is a reminder that computational immune cell estimates are model-dependent and should be cross-checked.
This framework is behind the everyday language of hot and cold tumours and the design of combination trials that pair checkpoint inhibitors with treatments meant to draw T cells into the tumour.
This atlas is the reference for how immune the different cancers are and is widely used to choose which tumours to test immunotherapies in and to interpret immune gene signatures. It shows why immunotherapy responses depend on the tumour's immune context as much as on its tissue.
TIMER made immune infiltration analysis accessible to any group with tumour expression data, which is why it is cited so heavily; it is a standard first step in linking a gene or mutation to the immune state of a cancer.
The cycle is the most used framework for designing immunotherapy combinations, from vaccines and radiotherapy that release antigens to drugs that recruit T cells into cold tumours. Most trial rationales in immuno-oncology cite it.
Immunoediting is the conceptual backbone of modern immuno-oncology: it explains tumour heterogeneity, dormancy and late relapse, and why immunotherapy works by releasing pre-existing but suppressed immunity.
This paper showed that the immune response to a cancer is part of its prognosis, not background noise, and it introduced the idea of the immune contexture that underlies both the Immunoscore and the biomarker work in immunotherapy.
This paper is why the tumour microenvironment is studied as intensely as the cancer cell itself. It underpins vaccination against HPV and hepatitis B as cancer prevention, aspirin and anti-inflammatory trials in bowel cancer, and the current work on macrophages and myeloid cells as immunotherapy targets.
Shares Li 2020: TIMER2.0 for analysis of tumour-infiltrating immune cells, Li 2017: TIMER, a web server for estimating immune cells in tumour genomic data, Thorsson 2018: the immune landscape of cancer across 10,000 tumours, Binnewies 2018: understanding the tumour immune microenvironment for effective therapy.
Shares Coussens and Werb 2002: inflammation and cancer, Macrophage, Inflammation.
Shares Lymph node, B cell, Antibody, T cell.
Shares Chen and Mellman 2013: the cancer-immunity cycle, Schreiber, Old and Smyth 2011: cancer immunoediting, Immune checkpoint.
Shares Li 2020: TIMER2.0 for analysis of tumour-infiltrating immune cells, Li 2017: TIMER, a web server for estimating immune cells in tumour genomic data.
Shares Coussens and Werb 2002: inflammation and cancer, Macrophage, Inflammation, Tumour microenvironment (TME).