# Binnewies 2018: understanding the tumour immune microenvironment for effective therapy

Source: https://onco.cc/key-papers/paper-binnewies-tumor-immune-microenvironment-natmed-2018/  
OnCo record `paper-binnewies-tumor-immune-microenvironment-natmed-2018` (Key paper). Data CC BY-NC 4.0, attribute "Data from OnCo (onco.cc)"; commercial use needs a licence.

## TL;DR

A review that sorted tumours by where their immune cells sit, inflamed and infiltrated, infiltrated but excluded, or immune-poor, and argued that this classification should guide which immunotherapy a patient receives.

## Summary

Binnewies, Krummel and colleagues proposed classifying the tumour immune microenvironment (TIME) by the density and position of immune cells: infiltrated-excluded tumours with T cells confined to the margins and stroma, infiltrated-inflamed tumours with T cells among the cancer cells and high PD-L1, and a subclass with tertiary lymphoid structures. They reviewed how these states arise from tumour genetics, the microbiome and host factors, how they predict response to checkpoint blockade, and how therapies including chemotherapy, radiotherapy and myeloid-targeting agents might convert excluded or cold tumours into inflamed ones.

## Fields

- Kind: Key paper
- Last checked: 2026-09-08
- Journal: Nature Medicine
- Year: 2018
- DOI: 10.1038/s41591-018-0014-x
- Authors: Binnewies M, Roberts EW, Kersten K, et al.
- Findings: Tumour immune microenvironments fall into infiltrated-excluded, infiltrated-inflamed and tertiary lymphoid structure classes.; Inflamed tumours with intratumoural T cells and PD-L1 are the most likely to respond to checkpoint blockade.; Proposed therapeutic strategies to convert excluded or immune-poor tumours into inflamed ones.
- What it means: 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.
- Caveats: Classes are descriptive and the boundaries between them are not sharp.; A review; prospective use of TIME classification to choose therapy is still being tested.

## Sources

- Full text (DOI): https://doi.org/10.1038/s41591-018-0014-x

## Connected records

- key papers: [Chen and Mellman 2013: the cancer-immunity cycle](https://onco.cc/key-papers/paper-chen-mellman-cancer-immunity-cycle-immunity-2013/), [Thorsson 2018: the immune landscape of cancer across 10,000 tumours](https://onco.cc/key-papers/paper-thorsson-immune-landscape-of-cancer-immunity-2018/), [Tumeh 2014: PD-1 blockade works by releasing T cells already present at the tumour edge](https://onco.cc/key-papers/paper-tumeh-pd1-adaptive-immune-resistance-nature-2014/)
- technologies: [Immune checkpoint inhibitors](https://onco.cc/technologies/checkpoint-inhibitor/)
- targets: [PD-L1](https://onco.cc/targets/pdl1/)
- institutions: [UCSF Helen Diller Family Comprehensive Cancer Center](https://onco.cc/institutions/ucsf/)
- terms: [Hot vs cold tumours](https://onco.cc/terms/cold-vs-hot/), [Immune system](https://onco.cc/terms/immune-system/), [Tumour-infiltrating lymphocytes (TILs)](https://onco.cc/terms/tils/)

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