Spatial immunophenotypes predict response to anti-PD1 treatment and capture distinct paths of T cell evasion in triple negative breast cancer.
Dora HammerlJohn W M MartensMieke TimmermansMarcel SmidAnita M Trapman-JansenRenée FoekensOlga I IsaevaLeonie VoorwerkHayri E BalciogluRebecca WijersIris NederlofRoberto SalgadoHugo Mark HorlingsMarleen KokReno DebetsPublished in: Nature communications (2021)
Only a subgroup of triple-negative breast cancer (TNBC) responds to immune checkpoint inhibitors (ICI). To better understand lack of response to ICI, we analyze 681 TNBCs for spatial immune cell contextures in relation to clinical outcomes and pathways of T cell evasion. Excluded, ignored and inflamed phenotypes can be captured by a gene classifier that predicts prognosis of various cancers as well as anti-PD1 response of metastatic TNBC patients in a phase II trial. The excluded phenotype, which is associated with resistance to anti-PD1, demonstrates deposits of collagen-10, enhanced glycolysis, and activation of TGFβ/VEGF pathways; the ignored phenotype, also associated with resistance to anti-PD1, shows either high density of CD163+ myeloid cells or activation of WNT/PPARγ pathways; whereas the inflamed phenotype, which is associated with response to anti-PD1, revealed necrosis, high density of CLEC9A+ dendritic cells, high TCR clonality independent of neo-antigens, and enhanced expression of T cell co-inhibitory receptors.
Keyphrases
- high density
- dendritic cells
- regulatory t cells
- end stage renal disease
- newly diagnosed
- induced apoptosis
- ejection fraction
- chronic kidney disease
- squamous cell carcinoma
- poor prognosis
- small cell lung cancer
- endothelial cells
- cell cycle arrest
- clinical trial
- insulin resistance
- acute myeloid leukemia
- vascular endothelial growth factor
- open label
- single cell
- oxidative stress
- adipose tissue
- binding protein
- long non coding rna
- endoplasmic reticulum stress
- fatty acid
- genome wide identification
- patient reported
- transcription factor
- double blind
- neural network