Noninvasive profiling of serum cytokines in breast cancer patients and clinicopathological characteristics.
Shakila JabeenJaime A EspinozaLilly Anne TorlandManuela ZucknickSurendra KumarVilde D HaakensenTorben LüdersOlav EngebraatenAnne-Lise Børresen-DaleJon Amund KytePavel GromovBjørn NaumeVessela N KristensenIrina GromovaXavier TekpliPublished in: Oncoimmunology (2018)
Cancers elicit an immune response by modifying the microenvironment. The immune system plays a pivotal role in cancer recognition and eradication. While the potential clinical value of infiltrating lymphocytes at the tumor site has been assessed in breast cancer, circulating cytokines - the molecules coordinating and fine-tuning immune response - are still poorly characterized. Using two breast cancer cohorts (MicMa, n = 131, DCTB, n = 28) and the multiplex Luminex platform, we measured the levels of 27 cytokines in the serum of breast cancer patients prior to treatment. We investigated the cytokine levels in relation to clinicopathological characteristics and in perspective of the tumor infiltrating immune cells predicted from the bulk mRNA expression data. Unsupervised clustering analysis of the serum cytokine levels in the MicMa cohort identified a cluster of pro-inflammatory, pro-angiogenic, and Th2-related cytokines which was associated with poor prognosis. Notably high levels of platelet derived growth factor BB (PDGF) reflected a more aggressive tumor phenotype and larger tumor size. A significant positive correlation between serum levels of interferon gamma-induced protein 10 (IP10) and its mRNA expression at the tumor site suggested that tumor-IP10-production may outflow to the bloodstream. High IP10 serum levels were associated with a worse prognosis. Finally, we found serum levels of both PDGF and IP10 associated with enrichment scores of specific tumor infiltrating immune cells. Our study suggests that monitoring cytokine circulating levels in breast cancer could be used to characterize breast cancers and the immune composition of their microenvironment through readily available biological material.
Keyphrases
- growth factor
- immune response
- poor prognosis
- stem cells
- machine learning
- escherichia coli
- squamous cell carcinoma
- single cell
- high throughput
- risk assessment
- oxidative stress
- big data
- endothelial cells
- electronic health record
- drug induced
- high glucose
- diabetic rats
- papillary thyroid
- protein protein
- high resolution
- artificial intelligence