| Literature DB >> 29212855 |
Rasheed Zakaria1,2, Angela Platt-Higgins2, Nitika Rathi3, Mark Radon4, Sumit Das3, Kumar Das4, Maneesh Bhojak4, Andrew Brodbelt5, Emmanuel Chavredakis5, Michael D Jenkinson5,6, Philip S Rudland2.
Abstract
Brain metastases are common and are usually detected by MRI. Diffusion tensor imaging (DTI) is a derivative MRI technique that can detect disruption of white matter tracts in the brain. We have matched preoperative DTI with image-guided sampling of the brain-tumor interface in 26 patients during resection of a brain metastasis and assessed mean diffusivity and fractional anisotropy (FA). The tissue samples were analyzed for vascularity, inflammatory cell infiltration, growth pattern, and tumor expression of proteins associated with growth or local invasion such as Ki67, S100A4, and MMP2, 9, and 13. A lower FA in the peritumoral region indicated more white matter tract disruption and independently predicted longer overall survival times (HR for death = 0.21; 95% confidence interval, 0.06-0.82; P = 0.024). Of all the biological markers studied, only increased density of CD3+ lymphocytes in the same region correlated with decreased FA (Mann-Whitney U, P = 0.037) as well as confounding completely the effect of FA on multivariate survival analyses. We conclude that the T-cell response to brain metastases is not a surrogate of local tumor invasion, primary cancer type, or aggressive phenotype and is associated with patient survival time regardless of these biological factors. Furthermore, it can be assayed by DTI, potentially offering a quick, noninvasive, clinically available method to detect an active immune microenvironment and, in principle, to measure susceptibility to immunotherapy.Significance: These findings show that white matter tract integrity is degraded in areas where T-cell infiltration is highest, providing a noninvasive method to identify immunologically active microenvironments in secondary brain tumors. Cancer Res; 78(3); 610-6. ©2017 AACR. ©2017 American Association for Cancer Research.Entities:
Mesh:
Year: 2017 PMID: 29212855 PMCID: PMC5796648 DOI: 10.1158/0008-5472.CAN-17-1720
Source DB: PubMed Journal: Cancer Res ISSN: 0008-5472 Impact factor: 12.701