Background: Histopathological prognostication relies on morphological pattern recognition, but as numbers of biomarkers increase, human prognostic pattern-recognition ability decreases. Follicular lymphoma (FL) has a variable outcome, partly determined by FOXP3 Tregs. We have developed an automated method, hypothesised interaction distribution (HID) analysis, to analyse spatial patterns of multiple biomarkers which we have applied to tumour-infiltrating lymphocytes in FL.
Methods: A tissue microarray of 40 patient samples was used in triplex immunohistochemistry for FOXP3, CD3 and CD69, and multispectral imaging used to determine the numbers and locations of CD3(+), FOXP3/CD3(+) and CD69/CD3(+) T cells. HID analysis was used to identify associations between cellular pattern and outcome.
Results: Higher numbers of CD3(+) (P=0.0001), FOXP3/CD3(+) (P=0.0031) and CD69/CD3(+) (P=0.0006) cells were favourable. Cross-validated HID analysis of cell pattern identified patient subgroups with statistically significantly different survival (35.5 vs 142 months, P=0.00255), a more diffuse pattern associated with favourable outcome and an aggregated pattern with unfavourable outcome.
Conclusions: A diffuse pattern of FOXP3 and CD69 positivity was favourable, demonstrating ability of HID analysis to automatically identify prognostic cellular patterns. It is applicable to large numbers of biomarkers, representing an unsupervised, automated method for identification of undiscovered prognostic cellular patterns in cancer tissue samples.