Dissection of prostate tumour, stroma and immune transcriptional components reveals a key contribution of the microenvironment for disease progression

Abstract

BackgroundProstate cancer is caused by genomic aberrations in normal epithelial cells, however clinical translation of findings from analyses of cancer cells alone has been very limited. A deeper understanding of the tumour microenvironment is needed to identify the key drivers of disease progression and reveal novel therapeutic opportunities. ResultsIn this study, the experimental enrichment of selected cell-types and the development a Bayesian inference model for continuous differential transcript abundance analyses permitted definition of the transcriptional landscape of the prostate cancer microenvironment across the disease progression spectrum. An important role of monocytes and macrophages in prostate cancer progression and disease recurrence was reinforced by both our transcriptional landscape findings and by differential tissue composition analyses. ConclusionsThis study contributes to understanding of monocyte-derived recruitment in primary prostate cancer, and supports a clear direction for further investigation into mechanisms of the immune system that contribute to disease progression.

A probabilistic framework for forecasting maize yield response to agricultural inputs with sub-seasonal climate predictions

“…The Bayesian approach is crucial to assess the risk bound to management decisions. The regularized horseshoe prior is a novel Bayesian method for dimension reduction [45] and has been successfully applied in other fields with sparse data [45][46][47], but its implementation is still incipient overall. The effects of the crop and environmental variables on the individual parameters were the product of a combination of a scaling parameter, and hierarchical shrinkage parameters [48].…”