Description
An analysis of expression of Immune checkpoint biomarkers in 15,454 patients with adverse pathology after radical prostatectomy: initial results from the Decipher GRID
Mohammed Alshalalfa1*, Mandeep Takhar1, Ewan Gibb1, Nicholas Erho1, Jonathan Lehrer1, Hussam Aldeen Ashab1, Elai Davicioni1, Ashley E. Ross2
1GenomeDx Biosciences, Vancouver, BC, Canada 2 Johns Hopkins Hospital, Baltimore, MD, USA*Corresponding author
Background: The modulation of immune inhibitory pathways represents a major breakthrough in cancer treatment.In this study, we quantified the expression of six immune checkpoint biomarkers, including PD1, PDL1, PDL2, B7-H3, CTLA4 and IDO1, in prostate cancer tissues using gene expression microarrays. We correlated the expression of distribution of these genes with prostate cancer disease signatures, including metastatic risk, luminal / basal subtyping and AR signaling, across a cohort of 15,454 radical prostatectomy Decipher cases.
The distribution of expression was calculated for each gene, with high and low expression values defined by thresholds based on median +/- 2*1.48*MAD (median absolute deviation).We found the median expression of B7-H3 and PD1 was significantly higher than the other four genes.For the 6 genes, percentage of patients with high expression above right threshold ranged between 2-5%.Expression of the B7-H3 gene was positively associated with AR-signaling (p < 0.0001) and metastatic risk based on Decipher score (p < 0.0001).In the majority of localized prostate cancer cases, we find robust B7-H3 and PD1 expression, with levels of B7-H3 increasing with tumor aggressiveness.
Expression profiling of immune inhibitory markers may inform optimal systemic therapy decisions and / or inclusion into clinical trials of novel targeted agents particularly to anti-B7-H3 antibodies such as enoblituzumab. This rich genomic resource is being made available on a research use only basis to prostate cancer researchers and to clinicians seeking to better understand prostate cancer in order to advance precision medicine.