Abstract
Background: Prostate cancer (PCa) is characterized by significant heterogeneity in its molecular, genomic, and immunologic characteristics. Methods: Whole transcriptome RNAseq data from The Cancer Genome Atlas of prostate adenocarcinomas (n = 492) was utilized. The immune microenvironment was characterized using the CIBERSORTX tool to identify immune cell type composition. Unsupervised hierarchical clustering was performed based on immune cell type content. Analyses of progression-free survival (PFS), distant metastases, and overall survival (OS) were performed using Kaplan–Meier estimates and Cox regression multivariable analyses. Results: Four immune clusters were identified, largely defined by plasma cell, CD4+ Memory Resting T Cells (CD4 MR), and M0 and M2 macrophage content (CD4 MRHighPlasma CellHighM0LowM2Mid, CD4 MRLowPlasma CellHighM0LowM2Low, CD4 MRHighPlasma CellLowM0HighM2Low, and CD4 MRHighPlasma CellLowM0LowM2High). The two macrophage-enriched/plasma cell non-enriched clusters (3 and 4) demonstrated worse PFS (HR 2.24, 95% CI 1.46–3.45, p = 0.0002) than the clusters 1 and 2. No metastatic events occurred in the plasma cell enriched, non-macrophage-enriched clusters. Comparing clusters 3 vs. 4, in patients treated by surgery alone, cluster 3 had zero progression events (p < 0.0001). However, cluster 3 patients had worse outcomes after post-operative radiotherapy (p = 0.018). Conclusion: Distinct tumor immune clusters with a macrophage-enriched, plasma cell non-enriched phenotype and reduced plasma cell enrichment independently characterize an aggressive phenotype in localized prostate cancer that may differentially respond to treatment.
Highlights
There were 358,989 deaths from prostate cancer (PCa) in 2018, and there are expected to be 378,553 deaths from Prostate cancer (PCa) in 2020 [1,2]
The advent of rapid sequencing technologies has opened the door across oncology to more precise targeting of treatment modalities tailored to specific patient subgroups
A mixture file containing the RNA Seq by Expression Maximization (RSEM) gene expression data from the samples in the TCGA prostate adenocarcinoma (PRAD) dataset was downloaded from the cBioPortal and formatted according to the guidelines outlined in the CIBERSORT manual [19,20]
Summary
There were 358,989 deaths from prostate cancer (PCa) in 2018, and there are expected to be 378,553 deaths from PCa in 2020 [1,2]. The heterogeneity of tumors’ molecular and cellular composition is exacerbated during the progression of the cancer, creating complexity in the cellular and noncellular components of the tumor niche—the tumor microenvironment (TME). Cell types across the immune system may be found within the TIME, but depending on varying molecular signals, the same immune cell type may promote or inhibit tumor progression [13,14]. This implies the multifactorial nature of the TIME, involving the interplay between antigen presentation, immune activation and immune suppression. Given the complex interplay of the immunologic composition, we sought to characterize the presentation and clinical outcomes of discrete immune clusters in localized PCa, and to test whether these TIME subtypes inform prognosis
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