Tumor Immune Microenvironment Clusters in Localized Prostate Adenocarcinoma: Prognostic Impact of Macrophage Enriched/Plasma Cell Non-enriched Subtypes

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=496) 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), M0 and M2 macrophage content (CD4 MRHighPlasma CellHighM0LowM2Low, CD4 MRLowPlasma CellHighM0LowM2Low, CD4 MRHighPlasma CellLowM0HighM2Low, and CD4 MRHighPlasma CellLowM0LowM2High). The two macrophage-enriched/plasma cell non-enriched clusters (3&4) demonstrated worse PFS (HR 2.24, 95% CI 1.46–3.45, p=0.0002) than the clusters 1&2. No metastatic events occurred in the 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 phenotype and reduced plasma cell enrichment independently characterize an aggressive phenotype in localized prostate cancer that may differentially respond to treatment.

Prognostic Value of Intratumoral Lymphocyte-to-Monocyte Ratio and M0 Macrophage Enrichment in Tumor Immune Microenvironment of Melanoma

“…Ultimately, M0s may represent another type of TAM or an incompletely differentiated M2 [51]. M0 macrophages have been found to be one of the cell subsets most strongly associated with poor outcome in breast cancer [53], prostate cancer [54] and lung adenocarcinoma [55], whereas reduced M0 content has been associated with better prognosis in bladder cancer [56]. In a comprehensive analysis of digestive system cancers, M0 macrophages were among the most prevalent immune cell fractions, with M0-enriched clusters associated with decreased recurrence-free survival and worse prognostic immune score [57].…”

Targeting the spectrum of immune checkpoints in prostate cancer

“…A recent study of mCRPC found that enzalutamide exposure increased gene expression of TGF-β signaling [57] suggesting that targeting this pathway may become even more important as CRPC acquires resistance to potent AR inhibition. Although it is not innate immune cells, some evidence suggests that tumor-associated plasma cells are associated with higher T cell infiltration into primary prostate cancer and better outcomes after local therapy [102,103]; however, the functional role of this cell type is not clear.…”

A fine-grained cell type deconvolution of bulk transcriptome from single-cell RNA-seq data reveals myeloid cells heterogeneity in lung adenocarcinomas

“…CIBERSORTx is a computational framework to accurately infer relative abundance of cell type from bulk RNA-seq according to the signature matrix generated from scRNA-seq by means of a deconvolution algorithm [13]. It has been successfully used and validated for revealing immune cell landscapes in melanomas [14], clear-cell renal cell carcinomas [15] and prostate cancer [16]. Unfortunately, CIBERSORTx does not seem to provide a standard procedure or pipeline describing how to integrate scRNA-seq data to construct a reference matrix, as it just uses all the scRNA-seq data as the input.…”