RESUMEN
The tumor microenvironment plays a crucial role in both the development and progression of prostate cancer. Furthermore, identifying protein and gene expression differences between different regions is valuable for treatment development. We applied Digital Spatial Profiling multiplex analysis to formalin-fixed paraffin embedded prostatectomy tissue blocks to investigate protein and transcriptome differences between tumor, tumor-adjacent stroma (TAS), CD45+ tumor, and CD45+ TAS tissue. Differential expression of an immunology/oncology protein panel (n = 58) was measured. OX40L and CTLA4 were expressed at higher levels while 22 other proteins, including CD11c, were expressed at lower levels (FDR < 0.2 and p-value < 0.05) in TAS as compared to tumor epithelia. A tissue microarray analysis of 97 patients with 1547 cores found positive correlations between high expression of CD11c and increased time to recurrence in tumor and TAS, and inverse relationships for CTLA4 and OX40L, where higher expression in tumor correlated with lower time to recurrence, but higher time to recurrence in TAS. Spatial transcriptomic analysis using a Cancer Transcriptome Atlas panel (n = 1825 genes) identified 162 genes downregulated and 69 upregulated in TAS versus tumor, 26 downregulated and 6 upregulated in CD45+ TAS versus CD45+ tumor. We utilized CIBERSORTx to estimate the relative immune cell fractions using CD45+ gene expression and found higher average fractions for memory B, naïve B, and T cells in TAS. In summary, the combination of protein expression differences, immune cell fractions, and correlations of protein expression with time to recurrence suggest that closely examining the tumor microenvironment provides valuable data that can improve prognostication and treatment techniques.
RESUMEN
Prostate cancer (PCa) in Black Americans (BA) is diagnosed at an earlier median age and a more advanced stage than PCa in White Americans (WA). Tumor-adjacent stroma (TAS) plays a critical role in tumorigenesis of prostate cancer. We examined RNA expression in both tumor and TAS of BA compared to WA. After evaluating the geographical ancestry of each sample, preliminary analysis of our own RNA-seq data of 7 BA and 7 WA TAS revealed 1706 downregulated and 1844 upregulated genes in BA relative to WA PCa patients (p adj < 0.05). An assessment of published RNA-seq data of clinically matched tumor-enriched tissues from 15 BA and 30 WA patients revealed 932 upregulated and 476 downregulated genes in BA relative to WA (p adj < 0.05). When TAS and tumor epithelial cohorts were compared for the top 2500 statistically significant genes, immune responses were downregulated in BA vs WA TAS, while T cell-exhaustion pathways and the immune checkpoint gene CTLA4 were upregulated in BA vs WA tumors. We found fewer activated dendritic cells in tumor and more CD8 T-cells in TAS of BA versus WA PCa patients. Further characterization of these differences in the immune response of PCa patients of distinct geographical ancestry could help to improve diagnostics, prognostics, and therapy.
RESUMEN
PURPOSE: Ovarian and uterine clear cell carcinomas (CCCs) are rare but associated with poor prognosis. This study explored RNA transcription patterns characteristic of these tumors. EXPERIMENTAL DESIGN: RNA sequencing (RNA-seq) of 11 ovarian CCCs and five uterine CCCs was performed and compared to publicly available data from high grade serous ovarian cancers (HGSOCs). Ingenuity Pathway Analyses were performed. CIBERSORT analyses estimated relative fractions of 22 immune cell types in each RNA-seq sample. Sequencing data was correlated with PD-L1 immunohistochemical expression. RESULTS: RNA-seq revealed 1,613 downregulated and 1,212 upregulated genes (corrected p < 0.05, |FC |≥10) in ovarian CCC versus HGSOC. Two subgroups were identified in the ovarian CCC, characterized by ethnicity and expression differences in ARID1A. There were 3,252 differentially expressed genes between PD-L1+/- ovarian CCCs, revealing immune response, cell death, and DNA repair networks, negatively correlated with PD-L1 expression, whereas cellular proliferation networks positively correlated with expression. In clear cell ovarian versus clear cell uterine cancer, 1,607 genes were significantly upregulated, and 109 genes were significantly downregulated (corrected p < 0.05, |FC|≥10). Comparative pathway analysis of late and early stage ovarian CCCs revealed unique metabolic and PTEN pathways, whereas uterine CCCs had unique Wnt/Ca+, estrogen receptor, and CCR5 signaling. CIBERSORT analysis revealed that activated mast cells and regulatory T cell populations were relatively enriched in uterine CCCs. The PD-L1+ ovarian CCCs had enriched resting NK cells and memory B cell populations, while PD-L1- had enriched CD8 T-cells, monocytes, eosinophils, and activated dendritic cells. CONCLUSIONS: Unique transcriptional expression profiles distinguish clear cell uterine and ovarian cancers from each other and from other more common histologic subtypes. These insights may aid in devising novel therapeutics.
