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miR-221 is regarded as an oncogene in many malignancies, and miR-221-mediated resistance towards TRAIL was one of the first oncogenic roles shown for this small noncoding RNA. In contrast, miR-221 is downregulated in prostate cancer (PCa), thereby implying a tumour suppressive function. By using proliferation and apoptosis assays, we show a novel feature of miR-221 in PCa cells: instead of inducing TRAIL resistance, miR-221 sensitized cells towards TRAIL-induced proliferation inhibition and apoptosis induction. Partially responsible for this effect was the interferon-mediated gene signature, which among other things contained an endogenous overexpression of the TRAIL encoding gene TNFSF10. This TRAIL-friendly environment was provoked by downregulation of the established miR-221 target gene SOCS3. Moreover, we introduced PIK3R1 as a target gene of miR-221 in PCa cells. Proliferation assays showed that siRNA-mediated downregulation of SOCS3 and PIK3R1 mimicked the effect of miR-221 on TRAIL sensitivity. Finally, Western blotting experiments confirmed lower amounts of phospho-Akt after siRNA-mediated downregulation of PIK3R1 in PC3 cells. Our results further support the tumour suppressing role of miR-221 in PCa, since it sensitises PCa cells towards TRAIL by regulating the expression of the oncogenes SOCS3 and PIK3R1. Given the TRAIL-inhibiting effect of miR-221 in various cancer entities, our results suggest that the influence of miR-221 on TRAIL-mediated apoptosis is highly context- and entity-dependent.
Downregulation of miR-221-3p expression in prostate cancer (PCa) predicted overall and cancer-specific survival of high-risk PCa patients. Apart from PCa, miR-221-3p expression levels predicted a response to tyrosine kinase inhibitors (TKI) in clear cell renal cell carcinoma (ccRCC) patients. Since this role of miR-221-3p was explained with a specific targeting of VEGFR2, we examined whether miR-221-3p regulated VEGFR2 in PCa. First, we confirmed VEGFR2/KDR as a target gene of miR-221-3p in PCa cells by applying Luciferase reporter assays and Western blotting experiments. Although VEGFR2 was mainly downregulated in the PCa cohort of the TCGA (The Cancer Genome Atlas) database, VEGFR2 was upregulated in our high-risk PCa cohort (n = 142) and predicted clinical progression. In vitro miR-221-3p acted as an escape mechanism from TKI in PC3 cells, as displayed by proliferation and apoptosis assays. Moreover, we confirmed that Sunitinib induced an interferon-related gene signature in PC3 cells by analyzing external microarray data and by demonstrating a significant upregulation of miR-221-3p/miR-222-3p after Sunitinib exposure. Our findings bear a clinical perspective for high-risk PCa patients with low miR-221-3p levels since this could predict a favorable TKI response. Apart from this therapeutic niche, we identified a partially oncogenic function of miR-221-3p as an escape mechanism from VEGFR2 inhibition.
(1) Background: C-X-C Motif Chemokine Receptor 4 (CXCR4) and Fibroblast Activation Protein Alpha (FAP) are promising theranostic targets. However, it is unclear whether CXCR4 and FAP positivity mark distinct microenvironments, especially in solid tumors. (2) Methods: Using Random Forest (RF) analysis, we searched for entity-independent mRNA and microRNA signatures related to CXCR4 and FAP overexpression in our pan-cancer cohort from The Cancer Genome Atlas (TCGA) database — representing n = 9242 specimens from 29 tumor entities. CXCR4- and FAP-positive samples were assessed via StringDB cluster analysis, EnrichR, Metascape, and Gene Set Enrichment Analysis (GSEA). Findings were validated via correlation analyses in n = 1541 tumor samples. TIMER2.0 analyzed the association of CXCR4 / FAP expression and infiltration levels of immune-related cells. (3) Results: We identified entity-independent CXCR4 and FAP gene signatures representative for the majority of solid cancers. While CXCR4 positivity marked an immune-related microenvironment, FAP overexpression highlighted an angiogenesis-associated niche. TIMER2.0 analysis confirmed characteristic infiltration levels of CD8+ cells for CXCR4-positive tumors and endothelial cells for FAP-positive tumors. (4) Conclusions: CXCR4- and FAP-directed PET imaging could provide a non-invasive decision aid for entity-agnostic treatment of microenvironment in solid malignancies. Moreover, this machine learning workflow can easily be transferred towards other theranostic targets.
Background: Renal cell carcinoma (RCC) is divided into three major histopathologic groups—clear cell (ccRCC), papillary (pRCC) and chromophobe RCC (chRCC). We performed a comprehensive re-analysis of publicly available RCC datasets from the TCGA (The Cancer Genome Atlas) database, thereby combining samples from all three subgroups, for an exploratory transcriptome profiling of RCC subgroups.
Materials and Methods: We used FPKM (fragments per kilobase per million) files derived from the ccRCC, pRCC and chRCC cohorts of the TCGA database, representing transcriptomic data of 891 patients. Using principal component analysis, we visualized datasets as t-SNE plot for cluster detection. Clusters were characterized by machine learning, resulting gene signatures were validated by correlation analyses in the TCGA dataset and three external datasets (ICGC RECA-EU, CPTAC-3-Kidney, and GSE157256).
Results: Many RCC samples co-clustered according to histopathology. However, a substantial number of samples clustered independently from histopathologic origin (mixed subgroup)—demonstrating divergence between histopathology and transcriptomic data. Further analyses of mixed subgroup via machine learning revealed a predominant mitochondrial gene signature—a trait previously known for chRCC—across all histopathologic subgroups. Additionally, ccRCC samples from mixed subgroup presented an inverse correlation of mitochondrial and angiogenesis-related genes in the TCGA and in three external validation cohorts. Moreover, mixed subgroup affiliation was associated with a highly significant shorter overall survival for patients with ccRCC—and a highly significant longer overall survival for chRCC patients.
Conclusions: Pan-RCC clustering according to RNA-sequencing data revealed a distinct histology-independent subgroup characterized by strengthened mitochondrial and weakened angiogenesis-related gene signatures. Moreover, affiliation to mixed subgroup went along with a significantly shorter overall survival for ccRCC and a longer overall survival for chRCC patients. Further research could offer a therapy stratification by specifically addressing the mitochondrial metabolism of such tumors and its microenvironment.
Prostate-specific membrane antigen (PSMA)-directed positron emission tomography/computed tomography (PET/CT) is increasingly utilized for staging of men with prostate cancer (PC). To increase interpretive certainty, the standardized PSMA reporting and data system (RADS) has been proposed. Using PSMA-RADS, we characterized lesions in 18 patients imaged with \(^{18}\)F-PSMA-1007 PET/CT for primary staging and determined the stability of semi-quantitative parameters. Six hundred twenty-three lesions were categorized according to PSMA-RADS and manually segmented. In this context, PSMA-RADS-3A (soft-tissue) or -3B (bone) lesions are defined as being indeterminate for the presence of PC. For PMSA-RADS-4 and -5 lesions; however, PC is highly likely or almost certainly present [with further distinction based on absence (PSMA-RADS-4) or presence (PSMA-RADS-5) of correlative findings on CT]. Standardized uptake values (SUV\(_{max}\), SUV\(_{peak}\), SUV\(_{mean}\)) were recorded, and volumetric parameters [PSMA-derived tumor volume (PSMA-TV); total lesion PSMA (TL-PSMA)] were determined using different maximum intensity thresholds (MIT) (40 vs. 45 vs. 50%). SUV\(_{max}\) was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories (p ≤ 0.0322). In particular, the clinically challenging PSMA-RADS-3A lesions showed significantly lower SUV\(_{max}\) and SUV\(_{peak}\) compared to the entire PSMA-RADS-4 or -5 cohort (p < 0.0001), while for PSMA-RADS-3B this only applies when compared to the entire PSMA-RADS-5 cohort (p < 0.0001), but not to the PSMA-RADS-4 cohort (SUV\(_{max}\), p = 0.07; SUV\(_{peak}\), p = 0.08). SUV\(_{mean}\) (p = 0.30) and TL-PSMA (p = 0.16) in PSMA-RADS-5 lesions were not influenced by changing the MIT, while PSMA-TV showed significant differences when comparing 40 vs. 50% MIT (p = 0.0066), which was driven by lymph nodes (p = 0.0239), but not bone lesions (p = 0.15). SUV\(_{max}\) was significantly higher in PSMA-RADS-5 lesions compared to all other PSMA-RADS categories in \(^{18}\)F-PSMA-1007 PET/CT. As such, the latter parameter may assist the interpreting molecular imaging specialist in assigning the correct PSMA-RADS score to sites of disease, thereby increasing diagnostic certainty. In addition, changes of the MIT in PSMA-RADS-5 lesions had no significant impact on SUV\(_{mean}\) and TL-PSMA in contrast to PSMA-TV.