Metformin Regulates the miR-205/VEGFA Axis in Renal Cell Carcinoma Cells: Exploring a Clinical Synergism with Tyrosine Kinase Inhibitors.

INTRODUCTION: Metformin (MF) intake could be associated with a favorable outcome in sunitinib (SUT)- and axitinib (AX)-treated clear cell renal cell carcinoma (ccRCC) patients. Functionally, MF induces miR-205, a microRNA serving as a tumor suppressor in several cancers. METHODS: Real-time quantitative PCR, viability assays, and Western blotting analyzed MF and SUT/AX effects in RCC4 and 786-O cells. A tetracycline-inducible overexpression model was used to study the role of miR-205 and its known target gene, VEGFA. We analyzed miR-205 and VEGFA within a public and an in-house ccRCC cohort. Human umbilical vein endothelial cell (HUVEC) sprouting assays examined miR-205 effects on angiogenesis initiation. To determine the influence of the von Hippel-Lindau tumor suppressor (VHL), we examined VHLwt reexpressing RCC4 and 786-O cells. RESULTS: Viability assays confirmed a sensitizing effect of MF toward SUT/AX in RCC4 and 786-O cells. Overexpression of miR-205 diminished VEGFA expression - as did treatment with MF. Tumor tissue displayed a downregulation of miR-205 and an upregulation of VEGFA. Accordingly, miR-205 caused less and shorter vessel sprouts in HUVEC assays. Finally, VHLwt-expressing RCC4 and 786-O cells displayed higher miR-205 and lower VEGFA levels. CONCLUSION: Our results support the protective role of MF in ccRCC and offer functional insights into the clinical synergism with tyrosine kinase inhibitors.

The importin beta superfamily member RanBP17 exhibits a role in cell proliferation and is associated with improved survival of patients with HPV+ HNSCC.

BACKGROUND: More than twenty years after its discovery, the role of the importin beta superfamily member Ran GTP-binding protein (RanBP) 17 is still ill defined. Previously, we observed notable RanBP17 RNA expression levels in head and neck squamous cell carcinoma (HNSCC) cell lines with disruptive TP53 mutations. METHODS: We deployed HNSCC cell lines as well as cell lines from other tumor entities such as HCT116, MDA-MB-231 and H460, which were derived from colon, breast and lung cancers respectively. RNAi was used to evaluate the effect of RanBP17 on cell proliferation. FACS analysis was used for cell sorting according to their respective cell cycle phase and for BrdU assays. Immunocytochemistry was deployed for colocalization studies of RanBP17 with Nucleolin and SC35 (nuclear speckles) domains. TCGA analysis was performed for prognostic assessment and correlation analysis of RanBP17 in HNSCC patients. RESULTS: RNAi knockdown of RanBP17, significantly reduced cell proliferation in HNSCC cell lines. This effect was also seen in the HNSCC unrelated cell lines HCT116 and MDA-MB-231. Similarly, inhibiting cell proliferation with cisplatin reduced RanBP17 in keratinocytes but lead to induction in tumor cell lines. A similar observation was made in tumor cell lines after treatment with the EGFR kinase inhibitor AG1478. In addition to previous reports, showing colocalization of RanBP17 with SC35 domains, we observed colocalization of RanBP17 to nuclear bodies that are distinct from nucleoli and SC35 domains. Interestingly, for HPV positive but not HPV negative HNSCC, TCGA data base analysis revealed a strong positive correlation of RanBP17 RNA with patient survival and CDKN2A. CONCLUSIONS: Our data point to a role of RanBP17 in proliferation of HNSCC and other epithelial cells. Furthermore, RanBP17 could potentially serve as a novel prognostic marker for HNSCC patients. However, we noted a major discrepancy between RanBP17 RNA and protein expression levels with the used antibodies. These observations could be explained by the presence of additional RanBP17 splice isoforms and more so of non-coding circular RanBP17 RNA species. These aspects need to be addressed in more detail by future studies.

NRF2 Enables EGFR Signaling in Melanoma Cells.

Receptor tyrosine kinases (RTK) are rarely mutated in cutaneous melanoma, but the expression and activation of several RTK family members are associated with a proinvasive phenotype and therapy resistance. Epidermal growth factor receptor (EGFR) is a member of the RTK family and is only expressed in a subgroup of melanomas with poor prognosis. The insight into regulators of EGFR expression and activation is important for the understanding of the development of this malignant melanoma phenotype. Here, we describe that the transcription factor NRF2, the master regulator of the oxidative and electrophilic stress response, mediates the expression and activation of EGFR in melanoma by elevating the levels of EGFR as well as its ligands EGF and TGFα. ChIP sequencing data show that NRF2 directly binds to the promoter of EGF, which contains a canonical antioxidant response element. Accordingly, EGF is induced by oxidative stress and is also increased in lung adenocarcinoma and head and neck carcinoma with mutationally activated NRF2. In contrast, regulation of EGFR and TGFA occurs by an indirect mechanism, which is enabled by the ability of NRF2 to block the activity of the melanocytic lineage factor MITF in melanoma. MITF effectively suppresses EGFR and TGFA expression and therefore serves as link between NRF2 and EGFR. As EGFR was previously described to stimulate NRF2 activity, the mutual activation of NRF2 and EGFR pathways was investigated. The presence of NRF2 was necessary for full EGFR pathway activation, as NRF2-knockout cells showed reduced AKT activation in response to EGF stimulation compared to controls. Conversely, EGF led to the nuclear localization and activation of NRF2, thereby demonstrating that NRF2 and EGFR are connected in a positive feedback loop in melanoma. In summary, our data show that the EGFR-positive melanoma phenotype is strongly supported by NRF2, thus revealing a novel maintenance mechanism for this clinically challenging melanoma subpopulation.

Comprehensive genetic diagnosis of acute myeloid leukemia by next-generation sequencing.

Differential induction therapy of all subtypes of acute myeloid leukemia other than acute promyelocytic leukemia is impeded by the long time required to complete complex and diverse cytogenetic and molecular genetic analyses for risk stratification or targeted treatment decisions. Here, we describe a reliable, rapid and sensitive diagnostic approach that combines karyotyping and mutational screening in a single, integrated, next-generation sequencing assay. Numerical karyotyping was performed by low coverage whole genome sequencing followed by copy number variation analysis using a novel algorithm based on in silico-generated reference karyotypes. Translocations and DNA variants were examined by targeted resequencing of fusion transcripts and mutational hotspot regions using commercially available kits and analysis pipelines. For the identification of FLT3 internal tandem duplications and KMT2A partial tandem duplications, we adapted previously described tools. In a validation cohort including 22 primary patients' samples, 9/9 numerically normal karyotypes were classified correctly and 30/31 (97%) copy number variations reported by classical cytogenetics and fluorescence in situ hybridization analysis were uncovered by our next-generation sequencing karyotyping approach. Predesigned fusion and mutation panels were validated exemplarily on leukemia cell lines and a subset of patients' samples and identified all expected genomic alterations. Finally, blinded analysis of eight additional patients' samples using our comprehensive assay accurately reproduced reference results. Therefore, calculated karyotyping by low coverage whole genome sequencing enables fast and reliable detection of numerical chromosomal changes and, in combination with panel-based fusion-and mutation screening, will greatly facilitate implementation of subtype-specific induction therapies in acute myeloid leukemia.

RNAi-Mediated Knockdown of Cottontail Rabbit Papillomavirus Oncogenes Using Low-Toxicity Lipopolyplexes as a Paradigm to Treat Papillomavirus-Associated Cancers.

The cottontail rabbit papillomavirus (CRPV)-associated VX2 carcinoma of the New Zealand White rabbit serves as a model system for human papillomavirus (HPV)-associated head and neck squamous cell carcinomas (HNSCCs). The aim of this study was to evaluate the tumor-inhibiting effect of RNAi-mediated knockdown of the CRPV oncogenes, E6 and E7, using siRNA-loaded lipopolyplexes (LPPs). VX2-carcinoma-derived cells were cultured for up to 150 passages. In addition, CRPV E6 and E7 oncogenes were transiently expressed in COS-7 cells. Efficiency and safety of LPPs were evaluated in both VX2 cells and the COS-7 cell line. Both of these in vitro CRPV systems were validated and characterized by fluorescence microscopy, Western blot, and RT-qPCR. Efficient knockdown of CRPV E6 and E7 was achieved in VX2 cells and COS-7 cells pretransfected with CRPV E6 and E7 expression vectors. Knockdown of CRPV oncogenes in VX2 cells resulted in reduced viability, migration, and proliferation and led to a G0/G1 block in the cell cycle. CRPV E6 and E7 siRNA-loaded LPPs could represent promising therapeutic agents serving as a paradigm for the treatment of papillomavirus-positive cancers and could be of value for the treatment of CRPV-associated diseases in the rabbit such as papillomas and cancers of the skin.

Critical Evaluation of a microRNA-Based Risk Classifier Predicting Cancer-Specific Survival in Renal Cell Carcinoma with Tumor Thrombus of the Inferior Vena Cava.

(1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCCIVC) represents a clinical high-risk setting. However, there is substantial heterogeneity within this patient subgroup regarding survival outcomes. Previously, members of our group developed a microRNA(miR)-based risk classifier-containing miR-21-5p, miR-126-3p and miR-221-3p expression-which significantly predicted the cancer-specific survival (CSS) of ccRCCIVC patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCCIVC, we measured the expression levels of miR-21, miR-126, and miR-221 using qRT-PCR. The prognostic impact of clinicopathological parameters and miR expression were investigated via single-variable and multivariable Cox regression. Referring to the previously established risk classifier, we performed Kaplan-Meier analyses for single miR expression levels and the combined risk classifier. Cut-off values and weights within the risk classifier were taken from the previous study. (3) Results: miR-21 and miR-126 expression were significantly associated with lymphonodal status at the time of surgery, the development of metastasis during follow-up, and cancer-related death. In Kaplan-Meier analyses, miR-21 and miR-126 significantly impacted CSS in our cohort. Moreover, applying the miR-based risk classifier significantly stratified ccRCCIVC according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCCIVC cohort.

Predicting Microenvironment in CXCR4- and FAP-Positive Solid Tumors-A Pan-Cancer Machine Learning Workflow for Theranostic Target Structures.

(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.

Visual Clustering of Transcriptomic Data from Primary and Metastatic Tumors-Dependencies and Novel Pitfalls.

Personalized oncology is a rapidly evolving area and offers cancer patients therapy options that are more specific than ever. However, there is still a lack of understanding regarding transcriptomic similarities or differences of metastases and corresponding primary sites. Applying two unsupervised dimension reduction methods (t-Distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP)) on three datasets of metastases (n =682 samples) with three different data transformations (unprocessed, log10 as well as log10 + 1 transformed values), we visualized potential underlying clusters. Additionally, we analyzed two datasets (n =616 samples) containing metastases and primary tumors of one entity, to point out potential familiarities. Using these methods, no tight link between the site of resection and cluster formation outcome could be demonstrated, or for datasets consisting of solely metastasis or mixed datasets. Instead, dimension reduction methods and data transformation significantly impacted visual clustering results. Our findings strongly suggest data transformation to be considered as another key element in the interpretation of visual clustering approaches along with initialization and different parameters. Furthermore, the results highlight the need for a more thorough examination of parameters used in the analysis of clusters.

Identifying New Potential Biomarkers in Adrenocortical Tumors Based on mRNA Expression Data Using Machine Learning.

Adrenocortical carcinoma (ACC) is a rare disease, associated with poor survival. Several "multiple-omics" studies characterizing ACC on a molecular level identified two different clusters correlating with patient survival (C1A and C1B). We here used the publicly available transcriptome data from the TCGA-ACC dataset (n = 79), applying machine learning (ML) methods to classify the ACC based on expression pattern in an unbiased manner. UMAP (uniform manifold approximation and projection)-based clustering resulted in two distinct groups, ACC-UMAP1 and ACC-UMAP2, that largely overlap with clusters C1B and C1A, respectively. However, subsequent use of random-forest-based learning revealed a set of new possible marker genes showing significant differential expression in the described clusters (e.g., SOAT1, EIF2A1). For validation purposes, we used a secondary dataset based on a previous study from our group, consisting of 4 normal adrenal glands and 52 benign and 7 malignant tumor samples. The results largely confirmed those obtained for the TCGA-ACC cohort. In addition, the ENSAT dataset showed a correlation between benign adrenocortical tumors and the good prognosis ACC cluster ACC-UMAP1/C1B. In conclusion, the use of ML approaches re-identified and redefined known prognostic ACC subgroups. On the other hand, the subsequent use of random-forest-based learning identified new possible prognostic marker genes for ACC.

Subgroup-Independent Mapping of Renal Cell Carcinoma-Machine Learning Reveals Prognostic Mitochondrial Gene Signature Beyond Histopathologic Boundaries.

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.

Cocaine reverses the changes in GABAA subunits and in glutamic acid decarboxylase isoenzymes mRNA expression induced by neonatal 6-hydroxydopamine.

Attention-deficit/hyperactivity disorder is related to altered functions in the dopaminergic and GABAergic pathways of cortical and subcortical brain areas The hyperactivity of attention-deficit/hyperactivity disorder is commonly modelled in rats after neonatal lesion with 6-hydroxydopamine (6-OHDA), and amphetamines are effective in reducing hyperactivity in this animal model. Our objectives were to evaluate whether cocaine reverses the motor hyperactivity of 6-OHDA-lesioned rats and to verify cocaine effects in altered mRNA expression of alpha2, alpha4, beta1 and beta2-GABAA subunits and GAD isoenzymes in the prefrontal cortex, hippocampus and striatum of 6-OHDA-lesioned rats. On PND4, 6-OHDA-lesioned or sham rats received 6-OHDA (100 microg intracisternal) or vehicle. Cocaine solution (0.1 mg/ml/day) was offered when adult for 23 days, using the two-bottle choice procedure. The subjects were evaluated in an open-field on the last day of cocaine treatment. 6-OHDA-lesioned rats showed increased locomotion and this hyperactivity was reversed during cocaine self-administration. 6-OHDA lesion caused an increase in the mRNA expression of GABAA subunits in specific brain areas and GAD isoenzymes in the hippocampus and striatum. Increased GAD65 and decreased GAD67 mRNA expression were also shown in the prefrontal cortex. Cocaine self-administration attenuated the effects of 6-OHDA lesions on the mRNA expression of alpha2-GABAA and beta2-GABAA subunits in the prefrontal cortex, reversed the mRNA expression of alpha2-GABAA subunits in the striatum and of alpha4-GABAA subunits in the prefrontal cortex and in the hippocampus, and reversed the mRNA expression of GAD65 and GAD67 in the brain areas studied. Our findings suggest that cocaine reverses some mRNA changes of GABAA subunits and GAD isoenzymes in reward circuits and the behavioural hyperactivity caused by 6-OHDA lesion.

miR-221-3p Regulates VEGFR2 Expression in High-Risk Prostate Cancer and Represents an Escape Mechanism from Sunitinib In Vitro.

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.

Development of a new macrophage-specific TRAP mouse (MacTRAP) and definition of the renal macrophage translational signature.

Tissue macrophages play an important role in organ homeostasis, immunity and the pathogenesis of various inflammation-driven diseases. One major challenge has been to selectively study resident macrophages in highly heterogeneous organs such as kidney. To address this problem, we adopted a Translational Ribosome Affinity Purification (TRAP)- approach and designed a transgene that expresses an eGFP-tagged ribosomal protein (L10a) under the control of the macrophage-specific c-fms promoter to generate c-fms-eGFP-L10a transgenic mice (MacTRAP). Rigorous characterization found no gross abnormalities in MacTRAP mice and confirmed transgene expression across various organs. Immunohistological analyses of MacTRAP kidneys identified eGFP-L10a expressing cells in the tubulointerstitial compartment which stained positive for macrophage marker F4/80. Inflammatory challenge led to robust eGFP-L10a upregulation in kidney, confirming MacTRAP responsiveness in vivo. We successfully extracted macrophage-specific polysomal RNA from MacTRAP kidneys and conducted RNA sequencing followed by bioinformatical analyses, hereby establishing a comprehensive and unique in vivo gene expression and pathway signature of resident renal macrophages. In summary, we created, validated and applied a new, responsive macrophage-specific TRAP mouse line, defining the translational profile of renal macrophages and dendritic cells. This new tool may be of great value for the study of macrophage biology in different organs and various models of injury and disease.

The transcription factor NRF2 enhances melanoma malignancy by blocking differentiation and inducing COX2 expression.

The transcription factor NRF2 is the major mediator of oxidative stress responses and is closely connected to therapy resistance in tumors harboring activating mutations in the NRF2 pathway. In melanoma, such mutations are rare, and it is unclear to what extent melanomas rely on NRF2. Here we show that NRF2 suppresses the activity of the melanocyte lineage marker MITF in melanoma, thereby reducing the expression of pigmentation markers. Intriguingly, we furthermore identified NRF2 as key regulator of immune-modulating genes, linking oxidative stress with the induction of cyclooxygenase 2 (COX2) in an ATF4-dependent manner. COX2 is critical for the secretion of prostaglandin E2 and was strongly induced by H2O2 or TNFα only in presence of NRF2. Induction of MITF and depletion of COX2 and PGE2 were also observed in NRF2-deleted melanoma cells in vivo. Furthermore, genes corresponding to the innate immune response such as RSAD2 and IFIH1 were strongly elevated in absence of NRF2 and coincided with immune evasion parameters in human melanoma datasets. Even in vitro, NRF2 activation or prostaglandin E2 supplementation blunted the induction of the innate immune response in melanoma cells. Transcriptome analyses from lung adenocarcinomas indicate that the observed link between NRF2 and the innate immune response is not restricted to melanoma.

Virome Analysis Reveals No Association of Head and Neck Vascular Anomalies with an Active Viral Infection.

BACKGROUND/AIM: Vascular anomalies encompass different vascular malformations [arteriovenous (AVM), lymphatic (LM), venous lymphatic (VLM), venous (VM)] and vascular tumors such as hemangiomas (HA). The pathogenesis of vascular anomalies is still poorly understood. Viral infection was speculated as a possible underlying cause. MATERIALS AND METHODS: A total of 13 human vascular anomalies and three human skin control tissues were used for viral analysis. RNA derived from AVM (n=4) and normal skin control (n=3) tissues was evaluated by RNA sequencing. The Virome Capture Sequencing Platform for Vertebrate Viruses (VirCapSeq-VERT) was deployed on 10 tissues with vascular anomalies (2×AVM, 1×HA, 1×LM, 2×VLM, 4×VM). RESULTS: RNA sequencing did not show any correlation of AVM with viral infection. By deploying VirCapSeq-VERT, no consistent viral association was seen in the tested tissues. CONCLUSION: The analysis does not point to the presence of an active viral infection in vascular anomalies. However, transient earlier viral infections, e.g. during pregnancy, cannot be excluded with this approach.