TY - JOUR A1 - Krebs, Markus A1 - Solimando, Antonio Giovanni A1 - Kalogirou, Charis A1 - Marquardt, André A1 - Frank, Torsten A1 - Sokolakis, Ioannis A1 - Hatzichristodoulou, Georgios A1 - Kneitz, Susanne A1 - Bargou, Ralf A1 - Kübler, Hubert A1 - Schilling, Bastian A1 - Spahn, Martin A1 - Kneitz, Burkhard T1 - miR-221-3p Regulates VEGFR2 Expression in High-Risk Prostate Cancer and Represents an Escape Mechanism from Sunitinib In Vitro JF - Journal of Clinical Medicine N2 - 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. KW - microRNA-221 KW - high-risk Prostate Cancer KW - angiogenesis KW - Sunitinib KW - Tyrosine kinase inhibition Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-203168 SN - 2077-0383 VL - 9 IS - 3 ER - TY - JOUR A1 - Hartrampf, Philipp E. A1 - Heinrich, Marieke A1 - Seitz, Anna Katharina A1 - Brumberg, Joachim A1 - Sokolakis, Ioannis A1 - Kalogirou, Charis A1 - Schirbel, Andreas A1 - Kübler, Hubert A1 - Buck, Andreas K. A1 - Lapa, Constantin A1 - Krebs, Markus T1 - Metabolic Tumour Volume from PSMA PET/CT Scans of Prostate Cancer Patients during Chemotherapy — Do Different Software Solutions Deliver Comparable Results? JF - Journal of Clinical Medicine N2 - (1) Background: Prostate-specific membrane antigen (PSMA)-derived tumour volume (PSMA-TV) and total lesion PSMA (TL-PSMA) from PSMA PET/CT scans are promising biomarkers for assessing treatment response in prostate cancer (PCa). Currently, it is unclear whether different software tools for assessing PSMA-TV and TL-PSMA produce comparable results. (2) Methods: \(^{68}\)Ga-PSMA PET/CT scans from n = 21 patients with castration-resistant PCa (CRPC) receiving chemotherapy were identified from our single-centre database. PSMA-TV and TL-PSMA were calculated with Syngo.via (Siemens) as well as the freely available Beth Israel plugin for FIJI (Fiji Is Just ImageJ) before and after chemotherapy. While statistical comparability was illustrated and quantified via Bland-Altman diagrams, the clinical agreement was estimated by matching PSMA-TV, TL-PSMA and relative changes of both variables during chemotherapy with changes in serum PSA (ΔPSA) and PERCIST (Positron Emission Response Criteria in Solid Tumors). (3) Results: Comparing absolute PSMA-TV and TL-PSMA as well as Bland–Altman plotting revealed a good statistical comparability of both software algorithms. For clinical agreement, classifying therapy response did not differ between PSMA-TV and TL-PSMA for both software solutions and showed highly positive correlations with BR. (4) Conclusions: due to the high levels of statistical and clinical agreement in our CRPC patient cohort undergoing taxane chemotherapy, comparing PSMA-TV and TL-PSMA determined by Syngo.via and FIJI appears feasible. KW - prostate-specific membrane antigen (PSMA) KW - metabolic tumour volume (MTV) KW - total lesion PSMA KW - biomarker KW - software KW - comparability KW - agreement Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-205893 SN - 2077-0383 VL - 9 IS - 5 ER - TY - JOUR A1 - Krebs, Markus A1 - Behrmann, Christoph A1 - Kalogirou, Charis A1 - Sokolakis, Ioannis A1 - Kneitz, Susanne A1 - Kruithof-de Julio, Marianna A1 - Zoni, Eugenio A1 - Rech, Anne A1 - Schilling, Bastian A1 - Kübler, Hubert A1 - Spahn, Martin A1 - Kneitz, Burkhard T1 - miR-221 Augments TRAIL-mediated apoptosis in prostate cancer cells by inducing endogenous TRAIL expression and targeting the functional repressors SOCS3 and PIK3R1 JF - BioMed Research International N2 - 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. KW - Cancer Cell Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-202480 VL - 2019 ER - TY - JOUR A1 - Hartrampf, Philipp E. A1 - Krebs, Markus A1 - Peter, Lea A1 - Heinrich, Marieke A1 - Ruffing, Julia A1 - Kalogirou, Charis A1 - Weinke, Maximilian A1 - Brumberg, Joachim A1 - Kübler, Hubert A1 - Buck, Andreas K. A1 - Werner, Rudolf A. A1 - Seitz, Anna Katharina T1 - Reduced segmentation of lesions is comparable to whole-body segmentation for response assessment by PSMA PET/CT: initial experience with the keyhole approach JF - Biology N2 - Simple Summary The calculation of PSMA-positive tumor volume (PSMA-TV) of the whole body from PSMA PET scans for response evaluation remains a time-consuming procedure. We hypothesized that it may be possible to quantify changes in PSMA-TV by considering only a limited number of representative tumor lesions. Changes in the whole-body PSMA-TV of 65 patients were comparable to the changes in PSMA-TV after including only the ten largest lesions. Moreover, changes in PSMA-TV correlated well with changes in PSA levels, as did the changes in PSMA-TV with the reduced number of lesions. We conclude that a response assessment using PSMA-TV with a reduced number of lesions is feasible and could lead to a simplified process for evaluating PSMA PET/CT. Abstract (1) Background: Prostate-specific membrane antigen (PSMA) positron emission tomography (PET)-derived parameters, such as the commonly used standardized uptake value (SUV) and PSMA-positive tumor volume (PSMA-TV), have been proposed for response assessment in metastatic prostate cancer (PCa) patients. However, the calculation of whole-body PSMA-TV remains a time-consuming procedure. We hypothesized that it may be possible to quantify changes in PSMA-TV by considering only a limited number of representative lesions. (2) Methods: Sixty-five patients classified into different disease stages were assessed by PSMA PET/CT for staging and restaging after therapy. Whole-body PSMA-TV and whole-body SUV\(_{max}\) were calculated. We then repeated this calculation only including the five or ten hottest or largest lesions. The corresponding serum levels of prostate-specific antigen (PSA) were also determined. The derived delta between baseline and follow-up values provided the following parameters: ΔSUV\(_{maxall}\), ΔSUV\(_{max10}\), ΔSUV\(_{max5}\), ΔPSMA-TV\(_{all}\), ΔPSMA-TV\(_{10}\), ΔPSMA-TV\(_{5}\), ΔPSA. Finally, we compared the findings from our whole-body segmentation with the results from our keyhole approach (focusing on a limited number of lesions) and correlated all values with the biochemical response (ΔPSA). (3) Results: Among patients with metastatic hormone-sensitive PCa (mHSPC), none showed a relevant deviation for ΔSUV\(_{max10}\)/ΔSUV\(_{max5}\) or ΔPSMA-TV\(_{10}\)/ΔPSMA-TV\(_{5}\) compared to ΔSUV\(_{maxall}\) and ΔPSMA-TV\(_{all}\). For patients treated with taxanes, up to 6/21 (28.6%) showed clinically relevant deviations between ΔSUV\(_{maxall}\) and ΔSUV\(_{max10}\) or ΔSUV\(_{max5}\), but only up to 2/21 (9.5%) patients showed clinically relevant deviations between ΔPSMA-TV\(_{all}\) and ΔPSMA-TV\(_{10}\) or ΔPSMA-TV\(_{5}\). For patients treated with radioligand therapy (RLT), up to 5/28 (17.9%) showed clinically relevant deviations between ΔSUV\(_{maxall}\) and ΔSUV\(_{max10}\) or ΔSUV\(_{max5}\), but only 1/28 (3.6%) patients showed clinically relevant deviations between ΔPSMA-TV\(_{all}\) and ΔPSMA-TV\(_{10}\) or ΔPSMA-TV\(_{5}\). The highest correlations with ΔPSA were found for ΔPSMA-TV\(_{all}\) (r ≥ 0.59, p ≤ 0.01), followed by ΔPSMA-TV\(_{10}\) (r ≥ 0.57, p ≤ 0.01) and ΔPSMA-TV\(_{5}\) (r ≥ 0.53, p ≤ 0.02) in all cohorts. ΔPSA only correlated with ΔSUV\(_{maxall}\) (r = 0.60, p = 0.02) and with ΔSUV\(_{max10}\) (r = 0.53, p = 0.03) in the mHSPC cohort, as well as with ΔSUV\(_{maxall}\) (r = 0.51, p = 0.01) in the RLT cohort. (4) Conclusion: Response assessment using PSMA-TV with a reduced number of lesions is feasible, and may allow for a simplified evaluation process for PSMA PET/CT. KW - PET/CT KW - PSMA-TV KW - SUV KW - prostate cancer KW - taxane KW - radioligand therapy Y1 - 2022 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-271191 SN - 2079-7737 VL - 11 IS - 5 ER - TY - JOUR A1 - Marquardt, André A1 - Solimando, Antonio Giovanni A1 - Kerscher, Alexander A1 - Bittrich, Max A1 - Kalogirou, Charis A1 - Kübler, Hubert A1 - Rosenwald, Andreas A1 - Bargou, Ralf A1 - Kollmannsberger, Philip A1 - Schilling, Bastian A1 - Meierjohann, Svenja A1 - Krebs, Markus T1 - Subgroup-Independent Mapping of Renal Cell Carcinoma — Machine Learning Reveals Prognostic Mitochondrial Gene Signature Beyond Histopathologic Boundaries JF - Frontiers in Oncology N2 - 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. KW - kidney cancer KW - pan-RCC KW - machine learning KW - mitochondrial DNA KW - mtDNA KW - mTOR Y1 - 2021 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-232107 SN - 2234-943X VL - 11 ER - TY - JOUR A1 - Kotlyar, Mischa J. A1 - Krebs, Markus A1 - Solimando, Antonio Giovanni A1 - Marquardt, André A1 - Burger, Maximilian A1 - Kübler, Hubert A1 - Bargou, Ralf A1 - Kneitz, Susanne A1 - Otto, Wolfgang A1 - Breyer, Johannes A1 - Vergho, Daniel C. A1 - Kneitz, Burkhard A1 - Kalogirou, Charis T1 - Critical evaluation of a microRNA-based risk classifier predicting cancer-specific survival in renal cell carcinoma with tumor thrombus of the inferior vena cava JF - Cancers N2 - (1) Background: Clear cell renal cell carcinoma extending into the inferior vena cava (ccRCC\(^{IVC}\)) 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 ccRCC\(^{IVC}\) patients. (2) Methods: Examining a single-center cohort of tumor tissue from n = 56 patients with ccRCC\(^{IVC}\), 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 ccRCC\(^{IVC}\) according to CSS. (4) Conclusions: In our retrospective analysis, we successfully validated the miR-based risk classifier within an independent ccRCC\(^{IVC}\) cohort. KW - kidney cancer KW - RCC KW - venous infiltration KW - biomarker KW - miR KW - risk stratification Y1 - 2023 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-311040 SN - 2072-6694 VL - 15 IS - 7 ER -