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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.
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.
Although decision making strategy based on clinico-histopathological criteria is well established, renal cell carcinoma (RCC) represents a spectrum of biological ecosystems characterized by distinct genetic and molecular alterations, diverse clinical courses and potential specific therapeutic vulnerabilities. Given the plethora of drugs available, the subtype-tailored treatment to RCC subtype holds the potential to improve patient outcome, shrinking treatment-related morbidity and cost. The emerging knowledge of the molecular taxonomy of RCC is evolving, whilst the antiangiogenic and immunotherapy landscape maintains and reinforces their potential. Although several prognostic factors of survival in patients with RCC have been described, no reliable predictive biomarkers of treatment individual sensitivity or resistance have been identified. In this review, we summarize the available evidence able to prompt more precise and individualized patient selection in well-designed clinical trials, covering the unmet need of medical choices in the era of next-generation anti-angiogenesis and immunotherapy.
(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.
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.
Clear cell renal cell carcinoma (ccRCC) characterized by a tumor thrombus (TT) extending into the inferior vena cava (IVC) generally indicates poor prognosis. Nevertheless, the risk for tumor recurrence after nephrectomy and thrombectomy varies. An applicable and accurate prediction system to select ccRCC patients with TT of the IVC (ccRCC/TT) at high risk after nephrectomy is urgently needed, but has not been established up to now. To our knowledge, a possible role of microRNAs (miRs) for the development of ccRCC/TT or their impact as prognostic markers in ccRCC/TT has not been explored yet. Therefore, we analyzed the expression of the previously described onco-miRs miR-200c, miR-210, miR-126, miR-221, let-7b, miR-21, miR-143 and miR-141 in a study collective of 74 ccRCC patients. Using the expression profiles of these eight miRs we developed classification systems that accurately differentiate ccRCC from non-cancerous renal tissue and ccRCC/TT from tumors without TT. In the subgroup of 37 ccRCC/TT cases we found that miR-21, miR-126, and miR-221 predicted cancer related death (CRD) accurately and independently from other clinico-pathological features. Furthermore, a combined risk score based on the expression of miR-21, miR-126 and miR-221 was developed and showed high sensitivity and specificity to predict cancer specific survival (CSS) in ccRCC/TT. Using the combined risk score we were able to classify ccRCC/TT patients correctly into high and low risk cases. The risk stratification by the combined risk score (CRS) will benefit from further cohort validation and might have potential for clinical application as a molecular prediction system to identify high- risk ccRCC/TT patients.
Background
Prostate cancer (PCa) is the most frequent cancer in men. The prognosis of PCa is heterogeneous with many clinically indolent tumors and rare highly aggressive cases. Reliable tissue markers of prognosis are lacking. Active cholesteryl ester synthesis has been associated with prostate cancer aggressiveness. Sterol-O-Acyl transferases (SOAT) 1 and 2 catalyze cholesterol esterification in humans.
Objective
To investigate the value of SOAT1 and SOAT2 tissue expression as prognostic markers in high risk PCa.
Patients and Methods
Formalin-fixed paraffin-embedded tissue samples from 305 high risk PCa cases treated with radical prostatectomy were analyzed for SOAT1 and SOAT2 protein expression by semi-quantitative immunohistochemistry. The Kaplan-Meier method and Cox proportional hazards modeling were used to compare outcome.
Main Outcome Measure
Biochemical recurrence (BCR) free survival.
Results
SOAT1 expression was high in 73 (25%) and low in 219 (75%; not evaluable: 13) tumors. SOAT2 was highly expressed in 40 (14%) and at low levels in 249 (86%) samples (not evaluable: 16). By Kaplan-Meier analysis, we found significantly shorter median BCR free survival of 93 months (95% confidence interval 23.6-123.1) in patients with high SOAT1 vs. 134 months (112.6-220.2, Log-rank p < 0.001) with low SOAT1. SOAT2 expression was not significantly associated with BCR. After adjustment for age, preoperative PSA, tumor stage, Gleason score, resection status, lymph node involvement and year of surgery, high SOAT1 but not SOAT2 expression was associated with shorter BCR free survival with a hazard ratio of 2.40 (95% CI 1.57-3.68, p < 0.001). Time to clinical recurrence and overall survival were not significantly associated with SOAT1 and SOAT2 expression CONCLUSIONS: SOAT1 expression is strongly associated with BCR free survival alone and after multivariable adjustment in high risk PCa. SOAT1 may serve as a histologic marker of prognosis and holds promise as a future treatment target.
A novel and convenient methodology for the one-pot synthesis of sterically congested triarylboranes by using bench-stable aryltrifluoroborates as the boron source is reported. This procedure gives systematic access to symmetrically and unsymmetrically substituted triarylboranes of the types BAr\(_{2}\)Ar’ and BArAr'Ar’’, respectively. Three unsymmetrically substituted triarylboranes as well as their iridium-catalyzed C−H borylation products are reported. These borylated triarylboranes contain one to three positions that can subsequently be orthogonally functionalized in follow-up reactions, such as Suzuki-Miyaura cross-couplings or Sonogashira couplings.
The treatment of high-risk prostate cancer (HRPCa) is a tremendous challenge for uro-oncologists. The identification of predictive moleculobiological markers allowing risk assessment of lymph node metastasis and systemic progression is essential in establishing effective treatment. In the current study, we investigate the prognostic potential of miR-205 in HRPCa study and validation cohorts, setting defined clinical endpoints for both. We demonstrate miR-205 to be significantly down-regulated in over 70% of the HRPCa samples analysed and that reconstitution of miR-205 causes inhibition of proliferation and invasiveness in prostate cancer (PCa) cell lines. Additionally, miR-205 is increasingly down-regulated in lymph node metastases compared to the primary tumour indicating that miR-205 plays a role in migration of PCa cells from the original location into extraprostatic tissue. Nevertheless, down-regulation of miR-205 in primary PCa was not correlated to the synchronous presence of metastasis and failed to predict the outcome for HRPCa patients. Moreover, we found a tendency for miR-205 up-regulation to correlate with an adverse outcome of PCa patients suggesting a pivotal role of miR-205 in tumourigenesis. Overall, we showed that miR-205 is involved in the development and metastasis of PCa, but failed to work as a useful clinical biomarker in HRPCa. These findings might have implications for the use of miR-205 as a prognostic or therapeutic target in HRPCa.
microRNA-221 und ihr Einfluss auf Zytokin-vermittelte Signalwege im Hochrisiko-Karzinom der Prostata
(2016)
Der klinische Verlauf von Prostatakarzinom(PCa)-Erkrankungen ist extrem unterschiedlich und lässt sich mit den bisher üblichen Verfahren wie der feingeweblichen Beurteilung der Prostatastanzbiopsie bzw. des OP-Präparates und der PSA-Wert-Bestimmung nur unzureichend vorhersagen. Für eine bessere Versorgung von PCa-Patienten sind deshalb neuartige Marker notwendig, die das individuelle Progressions-Risiko bestimmen. Ein hoffnungsvoller Ansatz sind miRNA-Vertreter als Prognose-Parameter. Besonders interessant in dieser Hinsicht ist miR-221, die im PCa-Gewebe signifikant niedriger exprimiert wird. Jedoch existieren für diese in den meisten Neoplasien als Onkogen betrachtete miRNA kaum Erklärungsansätze für eine tumorsuppressive Funktion im PCa.
Die vorliegende Arbeit konnte mit Hilfe von Microarray-basierten Expressionsanalysen und deren bioinformatischer Auswertung sowie zell- und molekularbiologischen Experimenten erstmals zeigen, dass miR-221 das protektive Interferon-Signal in PCa-Zellen stärkt und auf diese Weise deren Proliferation hemmt. Daneben konnten zwei prominente Inhibitoren dieses Signals, IRF2 und SOCS3, als neue Zielgene von miR-221 in vitro nachgewiesen und eine Korrelation von miR-221 mit diesen Zielgenen auch in PCa-Nativmaterial identifiziert werden. Somit konnte erstmals ein Mechanismus der – vorher lediglich aufgrund der Herabregulation in PCa-Nativmaterial postulierten – tumorsuppressiven Funktion von miR-221 im Rahmen der PCa-Entstehung und -Progression dargestellt werden.
Eine Aktivierung des JAK / STAT-vermittelten Interferon-Signals durch miR-221 erscheint auch in einem breiteren infektiologischen Kontext interessant – sind doch zahlreiche Virenarten wie das HI-Virus, Hepatitis- und Herpesviren in der Lage, die zelluläre miR-221-Expression zu vermindern und auf diese Weise wohl das antivirale Interferon-Signal zu umgehen. Die Erhöhung der zellulären miR-221-Spiegel könnte nach diesem Prinzip auch Interferon-basierte Therapie-Strategien unterstützen bzw. erst ermöglichen.
Für das PCa müssen weitere experimentelle sowie klinisch-translationale Untersuchungen zeigen, ob miR-221 als Bestandteil einer Biomarker-Signatur dazu beiträgt, Patienten mit einem letalen PCa frühzeitig zu identifizieren und der dringend notwendigen Primärtherapie bzw. einer adjuvanten Behandlung zuzuführen. Im Gegenzug könnte zahlreichen Patienten, deren (hohe) miR-221-Expression im Tumorgewebe einen günstigeren Verlauf prognostiziert, die übermäßige Therapie erspart werden.