[en] Several lines of evidence indicate that Sirt1, a class III histone deacetylase (HDAC) is implicated in the initiation and progression of malignancies and thus gained attraction as druggable target. Since data on the role of Sirt1 in pancreatic ductal adenocarcinoma (PDAC) are sparse, we investigated the expression profile and prognostic significance of Sirt1 in vivo as well as cellular effects of Sirt1 inhibition in vitro. Sirt1 expression was analyzed by immunohistochemistry in a large cohort of PDACs and correlated with clinicopathological and survival data. Furthermore, we investigated the impact of overexpression and small molecule inhibition on Sirt1 in pancreatic cancer cell culture models including combinatorial treatment with chemotherapy and EGFR-inhibition. Cellular events were measured quantitatively in real time and corroborated by conventional readouts including FACS analysis and MTT assays. We detected nuclear Sirt1 expression in 36 (27.9%) of 129 PDACs. SIRT1 expression was significantly higher in poorly differentiated carcinomas. Strong SIRT1 expression was a significant predictor of poor survival both in univariate (p = 0.002) and multivariate (HR 1.65, p = 0.045) analysis. Accordingly, overexpression of Sirt1 led to increased cell viability, while small molecule inhibition led to a growth arrest in pancreatic cancer cells and impaired cell survival. This effect was even more pronounced in combinatorial regimens with gefitinib, but not in combination with gemcitabine. Sirt1 is an independent prognosticator in PDACs and plays an important role in pancreatic cancer cell growth, which can be levered out by small molecule inhibition. Our data warrant further studies on SIRT1 as a novel chemotherapeutic target in PDAC

[en] MRI has limited ability to detect multifocal disease or the full extent of prostate involvement with clinically significant prostate cancer (sPC). We compare the spatial co-localization at sextant resolution of MRI lesions and histopathological mapping by combined targeted and extended systematic biopsies. Sextants were mapped for sPC (ISUP group $\ge <!--\; ???\; -->$ 2) by 24-core transperineal systematic biopsies in 316 patients with suspicion for sPC and by MR lesions of PI-RADS score of $\ge <!--\; ???\; -->$ 3. The gold standard is combined systematic (median 23 cores) and targeted biopsies. Of 316 men, 121 (38%) harbored sPC. Of these 121 patients, 4 (3%) had a negative MRI. MRI correctly identified 117/121 (97%) patients with sPC. In these patients, mpMRI missed no additional sPC in 96 (82%), while MRI-negative sPC lesions were present in 21 patients (18%). Of 1896 sextants, 379 (20%) harbored sPC. MR-positive sextants contained sPC in 26% (337/1275), compared to 7% (42/621) in MR-negative sextants. On a patient basis, sensitivity was 0.97, specificity 0.22, positive predictive value 0.43, and negative predictive value 0.91. On a sextant basis, sensitivity was 0.73, specificity 0.38, positive predictive value 0.26, and negative predictive value 0.93. MpMRI mapping agreed well with histopathology with, at the observed sPC prevalence and on a patient basis, excellent sensitivity and negative predictive value, and acceptable specificity and positive predictive value for sPC. However, 18% of sPC was outside the mpMRI mapped region, quantifying limitations of MRI for complete localization of disease extent. (orig.)

[en] The aim of the present study was to explore the clinical feasibility and reproducibility of a comprehensive whole-body ¹⁸F-PSMA-1007-PET/MRI protocol for imaging prostate cancer (PC) patients. Eight patients with high-risk biopsy-proven PC underwent a whole-body PET/MRI (3 h p.i.) including a multi-parametric prostate MRI after ¹⁸F-PSMA-1007-PET/CT (1 h p.i.) which served as reference. Seven patients presented with non-treated PC, whereas one patient presented with biochemical recurrence. SUV_mean-quantification was performed using a 3D-isocontour volume-of-interest. Imaging data was consulted for TNM-staging and compared with histopathology. PC was confirmed in 4/7 patients additionally by histopathology after surgery. PET-artifacts, co-registration of pelvic PET/MRI and MRI-data were assessed (PI-RADS 2.0). The examinations were well accepted by patients and comprised 1 h. SUV_mean-values between PET/CT (1 h p.i.) and PET/MRI (3 h p.i.) were significantly correlated (p < 0.0001, respectively) and similar to literature of ¹⁸F-PSMA-1007-PET/CT 1 h vs 3 h p.i. The dominant intraprostatic lesion could be detected in all seven patients in both PET and MRI. T2c, T3a, T3b and T4 features were detected complimentarily by PET and MRI in five patients. PET/MRI demonstrated moderate photopenic PET-artifacts surrounding liver and kidneys representing high-contrast areas, no PET-artifacts were observed for PET/CT. Simultaneous PET-readout during prostate MRI achieved optimal co-registration results. The presented ¹⁸F-PSMA-1007-PET/MRI protocol combines efficient whole-body assessment with high-resolution co-registered PET/MRI of the prostatic fossa for comprehensive oncological staging of patients with PC. (orig.)

[en] To simulate clinical deployment, evaluate performance, and establish quality assurance of a deep learning algorithm (U-Net) for detection, localization, and segmentation of clinically significant prostate cancer (sPC), ISUP grade group ≥ 2, using bi-parametric MRI. In 2017, 284 consecutive men in active surveillance, biopsy-naïve or pre-biopsied, received targeted and extended systematic MRI/transrectal US-fusion biopsy, after examination on a single MRI scanner (3 T). A prospective adjustment scheme was evaluated comparing the performance of the Prostate Imaging Reporting and Data System (PI-RADS) and U-Net using sensitivity, specificity, predictive values, and the Dice coefficient. In the 259 eligible men (median 64 [IQR 61–72] years), PI-RADS had a sensitivity of 98% [106/108]/84% [91/108] with a specificity of 17% [25/151]/58% [88/151], for thresholds at ≥ 3/≥ 4 respectively. U-Net using dynamic threshold adjustment had a sensitivity of 99% [107/108]/83% [90/108] (p > 0.99/> 0.99) with a specificity of 24% [36/151]/55% [83/151] (p > 0.99/> 0.99) for probability thresholds d3 and d4 emulating PI-RADS ≥ 3 and ≥ 4 decisions respectively, not statistically different from PI-RADS. Co-occurrence of a radiological PI-RADS ≥ 4 examination and U-Net ≥ d3 assessment significantly improved the positive predictive value from 59 to 63% (p = 0.03), on a per-patient basis. U-Net has similar performance to PI-RADS in simulated continued clinical use. Regular quality assurance should be implemented to ensure desired performance.

[en] Histone deacetylase inhibitors are promising new substances in cancer therapy and have also been shown to sensitize different tumor cells to irradiation (XRT). We explored the effect as well as the radiosensitizing properties of suberoylanilide hydroxamic acid (SAHA) in vivo in a malignant rhabdoid tumor (MRT) mouse model. Potential radiosensitization by SAHA was assessed in MRT xenografts by analysis of tumor growth delay, necrosis (HE), apoptosis (TUNEL), proliferation (ki-67) and γH2AX expression as well as dynamic "1"8F-Fluorodeoxyglucose Positron Emission Tomography ("1"8F-FDG -PET) after treatment with either SAHA alone, single-dose (10 Gy) or fractionated XRT (3 × 3Gy) solely as well as in combination with SAHA compared to controls. SAHA only had no significant effect on tumor growth. Combination of SAHA for 8 days with single-dose XRT resulted in a higher number of complete remissions, but failed to prove a significant growth delay compared to XRT only. In contrast fractionated XRT plus SAHA for 3 weeks did induce significant tumor growth delay in MRT-xenografts. The histological examination showed a significant effect of XRT in tumor necrosis, expression of Ki-67, γH2AX and apoptosis. SAHA only had no significant effect in the histological examination. Comparison of xenografts treated with XRT and XRT plus SAHA revealed a significantly increased γH2AX expression and apoptosis induction in the mice tumors after combination treatment with single-dose as well as fractionated XRT. The combination of SAHA with XRT showed a tendency to increased necrosis and decrease of proliferation compared to XRT only, which, however, was not significant. The "1"8F-FDG-PET results showed no significant differences in the standard uptake value or glucose transport kinetics after either treatment. SAHA did not have a significant effect alone, but proved to enhance the effect of XRT in our MRT in vivo model

[en] The introduction of next-generation sequencing (NGS) in the field of cancer research has boosted worldwide efforts of genome-wide personalized oncology aiming at identifying predictive biomarkers and novel actionable targets. Despite considerable progress in understanding the molecular biology of distinct cancer entities by the use of this revolutionary technology and despite contemporaneous innovations in drug development, translation of NGS findings into improved concepts for cancer treatment remains a challenge. The aim of this article is to describe shortly the NGS platforms for DNA sequencing and in more detail key achievements and unresolved hurdles. A special focus will be given on potential clinical applications of this innovative technique in the field of radiation oncology

[en] To evaluate a fully automatic deep learning system to detect and segment clinically significant prostate cancer (csPCa) on same-vendor prostate MRI from two different institutions not contributing to training of the system. In this retrospective study, a previously bi-institutionally validated deep learning system (UNETM) was applied to bi-parametric prostate MRI data from one external institution (A), a PI-RADS distribution-matched internal cohort (B), and a csPCa stratified subset of single-institution external public challenge data (C). csPCa was defined as ISUP Grade Group ≥ 2 determined from combined targeted and extended systematic MRI/transrectal US-fusion biopsy. Performance of UNETM was evaluated by comparing ROC AUC and specificity at typical PI-RADS sensitivity levels. Lesion-level analysis between UNETM segmentations and radiologist-delineated segmentations was performed using Dice coefficient, free-response operating characteristic (FROC), and weighted alternative (waFROC). The influence of using different diffusion sequences was analyzed in cohort A. In 250/250/140 exams in cohorts A/B/C, differences in ROC AUC were insignificant with 0.80 (95% CI: 0.74-0.85)/0.87 (95% CI: 0.83-0.92)/0.82 (95% CI: 0.75-0.89). At sensitivities of 95% and 90%, UNETM achieved specificity of 30%/50% in A, 44%/71% in B, and 43%/49% in C, respectively. Dice coefficient of UNETM and radiologist-delineated lesions was 0.36 in A and 0.49 in B. The waFROC AUC was 0.67 (95% CI: 0.60-0.83) in A and 0.7 (95% CI: 0.64-0.78) in B. UNETM performed marginally better on readout-segmented than on single-shot echo-planar-imaging. For same-vendor examinations, deep learning provided comparable discrimination of csPCa and non-csPCa lesions and examinations between local and two independent external data sets, demonstrating the applicability of the system to institutions not participating in model training. A previously bi-institutionally validated fully automatic deep learning system maintained acceptable exam-level diagnostic performance in two independent external data sets, indicating the potential of deploying AI models without retraining or fine-tuning, and corroborating evidence that AI models extract a substantial amount of transferable domain knowledge about MRI-based prostate cancer assessment.

[en] Minimal improvements in treatment or survival of patients with osteosarcoma have been achieved during the last three decades. Especially in the case of incomplete tumor resection, prognosis remains poor. Heavy ion radiotherapy (HIT) and modern anticancer drugs like histone deacetylase inhibitors (HDACi) have shown promising effects in osteosarcoma in vitro. In this study, we tested the effect of HIT and the combination of HIT and the HDACi suberoylanilide hydroxamic acid (SAHA) in a xenograft mouse model. Osteosarcoma xenografts were established by subcutaneous injection of KHOS-24OS cells and treated with either vehicle (DMSO), SAHA, HIT or HIT and SAHA. Tumor growth was determined and tumor necrosis, proliferation rate, apoptotic rate as well as vessel density were evaluated. Here, we show that the combination of HIT and SAHA induced a significant delay of tumor growth through increased rate of apoptosis, increased expression of p53 and p21"W"a"f"1"/"C"i"p"1, inhibition of proliferation and angiogenesis compared to tumors treated with HIT only. HIT and in particular the combination of HIT and histone deacetylase inhibition is a promising treatment strategy in OS and may be tested in clinical trials