A surgical strategy for intrahepatic cholangiocarcinoma - the hilar first concept.

PURPOSE: The present study assesses long-term overall survival (OS) and disease-free survival (DFS) after curative resection for intrahepatic cholangiocarcinoma (ICCA) depending on resection margin (RM) status and lymph node (LN) status. METHODS: Clinical data of all consecutively resected patients with ICCA at a single high-volume center between 2005 and 2018 were collected. Minimum follow-up was 36 months. Perioperative and long-term oncological outcome was assessed. RESULTS: One hundred ninety-two cases were included in the analysis. Thirty- and 90-day-mortality was 5.2% (n = 10) and 10.9% (n = 21). OS was 26 months with 1-, 2-, and 5-year-OS rates of 72%, 53%, and 26%. One-, 2-, and 5-year-DFS rates were 54%, 42%, and 35% (N0 vs. N1: 29 vs. 9 months, p = 0.116). R1 was not found to be an independent risk factor for reduced survival in the overall cohort (p = 0.098). When differentiating according to the LN status, clear resection margins were significantly associated with increased DFS for N0 cases (50 months vs. 9 months, p = 0.004). For N1 cases, no significant difference in DFS was calculated for R0 compared to R1 cases (9 months vs. 9 months, p = 0.88). For N0 cases, clear resection margins > 10 mm were associated with prolonged OS (p = 0.048). CONCLUSION: For N1 cases, there was no significant survival benefit when comparing R0 versus R1, while the complication rate remained high for the extended resection types. In view of merging multimodal treatment, the hilar first concept assesses locoregional LN status for optimal surgical therapy.

A Cellular Ground Truth to Develop MRI Signatures in Glioma Models by Correlative Light Sheet Microscopy and Atlas-Based Coregistration.

Glioblastoma is the most common malignant primary brain tumor with poor overall survival. Magnetic resonance imaging (MRI) is the main imaging modality for glioblastoma but has inherent shortcomings. The molecular and cellular basis of MR signals is incompletely understood. We established a ground truth-based image analysis platform to coregister MRI and light sheet microscopy (LSM) data to each other and to an anatomic reference atlas for quantification of 20 predefined anatomic subregions. Our pipeline also includes a segmentation and quantification approach for single myeloid cells in entire LSM datasets. This method was applied to three preclinical glioma models in male and female mice (GL261, U87MG, and S24), which exhibit different key features of the human glioma. Multiparametric MR data including T2-weighted sequences, diffusion tensor imaging, T2 and T2* relaxometry were acquired. Following tissue clearing, LSM focused on the analysis of tumor cell density, microvasculature, and innate immune cell infiltration. Correlated analysis revealed differences in quantitative MRI metrics between the tumor-bearing and the contralateral hemisphere. LSM identified tumor subregions that differed in their MRI characteristics, indicating tumor heterogeneity. Interestingly, MRI signatures, defined as unique combinations of different MRI parameters, differed greatly between the models. The direct correlation of MRI and LSM allows an in-depth characterization of preclinical glioma and can be used to decipher the structural, cellular, and, likely, molecular basis of tumoral MRI biomarkers. Our approach may be applied in other preclinical brain tumor or neurologic disease models, and the derived MRI signatures could ultimately inform image interpretation in a clinical setting.SIGNIFICANCE STATEMENT We established a histologic ground truth-based approach for MR image analyses and tested this method in three preclinical glioma models exhibiting different features of glioblastoma. Coregistration of light sheet microscopy to MRI allowed for an evaluation of quantitative MRI data in histologically distinct tumor subregions. Coregistration to a mouse brain atlas enabled a regional comparison of MRI parameters with a histologically informed interpretation of the results. Our approach is transferable to other preclinical models of brain tumors and further neurologic disorders. The method can be used to decipher the structural, cellular, and molecular basis of MRI signal characteristics. Ultimately, information derived from such analyses could strengthen the neuroradiological evaluation of glioblastoma as they enhance the interpretation of MRI data.

Brain tumor classification of virtual NMR voxels based on realistic blood vessel-induced spin dephasing using support vector machines.

Remodeling of tissue microvasculature commonly promotes neoplastic growth; however, there is no imaging modality in oncology yet that noninvasively quantifies microvascular changes in clinical routine. Although blood capillaries cannot be resolved in typical magnetic resonance imaging (MRI) measurements, their geometry and distribution influence the integral nuclear magnetic resonance (NMR) signal from each macroscopic MRI voxel. We have numerically simulated the expected transverse relaxation in NMR voxels with different dimensions based on the realistic microvasculature in healthy and tumor-bearing mouse brains (U87 and GL261 glioblastoma). The 3D capillary structure in entire, undissected brains was acquired using light sheet fluorescence microscopy to produce large datasets of the highly resolved cerebrovasculature. Using this data, we trained support vector machines to classify virtual NMR voxels with different dimensions based on the simulated spin dephasing accountable to field inhomogeneities caused by the underlying vasculature. In prediction tests with previously blinded virtual voxels from healthy brain tissue and GL261 tumors, stable classification accuracies above 95% were reached. Our results indicate that high classification accuracies can be stably attained with achievable training set sizes and that larger MRI voxels facilitated increasingly successful classifications, even with small training datasets. We were able to prove that, theoretically, the transverse relaxation process can be harnessed to learn endogenous contrasts for single voxel tissue type classifications on tailored MRI acquisitions. If translatable to experimental MRI, this may augment diagnostic imaging in oncology with automated voxel-by-voxel signal interpretation to detect vascular pathologies.

Large-scale characterization of the microvascular geometry in development and disease by tissue clearing and quantitative ultramicroscopy.

Three-dimensional assessment of optically cleared, entire organs and organisms has recently become possible by tissue clearing and selective plane illumination microscopy ("ultramicroscopy"). Resulting datasets can be highly complex, encompass over a thousand images with millions of objects and data of several gigabytes per acquisition. This constitutes a major challenge for quantitative analysis. We have developed post-processing tools to quantify millions of microvessels and their distribution in three-dimensional datasets from ultramicroscopy and demonstrate the capabilities of our pipeline within entire mouse brains and embryos. Using our developed acquisition, segmentation, and analysis platform, we quantify physiological vascular networks in development and the healthy brain. We compare various geometric vessel parameters (e.g. vessel density, radius, tortuosity) in the embryonic spinal cord and brain as well as in different brain regions (basal ganglia, corpus callosum, cortex). White matter tract structures (corpus callosum, spinal cord) showed lower microvascular branch densities and longer vessel branch length compared to grey matter (cortex, basal ganglia). Furthermore, we assess tumor neoangiogenesis in a mouse glioma model to compare tumor core and tumor border. The developed methodology allows rapid quantification of three-dimensional datasets by semi-automated segmentation of fluorescently labeled objects with conventional computer hardware. Our approach can aid preclinical investigations and paves the way towards "quantitative ultramicroscopy".

Thyroid surgery in children and young adults: potential overtreatment and complications.

PURPOSE: Thyroid nodules in the pediatric population are more frequently associated with malignant thyroid disease than in adult cohorts. Yet, there is a potential risk of surgical overtreatment. With this single center study, an analysis of potential overtreatment for suspected malignant thyroid disease in children and young adults was aimed for. METHODS: In a period from 2005 to 2018, 155 thyroid operations in children and young adults performed at the University Medical Center Mainz, Germany, were analyzed (patient age 3-20 years, 117 female). Cases were categorized for preoperative diagnosis: non-malignant (group I, n = 45) and malignant thyroid disease (group II, n = 110). Postoperative parameters (histology, complication rates) were assessed and compared between groups. RESULTS: 91.1% of group I were histologically benign. 44.5% of group II harbored malignancy. Permanent hypoparathyroidism was documented in group I (2.7%) and in group II (1.4%, p = 1.000). Wound infections were absent in group I but observed in group II (0.9%, p = 1.000). Transient vocal cord palsy was recorded only in group I (2.3%, 2/85 vs. 0/177 nerves at risk, p = 0.104). Permanent vocal cord palsies were absent. CONCLUSION: Preoperative diagnoses were correct in over 90% of group I and in nearly 45% of group II. The high proportion of carcinomas in group II ruled out the issue of potential overtreatment. The risk of severe postoperative complications was equally low in both patient groups.

Cardiac iron concentration in relation to systemic iron status and disease severity in non-ischaemic heart failure with reduced ejection fraction.

AIMS: Low cardiac iron levels promote heart failure in experimental models. While cardiac iron concentration (CI) is decreased in patients with advanced heart failure with reduced ejection fraction (HFrEF), CI has never been measured in non-advanced HFrEF. We measured CI in left ventricular (LV) endomyocardial biopsies (EMB) from patients with non-advanced HFrEF and explored CI association with systemic iron status and disease severity. METHODS AND RESULTS: We enrolled 80 consecutive patients with non-ischaemic HFrEF with New York Heart Association class II or III symptoms and a median (interquartile range) LV ejection fraction of 25 (18-33)%. CI was 304 (262-373) µg/g dry tissue. CI was not related to immunohistological findings or the presence of cardiotropic viral genomes in EMBs and was not related to biomarkers of systemic iron status or anaemia. Patients with CI in the lowest quartile (CIQ1 ) had lower body mass indices and more often presented with heart failure histories longer than 6 months than patients in the upper three quartiles (CIQ2-4 ). CIQ1 patients had higher serum N-terminal pro-B-type natriuretic peptide levels than CIQ2-4 patients [3566 (1513-6412) vs. 1542 (526-2811) ng/L; P = 0.005]. CIQ1 patients also had greater LV end-diastolic (P = 0.001) and end-systolic diameter indices (P = 0.003) and higher LV end-diastolic pressures (P = 0.046) than CIQ2-4 patients. CONCLUSION: Low CI is associated with greater disease severity in patients with non-advanced non-ischaemic HFrEF. CI is unrelated to systemic iron homeostasis. The prognostic and therapeutic implications of CI measurements in EMBs should be further explored.

Gibbs point field model quantifies disorder in microvasculature of U87-glioblastoma.

Microvascular proliferation in glioblastoma multiforme is a biological key mechanism to facilitate tumor growth and infiltration and a main target for treatment interventions. The vascular architecture can be obtained by Single Plane Illumination Microscopy (SPIM) to evaluate vascular heterogeneity in tumorous tissue. We make use of the Gibbs point field model to quantify the order of regularity in capillary distributions found in the U87 glioblastoma model in a murine model and to compare tumorous and healthy brain tissue. A single model parameter Γ was assigned that is linked to tissue-specific vascular topology through Monte-Carlo simulations. Distributions of the model parameter Γ differ significantly between glioblastoma tissue with mean 〈ΓG〉=2.1±0.4, as compared to healthy brain tissue with mean 〈ΓH〉=4.9±0.4, suggesting that the average Γ-value allows for tissue differentiation. These results may be used for diagnostic magnetic resonance imaging, where it has been shown recently that Γ is linked to tissue-inherent relaxation parameters.

PERK-mediated expression of peptidylglycine α-amidating monooxygenase supports angiogenesis in glioblastoma.

PKR-like kinase (PERK) plays a significant role in inducing angiogenesis in various cancer types including glioblastoma. By proteomics analysis of the conditioned medium from a glioblastoma cell line treated with a PERK inhibitor, we showed that peptidylglycine α-amidating monooxygenase (PAM) expression is regulated by PERK under hypoxic conditions. Moreover, PERK activation via CCT020312 (a PERK selective activator) increased the cleavage and thus the generation of PAM cleaved cytosolic domain (PAM sfCD) that acts as a signaling molecule from the cytoplasm to the nuclei. PERK was also found to interact with PAM, suggesting a possible involvement in the generation of PAM sfCD. Knockdown of PERK or PAM reduced the formation of tubes by HUVECs in vitro. Furthermore, in vivo data highlighted the importance of PAM in the growth of glioblastoma with reduction of PAM expression in engrafted tumor significantly increasing the survival in mice. In summary, our data revealed PAM as a potential target for antiangiogenic therapy in glioblastoma.

Glioblastoma multiforme restructures the topological connectivity of cerebrovascular networks.

Glioblastoma multiforme alters healthy tissue vasculature by inducing angiogenesis and vascular remodeling. To fully comprehend the structural and functional properties of the resulting vascular network, it needs to be studied collectively by considering both geometric and topological properties. Utilizing Single Plane Illumination Microscopy (SPIM), the detailed capillary structure in entire healthy and tumor-bearing mouse brains could be resolved in three dimensions. At the scale of the smallest capillaries, the entire vascular systems of bulk U87- and GL261-glioblastoma xenografts, their respective cores, and healthy brain hemispheres were modeled as complex networks and quantified with fundamental topological measures. All individual vessel segments were further quantified geometrically and modular clusters were uncovered and characterized as meta-networks, facilitating an analysis of large-scale connectivity. An inclusive comparison of large tissue sections revealed that geometric properties of individual vessels were altered in glioblastoma in a relatively subtle way, with high intra- and inter-tumor heterogeneity, compared to the impact on the vessel connectivity. A network topology analysis revealed a clear decomposition of large modular structures and hierarchical network organization, while preserving most fundamental topological classifications, in both tumor models with distinct growth patterns. These results augment our understanding of cerebrovascular networks and offer a topological assessment of glioma-induced vascular remodeling. The findings may help understand the emergence of hypoxia and necrosis, and prove valuable for therapeutic interventions such as radiation or antiangiogenic therapy.

RhoA regulates translation of the Nogo-A decoy SPARC in white matter-invading glioblastomas.

Glioblastomas strongly invade the brain by infiltrating into the white matter along myelinated nerve fiber tracts even though the myelin protein Nogo-A prevents cell migration by activating inhibitory RhoA signaling. The mechanisms behind this long-known phenomenon remained elusive so far, precluding a targeted therapeutic intervention. This study demonstrates that the prevalent activation of AKT in gliomas increases the ER protein-folding capacity and enables tumor cells to utilize a side effect of RhoA activation: the perturbation of the IRE1α-mediated decay of SPARC mRNA. Once translation is initiated, glioblastoma cells rapidly secrete SPARC to block Nogo-A from inhibiting migration via RhoA. By advanced ultramicroscopy for studying single-cell invasion in whole, undissected mouse brains, we show that gliomas require SPARC for invading into white matter structures. SPARC depletion reduces tumor dissemination that significantly prolongs survival and improves response to cytostatic therapy. Our finding of a novel RhoA-IRE1 axis provides a druggable target for interfering with SPARC production and underscores its therapeutic value.