Rho family small GTPases regulate multiple cellular functions through reorganization of the actin cytoskeleton. Among them, Cdc42 and Tc10 induce filopodia or peripheral processes in cultured cells. We have identified a member of the family, designated as RhoT, which is closely related to Tc10. Tc10 was highly expressed in muscular tissues and brain and remarkably induced during differentiation of C2 skeletal muscle cells and neuronal differentiation of PC12 and N1E-115 cells. On the other hand, RhoT was predominantly expressed in heart and uterus and induced during neuronal differentiation of N1E-115 cells. Tc10 exogenously expressed in fibroblasts generated actin-filament-containing peripheral processes longer than the Cdc42-formed filopodia, whereas RhoT produced much longer and thicker processes containing actin filaments. Furthermore, both Tc10 and RhoT induced neurite outgrowth in PC12 and N1E-115 cells, but Cdc42 did not do this by itself. Tc10 and RhoT as well as Cdc42 bound to the N-terminal CRIB-motif-containing portion of N-WASP and activated N-WASP to induce Arp2/3-complex-mediated actin polymerization. The formation of peripheral processes and neurites by Tc10 and RhoT was prevented by the coexpression of dominant-negative mutants of N-WASP. Thus, N-WASP is essential for the process formation and neurite outgrowth induced by Tc10 and RhoT. Neuronal differentiation of PC12 and N1E-115 cells induced by dibutyryl cyclic AMP and by serum starvation, respectively, was prevented by dominant-negative Cdc42,Tc10 and RhoT. Taken together, all these Rho family proteins are required for neuronal differentiation, but they exert their functions differentially in process formation and neurite extension. Consequently, N-WASP activated by these small GTPases mediates neuronal differentiation in addition to its recently identified role in glucose uptake.

The mechanochemical behavior of Pt(5dpb)Cl (5dpbH = 1,3-di(5-methyl-2-pyridyl)benzene) was investigated in terms of solid-state luminescence. The yellow luminescence of the crystalline complex changed to orange when grinding into fine powder on a glass substrate with a spatula. A broad emission band, which was not detected for the crystal, was observed at around 670 nm for the powder. The powder X-ray diffraction (XRD) pattern was the same as that calculated from X-ray crystallographic data of the single crystal. A broad band appeared within 100 ns after laser excitation accompanied by quenching of the s(pi,pi*) emission of Pt(5dpb)Cl, which was then weakened with decreasing temperature and disappeared below 120 K. The phenomenon was very similar to the excimer formation observed in solution. A related complex, Pt(dpb)Cl (dpbH = 1,3-di(2-pyridyl)benzene), also exhibited luminescent mechanochromism. However, the broad emission that appeared upon grinding still remained at 77 K, and XRD showed that the ground sample of Pt(dpb)Cl was amorphous.

Purpose: Cancer-associated fibroblasts have emerged to be highly heterogenous and can play multifaceted roles in dictating pancreatic ductal adenocarcinoma (PDAC) progression, immunosuppression, and therapeutic response, highlighting the need for a deeper understanding of stromal heterogeneity between patients and even within a single tumor. We hypothesized that image analysis of fibroblast subpopulations and collagen in PDAC tissues might guide stroma-based patient stratification to predict clinical outcomes and tumor characteristics. Experimental Design: A novel multiplex IHC-based image analysis system was established to digitally differentiate fibroblast subpopulations. Using whole-tissue slides from 215 treatment-naïve PDACs, we performed concurrent quantification of principal fibroblast subpopulations and collagen and defined three stroma types: collagen-rich stroma, fibroblast activation protein α (FAP)-dominant fibroblast-rich stroma, and α smooth muscle actin (ACTA2)-dominant fibroblast-rich stroma. These stroma types were assessed for the associations with cancer-specific survival by multivariable Cox regression analyses and with clinicopathologic factors, including CD8+ cell density. Results: FAP-dominant fibroblasts and ACTA2-dominant fibroblasts represented the principal distinct fibroblast subpopulations in tumor stroma. Stroma types were associated with patient survival, SMAD4 status, and transcriptome signatures. Compared with FAP-dominant fibroblast-rich stroma, collagen-rich stroma correlated with prolonged survival [HR, 0.57; 95% confidence interval (CI), 0.33–0.99], while ACTA2-dominant fibroblast-rich stroma exhibited poorer prognosis (HR, 1.65; 95% CI, 1.06–2.58). FAP-dominant fibroblast-rich stroma was additionally characterized by restricted CD8+ cell infiltrates and intense neutrophil infiltration. Conclusions: This study identified three distinct stroma types differentially associated with survival, immunity, and molecular features, thereby underscoring the importance of stromal heterogeneity in subtyping pancreatic cancers and supporting the development of antistromal therapies.

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Midkine is a heparin-binding growth factor highly expressed in various cancers, including neuroblastoma, the most common extracranial pediatric solid tumor. Prognosis of patients with neuroblastoma in which MYCN is amplified remains particularly poor. In this study, we used a MYCN transgenic model for neuroblastoma in which midkine is highly expressed in precancerous lesions of sympathetic ganglia. Genetic ablation of midkine in this model delayed tumor formation and reduced tumor incidence. Furthermore, an RNA aptamer that specifically bound midkine suppressed the growth of neuroblastoma cells in vitro and in vivo in tumor xenografts. In precancerous lesions, midkine-deficient MYCN transgenic mice exhibited defects in activation of Notch2, a candidate midkine receptor, and expression of the Notch target gene HES1. Similarly, RNA aptamer-treated tumor xenografts also showed attenuation of Notch2-HES1 signaling. Our findings establish a critical role for the midkine-Notch2 signaling axis in neuroblastoma tumorigenesis, which implicates new strategies to treat neuroblastoma. Cancer Res; 73(4); 1318-27. Ó2012 AACR.

Accurate staging of liver fibrosis is crucial to guide therapeutic decisions for patients with nonalcoholic fatty liver disease (NAFLD). Digital image analysis has emerged as a promising tool for quantitative assessment of fibrosis in chronic liver diseases. We sought to determine the relationship of histologic fibrosis stage with fiber amounts quantified in liver biopsy specimens for the better understanding of NAFLD progression. We measured area ratios of collagen and elastin fibers in Elastica van Gieson‐stained biopsy tissues from 289 patients with NAFLD from four hospitals using an automated computational method and examined their correlations with Brunt's fibrosis stage. As a secondary analysis, we performed multivariable logistic regression analysis to assess the associations of the combined area ratios of collagen and elastin with noninvasive fibrosis markers. The combined fiber area ratios correlated strongly with Brunt's stage (Spearman correlation coefficient, 0.78; P < 0.0001), but this relationship was nonlinear (P = 0.007) with striking differences between stage 4 (median area ratios, 12.3%) and stages 0‐3 (2.1%, 2.8%, 4.3%, and 4.8%, respectively). Elastin accumulation was common in areas of thick bridging fibrosis and thickened venous walls but not in areas of perisinusoidal fibrosis. The highest tertile of the combined fiber area ratios was associated with the fibrosis‐4 index and serum type IV collagen 7s domain (7s collagen) levels, whereas the upper two tertiles of the fiber amounts significantly associated with body mass index, aspartate aminotransferase, and 7s collagen in the multivariable analysis. Conclusion: Quantitative fibrosis assessment reveals a nonlinear relationship between fibrosis stage and fiber amount, with a marked difference between stage 4 and stage 3 and much smaller differences among stages 0‐3, suggesting a heterogeneity in disease severity within NAFLD‐related cirrhosis. (Hepatology Communications 2018;2:58–68)

Histological evaluation of fibrosis after a liver biopsy is crucial for evaluating the pathology of patients with chronic liver disease. Previous studies have reported quantitative analyses of fibrosis using images of collagen-stained sections. However, analysis of these studies requires manual selection of the region of interest. In addition, the quantification of elastic fibers is not considered. The present study was conducted in order to measure both the collagen and elastic fiber area ratios using Elastica van Gieson-stained whole-slide images (WSIs) of liver biopsy specimens. High-resolution WSIs provide precise color classification, enabling accurate detection of even fine collagen and elastic fibers. To minimize the influence of pre-existing fibrous tissue, median area ratios of the collagen and elastic fibers were independently calculated from the image tiles of the WSIs. These median area ratios were highly concordant with area ratios after the pre-existing fibrous tissues were manually trimmed from the WSI. Further, these median area ratios were correlated with liver stiffness as measured by transient elastography (collagen: r = 0.73 [P < 0.01], elastic: r = 0.53 [P < 0.01]). Our approach to quantifying liver fibrosis will serve as an effective tool to evaluate liver diseases in routine practice.

Background & AimsThe fibrosis stage, which is evaluated by the distribution pattern of collagen fibers, is a major predictor for the development of hepatocellular carcinoma (HCC) for patients with hepatitis C. Meanwhile, the role of elastin fibers has not yet been elucidated. The present study was conducted to determine the significance of quantifying both collagen and elastin fibers.MethodsWe enrolled 189 consecutive patients with hepatitis C and advanced fibrosis. Using Elastica van Gieson-stained whole-slide images of pretreatment liver biopsies, collagen and elastin fibers were evaluated pixel by pixel (0.46 μm/pixel) using an automated computational method. Consequently, fiber amount and cumulative incidences of HCC within 3 years were analyzed.ResultsThere was a significant correlation between collagen and elastin fibers, whereas variation in elastin fiber was greater than in collagen fiber. Both collagen fiber (p = 0.008) and elastin fiber (p < 0.001) were significantly correlated with F stage. In total, 30 patients developed HCC during follow-up. Patients who have higher elastin fiber (p = 0.002) in addition to higher collagen fiber (p = 0.05) showed significantly higher incidences of HCC. With regard to elastin fiber, this difference remained significant in F3 patients. Furthermore, for patients with a higher collagen fiber amount, higher elastin was a significant predictor for HCC development (p = 0.02).ConclusionsComputational analysis is a novel technique for quantification of fibers with the added value of conventional staging. Elastin fiber is a predictor for the development of HCC independently of collagen fiber and F stage.