Heparanase expression and localization in different types of human lung cancer

Background

Heparanase is the only known mammalian glycosidase capable of cleaving heparan sulfate chains. The expression of this enzyme has been associated with tumor development because of its ability to degrade extracellular matrix and promote cell invasion.

Methods

We analyzed heparanase expression in lung cancer samples to understand lung tumor progression and malignancy. Of the samples from 37 patients, there were 14 adenocarcinomas, 13 squamous cell carcinomas, 5 large cell carcinomas, and 5 small cell carcinomas. Immunohistochemistry was performed to ascertain the expression and localization of heparanase.

Results

All of the tumor types expressed heparanase, which was predominantly localized within the cytoplasm and nucleus. Significant enzyme expression was also observed in cells within the tumor microenvironment, such as fibroblasts, epithelial cells, and inflammatory cells. Adenocarcinomas exhibited the strongest heparanase staining intensity and the most widespread heparanase distribution. Squamous cell carcinomas, large cell carcinomas, and small cell carcinomas had a similar subcellular distribution of heparanase to adenocarcinomas but the distribution was less widespread. Heparanase expression tended to correlate with tumor node metastasis (TNM) staging in non-small cell lung carcinoma.

Conclusion

In this study, we showed that heparanase was localized to the cytoplasm and nucleus of tumor cells and to cells within the microenvironment in different types of lung cancer. This enzyme exhibited a differential distribution based on the type of lung tumor.General significanceElucidating the heparanase expression patterns in different types of lung cancer increased our understanding of the crucial role of heparanase in lung cancer biology. This article is part of a Special Issue entitled Matrix-mediated cell behaviour and properties.     

In vitro induction of apoptosis by isosclerone from marine-derived fungus Aspergillus fumigatus

In the present study, we investigated the apoptotic effects of isosclerone from marine-derived fungi on human breast cancer MCF-7 cells. Treatment with isosclerone exhibited a characteristic feature of apoptosis including significant cytotoxicity and DNA fragmentation in cancer cells. In addition, The apoptosis induction abilities of the isosclerone was studied by analyzing the expression of caspase-3, -8 and -9, Bcl-2 family, NF-κ-B P50, P65, and IKK proteins. Western blot and RT-PCR analysis have indicated that isosclerone induce cancer cells apoptosis through down-regulated Bcl-2 family and up-regulated caspases, and activating the NF-κ-B signaling pathway. Our data demonstrate that isosclerone specifically binds to crystal structure of apoptosis regulator BCL-2 and pseudo-activated procaspase-3 proteins through down-regulated Bcl-2 family and up-regulated caspases, and activating the NF-κ-B signaling pathway. Our proof-of-principle study should have a positive impact on future drug discovery.     

Molecular structure and dynamics of the dimeric human small heat shock protein HSPB6

ATP-independent small heat-shock proteins (sHSPs) are an essential component of the cellular chaperoning machinery. Under both normal and stress conditions, sHSPs bind partially unfolded proteins and prevent their irreversible aggregation. Canonical vertebrate sHSPs, such as the α-crystallins, form large polydisperse oligomers from which smaller, functionally active subspecies dissociate. Here we focus on human HSPB6 which, despite having considerable homology to the α-crystallins in both the N-terminal region and the signature α-crystallin domain (ACD), only forms dimers in solution that represent the basic chaperoning subspecies. We addressed the three-dimensional structure and functional properties of HSPB6 in a hybrid study employing X-ray crystallography, solution small-angle X-ray scattering (SAXS), mutagenesis, size-exclusion chromatography and chaperoning assays. The crystal structure of a proteolytically stable fragment reveals typical ACD dimers which further form tetrameric assemblies as a result of extensive inter-dimer patching of the β4/β8 grooves. The patching is surprisingly mediated by tripeptide motifs, found in the N-terminal domain directly adjacent to the ACD, that are resembling but distinct from the canonical IxI sequence commonly binding this groove. By combining the crystal structure with SAXS data for the full-length protein, we derive a molecular model of the latter. In solution, HSPB6 shows a strong attractive self-interaction, a property that correlates with its chaperoning activity. Both properties are dictated by the unstructured yet compact N-terminal domain, specifically a region highly conserved across vertebrate sHSPs.     

Solution conformation of adenovirus virus associated RNA-I and its interaction with PKR

Adenovirus virus-associated RNA (VA_I) provides protection against the host antiviral response in part by inhibiting the interferon-induced double stranded RNA-activated protein kinase (PKR). VA_I consists of three base-paired regions; the apical stem responsible for the interaction with double-stranded RNA binding motifs (dsRBMs) of PKR, the central stem required for inhibition, and the terminal stem. The solution conformation of VA_I and VA_I lacking the terminal stem were determined using SAXS that suggested extended conformations that are in agreement with their secondary structures. Solution conformations of VA_I lacking the terminal stem in complex with the dsRBMs of PKR indicated that the apical stem interacts with both dsRNA-binding motifs whereas the central stem does not. Hydrodynamic properties calculated from ab initio models were compared to experimentally determined parameters for model validation. Furthermore, SAXS envelopes were used as a constraint for the in silico modeling of tertiary structure for RNA and RNA–protein complex. Finally, full-length PKR was also studied, but concentration-dependent changes in hydrodynamic parameters prevented ab initio shape determination. Taken together, results provide an improved structural framework that further our understanding of the role VA_I plays in evading host innate immune responses.     

Endogenous Small RNA Clusters in Plants

In plants, small RNAs（sRNAs） usually refer to non-coding RNAs（ncRNAs） with lengths of 20–24 nucleotides. sRNAs are involved in the regulation of many essential processes related to plant development and environmental responses. sRNAs in plants are mainly grouped into microRNAs（miRNAs） and small interfering RNAs（siRNAs）, and the latter can be further classified into trans-acting siRNAs（ta-siRNAs）, repeat-associated siRNAs（ra-siRNAs）, natural anti-sense siRNAs（nat-siRNAs）, etc. Many sRNAs exhibit a clustered distribution pattern in the genome. Here, we summarize the features and functions of cluster-distributed sRNAs, aimed to not only provide a thorough picture of sRNA clusters（SRCs） in plants, but also shed light on the identification of new classes of functional sRNAs.     

Viral RNA recognition by the Drosophila small interfering RNA pathway

Viral RNA is a common activator of antiviral responses. In this review, we dissect the mechanism of viral RNA recognition by the small interfering RNA pathway in Drosophila melanogaster. This antiviral response in fruit flies can help understand general principles of nucleic acid recognition.     

Estimating the abundance of rare and elusive carnivores from photographic-sampling data when the population size is very small

Conservation and management agencies require accurate and precise estimates of abundance when considering the status of a species and the need for directed actions. Due to the proliferation of remote sampling cameras, there has been an increase in capture–recapture studies that estimate the abundance of rare and/or elusive species using closed capture–recapture estimators (C–R). However, data from these studies often do not meet necessary statistical assumptions. Common attributes of these data are (1) infrequent detections, (2) a small number of individuals detected, (3) long survey durations, and (4) variability in detection among individuals. We believe there is a need for guidance when analyzing this type of sparse data. We highlight statistical limitations of closed C–R estimators when data are sparse and suggest an alternative approach over the conventional use of the Jackknife estimator. Our approach aims to maximize the probability individuals are detected at least once over the entire sampling period, thus making the modeling of variability in the detection process irrelevant, estimating abundance accurately and precisely. We use simulations to demonstrate when using the unconditional-likelihood M ₀ (constant detection probability) closed C–R estimator with profile-likelihood confidence intervals provides reliable results even when detection varies by individual. If each individual in the population is detected on average of at least 2.5 times, abundance estimates are accurate and precise. When studies sample the same species at multiple areas or at the same area over time, we suggest sharing detection information across datasets to increase precision when estimating abundance. The approach suggested here should be useful for monitoring small populations of species that are difficult to detect.