Tumor suppressor function of the SEMA3B gene in human lung and renal cancers

The SEMA3B gene is located in the 3p21.3 LUCA region, which is frequently affected in different types of cancer. The objective of our study was to expand our knowledge of the SEMA3B gene as a tumor suppressor and the mechanisms of its inactivation. In this study, several experimental approaches were used: tumor growth analyses and apoptosis assays in vitro and in SCID mice, expression and methylation assays and other. With the use of the small cell lung cancer cell line U2020 we confirmed the function of SEMA3B as a tumor suppressor, and showed that the suppression can be realized through the induction of apoptosis and, possibly, associated with the inhibition of angiogenesis. In addition, for the first time, high methylation frequencies have been observed in both intronic (32-39%) and promoter (44-52%) CpG-islands in 38 non-small cell lung carcinomas, including 16 squamous cell carcinomas (SCC) and 22 adenocarcinomas (ADC), and in 83 clear cell renal cell carcinomas (ccRCC). Correlations between the methylation frequencies of the promoter and the intronic CpG-islands of SEMA3B with tumor stage and grade have been revealed for SCC, ADC and ccRCC. The association between the decrease of the SEMA3B mRNA level and hypermethylation of the promoter and the intronic CpG-islands has been estimated in renal primary tumors (P < 0.01). Using qPCR, we observed on the average 10- and 14-fold decrease of the SEMA3B mRNA level in SCC and ADC, respectively, and a 4-fold decrease in ccRCC. The frequency of this effect was high in both lung (92-95%) and renal (84%) tumor samples. Moreover, we showed a clear difference (P < 0.05) of the SEMA3B relative mRNA levels in ADC with and without lymph node metastases. We conclude that aberrant expression and methylation of SEMA3B could be suggested as markers of lung and renal cancer progression

Patterns in the Distribution Capacity of Thin Plates Under Different Condition for Their Resting on Supports

This paper reports a study into the distribution capacity of a flexible plate in different cross-sections exposed to the external vertical concentrated forces applied in any place of its area. A plate with one pinched side and a series of racks arranged at any distance from the pinching has been considered. In terms of the theory of elasticity and mathematics, solving this problem poses significant difficulties. This has study found that a lateral distribution coefficient could be used to simplify calculations aimed at determining the stressed-strained state of the system. In determining the stressed-strained state of the plate, the calculation method described in work [1] was applied. The plate is cut into a series of longitudinal strips that represent, from the standpoint of construction mechanics, a console strip with one pinched end and resting on a stationary support located at any distance from the pinching. It has been revealed that the distribution capacity of the examined plate in the same cross-section depends insignificantly on the point of application of the concentrated load along the length of the longitudinal strip (between 2.6 and 6.7 %). The distribution capacity in different cross-sections does differ greatly (in the range of 10 to 30 %). The result of this study is the proposed unified and easy-to-implement method of calculating plates under any conditions for their resting on supports and when exposed to any external loads. There is also no difficulty in calculating the plates backed by edges in both directions. Other estimation methods in these cases require a different mathematical approach, and, for the case of a series of external loads, or under difficult plate rest conditions, the issue relating to the stressed-strained state of the system remains ope

Adaptive Digital Hologram Binarization Method Based on Local Thresholding, Block Division and Error Diffusion

High-speed optical reconstruction of 3D-scenes can be achieved using digital holography with binary digital micromirror devices (DMD) or a ferroelectric spatial light modulator (fSLM). There are many algorithms for binarizing digital holograms. The most common are methods based on global and local thresholding and error diffusion techniques. In addition, hologram binarization is used in optical encryption, data compression, beam shaping, 3D-displays, nanofabrication, materials characterization, etc. This paper proposes an adaptive binarization method based on a combination of local threshold processing, hologram division into blocks, and error diffusion procedure (the LDE method). The method is applied for binarization of optically recorded and computer-generated digital holograms of flat objects and three-dimensional scenes. The quality of reconstructed images was compared with different methods of error diffusion and thresholding. Image reconstruction quality was up to 22% higher by various metrics than that one for standard binarization methods. The optical hologram reconstruction using DMD confirms the results of the numerical simulations

Relative mRNA level of the <i>SEMA3B</i> gene in NSCLC (A) and ccRCC (B).

<p>QPCR data, additional samplings. Light grey columns—samples without metastases, dark grey columns—samples with lymph node or distant metastases. The numbers of primary tumors correspond to those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123369#pone.0123369.s001" target="_blank">S1 Table</a>. Mean values ± standard deviations for 3 replicates are represented.</p

<i>SEMA3B</i> gene expression level (A), copy number (C) and methylation status of its two CpG-islands (B) in the same ccRCC samples.

<p>Semi-quantitative PCR (A, C) and MSP (B) data. Numbers of primary tumors correspond to those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123369#pone.0123369.s001" target="_blank">S1 Table</a> and <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123369#pone.0123369.g005" target="_blank">Fig 5B</a>. (A) Light grey columns—samples without metastases, dark grey columns—samples with lymph node or distant metastases. (B) 1-st CpG—promoter CpG-island, 2-nd CpG—intronic CpG-island. Grey squares show methylated CpG-islands, white squares—unmethylated. (C) Grey squares show hemi- or homozygous deletions of the 5’Sema5 marker, black—amplification, white squares—retention. Assessed mean values ± error bars are represented in the “A” part.</p

Inhibition of tumor growth by <i>SEMA3B</i> re-expression.

<p>The growth rate of U2020 cells (U7111 clone) in SCID mice: blue line—U2020 cells without <i>SEMA3B</i> expression (+ doxycycline, 4 mice), red and yellow line—U2020 cells with <i>SEMA3B</i> expression (- doxycycline, 4 mice and 1 mouse respectively). *—no expression of <i>SEMA3B</i> gene according to the Northern blot (data not shown). One +dox and one—dox mice were withdrawn from the study after one month.</p

Methylation profile of the promoter CpG-island of the <i>SEMA3B</i> gene in lung (A) and renal (B) cancer cell lines and primary tumors.

<p>Bisulfite sequencing data, 16 CpG-dinucleotides (2–17) of the CpG-island are given. Grey squares show methylated CpG-dinucleotides, white squares—unmethylated. Numbers of primary tumors correspond to those in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0123369#pone.0123369.s001" target="_blank">S1 Table</a>. The bold numbers of CpG-dinucleotides (3–4 and 9–12) indicate the location of the primers that were used for MSP method.</p

Absence of <i>SEMA3B</i> expression in tumors grown <i>in vivo</i>.

<p>Electropherogram of multiplex PCR from plasmids, clones and SCID mice tumors of three genes. M—marker, 1—PCR from plasmid pETE/<i>SEMA3B</i>, 2—PCR from plasmid pETE/<i>TUSC2</i>, 3—PCR from plasmid pETE/<i>ZMYND10</i>, 4—PCR from U7111/<i>SEMA3B</i> cell clone 1, 5—PCR from U7111/<i>TUSC2</i> cell clone 3, 6—PCR from U7111/<i>ZMYND10</i> cell clone 4, 7—mixed cell clones, 8—PCR from tumor 1, 9—PCR from tumor 2, 10—PCR from tumor 3, 11—negative control.</p

Pathological and histological characteristics of the tumors.

<p>Note: The slash separates the number of samples used in the methylation studies and the expression or copy number studies by semi-quantitative RT-PCR and the number of samples used in the qPCR expression studies.</p><p>Pathological and histological characteristics of the tumors.</p