High Expression of Glycolytic Genes in Clinical Glioblastoma Patients Correlates With Lower Survival

Glioblastoma (GBM), the most aggressive brain tumor, is associated with a median survival at diagnosis of 16–20 months and limited treatment options. The key hallmark of GBM is altered tumor metabolism and marked increase in the rate of glycolysis. Aerobic glycolysis along with elevated glucose consumption and lactate production supports rapid cell proliferation and GBM growth. In this study, we examined the gene expression profile of metabolic targets in GBM samples from patients with lower grade glioma (LGG) and GBM. We found that gene expression of glycolytic enzymes is up-regulated in GBM samples and significantly associated with an elevated risk for developing GBM. Our findings of clinical outcomes showed that GBM patients with high expression of HK2 and PKM2 in the glycolysis related genes and low expression of genes involved in mitochondrial metabolism-SDHB and COX5A related to tricarboxylic acid (TCA) cycle and oxidative phosphorylation (OXPHOS), respectively, was associated with poor patient overall survival. Surprisingly, expression levels of genes involved in mitochondrial oxidative metabolism are markedly increased in GBM compared to LGG but was lower compared to normal brain. The fact that in GBM the expression levels of TCA cycle and OXPHOS-related genes are higher than those in LGG patients suggests the metabolic shift in GBM cells when progressing from LGG to GBM. These results are an important step forward in our understanding of the role of metabolic reprogramming in glioma as drivers of the tumor and could be potential prognostic targets in GBM therapies

Depletion of mitochondrial protease OMA1 alters proliferative properties and promotes metastatic growth of breast cancer cells

Metastatic competence of cancer cells is influenced by many factors including metabolic alterations and changes in mitochondrial biogenesis and protein homeostasis. While it is generally accepted that mitochondria play important roles in tumorigenesis, the respective molecular events that regulate aberrant cancer cell proliferation remain to be clarified. Therefore, understanding the mechanisms underlying the role of mitochondria in cancer progression has potential implications in the development of new therapeutic strategies. We show that low expression of mitochondrial quality control protease OMA1 correlates with poor overall survival in breast cancer patients. Silencing OMA1 in vitro in patientderived metastatic breast cancer cells isolated from the metastatic pleural effusion and atypical ductal hyperplasia mammary tumor specimens (21MT-1 and 21PT) enhances the formation of filopodia, increases cell proliferation (Ki67 expression), and induces epithelial-mesenchymal transition (EMT). Mechanistically, loss of OMA1 results in alterations in the mitochondrial protein homeostasis, as reflected by enhanced expression of canonic mitochondrial unfolded protein response genes. These changes significantly increase migratory properties in metastatic breast cancer cells, indicating that OMA1 plays a critical role in suppressing metastatic competence of breast tumors. Interestingly, these results were not observed in OMA1-depleted non-tumorigenic MCF10A mammary epithelial cells. This newly identified reduced activity/levels of OMA1 provides insights into the mechanisms leading to breast cancer development, promoting malignant progression of cancer cells and unfavorable clinical outcomes, which may represent possible prognostic markers and therapeutic targets for breast cancer treatment

Mechanical Behavior of a Magnesium Alloy Nanocomposite under Conditions of Static Tension and Dynamic Fatigue

In this paper, the intrinsic influence of nano-alumina particulate (Al2O3p) reinforcements on microstructure, microhardness, tensile properties, tensile fracture, cyclic stress-controlled fatigue, and final fracture behavior of a magnesium alloy is presented and discussed. The unreinforced magnesium alloy (AZ31) and the reinforced composite counterpart (AZ31/1.5 vol.% Al2O3) were manufactured by solidification processing followed by hot extrusion. The elastic modulus, yield strength, and tensile strength of the nanoparticle-reinforced magnesium alloy were noticeably higher than the unreinforced counterpart. The ductility, quantified by elongation-to-failure, of the composite was observably lower than the unreinforced monolithic counterpart (AZ31). The nanoparticle-reinforced composite revealed improved cyclic fatigue resistance over the entire range of maximum stress at both the tested load ratios. Under conditions of fully reversed loading (R = −1) both materials showed observable degradation in behavior quantified in terms of cyclic fatigue life. The conjoint influence of reinforcement, processing, intrinsic microstructural features and loading condition on final fracture behavior is presented and discussed

Gentile statistics and restricted partitions

In a recent paper (Tran et al, Ann. Phys.311, 204 (2004)), some asymptotic number theoretical results on the partitioning of an integer were derived exploiting its connection to the quantum density of states of a many-particle system. We generalise these results to obtain an asymptotic formula for the restricted or coloured partitions pks (n), which is the number of partitions of an integer n into the summand of sth powers of integers such that each power of a given integer may occur utmost k times. While the method is not rigorous, it reproduces the well-known asymptotic results for s = 1 apart from yielding more general results for arbitrary values of s

Depletion of mitochondrial protease OMA1 alters proliferative properties and promotes metastatic growth of breast cancer cells

Metastatic competence of cancer cells is influenced by many factors including metabolic alterations and changes in mitochondrial biogenesis and protein homeostasis. While it is generally accepted that mitochondria play important roles in tumorigenesis, the respective molecular events that regulate aberrant cancer cell proliferation remain to be clarified. Therefore, understanding the mechanisms underlying the role of mitochondria in cancer progression has potential implications in the development of new therapeutic strategies. We show that low expression of mitochondrial quality control protease OMA1 correlates with poor overall survival in breast cancer patients. Silencing OMA1 in vitro in patientderived metastatic breast cancer cells isolated from the metastatic pleural effusion and atypical ductal hyperplasia mammary tumor specimens (21MT-1 and 21PT) enhances the formation of filopodia, increases cell proliferation (Ki67 expression), and induces epithelial-mesenchymal transition (EMT). Mechanistically, loss of OMA1 results in alterations in the mitochondrial protein homeostasis, as reflected by enhanced expression of canonic mitochondrial unfolded protein response genes. These changes significantly increase migratory properties in metastatic breast cancer cells, indicating that OMA1 plays a critical role in suppressing metastatic competence of breast tumors. Interestingly, these results were not observed in OMA1-depleted non-tumorigenic MCF10A mammary epithelial cells. This newly identified reduced activity/levels of OMA1 provides insights into the mechanisms leading to breast cancer development, promoting malignant progression of cancer cells and unfavorable clinical outcomes, which may represent possible prognostic markers and therapeutic targets for breast cancer treatment

Using deep learning to detect digitally encoded DNA trigger for Trojan malware in Bio‑Cyber attacks

This article uses Deep Learning technologies to safeguard DNA sequencing against Bio-Cyber attacks. We consider a hybrid attack scenario where the payload is encoded into a DNA sequence to activate a Trojan malware implanted in a software tool used in the sequencing pipeline in order to allow the perpetrators to gain control over the resources used in that pipeline during sequence analysis. The scenario considered in the paper is based on perpetrators submitting synthetically engineered DNA samples that contain digitally encoded IP address and port number of the perpetrator’s machine in the DNA. Genetic analysis of the sample’s DNA will decode the address that is used by the software Trojan malware to activate and trigger a remote connection. This approach can open up to multiple perpetrators to create connections to hijack the DNA sequencing pipeline. As a way of hiding the data, the perpetrators can avoid detection by encoding the address to maximise similarity with genuine DNAs, which we showed previously. However, in this paper we show how Deep Learning can be used to successfully detect and identify the trigger encoded data, in order to protect a DNA sequencing pipeline from Trojan attacks. The result shows nearly up to 100% accuracy in detection in such a novel Trojan attack scenario even after applying fragmentation encryption and steganography on the encoded trigger data. In addition, feasibility of designing and synthesizing encoded DNA for such Trojan payloads is validated by a wet lab experiment

An inhibitory role for FAK in regulating proliferation: a link between limited adhesion and RhoA-ROCK signaling

Focal adhesion kinase (FAK) transduces cell adhesion to the extracellular matrix into proliferative signals. We show that FAK overexpression induced proliferation in endothelial cells, which are normally growth arrested by limited adhesion. Interestingly, displacement of FAK from adhesions by using a FAK−/− cell line or by expressing the C-terminal fragment FRNK also caused an escape of adhesion-regulated growth arrest, suggesting dual positive and negative roles for FAK in growth regulation. Expressing kinase-dead FAK-Y397F in FAK−/− cells prevented uncontrolled growth, demonstrating the antiproliferative function of inactive FAK. Unlike FAK overexpression–induced growth, loss of growth control in FAK−/− or FRNK-expressing cells increased RhoA activity, cytoskeletal tension, and focal adhesion formation. ROCK inhibition rescued adhesion-dependent growth control in these cells, and expression of constitutively active RhoA or ROCK dysregulated growth. These findings demonstrate the ability of FAK to suppress and promote growth, and underscore the importance of multiple mechanisms, even from one molecule, to control cell proliferation

PIQA: pipeline for Illumina G1 genome analyzer data quality assessment

Summary: PIQA is a quality analysis pipeline designed to examine genomic reads produced by Next Generation Sequencing technology (Illumina G1 Genome Analyzer). A short statistical summary, as well as tile-by-tile and cycle-by-cycle graphical representation of clusters density, quality scores and nucleotide frequencies allow easy identification of various technical problems including defective tiles, mistakes in sample/library preparations and abnormalities in the frequencies of appearance of sequenced genomic reads. PIQA is written in the R statistical programming language and is compatible with bustard, fastq and scarf Illumina G1 Genome Analyzer data formats