Proteomic analysis of colorectal cancer metastasis:stathmin-1 revealed as a player in cancer cell migration and prognostic marker

Metastasis accounts largely for the high mortality rate of colorectal cancer (CRC) patients. In this study, we performed comparative proteome analysis of primary CRC cell lines HCT-116 and its metastatic derivative E1 using 2-D DIGE. We identified 74 differentially expressed proteins, many of which function in transcription, translation, angiogenesis signal transduction, or cytoskeletal remodeling pathways, which are indispensable cellular processes involved in the metastatic cascade. Among these proteins, stathmin-1 (STMN1) was found to be highly up-regulated in E1 as compared to HCT-116 and was thus selected for further functional studies. Our results showed that perturbations in STMN1 levels resulted in significant changes in cell migration, invasion, adhesion, and colony formation. We further showed that the differential expression of STMN1 correlated with the cells' metastatic potential in other paradigms of CRC models. Using immunohistochemistry, we also showed that STMN1 was highly expressed in colorectal primary tumors and metastatic tissues as compared to the adjacent normal colorectal tissues. Furthermore, we also showed via tissue microarray analyses of 324 CRC tissues and Kaplan-Meier survival plot that CRC patients with higher expression of STMN1 have poorer prognosis.

Connectivity Mapping for Candidate Therapeutics Identification Using Next Generation Sequencing RNA-Seq Data

The advent of next generation sequencing technologies (NGS) has expanded the area of genomic research, offering high coverage and increased sensitivity over older microarray platforms. Although the current cost of next generation sequencing is still exceeding that of microarray approaches, the rapid advances in NGS will likely make it the platform of choice for future research in differential gene expression. Connectivity mapping is a procedure for examining the connections among diseases, genes and drugs by differential gene expression initially based on microarray technology, with which a large collection of compound-induced reference gene expression profiles have been accumulated. In this work, we aim to test the feasibility of incorporating NGS RNA-Seq data into the current connectivity mapping framework by utilizing the microarray based reference profiles and the construction of a differentially expressed gene signature from a NGS dataset. This would allow for the establishment of connections between the NGS gene signature and those microarray reference profiles, alleviating the associated incurring cost of re-creating drug profiles with NGS technology. We examined the connectivity mapping approach on a publicly available NGS dataset with androgen stimulation of LNCaP cells in order to extract candidate compounds that could inhibit the proliferative phenotype of LNCaP cells and to elucidate their potential in a laboratory setting. In addition, we also analyzed an independent microarray dataset of similar experimental settings. We found a high level of concordance between the top compounds identified using the gene signatures from the two datasets. The nicotine derivative cotinine was returned as the top candidate among the overlapping compounds with potential to suppress this proliferative phenotype. Subsequent lab experiments validated this connectivity mapping hit, showing that cotinine inhibits cell proliferation in an androgen dependent manner. Thus the results in this study suggest a promising prospect of integrating NGS data with connectivity mapping. © 2013 McArt et al.

Are We Ready for SDN? Implementation Challenges for Software-Defined Networks

Cloud services are exploding, and organizations are converging their data centers in order to take advantage of the predictability, continuity, and quality of service delivered by virtualization technologies. In parallel, energy-efficient and high-security networking is of increasing importance. Network operators, and service and product providers require a new network solution to efficiently tackle the increasing demands of this changing network landscape. Software-defined networking has emerged as an efficient network technology capable of supporting the dynamic nature of future network functions and intelligent applications while lowering operating costs through simplified hardware, software, and management. In this article, the question of how to achieve a successful carrier grade network with software-defined networking is raised. Specific focus is placed on the challenges of network performance, scalability, security, and interoperability with the proposal of potential solution directions.

SMART Arm with outcome-triggered electrical stimulation:a pilot randomized clinical trial

The SMART (SensoriMotor Active Rehabilitation Training) Arm is a nonrobotic device designed to allow stroke survivors with severe paresis to practice reaching. It can be used with or without outcome-triggered electrical stimulation (OT-stim) to augment movement. The aim of this study was to evaluate the efficacy of SMART Arm training when used with or without OT-stim, in addition to usual care, as compared with usual care alone during inpatient rehabilitation.

The efficacy of SMART Arm training early after stroke for stroke survivors with severe upper limb disability:a protocol for a randomised controlled trial

Recovery of upper limb function after stroke is poor. The acute to subacute phase after stroke is the optimal time window to promote the recovery of upper limb function. The dose and content of training provided conventionally during this phase is however, unlikely to be adequate to drive functional recovery, especially in the presence of severe motor disability. The current study concerns an approach to address this shortcoming, through evaluation of the SMART Arm, a non-robotic device that enables intensive and repetitive practice of reaching by stroke survivors with severe upper limb disability, with the aim of improving upper limb function. The outcomes of SMART Arm training with or without outcome-triggered electrical stimulation (OT-stim) to augment movement and usual therapy will be compared to usual therapy alone.

AXL Is a Key Regulator of Inherent and Chemotherapy-Induced Invasion and Predicts a Poor Clinical Outcome in Early-Stage Colon Cancer

Purpose: Despite the use of 5-fluorouracil (5-FU)–based adjuvant treatments, a large proportion of patients with high-risk stage II/III colorectal cancer will relapse. Thus, novel therapeutic strategies are needed for early-stage colorectal cancer. Residual micrometastatic disease from the primary tumor is a major cause of patient relapse.

Experimental Design: To model colorectal cancer tumor cell invasion/metastasis, we have generated invasive (KRASMT/KRASWT/+chr3/p53-null) colorectal cancer cell subpopulations. Receptor tyrosine kinase (RTK) screens were used to identify novel proteins that underpin the migratory/invasive phenotype. Migration/invasion was assessed using the XCELLigence system. Tumors from patients with early-stage colorectal cancer (N = 336) were examined for AXL expression.

Results: Invasive colorectal cancer cell subpopulations showed a transition from an epithelial-to-mesenchymal like phenotype with significant increases in migration, invasion, colony-forming ability, and an attenuation of EGF receptor (EGFR)/HER2 autocrine signaling. RTK arrays showed significant increases in AXL levels in all invasive sublines. Importantly, 5-FU treatment resulted in significantly increased migration and invasion, and targeting AXL using pharmacologic inhibition or RNA interference (RNAi) approaches suppressed basal and 5-FU–induced migration and invasion. Significantly, high AXL mRNA and protein expression were found to be associated with poor overall survival in early-stage colorectal cancer tissues.

Conclusions: We have identified AXL as a poor prognostic marker and important mediator of cell migration/invasiveness in colorectal cancer. These findings provide support for the further investigation of AXL as a novel prognostic biomarker and therapeutic target in colorectal cancer, in particular in the adjuvant disease in which EGFR/VEGF–targeted therapies have failed.