Overexpression of neurone glial-related cell adhesion molecule is an independent predictor of poor prognosis in advanced colorectal cancer

A downstream target of the Wnt pathway, neurone glial-related cell adhesion molecule (Nr-CAM) has recently been implicated in human cancer development. However, its role in colorectal cancer (CRC) pathobiology and clinical relevance remains unknown. In this study, we examined the clinical significance of Nr-CAM protein expression in a retrospective series of 428 CRCs using immunohistochemistry and tissue microarrays. Cox proportional hazards regression was used to calculate hazard ratios (HR) of mortality according to various clinicopathological features and molecular markers. All CRC samples were immunoreactive for Nr-CAM protein expression, compared to 10 / 245 (4%) matched normal tissue (P <0.0001). Of 428 CRC samples, 97 (23%) showed Nr-CAM overexpression, which was significantly associated with nodal (P = 0.012) and distant (P = 0.039) metastasis, but not with extent of local invasion or tumor size. Additionally, Nr-CAM overexpression was associated with vascular invasion (P = 0.0029), p53 expression (P = 0.036), and peritoneal metastasis at diagnosis (P = 0.013). In a multivariate model adjusted for other clinicopathological predictors of survival, Nr-CAM overexpression correlated with a significant increase in disease-specific (HR 1.66; 95% confidence interval 1.11-2.47; P = 0.014) and overall mortality (HR 1.57; 95% confidence interval 1.07-2.30; P = 0.023) in advanced but not early stage disease. Notably, 5-fluorouracil-based chemotherapy conferred significant survival benefit to patients with tumors negative for Nr-CAM overexpression but not to those with Nr-CAM overexpressed tumors. In conclusion, Nr-CAM protein expression is upregulated in CRC tissues. Nr-CAM overexpression is an independent marker of poor prognosis among advanced CRC patients, and is a possible predictive marker for non-beneficence to 5-fluorouracil- based chemotherapy.

RUNX3 acts as a tumor suppressor in breast cancer by targeting estrogen receptor α

Transcription factor RUNX3 is inactivated in a number of malignancies, including breast cancer, and is suggested to function as a tumor suppressor. How RUNX3 functions as a tumor suppressor in breast cancer remains undefined. Here, we show that about 20% of female Runx3(+/-) mice spontaneously developed ductal carcinoma at an average age of 14.5 months. Additionally, RUNX3 inhibits the estrogen-dependent proliferation and transformation potential of ERa-positive MCF-7 breast cancer cells in liquid culture and in soft agar and suppresses the tumorigenicity of MCF-7 cells in severe combined immunodeficiency mice. Furthermore, RUNX3 inhibits ERa-dependent transactivation by reducing the stability of ERa. Consistent with its ability to regulate the levels of ERa, expression of RUNX3 inversely correlates with the expression of ERa in breast cancer cell lines, human breast cancer tissues and Runx3(+/-) mouse mammary tumors. By destabilizing ERa, RUNX3 acts as a novel tumor suppressor in breast cancer.

Combined genomic and phenotype screening reveals secretory factor SPINK1 as an invasion and survival factor associated with patient prognosis in breast cancer

Secretory factors that drive cancer progression are attractive immunotherapeutic targets. We used a whole-genome data-mining approach on multiple cohorts of breast tumours annotated for clinical outcomes to discover such factors. We identified Serine protease inhibitor Kazal-type 1 (SPINK1) to be associated with poor survival in estrogen receptor-positive (ER+) cases. Immunohistochemistry showed that SPINK1 was absent in normal breast, present in early and advanced tumours, and its expression correlated with poor survival in ER+ tumours. In ER- cases, the prognostic effect did not reach statistical significance. Forced expression and/or exposure to recombinant SPINK1 induced invasiveness without affecting cell proliferation. However, down-regulation of SPINK1 resulted in cell death. Further, SPINK1 overexpressing cells were resistant to drug-induced apoptosis due to reduced caspase-3 levels and high expression of Bcl2 and phospho-Bcl2 proteins. Intriguingly, these anti-apoptotic effects of SPINK1 were abrogated by mutations of its protease inhibition domain. Thus, SPINK1 affects multiple aggressive properties in breast cancer: survival, invasiveness and chemoresistance. Because SPINK1 effects are abrogated by neutralizing antibodies, we suggest that SPINK1 is a viable potential therapeutic target in breast cancer.

RUNX3 functions as an oncogene in ovarian cancer

The Runt domain transcription factor, RUNX3, has been shown to be a tumor suppressor in a variety of cancers including gastric, colon and breast cancer. Interestingly, an oncogenic role for RUNX3 has also been suggested in basal cell carcinoma and head and neck cancer. Here, we explore the role of RUNX3 in ovarian cancer.

Identification of MET genomic amplification, protein expression and alternative splice isoforms in neuroblastomas

Crizotinib, a dual anaplastic lymphoma kinase (ALK) and mesenchymal-epithelial transition (MET) tyrosine kinase inhibitor, is currently being evaluated for the treatment of neuroblastoma. Its effects are thought to be mediated mainly via its activity against ALK. Although MET genomic/protein expression status might conceivably affect crizotinib efficacy, this issue has hitherto not received attention in neuroblastomas.

Development of a Portable Tissue Micro Array Instrument

Tissue micro array (TMA) is based on the idea of applying miniaturization and a high throughput approach to hybridization-based analyses of tissues. It facilitates biomedical research on a large scale in a single experiment; thus representing one of the most commonly used technologies in translational research. A critical analysis of the existing TMA instruments indicates that there are potential constraints in terms of portability, apart from costs and complexity. This paper will present the development of an affordable, configurable, and portable TMA instrument to allow an efficient collection of tissues, especially in instrument-to-tissue scenarios. The purely mechanical instrument requires no energy sources other than the user, is light weight, portable, and simple to use. [DOI: 10.1115/1.4004922]

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.

Validation of Next Generation Sequencing Technologies in Comparison to Current Diagnostic Gold Standards for BRAF, EGFR and KRAS Mutational Analysis

Next Generation Sequencing (NGS) has the potential of becoming an important tool in clinical diagnosis and therapeutic decision-making in oncology owing to its enhanced sensitivity in DNA mutation detection, fast-turnaround of samples in comparison to current gold standard methods and the potential to sequence a large number of cancer-driving genes at the one time. We aim to test the diagnostic accuracy of current NGS technology in the analysis of mutations that represent current standard-of-care, and its reliability to generate concomitant information on other key genes in human oncogenesis. Thirteen clinical samples (8 lung adenocarcinomas, 3 colon carcinomas and 2 malignant melanomas) already genotyped for EGFR, KRAS and BRAF mutations by current standard-of-care methods (Sanger Sequencing and q-PCR), were analysed for detection of mutations in the same three genes using two NGS platforms and an additional 43 genes with one of these platforms. The results were analysed using closed platform-specific proprietary bioinformatics software as well as open third party applications. Our results indicate that the existing format of the NGS technology performed well in detecting the clinically relevant mutations stated above but may not be reliable for a broader unsupervised analysis of the wider genome in its current design. Our study represents a diagnostically lead validation of the major strengths and weaknesses of this technology before consideration for diagnostic use.

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.

cudaMap: a GPU accelerated program for gene expression connectivity mapping

Background: Modern cancer research often involves large datasets and the use of sophisticated statistical techniques. Together these add a heavy computational load to the analysis, which is often coupled with issues surrounding data accessibility. Connectivity mapping is an advanced bioinformatic and computational technique dedicated to therapeutics discovery and drug re-purposing around differential gene expression analysis. On a normal desktop PC, it is common for the connectivity mapping task with a single gene signature to take >2h to complete using sscMap, a popular Java application that runs on standard CPUs (Central Processing Units). Here, we describe new software, cudaMap, which has been implemented using CUDA C/C++ to harness the computational power of NVIDIA GPUs (Graphics Processing Units) to greatly reduce processing times for connectivity mapping.

Results: cudaMap can identify candidate therapeutics from the same signature in just over thirty seconds when using an NVIDIA Tesla C2050 GPU. Results from the analysis of multiple gene signatures, which would previously have taken several days, can now be obtained in as little as 10 minutes, greatly facilitating candidate therapeutics discovery with high throughput. We are able to demonstrate dramatic speed differentials between GPU assisted performance and CPU executions as the computational load increases for high accuracy evaluation of statistical significance.

Conclusion: Emerging 'omics' technologies are constantly increasing the volume of data and information to be processed in all areas of biomedical research. Embracing the multicore functionality of GPUs represents a major avenue of local accelerated computing. cudaMap will make a strong contribution in the discovery of candidate therapeutics by enabling speedy execution of heavy duty connectivity mapping tasks, which are increasingly required in modern cancer research. cudaMap is open source and can be freely downloaded from http://purl.oclc.org/NET/cudaMap.