Gene Expression Meta-Analysis Identifies VDAC1 as a Predictor of Poor Outcome in Early Stage Non-Small Cell Lung Cancer

Background: The bioenergetic status of non-small cell lung cancer correlates with tumour aggressiveness. The voltage dependent anion channel type 1 (VDAC1) is a component of the mitochondrial permeability transition pore, regulates mitochondrial ATP/ADP exchange suggesting that its over-expression could be associated with energy dependent processes including increased proliferation and invasiveness. To test this hypothesis, we conducted an in vivo gene-expression meta-analysis of surgically resected non-small cell lung cancer (NSCLC) using 602 individual expression profiles, to examine the impact of VDAC1 on survival.

Identification of candidate small-molecule therapeutics to cancer by gene-signature perturbation in connectivity mapping.

Connectivity mapping is a recently developed technique for discovering the underlying connections between different biological states based on gene-expression similarities. The sscMap method has been shown to provide enhanced sensitivity in mapping meaningful connections leading to testable biological hypotheses and in identifying drug candidates with particular pharmacological and/or toxicological properties. Challenges remain, however, as to how to prioritise the large number of discovered connections in an unbiased manner such that the success rate of any following-up investigation can be maximised. We introduce a new concept, gene-signature perturbation, which aims to test whether an identified connection is stable enough against systematic minor changes (perturbation) to the gene-signature. We applied the perturbation method to three independent datasets obtained from the GEO database: acute myeloid leukemia (AML), cervical cancer, and breast cancer treated with letrozole. We demonstrate that the perturbation approach helps to identify meaningful biological connections which suggest the most relevant candidate drugs. In the case of AML, we found that the prevalent compounds were retinoic acids and PPAR activators. For cervical cancer, our results suggested that potential drugs are likely to involve the EGFR pathway; and with the breast cancer dataset, we identified candidates that are involved in prostaglandin inhibition. Thus the gene-signature perturbation approach added real values to the whole connectivity mapping process, allowing for increased specificity in the identification of possible therapeutic candidates.

Positive association between nuclear Runx2 and oestrogen-progesterone receptor gene expression characterises a biological subtype of breast cancer

Purpose: The runt-related transcription factor, Runx2 may have an oncogenic role in mediating metastatic events in breast cancer, but whether Runx2 has a role in the early phases of breast cancer development is not clear. We examined the expression of Runx2 and its relationship with oestrogen receptor (ER) and progesterone receptor (PR) in breast cancer cell lines and tissues.

Novel breast cancer biomarkers identified by integrative proteomic and gene expression mapping

Proteomic and transcriptomic platforms both play important roles in cancer research, with differing strengths and limitations. Here, we describe a proteo-transcriptomic integrative strategy for discovering novel cancer biomarkers, combining the direct visualization of differentially expressed proteins with the high-throughput scale of gene expression profiling. Using breast cancer as a case example, we generated comprehensive two-dimensional electrophoresis (2DE)/mass spectrometry (MS) proteomic maps of cancer (MCF-7 and HCC-38) and control (CCD-1059Sk) cell lines, identifying 1724 expressed protein spots representing 484 different protein species. The differentially expressed cell-line proteins were then mapped to mRNA transcript databases of cancer cell lines and primary breast tumors to identify candidate biomarkers that were concordantly expressed at the gene expression level. Of the top nine selected biomarker candidates, we reidentified ANX1, a protein previously reported to be differentially expressed in breast cancers and normal tissues, and validated three other novel candidates, CRAB, 6PGL, and CAZ2, as differentially expressed proteins by immunohistochemistry on breast tissue microarrays. In total, close to half (4/9) of our protein biomarker candidates were successfully validated. Our study thus illustrates how the systematic integration of proteomic and transcriptomic data from both cell line and primary tissue samples can prove advantageous for accelerating cancer biomarker discovery.

Molecular Modeling on Inhibitor Complexes and Active-Site Dynamics of Cytochrome P450 C17, a Target for Prostate Cancer Therapy

A molecular model for the P450 enzyme cytochrome P450 C17 (CYP17) is presented based on sequence alignments of multiple template structures and homology modeling. This enzyme plays a central role in the biosynthesis of testosterone and is emerging as a major target in prostate cancer, with the recently developed inhibitor abiraterone currently in advanced clinical trials. The model is described in detail, together with its validation, by providing structural explanations to available site-directed mutagenesis data. The CYP17 molecule in this model is in the form of a triangular prism, with an edge of similar to 55 angstrom and a thickness of similar to 37 angstrom. It is predominantly helical, comprising 13 alpha helices interspersed by six 3(10) helices and 11 beta-sheets. Multinanosecond molecular dynamics simulations in explicit solvent have been carried out, and principal components analysis has been used to reveal the details of dynamics around the active site. Coarse-grained methods have also been used to verify low-frequency motions, which have been correlated with active-site gating. The work also describes the results of docking synthetic inhibitors, including the drug abiraterone and the natural substrate pregnenolone, in the CYP17 active site together with molecular dynamics simulations on the complexes. (C) 2010 Elsevier Ltd. All rights reserved.

Proteasome inhibitors in cancer therapy

The ubiquitin proteasome pathway plays a critical role in regulating many processes in the cell which are important for tumour cell growth and survival. Inhibition of proteasome function has emerged as a powerful strategy for anti-cancer therapy. Clinical validation of the proteasome as a therapeutic target was achieved with bortezomib and has prompted the development of a second generation of proteasome inhibitors with improved pharmacological properties. This review summarises the main mechanisms of action of proteasome inhibitors in cancer, the development of proteasome inhibitors as therapeutic agents and the properties and progress of next generation proteasome inhibitors in the clinic.