Background Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism’s fitness. SL gene network for human. In addition, available data on cancer mutated genes (COSMIC and Cancer Gene Census databases) as well as on existent approved drugs (DrugBank database) supports our selection of cancer-therapy candidates. Conclusions Our work provides a complementary alternative to the current methods for drug discovering and gene target identification in anti-cancer research. Novel SL screening analysis and the use of highly curated databases would contribute to improve the results of this methodology. Background High-throughput analyses have provided a tremendous boost to massive drug screening [1]. However, these improved techniques are still blind to biological or structural knowledge. In this sense, chemogenomics provides a complementary strategy for a rational screening that includes structural information of chemical compounds for gene targets [2,3]. Computational approaches in this so-called virtual screening allow the matching of compounds to their specific gene-product targets, completing the experimental screening [4]. However, the computational approach is still limited by the huge combinatorics represented by the chemical space of possibilities associated to the compounds and their possible targets. As a consequence, all these experimental and computational approaches require the use of the cumulative biological knowledge. For this purpose, database integration into an ontological business of the current biological knowledge has been suggested as a way to reduce the combinatorics either in virtual or experimental screenings [5]. The work presented here belongs to this last framework, intended as a tool for identifying potential targets for anti-cancer therapy. Cancer is a heterogeneous disease with numerous causes and typologies [6]. One of the essential traits of cancer progression is the underlying high mutational capacity of tumor cells [7-9], having as a consequence the rapid adaptive capacity of the disease. It has been suggested that these ingredients define cancer progression as a Darwinian micro-evolutionary process [10]. As a consequence, cancer cells which have lost essential genes by a mutation are eliminated from the tumor population. Therefore, it is expected that essential genes are conserved in cancer. Under this perspective, targeting essential buy 177610-87-6 genes in anti-cancer therapy could kill malignant cells, but might result to be lethal for healthy cells too. This is the case of the anti-proliferative drugs that also damage high turnover tissues, such as buy 177610-87-6 epithelium. The problems reported from the failure of most single-target drug treatments [11] suggest that a new perspective is needed. In this context, a different conceptual framework related with synthetic lethality has been suggested for anti-cancer research [12-14]. Two genes are called synthetic lethal (SL) if mutation of either alone is not lethal, but mutation of both leads to death or a significant decrease in organism’s fitness. According to screening methodology, two main types of mutations are considered: amorphic and hypormorphic mutations. The former causes a complete loss of gene function, while the latter refers to a mutation leading to a decreased activity in the respective gene function [15]. In genome-wide screenings of genetic interactions, hypomorphs are associated to essential genes such that the decrease of the gene expression does not result buy 177610-87-6 in inviable organisms [16]. The rationale of synthetic lethality offers new insights on selective anti-cancer therapy design by exploiting the presence of SL partners of mutated (cancer-related) genes [12,17,18]. Accordingly, given a mutated gene causing function deletion (amorphic mutation) or function decrease (hypomorphic mutation) in a cancer cell, an attack using specific drugs to block the activity of one of its SL partners would cause a lethal condition in such tumor cells. Meanwhile, only minor damage in healthy cells would be expected, constituting thus a selective anti-cancer therapy (see Figure ?Determine1).1). And thus, this approximation can help to overcome a dramatic limitation in drug design. Determine 1 The rationale of synthetic lethality applied to the design of novel anti-cancer therapies. Two linked nodes (blue circles) represent a SL interaction. (A) In cancer disease, one of the SL partners would appear mutated (red triangle) contrasting to healthy … Another relevant aspect in drug screening is that one drug is tested only for a specific disease and related pathologies. Given a SL pair of genes as described above, one cancer mutated and the other non-mutated, conceptually it is possible that an already approved and even commercialized drug Rabbit polyclonal to HPX might block the activity of the non-mutated gene product. Therefore, SL-partner screening has a special interest for gene-target identification but also for drug repositioning, i.e, the discovering of novel uses for aged drugs [19]. Unfortunately, large-scale screenings of SL gene pairs have been performed only in yeast [20-23] and, to a significantly smaller degree, in C. elegans [24-26] and in other model organisms. To overcome this limitation, we propose the use of the phylogenetic inference of SL genes from yeast to.