Exploration of synthetic lethal interactions as cancer drug targets

Cell cycle-tailored targeting of metastatic melanoma: Challenges and opportunities

The advent of targeted therapies of metastatic melanoma, such as MAPK pathway inhibitors and immune checkpoint antagonists, has turned dermato-oncology from the "bad guy" to the "poster child" in oncology. Current targeted therapies are effective, although here is a clear need to develop combination therapies to delay the onset of resistance. Many antimelanoma drugs impact on the cell cycle but are also dependent on certain cell cycle phases resulting in cell cycle phase-specific drug insensitivity. Here, we raise the question: Have combination trials been abandoned prematurely as ineffective possibly only because drug scheduling was not optimized? Firstly, if both drugs of a combination hit targets in the same melanoma cell, cell cycle-mediated drug insensitivity should be taken into account when planning combination therapies, timing of dosing schedules and choice of drug therapies in solid tumors. Secondly, if the combination is designed to target different tumor cell subpopulations of a heterogeneous tumor, one drug effective in a particular subpopulation should not negatively impact on the other drug targeting another subpopulation. In addition to the role of cell cycle stage and progression on standard chemotherapeutics and targeted drugs, we discuss the utilization of cell cycle checkpoint control defects to enhance chemotherapeutic responses or as targets themselves. We propose that cell cycle-tailored targeting of metastatic melanoma could further improve therapy outcomes and that our real-time cell cycle imaging 3D melanoma spheroid model could be utilized as a tool to measure and design drug scheduling approaches.

A New Strategy to Reduce Influenza Escape: Detecting Therapeutic Targets Constituted of Invariance Groups

The pathogenicity of the different flu species is a real public health problem worldwide. To combat this scourge, we established a method to detect drug targets, reducing the possibility of escape. Besides being able to attach a drug candidate, these targets should have the main characteristic of being part of an essential viral function. The invariance groups that are sets of residues bearing an essential function can be detected genetically. They consist of invariant and synthetic lethal residues (interdependent residues not varying or slightly varying when together). We analyzed an alignment of more than 10,000 hemagglutinin sequences of influenza to detect six invariance groups, close in space, and on the protein surface. In parallel we identified five potential pockets on the surface of hemagglutinin. By combining these results, three potential binding sites were determined that are composed of invariance groups located respectively in the vestigial esterase domain, in the bottom of the stem and in the fusion area. The latter target is constituted of residues involved in the spring-loaded mechanism, an essential step in the fusion process. We propose a model describing how this potential target could block the reorganization of the hemagglutinin HA2 secondary structure and prevent viral entry into the host cell.

Malignancy of Cancers and Synthetic Lethal Interactions Associated With Mutations of Cancer Driver Genes

The mutation status of cancer driver genes may correlate with different degrees of malignancy of cancers. The doubling time and multidrug resistance are 2 phenotypes that reflect the degree of malignancy of cancer cells. Because most of cancer driver genes are hard to target, identification of their synthetic lethal partners might be a viable approach to treatment of the cancers with the relevant mutations.The genome-wide screening for synthetic lethal partners is costly and labor intensive. Thus, a computational approach facilitating identification of candidate genes for a focus synthetic lethal RNAi screening will accelerate novel anticancer drug discovery.We used several publicly available cancer cell lines and tumor tissue genomic data in this study.We compared the doubling time and multidrug resistance between the NCI-60 cell lines with mutations in some cancer driver genes and those without the mutations. We identified some candidate synthetic lethal genes to the cancer driver genes APC, KRAS, BRAF, PIK3CA, and TP53 by comparison of their gene phenotype values in cancer cell lines with the relevant mutations and wild-type background. Further, we experimentally validated some of the synthetic lethal relationships we predicted.We reported that mutations in some cancer driver genes mutations in some cancer driver genes such as APC, KRAS, or PIK3CA might correlate with cancer proliferation or drug resistance. We identified 40, 21, 5, 43, and 18 potential synthetic lethal genes to APC, KRAS, BRAF, PIK3CA, and TP53, respectively. We found that some of the potential synthetic lethal genes show significantly higher expression in the cancers with mutations of their synthetic lethal partners and the wild-type counterparts. Further, our experiments confirmed several synthetic lethal relationships that are novel findings by our methods.We experimentally validated a part of the synthetic lethal relationships we predicted. We plan to perform further experiments to validate the other synthetic lethal relationships predicted by this study.Our computational methods achieve to identify candidate synthetic lethal partners to cancer driver genes for further experimental screening with multiple lines of evidences, and therefore contribute to development of anticancer drugs.

Synthetic lethals in HIV: ways to avoid drug resistance : Running title: Preventing HIV resistance

Background

RNA viruses rapidly accumulate genetic variation, which can give rise to synthetic lethal (SL) and deleterious (SD) mutations. Synthetic lethal mutations (non-lethal when alone but lethal when combined in one genome) have been studied to develop cancer therapies. This principle can also be used against fast-evolving RNA-viruses. Indeed, targeting protein sites involved in SD + SL interactions with a drug would render any mutation of such sites, lethal.

Results

Here, we set up a strategy to detect intragenic pairs of SL and SD at the surface of the protein to predict less escapable drug target sites. For this, we detected SD + SL, studying HIV protease (PR) and reverse transcriptase (RT) sequence alignments from two groups of VIH⁺ individuals: treated with drugs (T) or not (NT). Using a series of statistical approaches, we were able to propose bona fide SD + SL couples. When focusing on spatially close co-variant SD + SL couples at the surface of the protein, we found 5 SD + SL groups (2 in the protease and 3 in the reverse transcriptase), which could be good candidates to form pockets to accommodate potential drugs.

Conclusions

Thus, designing drugs targeting these specific SD + SL groups would not allow the virus to mutate any residue involved in such groups without losing an essential function. Moreover, we also show that the selection pressure induced by the treatment leads to the appearance of new mutations, which change the mutational landscape of the protein. This drives the existence of differential SD + SL couples between the drug-treated and non-treated groups. Thus, new anti-viral drugs should be designed differently to target such groups.

Reviewers

This article was reviewed by Neil Greenspan Csaba Pal and István Simon.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-015-0044-y) contains supplementary material, which is available to authorized users.

Systems cell biology

Systems cell biology melds high-throughput experimentation with quantitative analysis and modeling to understand many critical processes that contribute to cellular organization and dynamics. Recently, there have been several advances in technology and in the application of modeling approaches that enable the exploration of the dynamic properties of cells. Merging technology and computation offers an opportunity to objectively address unsolved cellular mechanisms, and has revealed emergent properties and helped to gain a more comprehensive and fundamental understanding of cell biology.

DNA repair and cell cycle checkpoint defects as drivers and therapeutic targets in melanoma

The ultraviolet radiation (UVR) component of sunlight is the major environmental risk factor for melanoma, producing DNA lesions that can be mutagenic if not repaired. The high level of mutations in melanomas that have the signature of UVR-induced damage indicates that the normal mechanisms that detect and repair this damage must be defective in this system. With the exception of melanoma-prone heritable syndromes which have mutations of repair genes, there is little evidence for somatic mutation of known repair genes. Cell cycle checkpoint controls are tightly associated with repair mechanisms, arresting cells to allow for repair before continuing through the cell cycle. Checkpoint signaling components also regulate the repair mechanisms. Defects in checkpoint mechanisms have been identified in melanomas and are likely to be responsible for increased mutation load in melanoma. Loss of the checkpoint responses may also provide an opportunity to target melanomas using a synthetic lethal approach to identify and inhibit mechanisms that compensate for the defective checkpoints.

Genistein abrogates G2 arrest induced by curcumin in p53 deficient T47D cells

BACKGROUND

The high cost and low level of cancer survival urge the finding of new drugs having better mechanisms. There is a high trend of patients to be "back to nature" and use natural products as an alternative way to cure cancer. The fact is that some of available anticancer drugs are originated from plants, such as taxane, vincristine, vinblastine, pacitaxel. Curcumin (diferuloylmethane), a dietary pigment present in Curcuma longa rizhome is reported to induce cell cycle arrest in some cell lines. Other study reported that genistein isolated from Glycine max seed inhibited phosphorylation of cdk1, gene involved during G2/M transition and thus could function as G2 checkpoint abrogator. The inhibition of cdk1 phosphorylation is one of alternative strategy which could selectively kill cancer cells and potentially be combined with DNA damaging agent such as curcumin.

METHODS

T47D cell line was treated with different concentrations of curcumin and genistein, alone or in combination; added together or with interval time. Flow Cytometry and MTT assay were used to evaluate cell cycle distribution and viability, respectively. The presence of apoptotic cells was determined using acridine orange-ethidium bromide staining.

RESULTS

In this study curcumin induced G2 arrest on p53 deficient T47D cells at the concentration of 10 μM. Increasing concentration up to 30 μM increased the number of cell death. Whilst genistein alone at low concentration (≤10 μM) induced cell proliferation, addition of genistein (20 μM) 16 h after curcumin resulted in more cell death (89%), 34% higher than that administered at the same time (56%). The combination treatment resulted in apoptotic cell death. Combining curcumin with high dose of genistein (50 μM) induced necrotic cells.

CONCLUSIONS

Genistein increased the death of curcumin treated T47D cells. Appropriate timing of administration and concentration of genistein determine the outcome of treatment and this method could potentially be developed as an alternative strategy for treatment of p53 defective cancer cells.

Systems genetics in "-omics" era: current and future development

The systems genetics is an emerging discipline that integrates high-throughput expression profiling technology and systems biology approaches for revealing the molecular mechanism of complex traits, and will improve our understanding of gene functions in the biochemical pathway and genetic interactions between biological molecules. With the rapid advances of microarray analysis technologies, bioinformatics is extensively used in the studies of gene functions, SNP-SNP genetic interactions, LD block-block interactions, miRNA-mRNA interactions, DNA-protein interactions, protein-protein interactions, and functional mapping for LD blocks. Based on bioinformatics panel, which can integrate "-omics" datasets to extract systems knowledge and useful information for explaining the molecular mechanism of complex traits, systems genetics is all about to enhance our understanding of biological processes. Systems biology has provided systems level recognition of various biological phenomena, and constructed the scientific background for the development of systems genetics. In addition, the next-generation sequencing technology and post-genome wide association studies empower the discovery of new gene and rare variants. The integration of different strategies will help to propose novel hypothesis and perfect the theoretical framework of systems genetics, which will make contribution to the future development of systems genetics, and open up a whole new area of genetics.

Defective cell cycle checkpoints as targets for anti-cancer therapies

Conventional chemotherapeutics target the proliferating fraction of cells in the patient's body, which will include the tumor cells, but are also toxic to actively proliferating normal tissues. Cellular stresses, such as those imposed by chemotherapeutic drugs, induce cell cycle checkpoint arrest, and currently approaches targeting these checkpoints are being explored to increase the efficacy and selectivity of conventional chemotherapeutic treatments. Loss of a checkpoint may also make cancer cells more reliant on other mechanisms to compensate for the loss of this function, and these compensatory mechanisms may be targeted using synthetic lethal approaches. Here we will discuss the utility of targeting checkpoint defects as novel anti-cancer therapies.