Drugs aimed at targeting characteristic karyotypic phenotypes of cancer cells

Drosophila as a model for chromosomal instability

Chromosomal instability (CIN) is a common feature of tumours that leads to increased genetic diversity in the tumour and poor clinical outcomes. There is considerable interest in understanding how CIN comes about and how its contribution to drug resistance and metastasis might be counteracted. In the last decade a number of CIN model systems have been developed in Drosophila that offer unique benefits both in understanding the development of CIN in a live animal as well as giving the potential to do genome wide screens for therapeutic candidate genes. This review outlines the mechanisms used in several Drosophila CIN model systems and summarizes some significant outcomes and opportunities that they have produced.

In silico pathway analysis based on chromosomal instability in breast cancer patients

BACKGROUND

Complex genomic changes that arise in tumors are a consequence of chromosomal instability. In tumor cells genomic aberrations disrupt core signaling pathways involving various genes, thus delineating of signaling pathways can help understand the pathogenesis of cancer. The bioinformatics tools can further help in identifying networks of interactions between the genes to get a greater biological context of all genes affected by chromosomal instability.

METHODS

Karyotypic analyses was done in 150 clinically confirmed breast cancer patients and 150 age and gender matched healthy controls after 72 h Peripheral lymphocyte culturing and GTG-banding. Reactome database from Cytoscape software version 3.7.1 was used to perform in-silico analysis (functional interaction and gene enrichment).

RESULTS

Frequency of chromosomal aberrations (structural and numerical) was found to be significantly higher in patients as compared to controls. The genes harbored by chromosomal regions showing increased aberration frequency in patients were further analyzed in-silico. Pathway analysis on a set of genes that were not linked together revealed that genes HDAC3, NCOA1, NLRC4, COL1A1, RARA, WWTR1, and BRCA1 were enriched in the RNA Polymerase II Transcription pathway which is involved in recruitment, initiation, elongation and dissociation during transcription.

CONCLUSION

The current study employs the information inferred from chromosomal instability analysis in a non-target tissue for determining the genes and the pathways associated with breast cancer. These results can be further extrapolated by performing either mutation analysis in the genes/pathways deduced or expression analysis which can pinpoint the relevant functional impact of chromosomal instability.

Identifying new topoisomerase II poison scaffolds by combining publicly available toxicity data and 2D/3D-based virtual screening

Molecular descriptor (2D) and three dimensional (3D) shape based similarity methods are widely used in ligand based virtual drug design. In the present study pairwise structure comparisons among a set of 4858 DTP compounds tested in the NCI60 tumor cell line anticancer drug screen were computed using chemical hashed fingerprints and 3D molecule shapes to calculate 2D and 3D similarities, respectively. Additionally, pairwise biological activity similarities were calculated by correlating the 60 element vectors of pGI50 values corresponding to the cytotoxicity of the compounds across the NCI60 panel. Subsequently, we compared the power of 2D and 3D structural similarity metrics to predict the toxicity pattern of compounds. We found that while the positive predictive value and sensitivity of 3D and molecular descriptor based approaches to predict biological activity are similar, a subset of molecule pairs yielded contradictory results. By simultaneously requiring similarity of biological activities and 3D shapes, and dissimilarity of molecular descriptor based comparisons, we identify pairs of scaffold hopping candidates displaying characteristic core structural changes such as heteroatom/heterocycle change and ring closure. Attempts to discover scaffold hopping candidates of mitoxantrone recovered known Topoisomerase II (Top2) inhibitors, and also predicted new, previously unknown chemotypes possessing in vitro Top2 inhibitory activity.

Multi-layered cancer chromosomal instability phenotype

Whole-chromosomal instability (W-CIN) – unequal chromosome distribution during cell division – is a characteristic feature of a majority of cancer cells distinguishing them from their normal counterparts. The precise molecular mechanisms that may cause mis-segregation of chromosomes in tumor cells just recently became more evident. The consequences of W-CIN are numerous and play a critical role in carcinogenesis. W-CIN mediates evolution of cancer cell population under selective pressure and can facilitate the accumulation of genetic changes that promote malignancy. It has both tumor-promoting and tumor-suppressive effects, and their balance could be beneficial or detrimental for carcinogenesis. The characterization of W-CIN as a complex multi-layered adaptive phenotype highlights the intra- and extracellular adaptations to the consequences of genome reshuffling. It also provides a framework for targeting aggressive chromosomally unstable cancers.

Targeting aneuploid cancer cells

INTRODUCTION

Most cancers are characterized by some degree of aneuploidy, although its relevance for tumor initiation or progression and the nature of the initial trigger are still not well understood. It was Theodor Boveri who first suggested a link between aneuploidy and cancer at the beginning of the last century, but it is only recently that the molecular mechanisms involved have started to be uncovered.

AREAS COVERED

The molecular mechanisms that are at the origin of aneuploidy and their cellular consequences. Based on these new findings molecular targets have emerged which could lead to a specific treatment of at least some types of aneuploid tumors.

EXPERT OPINION

Therapeutic intervention specifically for aneuploid cells is a very promising approach, however, although new promising targets have been spotted they still need to be tested for proof of concept. Targeting the spindle checkpoint could be an interesting approach for cancer therapy, however, as for other mitotic targets, the open question of the therapeutic window and sensitivity of normal hemopoietic cells has to be considered carefully. Future challenges will not only include identifying and validating druggable targets related to the relevant pathways, but also finding predictive biomarkers to define the responding patient population(s).

Targeting karyotypic complexity and chromosomal instability of cancer cells

Multiple karyotypic abnormalities and chromosomal instability are characteristic features of many cancers that are relatively resistant to chemotherapeutic agents currently used in the clinic. These same features represent potentially targetable "states" that are essentially tumor specific. The assessment of the chromosomal state of a cancer cell population may provide a guide for the selection or development of drugs active against aggressive and intractable cancers.

Chromosomal instability is associated with higher expression of genes implicated in epithelial-mesenchymal transition, cancer invasiveness, and metastasis and with lower expression of genes involved in cell cycle checkpoints, DNA repair, and chromatin maintenance

Chromosomal instability-a hallmark of epithelial cancers-is an ongoing process that results in aneuploidy and karyotypic heterogeneity of a cancer cell population. Previously, we stratified cancer cell lines in the NCI-60 drug discovery panel based on their karyotypic complexity and heterogeneity. Using this stratification in conjunction with drug response data for the cell lines allowed us to identify classes of chemical compounds whose growth-inhibitory activity correlates with karyotypic complexity and chromosomal instability. In this article, we asked the question: What are the biological processes, pathways, or genes associated with chromosomal instability of cancer cells? We found that increased instability of the chromosomal content in a cancer cell population, particularly, persistent gains and losses of chromosomes, is associated with elevated expression of genes involved with aggressive cellular behavior, including invasion- and metastasis-associated changes in cell communication, adhesion, motility, and migration. These same karyotypic features are negatively correlated with the expression of genes involved in cell cycle checkpoints, DNA repair, and chromatin maintenance.

Genetic variations and gene expression of transporters in drug disposition and response

BACKGROUND

The importance of transporters in drug disposition and response has led to increasing interest in genetic variations and expression differences of their genes.

OBJECTIVE

This review summarizes: i) genetic variations in transporters and associated drug response; and ii) a pharmacogenomic approach to correlate transporter expression and drug response.

METHODS

Several transporters in ATP-binding cassette family and solute carrier family are discussed.

CONCLUSION

The field of transporter pharmacogenomics is in its early stage. Transporter expression at mRNA levels could be more directly related to their functions and more practical to be assayed in high throughput. Correlating microarray expression of transporters with anticancer drug activity in the NCI-60 panel has provided an approach for identifying drug-transporter relationships and predicting drug response.

Connecting chemosensitivity, gene expression and disease

Omics-based investigations offer potentially powerful readouts that might be useful for probing the underlying biology of normal and diseased states, identifying novel therapeutic targets and proposing relevant markers for designing treatment strategies. A vital component of these investigations involves a systematic analysis of gene expression and chemosensitivity data in the context of disease states and small molecule probes into the function of targets responsible for a disease phenotype. Systematic analysis of chemical and pharmacogenetics data offers a possible means to identify novel, small-molecule, potentially therapeutic, agents that affect the phenotype of a particular target. Elegantly simple in concept, the covariation of genetic and chemosensitivity readouts provide a hypothetical link for relating compounds through genomic expression profiles to underlying biology.

Anticancer medicines in development: assessment of bioactivity profiles within the National Cancer Institute anticancer screening data

We present an analysis of current anticancer compounds that are in phase I, II, or III clinical trials and their structural analogues that have been screened in the National Cancer Institute (NCI) anticancer screening program. Bioactivity profiles, measured across the NCI 60 cell lines, were examined for a correspondence between the type of cancer proposed for clinical testing and selective sensitivity to appropriately matched tumor subpanels in the NCI screen. These results find strongest support for using the NCI anticancer screen to select analogue compounds with selective sensitivity to the leukemia, colon, central nervous system, melanoma, and ovarian panels, but not for renal, prostate, and breast panels. These results are extended to applications of two-dimensional structural features to further refine compound selections based on tumor panel sensitivity obtained from tumor screening results.

MicroRNA expression profiles for the NCI-60 cancer cell panel

Advances in the understanding of cancer cell biology and response to drug treatment have benefited from new molecular technologies and methods for integrating information from multiple sources. The NCI-60, a panel of 60 diverse human cancer cell lines, has been used by the National Cancer Institute to screen >100,000 chemical compounds and natural product extracts for anticancer activity. The NCI-60 has also been profiled for mRNA and protein expression, mutational status, chromosomal aberrations, and DNA copy number, generating an unparalleled public resource for integrated chemogenomic studies. Recently, microRNAs have been shown to target particular sets of mRNAs, thereby preventing translation or accelerating mRNA turnover. To complement the existing NCI-60 data sets, we have measured expression levels of microRNAs in the NCI-60 and incorporated the resulting data into the CellMiner program package for integrative analysis. Cell line groupings based on microRNA expression were generally consistent with tissue type and with cell line clustering based on mRNA expression. However, mRNA expression seemed to be somewhat more informative for discriminating among tissue types than was microRNA expression. In addition, we found that there does not seem to be a significant correlation between microRNA expression patterns and those of known target transcripts. Comparison of microRNA expression patterns and compound potency patterns showed significant correlations, suggesting that microRNAs may play a role in chemoresistance. Combined with gene expression and other biological data using multivariate analysis, microRNA expression profiles may provide a critical link for understanding mechanisms involved in chemosensitivity and chemoresistance.

Streamlining lead discovery by aligning in silico and high-throughput screening

Lead discovery in the pharmaceutical environment is largely an industrial-scale process in which it is typical to screen 1-5 million compounds in a matter of weeks using High Throughput Screening (HTS). This process is a very costly endeavor. Typically a HTS campaign of 1 million compounds will cost anywhere from $500000 to $1000000. There is consequently a great deal of pressure to maximize the return on investment by finding fast and more effective ways to screen. A panacea that has emerged over the past few years to help address this issue is in silico screening. In silico screening is now incorporated in all areas of lead discovery; from target identification and library design, to hit analysis and compound profiling. However, as lead discovery has evolved over the past few years, so has the role of in silico screening.