Applying synthetic lethality for the selective targeting of cancer

Novel Targeted Agents in Head and Neck Squamous Cell Carcinoma

Based on currently available genomic data, most head and neck squamous cell carcinoma have few targetable aberrations and immediate clinical translation is challenging. However, potential therapeutic agents listed in this article need to be thoroughly evaluated because there are compelling scientific rationales supporting their development. Concerted effort is required to identify better predictive biomarkers of clinical benefit and improve the therapeutic index. Clinicians need to better understand resistance mechanisms, generate novel hypotheses for appropriate combination regimens and dosing schedules, develop more accurate model systems, and conduct innovative clinical trials.

High burden of copy number alterations and c-MYC amplification in prostate cancer from BRCA2 germline mutation carriers

BACKGROUND

Germline BRCA2 mutations are associated with poorer outcome prostate cancer (PCa) compared with sporadic tumours but this association remains to be characterised. In this study, we aim to assess if there is a signature set of copy number alterations (CNA) that could aid to the identification of BRCA2-mutated tumours and would assist us to understand their aggressive clinical behaviour.

METHODS

High-resolution array comparative genomic hybridisation profiling of DNA from PCa and matched morphologically normal prostate samples from 9 BRCA2 germline mutation carriers and 16 non-carriers in combination with unsupervised analysis was used to define copy number features.

RESULTS

PCa from BRCA2 germline mutation carriers (B2T) harbour significantly more CNA than non-carrier tumours (NCTs) (P = 14 × 10(-6)). A hundred and sixteen regions had a significantly different distribution with both false discovery rate (FDR) and P value <0.01, including CNA in the genomic region containing c-MYC that was present in 89% B2T versus 12.5% NCT (P = 3 × 10(-4)). Loss of heterozygosity (LOH) at the BRCA2 locus was observed in 67% of B2T. Elevated CNA are already present in 50% of the morphologically normal prostate tissue from BRCA2 carriers.

CONCLUSION

The relative high amount of CNAs in morphologically normal prostate tissue of BRCA2 carriers implies a field effect and together with the observed LOH could be used as a marker of PCa risk in these men. Several features previously associated with poor PCa outcome have been found to be significantly more common in BRCA2-mutated PCa than in sporadic tumours and may help to explain their adverse prognosis and be of relevance for targeted therapies.

SynLethDB: synthetic lethality database toward discovery of selective and sensitive anticancer drug targets

Synthetic lethality (SL) is a type of genetic interaction between two genes such that simultaneous perturbations of the two genes result in cell death or a dramatic decrease of cell viability, while a perturbation of either gene alone is not lethal. SL reflects the biologically endogenous difference between cancer cells and normal cells, and thus the inhibition of SL partners of genes with cancer-specific mutations could selectively kill cancer cells but spare normal cells. Therefore, SL is emerging as a promising anticancer strategy that could potentially overcome the drawbacks of traditional chemotherapies by reducing severe side effects. Researchers have developed experimental technologies and computational prediction methods to identify SL gene pairs on human and a few model species. However, there has not been a comprehensive database dedicated to collecting SL pairs and related knowledge. In this paper, we propose a comprehensive database, SynLethDB (http://histone.sce.ntu.edu.sg/SynLethDB/), which contains SL pairs collected from biochemical assays, other related databases, computational predictions and text mining results on human and four model species, i.e. mouse, fruit fly, worm and yeast. For each SL pair, a confidence score was calculated by integrating individual scores derived from different evidence sources. We also developed a statistical analysis module to estimate the druggability and sensitivity of cancer cells upon drug treatments targeting human SL partners, based on large-scale genomic data, gene expression profiles and drug sensitivity profiles on more than 1000 cancer cell lines. To help users access and mine the wealth of the data, we developed other practical functionalities, such as search and filtering, orthology search, gene set enrichment analysis. Furthermore, a user-friendly web interface has been implemented to facilitate data analysis and interpretation. With the integrated data sets and analytics functionalities, SynLethDB would be a useful resource for biomedical research community and pharmaceutical industry.

Prediction of Genetic Interactions Using Machine Learning and Network Properties

A genetic interaction (GI) is a type of interaction where the effect of one gene is modified by the effect of one or several other genes. These interactions are important for delineating functional relationships among genes and their corresponding proteins, as well as elucidating complex biological processes and diseases. An important type of GI - synthetic sickness or synthetic lethality - involves two or more genes, where the loss of either gene alone has little impact on cell viability, but the combined loss of all genes leads to a severe decrease in fitness (sickness) or cell death (lethality). The identification of GIs is an important problem for it can help delineate pathways, protein complexes, and regulatory dependencies. Synthetic lethal interactions have important clinical and biological significance, such as providing therapeutically exploitable weaknesses in tumors. While near systematic high-content screening for GIs is possible in single cell organisms such as yeast, the systematic discovery of GIs is extremely difficult in mammalian cells. Therefore, there is a great need for computational approaches to reliably predict GIs, including synthetic lethal interactions, in these organisms. Here, we review the state-of-the-art approaches, strategies, and rigorous evaluation methods for learning and predicting GIs, both under general (healthy/standard laboratory) conditions and under specific contexts, such as diseases.

Advances in small-molecule drug discovery for triple-negative breast cancer

Triple-negative breast cancer (TNBC) is a subtype of poor prognosis, highly invasive and difficult-to-treat breast cancers accounting for approximately 15% of clinical cases. Given the poor outlook and lack of sustained response to conventional therapies, TNBC has been the subject of intense studies on new therapeutic approaches in recent years. The development of targeted cancer therapies, often in combination with established chemotherapy, has been applied to a number of new clinical studies in this setting in recent years. This review will highlight recent therapeutic advances in TNBC, focusing on small-molecule drugs and their associated biological mechanisms of action, and offering the possibility of improved prospects for this patient group in the near future.

Molecular Aspects of Head and Neck Cancer Therapy

In spite of a rapidly expanding understanding of head and neck tumor biology and optimization of radiation, chemotherapy, and surgical treatment modalities, head and neck squamous cell carcinoma (HNSCC) remains a major cause of cancer-related morbidity and mortality. Although our biologic understanding of these tumors had largely been limited to pathways driving proliferation, survival, and differentiation, the identification of HPV as a major driver of HNSCC and genomic sequencing analyses has dramatically influenced our understanding of tumor biology and approach to therapy. Here, we summarize molecular aspects of HNSCC biology and identify promising areas for potential diagnostic and therapeutic agents.

Defective sister chromatid cohesion is synthetically lethal with impaired APC/C function

Warsaw breakage syndrome (WABS) is caused by defective DDX11, a DNA helicase that is essential for chromatid cohesion. Here, a paired genome-wide siRNA screen in patient-derived cell lines reveals that WABS cells do not tolerate partial depletion of individual APC/C subunits or the spindle checkpoint inhibitor p31^comet. A combination of reduced cohesion and impaired APC/C function also leads to fatal mitotic arrest in diploid RPE1 cells. Moreover, WABS cell lines, and several cancer cell lines with cohesion defects, display a highly increased response to a new cell-permeable APC/C inhibitor, apcin, but not to the spindle poison paclitaxel. Synthetic lethality of APC/C inhibition and cohesion defects strictly depends on a functional mitotic spindle checkpoint as well as on intact microtubule pulling forces. This indicates that the underlying mechanism involves cohesion fatigue in response to mitotic delay, leading to spindle checkpoint re-activation and lethal mitotic arrest. Our results point to APC/C inhibitors as promising therapeutic agents targeting cohesion-defective cancers.

Cohesion is associated with many forms of cancer. De Lange et al. show that such cohesion defects can sensitise cells to apoptosis in response to a new APC/C ubiquitin ligase inhibitor, by prolonging mitotic arrest and checkpoint activation due to cohesion fatigue.

Inferring synthetic lethal interactions from mutual exclusivity of genetic events in cancer

Background

Synthetic lethality (SL) refers to the genetic interaction between two or more genes where only their co-alteration (e.g. by mutations, amplifications or deletions) results in cell death. In recent years, SL has emerged as an attractive therapeutic strategy against cancer: by targeting the SL partners of altered genes in cancer cells, these cells can be selectively killed while sparing the normal cells. Consequently, a number of studies have attempted prediction of SL interactions in human, a majority by extrapolating SL interactions inferred through large-scale screens in model organisms. However, these predicted SL interactions either do not hold in human cells or do not include genes that are (frequently) altered in human cancers, and are therefore not attractive in the context of cancer therapy.

Results

Here, we develop a computational approach to infer SL interactions directly from frequently altered genes in human cancers. It is based on the observation that pairs of genes that are altered in a (significantly) mutually exclusive manner in cancers are likely to constitute lethal combinations. Using genomic copy-number and gene-expression data from four cancers, breast, prostate, ovarian and uterine (total 3980 samples) from The Cancer Genome Atlas, we identify 718 genes that are frequently amplified or upregulated, and are likely to be synthetic lethal with six key DNA-damage response (DDR) genes in these cancers. By comparing with published data on gene essentiality (~16000 genes) from ten DDR-deficient cancer cell lines, we show that our identified genes are enriched among the top quartile of essential genes in these cell lines, implying that our inferred genes are highly likely to be (synthetic) lethal upon knockdown in these cell lines. Among the inferred targets are tousled-like kinase 2 (TLK2) and the deubiquitinating enzyme ubiquitin-specific-processing protease 7 (USP7) whose overexpression correlates with poor survival in cancers.

Conclusion

Mutual exclusivity between frequently occurring genetic events identifies synthetic lethal combinations in cancers. These identified genes are essential in cell lines, and are potential candidates for targeted cancer therapy. Availability: http://bioinformatics.org.au/tools-data/underMutExSL

Reviewers

This article was reviewed by Dr Michael Galperin, Dr Sebastian Maurer-Stroh and Professor Sanghyuk Lee.

Electronic supplementary material

The online version of this article (doi:10.1186/s13062-015-0086-1) contains supplementary material, which is available to authorized users.

Mutational landscapes of tongue carcinoma reveal recurrent mutations in genes of therapeutic and prognostic relevance

Background

Carcinoma of the oral tongue (OTSCC) is the most common malignancy of the oral cavity, characterized by frequent recurrence and poor survival. The last three decades has witnessed a change in the OTSCC epidemiological profile, with increasing incidence in younger patients, females and never-smokers. Here, we sought to characterize the OTSCC genomic landscape and to determine factors that may delineate the genetic basis of this disease, inform prognosis and identify targets for therapeutic intervention.

Methods

Seventy-eight cases were subjected to whole-exome (n = 18) and targeted deep sequencing (n = 60).

Results

While the most common mutation was in TP53, the OTSCC genetic landscape differed from previously described cohorts of patients with head and neck tumors: OTSCCs demonstrated frequent mutations in DST and RNF213, while alterations in CDKN2A and NOTCH1 were significantly less frequent. Despite a lack of previously reported NOTCH1 mutations, integrated analysis showed enrichments of alterations affecting Notch signaling in OTSCC. Importantly, these Notch pathway alterations were prognostic on multivariate analyses. A high proportion of OTSCCs also presented with alterations in drug targetable and chromatin remodeling genes. Patients harboring mutations in actionable pathways were more likely to succumb from recurrent disease compared with those who did not, suggesting that the former should be considered for treatment with targeted compounds in future trials.

Conclusions

Our study defines the Asian OTSCC mutational landscape, highlighting the key role of Notch signaling in oral tongue tumorigenesis. We also observed somatic mutations in multiple therapeutically relevant genes, which may represent candidate drug targets in this highly lethal tumor type.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0219-2) contains supplementary material, which is available to authorized users.

Improving Prospects for Targeting RAS

RAS mutations are among the most common oncogenic drivers in human cancers, affecting nearly a third of all solid tumors and around a fifth of common myeloid malignancies, but they have evaded therapeutic interventions, despite being the focus of intense research over the last three decades. Recent discoveries lend new understanding about the structure, function, and signaling of RAS and have opened new avenues for development of much needed new therapies. We discuss the various approaches under investigation to target mutant RAS proteins. The recent development of direct RAS inhibitors specific to KRAS G12C mutations represents a landmark discovery that promises to change the perception about RAS's druggability. Multiple clinical trials targeting synthetically lethal partners and/or downstream signaling partners of RAS are underway. Novel inhibitors targeting various arms of RAS processing and signaling have yielded encouraging results in the laboratory, but refinement of the drug-like properties of these molecules is required before they will be ready for the clinic.

Enzyme-responsive doxorubicin release from dendrimer nanoparticles for anticancer drug delivery

Background

Since cancer cells are normally over-expressed cathepsin B, we synthesized dendrimer-methoxy poly(ethylene glycol) (MPEG)-doxorubicin (DOX) conjugates using a cathepsin B-cleavable peptide for anticancer drug targeting.

Methods

Gly-Phe-Leu-Gly peptide was conjugated with the carboxylic acid end groups of a dendrimer, which was then conjugated with MPEG amine and doxorubicin by aid of carbodiimide chemistry (abbreviated as DendGDP). Dendrimer-MPEG-DOX conjugates without Gly-Phe-Leu-Gly peptide linkage was also synthesized for comparison (DendDP). Nanoparticles were then prepared using a dialysis procedure.

Results

The synthesized DendGDP was confirmed with ¹H nuclear magnetic resonance spectroscopy. The DendDP and DendGDP nanoparticles had a small particle size of less than 200 nm and had a spherical morphology. DendGDP had cathepsin B-sensitive drug release properties while DendDP did not show cathepsin B sensitivity. Further, DendGDP had improved anticancer activity when compared with doxorubicin or DendDP in an in vivo CT26 tumor xenograft model, ie, the volume of the CT26 tumor xenograft was significantly inhibited when compared with xenografts treated with doxorubicin or DendDP nanoparticles. The DendGDP nanoparticles were found to be relatively concentrated in the tumor tissue and revealed stronger fluorescence intensity than at other body sites while doxorubicin and DendDP nanoparticles showed strong fluorescence intensity in the various organs, indicating that DendGDP has cathepsin B sensitivity.

Conclusion

DendGDP is sensitive to cathepsin B in tumor cells and can be used as a cathepsin B-responsive drug targeting strategy. We suggest that DendGDP is a promising vehicle for cancer cell targeting.

Massively parallel high-order combinatorial genetics in human cells

The systematic functional analysis of combinatorial genetics has been limited by the throughput that can be achieved and the order of complexity that can be studied. To enable massively parallel characterization of genetic combinations in human cells, we developed a technology for rapid, scalable assembly of high-order barcoded combinatorial genetic libraries that can be quantified with high-throughput sequencing. We applied this technology, combinatorial genetics en masse (CombiGEM), to create high-coverage libraries of 1,521 two-wise and 51,770 three-wise barcoded combinations of 39 human microRNA (miRNA) precursors. We identified miRNA combinations that synergistically sensitize drug-resistant cancer cells to chemotherapy and/or inhibit cancer cell proliferation, providing insights into complex miRNA networks. More broadly, our method will enable high-throughput profiling of multifactorial genetic combinations that regulate phenotypes of relevance to biomedicine, biotechnology and basic science.

Cancer in the parasitic protozoans Trypanosoma brucei and Toxoplasma gondii

Cancer is a general name for more than 100 malignant diseases. It is postulated that all cancers start from a single abnormal cell that grows out of control. Untreated cancers can cause serious consequences and deaths. Great progress has been made in cancer research that has significantly improved our knowledge and understanding of the nature and mechanisms of the disease, but the origins of cancer are far from being well understood due to the limitations of suitable model systems and to the complexities of the disease. In view of the fact that cancers are found in various species of vertebrates and other metazoa, here, we suggest that cancer also occurs in parasitic protozoans such as Trypanosoma brucei, a blood parasite, and Toxoplasma gondii, an obligate intracellular pathogen. Without treatment, these protozoan cancers may cause severe disease and death in mammals, including humans. The simpler genomes of these single-cell organisms, in combination with their complex life cycles and fascinating life cycle differentiation processes, may help us to better understand the origins of cancers and, in particular, leukemias.

Network-based approaches for drug response prediction and targeted therapy development in cancer

Signaling pathways implicated in cancer create a complex network with numerous regulatory loops and redundant pathways. This complexity explains frequent failure of one-drug-one-target paradigm of treatment, resulting in drug resistance in patients. To overcome the robustness of cell signaling network, cancer treatment should be extended to a combination therapy approach. Integrating and analyzing patient high-throughput data together with the information about biological signaling machinery may help deciphering molecular patterns specific to each patient and finding the best combinations of candidates for therapeutic targeting. We review state of the art in the field of targeted cancer medicine from the computational systems biology perspective. We summarize major signaling network resources and describe their characteristics with respect to applicability for drug response prediction and intervention targets suggestion. Thus discuss methods for prediction of drug sensitivity and intervention combinations using signaling networks together with high-throughput data. Gradual integration of these approaches into clinical routine will improve prediction of response to standard treatments and adjustment of intervention schemes.

Selective Targeting of CTNBB1-, KRAS- or MYC-Driven Cell Growth by Combinations of Existing Drugs

The aim of combination drug treatment in cancer therapy is to improve response rate and to decrease the probability of the development of drug resistance. Preferably, drug combinations are synergistic rather than additive, and, ideally, drug combinations work synergistically only in cancer cells and not in non-malignant cells. We have developed a workflow to identify such targeted synergies, and applied this approach to selectively inhibit the proliferation of cell lines with mutations in genes that are difficult to modulate with small molecules. The approach is based on curve shift analysis, which we demonstrate is a more robust method of determining synergy than combination matrix screening with Bliss-scoring. We show that the MEK inhibitor trametinib is more synergistic in combination with the BRAF inhibitor dabrafenib than with vemurafenib, another BRAF inhibitor. In addition, we show that the combination of MEK and BRAF inhibitors is synergistic in BRAF-mutant melanoma cells, and additive or antagonistic in, respectively, BRAF-wild type melanoma cells and non-malignant fibroblasts. This combination exemplifies that synergistic action of drugs can depend on cancer genotype. Next, we used curve shift analysis to identify new drug combinations that specifically inhibit cancer cell proliferation driven by difficult-to-drug cancer genes. Combination studies were performed with compounds that as single agents showed preference for inhibition of cancer cells with mutations in either the CTNNB1 gene (coding for β-catenin), KRAS, or cancer cells expressing increased copy numbers of MYC. We demonstrate that the Wnt-pathway inhibitor ICG-001 and trametinib acted synergistically in Wnt-pathway-mutant cell lines. The ERBB2 inhibitor TAK-165 was synergistic with trametinib in KRAS-mutant cell lines. The EGFR/ERBB2 inhibitor neratinib acted synergistically with the spindle poison docetaxel and with the Aurora kinase inhibitor GSK-1070916 in cell lines with MYC amplification. Our approach can therefore efficiently discover novel drug combinations that selectively target cancer genes.

Epigenetic reduction of DNA repair in progression to gastrointestinal cancer

Deficiencies in DNA repair due to inherited germ-line mutations in DNA repair genes cause increased risk of gastrointestinal (GI) cancer. In sporadic GI cancers, mutations in DNA repair genes are relatively rare. However, epigenetic alterations that reduce expression of DNA repair genes are frequent in sporadic GI cancers. These epigenetic reductions are also found in field defects that give rise to cancers. Reduced DNA repair likely allows excessive DNA damages to accumulate in somatic cells. Then either inaccurate translesion synthesis past the un-repaired DNA damages or error-prone DNA repair can cause mutations. Erroneous DNA repair can also cause epigenetic alterations (i.e., epimutations, transmitted through multiple replication cycles). Some of these mutations and epimutations may cause progression to cancer. Thus, deficient or absent DNA repair is likely an important underlying cause of cancer. Whole genome sequencing of GI cancers show that between thousands to hundreds of thousands of mutations occur in these cancers. Epimutations that reduce DNA repair gene expression and occur early in progression to GI cancers are a likely source of this high genomic instability. Cancer cells deficient in DNA repair are more vulnerable than normal cells to inactivation by DNA damaging agents. Thus, some of the most clinically effective chemotherapeutic agents in cancer treatment are DNA damaging agents, and their effectiveness often depends on deficient DNA repair in cancer cells. Recently, at least 18 DNA repair proteins, each active in one of six DNA repair pathways, were found to be subject to epigenetic reduction of expression in GI cancers. Different DNA repair pathways repair different types of DNA damage. Evaluation of which DNA repair pathway(s) are deficient in particular types of GI cancer and/or particular patients may prove useful in guiding choice of therapeutic agents in cancer therapy.

Deficient mismatch repair in colorectal cancer: current perspectives on patient management and future directions

Abstract 

Molecular aberrations leading to colorectal cancer are diverse and heterogeneity exists both at a molecular level and in clinical behavior. Defective mismatch repair (dMMR) is a feature of 15% of colorectal cancers. These are hypermutated tumors, mostly right sided and histopathologically elicit a marked immune response. A proportion of these arise due to germline mutation of a mismatch repair gene giving rise to Lynch syndrome, while the majority arise sporadically due to somatic alteration of the MLH1 mismatch repair gene. Although dMMR is associated with an excellent patient prognosis, as tumor stage advances the frequency of dMMR declines and the association with improved prognosis dissipates. It is apparent that dMMR tumors do not represent a unique molecular subset. As the knowledge of the underlying biology evolves, the hope is for individualized therapy that goes well beyond the crude and oversimplified categorization of dMMR versus proficient MMR.

Investigational therapies up to Phase II which target PDGF receptors: potential anti-cancer therapeutics

INTRODUCTION

The platelet-derived growth factor receptor (PDGFR) pathway has important functions in cell growth and, by overexpression or mutation, could also be a driver for tumor development. Moreover, PDGFR is expressed in a tumoral microenvironment and could promote tumorigenesis. With these biological considerations, the PDGFR pathway could be an interesting target for therapeutics. Currently, there are many molecules under development that target the PDGFR pathway in different types of cancer.

AREAS COVERED

In this review, the authors report the different molecules under development, as well as those approved albeit briefly, which inhibit the PDGFR pathway. Furthermore, the authors summarize their specificities, their toxicities, and their development.

EXPERT OPINION

Currently, most PDGFR kinase inhibitors are multikinase inhibitors and therefore do not simply target the PDGFR pathway. The development of more specific PDGFR inhibitors could improve drug efficacy. Moreover, selecting tumors harboring mutations or amplifications of PDGFR could improve outcomes associated with the use of these molecules. The authors believe that new technologies, such as kinome arrays or pharmacologic assays, could be of benefit to understanding resistance mechanisms and develop more selective PDGFR inhibitors.