Integrating genetic approaches into the discovery of anticancer drugs

Synthetic lethal therapies for cancer: what's next after PARP inhibitors?

The genetic concept of synthetic lethality has now been validated clinically through the demonstrated efficacy of poly(ADP-ribose) polymerase (PARP) inhibitors for the treatment of cancers in individuals with germline loss-of-function mutations in either BRCA1 or BRCA2. Three different PARP inhibitors have now been approved for the treatment of patients with BRCA-mutant ovarian cancer and one for those with BRCA-mutant breast cancer; these agents have also shown promising results in patients with BRCA-mutant prostate cancer. Here, we describe a number of other synthetic lethal interactions that have been discovered in cancer. We discuss some of the underlying principles that might increase the likelihood of clinical efficacy and how new computational and experimental approaches are now facilitating the discovery and validation of synthetic lethal interactions. Finally, we make suggestions on possible future directions and challenges facing researchers in this field.

[Searching for essential genes in cancer genomes]

The concept of essential genes, whose loss of functionality leads to cell death, is one of the fundamental concepts of genetics and is important for fundamental and applied research. This field is particularly promising in relation to oncology, since the search for genetic vulnerabilities of cancer cells allows us to identify new potential targets for antitumor therapy. The modern biotechnology capacities allow carrying out large-scale projects for sequencing somatic mutations in tumors, as well as directly interfering the genetic apparatus of cancer cells. They provided accumulation of a considerable body of knowledge about genetic variants and corresponding phenotypic manifestations in tumors. In the near future this knowledge will find application in clinical practice. This review describes the main experimental and computational approaches to the search for essential genes, concentrating on the application of these methods in the field of molecular oncology.

Identification of synthetic lethality based on a functional network by using machine learning algorithms

Synthetic lethality is the synthesis of mutations leading to cell death. Tumor-specific synthetic lethality has been targeted in research to improve cancer therapy. With the advances of techniques in molecular biology, such as RNAi and CRISPR/Cas9 gene editing, efforts have been made to systematically identify synthetic lethal interactions, especially for frequently mutated genes in cancers. However, elucidating the mechanism of synthetic lethality remains a challenge because of the complexity of its influencing conditions. In this study, we proposed a new computational method to identify critical functional features that can accurately predict synthetic lethal interactions. This method incorporates several machine learning algorithms and encodes protein-coding genes by an enrichment system derived from gene ontology terms and Kyoto Encyclopedia of Genes and Genomes pathways to represent their functional features. We built a random forest-based prediction engine by using 2120 selected features and obtained a Matthews correlation coefficient of 0.532. We examined the top 15 features and found that most of them have potential roles in synthetic lethality according to previous studies. These results demonstrate the ability of our proposed method to predict synthetic lethal interactions and provide a basis for further characterization of these particular genetic combinations.

Therapeutic targeting of PGBD5-induced DNA repair dependency in pediatric solid tumors

Despite intense efforts, the cure rates of childhood and adult solid tumors are not satisfactory. Resistance to intensive chemotherapy is common, and targets for molecular therapies are largely undefined. We have found that the majority of childhood solid tumors, including rhabdoid tumors, neuroblastoma, medulloblastoma, and Ewing sarcoma, express an active DNA transposase, PGBD5, that can promote site-specific genomic rearrangements in human cells. Using functional genetic approaches, we discovered that mouse and human cells deficient in nonhomologous end joining (NHEJ) DNA repair cannot tolerate the expression of PGBD5. In a chemical screen of DNA damage signaling inhibitors, we identified AZD6738 as a specific sensitizer of PGBD5-dependent DNA damage and apoptosis. We found that expression of PGBD5, but not its nuclease activity-deficient mutant, was sufficient to induce sensitivity to AZD6738. Depletion of endogenous PGBD5 conferred resistance to AZD6738 in human tumor cells. PGBD5-expressing tumor cells accumulated unrepaired DNA damage in response to AZD6738 treatment and underwent apoptosis in both dividing and G₁-phase cells in the absence of immediate DNA replication stress. Accordingly, AZD6738 exhibited nanomolar potency against most neuroblastoma, medulloblastoma, Ewing sarcoma, and rhabdoid tumor cells tested while sparing nontransformed human and mouse embryonic fibroblasts in vitro. Finally, treatment with AZD6738 induced apoptosis and regression of human neuroblastoma and medulloblastoma tumors engrafted in immunodeficient mice in vivo. This effect was potentiated by combined treatment with cisplatin, including substantial antitumor activity against patient-derived primary neuroblastoma xenografts. These findings delineate a therapeutically actionable synthetic dependency induced in PGBD5-expressing solid tumors.

Harnessing synthetic lethality to predict the response to cancer treatment

While synthetic lethality (SL) holds promise in developing effective cancer therapies, SL candidates found via experimental screens often have limited translational value. Here we present a data-driven approach, ISLE (identification of clinically relevant synthetic lethality), that mines TCGA cohort to identify the most likely clinically relevant SL interactions (cSLi) from a given candidate set of lab-screened SLi. We first validate ISLE via a benchmark of large-scale drug response screens and by predicting drug efficacy in mouse xenograft models. We then experimentally test a select set of predicted cSLi via new screening experiments, validating their predicted context-specific sensitivity in hypoxic vs normoxic conditions and demonstrating cSLi's utility in predicting synergistic drug combinations. We show that cSLi can successfully predict patients' drug treatment response and provide patient stratification signatures. ISLE thus complements existing actionable mutation-based methods for precision cancer therapy, offering an opportunity to expand its scope to the whole genome.

A Novel Use of Olaparib for the Treatment of Metastatic Castration-Recurrent Prostate Cancer

Although mortality from prostate cancer has declined over the past 20 years as a result of early detection and treatment, the 5-year survival rate for men with prostate cancer who develop metastatic disease is only 29%. Current treatment options for metastatic castration-recurrent prostate cancer (mCRPC) are associated with toxicity and a limited durable response; therefore, additional lines of efficacious and minimally toxic therapy are needed. Olaparib, a poly(adenosine 5'-diphosphate) ribose polymerase (PARP) inhibitor, received a U.S. Food and Drug Administration breakthrough therapy designation in January 2016 for the treatment of patients with BRCA1/2 or ATM gene-mutated mCRPC based on results of a compelling phase II trial of olaparib in patients with advanced castration-resistant prostate cancer (TOPARP-A). This study found that men with mCRPC and genetic mutations in DNA damage repair genes had an overall response rate of nearly 90% with olaparib treatment. In this review, we describe current therapies for mCRPC, the rationale for anti-PARP therapies, the pharmacology of olaparib for prostate cancer, clinical trials of olaparib for mCRPC, our clinical experience with olaparib for prostate cancer at a comprehensive cancer center, and future directions of olaparib for the treatment of mCRPC. Olaparib may constitute a promising treatment to prolong survival in patients with mCRPC, with an acceptable adverse effect profile. As the role of PARP inhibition in prostate cancer and other malignancies becomes further elucidated, olaparib may be shown to be beneficial for other patient populations.

The Multiple Myeloma Drug Pipeline-2018: A Review of Small Molecules and Their Therapeutic Targets

Treatment of multiple myeloma (MM), a neoplasm of plasma cells, formerly dependent on alkylating drugs, corticosteroids, and autologous stem cell transplantation, has changed dramatically in the past 20 years because 3 new classes of small molecule drugs (arbitrarily defined as having a molecular weight of < 900 kDa)-immunomodulators, proteasome inhibitors, and histone deacetylase blockers-have been introduced for the disease. Therapeutic options for MM expanded further in 2015 when 2 new monoclonal antibodies (daratumumab and elotuzumab) were approved by the Food and Drug Administration for MM. Although MM remains incurable, the cumulative effect of these advances has resulted in a near-doubling of the 5-year survival rate since the late 1980s. Despite these advances, therapy for MM continues to pose substantial challenges because resistance to therapy frequently develops, and relapse and recurrence are all too common. The present review focused on the pipeline for new small molecules in various stages of development and their associated cellular targets. In addition to newer versions of alkylators, immunomodulators, proteasome inhibitors, and histone deacetylase inhibitors, the present review considered the prospects for adding new classes of small molecules to the MM armamentarium, which offer the potential for oral efficacy, relative simplicity of preparation, and prospects for improvement in the cost-to-benefit ratio. Included are agents that affect myeloma epigenetics and the ubiquitination-proteasome system and the unfolded protein response, apoptotic mechanisms, chromosomal abnormalities, nuclear protein transport, and various kinases involved in cellular signaling pathways.

Synthetic Lethality-based Identification of Targets for Anticancer Drugs in the Human Signaling Network

Chemotherapy agents can cause serious adverse effects by attacking both cancer tissues and normal tissues. Therefore, we proposed a synthetic lethality (SL) concept-based computational method to identify specific anticancer drug targets. First, a 3-step screening strategy (network-based, frequency-based and function-based screening) was proposed to identify the SL gene pairs by mining 697 cancer genes and the human signaling network, which had 6306 proteins and 62937 protein-protein interactions. The network-based screening was composed of a stability score constructed using a network information centrality measure (the average shortest path length) and the distance-based screening between the cancer gene and the non-cancer gene. Then, the non-cancer genes were extracted and annotated using drug-target interaction and drug description information to obtain potential anticancer drug targets. Finally, the human SL data in SynLethDB, the existing drug sensitivity data and text-mining were utilized for target validation. We successfully identified 2555 SL gene pairs and 57 potential anticancer drug targets. Among them, CDK1, CDK2, PLK1 and WEE1 were verified by all three aspects and could be preferentially used in specific targeted therapy in the future.

Elucidating drug targets and mechanisms of action by genetic screens in mammalian cells

Phenotypic screening is a powerful approach to discover small molecules with desired effects on biological systems, which can then be developed into therapeutic drugs. The identification of the target and mechanism of action of compounds discovered in phenotypic screens remains a major challenge. This feature article describes the use of genetic tools to reveal drug targets and mechanisms in mammalian cells. Until recently, RNA interference was the method of choice for such studies. Here, we highlight very recent additions to the genetic toolkit in mammalian cells, including CRISPR, CRISPR interference, and CRISPR activation, and illustrate their usefulness for drug target identification.

Cutting down the time to identify challenging tumor therapeutic targets and drug combinations using synthetic lethal approaches

Cancer drug discoverers and developers are blessed and cursed with a plethora of drug targets in the tumor cells themselves and the surrounding stromal elements. This bounty of targets has, at least in part, inspired the rapid increase in the number of clinically available small-molecule, biological, and cellular therapies for solid and hematological malignancies. Among the most challenging questions in cancer therapeutics, especially for small molecules, is how to approach loss-of-function gene mutations or deletions that encode tumor suppressors. A second mounting question is what are the optimal drug combinations. This article will briefly review the recent advances in exploiting in vitro and in vivo synthetic lethal screens to expose cancer pharmacological targets with the goal of developing new drug combinations.

Toward an integrated map of genetic interactions in cancer cells

Cancer genomes often harbor hundreds of molecular aberrations. Such genetic variants can be drivers or passengers of tumorigenesis and create vulnerabilities for potential therapeutic exploitation. To identify genotype-dependent vulnerabilities, forward genetic screens in different genetic backgrounds have been conducted. We devised MINGLE, a computational framework to integrate CRISPR/Cas9 screens originating from different libraries building on approaches pioneered for genetic network discovery in model organisms. We applied this method to integrate and analyze data from 85 CRISPR/Cas9 screens in human cancer cells combining functional data with information on genetic variants to explore more than 2.1 million gene-background relationships. In addition to known dependencies, we identified new genotype-specific vulnerabilities of cancer cells. Experimental validation of predicted vulnerabilities identified GANAB and PRKCSH as new positive regulators of Wnt/β-catenin signaling. By clustering genes with similar genetic interaction profiles, we drew the largest genetic network in cancer cells to date. Our scalable approach highlights how diverse genetic screens can be integrated to systematically build informative maps of genetic interactions in cancer, which can grow dynamically as more data are included.

CRISPR Approaches to Small Molecule Target Identification

A long-standing challenge in drug development is the identification of the mechanisms of action of small molecules with therapeutic potential. A number of methods have been developed to address this challenge, each with inherent strengths and limitations. We here provide a brief review of these methods with a focus on chemical-genetic methods that are based on systematically profiling the effects of genetic perturbations on drug sensitivity. In particular, application of these methods to mammalian systems has been facilitated by the recent advent of CRISPR-based approaches, which enable one to readily repress, induce, or delete a given gene and determine the resulting effects on drug sensitivity.

Ranking novel cancer driving synthetic lethal gene pairs using TCGA data

Synthetic lethality (SL) has emerged as a promising approach to cancer therapy. In contrast to the costly and labour-intensive genome-wide siRNA or CRISPR-based human cell line screening approaches, computational approaches to prioritize potential synthetic lethality pairs for further experimental validation represent an attractive alternative. In this study, we propose an efficient and comprehensive in-silico pipeline to rank novel SL gene pairs by mining vast amounts of accumulated tumor high-throughput sequencing data in The Cancer Genome Atlas (TCGA), coupled with other protein interaction networks and cell line information. Our pipeline integrates three significant features, including mutation coverage in TCGA, driver mutation probability and the quantified cancer network information centrality, into a ranking model for SL gene pair identification, which is presented as the first learning-based method for SL identification. As a result, 107 potential SL gene pairs were obtained from the top 10 results covering 11 cancers. Functional analysis of these genes indicated that several promising pathways were identified, including the DNA repair related Fanconi Anemia pathway and HIF-1 signaling pathway. In addition, 4 SL pairs, mTOR-TP53, VEGFR2-TP53, EGFR-TP53, ATM-PRKCA, were validated using drug sensitivity information in the cancer cell line databases CCLE or NCI60. Interestingly, significant differences in the cell growth of mTOR siRNA or EGFR siRNA knock-down were detected between cancer cells with wild type TP53 and mutant TP53. Our study indicates that the pre-screening of potential SL gene pairs based on the large genomics data repertoire of tumor tissues and cancer cell lines could substantially expedite the identification of synthetic lethal gene pairs for cancer therapy.

A High-Resolution Genome-Wide CRISPR/Cas9 Viability Screen Reveals Structural Features and Contextual Diversity of the Human Cell-Essential Proteome

To interrogate genes essential for cell growth, proliferation and survival in human cells, we carried out a genome-wide clustered regularly interspaced short palindromic repeat (CRISPR)/Cas9 screen in a B-cell lymphoma line using a custom extended-knockout (EKO) library of 278,754 single-guide RNAs (sgRNAs) that targeted 19,084 RefSeq genes, 20,852 alternatively spliced exons, and 3,872 hypothetical genes. A new statistical analysis tool called robust analytics and normalization for knockout screens (RANKS) identified 2,280 essential genes, 234 of which were unique. Individual essential genes were validated experimentally and linked to ribosome biogenesis and stress responses. Essential genes exhibited a bimodal distribution across 10 different cell lines, consistent with a continuous variation in essentiality as a function of cell type. Genes essential in more lines had more severe fitness defects and encoded the evolutionarily conserved structural cores of protein complexes, whereas genes essential in fewer lines formed context-specific modules and encoded subunits at the periphery of essential complexes. The essentiality of individual protein residues across the proteome correlated with evolutionary conservation, structural burial, modular domains, and protein interaction interfaces. Many alternatively spliced exons in essential genes were dispensable and were enriched for disordered regions. Fitness defects were observed for 44 newly evolved hypothetical reading frames. These results illuminate the contextual nature and evolution of essential gene functions in human cells.

Investigating BRCA Mutations: A Breakthrough in Precision Medicine of Castration-Resistant Prostate Cancer

Despite the development of novel effective therapeutic strategies, metastatic castration-resistant prostate cancer (mCRPC) remains a disease with a lethal course and a high biological and molecular heterogeneity. To date, germline mutations in the BRCA gene represent one of the main risk factors for developing prostate cancer, with a strong association with aggressive phenotype and poor clinical outcomes. A better understanding of the genomic landscape of prostate cancer has strengthened the idea that "synthetic lethality" of this disease might be useful in cancer-drug discovery, focusing on agents such as platinum compounds and poly (adenosine diphosphate [ADP]-ribose) polymerase inhibitors (PARPi). In this review, we summarize the main data available on BRCA mutations and discuss the clinical implications of these genomic aberrations in the management of prostate cancer, stressing the need to identify prognostic and predictive biomarkers and to deeply understand the mechanisms of treatment resistance, in order to maximize personalized medicine protocols and therefore clinical benefit.

Precision Oncology: The Road Ahead

Current efforts in precision oncology largely focus on the benefit of genomics-guided therapy. Yet, advances in sequencing techniques provide an unprecedented view of the complex genetic and nongenetic heterogeneity within individual tumors. Herein, we outline the benefits of integrating genomic and transcriptomic analyses for advanced precision oncology. We summarize relevant computational approaches to detect novel drivers and genetic vulnerabilities, suitable for therapeutic exploration. Clinically relevant platforms to functionally test predicted drugs/drug combinations for individual patients are reviewed. Finally, we highlight the technological advances in single cell analysis of tumor specimens. These may ultimately lead to the development of next-generation cancer drugs, capable of tackling the hurdles imposed by genetic and phenotypic heterogeneity on current anticancer therapies.

Next-generation Sequencing-based genomic profiling: Fostering innovation in cancer care?

OBJECTIVES

With the development of next-generation sequencing (NGS) technologies, DNA sequencing has been increasingly utilized in clinical practice. Our goal was to investigate the impact of genomic evaluation on treatment decisions for heavily pretreated patients with metastatic cancer.

METHODS

We analyzed metastatic cancer patients from a single institution whose cancers had progressed after all available standard-of-care therapies and whose tumors underwent next-generation sequencing analysis. We determined the percentage of patients who received any therapy directed by the test, and its efficacy.

RESULTS

From July 2013 to December 2015, 185 consecutive patients were tested using a commercially available next-generation sequencing-based test, and 157 patients were eligible. Sixty-six patients (42.0%) were female, and 91 (58.0%) were male. The mean age at diagnosis was 52.2 years, and the mean number of pre-test lines of systemic treatment was 2.7. One hundred and seventy-seven patients (95.6%) had at least one identified gene alteration. Twenty-four patients (15.2%) underwent systemic treatment directed by the test result. Of these, one patient had a complete response, four (16.7%) had partial responses, two (8.3%) had stable disease, and 17 (70.8%) had disease progression as the best result. The median progression-free survival time with matched therapy was 1.6 months, and the median overall survival was 10 months.

CONCLUSION

We identified a high prevalence of gene alterations using an next-generation sequencing test. Although some benefit was associated with the matched therapy, most of the patients had disease progression as the best response, indicating the limited biological potential and unclear clinical relevance of this practice.

Computational Approaches to Identify Genetic Interactions for Cancer Therapeutics

The development of improved cancer therapies is frequently cited as an urgent unmet medical need. Here we describe how genetic interactions are being therapeutically exploited to identify novel targeted treatments for cancer. We discuss the current methodologies that use 'omics data to identify genetic interactions, in particular focusing on synthetic sickness lethality (SSL) and synthetic dosage lethality (SDL). We describe the experimental and computational approaches undertaken both in humans and model organisms to identify these interactions. Finally we discuss some of the identified targets with licensed drugs, inhibitors in clinical trials or with compounds under development.

Small-Molecule Inhibitors Targeting DNA Repair and DNA Repair Deficiency in Research and Cancer Therapy

To maintain stable genomes and to avoid cancer and aging, cells need to repair a multitude of deleterious DNA lesions, which arise constantly in every cell. Processes that support genome integrity in normal cells, however, allow cancer cells to develop resistance to radiation and DNA-damaging chemotherapeutics. Chemical inhibition of the key DNA repair proteins and pharmacologically induced synthetic lethality have become instrumental in both dissecting the complex DNA repair networks and as promising anticancer agents. The difficulty in capitalizing on synthetically lethal interactions in cancer cells is that many potential targets do not possess well-defined small-molecule binding determinates. In this review, we discuss several successful campaigns to identify and leverage small-molecule inhibitors of the DNA repair proteins, from PARP1, a paradigm case for clinically successful small-molecule inhibitors, to coveted new targets, such as RAD51 recombinase, RAD52 DNA repair protein, MRE11 nuclease, and WRN DNA helicase.

Genome-Wide RNA Interference: Functional Genomics in the Postgenomics Era

This introduction briefly describes the types of RNAi libraries (both shRNA-based and double-stranded siRNA-based) that are available for understanding diverse biological questions and then discusses recent advances in RNAi screening methodologies in mouse, rat, humans, Drosophila, and worms.

Changes in gene expression variability reveal a stable synthetic lethal interaction network in BRCA2-ovarian cancers

Synthetic lethal interactions (SLIs) are robust mechanisms that provide cells with the ability to remain viable despite having mutations in genes critical to the DNA damage response, a core cellular process. Studies in model organisms such as S. cerevisiae showed that thousands of genes important in maintaining DNA integrity cooperated in a SLI network. Two genes participate in a SLI when a mutation in one gene has no effect on the cell, but mutations in both interacting genes are lethal. Furthermore in C. elegans, a mutation in a critical gene that is important for development induced a change in expression variability in the synthetic lethal interactor. In cancer, targeting SLIs shows promise in selectively killing cancer cells. For example, targeting PARP1 is an effective treatment for BRCA1/2- breast and ovarian cancers. Although PARP1 is already identified as having a SLI with BRCA1/2-, computationally searching for other genes that cooperate in the SLI network could highlight genes that may have promise for being a cancer-specific drug target. Using RNA sequencing data for ovarian cancer patients with BRCA2 mutations and the R Bioconductor package pathVar, we showed that genes whose expression changes to an invariant, stable expression state are likely candidates for SLIs with BRCA2. Our results highlight the interactions between the genes with predicted SLIs and protein-coding genes that are functionally important in the DNA damage response. The method of analyzing expression variability to computationally identify genes with SLIs can be applied to query SLIs in other tumor types.

Bioinformatics in translational drug discovery

Bioinformatics approaches are becoming ever more essential in translational drug discovery both in academia and within the pharmaceutical industry. Computational exploitation of the increasing volumes of data generated during all phases of drug discovery is enabling key challenges of the process to be addressed. Here, we highlight some of the areas in which bioinformatics resources and methods are being developed to support the drug discovery pipeline. These include the creation of large data warehouses, bioinformatics algorithms to analyse 'big data' that identify novel drug targets and/or biomarkers, programs to assess the tractability of targets, and prediction of repositioning opportunities that use licensed drugs to treat additional indications.

Epistasis in genomic and survival data of cancer patients

Cancer aggressiveness and its effect on patient survival depends on mutations in the tumor genome. Epistatic interactions between the mutated genes may guide the choice of anticancer therapy and set predictive factors of its success. Inhibitors targeting synthetic lethal partners of genes mutated in tumors are already utilized for efficient and specific treatment in the clinic. The space of possible epistatic interactions, however, is overwhelming, and computational methods are needed to limit the experimental effort of validating the interactions for therapy and characterizing their biomarkers. Here, we introduce SurvLRT, a statistical likelihood ratio test for identifying epistatic gene pairs and triplets from cancer patient genomic and survival data. Compared to established approaches, SurvLRT performed favorable in predicting known, experimentally verified synthetic lethal partners of PARP1 from TCGA data. Our approach is the first to test for epistasis between triplets of genes to identify biomarkers of synthetic lethality-based therapy. SurvLRT proved successful in identifying the known gene TP53BP1 as the biomarker of success of the therapy targeting PARP in BRCA1 deficient tumors. Search for other biomarkers for the same interaction revealed a region whose deletion was a more significant biomarker than deletion of TP53BP1. With the ability to detect not only pairwise but twelve different types of triple epistasis, applicability of SurvLRT goes beyond cancer therapy, to the level of characterization of shapes of fitness landscapes.

Genomic alterations in tumors affect the fitness of tumor cells, controlling how well they replicate and survive compared to other cells. The landscape of tumor fitness is shaped by epistasis. Epistasis occurs when the contribution of gene alterations to the total fitness is non-linear. The type of epistatic genetic interactions with great potential for cancer therapy is synthetic lethality. Inhibitors targeting synthetic lethal partners of genes mutated in tumors can selectively kill tumor and not normal cells. Therapy based on synthetic lethality is, however, context dependent, and it is crucial to identify its biomarkers. Unfortunately, the space of possible interactions and their biomarkers is overwhelming for experimental validation. Computational pre-selection methods are required to limit the experimental effort. Here, we introduce a statistical approach called SurvLRT, for the identification of epistatic gene pairs and triplets based on patient genomic and survival data. First, we show that using SurvLRT, we can deliver synthetic lethal interactions of pairs of genes that are specific to cancer. Second, we demonstrate the applicability of SurvLRT to identify biomarkers for synthetic lethality, such as mutational status of other genes that can alleviate the synthetic effect.

Synthetic essentiality: Targeting tumor suppressor deficiencies in cancer

In this review, we summarize recent work exploring a novel conceptual approach termed "synthetic essentiality" as a means for targeting specific tumor suppressor gene deficiencies in cancer. With the aid of extensive publically available cancer genome and clinical databases, "synthetic essentiality" could be utilized to identify synthetic essential genes, which might be occasionally deleted in some cancers but almost always retained in the context of a specific tumor suppressor deficiency. Synthetic essentiality expands the existing concepts for therapeutic strategies, including oncogene addiction, tumor maintenance, synthetic, and collateral lethality, to provide a framework for the discovery of cancer-specific vulnerabilities. Enabled by ever-expanding large-scale genome datasets and genome-scale functional screens, the "synthetic essentiality" framework provides an avenue for the identification of context-specific therapeutic targets and development of patient responder hypotheses for novel and existing therapies.

Repurposing DNA repair factors to eradicate tumor cells upon radiotherapy

Cancer is the leading cause of death worldwide. Almost 50% of all cancer patients undergo radiation therapy (RT) during treatment, with varying success. The main goal of RT is to kill tumor cells by damaging their DNA irreversibly while sparing the surrounding normal tissue. The outcome of RT is often determined by how tumors recognize and repair their damaged DNA. A growing body of evidence suggests that tumors often show abnormal expression of DNA double-strand break (DSB) repair genes that are absent from normal cells. Defects in a specific DNA repair pathway make tumor cells overly dependent on alternative or backup pathways to repair their damaged DNA. These tumor cell-specific abnormalities in the DNA damage response (DDR) machinery can potentially be used as biomarkers for treatment outcomes or as targets for sensitization to ionizing radiation (IR). An improved understanding of genetic or epigenetic alterations in the DNA repair pathways specific to cancer cells has paved the way for new treatments that combine pharmacological exploitation of tumor-specific molecular vulnerabilities with IR. Inhibiting DNA repair pathways has the potential to greatly enhance the therapeutic ratio of RT. In this review, we will discuss DNA repair pathways in active cells and how these pathways are deregulated in tumors. We will also describe the impact of targeting cancer-specific aberrations in the DDR as a treatment strategy to improve the efficacy of RT. Finally, we will address the current roadblocks and future prospects of these approaches.

Synthetic lethality and cancer

A synthetic lethal interaction occurs between two genes when the perturbation of either gene alone is viable but the perturbation of both genes simultaneously results in the loss of viability. Key to exploiting synthetic lethality in cancer treatment are the identification and the mechanistic characterization of robust synthetic lethal genetic interactions. Advances in next-generation sequencing technologies are enabling the identification of hundreds of tumour-specific mutations and alterations in gene expression that could be targeted by a synthetic lethality approach. The translation of synthetic lethality to therapy will be assisted by the synthesis of genetic interaction data from model organisms, tumour genomes and human cell lines.

'Big data' approaches for novel anti-cancer drug discovery

INTRODUCTION

The development of improved cancer therapies is frequently cited as an urgent unmet medical need. Recent advances in platform technologies and the increasing availability of biological 'big data' are providing an unparalleled opportunity to systematically identify the key genes and pathways involved in tumorigenesis. The discoveries made using these new technologies may lead to novel therapeutic interventions. Areas covered: The authors discuss the current approaches that use 'big data' to identify cancer drivers. These approaches include the analysis of genomic sequencing data, pathway data, multi-platform data, identifying genetic interactions such as synthetic lethality and using cell line data. They review how big data is being used to identify novel drug targets. The authors then provide an overview of the available data repositories and tools being used at the forefront of cancer drug discovery. Expert opinion: Targeted therapies based on the genomic events driving the tumour will eventually inform treatment protocols. However, using a tailored approach to treat all tumour patients may require developing a large repertoire of targeted drugs.

Therapeutic targeting and patient selection for cancers with homologous recombination defects

INTRODUCTION

DNA double-strand breaks (DSBs) are toxic DNA lesions that can be repaired by non-homologous end-joining (NHEJ) or homologous recombination (HR). Mutations in HR genes elicit a predisposition to cancer; yet, they also result in increased sensitivity to certain DNA damaging agents and poly (ADP-ribose) polymerase (PARP) inhibitors. To optimally implement PARP inhibitor treatment, it is important that patients with HR-deficient tumors are adequately selected. Areas covered: Herein, the authors describe the HR pathway mechanistically and review the treatment of HR-deficient cancers, with a specific focus on PARP inhibition for BRCA1/2-mutated breast and ovarian cancer. In addition, mechanisms of acquired PARP inhibitor resistance are discussed. Furthermore, combination therapies with PARP inhibitors are reviewed, in the context of both HR-deficient and HR-proficient tumors and methods for proper patient selection are also discussed. Expert opinion: Currently, only patients with germline or somatic BRCA1/2 mutations are eligible for PARP inhibitor treatment and only a proportion of patients respond. Patients with HR-deficient tumors caused by other (epi)genetic events may also benefit from PARP inhibitor treatment. Ideally, selection of eligible patients for PARP inhibitor treatment include a functional HR read-out, in which cancer cells are interrogated for their ability to perform HR repair and maintain replication fork stability.

Synthetic lethal targeting of RNF20 through PARP1 silencing and inhibition

PURPOSE

The identification of novel therapeutic targets that exploit the aberrant genetics driving oncogenesis is critical to better combat cancer. RNF20 is somatically altered in numerous cancers, and its diminished expression drives genome instability, a driving factor of oncogenesis. Accordingly, we sought to determine whether PARP1 silencing and inhibition could preferentially kill RNF20-deficient cells using a synthetic lethal strategy.

METHODS

RNF20 and PARP1 were silenced using RNAi-based approaches. Direct synthetic lethal tests were performed by silencing RNF20 with and without PARP1 and the impact on cell numbers was evaluated using semi-quantitative imaging microscopy. Next, Olaparib and BMN673 (PARP1 inhibitors) were evaluated for their ability to induce preferential killing in RNF20 silenced cells, while real-time cell analyses were used to distinguish cell cytotoxicity from cell cycle arrest. Finally, quantitative imaging microscopy was employed to evaluate marks associated with DNA double-strand breaks (γ-H2AX) and apoptosis (cleaved Caspase-3).

RESULTS

We found that PARP1 silencing resulted in a decrease in number of RNF20 silenced cells relative to controls. We further found that Olaparib and BMN673 treatments also resulted in fewer RNF20 silenced cells relative to controls. Finally, we found by quantitative imaging microscopy that RNF20 silenced cells treated with BMN673 exhibited significant increases in γ-H2AX and cleaved Caspase-3, suggesting that these treatments induce DNA double-strand breaks that are not adequately repaired within RNF20-silenced cells.

CONCLUSIONS

Collectively, our data indicate that RNF20 and PARP1 are synthetic lethal interactors, suggesting that cancers with diminished RNF20 expression and/or function may be susceptible to PARP1 inhibitors.

The enigmatic oncogene and tumor suppressor-like properties of RAD54B: Insights into genome instability and cancer

One of the major challenges to the cell is to ensure genome stability, which can be compromised through endogenous errors or exogenous DNA damaging agents, such as ionizing radiation or common chemotherapeutic agents. To maintain genome stability the cell has a multifaceted line of defense, including cell cycle checkpoints and DNA damage repair pathways. RAD54B is involved in many of these pathways and thus exhibits a role in maintaining and repairing genome stability following DNA damage. RAD54B is involved in cell cycle regulation after DNA damage and participates in homologous recombinational repair, which ensures the precise repair of the most deleterious DNA lesions, double-stranded breaks. This review focuses on structural aspects of RAD54B, molecular functions associated with its cellular roles in preventing genome instability, and how aberrant function contributes to oncogenesis. By understanding how aberrant RAD54B expression and/or function can contribute to oncogenesis, novel therapeutic approaches that specifically exploit these aberrant genetics are now being explored for precision medicine targeting. RAD54B represents an ideal candidate for synthetic genetic therapeutic approaches (synthetic dosage lethality or synthetic lethality), which are designed to target the specific genetics associated with cancer formation. These therapeutic approaches represent a precision-based approach, which is ideal as we are now entering the era of precision medicine.

The emerging role of homologous recombination repair and PARP inhibitors in genitourinary malignancies

As cells age and are exposed to genotoxic stress, preservation of the genomic code requires multiple DNA repair pathways to remove single-strand or double-strand breaks. Loss of function somatic genomic aberrations or germline deficiency in genes involved in DNA repair can result in acute cell death or, after a latency period, cellular transformation. Therapeutic exploitation of DNA repair by inhibition of poly (adenosine diphosphate [ADP]) ribose polymerases (PARP), a family of enzymes involved in the repair of single-strand and in some cases double-strand breaks, has become a novel cancer treatment. Although the application of PARP inhibitors (PARPis) initially focused on tumors with BRCA1 or BRCA2 deficiencies, synthetic susceptibilities to PARPis have been expanded due to the identification of tumors with mutations pathways involved in DNA damage repair, in particular those that repair double-strand breaks using homologous recombination (HR). There is an increasing appreciation that genitourinary (GU) malignancies, including bladder cancer and especially prostate cancer, contain subsets of patients with germline and somatic alterations in HR genes that may reflect an increased response to PARPis. In this review, the authors describe the mechanisms and rationale of the use of PARPis in patients with GU cancers, summarize previously reported preclinical and clinical trials, and identify ongoing trials to determine how PARPis and strategies targeted at HR repair can have widespread application in patients with GU cancers. Cancer 2017;123:1912-1924. © 2017 American Cancer Society.

Unraveling new functions of superoxide dismutase using yeast model system: Beyond its conventional role in superoxide radical scavenging

To deal with chemically reactive oxygen molecules constantly threatening aerobic life, cells are readily equipped with elaborate biological antioxidant systems. Superoxide dismutase is a metalloenzyme catalytically eliminating superoxide radical as a first-line defense mechanism against oxidative stress. Multiple different SOD isoforms have been developed throughout evolution to play distinct roles in separate subcellular compartments. SOD is not essential for viability of most aerobic organisms and intriguingly found even in strictly anaerobic bacteria. Sod1 has recently been known to play important roles as a nuclear transcription factor, an RNA binding protein, a synthetic lethal interactor, and a signal modulator in glucose metabolism, most of which are independent of its canonical function as an antioxidant enzyme. In this review, recent advances in understanding the unconventional role of Sod1 are highlighted and discussed with an emphasis on its genetic crosstalk with DNA damage repair/checkpoint pathways. The budding yeast Saccharomyces cerevisiae has been successfully used as an efficient tool and a model organism to investigate a number of novel functions of Sod1.

A global genetic interaction network maps a wiring diagram of cellular function

We generated a global genetic interaction network for Saccharomyces cerevisiae, constructing more than 23 million double mutants, identifying about 550,000 negative and about 350,000 positive genetic interactions. This comprehensive network maps genetic interactions for essential gene pairs, highlighting essential genes as densely connected hubs. Genetic interaction profiles enabled assembly of a hierarchical model of cell function, including modules corresponding to protein complexes and pathways, biological processes, and cellular compartments. Negative interactions connected functionally related genes, mapped core bioprocesses, and identified pleiotropic genes, whereas positive interactions often mapped general regulatory connections among gene pairs, rather than shared functionality. The global network illustrates how coherent sets of genetic interactions connect protein complex and pathway modules to map a functional wiring diagram of the cell.

Epistasis and the Evolution of Antimicrobial Resistance

The fitness effects of a mutation can depend, sometimes dramatically, on genetic background; this phenomenon is often referred to as “epistasis.” Epistasis can have important practical consequences in the context of antimicrobial resistance (AMR). For example, genetic background plays an important role in determining the costs of resistance, and hence in whether resistance will persist in the absence of antibiotic pressure. Furthermore, interactions between resistance mutations can have important implications for the evolution of multi-drug resistance. I argue that there is a need to better characterize the extent and nature of epistasis for mutations and horizontally transferred elements conferring AMR, particularly in clinical contexts. Furthermore, I suggest that epistasis should be an important consideration in attempts to slow or limit the evolution of AMR.

PARP-1/PARP-2 double deficiency in mouse T cells results in faulty immune responses and T lymphomas

The maintenance of T-cell homeostasis must be tightly regulated. Here, we have identified a coordinated role of Poly(ADP-ribose) polymerase-1 (PARP-1) and PARP-2 in maintaining T-lymphocyte number and function. Mice bearing a T-cell specific deficiency of PARP-2 in a PARP-1-deficient background showed defective thymocyte maturation and diminished numbers of peripheral CD4⁺ and CD8⁺ T-cells. Meanwhile, peripheral T-cell number was not affected in single PARP-1 or PARP-2-deficient mice. T-cell lymphopenia was associated with dampened in vivo immune responses to synthetic T-dependent antigens and virus, increased DNA damage and T-cell death. Moreover, double-deficiency in PARP-1/PARP-2 in T-cells led to highly aggressive T-cell lymphomas with long latency. Our findings establish a coordinated role of PARP-1 and PARP-2 in T-cell homeostasis that might impact on the development of PARP-centred therapies.

Synthetic essentiality of chromatin remodelling factor CHD1 in PTEN-deficient cancer

Synthetic lethality and collateral lethality are two well-validated conceptual strategies for identifying therapeutic targets in cancers with tumour-suppressor gene deletions. Here, we explore an approach to identify potential synthetic-lethal interactions by screening mutually exclusive deletion patterns in cancer genomes. We sought to identify 'synthetic-essential' genes: those that are occasionally deleted in some cancers but are almost always retained in the context of a specific tumour-suppressor deficiency. We also posited that such synthetic-essential genes would be therapeutic targets in cancers that harbour specific tumour-suppressor deficiencies. In addition to known synthetic-lethal interactions, this approach uncovered the chromatin helicase DNA-binding factor CHD1 as a putative synthetic-essential gene in PTEN-deficient cancers. In PTEN-deficient prostate and breast cancers, CHD1 depletion profoundly and specifically suppressed cell proliferation, cell survival and tumorigenic potential. Mechanistically, functional PTEN stimulates the GSK3β-mediated phosphorylation of CHD1 degron domains, which promotes CHD1 degradation via the β-TrCP-mediated ubiquitination-proteasome pathway. Conversely, PTEN deficiency results in stabilization of CHD1, which in turn engages the trimethyl lysine-4 histone H3 modification to activate transcription of the pro-tumorigenic TNF-NF-κB gene network. This study identifies a novel PTEN pathway in cancer and provides a framework for the discovery of 'trackable' targets in cancers that harbour specific tumour-suppressor deficiencies.

PARP Inhibitors in Reproductive System Cancers: Current Use and Developments

The repair of DNA damage is a critical cellular process governed by multiple biochemical pathways that are often found to be defective in cancer cells. The poly(ADP-ribose) polymerase (PARP) family of proteins controls response to single-strand DNA breaks by detecting these damaged sites and recruiting the proper factors for repair. Blocking this pathway forces cells to utilize complementary mechanisms to repair DNA damage. While PARP inhibition may not, in itself, be sufficient to cause tumor cell death, inhibition of DNA repair with PARP inhibitors is an effective cytotoxic strategy when it is used in patients who carry other defective DNA-repair mechanisms, such as mutations in the genes BRCA 1 and 2. This discovery has supported the development of PARP inhibitors (PARPi), agents that have proven effective against various types of tumors that carry BRCA mutations. With the application of next-generation sequencing of tumors, there is increased interest in looking beyond BRCA mutations to identify genetic and epigenetic aberrations that might lead to similar defects in DNA repair, conferring susceptibility to PARP inhibition. Identification of these genetic lesions and the development of screening assays for their detection may allow for the selection of patients most likely to respond to this class of anticancer agents. This article provides an overview of clinical trial results obtained with PARPi and describes the companion diagnostic assays being established for patient selection. In addition, we review known mechanisms for resistance to PARPi and potential strategies for combining these agents with other types of therapy.

Cancer genomics guide clinical practice in personalized medicine

Targeted therapies have revolutionized the treatment of many cancers. Widely developed over the last decade, this new concept of precision medicine relies on the use of genomic technologies to analyze tumor samples in order to identify actionable targets and biomarkers of resistance. The goal is to optimize treatment by identifying which therapeutic approach is best for each patient, i.e. the treatment that is effective, has minimal adverse effects, and avoids unnecessary intervention and cost. The purpose of this review is to highlight, using a few seminal examples of therapeutic targets, the important contribution of appropriate analysis of key oncogenes or driver genes in making clinical decisions. Cancer genomics is now an indispensable part of clinical management. Furthermore, the development of next generation sequencing (NGS) will enable exploration of more and more genes of interest, leading to new treatment options for personalized medicine.

New Targeted Agents in Gynecologic Cancers: Synthetic Lethality, Homologous Recombination Deficiency, and PARP Inhibitors

OPINION STATEMENT

Inhibitors of poly (ADP-ribose) polymerase (PARP) have emerged as a new class of anti-cancer drugs, specifically for malignancies bearing aberrations of the homologous recombination pathway, like those with mutations in the BRCA 1 and BRCA 2 genes. Olaparib, a potent PARP1 and PARP2 inhibitor, has been shown to significantly increase progression-free survival (PFS) in women with recurrent ovarian cancer related to a germline BRCA mutation and is currently approved fourth-line treatment in these patients. PARP inhibitors (PARPi) target the genetic phenomenon known as synthetic lethality to exploit faulty DNA repair mechanisms. While ovarian cancer is enriched with a population of tumors with known homologous recombination defects, investigations are underway to help identify pathways in other gynecologic cancers that may demonstrate susceptibility to PARPi through synthetically lethal mechanisms. The ARIEL2 trial prospectively determined a predictive assay to identify patients with HRD. The future of cancer therapeutics will likely incorporate these HRD assays to determine the best treatment plan for patients. While the role of PARPi is less clear in non-ovarian gynecologic cancers, the discovery of a predictive assay for HRD may open the door for clinical trials in these other gynecologic cancers enriched with patients with HRD. Identification of patients with tumors deficient in homologous repair or have HRD-like behavior moves cancer treatment towards individualized therapies in order to maximize treatment effect and quality of life for women living with gynecologic cancers.

Yap1 and Skn7 genetically interact with Rad51 in response to oxidative stress and DNA double-strand break in Saccharomyces cerevisiae

Reactive oxygen species (ROS)-mediated DNA adducts as well as DNA strand breaks are highly mutagenic leading to genomic instability and tumorigenesis. DNA damage repair pathways and oxidative stress response signaling have been proposed to be highly associated, but the underlying interaction remains unknown. In this study, we employed mutant strains lacking Rad51, the homolog of E. coli RecA recombinase, and Yap1 or Skn7, two major transcription factors responsive to ROS, to examine genetic interactions between double-strand break (DSB) repair proteins and cellular redox regulators in budding yeast Saccharomyces cerevisiae. Abnormal expression of YAP1 or SKN7 aggravated the mutation rate of rad51 mutants and their sensitivity to DSB- or ROS-generating reagents. Rad51 deficiency exacerbated genome instability in the presence of increased levels of ROS, and the accumulation of DSB lesions resulted in elevated intracellular ROS levels. Our findings suggest that evident crosstalk between DSB repair pathways and ROS signaling proteins contributes to cell survival and maintenance of genome integrity in response to genotoxic stress.

Uncovering synthetic lethal interactions for therapeutic targets and predictive markers in lung adenocarcinoma

Two genes are called synthetic lethal (SL) if their simultaneous mutation leads to cell death, but mutation of either individual does not. Targeting SL partners of mutated cancer genes can selectively kill cancer cells, but leave normal cells intact. We present an integrated approach to uncover SL gene pairs as novel therapeutic targets of lung adenocarcinoma (LADC). Of 24 predicted SL pairs, PARP1-TP53 was validated by RNAi knockdown to have synergistic toxicity in H1975 and invasive CL1-5 LADC cells; additionally FEN1-RAD54B, BRCA1-TP53, BRCA2-TP53 and RB1-TP53 were consistent with the literature. While metastasis remains a bottleneck in cancer treatment and inhibitors of PARP1 have been developed, this result may have therapeutic potential for LADC, in which TP53 is commonly mutated. We also demonstrated that silencing PARP1 enhanced the cell death induced by the platinum-based chemotherapy drug carboplatin in lung cancer cells (CL1-5 and H1975). IHC of RAD54B↑, BRCA1↓-RAD54B↑, FEN1(N)↑-RAD54B↑ and PARP1↑-RAD54B↑ were shown to be prognostic markers for 131 Asian LADC patients, and all markers except BRCA1↓-RAD54B↑ were further confirmed by three independent gene expression data sets (a total of 426 patients) including The Cancer Genome Atlas (TCGA) cohort of LADC. Importantly, we identified POLB-TP53 and POLB as predictive markers for the TCGA cohort (230 subjects), independent of age and stage. Thus, POLB and POLB-TP53 may be used to stratify future non-Asian LADC patients for therapeutic strategies.

Drugging the addict: non-oncogene addiction as a target for cancer therapy

Historically, cancers have been treated with chemotherapeutics aimed to have profound effects on tumor cells with only limited effects on normal tissue. This approach was followed by the development of small‐molecule inhibitors that can target oncogenic pathways critical for the survival of tumor cells. The clinical targeting of these so‐called oncogene addictions, however, is in many instances hampered by the outgrowth of resistant clones. More recently, the proper functioning of non‐mutated genes has been shown to enhance the survival of many cancers, a phenomenon called non‐oncogene addiction. In the current review, we will focus on the distinct non‐oncogenic addictions found in cancer cells, including synthetic lethal interactions, the underlying stress phenotypes, and arising therapeutic opportunities.

Synthetic lethality in lung cancer and translation to clinical therapies

Lung cancer is a heterogeneous disease consisting of multiple histological subtypes each driven by unique genetic alterations. Despite the development of targeted therapies that inhibit the oncogenic mutations driving a subset of lung cancer cases, there is a paucity of effective treatments for the majority of lung cancer patients and new strategies are urgently needed. In recent years, the concept of synthetic lethality has been established as an effective approach for discovering novel cancer-specific targets as well as a method to improve the efficacy of existing drugs which provide partial but insufficient benefits for patients. In this review, we discuss the concept of synthetic lethality, the various types of synthetic lethal interactions in the context of oncology and the approaches used to identify these interactions, including recent advances that have transformed the ability to discover novel synthetic lethal combinations on a global scale. Lastly, we describe the specific synthetic lethal interactions identified in lung cancer to date and explore the pharmacological challenges and considerations in translating these discoveries to the clinic.

Chemogenetic profiling identifies RAD17 as synthetically lethal with checkpoint kinase inhibition

Chemical inhibitors of the checkpoint kinases have shown promise in the treatment of cancer, yet their clinical utility may be limited by a lack of molecular biomarkers to identify specific patients most likely to respond to therapy. To this end, we screened 112 known tumor suppressor genes for synthetic lethal interactions with inhibitors of the CHEK1 and CHEK2 checkpoint kinases. We identified eight interactions, including the Replication Factor C (RFC)-related protein RAD17. Clonogenic assays in RAD17 knockdown cell lines identified a substantial shift in sensitivity to checkpoint kinase inhibition (3.5-fold) as compared to RAD17 wild-type. Additional evidence for this interaction was found in a large-scale functional shRNA screen of over 100 genotyped cancer cell lines, in which CHEK1/2 mutant cell lines were unexpectedly sensitive to RAD17 knockdown. This interaction was widely conserved, as we found that RAD17 interacts strongly with checkpoint kinases in the budding yeast Saccharomyces cerevisiae. In the setting of RAD17 knockdown, CHEK1/2 inhibition was found to be synergistic with inhibition of WEE1, another pharmacologically relevant checkpoint kinase. Accumulation of the DNA damage marker γH2AX following chemical inhibition or transient knockdown of CHEK1, CHEK2 or WEE1 was magnified by knockdown of RAD17. Taken together, our data suggest that CHEK1 or WEE1 inhibitors are likely to have greater clinical efficacy in tumors with RAD17 loss-of-function.

Drug-Driven Synthetic Lethality: Bypassing Tumor Cell Genetics with a Combination of AsiDNA and PARP Inhibitors

Purpose: Cancer treatments using tumor defects in DNA repair pathways have shown promising results but are restricted to small subpopulations of patients. The most advanced drugs in this field are PARP inhibitors (PARPi), which trigger synthetic lethality in tumors with homologous recombination (HR) deficiency. Using AsiDNA, an inhibitor of HR and nonhomologous end joining, together with PARPi should allow bypassing the genetic restriction for PARPi efficacy.Experimental Design: We characterized the DNA repair inhibition activity of PARPi (olaparib) and AsiDNA by monitoring repair foci formation and DNA damage. We analyzed the cell survival to standalone and combined treatments of 21 tumor cells and three nontumor cells. In 12 breast cancer (BC) cell lines, correlation with sensitivity to each drug and transcriptome were statistically analyzed to identify resistance pathways.Results: Molecular analyses demonstrate that olaparib and AsiDNA respectively prevent recruitment of XRCC1 and RAD51/53BP1 repair enzymes to damage sites. Combination of both drugs increases the accumulation of unrepaired damage resulting in an increase of cell death in all tumor cells. In contrast, nontumor cells do not show an increase of DNA damage nor lethality. Analysis of multilevel omics data from BC cells highlighted different DNA repair and cell-cycle molecular profiles associated with resistance to AsiDNA or olaparib, rationalizing combined treatment. Treatment synergy was also confirmed with six other PARPi in development.Conclusions: Our results highlight the therapeutic interest of combining AsiDNA and PARPi to recapitulate synthetic lethality in all tumors independently of their HR status. Clin Cancer Res; 23(4); 1001-11. ©2016 AACR.

Panobinostat for the treatment of acute myelogenous leukemia

INTRODUCTION

Therapeutic strategies in patients with acute myeloid leukemia (AML) have not changed significantly over the last decades. Appropriate strategies are ultimately driven by the assessment of patients' fitness to define suitability for intensive induction chemotherapy, which produces high initial remission rates but, increased likelihood of relapse. Old/unfit AML patients still represent an urgent and unmet therapeutic need. Epigenetic deregulation represents a strategic characteristic of AML pathophysiology whereby aberrant gene transcription provides an advantage to leukemic cell survival. Efforts to re-establish impaired epigenetic regulation include hypomethylating agents and histone deacetylase inhibitors (HDACi).

AREAS COVERED

The review discusses the underlying mechanisms leading to disruption of lysine acetyltransferases (KAT or HAT)/deacetylase (KDAC or HDAC) balance and the rationale for using the HDACi panobinostat (LBH-589) in AML.

EXPERT OPINION

Although panobinostat has produced significant results in myeloma, its efficacy remains limited in AML. Panobinostat exerts pleiotropic activity and lack of specificity, which likely contributes to its inadequate safety in elderly AML patients. Phase I-II trials, utilizing panobinostat associated with well-known chemotherapeutic agents are ongoing and combinations with other druggable targets may likely be evaluated in future trials. The clinical use of this HDACi in AML the near future does not appearing promising.

Recent advances in cancer drug discovery targeting RAS

Mutated RAS is present in 30% of human tumors, appearing in 90% of pancreatic, 45% of colon and 35% of lung cancers. These high occurrences make RAS one of the most important drug targets in oncology. Three decades of effort to target RAS have been unsuccessful in generating drug therapies suggesting that it might represent an 'undruggable' target. However, recent reports highlighting new approaches for targeting RAS have uncovered more information on protein structure and identified new binding pockets. Efforts to target the KRAS G12C mutation specifically have shown promising results whereas other approaches have targeted various protein complexes. These advances could lead to development of new effective cancer drugs targeting RAS.