Synthetic lethal approaches for assessing combinatorial efficacy of chemotherapeutic drugs

Collateral lethality: A unique type of synthetic lethality in cancers

Genetic interactions play crucial roles in cell-essential functions. Intrinsic genetic defects in tumors typically involve gain-of- and loss-of-function mutations in tumor suppressor genes (TSGs) and oncogenes, respectively, providing potential antitumor vulnerabilities. Moreover, tumor cells with TSG deficiencies exhibit heightened sensitivity to the inhibition of compensatory pathways. Synthetic and collateral lethality are two strategies used for exploiting novel drug targets in multiple types of cancer. Collateral lethality is a unique type of synthetic lethality that occurs when passenger genes are co-deleted in neighboring TSGs. Although synthetic lethality has already been successfully demonstrated in clinical practice, antitumor therapeutics based on collateral lethality are predominantly still in the preclinical phase. Therefore, screening for potential genetic interactions within the cancer genome has emerged as a promising approach for drug development. Here, the two conceptual therapeutic strategies that involve the deletion or inactivation of cancer-specific TSGs are discussed. Moreover, existing approaches for screening and identifying potential gene partners are also discussed. Particularly, this review highlights the current advances of "collateral lethality" in the preclinical phase and addresses the challenges involved in translating them into therapeutic applications. This review provides insights into these strategies as new opportunities for the development of personalized antitumor therapies.

Machine learning optimized DriverDetect software for high precision prediction of deleterious mutations in human cancers

The detection of cancer-driving mutations is important for understanding cancer pathology and therapeutics development. Prediction tools have been created to streamline the computation process. However, most tools available have heterogeneous sensitivity or specificity. We built a machine learning-derived algorithm, DriverDetect that combines the outputs of seven pre-existing tools to improve the prediction of candidate driver cancer mutations. The algorithm was trained with cancer gene-specific mutation datasets of cancer patients to identify cancer drivers. DriverDetect performed better than the individual tools or their combinations in the validation test. It has the potential to incorporate future novel prediction algorithms and can be retrained with new datasets, offering an expanded application to pan-cancer analysis for cross-cancer study. (115 words).

Advancements and Obstacles of PARP Inhibitors in Gastric Cancer

Gastric cancer (GC) is a common and aggressive cancer of the digestive system, exhibiting high aggressiveness and significant heterogeneity. Despite advancements in improving survival rates over the past few decades, GC continues to carry a worrisome prognosis and notable mortality. As a result, there is an urgent need for novel therapeutic approaches to address GC. Recent targeted sequencing studies have revealed frequent mutations in DNA damage repair (DDR) pathway genes in many GC patients. These mutations lead to an increased reliance on poly (adenosine diphosphate-ribose) polymerase (PARP) for DNA repair, making PARP inhibitors (PARPi) a promising treatment option for GC. This article presents a comprehensive overview of the rationale and development of PARPi, highlighting its progress and challenges in both preclinical and clinical research for treating GC.

A Normalization Protocol Reduces Edge Effect in High-Throughput Analyses of Hydroxyurea Hypersensitivity in Fission Yeast

Edge effect denotes better growth of microbial organisms situated at the edge of the solid agar media. Although the precise reason underlying edge effect is unresolved, it is generally attributed to greater nutrient availability with less competing neighbors at the edge. Nonetheless, edge effect constitutes an unavoidable confounding factor that results in misinterpretation of cell fitness, especially in high-throughput screening experiments widely employed for genome-wide investigation using microbial gene knockout or mutant libraries. Here, we visualize edge effect in high-throughput high-density pinning arrays and report a normalization approach based on colony growth rate to quantify drug (hydroxyurea)-hypersensitivity in fission yeast strains. This normalization procedure improved the accuracy of fitness measurement by compensating cell growth rate discrepancy at different locations on the plate and reducing false-positive and -negative frequencies. Our work thus provides a simple and coding-free solution for a struggling problem in robotics-based high-throughput screening experiments.

Biomedicine Innovations and Its Nanohydrogel Classifications

As one of the most cutting-edge and promising polymer crosslinked network nanoparticle systems. Polymer nano-sized hydrogels (nanogels) have been a hot topic in the biomedical field over the last few decades. Due to their unique characteristics, which include their relatively high drug encapsulation efficiency, ease of preparation, high tunability, low toxicity, high stability in serum and responsive behavior to a range of stimuli to facilitate drug release. Nanogels are thought to be the next generation of drug delivery systems that can completely change the way that drug delivery systems have an impact on patients' lives. Nanogels have demonstrated significant potential in a variety of fields, including chemotherapy, diagnosis, organ targeting, and delivery of bioactive molecules of different dimensions. However, the lack of substantial clinical data from nanogels becomes one of the major barriers to translating the nanogel concept into a practical therapeutic application for many disease conditions. In addition, nanogel safety profiles have been the major concern that hinders it advancement to the clinical trial phase. This review aims to emphasize the unique properties of nanogels as delivery systems for a variety of bioactive molecules over other nano-delivery systems. Also, this review attempts to give insight into the recent progress in nanogels as a carrier in the field of nanomedicine to overcome complex biological barriers. Relevant scientific data and clinical rationale for the development and the potential use of nanogel as a carrier for targeted therapeutic interventions are discussed. Finally, the concluding points of this review highlight the importance of understanding the long-term toxicity profile of nanogel within the biological system to fully understand their biocompatibility.

Rapid-SL identifies synthetic lethal sets with an arbitrary cardinality

The multidrug resistance of numerous pathogenic microorganisms is a serious challenge that raises global healthcare concerns. Multi-target medications and combinatorial therapeutics are much more effective than single-target drugs due to their synergistic impact on the systematic activities of microorganisms. Designing efficient combinatorial therapeutics can benefit from identification of synthetic lethals (SLs). An SL is a set of non-essential targets (i.e., reactions or genes) that prevent the proliferation of a microorganism when they are "knocked out" simultaneously. To facilitate the identification of SLs, we introduce Rapid-SL, a new multimodal implementation of the Fast-SL method, using the depth-first search algorithm. The advantages of Rapid-SL over Fast-SL include: (a) the enumeration of all SLs that have an arbitrary cardinality, (b) a shorter runtime due to search space reduction, (c) embarrassingly parallel computations, and (d) the targeted identification of SLs. Targeted identification is important because the enumeration of higher order SLs demands the examination of too many reaction sets. Accordingly, we present specific applications of Rapid-SL for the efficient targeted identification of SLs. In particular, we found up to 67% of all quadruple SLs by investigating about 1% of the search space. Furthermore, 307 sextuples, 476 septuples, and over 9000 octuples are found for Escherichia coli genome-scale model, iAF1260.

Network Pharmacology Approach for Medicinal Plants: Review and Assessment

Natural products have played a critical role in medicine due to their ability to bind and modulate cellular targets involved in disease. Medicinal plants hold a variety of bioactive scaffolds for the treatment of multiple disorders. The less adverse effects, affordability, and easy accessibility highlight their potential in traditional remedies. Identifying pharmacological targets from active ingredients of medicinal plants has become a hot topic for biomedical research to generate innovative therapies. By developing an unprecedented opportunity for the systematic investigation of traditional medicines, network pharmacology is evolving as a systematic paradigm and becoming a frontier research field of drug discovery and development. The advancement of network pharmacology has opened up new avenues for understanding the complex bioactive components found in various medicinal plants. This study is attributed to a comprehensive summary of network pharmacology based on current research, highlighting various active ingredients, related techniques/tools/databases, and drug discovery and development applications. Moreover, this study would serve as a protocol for discovering novel compounds to explore the full range of biological potential of traditionally used plants. We have attempted to cover this vast topic in the review form. We hope it will serve as a significant pioneer for researchers working with medicinal plants by employing network pharmacology approaches.

Molecular mechanisms in governing genomic stability and tumor suppression by the SETD2 H3K36 methyltransferase

Epigenetic dysregulation is an important contributor to carcinogenesis. This is not surprising, as chromatin-genomic DNA organized around structural histone scaffolding-serves as the template on which occurs essential nuclear processes, such as transcription, DNA replication and DNA repair. Histone H3 lysine 36 (H3K36) methyltransferases, such as the SET-domain 2 protein (SETD2), have emerged as critical tumor suppressors. Previous work on mammalian SETD2 and its counterpart in model organisms, Set2, has highlighted the role of this protein in governing genomic stability through transcriptional elongation and splicing, as well as in DNA damage response processes and cell cycle progression. A compendium of SETD2 mutations have been documented, garnered from sequenced cancer patient genome data, and these findings underscore the cancer-driving properties of SETD2 loss-of-function. In this review, we consolidate the molecular mechanisms regulated by SETD2/Set2 and discuss evidence of its dysregulation in tumorigenesis. Insight into the genetic interactions that exist between SETD2 and various canonical intracellular signaling pathways has not only empowered pharmacological intervention by taking advantage of synthetic lethality but underscores SETD2 as a druggable target for precision cancer therapy.

Dual-target inhibitors of bromodomain and extra-terminal proteins in cancer: A review from medicinal chemistry perspectives

Bromodomain-containing protein 4 (BRD4), as the most studied member of the bromodomain and extra-terminal (BET) family, is a chromatin reader protein interpreting epigenetic codes through binding to acetylated histones and non-histone proteins, thereby regulating diverse cellular processes including cell cycle, cell differentiation, and cell proliferation. As a promising drug target, BRD4 function is closely related to cancer, inflammation, cardiovascular disease, and liver fibrosis. Currently, clinical resistance to BET inhibitors has limited their applications but synergistic antitumor effects have been observed when used in combination with other tumor inhibitors targeting additional cellular components such as PLK1, HDAC, CDK, and PARP1. Therefore, designing dual-target inhibitors of BET bromodomains is a rational strategy in cancer treatment to increase potency and reduce drug resistance. This review summarizes the protein structures and biological functions of BRD4 and discusses recent advances of dual BET inhibitors from a medicinal chemistry perspective. We also discuss the current design and discovery strategies for dual BET inhibitors, providing insight into potential discovery of additional dual-target BET inhibitors.

Clinical Candidates Targeting the ATR-CHK1-WEE1 Axis in Cancer

Selective killing of cancer cells while sparing healthy ones is the principle of the perfect cancer treatment and the primary aim of many oncologists, molecular biologists, and medicinal chemists. To achieve this goal, it is crucial to understand the molecular mechanisms that distinguish cancer cells from healthy ones. Accordingly, several clinical candidates that use particular mutations in cell-cycle progressions have been developed to kill cancer cells. As the majority of cancer cells have defects in G1 control, targeting the subsequent intra‑S or G2/M checkpoints has also been extensively pursued. This review focuses on clinical candidates that target the kinases involved in intra‑S and G2/M checkpoints, namely, ATR, CHK1, and WEE1 inhibitors. It provides insight into their current status and future perspectives for anticancer treatment. Overall, even though CHK1 inhibitors are still far from clinical establishment, promising accomplishments with ATR and WEE1 inhibitors in phase II trials present a positive outlook for patient survival.

Stage-specific protein-domain mutational profile of invasive ductal breast cancer

BACKGROUND

Understanding the mechanisms underlying the malignant progression of cancer cells is crucial for early diagnosis and therapeutic treatment for cancer. Mutational heterogeneity of breast cancer suggests that about a dozen of cancer genes consistently mutate, together with many other genes mutating occasionally, in patients.

METHODS

Using the whole-exome sequences and clinical information of 468 patients in the TCGA project data portal, we analyzed mutated protein domains and signaling pathway alterations in order to understand how infrequent mutations contribute aggregately to tumor progression in different stages.

RESULTS

Our findings suggest that while the spectrum of mutated domains was diverse, mutations were aggregated in Pkinase, Pkinase Tyr, Y-Phosphatase and Src-homology 2 domains, highlighting the genetic heterogeneity in activating the protein tyrosine kinase signaling pathways in invasive ductal breast cancer.

CONCLUSIONS

The study provides new clues to the functional role of infrequent mutations in protein domain regions in different stages for invasive ductal breast cancer, yielding biological insights into metastasis for invasive ductal breast cancer.

cGAS-STING pathway in oncogenesis and cancer therapeutics

The host innate immunity offers the first line of defense against infection. However, recent evidence shows that the host innate immunity is also critical in sensing the presence of cytoplasmic DNA derived from genomic instability events, such as DNA damage and defective cell cycle progression. This is achieved through the cyclic GMP-AMP synthase (cGAS)/Stimulator of interferon (IFN) genes (STING) pathway. Here we discuss recent insights into the regulation of this pathway in cancer immunosurveillance, and the downstream signaling cascades that coordinate immune cell recruitment to the tumor microenvironment to destroy transformed cells through cellular senescence or cell death programs. Its central role in immunosurveillance positions the cGAS-STING pathway as an attractive anti-cancer immunotherapeutic drug target for chemical agonists or vaccine adjuvants and suggests a key node to be targeted in a synthetic lethal approach. We also discuss adaptive mechanisms used by cancer cells to circumvent cGAS-STING signaling and present evidence linking chronic cGAS-STING activation to inflammation-induced carcinogenesis, cautioning against the use of activating the cGAS-STING pathway as an anti-tumor immunotherapy. A deeper mechanistic understanding of the cGAS-STING pathway will aid in the identification of potentially efficacious anti-cancer therapeutic targets.

Blocking Angiopoietin-2 Promotes Vascular Damage and Growth Inhibition in Mouse Tumors Treated with Small Doses of Radiation

Abnormal vasculature in tumors leads to poor tissue perfusion and cytostatic drug delivery. Although drugs inducing vascular normalization, for example, angiopoietin-2 (Ang2)-blocking antibodies, have shown promising results in preclinical tumor models, clinical studies have so far shown only little efficacy. Because Ang2 is known to play a protective role in stressed endothelial cells, we tested here whether Ang2 blocking could enhance radiation-induced tumor vascular damage. Tumor-bearing mice were treated with anti-Ang2 antibodies every 3 or 4 days starting 3 days before 3 × 2 Gy or 4 × 0.5 Gy whole-body or tumor-focused radiation. Combination treatment with anti-Ang2 and radiation improved tumor growth inhibition and extended the survival of mice with melanoma or colorectal tumors. Single-cell RNA-sequencing revealed that Ang2 blocking rescued radiation-induced decreases in T cells and cells of the monocyte/macrophage lineage. In addition, anti-Ang2 enhanced radiation-induced apoptosis in cultured endothelial cells. In vivo, combination treatment decreased tumor vasculature and increased tumor necrosis in comparison with tumors treated with monotherapies. These results suggest that a combination of Ang2-blocking antibodies with radiation increases tumor growth inhibition and extends the survival of tumor-bearing mice. SIGNIFICANCE: These findings offer a preclinical rationale for further testing of the use of radiation in combination with Ang2-blocking antibodies to improve the overall outcome of cancer treatment.

Discovery of ATR kinase inhibitor berzosertib (VX-970, M6620): Clinical candidate for cancer therapy

Chemoresistance, radioresistance, and the challenge of achieving complete resection are major driving forces in the search for more robust and targeted anticancer therapies. Targeting the DNA damage response has recently attracted research interest, as these processes are enhanced in tumour cells. The major replication stress responder is ATM and Rad3-related (ATR) kinase, which is attracting attention worldwide with four drug candidates currently in phase I/II clinical trials. This review addresses a potent and selective small-molecule ATR inhibitor, which is known as VX-970 (also known as berzosertib or M6620), and summarizes the existing preclinical data to provide deep insight regarding its real potential. We also outline the transition from preclinical to clinical studies, as well as its relationships with other clinical candidates (AZD6738, VX-803 [M4344], and BAY1895344). The results suggest that VX-970 is indeed a promising anticancer drug that can be used both as monotherapy and in combination with either chemotherapy or radiotherapy strategies. Based on patient anamnesis and biomarker identification, VX-970 could become a valuable tool for oncologists in the fight against cancer.

Individualized genetic network analysis reveals new therapeutic vulnerabilities in 6,700 cancer genomes

Tumor-specific genomic alterations allow systematic identification of genetic interactions that promote tumorigenesis and tumor vulnerabilities, offering novel strategies for development of targeted therapies for individual patients. We develop an Individualized Network-based Co-Mutation (INCM) methodology by inspecting over 2.5 million nonsynonymous somatic mutations derived from 6,789 tumor exomes across 14 cancer types from The Cancer Genome Atlas. Our INCM analysis reveals a higher genetic interaction burden on the significantly mutated genes, experimentally validated cancer genes, chromosome regulatory factors, and DNA damage repair genes, as compared to human pan-cancer essential genes identified by CRISPR-Cas9 screenings on 324 cancer cell lines. We find that genes involved in the cancer type-specific genetic subnetworks identified by INCM are significantly enriched in established cancer pathways, and the INCM-inferred putative genetic interactions are correlated with patient survival. By analyzing drug pharmacogenomics profiles from the Genomics of Drug Sensitivity in Cancer database, we show that the network-predicted putative genetic interactions (e.g., BRCA2-TP53) are significantly correlated with sensitivity/resistance of multiple therapeutic agents. We experimentally validated that afatinib has the strongest cytotoxic activity on BT474 (IC₅₀ = 55.5 nM, BRCA2 and TP53 co-mutant) compared to MCF7 (IC₅₀ = 7.7 μM, both BRCA2 and TP53 wild type) and MDA-MB-231 (IC₅₀ = 7.9 μM, BRCA2 wild type but TP53 mutant). Finally, drug-target network analysis reveals several potential druggable genetic interactions by targeting tumor vulnerabilities. This study offers a powerful network-based methodology for identification of candidate therapeutic pathways that target tumor vulnerabilities and prioritization of potential pharmacogenomics biomarkers for development of personalized cancer medicine.

Recent efforts to map genetic interactions in tumor cells have suggested that tumor vulnerabilities can be exploited for development of novel targeted therapies. Tumor-specific genomic alterations derived from multi-center cancer genome projects allow identification of genetic interactions that promote tumor vulnerabilities, offering novel strategies for development of targeted cancer therapies. This study develops a novel Individualized Network-based Co-Mutation (termed INCM) methodology for quantifying the putative genetic interactions in cancer. Trained on over 2.5 million nonsynonymous somatic mutations derived from 6,789 tumor exomes across 14 cancer type, we found that genes identified in the cancer type-specific genetic subnetworks were significantly enriched in established cancer pathways. The network-predicted putative genetic interactions are correlated with patient survival. By analyzing drug pharmacogenomics profiles, we showed that the network-predicted putative genetic interactions (e.g., BRCA2-TP53) were significantly correlated with sensitivity/resistance of anticancer drugs (e.g., afatinib) and we experimentally validated it in breast cancer cell lines. Finally, drug-target network analysis reveals several potential druggable genetic interactions (e.g., PIK3CA-PTEN) by targeting tumor vulnerabilities. This study offers a generalizable network-based approach for comprehensive identification of candidate therapeutic pathways that target tumor vulnerabilities and prioritization of potential prognostic and pharmacogenomics biomarkers for development of personalized cancer medicine.

DNA Double Strand Break Repair - Related Synthetic Lethality

Cancer is a heterogeneous disease with a high degree of diversity between and within tumors. Our limited knowledge of their biology results in ineffective treatment. However, personalized approach may represent a milestone in the field of anticancer therapy. It can increase specificity of treatment against tumor initiating cancer stem cells (CSCs) and cancer progenitor cells (CPCs) with minimal effect on normal cells and tissues. Cancerous cells carry multiple genetic and epigenetic aberrations which may disrupt pathways essential for cell survival. Discovery of synthetic lethality has led a new hope of creating effective and personalized antitumor treatment. Synthetic lethality occurs when simultaneous inactivation of two genes or their products causes cell death whereas individual inactivation of either gene is not lethal. The effectiveness of numerous anti-tumor therapies depends on induction of DNA damage therefore tumor cells expressing abnormalities in genes whose products are crucial for DNA repair pathways are promising targets for synthetic lethality. Here, we discuss mechanistic aspects of synthetic lethality in the context of deficiencies in DNA double strand break repair pathways. In addition, we review clinical trials utilizing synthetic lethality interactions and discuss the mechanisms of resistance.

Targeting epigenetics using synthetic lethality in precision medicine

Technological breakthroughs in genomics have had a significant impact on clinical therapy for human diseases, allowing us to use patient genetic differences to guide medical care. The "synthetic lethal approach" leverages on cancer-specific genetic rewiring to deliver a therapeutic regimen that preferentially targets malignant cells while sparing normal cells. The utility of this system is evident in several recent studies, particularly in poor prognosis cancers with loss-of-function mutations that become "treatable" when two otherwise discrete and unrelated genes are targeted simultaneously. This review focuses on the chemotherapeutic targeting of epigenetic alterations in cancer cells and consolidates a network that outlines the interplay between epigenetic and genetic regulators in DNA damage repair. This network consists of numerous synergistically acting relationships that are druggable, even in recalcitrant triple-negative breast cancer. This collective knowledge points to the dawn of a new era of personalized medicine.

SAHA and cisplatin sensitize gastric cancer cells to doxorubicin by induction of DNA damage, apoptosis and perturbation of AMPK-mTOR signalling

Chemotherapy remains the most prescribed anti-cancer therapy, despite patients suffering severe side effects and frequently developing chemoresistance. These complications can be partially overcome by combining different chemotherapeutic agents that target multiple biological pathways. However, selecting efficacious drug combinations remains challenging. We previously used fission yeast Schizosaccharomycespombe as a surrogate model to predict drug combinations, and showed that suberoylanilide hydroxamic acid (SAHA) and cisplatin can sensitise gastric adenocarcinoma cells toward the cytotoxic effects of doxorubicin. Yet, how this combination undermines cell viability is unknown. Here, we show that SAHA and doxorubicin markedly enhance the cleavage of two apoptosis markers, caspase 3 and poly-ADP ribose polymerase (PARP-1), and increase the phosphorylation of γH2AX, a marker of DNA damage. Further, we found a prominent reduction in Ser485 phosphorylation of AMP-dependent protein kinase (AMPK), and reductions in its target mTOR and downstream ribosomal protein S6 phosphorylation. We show that SAHA contributes most of the effect, as confirmed using another histone deacetylase inhibitor, trichostatin A. Overall, our results show that the combination of SAHA and doxorubicin can induce apoptosis in gastric adenocarcinoma in a synthetically lethal manner, and that fission yeast offers an efficient tool for identifying potent drug combinations against human cancer cells.

Integration of phytochemicals and phytotherapy into cancer precision medicine

Concepts of individualized therapy in the 1970s and 1980s attempted to develop predictive in vitro tests for individual drug responsiveness without reaching clinical routine. Precision medicine attempts to device novel individual cancer therapy strategies. Using bioinformatics, relevant knowledge is extracted from huge data amounts. However, tumor heterogeneity challenges chemotherapy due to genetically and phenotypically different cell subpopulations, which may lead to refractory tumors. Natural products always served as vital resources for cancer therapy (e.g., Vinca alkaloids, camptothecin, paclitaxel, etc.) and are also sources for novel drugs. Targeted drugs developed to specifically address tumor-related proteins represent the basis of precision medicine. Natural products from plants represent excellent resource for targeted therapies. Phytochemicals and herbal mixtures act multi-specifically, i.e. they attack multiple targets at the same time. Network pharmacology facilitates the identification of the complexity of pharmacogenomic networks and new signaling networks that are distorted in tumors. In the present review, we give a conceptual overview, how the problem of drug resistance may be approached by integrating phytochemicals and phytotherapy into academic western medicine. Modern technology platforms (e.g. “-omics” technologies, DNA/RNA sequencing, and network pharmacology) can be applied for diverse treatment modalities such as cytotoxic and targeted chemotherapy as well as phytochemicals and phytotherapy. Thereby, these technologies represent an integrative momentum to merge the best of two worlds: clinical oncology and traditional medicine. In conclusion, the integration of phytochemicals and phytotherapy into cancer precision medicine represents a valuable asset to chemically synthesized chemicals and therapeutic antibodies.

Nanoencapsulation of Novel Inhibitors of PNKP for Selective Sensitization to Ionizing Radiation and Irinotecan and Induction of Synthetic Lethality

There is increasing interest in developing and applying DNA repair inhibitors in cancer treatment to augment the efficacy of radiation and conventional genotoxic chemotherapy. However, targeting the inhibitor is required to avoid reducing the repair capacity of normal tissue. The aim of this study was to develop nanodelivery systems for the encapsulation of novel imidopiperidine-based inhibitors of the DNA 3'-phosphatase activity of polynucleotide kinase/phosphatase (PNKP), a DNA repair enzyme that plays a critical role in rejoining DNA single- and double-strand breaks. For this purpose, newly identified hit compounds with potent PNKP inhibitory activity, imidopiperidines A12B4C50 and A83B4C63 were encapsulated in polymeric micelles of different poly(ethylene oxide)- b-poly(ε-caprolactone) (PEO- b-PCL)-based structures. Our results showed efficient loading of A12B4C50 and A83B4C63 in PEO- b-PCLs with pendent carboxyl and benzyl carboxylate groups, respectively, and relatively slow release over 24 h. Both free and encapsulated inhibitors were able to sensitize HCT116 cells to radiation and the topoisomerase I poison, irinotecan. In addition, the encapsulated inhibitors were capable of inducing synthetic lethalilty in phosphatase and tensin homologue (PTEN)-deficient cells. We also established the validity of the peptide GE11 as a suitable ligand for active targeted delivery of nanoencapsulated drugs to colorectal cancer cells overexpressing epidermal growth factor receptor (EGFR). Our results show the potential of nanoencapsulated inhibitors of PNKP as either mono or combined therapeutic agents for colorectal cancer.

Practical aspects of NGS-based pathways analysis for personalized cancer science and medicine

Nowadays, the personalized approach to health care and cancer care in particular is becoming more and more popular and is taking an important place in the translational medicine paradigm. In some cases, detection of the patient-specific individual mutations that point to a targeted therapy has already become a routine practice for clinical oncologists. Wider panels of genetic markers are also on the market which cover a greater number of possible oncogenes including those with lower reliability of resulting medical conclusions. In light of the large availability of high-throughput technologies, it is very tempting to use complete patient-specific New Generation Sequencing (NGS) or other "omics" data for cancer treatment guidance. However, there are still no gold standard methods and protocols to evaluate them. Here we will discuss the clinical utility of each of the data types and describe a systems biology approach adapted for single patient measurements. We will try to summarize the current state of the field focusing on the clinically relevant case-studies and practical aspects of data processing.

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.

Prognostic and therapeutic value of disruptor of telomeric silencing-1-like (DOT1L) expression in patients with ovarian cancer

Background

Epigenetics has been known to play a critical role in regulating the malignant phenotype. This study was designed to examine the expression of DOT1L (histone 3 lysine 79 methyltransferase) and H3K79 methylation in normal ovarian tissues and ovarian tumors and to explore the function of DOT1L and its underline mechanisms in ovarian cancer.

Methods

The expression of DOT1L and H3K79 methylation in 250 ovarian tumor samples and 24 normal ovarian samples was assessed by immunohistochemistry. The effects of DOT1L on cell proliferation in vitro were evaluated using CCK8, colony formation and flow cytometry. The DOT1L-targeted genes were determined using chromatin immune-precipitation coupled with high-throughput sequencing (ChIP-seq) and ChIP-PCR. Gene expression levels were measured by real-time PCR and immunoblotting. The effects of DOT1L on tumor growth in vivo were evaluated using an orthotopic ovarian tumor model.

Results

DOT1L expression and H3K79 methylation was significantly increased in malignant ovarian tumors. High DOT1L expression was associated with International Federation of Gynecology and Obstetrics (FIGO) stage, histologic grade, and lymphatic metastasis. DOT1L was an independent prognostic factor for the overall survival (OS) and progression-free survival (PFS) of ovarian cancer, and higher DOT1L expression was associated with poorer OS and PFS. Furthermore, DOT1L regulates the transcription of G1 phase genes CDK6 and CCND3 through H3K79 dimethylation; therefore, blocking DOT1L could result in G1 arrest and thereby impede the cell proliferation in vitro and tumor growth in vivo.

Conclusions

Our findings first demonstrate that DOT1L over-expression has important clinical significance in ovarian cancer and also clarify that it drives cell cycle progression through transcriptional regulation of CDK6 and CCND3 through H3K79 methylation, suggesting that DOT1L might be potential target for prognostic assessment and therapeutic intervention in ovarian cancer.

Electronic supplementary material

The online version of this article (doi:10.1186/s13045-017-0400-8) contains supplementary material, which is available to authorized users.

Synthetic combinations of missense polymorphic genetic changes underlying Down syndrome susceptibility

Single nucleotide polymorphisms (SNPs) are important biomolecular markers in health and disease. Down syndrome, or Trisomy 21, is the most frequently occurring chromosomal abnormality in live-born children. Here, we highlight associations between SNPs in several important enzymes involved in the one-carbon folate metabolic pathway and the elevated maternal risk of having a child with Down syndrome. Our survey highlights that the combination of SNPs may be a more reliable predictor of the Down syndrome phenotype than single SNPs alone. We also describe recent links between SNPs in p53 and its related pathway proteins and Down syndrome, as well as highlight several proteins that help to associate apoptosis and p53 signaling with the Down syndrome phenotype. In addition to a comprehensive review of the literature, we also demonstrate that several SNPs reside within the same regions as these Down syndrome-linked SNPs, and propose that these closely located nucleotide changes may provide new candidates for future exploration.

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.

Network pharmacology of cancer: From understanding of complex interactomes to the design of multi-target specific therapeutics from nature

Despite massive investments in drug research and development, the significant decline in the number of new drugs approved or translated to clinical use raises the question, whether single targeted drug discovery is the right approach. To combat complex systemic diseases that harbour robust biological networks such as cancer, single target intervention is proved to be ineffective. In such cases, network pharmacology approaches are highly useful, because they differ from conventional drug discovery by addressing the ability of drugs to target numerous proteins or networks involved in a disease. Pleiotropic natural products are one of the promising strategies due to their multi-targeting and due to lower side effects. In this review, we discuss the application of network pharmacology for cancer drug discovery. We provide an overview of the current state of knowledge on network pharmacology, focus on different technical approaches and implications for cancer therapy (e.g. polypharmacology and synthetic lethality), and illustrate the therapeutic potential with selected examples green tea polyphenolics, Eleutherococcus senticosus, Rhodiola rosea, and Schisandra chinensis). Finally, we present future perspectives on their plausible applications for diagnosis and therapy of cancer.