Development of synthetic lethality in cancer: molecular and cellular classification. Signal Transduct Target Ther. 2020;5:241. [PMID: 33077733 PMCID: PMC7573576 DOI: 10.1038/s41392-020-00358-6]

Potential promising of synthetic lethality in cancer research and treatment

Cancer is a complex disease driven by multiple genetic changes, including mutations in oncogenes, tumor suppressor genes, DNA repair genes, and genes involved in cancer metabolism. Synthetic lethality (SL) is a promising approach in cancer research and treatment, where the simultaneous dysfunction of specific genes or pathways causes cell death. By targeting vulnerabilities created by these dysfunctions, SL therapies selectively kill cancer cells while sparing normal cells. SL therapies, such as PARP inhibitors, WEE1 inhibitors, ATR and ATM inhibitors, and DNA-PK inhibitors, offer a distinct approach to cancer treatment compared to conventional targeted therapies. Instead of directly inhibiting specific molecules or pathways, SL therapies exploit genetic or molecular vulnerabilities in cancer cells to induce selective cell death, offering benefits such as targeted therapy, enhanced treatment efficacy, and minimized harm to healthy tissues. SL therapies can be personalized based on each patient's unique genetic profile and combined with other treatment modalities to potentially achieve synergistic effects. They also broaden the effectiveness of treatment across different cancer types, potentially overcoming drug resistance and improving patient outcomes. This review offers an overview of the current understanding of SL mechanisms, advancements, and challenges, as well as the preclinical and clinical development of SL. It also discusses new directions and opportunities for utilizing SL in targeted therapy for anticancer treatment.

Graph based recurrent network for context specific synthetic lethality prediction

The concept of synthetic lethality (SL) has been successfully used for targeted therapies. To further explore SL for cancer therapy, identifying more SL interactions with therapeutic potential are essential. Recently, graph neural network-based deep learning methods have been proposed for SL prediction, which reduce the SL search space of wet-lab based methods. However, these methods ignore that most SL interactions depend strongly on genetic context, which limits the application of the predicted results. In this study, we proposed a graph recurrent network-based model for specific context-dependent SL prediction (SLGRN). In particular, we introduced a Graph Recurrent Network-based encoder to acquire a context-specific, low-dimensional feature representation for each node, facilitating the prediction of novel SL. SLGRN leveraged gate recurrent unit (GRU) and it incorporated a context-dependent-level state to effectively integrate information from all nodes. As a result, SLGRN outperforms the state-of-the-arts models for SL prediction. We subsequently validate novel SL interactions under different contexts based on combination therapy or patient survival analysis. Through in vitro experiments and retrospective clinical analysis, we emphasize the potential clinical significance of this context-specific SL prediction model.

Death ligand receptor (DLR) signaling: Its non-apoptotic functions in cancer and the consequences of DLR-directed therapies

Death ligands (DLs), particularly tumor necrosis factor alpha (TNF-α), FAS ligand (FASL), and TNF-related apoptosis-inducing ligand (TRAIL), collectively termed TFT, are pivotal members of the TNF superfamily. While traditionally linked to apoptosis, TFT proteins have emerged as key regulators of various non-apoptotic processes. This review summarizes the non-apoptotic functions of TFT in cancer and explores the intricate crosstalk signaling pathways and their impact on nuclear factor kappa B (NF-κB) signaling, inflammation, and pro-tumorigenic function. It also highlights the potential connections and hurdles that exist in translating synthetic lethality strategies involving DLs into clinical applications. Lastly, it discusses the challenges and opportunities associated with TFT-targeted therapeutic strategies for both malignant and non-malignant diseases.

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.

UBA1 inhibition sensitizes cancer cells to PARP inhibitors

Therapeutic strategies targeting the DNA damage response, such as poly (ADP-ribose) polymerase (PARP) inhibitors (PARPi), have revolutionized cancer treatment in tumors deficient in homologous recombination (HR). However, overcoming innate and acquired resistance to PARPi remains a significant challenge. Here, we employ a genome-wide CRISPR knockout screen and discover that the depletion of ubiquitin-activating enzyme E1 (UBA1) enhances sensitivity to PARPi in HR-proficient ovarian cancer cells. We show that silencing or pharmacological inhibition of UBA1 sensitizes multiple cell lines and organoid models to PARPi. Mechanistic studies uncover that UBA1 inhibition not only impedes HR repair to sensitize cells to PARP inhibition but also increases PARylation, which may subsequently be targeted by PARP inhibition. In vivo experiments using patient-derived xenografts demonstrate that combining PARP and UBA1 inhibition provided significant survival benefit compared to individual therapies with no detectable signs of toxicity, establishing this combination approach as a promising strategy to extend PARPi benefit.

CRISPR/Cas9 Technology Providing the Therapeutic Landscape of Metastatic Prostate Cancer

Prostate cancer (PCa) is the most prevalent malignancy and the second leading cause of cancer-related death in men. Although current therapies can effectively manage the primary tumor, most patients with late-stage disease manifest with metastasis in different organs. From surgery to treatment intensification (TI), several combinations of therapies are administered to improve the prognosis of patients with metastatic PCa. Due to the high frequency of the mutation during the metastatic phase, the clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated nuclease 9 (Cas9) genetic engineering tool can accelerate the effects of TI by enhancing targeted gene therapy or immunotherapy. This review describes the genetic background of metastatic PCa and how CRISPR/Cas9 technology can contribute to the field of PCa treatment development. It also discusses the current limitations of conventional PCa therapy and the potential of CRISPR-based PCa therapy.

GTF2H5 Identified as a crucial synthetic lethal target to counteract chemoresistance in colorectal cancer

BACKGROUND

Synthetic lethality (SL) emerges as a novel concept being explored to combat cancer progression and resistance to conventional therapy. Despite the efficacy of chemotherapy in select cases of colorectal cancer (CRC), a substantial proportion of patients encounter challenges, leading to an adverse prognosis of CRC patients. CRC-related SL genes offer a potential avenue for identifying therapeutic targets.

METHODS

CRC-related SL genes were obtained from the SynLethDB database. The bulk RNA sequencing data, mutation data, and clinical information for treated and untreated CRC patients were enrolled from the UCSC and GEO databases. The Tumor Immunology Single Cell Center database served as the repository for collecting and analyzing single-cell RNA sequencing data. The synergistic killing effect of SL genes and chemotherapeutic drugs on resistant cells was experimentally verified.

RESULTS

In the present study, pivotal SL genes associated with chemoresistance identified by using WGCNA and CRC patients categorized into two groups based on these genes. Variations between the groups were most pronounced in pathways associated with extracellular matrix remodeling. Further by integrating mutation data, five potential SL genes were discerned, which were highly expressed in the presence of TP53 or KRAS mutations, leading to a severely poor prognosis. Subsequent time series analysis revealed that the expression of GTF2H5 was gradually elevated at different stages of the transition from sensitive to resistant in CRC cells. Finally, it was preliminarily verified by experiments that GTF2H5 may play a key role in driving the drug-resistant transition within CRC cells.

CONCLUSIONS

The identification of SL genes that collaboratively interact with chemotherapeutic agents could provide new insights into solving the issue of chemotherapy resistance in CRC patients. And GTF2H5 wields a fundamental influence in inducing chemoresistance in CRC, which provided a potential therapeutic target for CRC.

Polθ: emerging synthetic lethal partner in homologous recombination-deficient tumors

The most remarkable finding in synthetic lethality (SL) is the hypersensitivity to PARP inhibitors (PARPis) of the tumors harboring defects in genes involved in homologous repair (HR) such as BRCA1/2. Despite initial responsiveness to PARPi, the penetrance of the synthetic lethal interactions between BRCA1/2 genes and PARPi is incomplete. Thus, a significant proportion of HR-defective tumors experience intrinsic or acquired resistance, representing a key challenge of clinical research. An expanded concept of SL is opening new ways and includes novel forms of genetic interactions, investigating not only traditional SL of pairs genes but also SL between biological pathways that regulate the same essential survival cell function. In this context, recent research showed that HR and theta-mediated end-joining (TMEJ) pathways exhibit SL. DNA polymerase theta (Polθ) is encoded by the POLQ gene and is a key component of the TMEJ, an essential backup pathway, intrinsically mutagenic, to repair resected double-strand breaks (DSBs) when the non-homologous end joining (NHEJ) and HR are impaired. Polθ is broadly expressed in normal tissues, overexpressed in several cancers, and typically associated with poor outcomes and shorter relapse-free survival. Notably, HR-deficient tumor cells present the characteristic mutational signatures of the error-prone TMEJ pathway. According to this observation, the loss of HR proteins, such as BRCA1 or BRCA2, contributes to increasing the TMEJ-specific genomic profile, suggesting synthetic lethal interactions between loss of the POLQ and HR genes, and resulting in the emerging interest for Polθ as a potential therapeutic target in BRCA1/2-associated tumors.This review summarizes the converging roles of the POLQ and HR genes in DNA DSB repair, the early-stage clinical trials using Polθ inhibitor to treat HR-defective tumors and to overcome BRCA-reversion mutations responsible for therapeutic resistance, and the novel pleiotropic effects of Polθ, paving the way for the development of unexplored synthetic lethality strategies.

An interpretable artificial intelligence framework for designing synthetic lethality-based anti-cancer combination therapies

INTRODUCTION

Synthetic lethality (SL) provides an opportunity to leverage different genetic interactions when designing synergistic combination therapies. To further explore SL-based combination therapies for cancer treatment, it is important to identify and mechanistically characterize more SL interactions. Artificial intelligence (AI) methods have recently been proposed for SL prediction, but the results of these models are often not interpretable such that deriving the underlying mechanism can be challenging.

OBJECTIVES

This study aims to develop an interpretable AI framework for SL prediction and subsequently utilize it to design SL-based synergistic combination therapies.

METHODS

We propose a knowledge and data dual-driven AI framework for SL prediction (KDDSL). Specifically, we use gene knowledge related to the SL mechanism to guide the construction of the model and develop a method to identify the most relevant gene knowledge for the predicted results.

RESULTS

Experimental and literature-based validation confirmed a good balance between predictive and interpretable ability when using KDDSL. Moreover, we demonstrated that KDDSL could help to discover promising drug combinations and clarify associated biological processes, such as the combination of MDM2 and CDK9 inhibitors, which exhibited significant anti-cancer effects in vitro and in vivo.

CONCLUSION

These data underscore the potential of KDDSL to guide SL-based combination therapy design. There is a need for biomedicine-focused AI strategies to combine rational biological knowledge with developed models.

Double Heterozygous Pathogenic Variants in TP53 and CHEK2 in Boy with Undifferentiated Embryonal Sarcoma of the Liver

Undifferentiated embryonal sarcoma of the liver is a rare mesenchymal malignancy that predominantly occurs in children. The relationship between this tumor entity and germline pathogenic variants (PVs) remains undefined. Here, we present the clinical case of a male patient diagnosed with undifferentiated embryonal sarcoma of the liver. Both germline and tumor samples were analyzed using next-generation sequencing. In the tumor tissue, PVs in TP53 (NM_000546.5):c.532del p.(His178Thrfs*69) and CHEK2 (NM_007194.4):c.85C>T p.(Gln29*) were identified, with both confirmed to be of germline origin. Copy number analyses indicated a loss of the wildtype TP53 allele in the tumor, consistent with a second hit, while it was the variant CHEK2 allele that was lost in the tumor. Our data indicate that the germline TP53 PV acts as a driver of tumorigenesis in the reported case and support a complex interaction between the germline TP53 and CHEK2 PVs. This case highlights the dynamic interplays of genetic alterations in tumorigenesis and emphasizes the need for continued investigation into the complex interactions between TP53 and CHEK2 PVs and into the association of undifferentiated embryonal sarcoma of the liver and Li-Fraumeni syndrome.

Benchmarking machine learning methods for synthetic lethality prediction in cancer

Synthetic lethality (SL) is a gold mine of anticancer drug targets, exposing cancer-specific dependencies of cellular survival. To complement resource-intensive experimental screening, many machine learning methods for SL prediction have emerged recently. However, a comprehensive benchmarking is lacking. This study systematically benchmarks 12 recent machine learning methods for SL prediction, assessing their performance across diverse data splitting scenarios, negative sample ratios, and negative sampling techniques, on both classification and ranking tasks. We observe that all the methods can perform significantly better by improving data quality, e.g., excluding computationally derived SLs from training and sampling negative labels based on gene expression. Among the methods, SLMGAE performs the best. Furthermore, the methods have limitations in realistic scenarios such as cold-start independent tests and context-specific SLs. These results, together with source code and datasets made freely available, provide guidance for selecting suitable methods and developing more powerful techniques for SL virtual screening.

Structure-based approaches in synthetic lethality strategies

Evolution has fostered robust DNA damage response (DDR) mechanisms to combat DNA lesions. However, disruptions in this intricate machinery can render cells overly reliant on the remaining functional but often less accurate DNA repair pathways. This increased dependence on error-prone pathways may result in improper repair and the accumulation of mutations, fostering genomic instability and facilitating the uncontrolled cell proliferation characteristic of cancer initiation and progression. Strategies based on the concept of synthetic lethality (SL) leverage the inherent genomic instability of cancer cells by targeting alternative pathways, thereby inducing selective death of cancer cells. This review emphasizes recent advancements in structural investigations of pivotal SL targets. The significant contribution of structure-based methodologies to SL research underscores their potential impact in characterizing the growing number of SL targets, largely due to advances in next-generation sequencing. Harnessing these approaches is essential for advancing the development of precise and personalized SL therapeutic strategies.

Altered metabolism in cancer: insights into energy pathways and therapeutic targets

Cancer cells undergo significant metabolic reprogramming to support their rapid growth and survival. This study examines important metabolic pathways like glycolysis, oxidative phosphorylation, glutaminolysis, and lipid metabolism, focusing on how they are regulated and their contributions to the development of tumors. The interplay between oncogenes, tumor suppressors, epigenetic modifications, and the tumor microenvironment in modulating these pathways is examined. Furthermore, we discuss the therapeutic potential of targeting cancer metabolism, presenting inhibitors of glycolysis, glutaminolysis, the TCA cycle, fatty acid oxidation, LDH, and glucose transport, alongside emerging strategies targeting oxidative phosphorylation and lipid synthesis. Despite the promise, challenges such as metabolic plasticity and the need for combination therapies and robust biomarkers persist, underscoring the necessity for continued research in this dynamic field.

New Horizons of Synthetic Lethality in Cancer: Current Development and Future Perspectives

In recent years, synthetic lethality has been recognized as a solid paradigm for anticancer therapies. The discovery of a growing number of synthetic lethal targets has led to a significant expansion in the use of synthetic lethality, far beyond poly(ADP-ribose) polymerase inhibitors used to treat BRCA1/2-defective tumors. In particular, molecular targets within DNA damage response have provided a source of inhibitors that have rapidly reached clinical trials. This Perspective focuses on the most recent progress in synthetic lethal targets and their inhibitors, within and beyond the DNA damage response, describing their design and associated therapeutic strategies. We will conclude by discussing the current challenges and new opportunities for this promising field of research, to stimulate discussion in the medicinal chemistry community, allowing the investigation of synthetic lethality to reach its full potential.

Discovery of Preclinical Candidate AD1058 as a Highly Potent, Selective, and Brain-Penetrant ATR Inhibitor for the Treatment of Advanced Malignancies

The ataxia telangiectasia-mutated and Rad3-related protein (ATR) plays a crucial role in regulating the cellular DNA-damage response (DDR), making it a promising target for antitumor drug development through synthetic lethality. In this study, we present the discovery and detailed characterization of AD1058, a highly potent and selective ATR inhibitor, with good preclinical pharmacokinetic profiles. AD1058 exhibits superior efficacy in inhibiting cell proliferation, disrupting the cell cycle, and inducing apoptosis compared to AZD6738. AD1058 displays potent antitumor effects as a single agent or in combination with clinically approved tumor therapies such as PARP inhibitors, ionizing radiotherapy, or chemotherapy in vivo. Considering its enhanced ability to permeate the blood-brain barrier, AD1058 is a promising clinical candidate for the treatment of brain metastases and leptomeningeal metastases in solid tumors. Additionally, among reported ATR inhibitors, AD1058 features the shortest synthesis route and the highest efficiency to date.

Adavosertib-encapsulated metal-organic frameworks for p53-mutated gallbladder cancer treatment via synthetic lethality

Adavosertib (ADA) is a WEE1 inhibitor that exhibits a synthetic lethal effect on p53-mutated gallbladder cancer (GBC). However, drug resistance due to DNA damage response compensation pathways and high toxicity limits further applications. Herein, estrone-targeted ADA-encapsulated metal-organic frameworks (ADA@MOF-EPL) for GBC synthetic lethal treatment by inducing conditional factors are developed. The high expression of estrogen receptors in GBC enables ADA@MOF-EPL to quickly enter and accumulate near the cell nucleus through estrone-mediated endocytosis and release ADA to inhibit WEE1 upon entering the acidic tumor microenvironment. Ultrasound irradiation induces ADA@MOF-EPL to generate reactive oxygen species (ROS), which leads to a further increase in DNA damage, resulting in a higher sensitivity of p53-mutated cancer cells to WEE1 inhibitor and promoting cell death via conditional synthetic lethality. The conditional factor induced by ADA@MOF-EPL further enhances the antitumor efficacy while significantly reducing systemic toxicity. Moreover, ADA@MOF-EPL demonstrates similar antitumor abilities in other p53-mutated solid tumors, revealing its potential as a broad-spectrum antitumor drug.

Unlocking Potential and Limits of Kinase Inhibitors: The Highway to Enhanced Cancer Targeted Therapy

Kinases are a family of enzymes comprising over five hundred members, which, when overexpressed or hyperactivated, are implicated in the pathogenesis of numerous hematological and solid cancers [...].

Fluorescence polarization assay for screening FANCM-RMI inhibitors to target the alternative lengthening of telomeres

Alternative Lengthening of Telomeres (ALT) is a mechanism used by 10-15% of all cancers to achieve replicative immortality, bypassing the DNA damage checkpoint associated with short telomeres that leads to cellular senescence or apoptosis. ALT does not occur in non-cancerous cells, presenting a potential therapeutic window for cancers where this mechanism is active. Disrupting the FANCM-RMI interaction has emerged as a promising therapeutic strategy that induces synthetic ALT lethality in genetic studies on cancer cell lines. There are currently no chemical inhibitors reported in the literature, in part due to the lack of reliable biophysical or biochemical assays to screen for FANCM-RMI disruption. Here we describe the development of a robust competitive fluorescence polarization (FP) assay that quantifies target binding at the FANCM-RMI interface. The assay employs a labeled peptide tracer TMR-RaMM2 derived from the native MM2 binding motif, which binds to recombinant RMI1-RMI2 and can be displaced by competitive inhibitors. We report the methods for recombinant production of RMI1-RMI2, design and evaluation of the tracer TMR-RaMM2, along with unlabeled peptide inhibitor controls to enable ALT-targeted drug discovery.

CSSLdb: Discovery of cancer-specific synthetic lethal interactions based on machine learning and statistic inference

Synthetic lethality (SL) occurs when the inactivation of two genes results in cell death while the inactivation of either gene alone is non-lethal. SL-based therapy has become a promising anti-cancer treatment option with the increasing researches and applications in clinical practice, while the specific therapeutic opportunities for various cancers have not yet been comprehensively investigated. Herein, we described a computational approach based on machine learning and statistical inference to discover the cancer-specific synthetic lethal interactions. First, Random Forest and One-Class SVM were used to perform cancer unbiased prediction of synthetic lethality. Then, two strategies, including mutual exclusivity and differential expression, were used to screen cancer-specific synthetic lethal interactions, resulting in 14,582 SL gene pairs in 33 cancer types. Finally, we developed a freely available database of CSSLdb (Cancer Specific Synthetic Lethality Database, http://www.tmliang.cn/CSSL/) to present cancer-specific synthetic lethal genetic interactions, which would enrich the relevant research and contribute to underlying therapy strategies based on synthetic lethality.

The power and the promise of synthetic lethality for clinical application in cancer treatment

Synthetic lethality is a phenomenon wherein the simultaneous deficiency of two or more genes results in cell death, while the deficiency of any individual gene does not lead to cell death. In recent years, synthetic lethality has emerged as a significant topic in the field of targeted cancer therapy, with certain drugs based on this concept exhibiting promising outcomes in clinical trials. Nevertheless, the presence of tumor heterogeneity and the intricate DNA repair mechanisms pose challenges to the effective implementation of synthetic lethality. This review aims to explore the concepts, development, and ethical quandaries surrounding synthetic lethality. Additionally, it will provide an in-depth analysis of the clinical application and underlying mechanism of synthetic lethality.

Cell fate regulation governed by p53: Friends or reversible foes in cancer therapy

Cancer is a leading cause of death worldwide. Targeted therapies aimed at key oncogenic driver mutations in combination with chemotherapy and radiotherapy as well as immunotherapy have benefited cancer patients considerably. Tumor protein p53 (TP53), a crucial tumor suppressor gene encoding p53, regulates numerous downstream genes and cellular phenotypes in response to various stressors. The affected genes are involved in diverse processes, including cell cycle arrest, DNA repair, cellular senescence, metabolic homeostasis, apoptosis, and autophagy. However, accumulating recent studies have continued to reveal novel and unexpected functions of p53 in governing the fate of tumors, for example, functions in ferroptosis, immunity, the tumor microenvironment and microbiome metabolism. Among the possibilities, the evolutionary plasticity of p53 is the most controversial, partially due to the dizzying array of biological functions that have been attributed to different regulatory mechanisms of p53 signaling. Nearly 40 years after its discovery, this key tumor suppressor remains somewhat enigmatic. The intricate and diverse functions of p53 in regulating cell fate during cancer treatment are only the tip of the iceberg with respect to its equally complicated structural biology, which has been painstakingly revealed. Additionally, TP53 mutation is one of the most significant genetic alterations in cancer, contributing to rapid cancer cell growth and tumor progression. Here, we summarized recent advances that implicate altered p53 in modulating the response to various cancer therapies, including chemotherapy, radiotherapy, and immunotherapy. Furthermore, we also discussed potential strategies for targeting p53 as a therapeutic option for cancer.

Identification of glucose-independent and reversible metabolic pathways associated with anti-proliferative effect of metformin in liver cancer cells

INTRODUCTION

Despite the ability of cancer cells to survive glucose deprivation, most studies on anti-cancer effect of metformin explored its impact on glucose metabolism. No study ever examined whether its anti-cancer effect is reversible. Existing evidences warrant understanding of glucose-independent non-cytotoxic anti-proliferative effect of metformin to rationalize its role in liver cancer.

OBJECTIVES

Characterization of glucose-independent anti-proliferative metabolic effects of metformin as well as analysis of their reversibility in liver cancer cells.

METHODOLOGY

The dose-dependent effects of metformin on HepG2 cells were examined in presence and absence of glucose. The longitudinal evolution of metabolome was analyzed along with gene and protein expression as well as their correlations with and reversibility of cellular phenotype and metabolic signatures.

RESULTS

Metformin concentrations up to 2.5 mM were found to be anti-proliferative irrespective of presence of glucose without significant increase in cytotoxicity. Apart from mitochondrial impairment, derangement of fatty acid desaturation, one-carbon, glutathione, and polyamine metabolism were associated with metformin treatment irrespective of glucose supplementation. Depletion of pantothenic acid, downregulation of essential amino acid uptake and metabolism alongside purine salvage were identified as novel glucose-independent effects of metformin. These were significantly correlated with cMyc expression and reduction in proliferation. Rescue experiments established reversibility upon metformin withdrawal and tight association between proliferation, metabotype, and cMyc expression.

CONCLUSIONS

The derangement of multiple glucose-independent metabolic pathways, which are often upregulated in therapy-resistant cancer, and concomitant cMyc downregulation coordinately contribute to the anti-proliferative effect of metformin in liver cancer cells. These are reversible and may influence its therapeutic utility.

shinyDeepDR: A user-friendly R Shiny app for predicting anti-cancer drug response using deep learning

Advancing precision oncology requires accurate prediction of treatment response and accessible prediction models. To this end, we present shinyDeepDR, a user-friendly implementation of our innovative deep learning model, DeepDR, for predicting anti-cancer drug sensitivity. The web tool makes DeepDR more accessible to researchers without extensive programming experience. Using shinyDeepDR, users can upload mutation and/or gene expression data from a cancer sample (cell line or tumor) and perform two main functions: "Find Drug," which predicts the sample's response to 265 approved and investigational anti-cancer compounds, and "Find Sample," which searches for cell lines in the Cancer Cell Line Encyclopedia (CCLE) and tumors in The Cancer Genome Atlas (TCGA) with genomics profiles similar to those of the query sample to study potential effective treatments. shinyDeepDR provides an interactive interface to interpret prediction results and to investigate individual compounds. In conclusion, shinyDeepDR is an intuitive and free-to-use web tool for in silico anti-cancer drug screening.

Proteomic and metabolomic signatures of U87 glioblastoma cells treated with cisplatin and/or paclitaxel

BACKGROUND

Glioblastoma (GBM) is a primary malignancy of the central nervous system and is classified as a grade IV astrocytoma by the World Health Organization (WHO). Although GBM rarely metastasizes, its prognosis remains poor. Moreover, the standard treatment for GBM, temozolomide (TMZ), is associated with chemoresistance, which is a major factor behind GBM-related deaths. Investigating drugs with repurposing potential in the context of GBM is worthwhile to bypass lengthy bench-to-bedside research. The field of omics has garnered significant interest in scientific research because of its potential to delineate the intricate regulatory network underlying tumor development. In particular, proteomic and metabolomic analyses are powerful approaches for the investigation of metabolic enzymes and intermediate metabolites since they represent the functional end of the cancer phenotype.

METHODS

We chose two of the most widely prescribed anticancer drugs, cisplatin and paclitaxel. To our knowledge, the current literature lacks studies examining their effects on metabolic and proteomic alterations in GBM. We employed the mass spectrometry technological platform 'UHPLC-Q-TOF-MS/MS' to examine the changes in the proteome and metabolome profiles of the U87 cell line with defined concentrations of cisplatin and/or paclitaxel via an untargeted approach.

RESULTS

A total of 1,419 distinct proteins and 90 metabolites were generated, and subsequent analysis was performed. We observed that upon treatment with cisplatin (9.5 μM), U87 cells exhibited apparent efforts to cope with this exogenous stressor, understanding the effect of paclitaxel (5.3 μM) on altering the transport machinery of the cell, and how the combination of cisplatin and/or paclitaxel suggests potential interactions with promising benefits in GBM therapeutics.

CONCLUSION

Our research provides a detailed map of alterations in response to cisplatin and paclitaxel treatment, provides crucial insights into the molecular basis of their action, and paves the way for further research to identify molecular targets for this elusive malignancy.

Emerging trends in gastrointestinal cancers: Targeting developmental pathways in carcinogenesis and tumor progression

Gastrointestinal carcinomas are a group of cancers associated with the digestive system and its accessory organs. The most prevalent cancers related to the gastrointestinal tract are colorectal, gall bladder, gastric, hepatocellular, and esophageal cancers, respectively. Molecular aberrations in different signaling pathways, such as signal transduction systems or developmental pathways are the chief triggering mechanisms in different cancers Though a massive advancement in diagnostic and therapeutic interventions results in improved survival of patients with gastrointestinal cancer; the lower malignancy stages of these carcinomas are comparatively asymptomatic. Various gastrointestinal-related cancers are detected at advanced stages, leading to deplorable prognoses and increased rates of recurrence. Recent molecular studies have elucidated the imperative roles of several signaling pathways, namely Wnt, Hedgehog, and Notch signaling pathways, play in the progression, therapeutic responsiveness, and metastasis of gastrointestinal-related cancers. This book chapter gives an interesting update on recent findings on the involvement of developmental signaling pathways their mechanistic insight in gastrointestinalcancer. Subsequently, evidences supporting the exploration of gastrointestinal cancer related molecular mechanisms have also been discussed for developing novel therapeutic strategies against these debilitating carcinomas.

A systematic analysis of the landscape of synthetic lethality-driven precision oncology

BACKGROUND

Synthetic lethality (SL) denotes a genetic interaction between two genes whose co-inactivation is detrimental to cells. Because more than 25 years have passed since SL was proposed as a promising way to selectively target cancer vulnerabilities, it is timely to comprehensively assess its impact so far and discuss its future.

METHODS

We systematically analyzed the literature and clinical trial data from the PubMed and Trialtrove databases to portray the preclinical and clinical landscape of SL oncology.

FINDINGS

We identified 235 preclinically validated SL pairs and found 1,207 pertinent clinical trials, and the number keeps increasing over time. About one-third of these SL clinical trials go beyond the typically studied DNA damage response (DDR) pathway, testifying to the recently broadening scope of SL applications in clinical oncology. We find that SL oncology trials have a greater success rate than non-SL-based trials. However, about 75% of the preclinically validated SL interactions have not yet been tested in clinical trials.

CONCLUSIONS

Dissecting the recent efforts harnessing SL to identify predictive biomarkers, novel therapeutic targets, and effective combination therapy, our systematic analysis reinforces the hope that SL may serve as a key driver of precision oncology going forward.

FUNDING

Funded by the Samsung Research Funding & Incubation Center of Samsung Electronics, the Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Republic of Korea government (MSIT), the Kwanjeong Educational Foundation, the Intramural Research Program of the National Institutes of Health (NIH), National Cancer Institute (NCI), and Center for Cancer Research (CCR).

Synthetic lethal approaches to target cancers with loss of PTEN function

Phosphatase and tensin homolog (PTEN) is a tumour suppressor gene and has a role in inhibiting the oncogenic AKT signalling pathway by dephosphorylating phosphatidylinositol 3,4,5-triphosphate (PIP3) into phosphatidylinositol 4,5-bisphosphate (PIP2). The function of PTEN is regulated by different mechanisms and inactive PTEN results in aggressive tumour phenotype and tumorigenesis. Identifying targeted therapies for inactive tumour suppressor genes such as PTEN has been challenging as it is difficult to restore the tumour suppressor functions. Therefore, focusing on the downstream signalling pathways to discover a targeted therapy for inactive tumour suppressor genes has highlighted the importance of synthetic lethality studies. This review focuses on the potential synthetic lethality genes discovered in PTEN-inactive cancer types. These discovered genes could be potential targeted therapies for PTEN-inactive cancer types and may improve the treatment response rates for aggressive types of cancer.

Unveiling the vulnerabilities of synthetic lethality in triple-negative breast cancer

Triple-negative breast cancer (TNBC) is the most invasive molecular subtype of breast cancer (BC), accounting for about nearly 15% of all BC cases reported annually. The absence of the three major BC hormone receptors, Estrogen (ER), Progesterone (PR), and Human Epidermal Growth Factor 2 (HER2) receptor, accounts for the characteristic "Triple negative" phraseology. The absence of these marked receptors makes this cancer insensitive to classical endocrine therapeutic approaches. Hence, the available treatment options remain solemnly limited to only conventional realms of chemotherapy and radiation therapy. Moreover, these therapeutic regimes are often accompanied by numerous treatment side-effects that account for early distant metastasis, relapse, and shorter overall survival in TNBC patients. The rigorous ongoing research in the field of clinical oncology has identified certain gene-based selective tumor-targeting susceptibilities, which are known to account for the molecular fallacies and mutation-based genetic alterations that develop the progression of TNBC. One such promising approach is synthetic lethality, which identifies novel drug targets of cancer, from undruggable oncogenes or tumor-suppressor genes, which cannot be otherwise clasped by the conventional approaches of mutational analysis. Herein, a holistic scientific review is presented, to undermine the mechanisms of synthetic lethal (SL) interactions in TNBC, the epigenetic crosstalks encountered, the role of Poly (ADP-ribose) polymerase inhibitors (PARPi) in inducing SL interactions, and the limitations faced by the lethal interactors. Thus, the future predicament of synthetic lethal interactions in the advancement of modern translational TNBC research is assessed with specific emphasis on patient-specific personalized medicine.

PARP inhibitors combined with radiotherapy: are we ready?

PARP was an enzyme found in the nucleus of eukaryotic cells that played a crucial role in repairing damaged DNA. Recently, PARP inhibitors have demonstrated great potential in cancer treatment. Thus, the FDA has approved several small-molecule PARP inhibitors for cancer maintenance therapy. The combination of PARP inhibitors and radiotherapy relies on synthetic lethality, taking advantage of the flaws in DNA repair pathways to target cancer cells specifically. Studies conducted prior to clinical trials have suggested that the combination of PARP inhibitors and radiotherapy can enhance the sensitivity of cancer cells to radiation, intensify DNA damage, and trigger cell death. Combining radiotherapy with PARP inhibitors in clinical trials has enhanced the response rate and progression-free survival of diverse cancer patients. The theoretical foundation of PARP inhibitors combined with radiotherapy is explained in detail in this article, and the latest advances in preclinical and clinical research on these inhibitors for tumor radiotherapy are summarized. The problems in the current field are recognized in our research and potential therapeutic applications for tumors are suggested. Nevertheless, certain obstacles need to be tackled when implementing PARP inhibitors and radiotherapies in clinical settings. Factors to consider when using the combination therapy are the most suitable schedule and amount of medication, identifying advantageous candidates, and the probable adverse effects linked with the combination. The combination of radiotherapy and PARP inhibitors can greatly enhance the effectiveness of cancer treatment.

Using graph-based model to identify cell specific synthetic lethal effects

Synthetic lethal (SL) pairs are pairs of genes whose simultaneous loss-of-function results in cell death, while a damaging mutation of either gene alone does not affect the cell's survival. This makes SL pairs attractive targets for precision cancer therapies, as targeting the unimpaired gene of the SL pair can selectively kill cancer cells that already harbor the impaired gene. Limited by the difficulty of finding true SL pairs, especially on specific cell types, current computational approaches provide only limited insights because of overlooking the crucial aspects of cellular context dependency and mechanistic understanding of SL pairs. As a result, the identification of SL targets still relies on expensive, time-consuming experimental approaches. In this work, we applied cell-line specific multi-omics data to a specially designed deep learning model to predict cell-line specific SL pairs. Through incorporating multiple types of cell-specific omics data with a self-attention module, we represent gene relationships as graphs. Our approach achieves the prediction of SL pairs in a cell-specific manner and demonstrates the potential to facilitate the discovery of cell-specific SL targets for cancer therapeutics, providing a tool to unearth mechanisms underlying the origin of SL in cancer biology. The code and data of our approach can be found at https://github.com/promethiume/SLwise.

SL-scan identifies synthetic lethal interactions in cancer using metabolic networks

Exploiting synthetic lethality is a promising strategy for developing targeted cancer therapies. However, identifying clinically significant synthetic lethal (SL) interactions among a large number of gene combinations is a challenging computational task. In this study, we developed the SL-scan pipeline based on metabolic network modeling to discover SL interaction. The SL-scan pipeline identifies the association between simulated Flux Balance Analysis knockout scores and mutation data across cancer cell lines and predicts putative SL interactions. We assessed the concordance of the SL pairs predicted by SL-scan with those of obtained from analysis of the CRISPR, shRNA, and PRISM datasets. Our results demonstrate that the SL-scan pipeline outperformed existing SL prediction approaches based on metabolic networks in identifying SL pairs in various cancers. This study emphasizes the importance of integrating multiple data sources, particularly mutation data, when identifying SL pairs for targeted cancer therapies. The findings of this study may lead to the development of novel targeted cancer therapies.

Multicellular Complex Tumor Spheroid Response to DNA Repair Inhibitors in Combination with DNA-damaging Drugs

Multicellular spheroids comprised of malignant cells, endothelial cells, and mesenchymal stem cells served as an in vitro model of human solid tumors to investigate the potentiation of DNA-damaging drugs by pharmacologic modulation of DNA repair pathways. The DNA-damaging drugs, topotecan, trabectedin, and temozolomide were combined with varied inhibitors of DNA damage response enzymes including PARP (olaparib or talazoparib), ATM (ataxia telangiectasia mutated; AZD-1390), ATR (ataxia telangiectasia and Rad3-related protein; berzosertib or elimusertib), and DNA-PK (DNA-dependent protein kinase; nedisertib or VX-984). A range of clinically achievable concentrations were tested up to the clinical Cmax, if known. Mechanistically, the types of DNA damage induced by temozolomide, topotecan, and trabectedin are distinct, which was apparent from the response of spheroids to combinations with various DNA repair inhibitors. Although most combinations resulted in additive cytotoxicity, synergistic activity was observed for temozolomide combined with PARP inhibitors as well as combinations of the ATM inhibitor AZD-1390 with either topotecan or trabectedin. These findings might provide guidance for the selection of anticancer agent combinations worthy of further investigation.

Significance

Clinical efficacy of DNA-damaging anticancer drugs can be influenced by the DNA damage response in tumor cells. The potentiation of DNA-damaging drugs by pharmacologic modulation of DNA repair pathways was assessed in multicellular tumor spheroids. Although most combinations demonstrated additive cytotoxicity, synergistic cytotoxicity was observed for several drug combinations.

Updates on Triple-Negative Breast Cancer in Type 2 Diabetes Mellitus Patients: From Risk Factors to Diagnosis, Biomarkers and Therapy

Triple-negative breast cancer (TNBC) is usually the most malignant and aggressive mammary epithelial tumor characterized by the lack of expression for estrogen receptors and progesterone receptors, and the absence of epidermal growth factor receptor (HER)2 amplification. Corresponding to 15-20% of all breast cancers and well-known by its poor clinical outcome, this negative receptor expression deprives TNBC from targeted therapy and makes its management therapeutically challenging. Type 2 diabetes mellitus (T2DM) is the most common ageing metabolic disorder due to insulin deficiency or resistance resulting in hyperglycemia, hyperinsulinemia, and hyperlipidemia. Due to metabolic and hormonal imbalances, there are many interplays between both chronic disorders leading to increased risk of breast cancer, especially TNBC, diagnosed in T2DM patients. The purpose of this review is to provide up-to-date information related to epidemiology and clinicopathological features, risk factors, diagnosis, biomarkers, and current therapy/clinical trials for TNBC patients with T2DM compared to non-diabetic counterparts. Thus, in-depth investigation of the diabetic complications on TNBC onset, development, and progression and the discovery of biomarkers would improve TNBC management through early diagnosis, tailoring therapy for a better outcome of T2DM patients diagnosed with TNBC.

Paralog-based synthetic lethality: rationales and applications

Tumor cells can result from gene mutations and over-expression. Synthetic lethality (SL) offers a desirable setting where cancer cells bearing one mutated gene of an SL gene pair can be specifically targeted by disrupting the function of the other genes, while leaving wide-type normal cells unharmed. Paralogs, a set of homologous genes that have diverged from each other as a consequence of gene duplication, make the concept of SL feasible as the loss of one gene does not affect the cell's survival. Furthermore, homozygous loss of paralogs in tumor cells is more frequent than singletons, making them ideal SL targets. Although high-throughput CRISPR-Cas9 screenings have uncovered numerous paralog-based SL pairs, the unclear mechanisms of targeting these gene pairs and the difficulty in finding specific inhibitors that exclusively target a single but not both paralogs hinder further clinical development. Here, we review the potential mechanisms of paralog-based SL given their function and genetic combination, and discuss the challenge and application prospects of paralog-based SL in cancer therapeutic discovery.

Small Molecules Targeting DNA Polymerase Theta (POLθ) as Promising Synthetic Lethal Agents for Precision Cancer Therapy

Synthetic lethality (SL) is an innovative strategy in targeted anticancer therapy that exploits tumor genetic vulnerabilities. This topic has come to the forefront in recent years, as witnessed by the increased number of publications since 2007. The first proof of concept for the effectiveness of SL was provided by the approval of poly(ADP-ribose)polymerase inhibitors, which exploit a SL interaction in BRCA-deficient cells, although their use is limited by resistance. Searching for additional SL interactions involving BRCA mutations, the DNA polymerase theta (POLθ) emerged as an exciting target. This review summarizes, for the first time, the POLθ polymerase and helicase inhibitors reported to date. Compounds are described focusing on chemical structure and biological activity. With the aim to enable further drug discovery efforts in interrogating POLθ as a target, we propose a plausible pharmacophore model for POLθ-pol inhibitors and provide a structural analysis of the known POLθ ligand binding sites.

Multi-omics characterization of synthetic lethality-related molecular features: implications for SL-based therapeutic target screening

Synthetic lethality (SL) represents the co-occurrence of two or more non-lethal disordered genes that could lead to cell death. SL-based anticancer therapeutics could specifically kill the cancer cells carrying the targeted mutated gene while leaving normal cells alive. Recent large-scale computational and experimental screenings provide rich resources of SL information while lacking systematic research on molecular features of SL genes. Combined with comprehensive multi-omics data analysis and experimental validation of one SL gene pair, Guo et al. portrayed a systematic layout of cancer-specific SL interactions that could improve understanding of carcinogenesis and potentially assist the subsequent screening of anticancer therapeutic targets.

Regulated cell death (RCD) in cancer: key pathways and targeted therapies

Regulated cell death (RCD), also well-known as programmed cell death (PCD), refers to the form of cell death that can be regulated by a variety of biomacromolecules, which is distinctive from accidental cell death (ACD). Accumulating evidence has revealed that RCD subroutines are the key features of tumorigenesis, which may ultimately lead to the establishment of different potential therapeutic strategies. Hitherto, targeting the subroutines of RCD with pharmacological small-molecule compounds has been emerging as a promising therapeutic avenue, which has rapidly progressed in many types of human cancers. Thus, in this review, we focus on summarizing not only the key apoptotic and autophagy-dependent cell death signaling pathways, but the crucial pathways of other RCD subroutines, including necroptosis, pyroptosis, ferroptosis, parthanatos, entosis, NETosis and lysosome-dependent cell death (LCD) in cancer. Moreover, we further discuss the current situation of several small-molecule compounds targeting the different RCD subroutines to improve cancer treatment, such as single-target, dual or multiple-target small-molecule compounds, drug combinations, and some new emerging therapeutic strategies that would together shed new light on future directions to attack cancer cell vulnerabilities with small-molecule drugs targeting RCD for therapeutic purposes.

The Differential Metabolic Signature of Breast Cancer Cellular Response to Olaparib Treatment

Simple Summary

Breast cancer remains a leading cause of female cancer related mortality worldwide. Loss of genomic stability and dysregulation of cellular metabolism are well-recognized features of breast cancer, presenting an opportunity to study the drivers of breast cancer progression and resistance to chemotherapy. The overarching goal of this work is to perform combined analysis of DNA damage repair and cellular metabolism in response to olaparib treatment in a panel of breast cancer cell lines. By applying a combined untargeted metabolomics and molecular biology approach, our findings show dysregulation of amino acid metabolism and metabolic reprogramming from glycolysis to amino acid utilization to be a common feature in all breast cancer cell lines examined, some of which are consistent with findings from the analysis of clinical breast cancer tumours. Functional assessment of genetic alterations offers the scope to design new prognostic tools and inform the design of new chemotherapies or drug combinations.

Abstract

Metabolic reprogramming and genomic instability are key hallmarks of cancer, the combined analysis of which has gained recent popularity. Given the emerging evidence indicating the role of oncometabolites in DNA damage repair and its routine use in breast cancer treatment, it is timely to fingerprint the impact of olaparib treatment in cellular metabolism. Here, we report the biomolecular response of breast cancer cell lines with DNA damage repair defects to olaparib exposure. Following evaluation of olaparib sensitivity in breast cancer cell lines, we immunoprobed DNA double strand break foci and evaluated changes in cellular metabolism at various olaparib treatment doses using untargeted mass spectrometry-based metabolomics analysis. Following identification of altered features, we performed pathway enrichment analysis to measure key metabolic changes occurring in response to olaparib treatment. We show a cell-line-dependent response to olaparib exposure, and an increased susceptibility to DNA damage foci accumulation in triple-negative breast cancer cell lines. Metabolic changes in response to olaparib treatment were cell-line and dose-dependent, where we predominantly observed metabolic reprogramming of glutamine-derived amino acids and lipids metabolism. Our work demonstrates the effectiveness of combining molecular biology and metabolomics studies for the comprehensive characterisation of cell lines with different genetic profiles. Follow-on studies are needed to map the baseline metabolism of breast cancer cells and their unique response to drug treatment. Fused with genomic and transcriptomics data, such readout can be used to identify key oncometabolites and inform the rationale for the design of novel drugs or chemotherapy combinations.

Synthetic Lethality Targeting Polθ

Research studies regarding synthetic lethality (SL) in human cells are primarily motivated by the potential of this phenomenon to be an effective, but at the same time, safe to the patient's anti-cancer chemotherapy. Among the factors that are targets for the induction of the synthetic lethality effect, those involved in DNA repair seem to be the most relevant. Specifically, when mutation in one of the canonical DNA double-strand break (DSB) repair pathways occurs, which is a frequent event in cancer cells, the alternative pathways may be a promising target for the elimination of abnormal cells. Currently, inhibiting RAD52 and/or PARP1 in the tumor cells that are deficient in the canonical repair pathways has been the potential target for inducing the effect of synthetic lethality. Unfortunately, the development of resistance to commonly used PARP1 inhibitors (PARPi) represents the greatest obstacle to working out a successful treatment protocol. DNA polymerase theta (Polθ), encoded by the POLQ gene, plays a key role in an alternative DSB repair pathway-theta-mediated end joining (TMEJ). Thus, it is a promising target in the treatment of tumors harboring deficiencies in homologous recombination repair (HRR), where its inhibition can induce SL. In this review, the authors discuss the current state of knowledge on Polθ as a potential target for synthetic lethality-based anticancer therapies.

p53-Mediated Indirect Regulation on Cellular Metabolism: From the Mechanism of Pathogenesis to the Development of Cancer Therapeutics

The transcription factor p53 is the most well-characterized tumor suppressor involved in multiple cellular processes, which has expanded to the regulation of metabolism in recent decades. Accumulating evidence reinforces the link between the disturbance of p53-relevant metabolic activities and tumor development. However, a full-fledged understanding of the metabolic roles of p53 and the underlying detailed molecular mechanisms in human normal and cancer cells remain elusive, and persistent endeavor is required to foster the entry of drugs targeting p53 into clinical use. This mini-review summarizes the indirect regulation of cellular metabolism by wild-type p53 as well as mutant p53, in which mechanisms are categorized into three major groups: through modulating downstream transcriptional targets, protein-protein interaction with other transcription factors, and affecting signaling pathways. Indirect mechanisms expand the p53 regulatory networks of cellular metabolism, making p53 a master regulator of metabolism and a key metabolic sensor. Moreover, we provide a brief overview of recent achievements and potential developments in the therapeutic strategies targeting mutant p53, emphasizing synthetic lethal methods targeting mutant p53 with metabolism. Then, we delineate synthetic lethality targeting mutant p53 with its indirect regulation on metabolism, which expands the synthetic lethal networks of mutant p53 and broadens the horizon of developing novel therapeutic strategies for p53 mutated cancers, providing more opportunities for cancer patients with mutant p53. Finally, the limitations and current research gaps in studies of metabolic networks controlled by p53 and challenges of research on p53-mediated indirect regulation on metabolism are further discussed.

Synthetic Vulnerabilities in the KRAS Pathway

Mutations in Kristen Rat Sarcoma viral oncogene (KRAS) are among the most frequent gain-of-function genetic alterations in human cancer. Most KRAS-driven cancers depend on its sustained expression and signaling. Despite spectacular recent success in the development of inhibitors targeting specific KRAS alleles, the discovery and utilization of effective directed therapies for KRAS-mutant cancers remains a major unmet need. One potential approach is the identification of KRAS-specific synthetic lethal vulnerabilities. For example, while KRAS-driven oncogenesis requires the activation of a number of signaling pathways, it also triggers stress response pathways in cancer cells that could potentially be targeted for therapeutic benefit. This review will discuss how the latest advances in functional genomics and the development of more refined models have demonstrated the existence of molecular pathways that can be exploited to uncover synthetic lethal interactions with a promising future as potential clinical treatments in KRAS-mutant cancers.

Recent Advances in Synergistic Antitumor Effects Exploited from the Inhibition of Ataxia Telangiectasia and RAD3-Related Protein Kinase (ATR)

As one of the key phosphatidylinositol 3-kinase-related kinases (PIKKs) family members, ataxia telangiectasia and RAD3-related protein kinase (ATR) is crucial in maintaining mammalian cell genomic integrity in DNA damage response (DDR) and repair pathways. Dysregulation of ATR has been found across different cancer types. In recent years, the inhibition of ATR has been proven to be effective in cancer therapy in preclinical and clinical studies. Importantly, tumor-specific alterations such as ATM loss and Cyclin E1 (CCNE1) amplification are more sensitive to ATR inhibition and are being exploited in synthetic lethality (SL) strategy. Besides SL, synergistic anticancer effects involving ATRi have been reported in an increasing number in recent years. This review focuses on the recent advances in different forms of synergistic antitumor effects, summarizes the pharmacological benefits and ongoing clinical trials behind the biological mechanism, and provides perspectives for future challenges and opportunities. The hope is to draw awareness to the community that targeting ATR should have great potential in developing effective anticancer medicines.

Computational methods, databases and tools for synthetic lethality prediction

Synthetic lethality (SL) occurs between two genes when the inactivation of either gene alone has no effect on cell survival but the inactivation of both genes results in cell death. SL-based therapy has become one of the most promising targeted cancer therapies in the last decade as PARP inhibitors achieve great success in the clinic. The key point to exploiting SL-based cancer therapy is the identification of robust SL pairs. Although many wet-lab-based methods have been developed to screen SL pairs, known SL pairs are less than 0.1% of all potential pairs due to large number of human gene combinations. Computational prediction methods complement wet-lab-based methods to effectively reduce the search space of SL pairs. In this paper, we review the recent applications of computational methods and commonly used databases for SL prediction. First, we introduce the concept of SL and its screening methods. Second, various SL-related data resources are summarized. Then, computational methods including statistical-based methods, network-based methods, classical machine learning methods and deep learning methods for SL prediction are summarized. In particular, we elaborate on the negative sampling methods applied in these models. Next, representative tools for SL prediction are introduced. Finally, the challenges and future work for SL prediction are discussed.

Cyclin-Dependent Kinase Synthetic Lethality Partners in DNA Damage Response

Cyclin-dependent kinases (CDKs) are pivotal mediators and effectors of the DNA damage response (DDR) that regulate both the pathway components and proteins involved in repair processes. Synthetic lethality (SL) describes a situation in which two genes are linked in such a way that the lack of functioning of just one maintains cell viability, while depletion of both triggers cell death. Synthetic lethal interactions involving CDKs are now emerging, and this can be used to selectively target tumor cells with DNA repair defects. In this review, SL interactions of CDKs with protooncogene products MYC, poly (ADP-ribose) polymerase (PARP-1), and cellular tumor antigen p53 (TP53) are discussed. The individual roles of each of the SL partners in DDR are described.

Therapeutic Opportunities of Disrupting Genome Integrity in Adult Diffuse Glioma

Adult diffuse glioma, particularly glioblastoma (GBM), is a devastating tumor of the central nervous system. The existential threat of this disease requires on-going treatment to counteract tumor progression. The present outcome is discouraging as most patients will succumb to this disease. The low cure rate is consistent with the failure of first-line therapy, radiation and temozolomide (TMZ). Even with their therapeutic mechanism of action to incur lethal DNA lesions, tumor growth remains undeterred. Delivering additional treatments only delays the inescapable development of therapeutic tolerance and disease recurrence. The urgency of establishing lifelong tumor control needs to be re-examined with a greater focus on eliminating resistance. Early genomic and transcriptome studies suggest each tumor subtype possesses a unique molecular network to safeguard genome integrity. Subsequent seminal work on post-therapy tumor progression sheds light on the involvement of DNA repair as the causative contributor for hypermutation and therapeutic failure. In this review, we will provide an overview of known molecular factors that influence the engagement of different DNA repair pathways, including targetable vulnerabilities, which can be exploited for clinical benefit with the use of specific inhibitors.

BRD4 inhibition induces synthetic lethality in ARID2-deficient hepatocellular carcinoma by increasing DNA damage

Hepatocellular carcinoma (HCC) has emerged as the third cause of cancer-related death owing to lacking effective systemic therapies. Genomic DNA sequencing revealed the high frequency of loss-of-function mutations in ARID2, which encodes a subunit of SWI/SNF chromatin remodeling complex, however, the therapeutic strategy for the HCC patients with ARID2 mutations is still completely unclear. In this study, we first performed a high-throughput screening approach using a compound library consisting of 2 180 FDA-approved drugs and other compounds, to elicit the potential drugs for synthetic lethality to target ARID2-deficient HCC cells. Interestingly, JQ1, a selective inhibitor of bromodomain protein BRD4, uniquely suppressed the growth of ARID2- deficient HCC cells. Next JQ1 is further confirmed to predominantly induce cell lethality upon ARID2 depletion through exacerbating DNA damage, especially double strand breaks (DSBs). Functional assays demonstrated that both BRD4 inhibition and ARID2 deficiency synergistically impede two main DNA damage repair pathways, homologous recombination (HR) and non-homologous end-joining (NHEJ), through attenuating the transcription of BRCA1, RAD51, and 53BP1, which encode the core molecules responsible for DSB repair. Mechanistically, both ARID2 and BRD4 exert a synergistic effect for maintaining transcriptional enhancer-promoter loops of these genes within chromatin conformation. However, as both ARID2 and BRD4 are disrupted, the expression of these DNA repair-related genes in response to DNA damage are hindered, resulting in DSB accumulation and cell apoptosis. Taken together, this study discloses that BRD4 inhibition may induce synthetic lethality in ARID2-deficient HCC cells, which might provide a potential therapeutic strategy for HCC patients with ARID2 mutations.

Discovery of small-molecule ATR inhibitors for potential cancer treatment: a patent review from 2014 to present

INTRODUCTION

Ataxia telangiectasia and RAD3-related kinase (ATR) is one of the key PIKKs family members important for DNA damage response and repair pathways. Targeting ATR kinase for potential cancer therapy has attracted a great deal of attention to both pharmaceutical industries and academic community.

AREA COVERED

This article surveys the patents published since 2014 aiming to analyze the structural features of scaffolds and the patent space. It also discusses the recent clinical developments and provides perspectives on the challenges and the future directions.

EXPERT OPINION

ATR kinase appears to be a viable drug target for anticancer therapy. Similar to DNA-PK inhibitors, the clinical investigation of an ATRi employs both monotherapy and combination strategy. In the combination strategy, an ATRi is typically combined with a radiation or a targeted drug such as chemotherapy agent poly (ADP-ribose) polymerase (PARP) inhibitor, etc. Diverse structures comprising different scaffolds from mono-heteroaryl to bicyclic heteroaryl to tricyclic heteroaryl to macrocycle are capable to achieve good ATR inhibitory activity and good ATR selectivity over other closely related enzymes. There are eight ATR inhibitors currently being evaluated in clinics, with the hope to get approval in the near future.

Discovery of AL-GDa62 as a Potential Synthetic Lethal Lead for the Treatment of Gastric Cancer

Diffuse gastric cancer and lobular breast cancer are aggressive malignancies that are frequently associated with inactivating mutations in the tumor suppressor gene CDH1. Synthetic lethal (SL) vulnerabilities arising from CDH1 dysfunction represent attractive targets for drug development. Recently, SLEC-11 (1) emerged as a SL lead in E-cadherin-deficient cells. Here, we describe our efforts to optimize 1. Overall, 63 analogues were synthesized and tested for their SL activity toward isogenic mammary epithelial CDH1-deficient cells (MCF10A-CDH1^-/-). Among the 26 compounds with greater cytotoxicity, AL-GDa62 (3) was four-times more potent and more selective than 1 with an EC₅₀ ratio of 1.6. Furthermore, 3 preferentially induced apoptosis in CDH1^-/- cells, and Cdh1^-/- mammary and gastric organoids were significantly more sensitive to 3 at low micromolar concentrations. Thermal proteome profiling of treated MCF10A-CDH1^-/- cell protein lysates revealed that 3 specifically inhibits TCOF1, ARPC5, and UBC9. In vitro, 3 inhibited SUMOylation at low micromolar concentrations.

Evaluation of the Role of p53 Tumour Suppressor Posttranslational Modifications and TTC5 Cofactor in Lung Cancer

Mutations in the p53 tumor suppressor are found in over 50% of cancers. p53 function is controlled through posttranslational modifications and cofactor interactions. In this study, we investigated the posttranslationally modified p53, including p53 acetylated at lysine 382 (K382), p53 phosphorylated at serine 46 (S46), and the p53 cofactor TTC5/STRAP (Tetratricopeptide repeat domain 5/ Stress-responsive activator of p300-TTC5) proteins in lung cancer. Immunohistochemical (IHC) analysis of lung cancer tissues from 250 patients was carried out and the results were correlated with clinicopathological features. Significant associations between total or modified p53 with a higher grade of the tumour and shorter overall survival (OS) probability were detected, suggesting that mutant and/or modified p53 acts as an oncoprotein in these patients. Acetylated at K382 p53 was predominantly nuclear in some samples and cytoplasmic in others. The localization of the K382 acetylated p53 was significantly associated with the gender and grade of the disease. The TTC5 protein levels were significantly associated with the grade, tumor size, and node involvement in a complex manner. SIRT1 expression was evaluated in 50 lung cancer patients and significant positive correlation was found with p53 S46 intensity, whereas negative TTC5 staining was associated with SIRT1 expression. Furthermore, p53 protein levels showed positive association with poor OS, whereas TTC5 protein levels showed positive association with better OS outcome. Overall, our results indicate that an analysis of p53 modified versions together with TTC5 expression, upon testing on a larger sample size of patients, could serve as useful prognostic factors or drug targets for lung cancer treatment.

PARP1 as a therapeutic target in acute myeloid leukemia and myelodysplastic syndrome

Poly(ADP-ribose) polymerase 1 (PARP1) is a key mediator of various forms of DNA damage repair and plays an important role in the progression of several cancer types. The enzyme is activated by binding to DNA single-strand and double-strand breaks. Its contribution to chromatin remodeling makes PARP1 crucial for gene expression regulation. Inhibition of its activity with small molecules leads to the synthetic lethal effect by impeding DNA repair in the treatment of cancer cells. At first, PARP1 inhibitors (PARPis) were developed to target breast cancer mutated cancer cells. Currently, PARPis are being studied to be used in a broader variety of patients either as single agents or in combination with chemotherapy, antiangiogenic agents, ionizing radiation, and immune checkpoint inhibitors. Ongoing clinical trials on olaparib, rucaparib, niraparib, veliparib, and the recent talazoparib show the advantage of these agents in overcoming PARPi resistance and underline their efficacy in targeted treatment of several hematologic malignancies. In this review, focusing on the crucial role of PARP1 in physiological and pathological effects in myelodysplastic syndrome and acute myeloid leukemia, we give an outline of the enzyme's mechanisms of action and its role in the pathophysiology and prognosis of myelodysplastic syndrome/acute myeloid leukemia and we analyze the available data on the use of PARPis, highlighting their promising advances in clinical application.