Discovering and validating cancer genetic dependencies: approaches and pitfalls

Frequent loss of FAM126A expression in colorectal cancer results in selective FAM126B dependency

Most advanced colorectal cancer (CRC) patients cannot benefit from targeted therapy due to lack of actionable targets. By mining data from the DepMap, we identified FAM126B as a specific vulnerability in CRC cell lines exhibiting low FAM126A expression. Employing a combination of genetic perturbation and inducible protein degradation techniques, we demonstrate that FAM126A and FAM126B function in a redundant manner to facilitate the recruitment of PI4KIIIα to the plasma membrane for PI4P synthesis. Examination of data from TCGA and GTEx revealed that over 7% of CRC tumor samples exhibited loss of FAM126A expression, contrasting with uniform FAM126A expression in normal tissues. In both CRC cell lines and tumor samples, promoter hypermethylation correlated with the loss of FAM126A expression, which could be reversed by DNA methylation inhibitors. In conclusion, our study reveals that loss of FAM126A expression results in FAM126B dependency, thus proposing FAM126B as a therapeutic target for CRC treatment.

Down-regulation of AKT proteins slows the growth of mutant-KRAS pancreatic tumors

Serine/threonine kinase AKT isoforms play a well-established role in cell metabolism and growth. Most pancreatic adenocarcinoma (PDAC) harbors activation mutations of KRAS, which activates the PI3K/AKT signaling pathway. However, AKT inhibitors are not effective in the treatment of pancreatic cancer. To better understand the role of AKT signaling in mutant-KRAS pancreatic tumors, this study utilizes proteolysis-targeting chimeras (PROTACs) and CRISPR-Cas9-genome editing to investigate AKT proteins. PROTAC down-regulation of AKT proteins markedly slowed the growth of three pancreatic tumor cell lines harboring mutant KRAS. In contrast, inhibition of AKT kinase activity alone had very little effect on the growth of these cell lines. Concurrent genetic deletion of all AKT isoforms (AKT1, AKT2, and AKT3) in the KPC (KrasG12D; Trp53R172H; Pdx1-Cre) pancreatic cancer cell line also dramatically slowed its growth in vitro and when orthotopically implanted in syngeneic mice. Surprisingly, insulin-like growth factor-1 (IGF-1), but not epidermal growth factor (EGF), restored KPC cell growth in serum-deprived conditions and the IGF-1 growth stimulation effect was AKT dependent. RNA-seq analysis of AKT1/2/3-deficient KPC cells suggested that reduced cholesterol synthesis may be responsible for the decreased response to IGF-1 stimulation. These results indicate that the presence of all three AKT isoforms supports pancreatic tumor cell growth and pharmacological degradation of AKT proteins may be more effective than AKT catalytic inhibitors for treating pancreatic cancer.

Pathway-based signatures predict patient outcome, chemotherapy benefit and synthetic lethal dependencies in invasive lobular breast cancer

BACKGROUND

Invasive Lobular Carcinoma (ILC) is a morphologically distinct breast cancer subtype that represents up to 15% of all breast cancers. Compared to Invasive Breast Carcinoma of No Special Type (IBC-NST), ILCs exhibit poorer long-term outcome and a unique pattern of metastasis. Despite these differences, the systematic discovery of robust prognostic biomarkers and therapeutically actionable molecular pathways in ILC remains limited.

METHODS

Pathway-centric multivariable models using statistical machine learning were developed and tested in seven retrospective clinico-genomic cohorts (n = 996). Further external validation was performed using a new RNA-Seq clinical cohort of aggressive ILCs (n = 48).

RESULTS AND CONCLUSIONS

mRNA dysregulation scores of 25 pathways were strongly prognostic in ILC (FDR-adjusted P < 0.05). Of these, three pathways including Cell-cell communication, Innate immune system and Smooth muscle contraction were also independent predictors of chemotherapy response. To aggregate these findings, a multivariable machine learning predictor called PSILC was developed and successfully validated for predicting overall and metastasis-free survival in ILC. Integration of PSILC with CRISPR-Cas9 screening data from breast cancer cell lines revealed 16 candidate therapeutic targets that were synthetic lethal with high-risk ILCs. This study provides interpretable prognostic and predictive biomarkers of ILC which could serve as the starting points for targeted drug discovery for this disease.

Synergistic lethality between auranofin-induced oxidative DNA damage and ATR inhibition in cancer cells

AIMS

Studies in the past have shown that inhibition of the ataxia telangiectasia and Rad3-related (ATR) kinase sensitizes cancer cells to genotoxic anticancer treatments, however, clinical use of ATR inhibitors in combination with DNA damaging chemotherapy is limited due to toxicity in healthy tissues. In this study, we investigated the synergistic anticancer effect between ATR inhibition and oxidative DNA damage induced by the thioredoxin reductase inhibitor auranofin.

MAIN METHODS

Cytotoxicity was evaluated by cell viability assays. Western blot, comet assay, immunostaining and flow cytometry were performed to dissect the underlying mechanisms. In vivo efficacy was examined against tumor xenografts.

KEY FINDINGS

Nontoxic doses of auranofin alone increased the levels of reactive oxygen species (ROS) in cancer but not noncancerous cells, resulting in oxidative DNA damage and activation of the ATR DNA damage response pathway selectively in cancer cells. Inhibition of ATR in auranofin-treated cancer cells resulted in unscheduled firing of dormant DNA replication origins, abrogation of the S phase cell cycle checkpoint and extensive DNA breakage, leading to replication catastrophe and potent synergistic lethality. Both the antioxidant NAC and the DNA polymerase inhibitor aphidicolin reduced replication stress and synergistic cytotoxicity, implicating replication stress-driven catastrophic cell death resulted from collision between oxidative DNA damage and dysregulated DNA replication. In vivo, auranofin and VE822 coadministration enabled marked regressions of tumor xenografts, while each drug alone had no effect.

SIGNIFICANCE

As increased generation of ROS is a universal feature of tumors, our findings may open new routes to broaden the therapeutic potential of ATR inhibitors.

Inhibition of a lower potency target drives the anticancer activity of a clinical p38 inhibitor

The small-molecule drug ralimetinib was developed as an inhibitor of the p38α mitogen-activated protein kinase, and it has advanced to phase 2 clinical trials in oncology. Here, we demonstrate that ralimetinib resembles EGFR-targeting drugs in pharmacogenomic profiling experiments and that ralimetinib inhibits EGFR kinase activity in vitro and in cellulo. While ralimetinib sensitivity is unaffected by deletion of the genes encoding p38α and p38β, its effects are blocked by expression of the EGFR-T790M gatekeeper mutation. Finally, we solved the cocrystal structure of ralimetinib bound to EGFR, providing further evidence that this drug functions as an ATP-competitive EGFR inhibitor. We conclude that, though ralimetinib is >30-fold less potent against EGFR compared to p38α, its ability to inhibit EGFR drives its primary anticancer effects. Our results call into question the value of p38α as an anticancer target, and we describe a multi-modal approach that can be used to uncover a drug's mechanism-of-action.

Targeting pan-essential pathways in cancer with cytotoxic chemotherapy: challenges and opportunities

Cytotoxic chemotherapy remains a key modality in cancer treatment. These therapies, successfully used for decades, continue to transform the lives of cancer patients daily. With the high attrition rate of current oncology drug development, combined with the knowledge that most new therapies do not displace standard-of-care treatments and that many healthcare systems cannot afford these new therapies; cytotoxic chemotherapies will remain an important component of cancer therapy for many years to come. The clinical value of these therapies is often under-appreciated within the pre-clinical cancer research community, where this diverse class of agents are often grouped together as non-specific cellular poisons killing tumor cells based solely upon proliferation rate; however, this is inaccurate. This review article seeks to reaffirm the importance of focusing research efforts upon improving our basic understanding of how these drugs work, discussing their ability to target pan-essential pathways in cancer cells, the relationship of this to the chemotherapeutic window, and highlighting basic science approaches that can be employed towards refining their use.

Oncogene-like addiction to aneuploidy in human cancers

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses p53 signaling, and we show that TP53 mutations are mutually exclusive with 1q aneuploidy in human cancers. Thus, tumor cells can be dependent on specific aneuploidies, raising the possibility that these "aneuploidy addictions" could be targeted as a therapeutic strategy.

Identification, characterization, and prognosis investigation of pivotal genes shared in different stages of breast cancer

One of the leading causes of death (20.1 per 100,000 women per year), breast cancer is the most prevalent cancer in females. Statistically, 95% of breast cancer are categorized as adenocarcinomas, and 55% of all patients may go into invasive phases; however, it can be successfully treated in approximately 70-80% of cases if diagnosed in the nascent stages. The emergence of breast tumor cells which are intensely resistant to conventional therapies, along with the high rate of metastasis occurrence, has highlighted the importance of finding novel strategies and treatments. One of the most advantageous schemes to alleviate this complication is to identify the common differentially expressed genes (DEGs) among primary and metastatic cancerous cells to use resultants for designing new therapeutic agents which are able to target both primary and metastatic breast tumor cells. In this study, the gene expression dataset with accession number GSE55715 was analyzed containing two primary tumor samples, three bone-metastatic samples, and three normal samples to distinguish the up- and down regulated genes in each stage compared to normal cells as control. In the next step, the common upregulated genes between the two experimental groups were detected by Venny online tool. Moreover, gene ontology, functions and pathways, gene-targeting microRNA, and influential metabolites were determined using EnrichR 2021 GO, KEGG pathways miRTarbase 2017, and HMDB 2021, respectively. Furthermore, elicited from STRING protein-protein interaction networks were imported to Cytoscape software to identify the hub genes. Then, identified hub genes were checked to validate the study using oncological databases. The results of the present article disclosed 1263 critical common DEGs (573 upregulated + 690 downregulated), including 35 hub genes that can be broadly used as new targets for cancer treatment and as biomarkers for cancer detection by evaluation of expression level. Besides, this study opens a new horizon to reveal unknown aspects of cancer signaling pathways by providing raw data evoked from in silico experiments. This study's outcomes can also be widely utilized in further lab research since it contains diverse information on common DEGs of varied stages and metastases of breast cancer, their functions, structures, interactions, and associations.

BCL-G: 20 years of research on a non-typical protein from the BCL-2 family

Proteins from the BCL-2 family control cell survival and apoptosis in health and disease, and regulate apoptosis-unrelated cellular processes. BCL-Gonad (BCL-G, also known as BCL2-like 14) is a non-typical protein of the family as its long isoform (BCL-G_L) consists of BH2 and BH3 domains without the BH1 motif. BCL-G is predominantly expressed in normal testes and different organs of the gastrointestinal tract. The complexity of regulatory mechanisms of BCL-G expression and post-translational modifications suggests that BCL-G may play distinct roles in different types of cells and disorders. While several genetic alterations of BCL2L14 have been reported, gene deletions and amplifications prevail, which is also confirmed by the analysis of sequencing data for different types of cancer. Although the studies validating the phenotypic consequences of genetic manipulations of BCL-G are limited, the role of BCL-G in apoptosis has been undermined. Recent studies using gene-perturbation approaches have revealed apoptosis-unrelated functions of BCL-G in intracellular trafficking, immunomodulation, and regulation of the mucin scaffolding network. These studies were, however, limited mainly to the role of BCL-G in the gastrointestinal tract. Therefore, further efforts using state-of-the-art methods and various types of cells are required to find out more about BCL-G activities. Deciphering the isoform-specific functions of BCL-G and the BCL-G interactome may result in the designing of novel therapeutic approaches, in which BCL-G activity will be either imitated using small-molecule BH3 mimetics or inhibited to counteract BCL-G upregulation. This review summarizes two decades of research on BCL-G.

Euchromatic Histone Lysine Methyltransferase 2 Inhibition Enhances Carfilzomib Sensitivity and Overcomes Drug Resistance in Multiple Myeloma Cell Lines

Proteasome inhibitors (PIs) are extensively used for the therapy of multiple myeloma. However, patients continuously relapse or are intrinsically resistant to this class of drugs. In addition, adverse toxic effects such as peripheral neuropathy and cardiotoxicity could arise. Here, to identify compounds that can increase the efficacy of PIs, we performed a functional screening using a library of small-molecule inhibitors covering key signaling pathways. Among the best synthetic lethal interactions, the euchromatic histone-lysine N-methyltransferase 2 (EHMT2) inhibitor UNC0642 displayed a cooperative effect with carfilzomib (CFZ) in numerous multiple myeloma (MM) cell lines, including drug-resistant models. In MM patients, EHMT2 expression correlated to worse overall and progression-free survival. Moreover, EHMT2 levels were significantly increased in bortezomib-resistant patients. We demonstrated that CFZ/UNC0642 combination exhibited a favorable cytotoxicity profile toward peripheral blood mononuclear cells and bone-marrow-derived stromal cells. To exclude off-target effects, we proved that UNC0642 treatment reduces EHMT2-related molecular markers and that an alternative EHMT2 inhibitor recapitulated the synergistic activity with CFZ. Finally, we showed that the combinatorial treatment significantly perturbs autophagy and the DNA damage repair pathways, suggesting a multi-layered mechanism of action. Overall, the present study demonstrates that EHMT2 inhibition could provide a valuable strategy to enhance PI sensitivity and overcome drug resistance in MM patients.

Clinicopathological and prognostic value of lncRNA TPT1-AS1 in cancer: a systematic review study and meta-analysis

INTRODUCTION

Aberrant expression of lncRNAs in cancer cells can impact their key phenotypes. We aimed to summarize available evidence on clinicopathological and prognostic value of lncRNA TPT1-AS1 in cancer.

METHODS

A systematic search was performed on Medline and Embase databases using relevant key terms covering lncRNA TPT1-AS1, cancer, and clinical outcomes. The effect size estimates and their 95 % confidence interval (CI) were pooled using random-effects models. Meta- analyses were conducted using STATA 16.0 software.

RESULTS

Seventeen articles met our eligibility criteria. Tumor tissue compared to normal tissue showed increased level of lncRNA TPT1-AS1 expression (pooled standardized mean difference (95 % CI): 0.65 (0.52-0.79)). Overexpression of this lncRNA was a significant predictor for poor prognosis (Pooled log-rank test P-value < 0.001); in patients with high-level of lncRNA TPT1-AS1, the risk of death at five years was 1.40 times greater than their counterparts. The pooled Odds ratios for association lncRNA TPT1-AS1 with tumor stage, tumor size, and lymph node metastasis were 1.94 (95 % CI: 0.90-4.19, 8 studies, I² = 79.6 %), 2.33 (95 % CI: 1.31-4.14, 5 studies, I² = 40.0 %), and 1.89 (95 % CI: 1.08-3.36, 5 studies, I² = 61.7 %), respectively. Regarding the identified potential mechanisms, lncRNA TPT1-AS1 plays a role in cancer growth mainly by sponging miRNAs and regulating their downstream targets or controlling the expression of key cell cycle regulators.

CONCLUSION

In cancer patients, elevated expression of lncRNA TPT1-AS1 might be associated with a shorter Overall Survival, advanced stages, larger tumor size, and lymph node metastasis.

Oncogene-like addiction to aneuploidy in human cancers

Most cancers exhibit aneuploidy, but its functional significance in tumor development is controversial. Here, we describe ReDACT (Restoring Disomy in Aneuploid cells using CRISPR Targeting), a set of chromosome engineering tools that allow us to eliminate specific aneuploidies from cancer genomes. Using ReDACT, we created a panel of isogenic cells that have or lack common aneuploidies, and we demonstrate that trisomy of chromosome 1q is required for malignant growth in cancers harboring this alteration. Mechanistically, gaining chromosome 1q increases the expression of MDM4 and suppresses TP53 signaling, and we show that TP53 mutations are mutually-exclusive with 1q aneuploidy in human cancers. Thus, specific aneuploidies play essential roles in tumorigenesis, raising the possibility that targeting these "aneuploidy addictions" could represent a novel approach for cancer treatment.

The era of high-quality chemical probes

Small-molecule chemical probes are among the most important tools to study the function of proteins in cells and organisms. Regrettably, the use of weak and non-selective small molecules has generated an abundance of erroneous conclusions in the scientific literature. More recently, minimal criteria have been outlined for investigational compounds, encouraging the selection and use of high-quality chemical probes. Here, we briefly recall the milestones and key initiatives that have paved the way to this new era, illustrate examples of recent high-quality chemical probes and provide our perspective on future challenges and developments.

Interactive webtool for analyzing drug sensitivity and resistance associated with genetic signatures of cancer cell lines

Purpose

A wide therapeutic repertoire has become available to oncologists including radio- and chemotherapy, small molecules and monoclonal antibodies. However, drug efficacy can be limited by genetic heterogeneity. Here, we designed a webtool that facilitates the data analysis of the in vitro drug sensitivity data on 265 approved compounds from the GDSC database in association with a plethora of genetic changes documented for 1001 cell lines in the CCLE data.

Methods

The webtool computes odds ratios of drug resistance for a queried set of genetic alterations. It provides results on the efficacy of single compounds or groups of compounds assigned to cellular signaling pathways. Webtool availability: https://tools.hornlab.org/GDSC/.

Results

We first replicated established associations of genetic driver mutations in BRAF, RAS genes and EGFR with drug response. We then tested the ‘BRCAness’ hypothesis and did not find increased sensitivity to the assayed PARP inhibitors. Analyzing specific PIK3CA mutations related to cancer and mendelian overgrowth, we found support for the described sensitivity of H1047 mutants to GSK690693 targeting the AKT pathway. Testing a co-mutated gene pair, GATA3 activation abolished PTEN-related sensitivity to PI3K/mTOR inhibition. Finally, the pharmacogenomic modifier ABCB1 was associated with olaparib resistance.

Conclusions

This tool could identify potential drug candidates in the presence of custom sets of genetic changes and moreover, improve the understanding of signaling pathways. The underlying computer code can be adapted to larger drug response datasets to help structure and accommodate the increasingly large biomedical knowledge base.

Macromolecular crowding in the development of a three-dimensional organotypic human breast cancer model

Although cell-derived matrices are at the forefront of scientific research and technological innovation for the development of in vitro tumour models, their two-dimensional structure and low extracellular matrix composition restrict their capacity to accurately predict toxicity of candidate molecules. Herein, we assessed the potential of macromolecular crowding (a biophysical phenomenon that significantly enhances and accelerates extracellular matrix deposition, resulting in three-dimensional tissue surrogates) in improving cell-derived matrices in vitro tumour models. Among the various decellularisation protocols assessed (NH4OH, DOC, SDS/EDTA, NP40), the NP40 appeared to be the most effective in removing cellular matter and the least destructive to the deposited matrix. Among the various cell types (mammary, skin, lung fibroblasts) used to produce the cell-derived matrices, the mammary fibroblast derived matrices produced under macromolecular crowding conditions and decellularised with NP40 resulted in significant increase in focal adhesion molecules, matrix metalloproteinases and proinflammatory cytokines, when seeded with MDA-MB-231 cells. Further, macromolecular crowding derived matrices significantly increased doxorubicin resistance and reduced the impact of intracellular reactive oxygen species mediated cell death. Collectively our data clearly illustrate the potential of macromolecular crowding in the development of cell-derived matrices-based in vitro tumour models that more accurately resemble the tumour microenvironment.

Computational estimation of quality and clinical relevance of cancer cell lines

Immortal cancer cell lines (CCLs) are the most widely used system for investigating cancer biology and for the preclinical development of oncology therapies. Pharmacogenomic and genome‐wide editing screenings have facilitated the discovery of clinically relevant gene–drug interactions and novel therapeutic targets via large panels of extensively characterised CCLs. However, tailoring pharmacological strategies in a precision medicine context requires bridging the existing gaps between tumours and in vitro models. Indeed, intrinsic limitations of CCLs such as misidentification, the absence of tumour microenvironment and genetic drift have highlighted the need to identify the most faithful CCLs for each primary tumour while addressing their heterogeneity, with the development of new models where necessary. Here, we discuss the most significant limitations of CCLs in representing patient features, and we review computational methods aiming at systematically evaluating the suitability of CCLs as tumour proxies and identifying the best patient representative in vitro models. Additionally, we provide an overview of the applications of these methods to more complex models and discuss future machine‐learning‐based directions that could resolve some of the arising discrepancies.

Metabolic modeling-based drug repurposing in Glioblastoma

The manifestation of intra- and inter-tumor heterogeneity hinders the development of ubiquitous cancer treatments, thus requiring a tailored therapy for each cancer type. Specifically, the reprogramming of cellular metabolism has been identified as a source of potential drug targets. Drug discovery is a long and resource-demanding process aiming at identifying and testing compounds early in the drug development pipeline. While drug repurposing efforts (i.e., inspecting readily available approved drugs) can be supported by a mechanistic rationale, strategies to further reduce and prioritize the list of potential candidates are still needed to facilitate feasible studies. Although a variety of ‘omics’ data are widely gathered, a standard integration method with modeling approaches is lacking. For instance, flux balance analysis is a metabolic modeling technique that mainly relies on the stoichiometry of the metabolic network. However, exploring the network’s topology typically neglects biologically relevant information. Here we introduce Transcriptomics-Informed Stoichiometric Modelling And Network analysis (TISMAN) in a recombinant innovation manner, allowing identification and validation of genes as targets for drug repurposing using glioblastoma as an exemplar.

Validating Small Molecule Chemical Probes for Biological Discovery

Small molecule chemical probes are valuable tools for interrogating protein biological functions and relevance as a therapeutic target. Rigorous validation of chemical probe parameters such as cellular potency and selectivity is critical to unequivocally linking biological and phenotypic data resulting from treatment with a chemical probe to the function of a specific target protein. A variety of modern technologies are available to evaluate cellular potency and selectivity, target engagement, and functional response biomarkers of chemical probe compounds. Here, we review these technologies and the rationales behind using them for the characterization and validation of chemical probes. In addition, large-scale phenotypic characterization of chemical probes through chemical genetic screening is increasingly leading to a wealth of information on the cellular pharmacology and disease involvement of potential therapeutic targets. Extensive compound validation approaches and integration of phenotypic information will lay foundations for further use of chemical probes in biological discovery. Expected final online publication date for the Annual Review of Biochemistry, Volume 91 is June 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Genome-wide identification and analysis of prognostic features in human cancers

Clinical decisions in cancer rely on precisely assessing patient risk. To improve our ability to identify the most aggressive malignancies, we constructed genome-wide survival models using gene expression, copy number, methylation, and mutation data from 10,884 patients. We identified more than 100,000 significant prognostic biomarkers and demonstrate that these genomic features can predict patient outcomes in clinically ambiguous situations. While adverse biomarkers are commonly believed to represent cancer driver genes and promising therapeutic targets, we show that cancer features associated with shorter survival times are not enriched for either oncogenes or for successful drug targets. Instead, the strongest adverse biomarkers represent widely expressed cell-cycle and housekeeping genes, and, correspondingly, nearly all therapies directed against these features have failed in clinical trials. In total, our analysis establishes a rich resource for prognostic biomarker analysis and clarifies the use of patient survival data in preclinical cancer research and therapeutic development.

Regulation of ROCK1/2 by long non‑coding RNAs and circular RNAs in different cancer types (Review)

Recent breakthroughs in high-throughput technologies have enabled the development of a better understanding of the functionalities of rho-associated protein kinases (ROCKs) under various physiological and pathological conditions. Since their discovery in the late 1990s, ROCKs have attracted the attention of interdisciplinary researchers due to their ability to pleiotropically modulate a myriad of cellular mechanisms. A rapidly growing number of published studies have started to shed light on the mechanisms underlying the regulation of ROCK1 and ROCK2 via long non-coding RNAs (lncRNAs) and circular RNAs (circRNAs) in different types of cancer. Detailed analyses have suggested that lncRNAs may be characteristically divided into oncogenic and tumor suppressor lncRNAs. Several exciting recent discoveries have also indicated how different lncRNAs and circRNAs modulate ROCK1/2 and mediate multistep cancer onset and progression. The present review chronicles the major advances that have been made in our understanding of the regulatory role of ROCK1/2 in different types of cancer, and how wide-ranging lncRNAs and circRNAs potentiate ROCK-driven signaling by blocking the targeting activities of tumor suppressor microRNAs.

Illuminating lncRNA Function Through Target Prediction

Most of the transcribed human genome codes for noncoding RNAs (ncRNAs), and long noncoding RNAs (lncRNAs) make for the lion's share of the human ncRNA space. Despite growing interest in lncRNAs, because there are so many of them, and because of their tissue specialization and, often, lower abundance, their catalog remains incomplete and there are multiple ongoing efforts to improve it. Consequently, the number of human lncRNA genes may be lower than 10,000 or higher than 200,000. A key open challenge for lncRNA research, now that so many lncRNA species have been identified, is the characterization of lncRNA function and the interpretation of the roles of genetic and epigenetic alterations at their loci. After all, the most important human genes to catalog and study are those that contribute to important cellular functions-that affect development or cell differentiation and whose dysregulation may play a role in the genesis and progression of human diseases. Multiple efforts have used screens based on RNA-mediated interference (RNAi), antisense oligonucleotide (ASO), and CRISPR screens to identify the consequences of lncRNA dysregulation and predict lncRNA function in select contexts, but these approaches have unresolved scalability and accuracy challenges. Instead-as was the case for better-studied ncRNAs in the past-researchers often focus on characterizing lncRNA interactions and investigating their effects on genes and pathways with known functions. Here, we focus most of our review on computational methods to identify lncRNA interactions and to predict the effects of their alterations and dysregulation on human disease pathways.

Harnessing the predictive power of preclinical models for oncology drug development

Recent progress in understanding the molecular basis of cellular processes, identification of promising therapeutic targets and evolution of the regulatory landscape makes this an exciting and unprecedented time to be in the field of oncology drug development. However, high costs, long development timelines and steep rates of attrition continue to afflict the drug development process. Lack of predictive preclinical models is considered one of the key reasons for the high rate of attrition in oncology. Generating meaningful and predictive results preclinically requires a firm grasp of the relevant biological questions and alignment of the model systems that mirror the patient context. In doing so, the ability to conduct both forward translation, the process of implementing basic research discoveries into practice, as well as reverse translation, the process of elucidating the mechanistic basis of clinical observations, greatly enhances our ability to develop effective anticancer treatments. In this Review, we outline issues in preclinical-to-clinical translatability of molecularly targeted cancer therapies, present concepts and examples of successful reverse translation, and highlight the need to better align tumour biology in patients with preclinical model systems including tracking of strengths and weaknesses of preclinical models throughout programme development.

Precise Characterization of Genetic Interactions in Cancer via Molecular Network Refining Processes

Genetic interactions (GIs), such as the synthetic lethal interaction, are promising therapeutic targets in precision medicine. However, despite extensive efforts to characterize GIs by large-scale perturbation screening, considerable false positives have been reported in multiple studies. We propose a new computational approach for improved precision in GI identification by applying constraints that consider actual biological phenomena. In this study, GIs were characterized by assessing mutation, loss of function, and expression profiles in the DEPMAP database. The expression profiles were used to exclude loss-of-function data for nonexpressed genes in GI characterization. More importantly, the characterized GIs were refined based on Kyoto Encyclopedia of Genes and Genomes (KEGG) or protein–protein interaction (PPI) networks, under the assumption that genes genetically interacting with a certain mutated gene are adjacent in the networks. As a result, the initial GIs characterized with CRISPR and RNAi screenings were refined to 65 and 23 GIs based on KEGG networks and to 183 and 142 GIs based on PPI networks. The evaluation of refined GIs showed improved precision with respect to known synthetic lethal interactions. The refining process also yielded a synthetic partner network (SPN) for each mutated gene, which provides insight into therapeutic strategies for the mutated genes; specifically, exploring the SPN of mutated BRAF revealed ELAVL1 as a potential target for treating BRAF-mutated cancer, as validated by previous research. We expect that this work will advance cancer therapeutic research.

Chromosomal instability and aneuploidy as causes of cancer drug resistance

High levels of aneuploidy and chromosomal instability (CIN) are correlated with poor patient outcomes, though the mechanism(s) underlying this relationship have not been established. Recent evidence has demonstrated that chromosome copy number changes can function as point mutation-independent sources of drug resistance in cancer, which may partially explain this clinical association. CIN generates intratumoral heterogeneity in the form of gene dosage alterations, upon which the selective pressures induced by drug treatments can act. Thus, although CIN and aneuploidy impair cell fitness under most conditions, CIN can augment cellular adaptability, establishing CIN as a bet-hedging mechanism in tumor evolution. CIN may also endow cancers with unique vulnerabilities, which could be exploited therapeutically to achieve better patient outcomes.

MEIS2 Is an Adrenergic Core Regulatory Transcription Factor Involved in Early Initiation of TH-MYCN-Driven Neuroblastoma Formation

Simple Summary

Neuroblastoma is a pediatric tumor originating from the sympathetic nervous system responsible for 10–15% of all childhood cancer deaths. Half of all neuroblastoma patients present with high-risk disease, of which nearly 50% relapse and die of their disease. In addition, standard therapies cause serious lifelong side effects and increased risk for secondary tumors. Further research is crucial to better understand the molecular basis of neuroblastomas and to identify novel druggable targets. Neuroblastoma tumorigenesis has to this end been modeled in both mice and zebrafish. Here, we present a detailed dissection of the gene expression patterns that underlie tumor formation in the murine TH-MYCN-driven neuroblastoma model. We identified key factors that are putatively important for neuroblastoma tumor initiation versus tumor progression, pinpointed crucial regulators of the observed expression patterns during neuroblastoma development and scrutinized which factors could be innovative and vulnerable nodes for therapeutic intervention.

Abstract

Roughly half of all high-risk neuroblastoma patients present with MYCN amplification. The molecular consequences of MYCN overexpression in this aggressive pediatric tumor have been studied for decades, but thus far, our understanding of the early initiating steps of MYCN-driven tumor formation is still enigmatic. We performed a detailed transcriptome landscaping during murine TH-MYCN-driven neuroblastoma tumor formation at different time points. The neuroblastoma dependency factor MEIS2, together with ASCL1, was identified as a candidate tumor-initiating factor and shown to be a novel core regulatory circuit member in adrenergic neuroblastomas. Of further interest, we found a KEOPS complex member (gm6890), implicated in homologous double-strand break repair and telomere maintenance, to be strongly upregulated during tumor formation, as well as the checkpoint adaptor Claspin (CLSPN) and three chromosome 17q loci CBX2, GJC1 and LIMD2. Finally, cross-species master regulator analysis identified FOXM1, together with additional hubs controlling transcriptome profiles of MYCN-driven neuroblastoma. In conclusion, time-resolved transcriptome analysis of early hyperplastic lesions and full-blown MYCN-driven neuroblastomas yielded novel components implicated in both tumor initiation and maintenance, providing putative novel drug targets for MYCN-driven neuroblastoma.

Cancer testis antigens and genomic instability: More than immunology

Cancer testis antigens or genes (CTA, CTG) are predominantly expressed in adult testes while silenced in most or all somatic tissues with sporadic expression in many human cancers. Concerted misexpression of numerous CTA/CTGs is rarely observed. This finding argues against the germ cell theory of cancer. A surprising number of CTA/CTGs are involved in meiotic chromosome metabolism and specifically in meiotic recombination. Recent discoveries with a group of CTGs established that their misexpression in somatic cells results in genomic instability by interfering with homologous recombination (HR), a DNA repair pathway for complex DNA damage such as DNA double-stranded breaks, interstrand crosslinks, and single-stranded DNA gaps. HR-deficient tumors have specific vulnerabilities and show synthetic lethality with inhibition of polyADP-ribose polymerase, opening the possibility that expression of CTA/CTGs that result in an HR-defect could be used as an additional biomarker for HR status. Here, we review the repertoire of CTA/CTGs focusing on a cohort that functions in meiotic chromosome metabolism by interrogating relevant cancer databases and discussing recent discoveries.

Integrative oncogene-dependency mapping identifies RIT1 vulnerabilities and synergies in lung cancer

CRISPR-based cancer dependency maps are accelerating advances in cancer precision medicine, but adequate functional maps are limited to the most common oncogenes. To identify opportunities for therapeutic intervention in other rarer subsets of cancer, we investigate the oncogene-specific dependencies conferred by the lung cancer oncogene, RIT1. Here, genome-wide CRISPR screening in KRAS, EGFR, and RIT1-mutant isogenic lung cancer cells identifies shared and unique vulnerabilities of each oncogene. Combining this genetic data with small-molecule sensitivity profiling, we identify a unique vulnerability of RIT1-mutant cells to loss of spindle assembly checkpoint regulators. Oncogenic RIT1M90I weakens the spindle assembly checkpoint and perturbs mitotic timing, resulting in sensitivity to Aurora A inhibition. In addition, we observe synergy between mutant RIT1 and activation of YAP1 in multiple models and frequent nuclear overexpression of YAP1 in human primary RIT1-mutant lung tumors. These results provide a genome-wide atlas of oncogenic RIT1 functional interactions and identify components of the RAS pathway, spindle assembly checkpoint, and Hippo/YAP1 network as candidate therapeutic targets in RIT1-mutant lung cancer.

Synthetic Lethality in Cancer Therapeutics: The Next Generation

Synthetic lethality (SL) provides a conceptual framework for tackling targets that are not classically "druggable," including loss-of-function mutations in tumor suppressor genes required for carcinogenesis. Recent technological advances have led to an inflection point in our understanding of genetic interaction networks and ability to identify a wide array of novel SL drug targets. Here, we review concepts and lessons emerging from first-generation trials aimed at testing SL drugs, discuss how the nature of the targeted lesion can influence therapeutic outcomes, and highlight the need to develop clinical biomarkers distinct from those based on the paradigms developed to target activated oncogenes. SIGNIFICANCE: SL offers an approach for the targeting of loss of function of tumor suppressor and DNA repair genes, as well as of amplification and/or overexpression of genes that cannot be targeted directly. A next generation of tumor-specific alterations targetable through SL has emerged from high-throughput CRISPR technology, heralding not only new opportunities for drug development, but also important challenges in the development of optimal predictive biomarkers.

Non-viral nanoparticles for RNA interference: Principles of design and practical guidelines

Ribonucleic acid interference (RNAi) is an innovative treatment strategy for a myriad of indications. Non-viral synthetic nanoparticles (NPs) have drawn extensive attention as vectors for RNAi due to their potential advantages, including improved safety, high delivery efficiency and economic feasibility. However, the complex natural process of RNAi and the susceptible nature of oligonucleotides render the NPs subject to particular design principles and requirements for practical fabrication. Here, we summarize the requirements and obstacles for fabricating non-viral nano-vectors for efficient RNAi. To address the delivery challenges, we discuss practical guidelines for materials selection and NP synthesis in order to maximize RNA encapsulation efficiency and protection against degradation, and to facilitate the cytosolic release of oligonucleotides. The current status of clinical translation of RNAi-based therapies and further perspectives for reducing the potential side effects are also reviewed.

Assessing Consistency Across Functional Screening Datasets in Cancer Cells

Motivation

Many high-throughput screening studies have been carried out in cancer cell lines to identify therapeutic agents and targets. Existing consistency assessment studies only examined two datasets at a time, with conclusions based on a subset of carefully selected features rather than considering global consistency of all the data. However, poor concordance can still be observed for a large part of the data even when selected features are highly consistent.

Results

In this study, we assembled nine compound screening datasets and three functional genomics datasets. We derived direct measures of consistency as well as indirect measures of consistency based on association between functional data and copy number-adjusted gene expression data. These results have been integrated into a web application—the Functional Data Consistency Explorer (FDCE), to allow users to make queries and generate interactive visualizations so that functional data consistency can be assessed for individual features of interest.

Availability and implementation

The FDCE web tool and we have developed and the functional data consistency measures we have generated are available at https://lccl.shinyapps.io/FDCE/.

Supplementary information

Supplementary data are available at Bioinformatics online.

The Landscape of Signaling Pathways and Proteasome Inhibitors Combinations in Multiple Myeloma

Multiple myeloma is a malignancy of terminally differentiated plasma cells, characterized by an extreme genetic heterogeneity that poses great challenges for its successful treatment. Due to antibody overproduction, MM cells depend on the precise regulation of the protein degradation systems. Despite the success of PIs in MM treatment, resistance and adverse toxic effects such as peripheral neuropathy and cardiotoxicity could arise. To this end, the use of rational combinatorial treatments might allow lowering the dose of inhibitors and therefore, minimize their side-effects. Even though the suppression of different cellular pathways in combination with proteasome inhibitors have shown remarkable anti-myeloma activities in preclinical models, many of these promising combinations often failed in clinical trials. Substantial progress has been made by the simultaneous targeting of proteasome and different aspects of MM-associated immune dysfunctions. Moreover, targeting deranged metabolic hubs could represent a new avenue to identify effective therapeutic combinations with PIs. Finally, epigenetic drugs targeting either DNA methylation, histone modifiers/readers, or chromatin remodelers are showing pleiotropic anti-myeloma effects alone and in combination with PIs. We envisage that the positive outcome of patients will probably depend on the availability of more effective drug combinations and treatment of early MM stages. Therefore, the identification of sensitive targets and aberrant signaling pathways is instrumental for the development of new personalized therapies for MM patients.

Aneuploidy as a promoter and suppressor of malignant growth

Aneuploidy has been recognized as a hallmark of tumorigenesis for more than 100 years, but the connection between chromosomal errors and malignant growth has remained obscure. New evidence emerging from both basic and clinical research has illuminated a complicated relationship: despite its frequency in human tumours, aneuploidy is not a universal driver of cancer development and instead can exert substantial tumour-suppressive effects. The specific consequences of aneuploidy are highly context dependent and are influenced by a cell's genetic and environmental milieu. In this Review, we discuss the diverse facets of cancer biology that are shaped by aneuploidy, including metastasis, drug resistance and immune recognition, and we highlight aneuploidy's distinct roles as both a tumour promoter and an anticancer vulnerability.

CRISPRing future medicines

Introduction: The ability to engineer mammalian genomes in a quick and cost-effective way has led to rapid adaptation of CRISPR technology in biomedical research. CRISPR-based engineering has the potential to accelerate drug discovery, to support the reduction of high attrition rate in drug development and to enhance development of cell and gene-based therapies.Areas covered: How CRISPR technology is transforming drug discovery is discussed in this review. From target identification to target validation in both in vitro and in vivo models, CRISPR technology is positively impacting the early stages of drug development by providing a straightforward way to genome engineering. This property also attracted attention for CRISPR application in the cell and gene therapy area.Expert opinion: CRISPR technology is rapidly becoming the preferred tool for genome engineering and nowadays it is hard to imagine the drug discovery pipeline without this technology. With the years to come, CRISPR technology will undoubtedly be further refined and will flourish into a mature technology that will play a key role in supporting genome engineering requirements in the drug discovery pipeline as well as in cell and gene therapy development.

In Vitro Silencing of lncRNA Expression Using siRNAs

Recent advances in sequencing technologies have uncovered the existence of thousands of long noncoding RNAs (lncRNAs) with dysregulated expression in cancer. As a result, there is burgeoning interest in understanding their function and biological significance in both homeostasis and disease. RNA interference (RNAi) enables sequence-specific gene silencing and can, in principle, be employed to silence virtually any gene. However, when applied to lncRNAs, it is important to consider current limitations in their annotation and current principles regarding lncRNA regulation and function when assessing their phenotype in cancer cell lines. In this chapter we describe the analysis of lncRNA splicing variant expression, including subcellular localization, transfection of siRNAs in cancer cell lines, and validation of gene silencing by quantitative PCR and single molecule in situ hybridization. All protocols can be performed in a laboratory with essential equipment for cell culture, molecular biology, and imaging.

N-Terminal Acetyltransferases Are Cancer-Essential Genes Prevalently Upregulated in Tumours

N-terminal acetylation (Nt-Ac) is an abundant eukaryotic protein modification, deposited in humans by one of seven N-terminal acetyltransferase (NAT) complexes composed of a catalytic and potentially auxiliary subunits. The involvement of NATs in cancers is being increasingly recognised, but a systematic cross-tumour assessment is currently lacking. To address this limitation, we conducted here a multi-omic data interrogation for NATs. We found that tumour genomic alterations of NATs or of their protein substrates are generally rare events, with some tumour-specific exceptions. In contrast, altered gene expression of NATs in cancers and their association with patient survival constitute a widespread cancer phenomenon. Examination of dependency screens revealed that (i), besides NAA60 and NAA80 and the NatA paralogues NAA11 and NAA16, the other ten NAT genes were within the top 80th percentile of the most dependent genes (ii); NATs act through distinct biological processes. NAA40 (NatD) emerged as a NAT with particularly interesting cancer biology and therapeutic potential, especially in liver cancer where a novel oncogenic role was supported by its increased expression in multiple studies and its association with patient survival. In conclusion, this study generated insights and data that will be of great assistance in guiding further research into the function and therapeutic potential of NATs in cancer.