Restraining Network Response to Targeted Cancer Therapies Improves Efficacy and Reduces Cellular Resistance

HSP90: A promising target for NSCLC treatments

The emergence of targeted therapies and immunotherapies has improved the overall survival of patients with nonsmall cell lung cancer (NSCLC), but the 5-year survival rate remains low. New drugs are needed to overcome this dilemma. Moreover, the significant correlation between various client proteins of heat-shock protein (HSP) 90 and tumor occurrence, progression, and drug resistance suggests that HSP90 is a potential therapeutic target for NSCLC. However, the outcomes of clinical trials for HSP90 inhibitors have been disappointing, indicating significant toxicity of these drugs and that further screening of the beneficiary population is required. NSCLC patients with oncogenic-driven gene mutations or those at advanced stages who are resistant to multi-line treatments may benefit from HSP90 inhibitors. Enhancing the therapeutic efficacy and reducing the toxicity of HSP90 inhibitors can be achieved via the optimization of their drug structure, using them in combination therapies with low-dose HSP90 inhibitors and other drugs, and via targeted administration to tumor lesions. Here, we provide a review of the recent research on the role of HSP90 in NSCLC and summarize relevant studies of HSP90 inhibitors in NSCLC.

Comprehensive multi-omics analysis reveals m7G-related signature for evaluating prognosis and immunotherapy efficacy in osteosarcoma

Background

Osteosarcoma is one of the most prevalent bone malignancies with a poor prognosis. The N7-methylguanosine (m7G) modification facilitates the modification of RNA structure and function tightly associated with cancer. Nonetheless, there is a lack of joint exploration of the relationship between m7G methylation and immune status in osteosarcoma.

Methods

With the support of TARGET and GEO databases, we performed consensus clustering to characterize molecular subtypes based on m7G regulators in all osteosarcoma patients. The least absolute shrinkage and selection operator (LASSO) method, Cox regression, and receiver operating characteristic (ROC) curves were employed to construct and validate m7G-related prognostic features and derived risk scores. In addition, GSVA, ssGSEA, CIBERSORT, ESTIMATE, and gene set enrichment analysis were conducted to characterize biological pathways and immune landscapes. We explored the relationship between risk scores and drug sensitivity, immune checkpoints, and human leukocyte antigens by correlation analysis. Finally, the roles of EIF4E3 in cell function were verified through external experiments.

Results

Two molecular isoforms based on regulator genes were identified, which presented significant discrepancies in terms of survival and activated pathways. Moreover, the six m7G regulators most associated with prognosis in osteosarcoma patients were identified as independent predictors for the construction of prognostic signature. The model was well stabilized and outperformed traditional clinicopathological features to reliably predict 3-year (AUC = 0.787) and 5-year (AUC = 0.790) survival in osteosarcoma cohorts. Patients with increased risk scores had a poorer prognosis, higher tumor purity, lower checkpoint gene expression, and were in an immunosuppressive microenvironment. Furthermore, enhanced expression of EIF4E3 indicated a favorable prognosis and affected the biological behavior of osteosarcoma cells.

Conclusions

We identified six prognostic relevant m7G modulators that may provide valuable indicators for the estimation of overall survival and the corresponding immune landscape in patients with osteosarcoma.

A targeted genetic modifier screen in Drosophila uncovers vulnerabilities in a genetically complex model of colon cancer

Received on 16 January 2023; accepted on 21 February 2023Kinases are key regulators of cellular signal transduction pathways. Many diseases, including cancer, are associated with global alterations in protein phosphorylation networks. As a result, kinases are frequent targets of drug discovery efforts. However, target identification and assessment, a critical step in targeted drug discovery that involves identifying essential genetic mediators of disease phenotypes, can be challenging in complex, heterogeneous diseases like cancer, where multiple concurrent genomic alterations are common. Drosophila is a particularly useful genetic model system to identify novel regulators of biological processes through unbiased genetic screens. Here, we report 2 classic genetic modifier screens focusing on the Drosophila kinome to identify kinase regulators in 2 different backgrounds: KRAS TP53 PTEN APC, a multigenic cancer model that targets 4 genes recurrently mutated in human colon tumors and KRAS alone, a simpler model that targets one of the most frequently altered pathways in cancer. These screens identified hits unique to each model and one shared by both, emphasizing the importance of capturing the genetic complexity of human tumor genome landscapes in experimental models. Our follow-up analysis of 2 hits from the KRAS-only screen suggests that classical genetic modifier screens in heterozygous mutant backgrounds that result in a modest, nonlethal reduction in candidate gene activity in the context of a whole animal-a key goal of systemic drug treatment-may be a particularly useful approach to identify the most rate-limiting genetic vulnerabilities in disease models as ideal candidate drug targets.

Mutational signatures and processes in hepatobiliary cancers

The evolutionary history of hepatobiliary cancers is embedded in their genomes. By analysing their catalogue of somatic mutations and the DNA sequence context in which they occur, it is possible to infer the mechanisms underpinning tumorigenesis. These mutational signatures reflect the exogenous and endogenous origins of genetic damage as well as the capacity of hepatobiliary cells to repair and replicate DNA. Genomic analysis of thousands of patients with hepatobiliary cancers has highlighted the diversity of mutagenic processes active in these malignancies, highlighting a prominent source of the inter-cancer-type, inter-patient, intertumour and intratumoural heterogeneity that is observed clinically. However, a substantial proportion of mutational signatures detected in hepatocellular carcinoma and biliary tract cancer remain of unknown cause, emphasizing the important contribution of processes yet to be identified. Exploiting mutational signatures to retrospectively understand hepatobiliary carcinogenesis could advance preventative management of these aggressive tumours as well as potentially predict treatment response and guide the development of therapies targeting tumour evolution.

Nek2 Kinase Signaling in Malaria, Bone, Immune and Kidney Disorders to Metastatic Cancers and Drug Resistance: Progress on Nek2 Inhibitor Development

Cell cycle kinases represent an important component of the cell machinery that controls signal transduction involved in cell proliferation, growth, and differentiation. Nek2 is a mitotic Ser/Thr kinase that localizes predominantly to centrosomes and kinetochores and orchestrates centrosome disjunction and faithful chromosomal segregation. Its activity is tightly regulated during the cell cycle with the help of other kinases and phosphatases and via proteasomal degradation. Increased levels of Nek2 kinase can promote centrosome amplification (CA), mitotic defects, chromosome instability (CIN), tumor growth, and cancer metastasis. While it remains a highly attractive target for the development of anti-cancer therapeutics, several new roles of the Nek2 enzyme have recently emerged: these include drug resistance, bone, ciliopathies, immune and kidney diseases, and parasitic diseases such as malaria. Therefore, Nek2 is at the interface of multiple cellular processes and can influence numerous cellular signaling networks. Herein, we provide a critical overview of Nek2 kinase biology and discuss the signaling roles it plays in both normal and diseased human physiology. While the majority of research efforts over the last two decades have focused on the roles of Nek2 kinase in tumor development and cancer metastasis, the signaling mechanisms involving the key players associated with several other notable human diseases are highlighted here. We summarize the efforts made so far to develop Nek2 inhibitory small molecules, illustrate their action modalities, and provide our opinion on the future of Nek2-targeted therapeutics. It is anticipated that the functional inhibition of Nek2 kinase will be a key strategy going forward in drug development, with applications across multiple human diseases.

Bridging the explanatory gaps: What can we learn from a biological agency perspective?

We begin this article by delineating the explanatory gaps left by prevailing gene-focused approaches in our understanding of phenotype determination, inheritance, and the origin of novel traits. We aim not to diminish the value of these approaches but to highlight where their implementation, despite best efforts, has encountered persistent limitations. We then discuss how each of these explanatory gaps can be addressed by expanding research foci to take into account biological agency-the capacity of living systems at various levels to participate in their own development, maintenance, and function by regulating their structures and activities in response to conditions they encounter. Here we aim to define formally what agency and agents are and-just as importantly-what they are not, emphasizing that agency is an empirical property connoting neither intention nor consciousness. Lastly, we discuss how incorporating agency helps to bridge explanatory gaps left by conventional approaches, highlight scientific fields in which implicit agency approaches are already proving valuable, and assess the opportunities and challenges of more systematically incorporating biological agency into research programs.

Evolution of kinase polypharmacology across HSP90 drug discovery

Most small molecules interact with several target proteins but this polypharmacology is seldom comprehensively investigated or explicitly exploited during drug discovery. Here, we use computational and experimental methods to identify and systematically characterize the kinase cross-pharmacology of representative HSP90 inhibitors. We demonstrate that the resorcinol clinical candidates ganetespib and, to a lesser extent, luminespib, display unique off-target kinase pharmacology as compared with other HSP90 inhibitors. We also demonstrate that polypharmacology evolved during the optimization to discover luminespib and that the hit, leads, and clinical candidate all have different polypharmacological profiles. We therefore recommend the computational and experimental characterization of polypharmacology earlier in drug discovery projects to unlock new multi-target drug design opportunities.

Drosophila RASopathy models identify disease subtype differences and biomarkers of drug efficacy

RASopathies represent a family of mostly autosomal dominant diseases that are caused by missense variants in the rat sarcoma viral oncogene/mitogen activated protein kinase (RAS/MAPK) pathway including KRAS, NRAS, BRAF, RAF1, and SHP2. These variants are associated with overlapping but distinct phenotypes that affect the heart, craniofacial, skeletal, lymphatic, and nervous systems. Here, we report an analysis of 13 Drosophila transgenic lines, each expressing a different human RASopathy isoform. Similar to their human counterparts, each Drosophila line displayed common aspects but also important differences including distinct signaling pathways such as the Hippo and SAPK/JNK signaling networks. We identified multiple classes of clinically relevant drugs-including statins and histone deacetylase inhibitors-that improved viability across most RASopathy lines; in contrast, several canonical RAS pathway inhibitors proved less broadly effective. Overall, our study compares and contrasts a large number of RASopathy-associated variants including their therapeutic responses.

Drug discovery and chemical probing in Drosophila

Flies are increasingly utilized in drug discovery and chemical probing in vivo, which are novel technologies complementary to genetic probing in fundamental biological studies. Excellent genetic conservation, small size, short generation time, and over one hundred years of genetics make Drosophila an attractive model for rapid assay readout and use of analytical amounts of compound, enabling the experimental iterations needed in early drug development at a fraction of time and costs. Here, we describe an effective drug-testing pipeline using adult flies that can be easily implemented to study several disease models and different genotypes to discover novel molecular insight, probes, quality lead compounds, and develop novel prototype drugs.

Translating Cancer Molecular Variability into Personalized Information Using Bulk and Single Cell Approaches

Cancer research is striving toward new frontiers of assigning the correct personalized drug(s) to a given patient. However, extensive tumor heterogeneity poses a major obstacle. Tumors of the same type often respond differently to therapy, due to patient-specific molecular aberrations and/or untargeted tumor subpopulations. It is frequently not possible to determine a priori which patients will respond to a certain therapy or how an efficient patient-specific combined therapy should be designed. Large-scale datasets have been growing at an accelerated pace and various technologies and analytical tools for single cell and bulk level analyses are being developed to extract significant individualized signals from such heterogeneous data. However, personalized therapies that dramatically alter the course of the disease remain scarce, and most tumors still respond poorly to medical care. In this review, the basic concepts of bulk and single cell approaches are discussed, as well as their emerging role in individualized designs of drug therapies, including the advantages and limitations of their applications in personalized medicine.

Synthetic lethality: A promising therapeutic strategy for hepatocellular carcinoma

Hepatocellular carcinoma (HCC), the main cause of liver cancer-related death, is one of the main cancers in terms of incidence and mortality. However, HCC is difficult to target and develops strong drug resistance. Therefore, a new treatment strategy is urgently needed. The clinical application of the concept of synthetic lethality in recent years provides a new therapeutic direction for the accurate treatment of HCC. Here, we introduce the concept of synthetic lethality, the screening used to study synthetic lethality, and the identified and potential genetic interactions that induce synthetic lethality in HCC. In addition, we propose opportunities and challenges for translating synthetic lethal interactions to the clinical treatment of HCC.

Drug screening in Drosophila; why, when, and when not?

The best global seller among oncology drugs in 2018 is lenalidomide, an analog of thalidomide. It took 53 years and a circuitous route from the discovery of thalidomide to approval of an analog for use in treatment of cancer. We understand now a lot more about the genetic and molecular basis of diseases than we did in 1953 when thalidomide was discovered. We have also no shortage of chemical libraries with hundreds of thousands of compounds, both synthetic and natural. What we need are better ways to search among these rich resources for compounds with the potential to do what we want them to do. This review summarizes examples from the literature that make Drosophila melanogaster a good model to screen for drugs, and discusses knowledge gaps and technical challenges that make Drosophila models not as widely used as they could or should be. This article is categorized under: Technologies > Analysis of Cell, Tissue, and Animal Phenotypes.

Integrated computational and Drosophila cancer model platform captures previously unappreciated chemicals perturbing a kinase network

Drosophila provides an inexpensive and quantitative platform for measuring whole animal drug response. A complementary approach is virtual screening, where chemical libraries can be efficiently screened against protein target(s). Here, we present a unique discovery platform integrating structure-based modeling with Drosophila biology and organic synthesis. We demonstrate this platform by developing chemicals targeting a Drosophila model of Medullary Thyroid Cancer (MTC) characterized by a transformation network activated by oncogenic dRet^M955T. Structural models for kinases relevant to MTC were generated for virtual screening to identify unique preliminary hits that suppressed dRet^M955T-induced transformation. We then combined features from our hits with those of known inhibitors to create a ‘hybrid’ molecule with improved suppression of dRet^M955T transformation. Our platform provides a framework to efficiently explore novel kinase inhibitors outside of explored inhibitor chemical space that are effective in inhibiting cancer networks while minimizing whole body toxicity.

Effective and safe treatment of multigenic diseases often involves drugs that address multiple points along disease networks, i.e., polypharmacology. Polypharmacology is increasingly appreciated as a potentially desirable property of kinase drugs. However, most known drugs that interact with multiple targets have been identified as such by chance and most polypharmacological compounds are not chemically unique, resembling structures of known kinase inhibitors. The fruit fly Drosophila provides an inexpensive, rapid, quantitative, whole animal screening platform that has the potential to complement computational approaches. We present a chemical genetics approach that efficiently combines Drosophila with structural prediction and virtual screening, creating a unique discovery platform. We demonstrate the utility of our approach by developing useful small molecules targeting a kinase network in a Drosophila model of Medullary Thyroid Cancer (MTC) driven by oncogenic dRet^M955T.

A Drosophila Based Cancer Drug Discovery Framework

In recent years, there has been growing interest in using Drosophila for drug discovery as it provides a unique opportunity to screen small molecules against complex disease phenotypes in a whole animal setting. Furthermore, gene-compound interaction experiments that combine compound feeding with complex genetic manipulations enable exploration of compound mechanisms of response and resistance to an extent that is difficult to achieve in other experimental models. Here, I discuss how compound screening and testing approaches reported in Drosophila fit into the current cancer drug discovery pipeline. I then propose a framework for a Drosophila-based cancer drug discovery strategy which would allow the Drosophila research community to effectively leverage the power of Drosophila to identify candidate therapeutics and push our discoveries into the clinic.

Drosophila melanogaster as a Model System for Human Glioblastomas

Glioblastoma multiforme (GBM) is the most common primary malignant adult brain tumor. Genomic amplifications, activating mutations, and overexpression of receptor tyrosine kinases (RTKs) such as EGFR, and genes in core RTK signaling transduction pathways such as PI3K are common in GBM. However, efforts to target these pathways have been largely unsuccessful in the clinic, and the median survival of GBM patients remains poor at 14-15 months. Therefore, to improve patient outcomes, there must be a concerted effort to elucidate the underlying biology involved in GBM tumorigenesis. Drosophila melanogaster has been a highly effective model for furthering our understanding of GBM tumorigenesis due to a number of experimental advantages it has over traditional mouse models. For example, there exists extensive cellular and genetic homology between humans and Drosophila, and 75% of genes associated with human disease have functional fly orthologs. To take advantage of these traits, we developed a Drosophila GBM model with constitutively active variants of EGFR and PI3K that effectively recapitulated key aspects of GBM disease. Researchers have utilized this model in forward genetic screens and have expanded on its functionality to make a number of important discoveries regarding requirements for key components in GBM tumorigenesis, including genes and pathways involved in extracellular matrix signaling, glycolytic metabolism, invasion/migration, stem cell fate and differentiation, and asymmetric cell division. Drosophila will continue to reveal novel biological pathways and mechanisms involved in gliomagenesis, and this knowledge may contribute to the development of effective treatment strategies to improve patient outcomes.