Next-generation sequencing in drug development: target identification and genetically stratified clinical trials

Advances in next-generation sequencing (NGS) applications in drug discovery and development

INTRODUCTION

Drug discovery is a complex and multifaceted process driven by scientific innovation and advanced technologies. Next-Generation Sequencing (NGS) platforms, encompassing both short-read and long-read technologies, have revolutionized the field by enabling the high-throughput and cost-effective analysis of DNA and RNA molecules. Continuous advancements in NGS-based technologies have enabled their seamless integration across preclinical and clinical workflows in drug discovery, encompassing early-stage drug target identification, candidate selection, genetically stratified clinical trials, and pharmacogenetic studies.

AREA COVERED

This review provides an overview of the current and potential applications of NGS-based technologies in drug discovery and development process, including their roles in novel drug target identification, high-throughput screening, clinical trials, and clinical medication studies. The review is based on literature retrieval from the PubMed and Web of Science databases between 2018 and 2024.

EXPERT OPINION

As technologies advance rapidly, NGS enhances accuracy and generates vast datasets. These datasets are extensively integrated with other heterogeneous data in systems biology and are mined using machine learning to extract significant insights, thereby driving progress in drug discovery.

Genetic Profiling of Acute and Chronic Leukemia via Next-Generation Sequencing: Current Insights and Future Perspectives

Leukemia is a heterogeneous group of hematologic malignancies characterized by distinct genetic and molecular abnormalities. Advancements in genomic technologies have significantly transformed the diagnosis, prognosis, and treatment strategies for leukemia. Among these, next-generation sequencing (NGS) has emerged as a powerful tool, enabling high-resolution genomic profiling that surpasses conventional diagnostic approaches. By providing comprehensive insights into genetic mutations, clonal evolution, and resistance mechanisms, NGS has revolutionized precision medicine in leukemia management. Despite its transformative potential, the clinical integration of NGS presents challenges, including data interpretation complexities, standardization issues, and cost considerations. However, continuous advancements in sequencing platforms and bioinformatics pipelines are enhancing the reliability and accessibility of NGS in routine clinical practice. The expanding role of NGS in leukemia is paving the way for improved risk stratification, targeted therapies, and real-time disease monitoring, ultimately leading to better patient outcomes. This review highlights the impact of NGS on leukemia research and clinical applications, discussing its advantages over traditional diagnostic techniques, key sequencing approaches, and emerging challenges. As precision oncology continues to evolve, NGS is expected to play an increasingly central role in the diagnosis and management of leukemia, driving innovations in personalized medicine and therapeutic interventions.

How Should we Teach Medicinal Chemistry in Higher Education to Prepare Students for a Future Career as Medicinal Chemists and Drug Designers? - A Teacher's Perspective

In the recent two decades, the multidisciplinary field of medicinal chemistry has undergone several conceptual and technology-driven paradigm changes with significant impact on the skill set medicinal chemists need to acquire during their education. Considering the need for academic medicinal chemistry teaching, this article aims at identifying important skills, competences, and basic knowledge as general learning outcomes based on an analysis of the relevant stakeholders and concludes effective teaching strategies preparing students for a future career as medicinal chemists and drug designers.

Accurate Detection of Multiple Tumor Mutations in Formalin-Fixed Paraffin-Embedded Tissues by Coupling Sequence Artifacts Elimination and Mutation Enrichment With MeltArray

Formalin-fixed paraffin-embedded (FFPE) tissues are the primary source of DNA for companion diagnostics (CDx) of cancers. Degradation of FFPE tissue DNA and inherent tumor heterogeneity constitute serious challenges in current CDx assays. To address these limitations, we introduced sequence artifact elimination and mutation enrichment to MeltArray, a highly multiplexed PCR approach, to establish an integrated protocol that provides accuracy, ease of use, and rapidness. Using PIK3CA mutations as a model, we established a MeltArray protocol that could eliminate sequence artifacts completely and enrich mutations from 23.5- to 59.4-fold via a single-reaction pretreatment step comprising uracil-DNA-glycosylase excision and PCR clamping. The entire protocol could identify 13 PIK3CA hotspot mutations of 0.05% to 0.5% mutant allele fractions within 5 hours. Evaluation of 106 breast cancer and 40 matched normal FFPE tissue samples showed that all 47 PIK3CA mutant samples were from the cancer tissue, and no false-positive results were detected in the normal samples. Further evaluation of 105 colorectal and 40 matched normal FFPE tissue samples revealed that 11 PIK3CA mutants were solely from the cancer sample. The detection results of our protocol were consistent with those of the droplet digital PCR assays that underwent sequence artifact elimination. Of the 60 colorectal samples with next-generation sequencing results, the MeltArray protocol detected 2 additional mutant samples with low mutant allele fractions. We conclude that the new protocol provides an improved alternative to current CDx assays for detecting tumor mutations in FFPE tissue DNA.

Assessment of Genetic Stability in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes by Using Droplet Digital PCR

Unintended genetic modifications that occur during the differentiation and proliferation of human induced pluripotent stem cells (hiPSCs) can lead to tumorigenicity. This is a crucial concern in the development of stem cell-based therapies to ensure the safety and efficacy of the final product. Moreover, conventional genetic stability testing methods are limited by low sensitivity, which is an issue that remains unsolved. In this study, we assessed the genetic stability of hiPSCs and hiPSC-derived cardiomyocytes using various testing methods, including karyotyping, CytoScanHD chip analysis, whole-exome sequencing, and targeted sequencing. Two specific genetic mutations in KMT2C and BCOR were selected from the 17 gene variants identified by whole-exome and targeted sequencing methods, which were validated using droplet digital PCR. The applicability of this approach to stem cell-based therapeutic products was further demonstrated with associated validation according to the International Council for Harmonisation (ICH) guidelines, including specificity, precision, robustness, and limit of detection. Our droplet digital PCR results showed high sensitivity and accuracy for quantitatively detecting gene mutations, whereas conventional qPCR could not avoid false positives. In conclusion, droplet digital PCR is a highly sensitive and precise method for assessing the expression of mutations with tumorigenic potential for the development of stem cell-based therapeutics.

RNA-seq RNAaccess identified as the preferred method for gene expression analysis of low quality FFPE samples

Clinical tumor tissues that are preserved as formalin-fixed paraffin-embedded (FFPE) samples result in extensive cross-linking, fragmentation, and chemical modification of RNA, posing significant challenges for RNA-seq-based gene expression profiling. This study sought to define an optimal RNA-seq protocol for FFPE samples. We employed a common RNA extraction method and then compared RNA-seq library preparation protocols including RNAaccess, RiboZero and PolyA in terms of sequencing quality and concordance of gene expression using FFPE and case-matched fresh-frozen (FF) triple-negative breast cancer (TNBC) tissues. We found that RNAaccess, a method based on exome capture, produced the most concordant results. Applying RNAaccess to FFPE gastric cancer tissues, we established a minimum RNA DV200 requirement of 10% and a RNA input amount of 10ng that generated highly reproducible gene expression data. Lastly, we demonstrated that RNAaccess and NanoString platforms produced highly concordant expression profiles from FFPE samples for shared genes; however, RNA-seq may be preferred for clinical biomarker discovery work because of the broader coverage of the transcriptome. Taken together, these results support the selection of RNA-seq RNAaccess method for gene expression profiling of FFPE samples. The minimum requirements for RNA quality and input established here may allow for inclusion of clinical FFPE samples of sub-optimal quality in gene expression analyses and ultimately increasing the statistical power of such analyses.

Public perspective on medications to delay Alzheimer's disease symptoms

Disease-modifying treatments for Alzheimer's disease are emerging. Our research examined how personal risk for AD may influence intentions to ask for medications to delay symptoms of AD, and how the availability of such medications impacts interest in AD-related genetic testing. Invitations to a web-based survey were posted on social media sites. Respondents were sequentially assigned to imagine that they had a 5%, 15%, or 35% chance of developing AD. They were then provided a hypothetical scenario describing a medication that delayed AD symptoms. After reporting intentions to ask for the medication, respondents were asked about their interest in genetic testing to predict AD risk. Data from 310 individuals were analyzed. Intentions to ask for a preventative medication were greater for respondents presented AD risks of 35% compared to risks of 15% and 5% (86% vs. 66% vs. 62%, respectively, p < 0.001). The proportion who would ask for genetic susceptibility testing increased from 58% to 79% when respondents were told to imagine that a medication that delayed AD symptoms existed (p < 0.001). Findings suggest that individuals who know they have an increased risk for AD are more likely pursue medications to delay onset of disease symptoms, and the availability of AD-delaying treatments will increase interest in associated genetic testing. Findings provide insight about who will pursue emerging preventative medications, including individuals for whom the medications may be inappropriate, and the impact on genetic test utilization.

NLRP3 mediates the neuroprotective effects of SVHRSP derived from scorpion venom in rotenone-induced experimental Parkinson's disease model

ETHNOPHARMACOLOGICAL RELEVANCE

In traditional Chinese medicine, scorpion is used to treat diseases with symptoms such as trembling, convulsion and dementia. Our laboratory employs patented technology to extract and purify the active single component from scorpion venom. We then utilize mass spectrometry to determine the amino acid sequence of the polypeptide and synthesize it artificially to acquire the polypeptide with a purity of 99.3%, named SVHRSP (Scorpion Venom Heat-Resistant Peptide). SVHRSP has been demonstrated to display potent neuroprotective efficacy in Parkinson's disease.

AIM OF THE STUDY

To explore the molecular mechanisms and potential molecular targets of SVHRSP-afforded neuroprotection in PD mouse models, as well as to investigate the role of NLRP3 in SVHRSP-mediated neuroprotection.

MATERIALS AND METHODS

The PD mouse model was induced by rotenone and the neuroprotective role of SVHRSP on the PD mouse model was measured using the gait test, rotarod test, the number of dopaminergic neurons, and the activation of microglia. RNA sequencing and GSEA analysis were performed to find the differentially biological pathways regulated by SVHRSP. Primary mid-brain neuron-glial cultures and NLRP3-/- mice were applied to verify the role of NLRP3 by using qRT-PCR, western blotting, enzyme-linked immunosorbent assay (ELISA) and immunostaining.

RESULTS

SVHRSP-afforded dopaminergic neuroprotection was accompanied with inhibition of microglia-mediated neuroinflammatory pathways. Importantly, depletion of microglia markedly reduced the neuroprotective efficacy of SVHRSP against rotenone-induced dopaminergic neurotoxicity in vitro. SVHRSP inhibited microglial NOD-like receptor pathway, mRNA expression and protein level of NLRP3 in rotenone PD mice. SVHRSP also reduced rotenone-induced caspse-1 activation and IL-1β maturation, indicating that SVHRSP mitigated activation of NLRP3 inflammasome. Moreover, inactivation of NLRP3 inflammasome by MCC950 or genetic deletion of NLRP3 almost abolished SVHRSP-afforded anti-inflammatory, neuroprotective effects and improvement of motor performance in response to rotenone.

CONCLUSIONS

NLRP3 mediated the neuroprotective effects of SVHRSP in rotenone-induced experimental PD model, providing additional evidence for the mechanisms of SVHRSP-afforded anti-inflammatory and neuroprotective effects in PD.

Discovery of dipeptidyl peptidase-4 inhibitor specific biomarker in NAFLD mouse models using modified basket trial

Background/Aims

We aimed to define an optimal target population and drug-specific biomarkers that may predict dipeptidyl peptidase (DPP)-4 inhibitor responses in non-alcoholic fatty liver disease (NAFLD).

Methods

An exploration study (study I) was performed using three different NAFLD models (basket study design; high-fat diet [HFD], methionine choline-deficient diet [MCD], and high-cholesterol Western diet [WD] models). RNA transcriptome analysis was performed on pre-studied liver tissues to identify biomarkers that could predict the response to DPP-4 inhibitors. In the validation study (study II), the HFD-induced NAFLD model was divided into high and low hepatic insulin-like growth factor binding protein 1 (Igfbp-1) groups based on the pre-study liver biopsy.

Results

DPP-4 inhibitor attenuated the NAFLD activity score and fibrosis stage in the HFD model but not in the WD and MCD models. The overall response rate was 19% across the modified basket NAFLD trial and 42%, 25%, and 0% in the HFD, WD, and MCD models. Hepatic Igfbp-1 expression was higher in the responder group than in the non-responder group in pre-study biopsy samples. In contrast, hepatic Igfbp-1 expression was lower in the responder group than in the non-responder group in the end-study biopsy samples. DPP-4 inhibitor response rates were 83% and 17% in the baseline hepatic high Igfbp-1 and low Igfbp-1 groups, respectively. Hepatic messenger RNA Igfbp-1 expression was positively correlated with serum IGFBP-1 levels.

Conclusions

The DPP-4 inhibitor response was higher in the HFD phenotype and pre-treatment levels of hepatic or serum IGFBP-1 were high.

Application of Organoids in Carcinogenesis Modeling and Tumor Vaccination

Organoids well recapitulate organ-specific functions from their tissue of origin and remain fundamental aspects of organogenesis. Organoids are widely applied in biomedical research, drug discovery, and regenerative medicine. There are various cultivated organoid systems induced by adult stem cells and pluripotent stem cells, or directly derived from primary tissues. Researchers have drawn inspiration by combination of organoid technology and tissue engineering to produce organoids with more physiological relevance and suitable for translational medicine. This review describes the value of applying organoids for tumorigenesis modeling and tumor vaccination. We summarize the application of organoids in tumor precision medicine. Extant challenges that need to be conquered to make this technology be more feasible and precise are discussed.

Understanding the Transcriptomic Landscape to Drive New Innovations in Musculoskeletal Regenerative Medicine

PURPOSE OF REVIEW

RNA-sequencing (RNA-seq) is a novel and highly sought-after tool in the field of musculoskeletal regenerative medicine. The technology is being used to better understand pathological processes, as well as elucidate mechanisms governing development and regeneration. It has allowed in-depth characterization of stem cell populations and discovery of molecular mechanisms that regulate stem cell development, maintenance, and differentiation in a way that was not possible with previous technology. This review introduces RNA-seq technology and how it has paved the way for advances in musculoskeletal regenerative medicine.

RECENT FINDINGS

Recent studies in regenerative medicine have utilized RNA-seq to decipher mechanisms of pathophysiology and identify novel targets for regenerative medicine. The technology has also advanced stem cell biology through in-depth characterization of stem cells, identifying differentiation trajectories and optimizing cell culture conditions. It has also provided new knowledge that has led to improved growth factor use and scaffold design for musculoskeletal regenerative medicine. This article reviews recent studies utilizing RNA-seq in the field of musculoskeletal regenerative medicine. It demonstrates how transcriptomic analysis can be used to provide insights that can aid in formulating a regenerative strategy.

Companion Diagnostics: State of the Art and New Regulations

Companion diagnostics (CDx) hail promise of improving the drug development process and precision medicine. However, there are various challenges involved in the clinical development and regulation of CDx, which are considered high-risk in vitro diagnostic medical devices given the role they play in therapeutic decision-making and the complications they may introduce with respect to their sensitivity and specificity. The European Union (E.U.) is currently in the process of bringing into effect in vitro Diagnostic Medical Devices Regulation (IVDR). The new Regulation is introducing a wide range of stringent requirements for scientific validity, analytical and clinical performance, as well as on post-market surveillance activities throughout the lifetime of in vitro diagnostics (IVD). Compliance with General Safety and Performance Requirements (GSPRs) adopts a risk-based approach, which is also the case for the new classification system. This changing regulatory framework has an impact on all stakeholders involved in the IVD Industry, including Authorized Representatives, Distributors, Importers, Notified Bodies, and Reference Laboratories and is expected to have a significant effect on the development of new CDx.

Immune checkpoints and immunotherapy in non-small cell lung cancer: Novel study progression, challenges and solutions

Lung cancer is the most common type of cancer with the highest mortality rate worldwide. Non-small cell lung cancer (NSCLC) accounts for ~85% of the total number of lung cancer cases. In the past two decades, immunotherapy has become a more promising treatment method than traditional treatments (surgery, radiotherapy and chemotherapy). Immunotherapy has been shown to improve the survival rate of patients and to have a superior effect when controlling lung cancer than traditional therapy. However, only a small number of patients can benefit from immunotherapy, and not all patients who qualify experience long-term benefits. In the clinic, the objective response rate of programmed cell death protein 1 treatment without the prior screening of patients is only 15-20%. Immunotherapy is associated with both opportunities and challenges for patients with NSCLC. The current challenges of immunotherapy include the lack of accurate biomarkers, inevitable resistance and insufficient understanding of immune checkpoints. In previous years, several methods for overcoming the challenges posed by immunotherapy have been proposed, but combination therapy is the most suitable choice. A large number of studies have shown that the combination of drugs can significantly improve their efficacy, compared with monotherapy, and that some therapeutic combinations have been approved by the Food and Drug Administration for the treatment of NSCLC. Traditional Chinese medicine (TCM) is a traditional medical practice in China that can play an important role in immunotherapy. Most agents used in TCM originate from plants, and have the advantages of low toxicity and multiple targets. In addition, TCM includes a unique class of drugs that can improve autoimmunity. Therefore, TCM may be a promising treatment method for all types of cancer.

Heterologous expression of a natural product biosynthetic gene cluster from Cordyceps militaris

Cordyceps is a genus of ascomycete fungi widely used in old Chinese medicine, and many investigations have focus on uncovering their biological activities. Until now, only a few compounds have been identified from Cordyceps, mainly due to their poor yield. So as to make full use of Cordyceps, we used the strategy of genome mining and heterologous expression to discover natural products (NPs) from Cordyceps militaris. Analysis of the genome sequence of Cordyceps militaris CM01 showed the presence of a cryptic gene cluster encoding a highly-reducing polyketide synthetase (HR-PKS), enoyl-reductase (ER) and cytochrome P450. Heterologous expression in Aspergillus nidulans enabled the identification of two new polyketides, cordypyrone A and B. Their structures were determined by 1D and 2D NMR techniques. They showed only modest activities against pathogenic bacteria including methicillin-resistant Staphylococcus aureus (MRSA), Mycobacteria tuberculosis and Bacillus cereus.

Next-Generation Sequencing in Clinical Practice: Is It a Cost-Saving Alternative to a Single-Gene Testing Approach?

OBJECTIVES

This study aimed to compare the costs of a next-generation sequencing-based (NGS-based) panel testing strategy to those of a single-gene testing-based (SGT-based) strategy, considering different scenarios of clinical practice evolution.

METHODS

Three Italian hospitals were analysed, and four different testing pathways (paths 1, 2, 3, and 4) were identified: two for advanced non-small-cell lung cancer (aNSCLC) patients and two for unresectable metastatic colon-rectal cancer (mCRC) patients. For each path, we explored four scenarios considering the current clinical practice and its expected evolution. The 16 testing cases (4 scenarios × 4 paths) were then compared in terms of differential costs between the NGS-based and SGT-based approaches considering personnel, consumables, equipment, and overhead costs. Break-even and sensitivity analyses were performed. Data gathering, aimed at identifying the hospital setup, was performed through a semi-structured questionnaire administered to the professionals involved in testing activities.

RESULTS

The NGS-based strategy was found to be a cost-saving alternative to the SGT-based strategy in 15 of the 16 testing cases. The break-even threshold, the minimum number of patients required to make the NGS-based approach less costly than the SGT-based approach, varied across the testing cases depending on molecular alterations tested, techniques adopted, and specific costs. The analysis found the NGS-based approach to be less costly than the SGT-based approach in nine of the 16 testing cases at any volume of tests performed; in six cases, the NGS-based approach was found to be less costly above a threshold (and in one case, it was found to be always more expensive). Savings obtained using an NGS-based approach ranged from €30 to €1249 per patient; in the unique testing case where NGS was more costly, the additional cost per patient was €25.

CONCLUSIONS

An NGS-based approach may be less costly than an SGT-based approach; also, generated savings increase with the number of patients and different molecular alterations tested.

High-throughput organ-on-chip platform with integrated programmable fluid flow and real-time sensing for complex tissue models in drug development workflows

Drug development suffers from a lack of predictive and human-relevant in vitro models. Organ-on-chip (OOC) technology provides advanced culture capabilities to generate physiologically appropriate, human-based tissue in vitro, therefore providing a route to a predictive in vitro model. However, OOC technologies are often created at the expense of throughput, industry-standard form factors, and compatibility with state-of-the-art data collection tools. Here we present an OOC platform with advanced culture capabilities supporting a variety of human tissue models including liver, vascular, gastrointestinal, and kidney. The platform has 96 devices per industry standard plate and compatibility with contemporary high-throughput data collection tools. Specifically, we demonstrate programmable flow control over two physiologically relevant flow regimes: perfusion flow that enhances hepatic tissue function and high-shear stress flow that aligns endothelial monolayers. In addition, we integrate electrical sensors, demonstrating quantification of barrier function of primary gut colon tissue in real-time. We utilize optical access to the tissues to directly quantify renal active transport and oxygen consumption via integrated oxygen sensors. Finally, we leverage the compatibility and throughput of the platform to screen all 96 devices using high content screening (HCS) and evaluate gene expression using RNA sequencing (RNA-seq). By combining these capabilities in one platform, physiologically-relevant tissues can be generated and measured, accelerating optimization of an in vitro model, and ultimately increasing predictive accuracy of in vitro drug screening.

Co-Therapy of Albendazole and Dexamethasone Reduces Pathological Changes in the Cerebral Parenchyma of Th-1 and Th-2 Dominant Mice Heavily Infected with Angiostrongylus cantonensis: Histopathological and RNA-seq Analyses

Administration of albendazole alone was not very suitable for the treatment of cerebral angiostrongyliasis. This study was designed to evaluate the effects of the co-therapy of this drug and dexamethasone in Th-1 and Th-2 dominant mice infected with Angiostrongylus cantonensis. Each of BALB/c and C57BL/6 mice infected with 50 A. cantonensis third-stage larvae were administered albendazole (10 mg/kg/day) alone, dexamethasone (0.5 mg/kg/day) alone, or co-therapy of the two drugs from day 7 or 14 post-infection for 7 or 14 days. After sacrifice, coronal slices were prepared from five brain regions and stained with hematoxylin and eosin. Eight pathological changes were employed to determine the therapeutic effectiveness using a scoring system. RNA-seq analysis was performed to confirm the histopathological findings. The infected BALB/c and C57BL/6 mice had similar patterns in the pathological changes. Meningitis, hemorrhage, size of worms, and encephalitis in the cerebral parenchyma were slighter in the mice treated with co-therapy than the remaining groups. Mice treated from day 14 had more severe changes than those from day 7. The histopathological findings were found to be consistent to immune responses determined by RNA-seq analysis. Co-therapy was determined to reduce pathological changes after administration to mice infected with A. cantonensis.

Deep learning in next-generation sequencing

Next-generation sequencing (NGS) methods lie at the heart of large parts of biological and medical research. Their fundamental importance has created a continuously increasing demand for processing and analysis methods of the data sets produced, addressing questions such as variant calling, metagenomic classification and quantification, genomic feature detection, or downstream analysis in larger biological or medical contexts. In addition to classical algorithmic approaches, machine-learning (ML) techniques are often used for such tasks. In particular, deep learning (DL) methods that use multilayered artificial neural networks (ANNs) for supervised, semisupervised, and unsupervised learning have gained significant traction for such applications. Here, we highlight important network architectures, application areas, and DL frameworks in a NGS context.

Predictors of early progression after curative resection followed by platinum-based adjuvant chemoradiotherapy in oral cavity squamous cell carcinoma

OBJECTIVES

Early progression, defined as a disease-free interval (DFI) of less than 6 months after completion of adjuvant platinum-based chemoradiotherapy (CRT), leads to poor outcomes in locally advanced oral cavity squamous cell carcinoma (OCSCC). However, appropriate biomarkers for predicting early progression remain unknown.

METHODS

In this study, 346 patients with OCSCC, who underwent curative surgical resection and platinum-based adjuvant CRT at the Taipei Veterans General Hospital (202 patients, training cohort) and Chung Shan Medical University Hospital (144 patients, validation cohort) were enrolled. The clinical-pathological variables were compared using the χ² test. Cox proportional-hazards analyses were performed for DFIs. Survival was estimated using the Kaplan-Meier method and log-rank tests, and a scoring system for predicting early progression was established.

RESULTS

One-fifth (20.5%, 71/346) of all patients experienced progression within 6 months. Each of the independent factors for the DFI in the training cohort, including pT3-4, extracapsular spread, and perineural invasion, were assigned a score of one point to establish a scoring system. The 6-month DFIs of the low-risk (score 0-1), intermediate-risk (score 2), and high-risk (score 3) groups were 97.8%, 78.7%, and 35.7% and 88.2%, 77.6%, and 42.1% in the training and validation cohorts, respectively. If the cutoff level was ≥2 or <2, the sensitivity/specificity/area under the curve for the training and validation cohorts were 94.4%/56.1%/0.837, and 73.3%/56.6%/0.703, respectively.

CONCLUSIONS

The established scoring system effectively predicted early progression after adjuvant CRT for locally advanced OCSCC.

PhosphoEffect: Prioritizing Variants On or Adjacent to Phosphorylation Sites through Their Effect on Kinase Recognition Motifs

Phosphorylation sites often have key regulatory functions and are central to many cellular signaling pathways, so mutations that modify them have the potential to contribute to pathological states such as cancer. Although many classifiers exist for prioritization of coding genomic variants, to our knowledge none of them explicitly account for the alteration or creation of kinase recognition motifs that alter protein structure, function, regulation of activity, and interaction networks through modifying the pattern of phosphorylation. We present a novel computational pipeline that uses a random forest classifier to predict the pathogenicity of a variant, according to its direct or indirect effect on local phosphorylation sites and the predicted functional impact of perturbing a phosphorylation event. We call this classifier PhosphoEffect and find that it compares favorably and with increased accuracy to the existing classifier PolyPhen 2.2.2 when tested on a dataset of known variants enriched for phosphorylation sites and their neighbors.

Involvement of Differentially Expressed microRNAs in the PEGylated Liposome Encapsulated 188Rhenium-Mediated Suppression of Orthotopic Hypopharyngeal Tumor

Hypopharyngeal cancer (HPC) accounts for the lowest survival rate among all types of head and neck cancers (HNSCC). However, the therapeutic approach for HPC still needs to be investigated. In this study, a theranostic ¹⁸⁸Re-liposome was prepared to treat orthotopic HPC tumors and analyze the deregulated microRNA expressive profiles. The therapeutic efficacy of ¹⁸⁸Re-liposome on HPC tumors was evaluated using bioluminescent imaging followed by next generation sequencing (NGS) analysis, in order to address the deregulated microRNAs and associated signaling pathways. The differentially expressed microRNAs were also confirmed using clinical HNSCC samples and clinical information from The Cancer Genome Atlas (TCGA) database. Repeated doses of ¹⁸⁸Re-liposome were administrated to tumor-bearing mice, and the tumor growth was apparently suppressed after treatment. For NGS analysis, 13 and 9 microRNAs were respectively up-regulated and down-regulated when the cutoffs of fold change were set to 5. Additionally, miR-206-3p and miR-142-5p represented the highest fold of up-regulation and down-regulation by ¹⁸⁸Re-liposome, respectively. According to Differentially Expressed MiRNAs in human Cancers (dbDEMC) analysis, most of ¹⁸⁸Re-liposome up-regulated microRNAs were categorized as tumor suppressors, while down-regulated microRNAs were oncogenic. The KEGG pathway analysis showed that cancer-related pathways and olfactory and taste transduction accounted for the top pathways affected by ¹⁸⁸Re-liposome. ¹⁸⁸Re-liposome down-regulated microRNAs, including miR-143, miR-6723, miR-944, and miR-136 were associated with lower survival rates at a high expressive level. ¹⁸⁸Re-liposome could suppress the HPC tumors in vivo, and the therapeutic efficacy was associated with the deregulation of microRNAs that could be considered as a prognostic factor.

The Effect of Substituted Benzene-Sulfonamides and Clinically Licensed Drugs on the Catalytic Activity of CynT2, a Carbonic Anhydrase Crucial for Escherichia coli Life Cycle

Proteins are relevant antimicrobial drug targets, and among them, enzymes represent a significant group, since most of them catalyze reactions essential for supporting the central metabolism, or are necessary for the pathogen vitality. Genomic exploration of pathogenic and non-pathogenic microorganisms has revealed genes encoding for a superfamily of metalloenzymes, known as carbonic anhydrases (CAs, EC 4.2.1.1). CAs catalyze the physiologically crucial reversible reaction of the carbon dioxide hydration to bicarbonate and protons. Herein, we investigated the sulfonamide inhibition profile of the recombinant β-CA (CynT2) identified in the genome of the Gram-negative bacterium Escherichia coli. This biocatalyst is indispensable for the growth of the microbe at atmospheric pCO₂. Surprisingly, this enzyme has not been investigated for its inhibition with any class of CA inhibitors. Here, we show that CynT2 was strongly inhibited by some substituted benzene-sulfonamides and the clinically used inhibitor sulpiride (K_Is in the range of 82–97 nM). This study may be relevant for identifying novel CA inhibitors, as well as for another essential part of the drug discovery pipeline, such as the structure–activity relationship for this class of enzyme inhibitors.

Next Generation Sequencing and Machine Learning Technologies Are Painting the Epigenetic Portrait of Glioblastoma

Even with a rare occurrence of only 1.35% of cancer cases in the United States of America, brain tumors are considered as one of the most lethal malignancies. The most aggressive and invasive type of brain tumor, glioblastoma, accounts for 60–70% of all gliomas and presents with life expectancy of only 12–18 months. Despite trimodal treatment and advances in diagnostic and therapeutic methods, there are no significant changes in patient outcome. Our understanding of glioblastoma was significantly improved with the introduction of next generation sequencing technologies. This led to the identification of different genetic and molecular subtypes, which greatly improve glioblastoma diagnosis. Still, because of the poor life expectancy, novel diagnostic, and treatment methods are broadly explored. Epigenetic modifications like methylation and changes in histone acetylation are such examples. Recently, in addition to genetic and molecular characteristics, epigenetic profiling of glioblastomas is also used for sample classification. Further advancement of next generation sequencing technologies is expected to identify in detail the epigenetic signature of glioblastoma that can open up new therapeutic opportunities for glioblastoma patients. This should be complemented with the use of computational power i.e., machine and deep learning algorithms for objective diagnostics and design of individualized therapies. Using a combination of phenotypic, genotypic, and epigenetic parameters in glioblastoma diagnostics will bring us closer to precision medicine where therapies will be tailored to suit the genetic profile and epigenetic signature of the tumor, which will grant longer life expectancy and better quality of life. Still, a number of obstacles including potential bias, availability of data for minorities in heterogeneous populations, data protection, and validation and independent testing of the learning algorithms have to be overcome on the way.

Transcriptomics analysis of pericytes from retinas of diabetic animals reveals novel genes and molecular pathways relevant to blood-retinal barrier alterations in diabetic retinopathy

Selective pericyte loss, the histological hallmark of early diabetic retinopathy (DR), enhances the breakdown of the blood-retinal barrier (BRB) in diabetes. However, the role of pericytes on BRB alteration in diabetes and the signaling pathways involved in their effects are currently unknown. To understand the role of diabetes-induced molecular alteration of pericytes, we performed transcriptomic analysis of sorted retinal pericytes from mice model of diabetes. Retinal tissue from non-diabetic and diabetic (duration 3 months) mouse eyes (n = 10 in each group) were used to isolate pericytes through fluorescent activated cell sorting (FACS) using pericyte specific fluorescent antibodies, PDGFRb-APC. For RNA sequencing and qPCR analysis, a cDNA library was generated using template switching oligo and the resulting libraries were sequenced using paired-end Illumina sequencing. Molecular functional pathways were analyzed using differentially expressed genes (DEGs). Differential expression analysis revealed 217 genes significantly upregulated and 495 genes downregulated, in pericytes isolated from diabetic animals. These analyses revealed a core set of differentially expressed genes that could potentially contribute to the pericyte dysfunction in diabetes and highlighted the pattern of functional connectivity between key candidate genes and blood retinal barrier alteration mechanisms. The top up-regulated gene list included: Ext2, B3gat3, Gpc6, Pip5k1c and Pten and down-regulated genes included: Notch3, Xbp1, Gpc4, Atp1a2 and AKT3. Out of these genes, we further validated one of the down regulated genes, Notch 3 and its role in BRB alteration in diabetic retinopathy. We confirmed the downregulation of Notch3 expression in human retinal pericytes exposed to Advanced Glycation End-products (AGEs) treatment mimicking the chronic hyperglycemia effect. Exploration of pericyte-conditioned media demonstrated that loss of NOTCH3 in pericyte led to increased permeability of endothelial cell monolayers. Collectively, we identify a role for NOTCH3 in pericyte dysfunction in diabetes. Further validation of other DEGs to identify cell specific molecular change through whole transcriptomic approach in diabetic retina will provide novel insight into the pathogenesis of DR and novel therapeutic targets.

Disclosing genetic risk for Alzheimer's dementia to individuals with mild cognitive impairment

INTRODUCTION

The safety of predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) dementia using apolipoprotein E (APOE) genotyping is unknown.

METHODS

We randomized 114 individuals with MCI to receive estimates of 3-year risk of conversion to AD dementia informed by APOE genotyping (disclosure arm) or not (non-disclosure arm) in a non-inferiority clinical trial. Primary outcomes were anxiety and depression scores. Secondary outcomes included other psychological measures.

RESULTS

Upper confidence limits for randomization arm differences were 2.3 on the State Trait Anxiety Index and 0.5 on the Geriatric Depression Scale, below non-inferiority margins of 3.3 and 1.0. Moreover, mean scores were lower in the disclosure arm than non-disclosure arm for test-related positive impact (difference: -1.9, indicating more positive feelings) and AD concern (difference: -0.3).

DISCUSSION

Providing genetic information to individuals with MCI about imminent risk for AD does not increase risks of anxiety or depression and may provide psychological benefits.

Disentangling the genetics of sarcopenia: prioritization of NUDT3 and KLF5 as genes for lean mass & HLA-DQB1-AS1 for hand grip strength with the associated enhancing SNPs & a scoring system

BACKGROUND

Sarcopenia is a skeletal muscle disease of clinical importance that occurs commonly in old age and in various disease sub-categories. Widening the scope of knowledge of the genetics of muscle mass and strength is important because it may allow to identify patients with an increased risk to develop a specific musculoskeletal disease or condition such as sarcopenia based on genetic markers.

METHODS

We used bioinformatics tools to identify gene loci responsible for regulating muscle strength and lean mass, which can then be a target for downstream lab experimentation validation. Single nuclear polymorphisms (SNPs) associated with various disease traits of muscles and specific genes were chosen according to their muscle phenotype association p-value, as traditionally done in Genome Wide Association Studies, GWAS. We've developed and applied a combination of expression quantitative trait loci (eQTLs) and GWAS summary information, to prioritize causative SNP and point out the unique genes associated in the tissues of interest (muscle).

RESULTS

We found NUDT3 and KLF5 for lean mass and HLA-DQB1-AS1 for hand grip strength as candidate genes to target for these phenotypes. The associated regulatory SNPs are rs464553, rs1028883 and rs3129753 respectively.

CONCLUSION

Transcriptome Wide Association Studies, TWAS, approaches of combining GWAS and eQTL summary statistics proved helpful in statistically prioritizing genes and their associated SNPs for the disease phenotype of study, in this case, Sarcopenia. Potentially regulatory SNPs associated with these genes, and the genes further prioritized by a scoring system, can be then wet lab verified, depending on the phenotype it is hypothesized to affect.

Transcriptomic Validation of the Protective Effects of Aqueous Bark Extract of Terminalia arjuna (Roxb.) on Isoproterenol-Induced Cardiac Hypertrophy in Rats

Aqueous extract of the bark of Terminalia arjuna (TA) is used by a large population in the Indian subcontinent for treating various cardiovascular conditions. Animal experiments have shown its anti-atherogenic, anti-hypertensive, and anti-inflammatory effects. It has several bioactive ingredients with hemodynamic, ROS scavenging, and anti-inflammatory properties. Earlier we have done limited proteomic and transcriptomic analysis to show its efficacy in ameliorating cardiac hypertrophy induced by isoproterenol (ISO) in rats. In the present study we have used high-throughput sequencing of the mRNA from control and treated rat heart to further establish its efficacy. ISO (5 mg/kg/day s.c.) was administered in male adult rats for 14 days to induce cardiac hypertrophy. Standardized aqueous extract TA bark extract was administered orally. Total RNA were isolated from control, ISO, ISO + TA, and TA treated rat hearts and subjected to high throughput sequence analysis. The modulations of the transcript levels were then subjected to bio-informatics analyses using established software. Treatment with ISO downregulated 1,129 genes and upregulated 204 others. Pre-treatment with the TA bark extracts markedly restored that expression pattern with only 97 genes upregulated and 85 genes downregulated. The TA alone group had only 88 upregulated and 26 downregulated genes. The overall profile of expression in ISO + TA and TA alone groups closely matched with the control group. The genes that were modulated included those involved in metabolism, activation of receptors and cell signaling, and cardiovascular and other diseases. Networks associated with those genes included those involved in angiogenesis, extracellular matrix organization, integrin binding, inflammation, drug metabolism, redox metabolism, oxidative phosphorylation, and organization of myofibril. Overlaying of the networks in ISO and ISO_TA group showed that those activated in ISO group were mostly absent in ISO_TA and TA group, suggesting a global effect of the TA extracts. This study for the first time reveals that TA partially or completely restores the gene regulatory network perturbed by ISO treatment in rat heart; signifying its efficacy in checking ISO-induced cardiac hypertrophy.

An omics perspective on drug target discovery platforms

The drug discovery process starts with identification of a disease-modifying target. This critical step traditionally begins with manual investigation of scientific literature and biomedical databases to gather evidence linking molecular target to disease, and to evaluate the efficacy, safety and commercial potential of the target. The high-throughput and affordability of current omics technologies, allowing quantitative measurements of many putative targets (e.g. DNA, RNA, protein, metabolite), has exponentially increased the volume of scientific data available for this arduous task. Therefore, computational platforms identifying and ranking disease-relevant targets from existing biomedical data sources, including omics databases, are needed. To date, more than 30 drug target discovery (DTD) platforms exist. They provide information-rich databases and graphical user interfaces to help scientists identify putative targets and pre-evaluate their therapeutic efficacy and potential side effects. Here we survey and compare a set of popular DTD platforms that utilize multiple data sources and omics-driven knowledge bases (either directly or indirectly) for identifying drug targets. We also provide a description of omics technologies and related data repositories which are important for DTD tasks.

Target discovery using biobanks and human genetics

Large-scale biobanks can yield unprecedented insights into our health and provide discoveries of new and potentially targetable biomarkers. Several protective loss-of-function alleles have been identified, including variants that protect against cardiovascular disease, obesity, type 2 diabetes, and asthma and allergic diseases. These alleles serve as indicators of efficacy, mimicking the effects of drugs and suggesting that inhibiting these genes could provide therapeutic benefit, as has been observed for PCSK9. We provide a context for these findings through a multifaceted review covering the use of genetics in drug discovery efforts through genome-wide and phenome-wide association studies, linking deep mutation scanning data to molecular function and highlighting some additional tools that might help in the interpretation of newly discovered variants.

Factors Affecting Combination Trial Success (FACTS): Investigator Survey Results on Early-Phase Combination Trials

Experimental therapeutic oncology agents are often combined to circumvent tumor resistance to individual agents. However, most combination trials fail to demonstrate sufficient safety and efficacy to advance to a later phase. This study collected survey data on phase 1 combination therapy trials identified from ClinicalTrials.gov between January 1, 2003 and November 30, 2017 to assess trial design and the progress of combinations toward regulatory approval. Online surveys (N = 289, 23 questions total) were emailed to Principal Investigators (PIs) of early-phase National Cancer Institute and/or industry trials; 263 emails (91%) were received and 113 surveys completed (43%). Among phase 1 combination trials, 24.9% (95%CI: 15.3%, 34.4%) progressed to phase 2 or further; 18.7% (95%CI: 5.90%, 31.4%) progressed to phase 3 or regulatory approval; and 12.4% (95%CI: 0.00%, 25.5%) achieved regulatory approval. Observations of “clinical promise” in phase 1 combination studies were associated with higher rates of advancement past each milestone toward regulatory approval (cumulative OR = 11.9; p = 0.0002). Phase 1 combination study designs were concordant with Clinical Trial Design Task Force (CTD-TF) Recommendations 79.6% of the time (95%CI: 72.2%, 87.1%). Most discordances occurred where no plausible pharmacokinetic or pharmacodynamic interactions were expected. Investigator-defined “clinical promise” of a combination is associated with progress toward regulatory approval. Although concordance between study designs of phase 1 combination trials and CTD-TF Recommendations was relatively high, it may be beneficial to raise awareness about the best study design to use when no plausible pharmacokinetic or pharmacodynamic interactions are expected.

The growing role of precision and personalized medicine for cancer treatment

Cancer is a devastating disease that takes the lives of hundreds of thousands of people every year. Due to disease heterogeneity, standard treatments, such as chemotherapy or radiation, are effective in only a subset of the patient population. Tumors can have different underlying genetic causes and may express different proteins in one patient versus another. This inherent variability of cancer lends itself to the growing field of precision and personalized medicine (PPM). There are many ongoing efforts to acquire PPM data in order to characterize molecular differences between tumors. Some PPM products are already available to link these differences to an effective drug. It is clear that PPM cancer treatments can result in immense patient benefits, and companies and regulatory agencies have begun to recognize this. However, broader changes to the healthcare and insurance systems must be addressed if PPM is to become part of standard cancer care.