Multi-Omics Analysis of Glioblastoma Cells' Sensitivity to Oncolytic Viruses

Both intrinsic and microenvironmental factors contribute to the regulation of stem cell quiescence

Precise regulation of stem cell quiescence is essential for tissue development and homeostasis. Therefore, its aberrant regulation is intimately correlated with various human diseases. However, the detailed mechanisms of stem cell quiescence and its specific role in the pathogenesis of various diseases remain to be determined. Recent studies have revealed that the intrinsic and microenvironmental factors are the potential candidates responsible for the orderly switch between the dormant and activated states of stem cells. In addition, defects in signaling pathways related to internal and external factors of stem cells might contribute to the initiation and development of diseases by altering the dormancy of stem cells. In this review, we focus on the mechanisms underlying stem cell quiescence, especially the involvement of intrinsic and microenvironmental factors. In addition, we discuss the relationship between the anomalies of stem cell quiescence and related diseases, hopefully providing therapeutic insights for developing novel treatments.

Polyamine Catabolism Revisited: Acetylpolyamine Oxidase Plays a Minor Role due to Low Expression

Biogenic polyamines are ubiquitous compounds. Dysregulation of their metabolism is associated with the development of various pathologies, including cancer, hyperproliferative diseases, and infections. The canonical pathway of polyamine catabolism includes acetylation of spermine and spermidine and subsequent acetylpolyamine oxidase (PAOX)-mediated oxidation of acetylpolyamines (back-conversion) or their direct efflux from the cell. PAOX is considered to catalyze a non-rate-limiting catabolic step. Here, we show that PAOX transcription levels are extremely low in various tumor- and non-tumor cell lines and, in most cases, do not change in response to altered polyamine metabolism. Its enzymatic activity is undetectable in the majority of cell lines except for neuroblastoma and low passage glioblastoma cell lines. Treatment of A549 cells with N1,N11-diethylnorspermine leads to PAOX induction, but its contribution to polyamine catabolism remains moderate. We also describe two alternative enzyme isoforms and show that isoform 4 has diminished oxidase activity and isoform 2 is inactive. PAOX overexpression correlates with the resistance of cancer cells to genotoxic antitumor drugs, indicating that PAOX may be a useful therapeutic target. Finally, PAOX is dispensable for the replication of various viruses. These data suggest that a decrease in polyamine levels is achieved predominantly by the secretion of acetylated spermine and spermidine rather than by back-conversion.

[Investigation of oncolytic potential of vaccine strains of yellow fever and tick-borne encephalitis viruses against glioblastoma and pancreatic carcinoma cell lines]

INTRODUCTION

Flaviviruses, possessing natural neurotropicity could be used in glioblastoma therapy using attenuated strains or as a delivery system for antitumor agents in an inactivated form.

OBJECTIVE

To investigate the sensitivity of glioblastoma and pancreatic carcinoma cell lines to vaccine strains of yellow fever and tick-borne encephalitis viruses.

MATERIALS AND METHODS

Cell lines: glioblastoma GL-6, T98G, LN-229, pancreatic carcinoma MIA RaCa-2 and human pancreatic ductal carcinoma PANC-1. Viral strains: 17D yellow fever virus (YF), Sofjin tick-borne encephalitis virus (TBEV). Virus concentration were determined by plaque assay and quantitative PCR. Determination of cell sensitivity to viruses by MTT assay.

RESULTS

17D YF was effective only against pancreatic carcinoma tumor cells MIA Paca-2 and had a limited effect against PANC-1. In glioblastoma cell lines (LN229, GL6, T98G), virus had no oncolytic effect and the viral RNA concentration fell in the culture medium. Sofjin TBEV showed CPE50 against MIA Paca-2 and a very limited cytotoxic effect against PANC-1. However, it had no oncolytic effect against glioblastoma cell lines (LN229, T98G and GL6), although virus reproduction continued in these cultures. For the GL6 glioblastoma cell line, the viral RNA concentration at the level with the infection dose was determined within 13 days, despite medium replacement, while in the case of the LN229 cell line, the virus concentration increased from 1 × 109 to 1 × 1010 copies/ml.

CONCLUSION

Tumor behavior in organism is more complex and is determined by different microenvironmental factors and immune status. In the future, it is advisable to continue studying the antitumor oncolytic and immunomodulatory effects of viral strains 17D YF and Sofjin TBEV using in vivo models.

Oncolytic Viruses in the Era of Omics, Computational Technologies, and Modeling: Thesis, Antithesis, and Synthesis

Oncolytic viruses (OVs) are the frontier therapy for refractory cancers, especially in integration with immunomodulation strategies. In cancer immunovirotherapy, the many available "omics" and systems biology technologies generate at a fast pace a challenging huge amount of data, where apparently clashing information mirrors the complexity of individual clinical situations and OV used. In this review, we present and discuss how currently big data analysis, on one hand and, on the other, simulation, modeling, and computational technologies, provide invaluable support to interpret and integrate "omic" information and drive novel synthetic biology and personalized OV engineering approaches for effective immunovirotherapy. Altogether, these tools, possibly aided in the future by artificial intelligence as well, will allow for the blending of the information into OV recombinants able to achieve tumor clearance in a patient-tailored way. Various endeavors to the envisioned "synthesis" of turning OVs into personalized theranostic agents are presented.

Unwinding the SARS-CoV-2 Ribosomal Frameshifting Pseudoknot with LNA and G-Clamp-Modified Phosphorothioate Oligonucleotides Inhibits Viral Replication

Ribosomal frameshifting (RFS) at the slippery site of SARS-CoV-2 RNA is essential for the biosynthesis of the viral replication machinery. It requires the formation of a pseudoknot (PK) structure near the slippery site and can be inhibited by PK-disrupting oligonucleotide-based antivirals. We obtained and compared three types of such antiviral candidates, namely locked nucleic acids (LNA), LNA-DNA gapmers, and G-clamp-containing phosphorothioates (CPSs) complementary to PK stems. Using optical and electrophoretic methods, we showed that stem 2-targeting oligonucleotide analogs induced PK unfolding at nanomolar concentrations, and this effect was particularly pronounced in the case of LNA. For the leading PK-unfolding LNA and CPS oligonucleotide analogs, we also demonstrated dose-dependent RSF inhibition in dual luciferase assays (DLAs). Finally, we showed that the leading oligonucleotide analogs reduced SARS-CoV-2 replication at subtoxic concentrations in the nanomolar range in two human cell lines. Our findings highlight the promise of PK targeting, illustrate the advantages and limitations of various types of DNA modifications and may promote the future development of oligonucleotide-based antivirals.

A new strategy for treating colorectal cancer: Regulating the influence of intestinal flora and oncolytic virus on interferon

Colorectal cancer (CRC) has the third highest incidence and the second highest mortality in the world, which seriously affects human health, while current treatments methods for CRC, including systemic therapy, preoperative radiotherapy, and surgical local excision, still have poor survival rates for patients with metastatic disease, making it critical to develop new strategies for treating CRC. In this article, we found that the gut microbiota can modulate the signaling pathways of cancer cells through direct contact with tumor cells, generate inflammatory responses and oxidative stress through interactions between the innate and adaptive immune systems, and produce diverse metabolic combinations to trigger specific immune responses and promote the initiation of systemic type I interferon (IFN-I) and anti-viral immunity. In addition, oncolytic virus-mediated immunotherapy for regulating oncolytic virus can directly lyse tumor cells, induce the immune activity of the body, interact with interferon, inhibit the anti-viral effect of IFN-I, and enhance the anti-tumor effect of IFN-II. Interferon plays an important role in the anti-tumor process. We put forward that exploring the effects of intestinal flora and oncolytic virus on interferon to treat CRC is a promising therapeutic option.

IQMMA: Efficient MS1 Intensity Extraction Pipeline Using Multiple Feature Detection Algorithms for DDA Proteomics

One of the key steps in data dependent acquisition (DDA) proteomics is detection of peptide isotopic clusters, also called "features", in MS1 spectra and matching them to MS/MS-based peptide identifications. A number of peptide feature detection tools became available in recent years, each relying on its own matching algorithm. Here, we provide an integrated solution, the intensity-based Quantitative Mix and Match Approach (IQMMA), which integrates a number of untargeted peptide feature detection algorithms and returns the most probable intensity values for the MS/MS-based identifications. IQMMA was tested using available proteomic data acquired for both well-characterized (ground truth) and real-world biological samples, including a mix of Yeast and E. coli digests spiked at different concentrations into the Human K562 digest used as a background, and a set of glioblastoma cell lines. Three open-source feature detection algorithms were integrated: Dinosaur, biosaur2, and OpenMS FeatureFinder. None of them was found optimal when applied individually to all the data sets employed in this work; however, their combined use in IQMMA improved efficiency of subsequent protein quantitation. The software implementing IQMMA is freely available at https://github.com/PostoenkoVI/IQMMA under Apache 2.0 license.

Proteomics-based scoring of cellular response to stimuli for improved characterization of signaling pathway activity

Omics technologies focus on uncovering the complex nature of molecular mechanisms in cells and organisms, including biomarkers and drug targets discovery. Aiming at these tasks, we see that information extracted from omics data is still underused. In particular, characteristics of differentially regulated molecules can be combined in a single score to quantify the signaling pathway activity. Such a metric can be useful for comprehensive data interpretation to follow: (1) developing molecular responses in time; (2) potency of a drug on a certain cell culture; (3) ranking the signaling pathway activity in stimulated cells; and (4) integration of the omics data and assay-based measurements of cell viability, cytotoxicity, and proliferation. With recent advances in ultrafast mass spectrometry for quantitative proteomics allowing data collection in a few minutes, proteomics score for cellular response to stimuli can become a fast, accurate, and informative complement to bioassays. Here, we utilized an interquartile-based selection of differentially regulated features and a variety of schemes for quantifying cellular responses to come up with the quantitative metric for total cellular response and pathway activity. Validation was performed using antiproliferative and virus assays and label-free proteomics data collected for cancer cells subjected to drug stimulation.

The emerging field of oncolytic virus-based cancer immunotherapy

Oncolytic viruses (OVs) provide novel and promising therapeutic options for patients with cancers resistant to traditional therapies. Natural or genetically modified OVs are multifaceted tumor killers. They directly lyse tumor cells while sparing normal cells, and indirectly potentiate antitumor immunity by releasing antigens and activating inflammatory responses in the tumor microenvironment. However, some limitations, such as limited penetration of OVs into tumors, short persistence, and the host antiviral immune response, are impeding the broad translation of oncolytic virotherapy into the clinic. If these challenges can be overcome, combination therapies, such as OVs plus immune checkpoint blockade (ICB), chimeric antigen receptor (CAR) T cells, or CAR natural killer (NK) cells, may provide powerful therapeutic platforms in the clinic.

SARS-CoV-2 Establishes a Productive Infection in Hepatoma and Glioblastoma Multiforme Cell Lines

Severe acute respiratory syndrome associated coronavirus 2 (SARS-CoV-2) emerged at the end of 2019 and rapidly caused a pandemic that led to the death of >6 million people due to hypercoagulation and cytokine storm. In addition, SARS-CoV-2 triggers a wide array of pathologies, including liver dysfunction and neurological disorders. It remains unclear if these events are due to direct infection of the respective tissues or result from systemic inflammation. Here, we explored the possible infection of hepatic and CNS cell lines by SARS-CoV-2. We show that even moderate expression levels of the angiotensin-converting enzyme 2 (ACE2) are sufficient for productive infection. SARS-CoV-2 infects hepatoma Huh7.5 and HepG2 cells but not non-transformed liver progenitor or hepatocyte/cholangiocyte-like HepaRG cells. However, exposure to the virus causes partial dedifferentiation of HepaRG cells. SARS-CoV-2 can also establish efficient replication in some low-passage, high-grade glioblastoma cell lines. In contrast, embryonal primary astrocytes or neuroblastoma cells did not support replication of the virus. Glioblastoma cell permissiveness is associated with defects in interferon production. Overall, these results suggest that liver dysfunction during COVID-19 is not due to infection of these tissues by SARS-CoV-2. Furthermore, tumors may potentially serve as reservoirs for the virus during infection.

Anti-cancer Virotherapy in Russia: Lessons from the Past, Current Challenges and Prospects for the Future

The idea of using the lytic power of viruses against malignant cells has been entertained for many decades. However, oncolytic viruses gained broad attention as an emerging anti-cancer therapy only recently with the successful implementation of several oncolytic viruses to treat advanced melanoma. Here we review the history of oncolytic viruses in the Russian Federation and recent biotechnological advances in connection with the perspectives of their practical use against aggressive tumors such as glioblastoma or pancreatic cancer. A particular emphasis is made on novel applications of safe non-lytic virus-derived vectors armed with prodrug-converting enzyme transgenes. Rational improvement of oncotropism by conjugation with biopolymers and nanoformulations is also discussed.

2-Deoxyglucose, an Inhibitor of Glycolysis, Enhances the Oncolytic Effect of Coxsackievirus

Glioblastoma multiforme (GBM) is one of the most common types of brain tumor. Despite intensive research, patients with GBM have a poor prognosis due to a very high rate of relapse and significant side effects of the treatment, with a median survival of 14.6 months. Oncolytic viruses are considered a promising strategy to eliminate GBM and other types of cancer, and several viruses have already been introduced into clinical practice. However, identification of the factors that underly the sensitivity of tumor species to oncolytic viruses or that modulate their clinical efficacy remains an important target. Here, we show that Coxsackievirus B5 (CVB5) demonstrates high oncolytic potential towards GBM primary cell species and cell lines. Moreover, 2-deoxyglucose (2DG), an inhibitor of glycolysis, potentiates the cytopathic effects of CVB5 in most of the cancer cell lines tested. The cells in which the inhibition of glycolysis enhanced oncolysis are characterized by high mitochondrial respiratory activity and glycolytic capacity, as determined by Seahorse analysis. Thus, 2-deoxyglucose and other analogs should be considered as adjuvants for oncolytic therapy of glioblastoma multiforme.

Decoding Diabetes Biomarkers and Related Molecular Mechanisms by Using Machine Learning, Text Mining, and Gene Expression Analysis

The molecular basis of diabetes mellitus is yet to be fully elucidated. We aimed to identify the most frequently reported and differential expressed genes (DEGs) in diabetes by using bioinformatics approaches. Text mining was used to screen 40,225 article abstracts from diabetes literature. These studies highlighted 5939 diabetes-related genes spread across 22 human chromosomes, with 112 genes mentioned in more than 50 studies. Among these genes, HNF4A, PPARA, VEGFA, TCF7L2, HLA-DRB1, PPARG, NOS3, KCNJ11, PRKAA2, and HNF1A were mentioned in more than 200 articles. These genes are correlated with the regulation of glycogen and polysaccharide, adipogenesis, AGE/RAGE, and macrophage differentiation. Three datasets (44 patients and 57 controls) were subjected to gene expression analysis. The analysis revealed 135 significant DEGs, of which CEACAM6, ENPP4, HDAC5, HPCAL1, PARVG, STYXL1, VPS28, ZBTB33, ZFP37 and CCDC58 were the top 10 DEGs. These genes were enriched in aerobic respiration, T-cell antigen receptor pathway, tricarboxylic acid metabolic process, vitamin D receptor pathway, toll-like receptor signaling, and endoplasmic reticulum (ER) unfolded protein response. The results of text mining and gene expression analyses used as attribute values for machine learning (ML) analysis. The decision tree, extra-tree regressor and random forest algorithms were used in ML analysis to identify unique markers that could be used as diabetes diagnosis tools. These algorithms produced prediction models with accuracy ranges from 0.6364 to 0.88 and overall confidence interval (CI) of 95%. There were 39 biomarkers that could distinguish diabetic and non-diabetic patients, 12 of which were repeated multiple times. The majority of these genes are associated with stress response, signalling regulation, locomotion, cell motility, growth, and muscle adaptation. Machine learning algorithms highlighted the use of the HLA-DQB1 gene as a biomarker for diabetes early detection. Our data mining and gene expression analysis have provided useful information about potential biomarkers in diabetes.

Direct and indirect effects of IFN-α2b in malignancy treatment: not only an archer but also an arrow

Interferon-α2b (IFN-α2b) is a highly active cytokine that belongs to the interferon-α (IFN-α) family. IFN-α2b has beneficial antiviral, antitumour, antiparasitic and immunomodulatory activities. Direct and indirect antiproliferative effects of IFN-α2b have been found to occur via multiple pathways, mainly the JAK-STAT pathway, in certain cancers. This article reviews mechanistic studies and clinical trials on IFN-α2b. Potential regulators of the function of IFN-α2b were also reviewed, which could be utilized to relieve the poor response to IFN-α2b. IFN-α2b can function not only by enhancing the systematic immune response but also by directly killing tumour cells. Different parts of JAK-STAT pathway activated by IFN-α2b, such as interferon alpha and beta receptors (IFNARs), Janus kinases (JAKs) and IFN‐stimulated gene factor 3 (ISGF3), might serve as potential target for enhancing the pharmacological action of IFN-α2b. Despite some issues that remain to be solved, based on current evidence, IFN-α2b can inhibit disease progression and improve the survival of patients with certain types of malignant tumours. More efforts should be made to address potential adverse effects and complications.

DirectMS1Quant: Ultrafast Quantitative Proteomics with MS/MS-Free Mass Spectrometry

Recently, we presented the DirectMS1 method of ultrafast proteome-wide analysis based on minute-long LC gradients and MS1-only mass spectra acquisition. Currently, the method provides the depth of human cell proteome coverage of 2500 proteins at a 1% false discovery rate (FDR) when using 5 min LC gradients and 7.3 min runtime in total. While the standard MS/MS approaches provide 4000-5000 protein identifications within a couple of hours of instrumentation time, we advocate here that the higher number of identified proteins does not always translate into better quantitation quality of the proteome analysis. To further elaborate on this issue, we performed a one-on-one comparison of quantitation results obtained using DirectMS1 with three popular MS/MS-based quantitation methods: label-free (LFQ) and tandem mass tag quantitation (TMT), both based on data-dependent acquisition (DDA) and data-independent acquisition (DIA). For comparison, we performed a series of proteome-wide analyses of well-characterized (ground truth) and biologically relevant samples, including a mix of UPS1 proteins spiked at different concentrations into an Echerichia coli digest used as a background and a set of glioblastoma cell lines. MS1-only data was analyzed using a novel quantitation workflow called DirectMS1Quant developed in this work. The results obtained in this study demonstrated comparable quantitation efficiency of 5 min DirectMS1 with both TMT and DIA methods, yet the latter two utilized a 10-20-fold longer instrumentation time.

Development of a recombinant oncolytic poliovirus type 3 strain with altered cell tropism

Diffuse gliomas are incurable, prevalent, and aggressive central nervous system tumors. Therefore, the development of selective oncolytic viral strains for malignant neoplasms is highly relevant. This study aimed to create an oncolytic virus based on a vaccine strain of poliovirus type 3 with natural antitumor activity. To achieve this goal, we replaced the internal ribosome entry site (IRES) of poliovirus with the corresponding fragment of human rhinovirus 30. The resulting recombinant oncolytic strain RVP3 retained the serotype of poliovirus type 3, as confirmed by virus neutralization micro-test with specific antiserum. In addition, the oncolytic efficacy of RVP3 was assessed in vitro on a broad panel of cell cultures. According to the results, RVP3 has changed its tropism, losing the ability to replicate in conditionally normal cell lines of embryonic astrocytes and embryonic fibroblasts while retaining the ability to replicate in tumor cells.