Aberrant DNA methylation distorts developmental trajectories in atypical teratoid/rhabdoid tumors

Atypical teratoid/rhabdoid tumors (AT/RTs) are pediatric brain tumors known for their aggressiveness and aberrant but still unresolved epigenetic regulation. To better understand their malignancy, we investigated how AT/RT-specific DNA hypermethylation was associated with gene expression and altered transcription factor binding and how it is linked to upstream regulation. Medulloblastomas, choroid plexus tumors, pluripotent stem cells, and fetal brain were used as references. A part of the genomic regions, which were hypermethylated in AT/RTs similarly as in pluripotent stem cells and demethylated in the fetal brain, were targeted by neural transcriptional regulators. AT/RT-unique DNA hypermethylation was associated with polycomb repressive complex 2 and linked to suppressed genes with a role in neural development and tumorigenesis. Activity of the several NEUROG/NEUROD pioneer factors, which are unable to bind to methylated DNA, was compromised via the suppressed expression or DNA hypermethylation of their target sites, which was also experimentally validated for NEUROD1 in medulloblastomas and AT/RT samples. These results highlight and characterize the role of DNA hypermethylation in AT/RT malignancy and halted neural cell differentiation.

Genomic characterization of IDH-mutant astrocytoma progression to grade 4 in the treatment setting

As the progression of low-grade diffuse astrocytomas into grade 4 tumors significantly impacts patient prognosis, a better understanding of this process is of paramount importance for improved patient care. In this project, we analyzed matched IDH-mutant astrocytomas before and after progression to grade 4 from six patients (discovery cohort) with genome-wide sequencing, 21 additional patients with targeted sequencing, and 33 patients from Glioma Longitudinal AnalySiS cohort for validation. The Cancer Genome Atlas data from 595 diffuse gliomas provided supportive information. All patients in our discovery cohort received radiation, all but one underwent chemotherapy, and no patient received temozolomide (TMZ) before progression to grade 4 disease. One case in the discovery cohort exhibited a hypermutation signature associated with the inactivation of the MSH2 and DNMT3A genes. In other patients, the number of chromosomal rearrangements and deletions increased in grade 4 tumors. The cell cycle checkpoint gene CDKN2A, or less frequently RB1, was most commonly inactivated after receiving both chemo- and radiotherapy when compared to other treatment groups. Concomitant activating PDGFRA/MET alterations were detected in tumors that acquired a homozygous CDKN2A deletion. NRG3 gene was significantly downregulated and recurrently altered in progressed tumors. Its decreased expression was associated with poorer overall survival in both univariate and multivariate analysis. We also detected progression-related alterations in RAD51B and other DNA repair pathway genes associated with the promotion of error-prone DNA repair, potentially facilitating tumor progression. In our retrospective analysis of patient treatment and survival timelines (n = 75), the combination of postoperative radiation and chemotherapy (mainly TMZ) outperformed radiation, especially in the grade 3 tumor cohort, in which it was typically given after primary surgery. Our results provide further insight into the contribution of treatment and genetic alterations in cell cycle, growth factor signaling, and DNA repair-related genes to tumor evolution and progression.

Structural analysis of human G-protein-coupled receptor 17 ligand binding sites

The human G protein coupled membrane receptor (GPR17), the sensor of brain damage, is identified as a biomarker for many neurological diseases. In human brain tissue, GPR17 exist in two isoforms, long and short. While cryo-electron microscopy technology has provided the structure of the long isoform of GPR17 with Gi complex, the structure of the short isoform and its activation mechanism remains unclear. Recently, we theoretically modeled the structure of the short isoform of GPR17 with Gi signaling protein and identified novel ligands. In the present work, we demonstrated the presence of two distinct ligand binding sites in the short isoform of GPR17. The molecular docking of GPR17 with endogenous (UDP) and synthetic ligands (T0510.3657, MDL29950) found the presence of two distinct binding pockets. Our observations revealed that endogenous ligand UDP can bind stronger in two different binding pockets as evidenced by glide and autodock vina scores, whereas the other two ligand's binding with GPR17 has less docking score. The analysis of receptor-UDP interactions shows complexes' stability in the lipid environment by 100 ns atomic molecular dynamics simulations. The amino acid residues VAL83, ARG87, and PHE111 constitute ligand binding site 1, whereas site 2 constitutes ASN67, ARG129, and LYS232. Root mean square fluctuation analysis showed the residues 83, 87, and 232 with higher fluctuations during molecular dynamics simulation in both binding pockets. Our findings imply that the residues of GPR17's two binding sites are crucial, and their interaction with UDP reveals the protein's hidden signaling and communication properties. Furthermore, this finding may assist in the development of targeted therapies for the treatment of neurological diseases.

Signaling landscape of mitochondrial non-coding RNAs

Human mitochondria are the vital cell organelle acting as a storehouse of energy generation and diverse regulatory functions. Mitochondrial DNA comprises 93% coding region and 7% non-coding regions, in which the non-coding region hypothesized as responsible for signaling is our specific interest. Here, we explored the unknown functions of mitochondrial non-coding RNAs by studying their respective signaling pathways. We retrieved conserved motifs of interactions from known experimental protein-RNA complexes to model unknown mitochondrial ncRNA sequences. Our results provide the ncRNAs list and show their involvement in four crucial pathways, such as (i) Processing of Capped Intron-Containing Pre-mRNA, (ii) Spliceosome, (iii) Spliceosomal assembly, and (iv) RNA Polymerase II Transcription, respectively. The interactome analysis revealed that the SRSF2 and U2AF2 proteins interact with ncRNAs. Further, we have simulated the selected ncRNA-protein complexes in cell-like environmental conditions and found them stable in terms of energetics. Through our study, we have identified an apparent interaction of mitochondrial ncRNAs with proteins and their role in critical signaling pathways, providing new insights into mitochondrial ncRNA-dependent gene regulation.Communicated by Ramaswamy H. Sarma.

Molecular modeling and dynamics studies of the synthetic small molecule agonists with GPR17 and P2Y1 receptor

The human Guanine Protein coupled membrane Receptor 17 (hGPR17), an orphan receptor that activates uracil nucleotides and cysteinyl leukotrienes is considered as a crucial target for the neurodegenerative diseases. Yet, the detailed molecular interaction of potential synthetic ligands of GPR17 needs to be characterized. Here, we have studied a comparative analysis on the interaction specificity of GPR17-ligands with hGPR17 and human purinergic G protein-coupled receptor (hP2Y1) receptors. Previously, we have simulated the interaction stability of synthetic ligands such as T0510.3657, AC1MLNKK, and MDL29951 with hGPR17 and hP2Y1 receptor in the lipid environment. In the present work, we have comparatively studied the protein-ligand interaction of hGPR17-T0510.3657 and P2Y1-MRS2500. Sequence analysis and structural superimposition of hGPR17 and hP2Y1 receptor revealed the similarities in the structural arrangement with the local backbone root mean square deviation (RMSD) value of 1.16 Å and global backbone RMSD value of 5.30 Å. The comparative receptor-ligand interaction analysis between hGPR17 and hP2Y1 receptor exposed the distinct binding sites in terms of geometrical properties. Further, the molecular docking of T0510.3657 with the hP2Y1 receptor have shown non-specific interaction. The experimental validation also revealed that Gi-coupled activation of GPR17 by specific ligands leads to the adenylyl cyclase inhibition, while there is no inhibition upon hP2Y1 activation. Overall, the above findings suggest that T0510.3657-GPR17 binding specificity could be further explored for the treatment of numerous neuronal diseases. Communicated by Ramaswamy H. Sarma.

EPCO-11. GATEKEEPER INACTIVATION DRIVES TUMOR PROGRESSION TO GRADE IV ASTROCYTOMA

IDH-mutant low-grade diffuse astrocytomas frequently progress to grade IV astrocytomas with implications for patient prognosis. To better understand this process, we applied whole-genome and transcriptome sequencing to matched tumor samples collected before and after progression to grade IV astrocytomas from five patients. All tumors carried an IDH1 mutation. The number of chromosomal rearrangements was increased between 1.3 and 3.5-fold in the tumors upon progression, with the exception of one case, in which the increase was only 1.03-fold. This case exhibited a hypermutation signature caused by homozygous deletion of the MSH2 gene, which encodes a member of the DNA mismatch repair complex. The most common genomic alterations acquired at progression were homozygous deletions in the CDKN2A/ RB1 -pathway or hemizygous deletion of PTEN. Additionally, PDGFRA was amplified in two grade IV tumors, with concordantly increased expression. For one of these cases, a PDGFRA-amplified subclone is likely to be present already in the low-grade astrocytoma. We further detected intrachromosomal rearrangements closeby the genes NRG3 in the progressed tumors as well as in the The Cancer Genome Atlas (TCGA) cohort. The expression of NRG3 decreased with increasing grade in the TCGA cohort and the gene was frequently deleted. Lower NRG3 expression was associated with shorter survival in the TCGA cohort. Several miRNAs showed differential expression upon progression. For two miRNAs the predicted targets were associated with cell cycle regulation and we detected inverse correlation between miRNA and target mRNA expression. While progression seems to occur via different pathways, the predicted outcome for many of the alterations was the inactivation of tumor suppressor genes and further dysregulation of cell proliferation.

EPCO-34. INTEGRATIVE DNA METHYLATION ANALYSIS OF PEDIATRIC BRAIN TUMORS REVEALS TUMOR TYPE-SPECIFIC DEVELOPMENTAL TRAJECTORIES AND EPIGENETIC SIGNATURES OF MALIGNANCY

Understanding oncogenic epigenetic mechanisms in brain tumors is crucial for improved diagnosis and treatment. Recently DNA methylation has proven to be powerful for brain tumor characterization and diagnostic classification. To evaluate tumor type specific features, we compared atypical teratoid/rhabdoid tumors (AT/RTs), medulloblastomas (MBs), and choroid plexus tumors with each other by integrating DNA methylation (507 samples), gene expression (120 samples), and transcription factor (TF) -binding data. Different tumor entities were used to find unique changes affecting each of the entities and further to identify functions driven by these changes. Our results provide insight on how the aberrant DNA methylation induces oncogenesis of AT/RTs. These tumors are known for their aggressiveness and exceptionally low mutation rates. Our results suggest that in AT/RT, elevated DNA methylation masks the binding sites of TFs such as NEUROD1, ASCL1 and MYCN driving neural development. DNA methylation in AT/RTs is also associated with reduced gene expression for specific neural regulators such as NEUROG1 and NEUROD2. For MBs, DNA methylation patterns predict a more advanced differentiation state. In MB, we found masked TF binding sites for TFs such as REST and ZEB1 that normally inhibit neural differentiation. We then wanted to further characterize DNA methylation and compared these tumors to pluripotent stem cells (PSCs) and normal fetal brain samples. As a result, we were able to find two different regulatory programs in AT/RTs: One in which DNA methylation is similar to PSCs and which harbors mostly neural TF binding sites. Second program has AT/RT-specific DNA methylation, and these sites are uniquely associated with polycomb repressive complex 2 members. However, this second program also covers neural TF binding sites and is likely to have relevance in oncogenic regulation.

What Is a Digital Twin? Experimental Design for a Data-Centric Machine Learning Perspective in Health

The idea of a digital twin has recently gained widespread attention. While, so far, it has been used predominantly for problems in engineering and manufacturing, it is believed that a digital twin also holds great promise for applications in medicine and health. However, a problem that severely hampers progress in these fields is the lack of a solid definition of the concept behind a digital twin that would be directly amenable for such big data-driven fields requiring a statistical data analysis. In this paper, we address this problem. We will see that the term 'digital twin', as used in the literature, is like a Matryoshka doll. For this reason, we unstack the concept via a data-centric machine learning perspective, allowing us to define its main components. As a consequence, we suggest to use the term Digital Twin System instead of digital twin because this highlights its complex interconnected substructure. In addition, we address ethical concerns that result from treatment suggestions for patients based on simulated data and a possible lack of explainability of the underling models.

Programmed cell death detection methods: a systematic review and a categorical comparison

Programmed cell death is considered a key player in a variety of cellular processes that helps to regulate tissue growth, embryogenesis, cell turnover, immune response, and other biological processes. Among different types of cell death, apoptosis has been studied widely, especially in the field of cancer research to understand and analyse cellular mechanisms, and signaling pathways that control cell cycle arrest. Hallmarks of different types of cell death have been identified by following the patterns and events through microscopy. Identified biomarkers have also supported drug development to induce cell death in cancerous cells. There are various serological and microscopic techniques with advantages and limitations, that are available and are being utilized to detect and study the mechanism of cell death. The complexity of the mechanism and difficulties in distinguishing among different types of programmed cell death make it challenging to carry out the interventions and delay its progression. In this review, mechanisms of different forms of programmed cell death along with their conventional and unconventional methods of detection of have been critically reviewed systematically and categorized on the basis of morphological hallmarks and biomarkers to understand the principle, mechanism, application, advantages and disadvantages of each method. Furthermore, a very comprehensive comparative analysis has been drawn to highlight the most efficient and effective methods of detection of programmed cell death, helping researchers to make a reliable and prudent selection among the available methods of cell death assay. Conclusively, how programmed cell death detection methods can be improved and can provide information about distinctive stages of cell death detection have been discussed.

P2Y1 agonist HIC in combination with androgen receptor inhibitor abiraterone acetate impairs cell growth of prostate cancer

P2Y receptors belong to the large superfamily of G-protein-coupled receptors and play a crucial role in cell death and survival. P2Y1 receptor has been identified as a marker for prostate cancer (PCa). A previously unveiled selective P2Y1 receptor agonist, the indoline-derived HIC (1-(1-((2-hydroxy-5-nitrophenyl)(4-hydroxyphenyl)methyl)indoline-4-carbonitrile), induces a series of molecular and biological responses in PCa cells PC3 and DU145, but minimal toxicity to normal cells. Here, we evaluated the combinatorial effect of HIC with abiraterone acetate (AA) targeted on androgen receptor (AR) on the inhibition of PCa cells. Here, the presence of HIC and AA significantly inhibited cell proliferation of PC3 and DU145 cells with time-dependent manner as a synerfistic combination. Moreover, it was also shown that the anticancer and antimetastasis effects of the combinratorial drugs were noticed through a decrease in colony-forming ability, cell migration, and cell invasion. In addition, the HIC + AA induced apoptotic population of PCa cells as well as cell cycle arrest in G1 progression phase. In summary, these studies show that the combination of P2Y1 receptor agonist, HIC and AR inhibitor, AA, effectively improved the antitumor activity of each drug. Thus, the combinatorial model of HIC and AA should be a novel and promising therapeutic strategy for treating prostate cancer.

GPR17 signaling activation by CHBC agonist induced cell death via modulation of MAPK pathway in glioblastoma

AIM

Glioblastoma multiforme (GBM) is the most common and aggressive primary adult brain tumor. GBM is characterized by a heterogeneous population of cells that are resistant to chemotherapy. Recently, we have synthesized CHBC, a novel indole derivative targeted to GBM biomarker G-protein-coupled receptor 17 and inhibitor of GBM cells. In this study, CHBC was further investigated to characterize the efficiency of this agonist at the molecular level and its underlying mechanism in GBM cell death induction.

MATERIALS AND METHODS

The effect of CHBC and TMZ was determined using time dependent inhibitor assay in glioblastoma cells, LN229 and SNB19. Drug induced cell cycle arrest was measured using PI staining followed by image analysis. The induction of apoptosis and mechanism of action of CHBC was studied using apoptosis, caspase 3/7 and mitochondrial membrane permeability assays. Modulation of the key genes involved in MAPK signaling pathway was also measured using immunoblotting array.

KEY FINDINGS

The inhibitory kinetic study has revealed that CHBC inhibited SNB19 and LN229 cell growth in a time-dependent manner. Furthermore, CHBC with the IC50 of 85 μM, mediated cell death through an apoptosis mechanism in both studied cell lines. The study also has revealed that CHBC targets GPR17 leading to the induction of apoptosis via the activation of Caspase 3/7 and dysfunction of mitochondrial membrane potential. In addition, CHBC treatment led to marked G2/M cell cycle arrest. The protein array has confirmed the anticancer effect of CHBC by the disruption of the mitogen-activated protein kinase pathway (MAPK).

SIGNIFICANCE

Taken together, these results demonstrated that CHBC induced G2/M cell cycle arrest and apoptosis by disrupting MAPK signaling in human glioblastoma cells. This study concludes that CHBC represent a class of compounds for treating glioblastoma.

Molecular interaction of HIC, an agonist of P2Y1 receptor, and its role in prostate cancer apoptosis

Prostate cancer is a heterogeneous, slow growing asymptomatic cancer that predominantly affects man. A purinergic G-protein coupled receptor, P2Y1R, is targeted for its therapeutic value since it plays a crucial role in many key molecular events of cancer progression and invasion. Our previous study demonstrated that indoline derivative, 1 ((1-(2-Hydroxy-5-nitrophenyl) (4-hydroxyphenyl) methyl)indoline-4‑carbonitrile; HIC), stimulates prostate cancer cell (PCa) growth inhibition via P2Y1R. However, the mode of interaction of P2Y1R with HIC involved in this process remains unclear. Here, we have reported the molecular interactions of HIC with P2Y1R. Molecular dynamics simulation was performed that revealed the stable specific binding of the protein-ligand complex. In vitro analysis has shown increased apoptosis of PCa-cells, PC3, and DU145, upon specific interaction of P2Y1R-HIC. This was further validated using siRNA analysis that showed a higher percentage of apoptotic cells in PCa-cells transfected with P2Y-siRNA-MRS2365 than P2Y-siRNA-HIC treatment. Decreased mitochondrial membrane potential (MMP) activity and reduced glutathione (GSH) level show their role in P2Y1R-HIC mediated apoptosis. These in silico and in vitro results confirmed that HIC could induce mitochondrial apoptotic signaling through the P2Y1R activation. Thus, HIC being a potential ligand upon interaction with P2Y1R might have therapeutic value for the treatment of prostate cancer.

Are There Limits in Explainability of Prognostic Biomarkers? Scrutinizing Biological Utility of Established Signatures

Prognostic biomarkers can have an important role in the clinical practice because they allow stratification of patients in terms of predicting the outcome of a disorder. Obstacles for developing such markers include lack of robustness when using different data sets and limited concordance among similar signatures. In this paper, we highlight a new problem that relates to the biological meaning of already established prognostic gene expression signatures. Specifically, it is commonly assumed that prognostic markers provide sensible biological information and molecular explanations about the underlying disorder. However, recent studies on prognostic biomarkers investigating 80 established signatures of breast and prostate cancer demonstrated that this is not the case. We will show that this surprising result is related to the distinction between causal models and predictive models and the obfuscating usage of these models in the biomedical literature. Furthermore, we suggest a falsification procedure for studies aiming to establish a prognostic signature to safeguard against false expectations with respect to biological utility.

Alkylaminophenol and GPR17 Agonist for Glioblastoma Therapy: A Combinational Approach for Enhanced Cell Death Activity

Drug resistance and tumor heterogeneity limits the therapeutic efficacy in treating glioblastoma, an aggressive infiltrative type of brain tumor. GBM cells develops resistance against chemotherapeutic agent, temozolomide (TMZ), which leads to the failure in treatment strategies. This enduring challenge of GBM drug resistance could be rational by combinatorial targeted therapy. Here, we evaluated the combinatorial effect of phenolic compound (2-(3,4-dihydroquinolin-1(2H)-yl)(p-tolyl)methyl)phenol (THTMP), GPR17 agonist 2-({5-[3-(Morpholine-4-sulfonyl)phenyl]-4-[4-(trifluoromethoxy)phenyl]-4H-1,2,4-triazol-3-yl}sulfanyl)-N-[4-(propan-2-yl)phenyl]acetamide (T0510.3657 or T0) with the frontline drug, TMZ, on the inhibition of GBM cells. Mesenchymal cell lines derived from patients' tumors, MMK1 and JK2 were treated with the combination of THTMP + T0, THTMP + TMZ and T0 + TMZ. Cellular migration, invasion and clonogenicity assays were performed to check the migratory behavior and the ability to form colony of GBM cells. Mitochondrial membrane permeability (MMP) assay and intracellular calcium, [Ca2+]i, assay was done to comprehend the mechanism of apoptosis. Role of apoptosis-related signaling molecules was analyzed in the induction of programmed cell death. In vivo validation in the xenograft models further validates the preclinical efficacy of the combinatorial drug. GBM cells exert better synergistic effect when exposed to the cytotoxic concentration of THTMP + T0, than other combinations. It also inhibited tumor cell proliferation, migration, invasion, colony-forming ability and cell cycle progression in S phase, better than the other combinations. Moreover, the combination of THTMP + T0 profoundly increased the [Ca2+]i, reactive oxygen species in a time-dependent manner, thus affecting MMP and leading to apoptosis. The activation of intrinsic apoptotic pathway was regulated by the expression of Bcl-2, cleaved caspases-3, cytochrome c, HSP27, cIAP-1, cIAP-2, p53, and XIAP. The combinatorial drug showed promising anti-tumor efficacy in GBM xenograft model by reducing the tumor volume, suggesting it as an alternative drug to TMZ. Our findings indicate the coordinated administration of THTMP + T0 as an efficient therapy for inhibiting GBM cell proliferation.

Targeting Orphan G Protein-Coupled Receptor 17 with T0 Ligand Impairs Glioblastoma Growth

Simple Summary

Glioblastoma multiforme (GBM), or glioblastoma chemotherapy, has one of the poorest improvements across all types of cancers. Despite the different rationales explored in targeted therapy for taming the GBM aggressiveness, its phenotypic plasticity, drug toxicity, and adaptive resistance mechanisms pose many challenges in finding an effective cure. Our manuscript reports the expression and prognostic role of orphan receptor GPR17 in glioma, the molecular mechanism of action of the novel ligand of GPR17, and provides evidence how the T0 agonist promotes glioblastoma cell death through modulation of the MAPK/ERK, PI3K–Akt, STAT, and NF-κB pathways. The highlights are as follows: GPR17 expression is associated with greater survival for both low-grade glioma (LGG) and GBM; GA-T0, a potent GPR17 receptor agonist, causes significant GBM cell death and apoptosis; GPR17 signaling promotes cell cycle arrest at the G1 phase in GBM cells; key genes are modulated in the signaling pathways that inhibit GBM cell proliferation; and GA-T0 crosses the blood–brain barrier and reduces tumor volume.

Abstract

Glioblastoma, an invasive high-grade brain cancer, exhibits numerous treatment challenges. Amongst the current therapies, targeting functional receptors and active signaling pathways were found to be a potential approach for treating GBM. We exploited the role of endogenous expression of GPR17, a G protein-coupled receptor (GPCR), with agonist GA-T0 in the survival and treatment of GBM. RNA sequencing was performed to understand the association of GPR17 expression with LGG and GBM. RT-PCR and immunoblotting were performed to confirm the endogenous expression of GPR17 mRNA and its encoded protein. Biological functions of GPR17 in the GBM cells was assessed by in vitro analysis. HPLC and histopathology in wild mice and an acute-toxicity analysis in a patient-derived xenograft model were performed to understand the clinical implication of GA-T0 targeting GPR17. We observed the upregulation of GPR17 in association with improved survival of LGG and GBM, confirming it as a predictive biomarker. GA-T0-stimulated GPR17 leads to the inhibition of cyclic AMP and calcium flux. GPR17 signaling activation enhances cytotoxicity against GBM cells and, in patient tissue-derived mesenchymal subtype GBM cells, induces apoptosis and prevents proliferation by stoppage of the cell cycle at the G1 phase. Modulation of the key genes involved in DNA damage, cell cycle arrest, and in several signaling pathways, including MAPK/ERK, PI3K–Akt, STAT, and NF-κB, prevents tumor regression. In vivo activation of GPR17 by GA-T0 reduces the tumor volume, uncovering the potential of GA-T0–GPR17 as a targeted therapy for GBM treatment. Conclusion: Our analysis suggests that GA-T0 targeting the GPR17 receptor presents a novel therapy for treating glioblastoma.

Synthesis and Preclinical Validation of Novel Indole Derivatives as a GPR17 Agonist for Glioblastoma Treatment

The discovery of a potential ligand-targeting G protein-coupled receptor 17 (GPR17) is important for developing chemotherapeutic agents against glioblastoma multiforme (GBM). We used the integration of ligand- and structure-based cheminformatics and experimental approaches for identifying the potential GPR17 ligand for GBM treatment. Here, we identified a novel indoline-derived phenolic Mannich base as an activator of GPR17 using molecular docking of over 6000 indoline derivatives. One of the top 10 hit molecules, CHBC, with a glide score of -8.390 was synthesized through a multicomponent Petasis borono-Mannich reaction. The CHBC-GPR17 interaction leads to a rapid decrease of cAMP and Ca²⁺. CHBC exhibits the cytotoxicity effect on GBM cells in a dose-dependent manner with an IC₅₀ of 85 μM, whereas the known agonist MDL29,951 showed a negligible effect. Our findings suggest that the phenolic Mannich base could be a better GPR17 agonist than MDL29,951, and further uncovering their pharmacological properties could potentiate an inventive GBM treatment.

Limitations of Explainability for Established Prognostic Biomarkers of Prostate Cancer

High-throughput technologies do not only provide novel means for basic biological research but also for clinical applications in hospitals. For instance, the usage of gene expression profiles as prognostic biomarkers for predicting cancer progression has found widespread interest. Aside from predicting the progression of patients, it is generally believed that such prognostic biomarkers also provide valuable information about disease mechanisms and the underlying molecular processes that are causal for a disorder. However, the latter assumption has been challenged. In this paper, we study this problem for prostate cancer. Specifically, we investigate a large number of previously published prognostic signatures of prostate cancer based on gene expression profiles and show that none of these can provide unique information about the underlying disease etiology of prostate cancer. Hence, our analysis reveals that none of the studied signatures has a sensible biological meaning. Overall, this shows that all studied prognostic signatures are merely black-box models allowing sensible predictions of prostate cancer outcome but are not capable of providing causal explanations to enhance the understanding of prostate cancer.

Alkylamino Phenol Derivative Induces Apoptosis by Inhibiting EGFR Signaling Pathway in Breast Cancer Cells

BACKGROUND AND OBJECTIVE

The present study was carried out to evaluate the anticancer property of an alkylamino phenol derivative -2-((3,4-Dihydroquinolin-1(2H)-yl)(p-tolyl)methyl)phenol) (THTMP) against human breast cancer cells. The cytotoxicity of the THTMP was assessed to know its specificity towards breast cancer cells without affecting the normal cells.

METHODS

The THTMP was synthesized and the cytotoxicity was assessed by MTT assay, Caspases enzyme activity, DNA fragmentation and FITC/Annexin V, AO/EtBr staining, RT-PCR and QSAR. In addition, ADME analysis was executed to understand the mode of action of THTMP.

RESULTS

THTMP showed potential cytotoxic activity against the growth of MCF7 and SK-BR3 cells with the IC50 values of 87.92μM and 172.51μM, respectively. Interestingly, THTMP found to activate caspase 3 and caspase 9 enzymes in cancer cells, which are the key enzymes implicated in apoptosis. THTMP induced apoptosis in which 33% of the cells entered the late apoptotic stage after 24h of treatment. The results also revealed that the apoptotic response could be influenced by the association of THTMP with the Epidermal Growth Factor Receptor (EGFR) mediated inhibition of the Phosphatidylinositol 3-Kinase (PI3K)/S6K1 signaling pathway. In addition, docking was performed to study the binding mode of the THTMP, which shows better interaction with EGFR. The structural elucidation of THTMP by Quantitative Structure-Activity Relationship model (QSAR) and ADMET screening suggested, THTMP as an effective anticancer compound.

CONCLUSION

This work strengthens the potential of a promising drug-like compound, THTMP, for the discovery of anticancer drug against breast cancer.

Molecular interaction study of novel indoline derivatives with EGFR-kinase domain using multiple computational analysis

Epidermal growth factor receptors are constitutively overexpressed in breast cancer cells, which in turn stimulate many downstream signaling pathways that are involved in many carcinogenic processes. This makes EGFR a striking target for cancer therapy. This study focuses on the EGFR kinase domain inactivation by novel synthesized indoline derivatives. The compounds used are N-(2-hydroxy-5-nitrophenyl (4'-methyl phenyl) methyl) indoline (HNPMI), alkylaminophenols - 2-((3,4-Dihydroquinolin-1(2H)-yl) (p-tolyl) methyl) phenol (THTMP) and 2-((1, 2, 3, 4-Tetrahydroquinolin-1-yl) (4 methoxyphenyl) methyl) phenol (THMPP). To get a clear insight into the molecular interaction of EGFR and the three compounds, we have used ADME/Tox prediction, Flexible docking analysis followed by MM/GB-SA, QM/MM analysis, E-pharmacophore mapping of the ligands and Molecular dynamic simulation of protein-ligand complexes. All three compounds showed good ADME/Tox properties obeying the rules of drug-likeliness and showed high human oral absorption. Molecular docking was performed with the compounds and EGFR using Glide Flexible docking mode. This showed that the HNPMI was best among the three compounds and had interactions with key residue Lys 721. The protein-ligand complexes were stable when simulated for 100 ns using Desmond software. The interactions were further substantiated using QM/MM analysis and MM-GB/SA analysis in which HNPMI was scored as the best molecule. All the analyses were carried out with a reference molecule-Gefitinib which is a known standard inhibitor of EGFR. Thus, the study elucidates the potential role of the indoline derivatives as an anti-cancer agent against breast cancer by effectively inhibiting EGFR.Communicated by Ramaswamy H. Sarma.

Prognostic gene expression signatures of breast cancer are lacking a sensible biological meaning

The identification of prognostic biomarkers for predicting cancer progression is an important problem for two reasons. First, such biomarkers find practical application in a clinical context for the treatment of patients. Second, interrogation of the biomarkers themselves is assumed to lead to novel insights of disease mechanisms and the underlying molecular processes that cause the pathological behavior. For breast cancer, many signatures based on gene expression values have been reported to be associated with overall survival. Consequently, such signatures have been used for suggesting biological explanations of breast cancer and drug mechanisms. In this paper, we demonstrate for a large number of breast cancer signatures that such an implication is not justified. Our approach eliminates systematically all traces of biological meaning of signature genes and shows that among the remaining genes, surrogate gene sets can be formed with indistinguishable prognostic prediction capabilities and opposite biological meaning. Hence, our results demonstrate that none of the studied signatures has a sensible biological interpretation or meaning with respect to disease etiology. Overall, this shows that prognostic signatures are black-box models with sensible predictions of breast cancer outcome but no value for revealing causal connections. Furthermore, we show that the number of such surrogate gene sets is not small but very large.

Identifying the miRNA Signature Association with Aging-Related Senescence in Glioblastoma

Glioblastoma (GBM) is the most common malignant brain tumor and its malignant phenotypic characteristics are classified as grade IV tumors. Molecular interactions, such as protein–protein, protein–ncRNA, and protein–peptide interactions are crucial to transfer the signaling communications in cellular signaling pathways. Evidences suggest that signaling pathways of stem cells are also activated, which helps the propagation of GBM. Hence, it is important to identify a common signaling pathway that could be visible from multiple GBM gene expression data. microRNA signaling is considered important in GBM signaling, which needs further validation. We performed a high-throughput analysis using micro array expression profiles from 574 samples to explore the role of non-coding RNAs in the disease progression and unique signaling communication in GBM. A series of computational methods involving miRNA expression, gene ontology (GO) based gene enrichment, pathway mapping, and annotation from metabolic pathways databases, and network analysis were used for the analysis. Our study revealed the physiological roles of many known and novel miRNAs in cancer signaling, especially concerning signaling in cancer progression and proliferation. Overall, the results revealed a strong connection with stress induced senescence, significant miRNA targets for cell cycle arrest, and many common signaling pathways to GBM in the network.

Vaccines, Repurposed Drugs and Alternative Biomedicines for the Management and Prevention of COVID-19

The Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) popularly called as COVID-19, is a pandemic having affected >200 countries. Globally, quarantine measures have been implemented to slow down the spread of the virus. Yet, the available vaccines and drugs for treating COVID-19 are still in design and developmental stage, requiring clinical validation. This review is focused on the progress in the development of medicines against SARS-CoV-2. As an alternative approach, both conventional and traditional biomedicines are also reported to be in practice, to treat the SARS-CoV-2 infected patients. Considering the therapeutic values of the folk medicines, this review focuses on the usage of high value added products from plants, against COVID-19 in managing the symptoms like fever, cough, cold, sore throat, respiratory disorders and kidney dysfunctions enlisting a few used since time immemorial. It is ardently hoped that scientific intervention of such traditional plants can be integrated to harmonise with modern medicine, to ensure its dosage and safety in augmenting disease management.

Artificial Intelligence: A Clarification of Misconceptions, Myths and Desired Status

The field artificial intelligence (AI) was founded over 65 years ago. Starting with great hopes and ambitious goals the field progressed through various stages of popularity and has recently undergone a revival through the introduction of deep neural networks. Some problems of AI are that, so far, neither the "intelligence" nor the goals of AI are formally defined causing confusion when comparing AI to other fields. In this paper, we present a perspective on the desired and current status of AI in relation to machine learning and statistics and clarify common misconceptions and myths. Our discussion is intended to lift the veil of vagueness surrounding AI to reveal its true countenance.

Erratum: Viswanathan, A., et al. Battling Glioblastoma: A Novel Tyrosine Kinase Inhibitor with Multi-Dimensional Anti-Tumor Effect (Running Title: Cancer Cells Death Signalling Activation). Cells 2019, 8, 1624

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Transcriptomic analysis of glioblastoma multiforme providing new insights into GPR17 signaling communication

Glioblastoma Multiforme (GBM) is one of the most aggressive malignant tumors in the central nervous system, which arises due to the failure or crosstalk in the signaling networks. GPR17, an orphan G protein-coupled receptor is anticipated to be associated with the biology of the GBM disease progression. In the present study, we have identified the differential expressions of around 170 genes along with GPR17 through the RNA-Seq analysis of 169 GBM samples. Coordinated expression patterns of all other gene products with this receptor were analysed using gene ontology and protein-protein interaction data. Several crucial signaling components and genes that play a significant role in tumor progression have been identified among which GPR17 was found to be significantly interacting with about 30 different pathways. High-throughput molecular docking of GPR17 by homology-based model against differentially expressed proteins, showed effective recognition and binding of PX, SH3, and Ig-like domains besides Gi protein. Pathways of PI3, Src, Ptdn, Ras, cytoplasmic tyrosine kinases, phospholipases, nexins and other proteins possessing these structural domains are identified as critical signaling components of the complex GBM signaling network. Our findings also provide a mechanistic insight of GPR17-T0510-3657 interaction, which potentially regulates the interaction of PX domain and helical mPTS recognition domain-containing proteins. Overall, our results demonstrate that GPR17 mediated signaling networks could be used as a therapeutic target for GBM.Communicated by Ramaswamy H. Sarma.

Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance

Gene ontology (GO) is an eminent knowledge base frequently used for providing biological interpretations for the analysis of genes or gene sets from biological, medical and clinical problems. Unfortunately, the interpretation of such results is challenging due to the large number of GO terms, their hierarchical and connected organization as directed acyclic graphs (DAGs) and the lack of tools allowing to exploit this structural information explicitly. For this reason, we developed the R package GOxploreR. The main features of GOxploreR are (I) easy and direct access to structural features of GO, (II) structure-based ranking of GO-terms, (III) mapping to reduced GO-DAGs including visualization capabilities and (IV) prioritizing of GO-terms. The underlying idea of GOxploreR is to exploit a graph-theoretical perspective of GO as manifested by its DAG-structure and the containing hierarchy levels for cumulating semantic information. That means all these features enhance the utilization of structural information of GO and complement existing analysis tools. Overall, GOxploreR provides exploratory as well as confirmatory tools for complementing any kind of analysis resulting in a list of GO-terms, e.g., from differentially expressed genes or gene sets, GWAS or biomarkers. Our R package GOxploreR is freely available from CRAN.

Antiproliferative and apoptotic effects of indole derivative, N-(2-hydroxy-5-nitrophenyl (4'-methylphenyl) methyl) indoline in breast cancer cells

Indoline derivatives functions as an inhibitors of epidermal growth factor receptor (EGFR) with the anticancer potential against various cancers. We aim to investigate anti-breast cancer effects and mechanism of action of novel indoline derivatives. Molecular docking of seven indoline derivates with EGFR revealed, N-(2-hydroxy-5-nitrophenyl (4'-methylphenyl) methyl) indoline (HNPMI) as the top lead compound. RT-PCR analysis showed the downregulation of PI3K/S6K1 genes in breast cancer cells through the activation of EGFR with HNPMI. This compound found to have higher cytotoxicity than Cyclophosphamide, with the IC₅₀ of 64.10 μM in MCF-7 and 119.99 μM in SkBr3 cells. HNPMI significantly reduced the cell proliferation of MCF-7 and SkBr3 cells, without affecting non-cancerous cells, H9C2. Induction of apoptosis was analyzed by Caspase-3 and -9, DNA fragmentation, AO/EtBr staining and flow cytometry assays. A fold change of 0.218- and 0.098- for caspase-3 and 0.478- and 0.269- for caspase-9 in MCF7 and SkBr3 cells was observed, respectively. Caspase mediated apoptosis caused DNA fragmentation in breast cancer cells upon HNPMI treatment. The structural elucidation of HNPMI by QSAR model and ADME-Tox suggests, a bi-molecular interaction of HNPMI-EGFR which is related to antiproliferative and apoptotic activity. The data concludes that, HNPMI-induced the apoptosis via EGFR signaling pathway in breast cancer cells. Thus, HNPMI might serve as a scaffold for developing a potential anti-breast cancer therapeutic agent.

Anticancer activity of THMPP: Downregulation of PI3K/ S6K1 in breast cancer cell line

Breast cancer is the most common cancer that majorly affects female. The present study is focused on exploring the potential anticancer activity of 2-((1, 2, 3, 4-Tetrahydroquinolin-1-yl) (4 methoxyphenyl) methyl) phenol (THMPP), against human breast cancer. The mechanism of action, activation of specific signaling pathways, structural activity relationship and drug-likeness properties of THMPP remains elusive. Cell proliferation and viability assay, caspase enzyme activity, DNA fragmentation and FITC/Annexin V, AO/EtBr staining, RT-PCR, QSAR and ADME analysis were executed to understand the mode of action of the drug. The effect of THMPP on multiple breast cancer cell lines (MCF-7 and SkBr3), and non-tumorigenic cell line (H9C2) was assessed by MTT assay. THMPP at IC50 concentration of 83.23 μM and 113.94 μM, induced cell death in MCF-7 and SkBr3 cells, respectively. Increased level of caspase-3 and -9, fragmentation of DNA, translocation of phosphatidylserine membrane and morphological changes in the cells confirmed the effect of THMPP in inducing the apoptosis. Gene expression analysis has shown that THMPP was able to downregulate the expression of PI3K/S6K1 genes, possibly via EGFR signaling pathway in both the cell lines, MCF-7 and SkBr3. Further, molecular docking also confirms the potential binding of THMPP with EGFR. QSAR and ADME analysis proved THMPP as an effective anti-breast cancer drug, exhibiting important pharmacological properties. Overall, the results suggest that THMPP induced cell death might be regulated by EGFR signaling pathway which augments THMPP being developed as a potential candidate for treating breast cancer.

Combining deep learning with token selection for patient phenotyping from electronic health records

Artificial intelligence provides the opportunity to reveal important information buried in large amounts of complex data. Electronic health records (eHRs) are a source of such big data that provide a multitude of health related clinical information about patients. However, text data from eHRs, e.g., discharge summary notes, are challenging in their analysis because these notes are free-form texts and the writing formats and styles vary considerably between different records. For this reason, in this paper we study deep learning neural networks in combination with natural language processing to analyze text data from clinical discharge summaries. We provide a detail analysis of patient phenotyping, i.e., the automatic prediction of ten patient disorders, by investigating the influence of network architectures, sample sizes and information content of tokens. Importantly, for patients suffering from Chronic Pain, the disorder that is the most difficult one to classify, we find the largest performance gain for a combined word- and sentence-level input convolutional neural network (ws-CNN). As a general result, we find that the combination of data quality and data quantity of the text data is playing a crucial role for using more complex network architectures that improve significantly beyond a word-level input CNN model. From our investigations of learning curves and token selection mechanisms, we conclude that for such a transition one requires larger sample sizes because the amount of information per sample is quite small and only carried by few tokens and token categories. Interestingly, we found that the token frequency in the eHRs follow a Zipf law and we utilized this behavior to investigate the information content of tokens by defining a token selection mechanism. The latter addresses also issues of explainable AI.

Ensuring Quality Standards and Reproducible Research for Data Analysis Services in Oncology: A Cooperative Service Model

Modern molecular high-throughput devices, e.g., next-generation sequencing, have transformed medical research. Resulting data sets are usually high-dimensional on a genomic-scale providing multi-factorial information from intertwined molecular and cellular activities of genes and their products. This genomics-revolution installed precision medicine offering breathtaking opportunities for patient's diagnosis and treatment. However, due to the speed of these developments the quality standards of the involved data analyses are lacking behind, as exemplified by the infamous Duke Saga. In this paper, we argue in favor of a two-stage cooperative serve model that couples data generation and data analysis in the most beneficial way from the perspective of a patient to ensure data analysis quality standards including reproducible research.

Data-driven multiscale modeling reveals the role of metabolic coupling for the spatio-temporal growth dynamics of yeast colonies

BACKGROUND

Multicellular entities like mammalian tissues or microbial biofilms typically exhibit complex spatial arrangements that are adapted to their specific functions or environments. These structures result from intercellular signaling as well as from the interaction with the environment that allow cells of the same genotype to differentiate into well-organized communities of diversified cells. Despite its importance, our understanding how this cell-cell and metabolic coupling lead to functionally optimized structures is still limited.

RESULTS

Here, we present a data-driven spatial framework to computationally investigate the development of yeast colonies as such a multicellular structure in dependence on metabolic capacity. For this purpose, we first developed and parameterized a dynamic cell state and growth model for yeast based on on experimental data from homogeneous liquid media conditions. The inferred model is subsequently used in a spatially coarse-grained model for colony development to investigate the effect of metabolic coupling by calibrating spatial parameters from experimental time-course data of colony growth using state-of-the-art statistical techniques for model uncertainty and parameter estimations. The model is finally validated by independent experimental data of an alternative yeast strain with distinct metabolic characteristics and illustrates the impact of metabolic coupling for structure formation.

CONCLUSIONS

We introduce a novel model for yeast colony formation, present a statistical methodology for model calibration in a data-driven manner, and demonstrate how the established model can be used to generate predictions across scales by validation against independent measurements of genetically distinct yeast strains.

Battling Glioblastoma: A Novel Tyrosine Kinase Inhibitor with Multi-Dimensional Anti-Tumor Effect (Running Title: Cancer Cells Death Signalling Activation)

Glioblastoma (GB), a grade IV glioma, with high heterogeneity and chemoresistance, obligates a multidimensional antagonist to debilitate its competence. Considering the previous reports on thioesters as antitumor compounds, this paper investigates on use of this densely functionalized sulphur rich molecule as a potent anti-GB agent. Bio-evaluation of 12 novel compounds, containing α-thioether ketone and orthothioester functionalities, identified that five analogs exhibited better cytotoxic profile compared to standard drug cisplatin. Detailed toxicity studies of top compound were evaluated in two cell lines, using cell viability test, apoptotic activity, oxidative stress and caspase activation and RNA-sequencing analysis, to obtain a comprehensive molecular profile of drug activity. The most effective molecule presented half maximal inhibitory concentration (IC₅₀) values of 27 μM and 23 μM against U87 and LN229 GB cells, respectively. Same compound effectively weakened various angiogenic pathways, mainly MAPK and JAK-STAT pathways, downregulating VEGF. Transcriptome analysis identified significant promotion of apoptotic genes, and genes involved in cell cycle arrest, with concurrent inhibition of various tyrosine kinase cascades and stress response genes. Docking and immunoblotting studies suggest EGFR as a strong target of the orthothioester identified. Therefore, orthothioesters can potentially serve as a multi-dimensional chemotherapeutic possessing strong cytotoxic, anti-angiogenic and chemo-sensitization activity, challenging glioblastoma pathogenesis.

Utilizing Social Media Data for Psychoanalysis to Study Human Personality

Social media data, for instance from Twitter or Facebook, provide a new type of data that consist of a mixture of text, image and video information. From a scientific point of view, the capabilities of this type of data from such microblogs are not well explored and to date it is largely unknown what principal knowledge can be extracted thereof. In this paper, we present a discussion of the capabilities of data from microblogs for performing a psychoanalysis. This could allow an analysis of the human personality of individual users. Such prospects raises serious concerns regarding the privacy of users of social media platforms.

In vitro anti-glioblastoma activity of L-valine derived boroxazolidones

In the present study, a series of L-valine derived boroxazolidones, previously synthesized and reported to have residual activity in a human epithelial cell line, have been evaluated in vitro for their anti-glioblastoma activity. A boroxazolidone derivative containing 2,4-difluorophenyl moieties (6) was found to have higher cytotoxicity than the standard drug, Temozolomide (TMZ). Compound 6 was found to exhibit dose-dependent growth inhibitory effects with an IC₅₀ of 49 μM and 53 μM for LN229 and SNB19 cells, respectively. Additionally, 6 was assessed for its role in apoptosis, caspase 3/7 activation and oxidative stress in SNB19 and LN229 cells. SNB19 cells treated with 6 showed 45.3% apoptosis in the population, while TMZ had 24.7%. In LN229 cells, the percentage of apoptotic cells treated with compound 6 and TMZ were the same. Both 6 and TMZ induced apoptosis through the activation of caspase 3/7 in SNB19 and LN229 cells. Interestingly, 6 exhibited a higher effectivity in promoting reactive oxygen species production in LN229, while it was 6-fold less in SNB19. Boroxazolidone-treated GBM cell lines increased reactive oxygen species production, suggesting that such species may be interlinked with the observed programmed cell death. Additionally, the treatment of both GBM cell lines with 6 led to G2/M phase arrest. The magnitude of anti-GBM effect of 6 is significantly higher than the known chemotherapeutic agent TMZ. This work further demonstrates the anticancer properties of L-valine derived boroxazolidones, adding another potential derivative to the collection of promising chemotherapeutic agents for GBM treatment.

Systems Pharmacogenomic Landscape of Drug Similarities from LINCS data: Drug Association Networks

Modern research in the biomedical sciences is data-driven utilizing high-throughput technologies to generate big genomic data. The Library of Integrated Network-based Cellular Signatures (LINCS) is an example for a large-scale genomic data repository providing hundred thousands of high-dimensional gene expression measurements for thousands of drugs and dozens of cell lines. However, the remaining challenge is how to use these data effectively for pharmacogenomics. In this paper, we use LINCS data to construct drug association networks (DANs) representing the relationships between drugs. By using the Anatomical Therapeutic Chemical (ATC) classification of drugs we demonstrate that the DANs represent a systems pharmacogenomic landscape of drugs summarizing the entire LINCS repository on a genomic scale meaningfully. Here we identify the modules of the DANs as therapeutic attractors of the ATC drug classes.

Alkylaminophenol Induces G1/S Phase Cell Cycle Arrest in Glioblastoma Cells Through p53 and Cyclin-Dependent Kinase Signaling Pathway

Glioblastoma (GBM) is the most common type of malignant brain tumor in adults. We show here that small molecule 2-[(3,4-dihydroquinolin-1(2H)-yl)(p-tolyl)methyl]phenol (THTMP), a potential anticancer agent, increases the human glioblastoma cell death. Its mechanism of action and the interaction of selective signaling pathways remain elusive. Three structurally related phenolic compounds were tested in multiple glioma cell lines in which the potential activity of the compound, THTMP, was further validated and characterized. Upon prolonged exposer to THTMP, all glioma cell lines undergo p53 and cyclin-dependent kinase mediated cell death with the IC₅₀ concentration of 26.5 and 75.4 μM in LN229 and Snb19, respectively. We found that THTMP strongly inhibited cell growth in a dose and in time dependent manner. THTMP treatment led to G1/S cell cycle arrest and apoptosis induction of glioma cell lines. Furthermore, we identified 3,714 genes with significant changes at the transcriptional level in response to THTMP. Further, a transcriptional analysis (RNA-seq) revealed that THTMP targeted the p53 signaling pathway specific genes causing DNA damage and cell cycle arrest at G1/S phase explained by the decrease of cyclin-dependent kinase 1, cyclin A2, cyclin E1 and E2 in glioma cells. Consistently, THTMP induced the apoptosis by regulating the expression of Bcl-2 family genes and reactive oxygen species while it also changed the expression of several anti-apoptotic genes. These observations suggest that THTMP exerts proliferation activity inhibition and pro-apoptosis effects in glioma through affecting cell cycle arrest and intrinsic apoptosis signaling. Importantly, THTMP has more potential at inhibiting GBM cell proliferation compared to TMZ, the current chemotherapy treatment administered to GBM patients; thus, we propose that THTMP may be an alternative therapeutic option for glioblastoma.

Decane-1,2-diol derivatives as potential antitumor agents for the treatment of glioblastoma

Glioblastoma remains the most common and aggressive type of malignant brain tumor among adults thus, considerable attention has been given to discovery of novel anti-tumor drugs for its treatment. This study reports the synthesis of a series of twelve novel decane-1,2-diol derivatives and evaluation of its anti-tumor activity in mammalian glioblastoma cell lines, U87 and LN229. Starting from decane-1,2-diol, several derivatives were prepared using a diversity oriented synthesis approach through which a small library composed of esters, silyl ethers, sulfonates, sulfites, sulfates, ketals, and phosphonates was built. The decane-1,2-diol ditosylated derivative, DBT, found to have higher cytotoxicity than the standard drug cisplatin, has IC₅₀ value of 52 µM in U87 and 270 µM in LN229. Migration analysis of U87 cell line treated with the DBT indicated its ability to effectively suppress proliferation during initial hours of treatment and decrease anti-proliferative property over time. Additionally, DBT was assessed for its role in apoptosis, oxidative stress and caspase 3/7 activation in U87. Interestingly, our experiments indicated that its cytotoxicity is independent of Reactive oxygen species induced caspase 3/7 activity. The compound also exhibited caspase independent apoptosis activity in U87. DBT treatment led to G1/S cell cycle arrest and apoptosis induction of glioma cell lines. In addition, we identified 1533 genes with significant changes at the transcriptional level, in response to DBT. A molecular docking study accounting for the interaction of DBT with NMDA receptor disclosed several hydrogen bonds and charged residue interactions with 17 amino acids, which might be the basis of the DBT cytotoxicity observed. We conclude that this molecule exerts its cytotoxicity via caspase 3/7 independent pathways in glioblastoma cells. Concisely, simple decane-1,2-diol derivatives might serve as scaffolds for the development of effective anti-glioblastoma agents.

Strong FGFR3 staining is a marker for FGFR3 fusions in diffuse gliomas

Background

Inhibitors of fibroblast growth factor receptors (FGFRs) have recently arisen as a promising treatment option for patients with FGFR alterations. Gene fusions involving FGFR3 and transforming acidic coiled-coil protein 3 (TACC3) have been detected in diffuse gliomas and other malignancies, and fusion-positive cases have responded well to FGFR inhibition. As high FGFR3 expression has been detected in fusion-positive tumors, we sought to determine the clinical significance of FGFR3 protein expression level as well as its potential for indicating FGFR3 fusions.

Methods

We performed FGFR3 immunohistochemistry on tissue microarrays containing 676 grades II-IV astrocytomas and 116 grades II-III oligodendroglial tumor specimens. Fifty-one cases were further analyzed using targeted sequencing.

Results

Moderate to strong FGFR3 staining was detected in gliomas of all grades, was more common in females, and was associated with poor survival in diffuse astrocytomas. Targeted sequencing identified FGFR3-TACC3 fusions and an FGFR3-CAMK2A fusion in 10 of 15 strongly stained cases, whereas no fusions were found in 36 negatively to moderately stained cases. Fusion-positive cases were predominantly female and negative for IDH and EGFR/PDGFRA/MET alterations. These and moderately stained cases show lower MIB-1 proliferation index than negatively to weakly stained cases. Furthermore, stronger FGFR3 expression was commonly observed in malignant tissue regions of lower cellularity in fusion-negative cases. Importantly, subregional negative FGFR3 staining was also observed in a few fusion-positive cases.

Conclusions

Strong FGFR3 protein expression is indicative of FGFR3 fusions and may serve as a clinically applicable predictive marker for treatment regimens based on FGFR inhibitors.

Abstract 3427: Gatekeeper inactivation drives glioma progression into secondary glioblastoma

<Glioblastoma (GBM) is the most common and lethal form of brain cancer in humans. Median survival is 15 months with best available treatment. Most GBMs arise de novo (primary GBM), but 5 - 10% progress from lower grade gliomas (secondary GBM). As progression of low grade glioma into secondary GBM significantly impacts prognosis, a better understanding of this process is paramount for treatment and monitoring of affected patients. In this study, we applied whole genome and transcriptome sequencing to primary glioma and relapsed secondary GBM tissue from seven patients with progression. All primary gliomas carried IDH1 mutations, and in all cases the mutation was inherited by the secondary GBM. ATRX alterations in all five astrocytomas and TERT promoter mutations in both 1p19q-codeleted oligoastrocytomas were also inherited in progressed tumors. In five patients, progression was associated with increased genomic instability, whereas mutation load was significantly increased in two other patients. One of them exhibited a hypermutation signature caused by a mutation in the proofreading domain of DNA polymerase epsilon, while the second had lost both copies of the DNA mismatch protein MSH2. In addition, both 1p19q-codeleted tumors had acquired focal inactivating deletions of the protein tyrosine phosphatase PTPRD at progression, suggesting a novel driver mechanism for GBM progression. The most common progression-related genomic alterations were CDKN2A deletions, TP53 mutations, RB1 deletions, PTEN deletions, and deletions of genes crucial to the double strand break repair pathway. Taken together, progression into secondary GBM was significantly related to deletions in tumor suppressor genes as well as TP53 mutations. Disruption of these gatekeepers appears to be a significant mechanism for glioma progression.>

Citation Format: Kirsi Johanna Granberg, Matti Annala, Serafiina Jaatinen, Joonas Haapasalo, Olli Yli-Harja, Hannu Haapasalo, Wei Zhang, Matti Nykter. Gatekeeper inactivation drives glioma progression into secondary glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3427.

Anticancer activity study of A3 adenosine receptor agonists

AIMS

A₃ adenosine receptor (A₃AR) signalling activation seems to mediate anticancer effect, and it has been targeted for drug development. The identification of potent and selective A₃AR agonists could be crucial for cancer drug development.

MATERIALS AND METHODS

In the present study was determined the in vitro activity of known 1-3 and newly 4-6 synthesized compounds with high A₃AR affinity and selectivity (K_i in the low nanomolar range) in binding studies. Effect of known and novel A₃AR agonists on human prostate cancer (PC3), hepatocellular carcinoma (Hep G2), and epithelial colorectal carcinoma (Caco-2) cells were analysed by cytotoxicity assay, dose and time dependent inhibitor assay, migration, apoptosis, autophagy and reactive oxygen species (ROS) assays.

KEY FINDINGS

Results show that the anticancer effect is not due to A₃AR activation alone. In fact, the more active and selective agonist versus A₃AR, compound 1, results inactive on cancer cells such as compounds 2-4. Moreover, results show that the novel compound 5, at micromolar concentration range (IC₅₀ = 28.0 μM), inhibits the growth of PC3, Hep G2, and Caco-2 cells and their migration in time- and dose- dependent manner. The mechanism involved in cell death is attributable to apoptosis. At the same time compound 5 promotes autophagy, which induce apoptosis producing autophagic cell death. Further investigation revealed that compound 5 elevates the level of ROS in all cancer cells tested, suggesting the involvement of ROS in cell death.

SIGNIFICANCE

These results show that the new compound 5 exerts inhibitory effect on cancer cells through differential effect and may serve as a potential anticancer agent.

A review of connectivity map and computational approaches in pharmacogenomics

Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.

A review of connectivity map and computational approaches in pharmacogenomics

Large-scale perturbation databases, such as Connectivity Map (CMap) or Library of Integrated Network-based Cellular Signatures (LINCS), provide enormous opportunities for computational pharmacogenomics and drug design. A reason for this is that in contrast to classical pharmacology focusing at one target at a time, the transcriptomics profiles provided by CMap and LINCS open the door for systems biology approaches on the pathway and network level. In this article, we provide a review of recent developments in computational pharmacogenomics with respect to CMap and LINCS and related applications.

In vitro characterization of arylhydrazones of active methylene derivatives

Arylhydrazones of active methylene compounds (AHAMCs) are potent chemotherapy agents for the cancer treatment. AHAMCs enhance the apoptotic cell death and antiproliferation properties in cancer cells. In this study, a series of AHAMCs, 13 compounds, was assayed for cytotoxicity, apoptosis, externalization of phosphatidylserine, heterogeneity and cellular calcium level changes. The in vitro cytotoxicity study against HEK293T cells suggests that AHAMCs have significant cytotoxic effect over the concentrations. Top 5 compounds, 5-(2-(2-hydroxyphenyl) hydrazono)pyrimidine-2,4,6(1H,3H,5H)-trione (5), 4-hydroxy-5-(2-(2,4,6-trioxo-tetrahydro-pyrimidin-5(6H) ylidene)hydrazinyl)benzene-1,3-disulfonic acid (6), 5-chloro-3-(2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl)-2-hydroxybenzenesulfonic acid (8), 5-(2-(4,4-dimethyl-2,6-dioxocyclohexylidene)hydrazinyl)-4-hydroxybenzene-1,3-disulfonic acid (9) and 2-(2-sulfophenylhydrazo)malononitrile (10) were chosen for the pharmacodynamics study. Among these, compound 5 exhibited the better cytotoxic effect with the IC₅₀ of 50.86 ± 2.5 mM. DNA cleavage study revealed that 5 induces cell death through apoptosis and shows more effects after 24 and/or 48 h. Independent validation of apoptosis by following the externalization of phosphatidylserine using Annexin-V is also in agreement with the potential activity of 5. Single cell image analysis of Annexin-V bound cells confirms the presence of mixture of early, mid and late apoptotic cells in the population of the cells treated with 5 and a decreased trend in cell-to-cell variation over the phase was also identified. Additionally, intracellular calcium level measurements identified the Ca²⁺ up-regulation in compound treated cells. A brief inspection of the effect of the compound 5 against multiple human brain astrocytoma cells showed a better cell growth inhibitory effect at micro molar level. These systematic studies provide insights in the development of novel AHAMACs compounds as potential cell growth inhibitors for cancer treatment.

In vitro characterization of alkylaminophenols-induced cell death

Alkylaminophenols are synthetic derivatives well known for their anticancer activity. In the previous studies, we described the activity of the series of Alkylaminophenols derivatives and their ability to induce cell death for many cancer cell lines. However, temporal heterogeneity in cell death induced by lead compounds, N-(2-hydroxy-5-nitrophenyl (4'-methylphenyl) methyl) indoline (Compound I) and 2-((3,4-dihydroquinolin-1(2H)-yl) (4-methoxyphenyl) methyl) phenol (Compound II), has never been tested on osteosarcoma cells (U2OS). Here, we address the level of cell-to-cell heterogeneity by examine whether differences in the type of compounds could influence its effects on cell death of U2OS. Here, we applied imaging, computational methods and biochemical methods to study heterogeneity, apoptosis, reactive oxygen species and caspase. Our results demonstrate that the Hill coefficient of dose-response curve of Compound II is greater than compound I in treated U2OS cells. Both Compounds trigger not only apoptotic cell death but also necro-apoptotic and necrotic cell death. The percentage of these sub-populations varies depending on compounds in which greater variance is induced by compound II than Compound I. We also identified the accumulation of compounds-induced reactive oxygen species during the treatment. This resulted in caspase 3/7 activation in turn induced apoptosis. In summary, the screening of Compound I and II molecules for heterogeneity, apoptosis, reactive oxygen species and caspase has identified compound II as promising anti-osteosarcoma cancer agent. Compound II could be a promising lead compound for future antitumor agent development.

Identification of novel GPR17-agonists by structural bioinformatics and signaling activation

G Protein-coupled Receptor 17 (GPR17) is phylogenetically related to the purinergic receptors emerged as a potential drug target for multiple sclerosis, Parkinson disease, Alzheimer disease and cancer. Unfortunately, the crystal structure of GPR17 is unresolved. With the interest in structure-based ligand discovery, we modeled the structure of GPR17. The model allowed us to identify two novel agonists, AC1MLNKK and T0510.3657 that selectively activate GPR17 which exhibit better interaction properties than previously known ligand, MDL29951. We report detailed protein-ligand interactions and the dynamics of GPR17-ligand interaction by molecular docking and molecular dynamics experiments. Ex vivo validation of GPR17-ligand interaction provides evidence that ligand T0510-3657 and AC1MLNKK inhibit the cAMP levels in GPR17-HEK293T cells, with a pEC₅₀ of 4.79 and 4.64, respectively. In silico and ex vivo validation experiments provided the deep understanding of ligand binding with GPR17 and the present findings reported here may lead to use these two compounds as a potential activator of GPR17 for therapeutic intervention.

Effect of alkylaminophenols on growth inhibition and apoptosis of bone cancer cells

In this work, we report the anticancer properties of a series of 11 chemically synthesized alkylaminophenols against human osteosarcoma U2OS tumor cell line. Several assays including cytotoxicity, inhibitor kinetic study, cell migration, Annexin-V/PI double staining, reactive oxygen species (ROS) and caspase 3/7 assays were conducted on this cell line. Cytotoxic 2-((3,4-dihydroquinolin-1(2H)-yl)(p-tolyl)methyl)phenol was determined to have an IC₅₀ value of 36.6μM against U2OS cells and it also inhibits the cell growth in time-dependent manner. The potent activity of lead compound against the growth of multiple cell lines, U2OS, MG-65 and HEK-293T, confirms the osteosarcoma cell specific inhibition. Further studies indicated that such compound is an inhibitor of metastatic property of tumor cells and inducing apoptosis agent. The ability of increasing ROS and inducing caspases 3 and 7 further confirm the contribution of programmed cell death in U2OS and HEK-293T cells. Additionally, four compounds based on the 2-(indolin-1-yl(aryl)methyl)-4-nitrophenol core were also identified to be cytotoxic with IC₅₀ values in the 66-88μM range. This work further demonstrates the anticancer properties of phenol derivatives, adding one more entry to the collection of promising chemotherapeutic agents for cancer treatment.

sgnesR: An R package for simulating gene expression data from an underlying real gene network structure considering delay parameters

Background

sgnesR (Stochastic Gene Network Expression Simulator in R) is an R package that provides an interface to simulate gene expression data from a given gene network using the stochastic simulation algorithm (SSA). The package allows various options for delay parameters and can easily included in reactions for promoter delay, RNA delay and Protein delay. A user can tune these parameters to model various types of reactions within a cell. As examples, we present two network models to generate expression profiles. We also demonstrated the inference of networks and the evaluation of association measure of edge and non-edge components from the generated expression profiles.

Results

The purpose of sgnesR is to enable an easy to use and a quick implementation for generating realistic gene expression data from biologically relevant networks that can be user selected.

Conclusions

sgnesR is freely available for academic use. The R package has been tested for R 3.2.0 under Linux, Windows and Mac OS X.

Electronic supplementary material

The online version of this article (doi:10.1186/s12859-017-1731-8) contains supplementary material, which is available to authorized users.