SAP30, an oncogenic driver of progression, poor survival, and drug resistance in neuroblastoma.

Neuroblastoma is the most devastating extracranial solid malignancy in children. Despite an intense treatment regimen, the prognosis for high-risk neuroblastoma patients remains poor, with less than 40% survival. So far, MYCN amplification status is considered the most prognostic factor but corresponds to only ∼25% of neuroblastoma patients. Therefore, it is essential to identify a better prognosis and therapy response marker in neuroblastoma patients. We applied robust bioinformatic data mining tools, such as weighted gene co-expression network analysis, cisTarget, and single-cell regulatory network inference and clustering on two neuroblastoma patient datasets. We found Sin3A-associated protein 30 (SAP30), a driver transcription factor positively associated with high-risk, progression, stage 4, and poor survival in neuroblastoma patient cohorts. Tumors of high-risk neuroblastoma patients and relapse-specific patient-derived xenografts showed higher SAP30 levels. The advanced pharmacogenomic analysis and CRISPR-Cas9 screens indicated that SAP30 essentiality is associated with cisplatin resistance and further showed higher levels in cisplatin-resistant patient-derived xenograft tumor cell lines. Silencing of SAP30 induced cell death in vitro and led to a reduced tumor burden and size in vivo. Altogether, these results indicate that SAP30 is a better prognostic and cisplatin-resistance marker and thus a potential drug target in high-risk neuroblastoma.

Immune checkpoint molecules in neuroblastoma: A clinical perspective.

High-risk neuroblastoma (NB) is challenging to treat with 5-year long-term survival in patients remaining below 50% and low chances of survival after tumor relapse or recurrence. Different strategies are being tested or under evaluation to destroy resistant tumors and improve survival outcomes in NB patients. Immunotherapy, which uses certain parts of a person's immune system to recognize or kill tumor cells, effectively improves patient outcomes in several types of cancer, including NB. One of the immunotherapy strategies is to block immune checkpoint signaling in tumors to increase tumor immunogenicity and anti-tumor immunity. Immune checkpoint proteins put brakes on immune cell functions to regulate immune activation, but this activity is exploited in tumors to evade immune surveillance and attack. Immune checkpoint proteins play an essential role in NB biology and immune escape mechanisms, which makes these tumors immunologically cold. Therapeutic strategies to block immune checkpoint signaling have shown promising outcomes in NB but only in a subset of patients. However, combining immune checkpoint blockade with other therapies, including conjugated antibody-based immunotherapy, radioimmunotherapy, tumor vaccines, or cellular therapies like modified T or natural killer (NK) cells, has shown encouraging results in enhancing anti-tumor immunity in the preclinical setting. An analysis of publicly available dataset using computational tools has unraveled the complexity of multiple cancer including NB. This review comprehensively summarizes the current information on immune checkpoint molecules, their biology, role in immune suppression and tumor development, and novel therapeutic approaches combining immune checkpoint inhibitors with other therapies to combat high-risk NB.

miR-15a and miR-15b modulate natural killer and CD8+T-cell activation and anti-tumor immune response by targeting PD-L1 in neuroblastoma.

Neuroblastoma (NB) is an enigmatic and deadliest pediatric cancer to treat. The major obstacles to the effective immunotherapy treatments in NB are defective immune cells and the immune evasion tactics deployed by the tumor cells and the stromal microenvironment. Nervous system development during embryonic and pediatric stages is critically mediated by non-coding RNAs such as micro RNAs (miR). Hence, we explored the role of miRs in anti-tumor immune response via a range of data-driven workflows and in vitro & in vivo experiments. Using the TARGET, NB patient dataset (n=249), we applied the robust bioinformatic workflows incorporating differential expression, co-expression, survival, heatmaps, and box plots. We initially demonstrated the role of miR-15a-5p (miR-15a) and miR-15b-5p (miR-15b) as tumor suppressors, followed by their negative association with stromal cell percentages and a statistically significant negative regulation of T and natural killer (NK) cell signature genes, especially CD274 (PD-L1) in stromal-low patient subsets. The NB phase-specific expression of the miR-15a/miR-15b-PD-L1 axis was further corroborated using the PDX (n=24) dataset. We demonstrated miR-15a/miR-15b mediated degradation of PD-L1 mRNA through its interaction with the 3'-untranslated region and the RNA-induced silencing complex using sequence-specific luciferase activity and Ago2 RNA immunoprecipitation assays. In addition, we established miR-15a/miR-15b induced CD8+T and NK cell activation and cytotoxicity against NB in vitro. Moreover, injection of murine cells expressing miR-15a reduced tumor size, tumor vasculature and enhanced the activation and infiltration of CD8+T and NK cells into the tumors in vivo. We further established that blocking the surface PD-L1 using an anti-PD-L1 antibody rescued miR-15a/miR-15b induced CD8+T and NK cell-mediated anti-tumor responses. These findings demonstrate that miR-15a and miR-15b induce an anti-tumor immune response by targeting PD-L1 in NB.

The emerging role of non-coding RNAs in the epigenetic regulation of pediatric cancers.

Epigenetics is a process that involves the regulation of gene expression without altering the sequence of DNA. Numerous studies have documented that epigenetic mechanisms play a critical role in cell growth, differentiation, and cancer over the past decade. The well-known epigenetic modifications are either on DNA or at the histone proteins. Although several studies have focused on regulating gene expression by non-coding RNAs, the current understanding of their biological functions in various human diseases, particularly in cancers, is inadequate. Only about two percent of DNA is involved in coding the protein-coding genes, and leaving the rest 98 percent is non-coding and the scientific community regarded as junk or noise with no known purpose. Most non-coding RNAs are derived from such junk DNA and are known to be involved in various signaling pathways involving cancer initiation, progression, and the development of therapy resistance in many human cancer types. Recent studies have suggested that non-coding RNAs, especially microRNAs, piwi-interactingRNAs, and long non-coding RNAs, play a significant role in controlling epigenetic mechanism(s), indicating the potential effect of epigenetic modulation of non-coding RNAs on cancer progression. In this review article, we briefly presented epigenetic marks' characteristics, crosstalk between epigenetic modifications and microRNAs, piwi-interactingRNAs, and long non-coding RNAs to uncover the effect on the phenotype of pediatric cancers. Further, current knowledge on understanding the RNA epigenetics will help design novel therapeutics that target epigenetic regulatory networks to benefit cancer patients in the clinic.

New insights into exosome mediated tumor-immune escape: Clinical perspectives and therapeutic strategies.

Recent advances in extracellular vesicle biology have uncovered a substantial role in maintaining cell homeostasis in health and disease conditions by mediating intercellular communication, thus catching the scientific community's attention worldwide. Extracellular microvesicles, some called exosomes, functionally transfer biomolecules such as proteins and non-coding RNAs from one cell to another, influencing the local environment's biology. Although numerous advancements have been made in treating cancer patients with immune therapy, controlling the disease remains a challenge in the clinic due to tumor-driven interference with the immune response and inability of immune cells to clear cancer cells from the body. The present review article discusses the recent findings and knowledge gaps related to the role of exosomes derived from tumors and the tumor microenvironment cells in tumor escape from immunosurveillance. Further, we highlight examples where exosomal non-coding RNAs influence immune cells' response within the tumor microenvironment and favor tumor growth and progression. Therefore, exosomes can be used as a therapeutic target for the treatment of human cancers.

COVID-19 and Cancer Comorbidity: Therapeutic Opportunities and Challenges.

The coronavirus disease 2019 (COVID-19) is a viral disease caused by a novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that affects the respiratory system of infected individuals. COVID-19 spreads between humans through respiratory droplets produced when an infected person coughs or sneezes. The COVID-19 outbreak originated in Wuhan, China at the end of 2019. As of 29 Sept 2020, over 235 countries, areas or territories across the globe reported a total of 33,441,919 confirmed cases, and 1,003,497 confirmed deaths due to COVID-19. Individuals of all ages are at risk for infection, but in most cases disease severity is associated with age and pre-existing diseases that compromise immunity, like cancer. Numerous reports suggest that people with cancer can be at higher risk of severe illness and related deaths from COVID-19. Therefore, managing cancer care under this pandemic is challenging and requires a collaborative multidisciplinary approach for optimal care of cancer patients in hospital settings. In this comprehensive review, we discuss the impact of the COVID-19 pandemic on cancer patients, their care, and treatment. Further, this review covers the SARS-CoV-2 pandemic, genome characterization, COVID-19 pathophysiology, and associated signaling pathways in cancer, and the choice of anticancer agents as repurposed drugs for treating COVID-19.

Amino Acids Regulate Cisplatin Insensitivity in Neuroblastoma.

Neuroblastoma are pediatric, extracranial malignancies showing alarming survival prognosis outcomes due to their resilience to current aggressive treatment regimens, including chemotherapies with cisplatin (CDDP) provided in the first line of therapy regimens. Metabolic deregulation supports tumor cell survival in drug-treated conditions. However, metabolic pathways underlying cisplatin-resistance are least studied in neuroblastoma. Our metabolomics analysis revealed that cisplatin-insensitive cells alter their metabolism; especially, the metabolism of amino acids was upregulated in cisplatin-insensitive cells compared to the cisplatin-sensitive neuroblastoma cell line. A significant increase in amino acid levels in cisplatin-insensitive cells led us to hypothesize that the mechanisms upregulating intracellular amino acid pools facilitate insensitivity in neuroblastoma. We hereby report that amino acid depletion reduces cell survival and cisplatin-insensitivity in neuroblastoma cells. Since cells regulate their amino acids levels through processes, such as autophagy, we evaluated the effects of hydroxychloroquine (HCQ), a terminal autophagy inhibitor, on the survival and amino acid metabolism of cisplatin-insensitive neuroblastoma cells. Our results demonstrate that combining HCQ with CDDP abrogated the amino acid metabolism in cisplatin-insensitive cells and sensitized neuroblastoma cells to sub-lethal doses of cisplatin. Our results suggest that targeting of amino acid replenishing mechanisms could be considered as a potential approach in developing combination therapies for treating neuroblastomas.

Identification of potential inhibitors based on compound proposal contest: Tyrosine-protein kinase Yes as a target.

A search of broader range of chemical space is important for drug discovery. Different methods of computer-aided drug discovery (CADD) are known to propose compounds in different chemical spaces as hit molecules for the same target protein. This study aimed at using multiple CADD methods through open innovation to achieve a level of hit molecule diversity that is not achievable with any particular single method. We held a compound proposal contest, in which multiple research groups participated and predicted inhibitors of tyrosine-protein kinase Yes. This showed whether collective knowledge based on individual approaches helped to obtain hit compounds from a broad range of chemical space and whether the contest-based approach was effective.

A robust tool for discriminative analysis and feature selection in paired samples impacts the identification of the genes essential for reprogramming lung tissue to adenocarcinoma.

BACKGROUND: Lung cancer is the leading cause of cancer deaths in the world. The most common type of lung cancer is lung adenocarcinoma (AC). The genetic mechanisms of the early stages and lung AC progression steps are poorly understood. There is currently no clinically applicable gene test for the early diagnosis and AC aggressiveness. Among the major reasons for the lack of reliable diagnostic biomarkers are the extraordinary heterogeneity of the cancer cells, complex and poorly understudied interactions of the AC cells with adjacent tissue and immune system, gene variation across patient cohorts, measurement variability, small sample sizes and sub-optimal analytical methods. We suggest that gene expression profiling of the primary tumours and adjacent tissues (PT-AT) handled with a rational statistical and bioinformatics strategy of biomarker prediction and validation could provide significant progress in the identification of clinical biomarkers of AC. To minimise sample-to-sample variability, repeated multivariate measurements in the same object (organ or tissue, e.g. PT-AT in lung) across patients should be designed, but prediction and validation on the genome scale with small sample size is a great methodical challenge. RESULTS: To analyse PT-AT relationships efficiently in the statistical modelling, we propose an Extreme Class Discrimination (ECD) feature selection method that identifies a sub-set of the most discriminative variables (e.g. expressed genes). Our method consists of a paired Cross-normalization (CN) step followed by a modified sign Wilcoxon test with multivariate adjustment carried out for each variable. Using an Affymetrix U133A microarray paired dataset of 27 AC patients, we reviewed the global reprogramming of the transcriptome in human lung AC tissue versus normal lung tissue, which is associated with about 2,300 genes discriminating the tissues with 100% accuracy. Cluster analysis applied to these genes resulted in four distinct gene groups which we classified as associated with (i) up-regulated genes in the mitotic cell cycle lung AC, (ii) silenced/suppressed gene specific for normal lung tissue, (iii) cell communication and cell motility and (iv) the immune system features. The genes related to mutagenesis, specific lung cancers, early stage of AC development, tumour aggressiveness and metabolic pathway alterations and adaptations of cancer cells are strongly enriched in the AC PT-AT discriminative gene set. Two AC diagnostic biomarkers SPP1 and CENPA were successfully validated on RT-RCR tissue array. ECD method was systematically compared to several alternative methods and proved to be of better performance and as well as it was validated by comparison of the predicted gene set with literature meta-signature. CONCLUSIONS: We developed a method that identifies and selects highly discriminative variables from high dimensional data spaces of potential biomarkers based on a statistical analysis of paired samples when the number of samples is small. This method provides superior selection in comparison to conventional methods and can be widely used in different applications. Our method revealed at least 23 hundreds patho-biologically essential genes associated with the global transcriptional reprogramming of human lung epithelium cells and lung AC aggressiveness. This gene set includes many previously published AC biomarkers reflecting inherent disease complexity and specifies the mechanisms of carcinogenesis in the lung AC. SPP1, CENPA and many other PT-AT discriminative genes could be considered as the prospective diagnostic and prognostic biomarkers of lung AC.

alpha-Amino acid derivatives as proton pump inhibitors and potent anti-ulcer agents.

In a program to identify new anti-ulcer compounds, a series of N-acyl derivatives of alpha-amino acids were screened for their in vitro H(+)/K(+) ATPase inhibitory activity, and in vivo efficacy in Pylorus ligation model. 3D-QSAR studies were carried out and a representative compound 13 was studied for the nature of its proton pump inhibition.

Evaluation of binary QSAR models derived from LUDI and MOE scoring functions for structure based virtual screening.

In today's world of high-throughput in silico screening, the development of virtual screening methodologies to prioritize small molecules as new chemical entities (NCEs) for synthesis is of current interest. Among several approaches to virtual screening, structure-based virtual screening has been considered the most effective. However the problems associated with the ranking of potential solutions in terms of scoring functions remains one of the major bottlenecks in structure-based virtual screening technology. It has been suggested that scoring functions may be used as filters for distinguishing binders from nonbinders instead of accurately predicting their binding free energies. Subsequently, several improvements have been made in this area, which include the use of multiple rather than single scoring functions and application of either consensus or multivariate statistical methods or both to improve the discrimination between binders and nonbinders. In view of it, the discriminative ability (distinguishing binders from nonbinders) of binary QSAR models derived using LUDI and MOE scoring functions has been compared with the models derived by Jacobbsson et al. on five data sets viz. estrogen receptor alphamimics (ERalpha_mimics), estrogen receptor alphatoxins (ERalpha_toxins), matrix metalloprotease 3 inhibitors (MMP-3), factor Xa inhibitors (fXa), and acetylcholine esterase inhibitors (AChE). The overall analyses reveal that binary QSAR is comparable to the PLS discriminant analysis, rule-based, and Bayesian classification methods used by Jacobsson et al. Further the scoring functions implemented in LUDI and MOE can score a wide range of protein-ligand interactions and are comparable to the scoring functions implemented in ICM and Cscore. Thus the binary QSAR models derived using LUDI and MOE scoring functions may be useful as a preliminary screening layer in a multilayered virtual screening paradigm.

2D-QSAR in hydroxamic acid derivatives as peptide deformylase inhibitors and antibacterial agents.

Peptide deformylase catalyzes the removal of N-formyl group from the N-formylmethionine of ribosome synthesized polypeptide in eubacteria. Quantitative structure-activity relationship (QSAR) studies have been carried out in a series of beta-sulfonyl and beta-sulfinyl hydroxamic acid derivatives for their PDF enzyme inhibitory and antibacterial activities against Escherichia coli DC2 and Moraxella catarrhalis RA21 which demonstrate that the PDF inhibitory activity in cell free and whole cell system increases with increase in molar refractivity and hydrophobicity. The comparison of the QSARs between the cell free and whole cell system indicate that the active binding sites in PDF isolated from E. coli and in M. catarrhalis RA21 are similar and the whole cell antibacterial activity is mainly due to the inhibition of PDF. Apart from this the QSARs on some matrixmetelloproteins (COL-1, COL-3, MAT and HME) and natural endopeptidase (NEP) indicate the possibilities of introducing selectivity in these hydroxamic acid derivatives for their PDF inhibitory activity.