Diffuse large B-cell lymphoma (DLBCL) is the most common form of non-Hodgkin lymphoma and frequently develops through the accumulation of several genetic variations. With the advancement in high-throughput techniques, in addition to mutations and copy number variations, structural variations have gained importance for their role in genome instability leading to tumorigenesis. In this study, in order to understand the genetics of DLBCL pathogenesis, we carried out a whole-genome mutation profile analysis of eleven human cell lines from germinal-center B-cell-like (GCB-7) and activated B-cell-like (ABC-4) subtypes of DLBCL. Analysis of genetic variations including small sequence variants and large structural variations across the cell lines revealed distinct variation profiles indicating the heterogeneous nature of DLBCL and the need for novel patient stratification methods to design potential intervention strategies. Validation and prognostic significance of the variants was assessed using annotations provided for DLBCL samples in cBioPortal for Cancer Genomics. Combining genetic variations revealed new subgroups between the subtypes and associated enriched pathways, viz., PI3K-AKT signaling, cell cycle, TGF-beta signaling, and WNT signaling. Mutation landscape analysis also revealed drug–variant associations and possible effectiveness of known and novel DLBCL treatments. From the whole-genome-based mutation analysis, our findings suggest putative molecular genetics of DLBCL lymphomagenesis and potential genomics-driven precision treatments. Diffuse large B-cell lymphoma (DLBCL) is the most aggressive form of non-Hodgkin’s lymphoma, demonstrating high molecular and clinical heterogeneity. Several classification systems have been proposed on the basis of the shared morphology, immunophenotype, clinical outcomes, etc., in order to stratify patients, decipher mechanisms of pathogenesis, and design suitable therapy ,2,3,4,5.Genetic variations, majorly categorized as small sequence variations (single-nucleotide variations and short insertion-deletions) and structural variations (copy number variations (CNVs), inversions, translocations, and mobile element insertions (MEIs)), are often associated with the initiation, progression, and varied outcomes in DLBCL ,8. SmallStructural variations (SVs) are broadly classified into balanced (translocations and inversions) and unbalanced variations . Despite balanced structural variations being generally harmless, the heterozygous condition of these variations is shown to result in genetic abnormalities and tumorigenesis. Recombination of VD(J) regions is another key event in antigen receptor loci of B cells and malfunction of the process that plays an important role in the generation of chromosomal translocations. Translocations of proto-oncogenes BCL6 and MYC (‘double-hit’) are observed in ≈10% of DLBCL cases and are categorized as ‘high-grade B-cell lymphoma’ by the WHO. These translocations are associated with deregulated cell cycle and faulty DNA repair mechanisms, leading to uncontrolled growth of lymphoma cells . AnotherAlthough the majority of DLBCL patients (≈60%) are cured with an R-CHOP immunochemotherapy regimen, a significant number of remaining patients do not benefit from it. Conversely, for a fraction of patients, it is refractory, whereas the rest succumb to progressive/relapsed disease. The difference in the outcome is indicative of the difference in the genetic variation profile of the patients. Recently, novel classifications of DLBCL subtypes have been proposed on the basis of genetic variations or including transcriptomic expression profiles. These studies have employed classification approaches such as random forest  or non-nCopy number aberrations are common in DLBCL  and have a very high impact due to their direct effect on oncogenes and tumor suppressor genes, as discussed in our earlier work . HoweverThe data comprised paired-end sequencing of lymphoma cell lines (7 GCB and 4 ABC subtypes) with a read length of 100 bp using an Illumina HiSeq 2000 platform . The whoFunctional annotation and prioritization of SSVs identified in DLBCL cell lines was carried out by the annotation module in SeqVItA. It provided annotations in three categories, viz., functional impact , clinical relevance , and variant/gene–drug associations (PharmGKB). Oncogenes (OGs) and tumor suppressor genes (TSGs) containing ‘high’ and ‘medium’ priority sequence variants and overlapping structural variants were identified using the Molecular Signatures Database (MSigDB) . ValidatThe number of SSVs, CNVs, INVs, TRAs, and MEIs identified across the 11 DLBCL cell lines are depicted in To assess the functional impact of SSVs and SVs in DLBCL lymphomagenesis, oncogenes and tumor suppressors encompassing these genetic variants were extracted using MSigDB  and are p-value: 0.03).Oncogenes and tumor suppressor genes containing ‘high’ and ‘medium’ priority mutations were extracted , and thoWe carried out an extensive functional analysis of CNVs in the 11 DLBCL cell lines in our previous work . BrieflyGenomic rearrangements through translocations were the most common type of genomic alterations detected in DLBCL. We observed both subtype-specific and commonly shared translocations between the GCB and ACB cell lines. Translocations between immunoglobulin heavy-chain (IgH) and BCL2 were observed in four GCB cell lines  in agreement with the cytogenetic results reported in the DSMZCellDive web portal , and betLimited studies have been carried out to identify and characterize inversions in DLBCL genomes probably because inversions are balanced variations and generally do not cause abnormality in the function of gene(s) spanning them. Nevertheless, a heterozygous inversion would result in the formation of abnormal chromatids and subsequently affect the gene expression. In our analysis, we observed several OGs and TSGs  altered due to heterozygous inversions . A largep-value: 9.77 × 10−9).The gene ABL2 is involved in cell growth and survival through cytoskeleton remodeling, while the gene PRRX1 enhances the DNA-binding activity of serum response factor, a protein required for the induction of genes by growth and differentiation factors. A large inversion of size 20 Mbp was observed at 11q12-q14 in the five DLBCL cell lines OCI-LY1, NU-DHL-1, SU-DHL-6, DOHH-2, and SU-DHL-9 and encompassed three oncogenes  and two TSGs . Among these, abnormal expression of CCND1 due to duplications/genomic rearrangements is previously reported in DLBCL , while hMobile element insertions, another common form of structural variations, were also observed in DLBCL cell lines. As shown in The number of OGs and TSGs were observed to overlap various genetic variations and may lead to the disruption of key cellular processes. To understand their functional impact in contributing to DLBCL development and progression, we investigated the role of these key genes (containing variations) using STRING and g:Profiler. Common immuno-oncogenic pathways, namely, B-cell receptor (BCR), cell cycle/apoptosis, JAK-STAT, MAPK, NF-κB, PI3K-AKT, and receptor tyrosine kinase (RTK), involved in cell growth, proliferation, and survival, were observed to be affected by these genetic variants. A few of these genes were also associated with pathways that are druggable, e.g., NF-κB, PI3K-AKT, and RTK.In different individuals, various routes to tumorigenesis were observed—different genetic variants leading to the disruption of the same pathways, or disruption of different genes/pathways and cross-talk between pathways is common. For example, in OCI-LY1, we observed 16 key genes (9 OGs and 7 TSGs) solely affected by CNVs, and on considering other genetic variations, ≈70 additional key genes that possibly participate in DLBCL pathogenesis were observed. This clearly suggests a need for integrating SSVs with CNVs and other SVs to obtain a complete variant profile of a patient for a better understanding of the DLBCL pathogenesis and to be able to prescribe individualized diagnosis and treatment. Different types of genetic variations in essential genes affecting various immuno-oncogenic pathways involved in lymphomagenesis across the 11 DLBCL cell lines are summarized in Below, we discuss our analysis by integrating the information of SSVs, CNVs, and SVs encompassing keys genes and show that it can provide insights into molecular differences between the two cell lines, DB (GCB subtype) and MD903 (ABC subtype). On comparing the genetic profile of these two cell lines, a striking difference in SSVs was observed, with mutations in EZH2 affecting the chromatin modifications in DB, while mutations in CARD11 led to constitutive expression of NF-κB signaling pathway in the MD903 cell line. Although most other pathways deregulated in these two cell lines are common , the genes/genetic variations involved in altering these pathways were different. For example, amplification of oncomir, mir-17-92 in DB and missense mutation in PIK3R1 in MD903 led to the disruption of the PI3K-AKT pathway in both the cell lines. Similarly, mutation/translocations in BCL2, mutations in TP53 and RUNX1 (DB), and copy loss of CDKN2A (MD903) were seen to affect cycle cell progression in the two cell lines. Even within the same subtype, differences in the genetic profile were observed. For instance, although the GCB cell lines DB and OCI-LY7 were identified with the amplification of mir-17-92 that directly affects the PI3K-AKT-mTOR pathway, mutations in different genes EZH2, RUNX1, CCND3, and BCL6 in the DB cell line, and HSP90AA1 and BCL2 in the OCI-LY7 cell line, were observed to affect distinct immuno-oncogenic pathways, as shown in A more complex picture of the pathways involved in tumorigenesis was observed by considering all the genes affected by SSVs, CNVs, and other SVs. For example, in the OCI-LY1 (GCB) cell line, shown in p-value: 0.05) compared to those without alterations in these genes reported in 48 patients reported in the TCGA. Furthermore, GCB cell lines NU-DHL-1 and DOHH-2 were identified with driver genetic variation through the loss of CDKN2A, which shared characteristics of the C2 subset reported in the same study. Other pairs of cell lines with shared genetic variants are listed in Detailed analysis of the genetic profiles of cell lines also revealed possible subgroups within the GCB and ABC subtypes that were based on shared genetic variations. For example, GCB cell lines OCI-LY1 and WSU-DLCL2 shared mutations in BCL2, EZH2, deletion/inversion of PTEN, and FOXO3/PDGFD translocations, and these cell lines may possibly follow a similar course  to DLBCL tumorigenesis because of their shared genetic profile. Moreover, this subgroup shared similar genetic features as the C3 subset identified by Chapuy et al. . InteresOn the basis of our analysis of complete genetic variant profiles of 11 cell lines, we observed different routes to the disruption of key immunogenic pathways, as shown in Alternate mechanisms were observed in four DLBCL cell lines  mainly through mutations in EP300, SMAD4, and APC, resulting in dysregulation of TGF-β signaling and WNT signaling pathways. Upon interaction of β-catenin with various transcription factors of the TCF/LEF family, several trans-activators such as the CREB binding proteins EP300 and BCL9 were recruited for downstream gene expression involved in carcinogenesis. In vitro studies revealed that histone acetyl transferases (HATs) such as EP300 are capable of binding to β-catenin, leading to the activation of the WNT signaling pathway. The gene EP300 also exhibits a dual role of inhibiting and activating BCL6 through acetylation, allowing B cells to rapidly reprogram to adapt to the signal. Mutations in gene BCL6 were observed in DLBCL cell lines. Additionally, EP300 influenced the activity of the tumor suppressor gene TP53, suggesting its role in tumorigenesis through alternate mechanisms . The genIn two cell lines (NU-DHL-1 and DOHH-2), genetic alterations were observed to directly influence the cell cycle pathway. Among various functions, MYC predominantly promotes the transition of cells from the G0 to the S1 phase, either through directly regulating the CCNDs or inhibiting cell cycle inhibitors. Genetic rearrangements in MYC result in its overexpression, eventually leading to the dysregulation of the cell cycle. Additionally, we observed a copy loss of TSG CDKN2A and driver mutations in TP53 and CCND3, further enabling the tumor cells to grow.We next examined pharmacogenomic implications of the genetic variations observed in DLBCL cell lines. From Apart from identifying targetable pathways, we observed that certain mutations in genes can also affect the drug response in patients. For example, a missense mutation (A>C) at chr1:161514542 rs396991) in the FCGR3A gene was identified in nine cell lines . Annotations in PharmGKB indicated the association of this mutation with an increase in the efficacy of the rituximab drug. The gene FCGR3A encodes for a receptor of the Fc portion of immunoglobulin G (IgG) and is involved in the elimination of antigen–antibody complexes. It also mediates antibody-dependent cellular cytotoxicity (ADCC), a complex process in which effector cells from the host immune system actively target and kill the cells whose membrane antigens are bound with specific antibodies. Aberrations in this gene are associated with increased susceptibility of recurrent viral infections, autoimmune disease systemic lupus erythematosus, etc. Interestingly, the action of drug rituximab, a monoclonal antibody (anti-CD20), is based on the ADCC mechanism, and the presence of the missense mutation (rs396991) is associated with increased affinity of FCGR3A for IgG. This results in increased efficacy of rituximab. The drug rituximab (R) is combined with the chemotherapy drug CHOP and is widely used in the treatment of DLBCL. In a cohort study on an East Asian population (n = 113), this mutation was shown to be associated with an increased complete response rate in patients treated with R-CHOP compared to those without this mutation . However6991 in tThe gene FLT4 encodes for receptor tyrosine kinase (RTK) for vascular endothelium growth factors, involved in lymph-angiogenesis, and promotes endothelium cell growth, proliferation, and survival. A missense mutation at chr5:180030313 (C>A) in the coding region of FLT4 was observed in five GCB cell lines , but not in any ABC cell lines. This mutation is associated with the decreased efficacy of the anti-angiogenetic drug sunitinib and reduced progression-free survival in renal cancer patients. A clinical phase II study indicated no effect of sunitinib in relapsed or refractory DLBCL patients and demonstrated higher hematologic toxicity than expected . The genImmortalized cell lines serve as renewable resources and essential models to study molecular mechanisms underlying cancer development and screening anti-cancer drugs. A comprehensive characterization of their genomes for sequence and structural variations would aid in understanding their potential influence when interpreting biological data. In this study, we carried out identification of small sequence variants (SSVs) using SeqVItA and large structural variations  using TIDDIT, MELT, and CNVs using iCopyDAV across 11 DLBCL cell lines. The validation of predicted SSVs and their prognostic significance in 1295 DLBCL patient samples from cBioPortal for Cancer Genomics is discussed. The analysis revealed the highly heterogeneous genomic landscape of DLBCL. Analysis of the complete spectrum of genetic variants helped in identifying recurrent pathways affected in the ABC and GCB subtypes.p-value < 0.05) on the basis of an analysis of 1295 DLBCL patients reported in cBioPortal. We observed SSVs contributing to impaired development and differentiation of immune cells, maintaining the immunosuppressive environment across all the cell lines via mutations in genes BCL6, CARD11, FANCA, EGFR, FOXO3, PICALM, NF1, TTL, etc. Aberrant lymphoid- and myeloid-derived immune cells influence the immune system by inducing oxidative stress, secreting immunomodulatory factors, regulating amino acid metabolism, and inhibiting T- or NK-cell viability. Subsequently, an immunosuppressive environment promotes development and progression of tumor cells. Another common pathway disrupted through mutations in genes NOTCH2 and NOTCH2NL is the NOTCH signaling pathway across all 11 cell lines. NOTCH signaling is involved in the regulation of cell proliferation, differentiation, and apoptosis, and activation of the NOTCH signaling pathway through genetic variations (mutations and amplifications) is well known in cancer progression. A recent study by Karube et al. [Functional interpretation of a large number of small sequence variations (SNVs and INDELs) identified in whole-genome sequence data is a challenging task. Generally, a majority of these SSVs are not functionally relevant. In this study, we filtered SSVs using the annotation and prioritization module of SeqVItA. In SeqVItA, a variant is assigned ‘high’ priority if the functional impact of the variant score is high (>0.65) from any one of the five resources , clinical association identified in at least one of the three resources , and variant-drug association identified in PharmGKB. A variant is assigned ‘medium’ priority if an annotation is reported from any of the three categories. Mutations identified as high or medium priority were only considered for the analysis. Key cancer genes such as TP53, NOTCH2, and KMT2C were observed to be mutated in the majority of the DLBCL cell lines, irrespective of their subtype. We also identified a few known subtype-specific gene-variants such as STAT6, EZH2, FOXO3 (GCB-specific), and CARD11 and CD79B (ABC specific). Mutations were identified in key genes such as regulator of apoptotic cell death, BCL2 (5/6 cell lines); transcriptional repressor, BCL6 (2/3 cell lines); and transcriptional regulator, TP53 (4/8 cell lines), in agreement with the prior work on these cell lines  summarize et al.  showed tThe genomic rearrangement, t was reported in six out of seven GCB-subtype DLBCL cell lines , differing from those shared by NU-DHL-1 and DOHH-2 cell lines . Similarly, within cell lines of the ABC subtype, we observed a common set of genetic aberrations in OCI-LY19 and SU-DHL-9 cell lines . Some combination of genetic variations was also observed in cell lines comprising the two subtypes. For example, cell lines OCI-LY7 (GCB) and MD903 (ABC) shared mutations in APC, BCL6, FANCD2, and SMAD4 and NOTCH2 MEIs, while cell lines SU-DHL-6 (GCB) and NU-DUL-1 (ABC) shared mutations in FOXO3, TP53, and RUNX1 genes; amplification of HSP90AA1 and IRF4 genes; and RAF1 translocations. Thus, we see that the genetic landscape of DLBCL cell lines clearly indicate a distinct evolutionary history of tumor cells within and between COO subtypes, leading to diverse therapeutic responses. Combining all the genetic variations also suggested distinct pathways in DLBCL cell lines, indicating possible mechanisms of lymphomagenesis. For example, cell lines OCI-LY1, WSU-DLCL2, SU-DHL6, and NU-DUL1 were identified with SNVs, CNVs, and SVs participating in the PI3K-AKT signaling pathway, while cell lines NU-DHL-1 and DOHH-2 demonstrated genetic variations altering components of the cell cycle. To understand the translational effect of SSVs, CNVs, SVs, or their combinations in the disruption of immuno-oncogenic pathways, one needs to examine their corresponding mRNA and protein expressions in the cell lines.Genetic aberrations in key OGs and TSGs also guide in identifying immuno-oncogenic pathways that are targetable. For example, missense mutations in tumor suppressor TP53 were observed in eight DLBCL cell lines (six GCB and two ABC), OCI-LY1, NU-DHL-1, DB, OCI-LY7, WSU-DLCL2, SU-DHL-6, NU-DUL-1, and SU-DHL-9 and in 151/1295 DLBCL patient samples from cBioPortal. They are involved in the regulation of several processes such as cell cycle arrest, induction of apoptosis, DNA repair, and inhibition of angiogenesis and metastasis. Mutations in TP53 were also observed to be associated with drug resistance, poor response to treatment, and short survival of DLBCL patients. The gene PARP1 was identified as accumulating at DNA damage sites and being involved in attracting DNA repair factors. Using PARP1 inhibitors such as olaparib and rituximab, in the presence of TP53 mutations, DNA damage response deficit tumors were shown to be repressed, and increased cytotoxicity was reported in DLBCL cell lines . In addiMolecular therapies targeting the aberrant immuno-oncogenic pathways identified in this study can potentially improve the effectiveness of standard R-CHOP. For example, targeting the PI3K-AKT pathway using the PI3K inhibitor duvelisib in combination with R-CHOP was proven to suppress the tumor growth in CHO resistant DLBCL cells . FurtherIn our study, we presented an extensive whole-genome sequence analysis of 11 DLBCL cell lines with the anticipation to aid the researchers in inferring meaningful data from these cell lines. Characterizing small sequence variants, copy number, and structural variations suggested causative drivers and enriched pathways leading to lymphomagenesis. Mutations identified in the cell lines were also annotated to infer the efficacy of known and novel drugs employed in DLBCL treatment. Clustering of cell lines on the basis of genetic alterations indicated novel subgroups within and between cell-of-origin subtypes (GCB and ABC). Although an extensive genomic analysis is presented, whether these genetic alterations are translated to transcripts and/or proteins needs to be verified using proteogenomics approaches. Moreover, DLBCL is a highly complex disease and often involves alterations at the epigenomic levels. Thus, integrating the data obtained from multi-omics techniques would enable us in identifying a prioritized set of driver genes and characterizing novel subgroups deviant of the cell-of-origin subtypes.


The presence of all these data in a review allows in one look to advance the research on CT using cell cultures by facilitating the selection of the most appropriate methods, conditions, and cell lines for future toxicological, pharmacological, and physiological studies.Cyanotoxins (CTs) are a large and diverse group of toxins produced by the peculiar photosynthetic prokaryotes of the domain Cyanoprokaryota. Toxin-producing aquatic cyanoprokaryotes can develop in mass, causing “water blooms” or “cyanoblooms,” which may lead to environmental disaster—water poisoning, extinction of aquatic life, and even to human death. CT studies on single cells and cells in culture are an important stage of toxicological studies with increasing impact for their further use for scientific and clinical purposes, and for policies of environmental protection. The higher cost of animal use and continuous resistance to the use of animals for scientific and toxicological studies lead to a progressive increase of cell lines use. This review aims to present (1) the important results of the effects of CT on human and animal cell lines, (2) the methods and concentrations used to obtain these results, (3) the studied cell lines and their tissues of origin, and (4) the intracellular targets of CT. CTs reviewed are presented in alphabetical order as follows: aeruginosins, anatoxins, BMAA ( Cyanotoxins (CTs) are a large and diverse group of toxins produced by the peculiar photosynthetic prokaryotes of the domain Eubacteria, commonly known as cyanobacteria or blue-green algae, and since 1999 named Cyanoprokaryota . Some aqDifferent approaches have been applied to classify CT, two of which are the most common: by the target of their action, or by chemical composition. By target, CT are classified as hepatotoxins, neurotoxins, dermatoxins, and cytotoxins, whereas chemically they are divided in peptides, alkaloids, phosphorylated cyclic N-hydroxyguanine, diaminoacids, and lipopolysaccharides, the last widely recognized as endotoxins. Prolonged use of drinking water, contaminated with low-doses CTs, may have also carcinogenic effect . Thus, mCell cultures are very convenient for toxicological studies. They allow to reveal the mechanisms of cytotoxic effects, the affected tissues, intracellular targets, and ways to minimize cytotoxicity . The useAlthough different methods are developed for testing of toxins in cell- and animal-based studies, during the last years, the trials on the use of animals have significantly decreased. This is caused by the high cost of these types of clinical trials and increasing resistance to the use of animals for scientific studies. Therefore, the significance and use of cell lines is gradually increasing.This review aims to present (1) the important results of the effects of CT on human and animal cell lines; (2) the methods and concentrations used to obtain these results, (3) the studied cell lines, and (4) the intracellular targets of CT. The presence of all these data in a review allows in one look to advance the toxicological and pharmacological studies of CT using cell cultures by facilitating the selection of the most appropriate methods, conditions, and cell lines.Aeruginosin CT contains as a basic structure 2-carboxy-6-hydroxyoctahydroindol that are serine protease inhibitors . They inAnatoxins-a are two types of low molecular bicyclic amino alkaloids: anatoxin-a (ANTX) and homoanatoxin-a (hANTX). The best known of them is ANTX, which was the first to be identified as a low molecular alkaloid (165 Da). hANTX is a homologue of anatoxin-a with molecular weight 179 Da and has propionyl instead of an acetyl group at C-2. ANTX and anatoxin-a (S) (ANTX(S)) are neurotoxins. ANTX binds competitively to acetylcholine receptors, while anatoxin-a (S) inhibits acetylcholine esterase [β-N-methylamino-L-alanine (BMAA) is an environmental nonprotein and toxic amino acid that may harm nervous system via oxidative stress, binding to neuromelanin, forming high toxic metabolites like formaldehyde or inhibiting enzyme activity of glutathione reductase, β-amilase, catalase, and RNase H, and in this way to provoke sporadic neurodegenerative development, such as Alzheimer's disease and amyotrophic lateral sclerosis [clerosis , 27, 28.clerosis  and refeCYN is a cyclic quinidine alkaloid combined with hydroxymethyl uracil . It has D (AT D), coibamide A (CoA), ichthyopeptins A (Ich A) and B (Ich B), kahalalide F (KF), 4-Fluoro-3-methyl-benzylamino-KF (KF2), morpholin-4-yl-benzylamino-KF (KF4), homodolastatin 16 (HD16), lagunamide C–Lag C, pitipeptolides–Pit A-F, aurilides and wewakpeptins A-D. Depsipeptides show cytotoxic activity and are protease inhibitors selective for chymotrypsin, leukocyte, and pancreatic elastases. They negatively influence the metabolism of human astrocytes [Depsipeptides are palmyramide A , apratoxin trocytes .LPS consist of lipid A, the core polysaccharides (mainly glucosamine) and an outer polysaccharide chain, and are common compounds of the cell walls of cyanoprokaryotes and Gram-negative bacteria . They haLyngbyatoxins were first identified from Moorea producens (formerly Lyngbya majuscula). They are tumor-promoting agents which bound eucaryotic protein kinase C (PKC) isozymes .β-amino acid 3-amino-9-methoxy-2,6,8-trimethyldeca-4,6-dienoic acid (ADDA). MC are lipophilic toxins very resistant to hydrolysis, oxidation, and high temperatures. The main route of human exposure is the ingestion of contaminated drinking water, consumption of contaminated food or algal dietary supplements, and body contact, while more occasional routes are hemodialysis and inhalation. MC are classified mainly as hepatotoxins because they block eucaryotic PP  [MC are cyclic nonribosomal heptapeptides with low molecular weight (800–1100 Da), which contain several uncommon nonproteinogenic amino acids such as N-methyldehydroalanin (MDHA) derivatives and the uncommon 4, PPP5) . Chronicßβ-amino acid -3-amino-9-methoxy-2,6,8-trimethyl-10-phenyldeca-4,6-dienoic acid (ADDA). Ten variants have been discovered with nodularin-R being the predominant toxin variant. NODs are relatively stable compounds, with low sensitivity to light or temperature. NOD affects hepatocytes binding their PPs by noncovalent bonds, which increases the rate of phosphorylation. They are often attributed to gastroenteritis, allergic irritation reactions, and liver diseases. Nodularin-R is the most notorious as a potent hepatotoxin that may cause serious damage to the liver of humans and other animals. NODs have similar effects as microcystins and weak carcinogenicity [Nodularins (NODs) are cyclic nonribosomal pentapeptides and contain several unusual nonproteinogenic amino acids such as N-methyl-didehydroaminobutyric acid and the Retinol, a novel retinoic acid (RA) analogue 7-hydroxy RA, 4-oxo-RA, and several analogues were identified in cyanobacterial blooms . They acSaxitoxin (SXT) is a collective name for a group of more than 20 cyclic nonribosomal peptide molecules, formed by sulphation at different sites of two basic molecules: SXT and neo-SXT. Based on their toxicology, SXT are grouped in three classes—carbamate derivatives, gonyautoxins, N-sulfocarbomoyl derivatives, and decarbomoyl derivatives—decarbamoylsaxitoxin. They have a neurotoxic effect by blocking voltage-gated sodium channels .50 or ID50 are different for cells in culture and human body.Studies on cell cultures cannot reveal all possible effects of toxins on the human body. This is due to the following reasons: (1) no matter how many cultures are tested, they will not cover the whole variety of cells in the body; (2) there are often significant differences between the cells in culture, the primary cell lines and the cells in the body tissues in the quantity and quality of expressed proteins (genes expression), metabolic pathways and cell function –115. Thein vitro formed organ-like structures such as artificial neuronal network [The use of cell cultures in toxicological studies will remain the main approach due to its speed, relatively low cost, reproducibility, precision with respect to the studied intracellular components, and ethical acceptability. The use of cell cocultures –118 and  network , cardiom network , and org network , which aThe presence of all these data on the cytotoxicity of aeruginosins, anatoxins, cylindrospermopsin, depsipeptides, lipopolysaccharides, lyngbyatoxins, microcystins, nodularins, cyanobacterial retinoids, and saxitoxins in a review is a great advantage. It allows the advancement of research on CT using cell cultures by facilitating the selection of the most appropriate methods, conditions, and cell lines for toxicological and pharmacological studies. In addition, it could increase the use of CT in functional studies of their intracellular targets. Therefore, this review allows in one look to advance the toxicological, physiological, and pharmacological studies of CT by the knowledge of their harmful effects with a focus on human and animal health as well as on environmental protection.


T-cell redirecting bispecific antibodies hold high promise for treatment of B-cell malignancies. B-cell maturation antigen (BCMA) exhibits high expression on normal and malignant mature B cells including plasma cells, which can be enhanced by inhibition of γ-secretase. BCMA is considered a validated target in multiple myeloma but whether mature B-cell lymphomas can be targeted by the BCMAxCD3 T-cell redirector teclistamab is currently unknown. BCMA expression on B-cell non–Hodgkin lymphoma and primary chronic lymphocytic leukemia (CLL) cells was assessed by flow cytometry and/or IHC. To assess teclistamab efficacy, cells were treated with teclistamab in presence of effector cells with/without γ-secretase inhibition. BCMA could be detected on all tested mature B-cell malignancy cell lines, while expression levels varied per tumor type. γ-secretase inhibition universally increased BCMA surface expression. These data were corroborated in primary samples from patients with Waldenstrom's macroglobulinemia, CLL, and diffuse large B-cell lymphoma. Functional studies with the B-cell lymphoma cell lines revealed teclistamab-mediated T-cell activation, proliferation, and cytotoxicity. This was independent of the level of BCMA expression, but generally lower in mature B-cell malignancies compared with multiple myeloma. Despite low BCMA levels, healthy donor T cells and CLL-derived T cells induced lysis of (autologous) CLL cells upon addition of teclistamab. These data show that BCMA is expressed on various B-cell malignancies and that lymphoma cell lines and primary CLL can be targeted using teclistamab. Further studies to understand the determinants of response to teclistamab are required to identify which other diseases might be suitable for teclistamab targeting.Besides reported BCMA expression on multiple myeloma, we demonstrate BCMA can be detected and enhanced using γ-secretase inhibition on cell lines and primary material of various B-cell malignancies. Furthermore, using CLL we demonstrate that low BCMA-expressing tumors can be targeted efficiently using the BCMAxCD3 DuoBody teclistamab. Treatment of B-cell lymphoproliferative disorders such as B-cell non–Hodgkin lymphoma (B-NHL) and chronic lymphocytic leukemia (CLL) has improved significantly over the last years. This is mostly due to a rapidly expanding treatment armamentarium of targeted agents such as inhibitors of pivotal B-cell receptor pathway kinases BTK and PI3K, and the Bcl-2 inhibitor venetoclax . NeverthFrom stem cell transplantations (SCT), it has become clear that long-lived T cell–mediated anticancer responses are feasible . HoweverFor hematologic malignancies, the most prominent TAA has been CD19. The first BsAb to be approved by the FDA for relapsed/refractory acute lymphoblastic leukemia was the CD19-targeting bispecific T-cell engager (BiTE) blinatumomab . The shoIn line with the expression of BCMA on PBs and PCs, BCMA is highly expressed on multiple myeloma cells, and is considered a validated target, based on approval of the BCMA-targeted therapies belantamab mafodotin and idecabtagene vicleucel, for treatment of advanced multiple myeloma . ComparaTo assess whether BCMA can be used as a target in B-NHL and CLL, we studied whether BCMAxCD3 BsAb  could mediate T-cell activation as well as killing of the lymphoma cell lines. This BsAb has been developed with Genmab DuoBody technology, resulting in enhanced stability compared with conventional BsAb formats. As a proof of concept that BCMA can evoke an autologous T-cell response, CLL was used as a target.+CD19+ of at least 85%. Paraffin‐embedded bone marrow (BM) and lymph node (LN) tissue  was obtained from the pathology department of the Amsterdam University Medical Centers, location AMC. BM mononuclear cells  were isolated from peripheral blood of patients with CLL  or buffy BM-MNC;  from BM  BM-MNC; .Written Full BCMAxCD3 BsAb (teclistamab) and controls BCMAxnull (BC3B4) and nullxCD3 (CNTO7008) were provided by Janssen Pharmaceuticals.Mycoplasma by PCR. Cell lines were authenticated by short tandem repeat analysis and were thawed at least 1 week prior to starting experiments. Cell lines were acquired in the following years: RPMI-8226 in 2015, MWCL-1 in 2018, BCWM.1 in 2018, Mec-1 in 2005, Ramos in 1999, OCI-Ly7 in 2016, Jurkat in 2002, U266 in 2015, CII in 2012, PGA-1 in 2012, Daudi in 2018, OCI-Ly3 in 2016, and JeKo-1 in 2013.Primary CLL cells, RPMI-8226, MWCL-1, BCWM.1, Mec-1, Ramos, OCI-Ly7, and Jurkat cells were cultured in Iscove's Modified Dulbecco's Medium . HD-derived PBMCs, U266, CII, PGA-1, Daudi, OCI-Ly3, and JeKo-1 cells were cultured in RPMI1640 medium (Thermo Fisher Scientific). Medium was supplemented with 10% FCS and 1% penicillin/streptomycin. MWCL-1 and BCWM.1 cell lines were kindly provided to M. Spaargaren by Dr. S.P. Treon, OCI-LY3 by Dr. R. Kuppers and OCI-LY7 by Dr. U. Klein, RPMI-8226 was obtained from ATCC and all other cell lines from DSMZ. Cell lines were tested every 2 months for PBMCs were washed with PBA  and stained using fluorescently labeled antibodies for 20 minutes on ice. The following antibodies were used: BCMA APC, BCMA PE (BioLegend), IgG2a kappa isotype PE (BD Biosciences), CD3 V500 (BD Biosciences), CD4 BV605 (BD Biosciences), CD4 PerCPefl710 (eBioscience), CD5 PE (eBioscience), CD5 PerCPCy5.5 (BioLegend), CD8 BV510 (BioLegend), CD8 PECy7 (eBioscience), CD19 APC (BD Biosciences), CD19 FITC (BD Biosciences), CD20 FITC (BD Biosciences), CD25 APC (BD Biosciences), CD25 BV786 (BD Biosciences), CD27 PerCPefl710 (eBioscience), CD38 PE (BD Biosciences), CD38 BV421 (Sony), CD45RA BV650 (BioLegend), CD107a PECy7 (BD Biosciences), CD138 FITC (Molecular Probes), CCR7 BUV395 (BD Biosciences), IgD PE-CF594 (BD Biosciences), IFNγ BV421 (BD Biosciences), IL2 PE-Dazzle594 (BioLegend), TNFα AF700 (BD Biosciences). To exclude dead cells, Fixable Viability Dye eFluor 780 was used according to manufacturer's instructions. For staining of intracellular cytokines, cells were fixed and permeabilized using the Fixation/Permeabilization Solution Kit (BD Biosciences). After antibody staining, samples were washed using PBA and acquired on BD FACS Canto or LSR Fortessa flow cytometer and analyzed with FlowJo v10. To quantify number of cells using flow cytometry, 123count eBeads Counting Beads (Thermo Fisher Scientific) according to manufacturer's instructions. BCMA molecules per cell were determined by usage of PE Fluorescence Quantitation Kit (BD Biosciences).Cell lines or CLL cells were cultured either in medium or in presence of 100 nmol/L γ-secretase inhibitor . After 24 or 48 hours, BCMA was detected by flow cytometry as described above. Relative expression was calculated compared with isotype controls. For qPCR, total RNA was isolated using the RNeasy mini kit (Qiagen) and cDNA was transcribed by RevertAid (Fermentas), using random hexamer primers (Promega). qPCRs were performed using SYBR Green master mix (Applied Biosystems) and measured on a Quantstudio 3 (Applied Biosystems). Expression of BCMA was normalized to GAPDH. Linear regression software was used for analysis.+ and CD8+ T cells were isolated using MACS beads (Miltenyi Biotec), according to manufacturer's instructions. Cocultures were incubated in the presence of 100 ng/mL BCMAxCD3, BCMAxnull, or nullxCD3. A total of 100 nmol/L γ-secretase inhibitor (Ly411575) was added where indicated. Viability of the target cells was assessed using TO-PRO-3 (Invitrogen) and MitoTracker Orange (Invitrogen) using flow cytometry. Specific lysis of target cells was calculated as (% target cell death in treated sample − % cell death target cells in medium control)/(100 − % cell death target cells in medium control) *100%. Samples were excluded when cell death in medium controls exceeded 50%.Cell lines or primary CLL samples were labeled with Cell Trace Violet  or carboxyfluorescein diacetate succinimidyl ester (Thermo Fisher Scientific) according to manufacturer's instructions and cocultured with HD PBMCs or CLL-derived (autologous) T cells in different effector-target (E:T) ratios. Where indicated prior to co-culture CD4+ multiple myeloma cells in the BM-MNCs was determined by flow cytometry, as described previously (+ cells in the presence of Flow-Count Fluorospheres (Beckman Coulter) and LIVE/DEAD Fixable Dead Cell Stain Near-IR fluorescent reactive dye (Invitrogen). The percentage of lysis induced by teclistamab was calculated using the following formula: % lysis multiple myeloma cells = 1 − (absolute number of surviving CD138+ cells in treated wells/absolute number of surviving CD138+ cells in untreated wells) × 100%.BM-MNCs derived from 6 patients with multiple myeloma, containing 2%–65% tumor cells, as well as autologous effector cells and immune suppressive cells, were used in flow cytometry–based lysis assays. Sample viability at start of the assays, assessed using 7-AAD (BD Biosciences), was more than 95%. BM-MNCs were incubated in RPMI1640 + 10% FBS (Integro) with teclistamab (0.16 μg/mL) in 96-well U-bottom plates for 48 hours. The survival of primary CD138eviously . BrieflyPBMCs from HD patients were labeled with CTV and cultured alone or in 1:1 E:T ratio with RPMI-8226, JeKo-1, CII or BCWM1. PBMCs were incubated in the presence of 100 ng/mL BCMAxCD3, BCMAxnull, or nullxCD3 or stimulated with CD3 (clone 1XE) and CD28 (clone 15E8) antibodies. A total of 100 nmol/L γ-secretase inhibitor (Ly411575) was added where indicated. After 4 days, proliferation was measured by flow cytometry as described above.PBMCs from HD or CLL patients were incubated in the presence of 100 ng/mL BCMAxCD3, BCMAxnull, or nullxCD3 or stimulated with CD3 (clone 1XE) and CD28 (clone 15E8) antibodies for 2 days. Where indicated HD PBMCs were cocultured in a 1:1 E:T ratio with RPMI-8226, JeKo-1, CII, or BCWM1. A total of 100 nmol/L γ-secretase inhibitor (Ly411575) was added where indicated. Brefeldin A , GolgiStop (BD Biosciences), and anti-CD107a PE-Cy7 were added 4–6 hours before assessment of activation, degranulation, and cytokine production by flow cytometry as described above.Cell lines or CLL cells were cultured either in medium or in presence of 100 nmol/L γ-secretase inhibitor . After 24 or 48 hours, supernatants were harvested and stored at −20°C. sBCMA in supernatants was measured by ELISA using antibody pairs for BCMA.IHC staining for BCMA , CD138, Pax-5, cyclin D1, and IgM were performed on paraffin‐embedded BM and LN tissue. Staining was performed by PhenoPath Laboratories on a Dako Autostainer EQ240 system. Results were assessed by two independent pathologists (C.J.M. van Noesel).n < 5 a Shapiro–Wilk test. P values were calculated by using two-sided paired or unpaired t tests, Wilcoxon matched-pairs signed-rank test, Mann–Whitney test, repeated measures or ordinary one-way ANOVA (followed by Bonferroni post hoc test) or Kruskal–Wallis test (followed by Dunn post hoc test). Correlations were determined by simple linear regression. Statistical analysis was performed using Graphpad PRISM version 8.3.0 with significance set at P < 0.05.Data were checked for normality by a D'Agostino–Pearson test or if The data generated in this study are available upon request from the corresponding author.B-cell malignancy cell lines were tested for BCMA expression by flow cytometry. As expected, the multiple myeloma cell lines U266  and RPMI-8226 (gMFI 4621) expressed high levels of BCMA . AlthougR2 = 0.92). Together, these data indicate that besides multiple myeloma, cell lines derived from other B-cell malignancies express BCMA which can be enhanced by γ-secretase inhibition.Because BCMA is cleaved off by γ-secretase, the different B-cell malignancy lines were incubated for 24–48 hours with 100 nmol/L γ-secretase inhibitor (Ly411575). All lymphoma cell lines showed an increased BCMA level after γ-secretase inhibition . ViabiliThe results regarding BCMA expression on different B-cell lymphoma cell lines prompted us to explore primary material of patients with CLL and B-cell lymphoma. Primary CLL cells showed marginal expression of BCMA protein and mRNA  and B. IBCMA expression by IHC was assessed on primary tissue of BM and/or LNs infiltrated by multiple myeloma, LPL (WM), DLBCL, CLL, or MCL. To determine the fraction of tumor cells expressing BCMA, tissues were also stained for CD138 (multiple myeloma), IgM (LPL), cyclin D1 (MCL), and Pax-5  after 2 days of coculture with the different cell lines in the presence of either teclistamab or anti-CD3/CD28 stimulation , BCWM.1 , CII , and JeKo-1 . Cell lines and age-matched HD PBMCs were cultured in the presence of 100 ng/mL teclistamab or the control BsAbs (BCMAxnull or nullxCD3) with or without 100 nmol/L γ-secretase inhibitor. As a positive control, anti-CD3/CD28 antibodies were added to the cocultures. Both CD4mulation . No T-cemulation . Similarmulation . Activatmulation . In addimulation . Again, mulation . It ther+ or CD8+ or CD4+ and CD8+ together (1:1 ratio) in the presence of teclistamab for 96 hours. Surprisingly, CD4+ T cells were not able to induce killing, in sharp contrast to CD8+ T cells, which induced lysis up to 60% , CLL and DLBCL primary samples. Despite low BCMA expression on CLL, teclistamab could efficiently lyse CLL cells, using both HD T cells or autologous-derived T cells.Our data indicate that BCMA expression below a certain threshold level of BCMA is needed for γ-secretase inhibition to be additive/synergistic in the context of teclistamab. Above that level of BCMA, using γ-secretase inhibition does not enhance lysis, proliferation, or secretion of cytokines by T cells. This is in line with an earlier study of teclistamab in multiple myeloma , but in Nevertheless, γ-secretase inhibition could be useful for patients that express BCMA just below threshold level. γ-secretase inhibitors have been used in clinical trials for treatment of Alzheimer's disease , as wellDespite high BCMA expression on BCWM.1 and CII, coculture with HD T cells and teclistamab led to less efficient killing of these cell lines as compared with the low BCMA-expressing cell line JeKo-1. Because also anti-CD3/CD28 stimulation led to lower responses upon coculture of these cell lines, the T-cell suppressive effect is likely caused by the tumor cells. For CLL and DLBCL, evidence has accumulated for an immunosuppressive tumor microenvironment, that favors tumor growth. Furthermore, in many of these diseases T-cell dysfunction has been described in terms of upregulation of exhaustion markers , defectiIn conclusion, our data show that BCMA expression is not only limited to multiple myeloma, but can also be detected to various levels on other B-NHL subtypes and CLL. Treatment of B-cell lines using the BCMAxCD3 BsAb teclistamab led to lysis of these cells as well as to robust T-cell activation, independent of BCMA expression level. CLL cells, which expressed low levels of BCMA could be efficiently targeted by teclistamab, providing proof of principle that BCMA-directed therapies might be beneficial for other B-cell malignancy patients besides multiple myeloma.Supplementary Tables 1-3, Figures 1-4Supplementary Table 1. CLL Patient characteristics. Supplementary Table 2. Healthy donor characteristics. Supplementary Table 3. MM patient characteristics. Supplementary Figure 1. γ-secretase inhibition increases BCMA levels but does not affect viability of B-cell malignancy cell lines. Supplementary Figure 2. γ-secretase inhibition does not affect viability CLL cells. Supplementary Figure 3. BCMAxCD3 DuoBody® induces activation, degranulation, and cytokine secretion by T cells in the presence of B cell malignancy cell lines. Supplementary Figure 4. BCMAxCD3 DuoBody® induces autologous killing of MM cells.Click here for additional data file.


Middle East respiratory syndrome coronavirus (MERS-CoV) is caused by a well-known coronavirus first identified in a hospitalized patient in the Kingdom of Saudi Arabia. MERS-CoV is a serious pathogen affecting both human and camel health globally, with camels being known carriers of viruses that spread to humans. In this work, MERS-CoV genomic sequences were retrieved and analyzed by multiple sequence alignment to design and predict siRNAs with online software. The siRNAs were designed from the orf1ab region of the virus genome because of its high sequence conservation and vital role in virus replication. The designed siRNAs were used for experimental evaluation in selected cell lines: Vero cells, HEK-293-T, and Huh-7. Virus inhibition was assessed according to the cycle threshold value during a quantitative real-time polymerase chain reaction. Out of 462 potential siRNAs, we filtered out 21 based on specific selection criteria without off-target effect. The selected siRNAs did not show any cellular toxicity in the tested cell lines at various concentrations. Based on our results, it was obvious that the combined use of siRNAs exhibited a reduction in MERS-CoV replication in the Vero, HEK-293-T, and Huh-7 cell lines, with the highest efficacy displayed in the Vero cells.  In 2012, a new coronavirus was identified in an infected butcher in the Kingdom of Saudi Arabia, who developed a respiratory illness and died 11 days after hospital admission [l health . Camels l health ,4. The ml health ,6. Coronaviridae. The size of the viral genome is approximately 25–32 kb. MERS-CoV falls under lineage C betacoronaviruses (βCoVs). To date, only four coronavirus groups have been reported—designated as Alpha, Beta, Gamma, and Delta—and they have high genetic diversity, which favors the emergence of new strains [The MERS-CoV belongs to the family  strains . Genetic strains . Current strains ,10, bact strains , fungal  strains ,13, para strains ,15, vira strains . Several strains . Additio strains . The det strains ,20,21,22 strains ,27,28,29 strains  against  strains , dengue  strains , influen strains ,35, hepa strains , human p strains , SARS co strains , and MERThis present work gains significance because of the lack of antiviral therapy or vaccines for MERS-CoV, and the generated data will provide valuable information about the advancement and further use of oligonucleotide-based antivirals as an alternative therapy. The main objectives of this work were to design potential siRNAs by using a computational approach and to experimentally evaluate the reduction of viral load in Vero, HEK-293-T, and Huh-7 cell lines. Based on the results, a significant reduction in viral RNA was observed after using the combined siRNAs.The MERS-CoV genomic sequences were retrieved from GenBank  and aligned by using BioEdit software (Version 7.2). The orf1ab region was identified as a potential target during siRNA design. The siRNAs were designed and selected by siDirect (Version 2.0) ,29,39,40http://rna.tbi.univie.ac.at accessed on 1 May 2022) was used to predict the secondary structure of the siRNAs. We have provided figures of the predicted siRNAs in our manuscript. An online bioinformatics tool (RNAfold server—4) with 60–80% confluency. All the experiments were performed in triplicate. The antiviral potency of the siRNAs was accessed 48 h post-transfection. We selected these three cell lines  based on their differential cell line susceptibility, replicative capacity, better cell growth and multiplication, and their cytopathic effects in in vitro assays [Dulbecco’s modified Eagle’s medium (DMEM) was used to grow the cells at 37 °C. The growth and quantification of MERS-CoV infection as well as viral RNA products of replication were performed by using standard published protocols ,41. The o assays ,43,44. ® and further grown in a standard culture plate at defined conditions in DMEM. The standard siRNA dilutions were prepared at various concentrations  from 50 μM stock solutions by adding 100 μL of Opti-MEM and Lipofectamine 2000 and further incubated at room temperature for 30 min. The complex mixture was delivered slowly to the grown cells, which were allowed to grow further for 24 h at 37 °C. The cellular toxicity of the siRNAs in different cell lines was analyzed by using an MTT assay kit (Invitrogen) following the manufacturer’s instructions. The absorbance was measured at 570 nm using a SpectraMax i3x imaging cytometer, and the standard formula was applied for the cytotoxicity calculation. The detailed protocol for the cytotoxicity assay has been described previously [The siRNAs were delivered to the grown cells by using reverse transfection with Lipofectamine 2000  following the manufacturer’s instructions. The cells were procured from ATCCeviously .To evaluate the inhibitory effect of siRNAs against MERS-CoV experimentally, we used multiple combinations of siRNAs with various doses  on selected grown cells. In our earlier study, we evaluated the siRNAs at various concentrations ranging from 0.1, 0.5, 1.0, 2.5, 5.0, 10, 25, and 50 nM. Here, the concentrations of siRNAs  were chosen because they produced better results than other concentrations in our previous study ,45. The The multiple sequence alignment results showed high conservation at various locations among the human and camel isolates. The conserved region of the ORF1ab gene is presented in p-value of <0.0001. The cytotoxicity results of each cell line are provided in The cellular toxicities of the designed siRNAs were evaluated in the three selected cell lines and were observed to be concentration-dependent. None of the tested siRNAs displayed significant toxicity in any cell lines. The data were statistically analyzed by using the GraphPad Prism (9.3.0) two-way ANOVA software and considered significant with a The virus inhibition and the level of viral RNA in the cell lines were determined by the Ct value of qPCR for all combinations of siRNAs in the cell supernatant as well as the cell lysate. The analysis was performed by using only four different concentrations  of siRNAs, as per previous works ,29. The The RNAfold server was used to predict the secondary structure of the designed siRNAs. The minimum free energy (MFE) and thermodynamics ensemble (%) data for all siRNAs are provided in In 2012, MERS-CoV was identified in a hospitalized patient in the Kingdom of Saudi Arabia, where the highest fatality rate of the disease has been reported. Tremendous efforts have been made in MERS-CoV research using varied approaches that have contributed significantly towards disease management. Despite this enormous global research effort, no vaccines or antivirals are currently available against MERS-CoV, but various strategies are being used for their development, including oligonucleotide (siRNAs/miRNAs)-based therapy ,49,50,51In our study, the software produced 462 siRNAs from the orf1ab region. We selected and evaluated only 21 siRNAs following the standard criteria for filtration ,26. The We evaluated only certain siRNAs for combined use in the Vero, Huh-7, and HEK-293-T cell lines. The cellular toxicity of each designed siRNA was evaluated in the three cell lines before inducing virus infection and qPCR. The results showed no cytotoxicity of the evaluated siRNAs in the tested cell lines. The experimental evaluation results of each siRNA combination and their antiviral potency were significantly variable across different cell lines, even at the same concentration, which could be due to the growth and multiplication properties of the cell lines after siRNA delivery and virus infection. Many siRNA combinations showed significant and strong inhibitory effects toward viral replication in Vero cells. The Ct values from the qPCR data indicated a significant inhibition of replication and a reduction in viral RNA in both the cell supernatant and lysate of the Vero, Huh-7, and HEK-293-T cell lines. We evaluated all 21 combinations of siRNAs in the selected cell lines. Better siRNA efficacy and reduction of viral load were observed in Vero cells due to the better growth and multiplication of the virus in this cell line. In silico approaches are commonly used to screen possible strategies for overcoming infections, with successful examples in similar studies that emphasize bioinformatic approaches and their utility . One limBased on our computational approach combined with the experimental evaluation of selected siRNAs in terms of cytotoxicity and qPCR, we concluded that the in silico designing and filtration of siRNAs can be an effective approach to alternative oligonucleotide-based therapeutics for MERS-CoV. The experimental evaluation results of the antiviral potency of siRNAs provided valuable information about the selection of siRNAs tested in various cell lines at selected concentrations with multiple combinations. Recently, after many barriers and challenges were overcome, the FDA approved several siRNA-based therapeutics. However, many other challenges must still be addressed, such as enzymatic degradation, rapid renal clearance, endosomal trapping, plasma protein sequestration, and activation of the immune system. To overcome these barriers, many strategies and techniques are being used to modify the backbone, bases, sugars, conjugation of aptamers, and exosome-based delivery of siRNAs. We observed that the Vero cells were better than other cells because of virus multiplication and cell growth for testing the siRNAs against MERS-CoV. Finally, the overall results proved that the computational approach of this study can be used to design siRNAs as potential therapeutics against MERS-CoV, and our experimental evaluation provided information about the selection of these siRNAs.


Malignant pleural mesothelioma (MPM) is a deadly cancer primarily of the lung pleura, strongly associated with asbestos exposure. According to the ESMO Clinical Practice Guidelines, MPM patients may be suitable for best supportive care only, active  or multimodality treatments. Surgery, although controversial, is an option in some centres, but the recognised standard of care is systemic chemotherapy (cisplatin-pemetrexed) while other therapies, including immunotherapy  or combination therapies  are being investigated . DespiteRobinson et al. review their use of different mouse models to investigate therapeutic approaches to treat MPM. They developed some of the first human and mouse mesothelioma cell lines using human tumours in immunocompromised mice and intraperitoneal injection of asbestos respectively. They also developed the MexTAg mouse, an asbestos-induced mesothelioma mouse model in which expression of the Simian Virus 40 large T antigen (SV40 TAg) is controlled by a mesothelin tissue-specific promoter. The advantage with this model is it generates 100% mesotheliomas in response to asbestos. More recently, they also developed a bilateral tumour model which was developed to analyse the difference between immune checkpoint blockade responsive and non-responsive tumours against a homogeneous background.The development of novel treatments for MPM requires substantial preclinical data before drugs can enter a clinical trial. Mesothelioma cell lines are extensively used to screen individual or combinations of drugs to determine cytotoxicity, anti-cancer mechanisms and drug resistance, and to identify potentially clinically relevant biomarkers. However, 2D cell culture has limitations as lack of heterogeneity and a tumour microenvironment and acquisition of mutations limit their usefulness . Three-dPezzicoli et al. discussed current and potentially upcoming standards of care for MPM and reviewed several novel therapeutic agents recently in clinical trial. Lurbinectedin is a transcriptional inhibitor and blocks the function of tumour associated macrophages. Mesothelioma cell lines were highly sensitive to lurbinectedin and in the SAKK 17/16 phase II clinical trial, lurbinectedin demonstrated activity following immune checkpoint inhibitor therapy, indicating a phase III trial is warranted. Pezzicoli et al. also discussed the outcome pf several tyrosine kinase inhibitor trials. Of particular interest, were results from preclinical studies using CDK4/6 inhibitors, that demonstrated cell toxicity and inhibition of tumour growth in mouse models. The MiST2 study  was recently announced. The median progression free survival and overall survival was 128 and 217 days respectively. The authors plan to further investigate CDK4/6 inhibition in another randomised study  in MPM which have not yet entered clinical trial. STAT3 is important for cell survival, proliferation, self-renewal and chemoresistance. KDM4A demethylates the tumor suppressor SETD2 products H3K36me3 and H3K9me3, which are essential in cell growth and DNA damage repair. Heparanase promotes tumor growth, angiogenesis, metastasis and chemoresistance. All molecules reviewed impact some of the hallmarks of cancers but their role in MPM and the effect of targeting these molecules on MPM tumour growth require considerably more preclinical studies.Oien et al. to have anti-cancer effects in cisplatin-resistant and pemetrexed-resistant MPM cell lines. Interestingly, NF2-mutated cell lines were more sensitive to QC. Inhibition of the hippo pathway was identified using RNA-seq and closely-associated transcription factors YAP1, CDK4, and KRAS were downregulated. However, the effect of QC in vivo has not been investigated.Repurposing of existing drugs has also been proposed for MPM. Quinacrine (QC), which is an antimalarial drug and an antibiotic, was shown by Precision medicine approaches to treat MPM have been proposed  and the in vitro and in vivo models to test gene and variant function. Together, scientists and clinicians can utilise their specific expertise to collaborate and plan better animal studies and clinical trials to maximise effective drug design to treat diseases like MPM which have shown limited therapeutic improvement.Developing new approaches for treating MPM are urgently needed and it has been suggested that a circular pathway of bench to bedside and back again approach may be key to clinical breakthroughs . Many pr


Almost all living cells maintain size uniformity through successive divisions. Proteins that over and underscale with size can act as rheostats, which regulate cell cycle progression. Using a multiomic strategy, we leveraged the heterogeneity of melanoma cell lines to identify peptides, transcripts, and phosphorylation events that differentially scale with cell size. Subscaling proteins are enriched in regulators of the DNA damage response and cell cycle progression, whereas super-scaling proteins included regulators of the cytoskeleton, extracellular matrix, and inflammatory response. Mathematical modeling suggested that decoupling growth and proliferative signaling may facilitate cell cycle entry over senescence in large cells when mitogenic signaling is decreased. Regression analysis reveals that up-regulation of TP53 or CDKN1A/p21CIP1 is characteristic of proliferative cancer cells with senescent-like sizes/proteomes. This study provides one of the first demonstrations of size-scaling phenomena in cancer and how morphology influences the chemistry of the cell. Molecules that super- and subscale with cancer cell size and the consequences for cell growth are defined. Xenopus oocytes  (P < 0.001). By retrieving the W statistic, we calculated the “common language effect size” for each comparison. This produced a matrix of pairwise comparisons between all cell lines that measured the degree of difference in median area between them. Clustering the lines according to this difference, let us define three area classes , and the CV differed only modestly between cell lines   . This su2) and 5555 (490 μm2)] and large [B14341 (1500 μm2) and 17864A (900 μm2)] cell lines are largely 2N, and all exhibit partial 4N populations. We note that 21917 (800 μm2) and 24038 (2400 μm2) were almost entirely tetraploid.Previous studies have indicated that DNA content  when populations are pooled and  when considered independently  and identified two distinct clusters of cell lines: a set of smaller cell lines with a relatively high D/C and a set of large lines with a relatively low D/C ratio  across lines. This metric differs from ploidy because it considers the amount of Hoechst staining within the nucleus, which can be affected by factors such as packing, but facilitates the measurement of many more cells. We observed two independent linear relationships between DNA content and cell area across cell lines . Peptide expressions, normalized to reflect the relative difference in mass fractions across cells lines (Methods), were correlated to cell areas revealing proteins whose concentrations continuously scale with size.RB1 concentration at which cells commit to division , P < 0.05, n = 10 (or 11)] ] . SpecifiR = −0.38, P > 0.05, n = 11)  pathway, rather than across sizes (see data S2 for phosphoproteomic data on the MAPK pathway in these cell lines). Despite their size and low RB1 mass fraction, 21015 BRAF and C876 NRAS exhibited a CCND1 mass fraction comparable to smaller cell lines, whereas our similarly large KDBRAF cell lines, 24038 and B14341, showed the lowest CCND1 expression   (data S2). We concluded that the set point, where CDK4/6:CCND1 activation exceeds RB1 activity to putatively drive proliferation, is thus similar across lines.CCND1 abundance was found to be weakly negatively correlated with size ( n = 11) . This su = 2, 9) . The ratCCND1, we established a method to quantify the signaling activity upstream of CCND1 using the phosphorylation state of transcriptional regulators of CCND1, as defined by the ENCODE database ( CCND1regs) across different melanoma lines. All phosphorylations used in the analysis with known causative kinases or documented cellular effects . Moreover, this implies that the CCND1 levels in larger lines are not due to differences in mitogen signaling alone.We observed a negative relationship between cell size and the ratio between RB1/pCCND1reg ratio  is associated with lower expression of ribosomal and spliceosome proteins   .R| >0.55), which were then sorted into two groups. One group of peptides are those expressed in class 1/2  cells  and those expressed in class 2/3 (large) cells . We conducted an ontological analysis on all the hit peptides (P <10−9). These proteins included checkpoint mediators ATM, BRCA1, and WEE1 and the mitotic cyclin CCNB2. In contrast, class 2/3 large lines were statistically enriched for superscaling peptides from lipid/glycolipid metabolic processes and components of the ECM. These included MVK, MVD, ACAT2, and COL2A1   and biosynthetic processes , including the canonical mTORC1-activating phosphorylation, S2448 , implying up-regulation in small cell lines. Class 2/3 larger cell lines were enriched for superscaling phosphorylations on guanosine triphosphatase (GTPase) and cytoskeletal regulators  and also set of growth regulators , implying differential regulation of biosynthesis across the size range  and a CTNNB1 degradation signal (S29) , including BRCA1 S686 an AKT1 target and stabilizing phosphorylation (eEIF4B and EIF5B), “spliceosome machinery” , “cell adhesion” peptides , and increased expression of “growth signaling”  peptides (P < 10−3). Despite mTOR S2448 subscaling, many phosphorylations enriched in larger cell lines correspond to insulin signaling events such as EIF4B S497 .peptides   mass fractions and increased relative expression of ECM and lipid metabolic components. Further, large sizes coincide with increased phosphorylation of cytoskeletal effectors and differential regulation of the biosynthetic machinery.Larger cell sizes, related to lower D/C ratios, are associated with decreased G BARD1, WEE1, E2F8, and RB1) and control of gene expression  subscaled with cell size (enrichments significant to at least P < 1 × 10−3) , interferon induced protein with tetratricopeptide repeats 1, interferon regulatory factor 5 (IRF5) and IRF7, and adenosine deaminase RNA specific] were up-regulated in larger cell lines (enrichments significant to at least P < 1 × 10−3).We next performed transcriptomic experiments to gain further insight into the relationship between size and signaling network organization and activity. We measured the abundance of 24988 RNA molecules overlapping with 9290 measured peptides (data S5). We conducted a volcano analysis, as described previously (Methods), to identify a list of transcripts that super- and subscale with size across lines . mRNA’s 2-M regulators, altered metabolism and biosynthesis, and an increased inflammatory (transcript) mass fraction.In conjunction with that observed in the proteomic data, these data show that compared to class 1/2 smaller cells, class 2/3 larger cells have decreased levels Gn = 9290), in agreement with previous studies  correlations with peptide abundances, we observed an obvious enrichment of cell cycle and DNA repair/replication genes   . As pept2), and recalculated the correlation coefficients between mRNA and peptide fractions. At the gene level, in the smaller subset, we observed enrichment of inflammatory, adhesion and cell cycle regulators  . In large cells, there was a strong correlation between mRNA and the protein mass fraction of ribosomal and translational genes     in the lnd ETF1) . This sund ETF1)  to the mTogether, these data suggest that the disruption of cell transcription relates to the subscaling of the biosynthetic mass fraction in larger, low D/C, cell lines. This may occur through the decreased RNAP expression at larger sizes. Depressed biosynthetic expression and signaling may underpin further scaling relationships.P < 10−3, e.g., “BOK,” “Toll-like receptor 3 (TLR3),” “TLR4,” “BCL2,” and “TICAM1”] and lipid/carbohydrate metabolism  is associated with large cell lines. Excluding the “overexpressed” genes, we observe enrichment of lipid metabolic proteins alone . In contrast, we observe a clear enrichment of cell cycle , mitotic  and DNA repair  peptides in smaller lines indicating subscaling (fig. S4 and data S3).To assess the universality of our size-scaling relationships, we extended our panel of 11 lines to include a further 12 composed of the same genotypes as before and conducted further quantitative morphological and phosphoproteomic experiments and analyses . In contrast to the previous analysis, we note an additional “arm” of the volcano plot indicating a subset of peptides extremely enriched in larger cell lines (fig. S3). We hypothesize that this represents gene overexpression rather than superscaling relationships, as there is no smooth transition in between the arms. Initially including these genes in the analysis, we found that an increased mass fraction of apoptotic effectors . A summWe noted that the α  and β (growth rate) parameters of our model showed nonlinear relationships with cell size ; thus, we expected that peptides whose levels correlated with α and β would be (partly) independent of those that correlate with size as determined by imaging . Thus, bR = 0.98). Fivefold cross validation was used to select the number of components and maximize transferability of the model  model predicting parameter values from the proteomic expression data  [false discovery rate (FDR) < 0.05], including d CDC25A . Expressand TP53 . Many ofTP53 and CDKN1A/p21, which covaried with proteins that are predictive of growth . However, these lines were notably different in their levels of CDNK1A and TP53. One group of BRAFKD cells has high growth rates and large size and is CDKN1A low and TP53 high. However, the other group of NRAS and BRAF mutant cells has high growth rates and large size and is CDKN1A high and TP53 low. Further, CDKN1A and CCND1 mass fractions were observed to scale linearly with one another . Thus, in these cell lines, a high growth rate (and large size) is associated with two distinct states: a /TP53low/p21high/CCND1high state and a /TP53high, /p21low/CCND1low state  dilution to size determination and control  stage cycle, implying the dominance of a small subset of proliferative regulators. This suggests a more central role for the RB1 subscaling observed in these cell lines.We constructed a simple theoretical model to demonstrate how continued growth under proliferative stress could maintain the cell proliferation rate. This relied on the probability of a cell transitioning to the next stage of the cell cycle being proportional to its size . This shows that larger cell lines maintain high growth rates despite down-regulation of anabolic pathways and decreased ribosomal mass fractions, qualities typically associated with decreased biosynthesis  and β (growth rate) parameters of our model, we found that they were best predicted by the expression of TP53 or CDKN1A/p21 may actually facilitate progression in large cells, by resolving stresses or acting at checkpoint proteins. For example, TP53 or CDNK1A/p21 expression in large cells might act to slow proliferation transiently (as cells grow), allowing engagement of the DDR  followed by centrifugation  and resuspension in complete medium. Cell counting was performed using a Countess automated cell counter with trypan blue exclusion (Thermo Fisher Scientific).Cell lines were maintained in standard culture conditions . Cells were incubated in DMEM media with 10% FBS and Primocin antibiotic at 37°C and 5% carbon dioxide. Cells were imaged at 4-hour intervals using the Incucyte imaging system. Nine fields of view were imaged from each well. Images were segmented using Ilastik image segmentation software to identify individual cells. The number of cells in each field of view was calculated using CellProfiler. Growth curves were plotted using the ggplot2 library from the R programming language. Average growth rates were computed as Gr = 2/3*(Mean_Area)/(Doubling_time), where doubling time is the average time taken for cell number to double in the population.Samples were fixed in freshly prepared 4% paraformaldehyde (PFA)/phosphate-buffered saline (PBS) for 15 min. Slides were subsequently permeabilized with 0.25% Triton/PBS for 10 min and blocked with 0.5% bovine serum albumin (BSA)/0.02% glycine/PBS for 30 min. Primary antibodies were introduced via the same solution in a 1:1000 dilution and left on for 1 hour. The slides were washed with PBS, and the same was carried out for the secondary antibodies (kept in the dark to avoid bleaching). Hoechst stain was added postsecondary (1:500) to stain DNA as was phalloidin to stain actin.Image acquisition was performed using an Opera Cell:Explorer-automated spinning disk confocal microscope. Twenty fields of view were imaged in each well . Cell segmentation was performed using Acapella software (PerkinElmer). Nuclei were segmented using the Hoechst channel (405 to 450) and cell bodies defined by the tubulin signal (568 to 603). Geometric features measured include the area of all subcellular regions; the length, width, and elongation (length/width) of the cell and nucleus; cell and nuclear roundness; and nucleus area/cytoplasm area.Statistical tests were carried out in the MATLAB (MathWorks) environment. Cell area data were “acosh”-transformed to induce a normal distribution of areas in each cell line and standardize the variances before ANOVA and Mann-Whitney/Wilcoxon tests. Standardization success was determined using the Shapiro-Wilks normalization test, ensuring that the data are normally distributed, and the Bartlett test, to guarantee equal variances across lines.6 cells were seeded in Falcon T25 flasks and incubated overnight in media containing the appropriate aphidicolin concentration  before FACS analysis of DNA content as above.Cells were trypsinized and harvested into a 15-ml falcon tube for cell counting. After centrifuging the falcon at 2400 rpm for 5 min, the supernatant was discarded, and the cells were resuspended in 1-ml of 1% fetal calf serum in PBS. Three-milliliter ice cold 100% ethanol was added dropwise to the cells while slowly vortexing and left to fix overnight. The cells were then pelleted by centrifugation for 5 min at 2400 rpm and resuspended in 5 ml of PBS. They were incubated at room temperature for 20 min. After centrifuging for 7 min at 1200 rpm, the pellet was resuspended in 1 ml of propidium iodide (PI) solution through the cell strainer into a FACS tube. The PI solution was made with 1:100 PI at 5 mg/ml and 1:1000 ribonuclease A at 10 mg/ml in PBS. The cell cycle composition was measured using the BDSAria, and the data were analyzed using FlowJo. For EdU (5-ethynyl-2′-deoxyuridine) incorporation assays, cells were treated with a final concentration of 10 μM EdU before harvesting. Instead of fixing with ethanol and staining with PI, cells were resuspended in 4% PFA for 15 min at room temperature. They were then pelleted by centrifugation and PFA aspirated, followed by a wash. Five hundred microliters of the appropriate Thermo Fisher Scientific Click-iT reaction cocktail was added to each sample and incubated for 30 min in the dark, according to the manufacturer’s instructions. Cells were washed once, stained, and then transferred via a cell strainer into a FACS tube for analysis as above. Washes used 1% BSA in PBS. Staining used Hoechst (20 μg/ml) added to 0.1% Triton-X in PBS. If applicable, 10Cell pellets were dissolved in 150 μl of lysis buffer containing 1% sodium deoxycholate, 100 mM triethylammonium bicarbonate, 10% isopropanol, 50 mM NaCl, and Halt protease and phosphatase inhibitor cocktail (100×)  on ice with pulsed probe sonication for 15 s. Samples were boiled at 90°C for 5 min and sonicated for another 5 s. Protein concentration was measured with the Quick Start Bradford Protein Assay (Bio-Rad) according to the manufacturer’s instructions. Aliquots containing 100 μg of protein were reduced with 5 mM tris-2-carboxyethyl phosphine for 1 hour at 60°C and alkylated with 10 mM iodoacetamide for 30 min in the dark. Proteins were then digested overnight by adding trypsin at final concentration of 75 ng/μl (Pierce). The resultant peptides were labeled with the tandem mass tag (TMT)-11plex reagents (Thermo Fisher Scientific) according to the manufacturer’s instructions and were combined in equal amounts into a single tube. The combined sample was then dried with a centrifugal vacuum concentrator. Two technical replicate TMT batches from the same protein extracts were prepared to assess reproducibility. One TMT batch was fractionated offline with high-pH reversed-phase chromatography using the XBridge C18 column  on a Dionex UltiMate 3000 high-performance liquid chromatography (HPLC) system. Mobile phase A was 0.1% ammonium hydroxide (v/v), and mobile phase B was acetonitrile and 0.1% ammonium hydroxide (v/v). The TMT-labeled peptide mixture was reconstituted in 100 μl of mobile phase A and fractionated with a gradient elution method at 0.2 ml/min as follows: for 5-min isocratic at 5% B, for 35-min gradient to 35% B, gradient to 80% B in 5 min, isocratic for 5 min, and re-equilibration to 5% B. Fractions were collected every 42 s and vacuum-dried. The second TMT replicate batch was fractionated with the Pierce High pH Reversed-Phase Peptide Fractionation Kit according to the manufacturer’s instructions.Peptide fractions from the first TMT batch were reconstituted in 10 μl of 20% isopropanol and 0.5% formic acid binding solution and were loaded on 10 μl of phosphopeptide enrichment immobilized metal affinity chromatography resin  already washed and conditioned with binding solution in custom-made filter tips fitted on Eppendorf tube caps. After 2 hours of binding at room temperature, the resin was washed three times with 40 μl of binding solution at 300 g, and the flow-through solutions were collected for total proteome analysis. Phosphopeptides were eluted three times with 70 μl of 40% acetonitrile and 400 mM ammonium hydroxide solution. Eluents and flow-through samples were vacuum-dried and stored at −20°C until the liquid chromatography–mass spectrometry (LC-MS) analysis.5, and 50 ms ion trap (IT) with the top speed mode in 3 s and were isolated for collision-induced dissociation (CID) fragmentation with quadrupole isolation width 0.7 Th. Collision energy (CE) was 35% with AGC 1 × 104 and IT 50 ms. MS3 quantification was obtained with Higher-energy C-trap dissociation (HCD) fragmentation of the top five most abundant CID fragments isolated with Synchronous Precursor Selection. Quadrupole isolation width was 0.7 Th, CE 65%, AGC 1 × 105, and 105 ms IT. The HCD MS3 spectra were acquired for the mass range 100 to 500 with 50 K resolution. Targeted precursors were dynamically excluded for further isolation and activation for 45 s with 7 parts per million (ppm) mass tolerance. Phosphopeptide samples were analyzed with an HCD method at the MS2 level with CE 38%, AGC 1 × 105 and max IT 105 ms.LC-MS analysis was performed on the Dionex UltiMate UHPLC 3000 system coupled with the Orbitrap Lumos mass spectrometer (Thermo Fisher Scientific). Peptides were loaded to the Acclaim PepMap 100, 100 μm by 2 cm C18, 5 μm, 100 Ȧ trapping column at a flow rate of 10 μl/min. The sample was then subjected to a gradient elution on the Acclaim PepMap RSLC  C18 capillary column at 45°C. Mobile phase A was 0.1% formic acid, and mobile phase B was 80% acetonitrile and 0.1% formic acid. The separation method at flow rate 300 nl/min was as follows: for 90 min (or 150 min for the replicate batch) gradient from 10 to 38% B, for 10 min up to 95% B, for 5 min isocratic at 95% B, reequilibration to 10% B in 5 min, for 10 min isocratic at 10% B. Precursors between 375 and 1500 mass/charge ratio were selected with mass resolution of 120 K, automatic gain control (AGC) 4 × 10q value and decoy database search. Spectra were searched against reviewed UniProt mouse protein entries. The reporter ion quantifier node included a TMT 11plex quantification method with an integration window tolerance of 15 ppm and integration method based on the most confident centroid peak at the MS3 or MS2 level. Only unique peptides were used for quantification, considering protein groups for peptide uniqueness. Peptides with average reporter signal-to-noise of >3 were used for quantification.The SequestHT search engine was used to analyze the acquired mass spectra in Proteome Discoverer 2.2 (Thermo Fisher Scientific) for protein identification and quantification. Precursor mass tolerance was 20 ppm, and fragment ion mass tolerance was 0.5 Da for the CID and 0.02 Da for the HCD spectra. Spectra were searched for fully tryptic peptides with maximum of two miss-cleavages. TMT6plex at N terminus/K and carbamidomethyl at C were defined as static modifications. Dynamic modifications included oxidation of M and deamidation of N/Q. Dynamic phosphorylation of S/T/Y was included for the phospho-enriched samples. Peptide confidence was estimated with the percolator node. Peptide FDR was set at 0.01, and validation was based on R, and a fold change was calculated between cells lying above or below the mean. Peptides scoring Fc > 1.5 or <0.66 and |R| > 0.55 were taken as hit super/subscaling peptides. The Fc threshold of 1.5 stems from a power analysis: An Fc of 1.5 is the minimal detectable difference between groups we can detect by a t test between small and large cell line clusters  when accepting a true-positive rate of 0.95 . The fold change was defined asA” denotes the mean abundance of the peptide in cluster 1, and M(A) denotes the minimal value of the mean of cluster 2 for there to be a detectable difference in mean as above. The “100” stems from all peptides being scaled across line to have a mean value of 100. This value was calculated using the “samplesizepwr” function in MATLAB (MathWorks) statistics and machine learning toolbox. Transcripts are treated identically to peptides.Peptide abundances were scaled relative to other detected peptides in the sample such that they reflect abundance/total protein mass. The expression of each peptide was correlated to average cell line area to derive a correlation coefficient, Geneontology.org’s downloadable database  according to the manufacturer’s protocol. The evaluation of the isolated RNA integrity and quantity was carried out by the Agilent TapeStation system using an RNA ScreenTape .For the mRNA library preparation, 4000 ng of total RNA was treated with TurboDNase to remove genomic DNA contamination, . PolyA RNA was selected from 1000 ng of the purified RNA using NEBNext mRNA magnetic isolation module  following the manufacturer’s directions. From the resulting mRNA, strand-specific libraries were created using the NEBNext Ultra II Directional RNA Library Prep Kit for Illumina . Final libraries were quantified using quantitative polymerase chain reaction and clustered at a molarity of 300 pM. Sequencing was performed on an Illumina NovaSeq 6000 (Illumina) using paired end ×100 cycles v1.0 chemistry, to achieve coverage of 25 million reads per sample.k/α (the expected mean of the distribution). Every generation, the area distribution is convolved with the mass-gain distribution, computed by performing an inverse Fourier transform on the product of the two distributions respective Fourier transforms. This produces the division area distribution, Ad(A), which must be transformed to Ad(2A) to capture the effects of cell division. We perform this by setting Ab(Ax) = Ad(Ai) + Ad(Ai + 1), where “I” = xn − xn-1 for all x, where Ab denotes the birth size distribution. This is then convolved with the gain distribution as before to generate the next division distribution and so on until a desired number of generations has been reached.The initial cell area distribution is considered a delta function centered on P = αAdiv, and a random number, “r,” is drawn from a flat distribution. Should r be less than the division probability of a cell, the cell divides symmetrically in two, adding a new cell to the population with half the size of the mother, and halving the mother size. If r is greater than the division probability, then the cell size increases according to β = kAdiv. This system continues until a final cell count of 20,000 was achieved.An initial population of 1000 cells was assigned an α and β value and a random initial area. At each time step, the division probability for each cell is calculated, according to Initially, α values were exhaustively tested (β is determined from the proliferation and area measurements on a per cell line basis). For each, we calculated the Kullbeck-Liebler divergence between the experimental and simulated dataHaving identified approximate minima from the low-resolution parameter screen, we used the values defining this region as an initial state for a stochastic gradient descent minimizing along the gradientModel fitting was conducted within the commercial MATLAB (MathWorks) software’s machine learning toolbox.r-squared metric.Regression analyses were conducted with the MATLAB (MathWorks) environment using the plsregress function from the machine learning toolbox. Partial least square regression was selected as the method to help mitigate the influence of colinearity in the predictor dataset. Model components were selected through fivefold cross validation using the elbow method on the mean square error as a function of component number. All peptides were mean-centralized before model construction. Fit quality was assessed through the wjf is the weight value for j variable and f component, and SSYf is the sum of squares of explained variance for the fth component and J number of X variables. SSYtotal is the total sum of squares explained of the dependent variable, and F is the total number of components. Features with a VIP score greater than 1 were taken as major drivers of the model. VIP scores of peptides with negative weights in the first PLSR component were made negative in preparation for enrichment analysis.The influence a feature has on a model was estimated through VIP scores calculated asGSEA was conducted using the “WebGestalt” web application on our ranked list of peptides (VIP score defined the rank) (


Myrica cerifera root bark, was investigated using enzymatic activity assays and molecular docking procedures. Dimethylmyricacene was shown to inhibit both the cleavage and the religation steps of the enzymatic reaction, and cell viability of A-253, FaDu, MCF-7, HeLa and HCT-116 tumor cell lines.Human topoisomerase 1B regulates the topological state of supercoiled DNA enabling all fundamental cell processes. This enzyme, which is the unique molecular target of the natural anticancer compound camptothecin, acts by nicking one DNA strand and forming a transient protein–DNA covalent complex. The interaction of human topoisomerase 1B and dimethylmyricacene, a compound prepared semisynthetically from myricanol extracted from  Human DNA topoisomerase 1B (hTop1) is a ubiquitous enzyme, essential in mammals . This moSilybum marianum, that alone does not show any effect on hTop1, but inhibits the enzyme, in the form of oxidovanadium (IV) complexes [Natural products (NPs) remain an extensive and excellent source of inspiration for the development of new pharmaceuticals, and most of the drugs currently used in the clinic are NPs that display inhibition towards a specific target . Howeveromplexes . Anotheromplexes .Myrica cerifera root bark [Modification of these naturally occurring compounds led to the discovery of several hTop1 catalytic inhibitors, such as CYB-L10, that has a higher hTop1 inhibition activity, compared with its parent indolizinoquinolinedione . Identifoot bark . Reportsoot bark . Concernoot bark . In thisHTop1, for time course and dose dependent assays, has been expressed in the top1 null EKY3 yeast strain and purified by affinity chromatography, as described elsewhere . To valiDulbecco’s modified Eagle’s medium high glucose (DMEM), RPMI 1640 medium, fetal bovine serum (FBS), L-glutamine and penicillin/streptomycin, were purchased from Euroclone , McCoy’s and Minimum essential Medium Eagle (EMEM) were purchased from the Lonza group Ltd. . Complete media (CM) were supplemented with 10% FBS, 2 mM L-glutamine, 0.1 mg/mL streptomycin and 100 U/mL penicillin. The ovarian cancer cell line SKOV-3 was purchased from Cell Biolabs Inc., and maintained in DMEM-high glucose, CM.The colorectal adenocarcinoma cell line, HT-29, colorectal carcinoma cell line HCT-116 and melanoma cell SK-MEL-28, were gifted by Dr Cinzia Tesauro  and maintained in RPMI 1640 CM. A non-small-cell lung cancer cell line, A-549, triple negative breast cancer cell SUM-159, MDA-MB-468 and MDA-MB-231, HER2/c-erb-2 positive breast cancer cell line SK-BR-3, MCF-7 and T-47-D ER+, PR+/–, HER2– and the adenocarcinoma HeLa cell line were provided by Dr. Giuseppe Sconocchia  and were maintained in DMEM-high glucose, CM. The submandibular gland squamous cell carcinoma cell line A-253 and hypopharyngeal squamous cell carcinoma cell line FaDu were gently provided by Dr. Angelo Peschiaroli  and maintained in McCoy’s CM and E-MEM CM, respectively. All cell lines were kept in culture for a maximum of eight passages and were tested for mycoplasma, using the PCR detection Kit (Euroclone).1H NMR spectra of DM was recorded in CDCl3, using a Varian 600 MHz broadband instrument and is reported in DM was produced, according to reference . Briefly2 and 5 μg/mL acetylated bovine serum albumin) with 150 mM KCl, 0.5 μg pBlueScript and 1 U of purified htop1, with different concentrations of DM. As a positive control, the enzyme was incubated with the same amount of ACN used to dissolve the compound. Following 1 h incubation at 37 °C, the reaction was stopped by adding 0.5% SDS stop dye. To evaluate the reversibility or irreversibility of DM, the same experiment was carried out with 100 μM of DM as a function of time, and reactions were stopped at the indicated time points with a final concentration of SDS 0.5%. All samples were run on 1% agarose gel with TBE 1 X buffer . The presence of relaxed supercoiled DNA was visualized through a UV transilluminator after a gel staining in 0.5 μg/mL EtBr and destaining in dH2O.To assess the minimal dose of DM inhibiting hTop1 a dose dependent relaxation assay of negatively supercoiled DNA pBlueScript KSII (-) was performed. In a volume of 30 μL, were mixed TOPO mix buffer 1X . The cleavage reaction was performed at different time points with 100 μM of DM, by incubating 0.6 pmol of SS with 1.2 pmol hTop1 (Prospec), as previously described . The rea2 with the appropriate medium, to evaluate the cell viability, as previously described [2. Following the incubation, the medium was then removed and replaced with 0.5 mg/mL of MTT reagent in a final volume of 200 μL diluted with the medium. The plates were incubated again for 4 h at 37 °C, 5% CO2. Prior to measuring the absorbance at 570 nm, the medium was replaced with 100 μL of DMSO and placed on a shaking incubator for 15 min at room temperature, covered from light. The dose dependent assay cells were plated in a 96-well plate the day before the experiment. Then, 24 h later, the medium was removed and replaced with different amounts of DM. In detail, the cells were treated with 12.5, 25, 50 and 100 μM of DM and the same concentrations were used to treat cells with TPT as well, representing the positive cytotoxicity control. The plates were incubated again for 48 h at 37 °C under 5% CO2. To evaluate the minimal dose of DM reducing cell viability, the cells were subjected to the MTT reagent, as described above.All tumor cell lines were seeded in a 96-well plate for 24 h before performing the experiment at 37 °C, 5% COescribed . The celhttps://www.chemaxon.com accessed on 22 July 2022) and converted in 3D using the OpenBabel routines [The crystal structure of the human DNA-bound topoisomerase IB (PDB ID: 1T8I),  lacking routines . The recroutines . The proroutines . A molec−1∙Å−2 was imposed on the protein, DNA and ligand atoms, being slowly reduced, and finally removed in the last minimization cycle. The system’s temperature was gradually increased from 0 to 300 K in an NVT ensemble, using the Langevin thermostat [−1∙Å−2 was imposed on the protein, DNA and the ligand atoms, and then gradually decreased to relax the entire system. The systems were then simulated in an isobaric-isothermal (NPT) ensemble for 2.0 ns, using the Langevin barostat, imposing a pressure of 1.0 atm and maintaining the temperature to 300 K [The tleap module of the AmberTools19 program  was usedermostat , over a to 300 K . The SHAto 300 K . The pmeto 300 K . The cooto 300 K .GROMACS 2021.2 analysis tools  have beet-test. All data were expressed with mean ± SD values. * p ≤ 0.05, ** p ≤ 0.01, *** p ≤ 0.001 and **** p ≤ 0.0001.The cleavage and religation kinetics and dose dependent cell viability assay were analyzed by a two-way ANOVA test, using GraphPad Prism. The statistical analysis for the cell viability assay was evaluated by GraphPad Prism software, using the multiple To screen myricanol and its derivatives A–D againThe addition of DM to the hTop1 and DNA determines an inhibition of the relaxation activity, already detectable at a concentration of 80 μM A, lane 6The relaxation assay performed as a function of time with DM at a concentration of 100 μM, shows a lasting effect over time  in the absence and presence of DM, in a time course experiment, as in . BrieflyAnalysis of the religation step was carried out by incubating 0.6 pmol of the enzyme with 1.2 pmol of the suicide substrate to obtain the cleavage complex A, lane 2The results indicate that the presence of DM strongly inhibits the religation step of the enzyme catalytic cycle  simulation, to both validate the stability of the complexes and to correctly estimate the interaction energy between the hTop1-DNA and the drug. The results of the MM/GBSA calculations corroborated the strong interaction between DM and the hTop1-DNA structure, which is characterized by an interaction of free energy of −32.6 and −22.7 kcal/mol, for the drug inside the catalytic site or intercalated, respectively .Both vdW and electrostatic interactions contribute to the binding, although the electrostatic contribution is higher when the drug binds within the catalytic pentad. In order to provide an estimate of the contribution given by single residues or DNA bases to the total binding energy of the drug, the MM/GBSA per-residue decomposition analyses  were carVisual inspection of the trajectory indicates a partial rearrangement of DM within the binding site, which turns into a partially intercalated conformation , thus beDynamic cross-correlation maps (DCCM), based on the atomic fluctuations of 565 Cα atoms of hTop1, were generated from the three MD trajectories of the hTop1-DNA and hTop1-DNA-drug complexes, to evaluate whether the presence of the drug could induce changes in the structural-dynamical properties of the enzyme. In this representation, the positive values indicate a correlation of the motion between the two residues, which move in the same direction in space, while negative ones represent an anti-correlated motion, with residues moving in opposite directions. Indeed, MD simulations identify strong differences between the unbound and bound complexes and show the presence of functional structural motions in the hTop1 unbound structure . In the work of Tesauro et al., it was demonstrated that Ery-C is an in vitro catalytic inhibitor of hTop1, that efficiently acts on both the cleavage and the religation reactions . DM, a sf Ery-C, : this drThe inhibitory effect of the drug on different cancer cell lines, reported in Further experiments need to be performed to clarify the off-target mechanism, and additional chemical modifications need to be explored to improve the DM activity against hTop1, in order to develop a new anticancer drug targeting only hTop1, that could be used in clinic.