Isolation and characterization of rabies monoclonal antibody charge variants.

Current postexposure prophylaxis of rabies includes vaccines, human rabies immunoglobulin (RIG), equine RIG, and recombinant monoclonal antibodies (mAb). In the manufacturing of rabies recombinant mAb, charge variants are the most common source of heterogeneity. Charge variants of rabies mAb were isolated by salt gradient cation exchange chromatography (CEX) to separate acidic and basic and main charge variants. Separated variants were further extensively characterized using orthogonal analytical techniques, which include secondary and tertiary structure determination by far and near ultraviolet circular dichroism spectroscopy. Charge and size heterogeneity were evaluated using CEX, isoelectric focusing (IEF), capillary-IEF, size exclusion chromatography, sodium dodecyl sulfate polyacrylamide gel electrophoresis, and western blotting. Antigen binding affinity was assessed by enzyme linked immuno-sorbent assay and rapid florescence foci inhibition test. Results from structural and physicochemical characterizations concluded that charge variants are formed due to posttranslational modification demonstrating that the charge heterogeneity, these charge variants did neither show any considerable physicochemical change nor affect its biological function. This study shows that charge variants are effective components of mAb and there is no need of deliberate removal, until biological functions of rabies mAb will get affected.

Choice of Metric Divergence in Genome Sequence Comparison.

The paper introduces a novel probability descriptor for genome sequence comparison, employing a generalized form of Jensen-Shannon divergence. This divergence metric stems from a one-parameter family, comprising fractions up to a maximum value of half. Utilizing this metric as a distance measure, a distance matrix is computed for the new probability descriptor, shaping Phylogenetic trees via the neighbor-joining method. Initial exploration involves setting the parameter at half for various species. Assessing the impact of parameter variation, trees drawn at different parameter values (half, one-fourth, one-eighth). However, measurement scales decrease with parameter value increments, with higher similarity accuracy corresponding to lower scale values. Ultimately, the highest accuracy aligns with the maximum parameter value of half. Comparative analyses against previous methods, evaluating via Symmetric Distance (SD) values and rationalized perception, consistently favor the present approach's results. Notably, outcomes at the maximum parameter value exhibit the most accuracy, validating the method's efficacy against earlier approaches.

MMV method: a new approach to compare protein sequences under binary representation.

In the present work, a new form of descriptor using minimal moment vector (MMV) is introduced to compare protein sequences in the frequency domain under their component wise binary representations. From every sequence, 20 different binary component sequences are formed, each corresponding to 20 amino acids. Each such vector is now shifted from the time domain to the frequency domain by applying the Fast Fourier Transform (FFT). Next, the power spectrum calculated from the FFT values for each component sequence is so normalized that the sum of the components equals 1. The descriptor is defined as a 20-component vector composed of the 20 second-order minimal moments calculated from the normalized spectrum of the 20 component sequences. Once the descriptor is known, the distance matrix is created by applying the Euclidean Distance measure. The phylogenetic tree is generated by applying the unweighted pair group method with the arithmetic mean (UPGMA) algorithm using Molecular Evolutionary Genetics Analysis11 (MEGA11) software. In this work, the datasets used for similarity studies are 9 NADH dehydrogenase 5 (ND5), 12 Baculoviruses, 24 Transferrins (TF) proteins, and 50 Spike Protein of coronavirus. A qualitative measure using rationalized perception is used to compare the effectiveness of the proposed method. Quantitative measure based on symmetric distance (SD) is used to compare the phylogenetic trees of the present method with those obtained by other methods. It is observed that the phylogenetic trees generated by the proposed technique are at par with their known biological references, and they produce results better than those of the earlier methods.Communicated by Ramaswamy H. Sarma.

Intracellular Ellagic Acid Derived from Goat Urine DMSO Fraction (GUDF) Predicted as an Inhibitor of c-Raf Kinase.

BACKGROUND: Dietary chemicals and their gut-metabolized products are explored for their anti-proliferative and pro-cell death effects. Dietary and metabolized chemicals are different from ruminants such as goats over humans. METHODS: Loss of cell viability and induction of death due to goat urine DMSO fraction (GUDF) derived chemicals were assessed by routine in vitro assays upon MCF-7 breast cancer cells. Intracellular metabolite profiling of MCF-7 cells treated with goat urine DMSO fraction (GUDF) was performed using an in-house designed vertical tube gel electrophoresis (VTGE) assisted methodology, followed by LC-HRMS. Next, identified intracellular dietary chemicals such as ellagic acid were evaluated for their inhibitory effects against transducers of the c-Raf signaling pathway employing molecular docking and molecular dynamics (MD) simulation. RESULTS: GUDF treatment upon MCF-7 cells displayed significant loss of cell viability and induction of cell death. A set of dietary and metabolized chemicals in the intracellular compartment of MCF-7 cells, such as ellagic acid, 2-hydroxymyristic acid, artelinic acid, 10-amino-decanoic acid, nervonic acid, 2,4-dimethyl-2-eicosenoic acid, 2,3,4'- Trihydroxy,4-Methoxybenzophenone and 9-amino-nonanoic acid were identified. Among intracellular dietary chemicals, ellagic acid displayed a strong inhibitory affinity (-8.7 kcal/mol) against c-Raf kinase. The inhibitory potential of ellagic acid was found to be significantly comparable with a known c-Raf kinase inhibitor sorafenib with overlapping inhibitory site residues (ARG450, GLU425, TRP423, VA403). CONCLUSION: Intracellular dietary-derived chemicals such as ellagic acid are suggested for the induction of cell death in MCF-7 cells. Ellagic acid is predicted as an inhibitor of c-Raf kinase and could be explored as an anti-cancer drug.

Use of 2D FFT and DTW in Protein Sequence Comparison.

Protein sequence comparison remains a challenging work for the researchers owing to the computational complexity due to the presence of 20 amino acids compared with only four nucleotides in Genome sequences. Further, protein sequences of different species are of different lengths; it throws additional changes to the researchers to develop methods, specially alignment-free methods, to compare protein sequences. In this work, an efficient technique to compare protein sequences is developed by a graphical representation. First, the classified grouping of 20 amino acids with a cardinality of 4 based on polar class is considered to narrow down the representational range from 20 to 4. Then a unit vector technique based on a two-quadrant Cartesian system is proposed to provide a new two-dimensional graphical representation of the protein sequence. Now, two approaches are proposed to cope with the varying lengths of protein sequences from various species: one uses Dynamic Time Warping (DTW), while the other one uses a two-dimensional Fast Fourier Transform (2D FFT). Next, the effectiveness of these two techniques is analyzed using two evaluation criteria-quantitative measures based on symmetric distance (SD) and computational speed. An analysis is performed on five data sets of 9 ND4, 9 ND5, 9 ND6, 12 Baculovirus, and 24 TF proteins under the two methods. It is found that the FFT-based method produces the same results as DTW but in less computational time. It is found that the result of the proposed method agrees with the known biological reference. Further, the present method produces better clustering than the existing ones.

Protein sequence comparison based on representation on a finite dimensional unit hypercube.

Numerous techniques are used to compare protein sequences based on the values of the physiochemical properties of amino acids. In this work, a single physical/chemical property value based non-binary representation of protein sequences is obtained on a 20 × 20-dimensional unit hypercube. The represented vector expressed in the matrix form is taken as the descriptor. The generalized NTV metric, which is an extension of the NTV metric used for polynucleotide space is taken as a distance measure. Based on this distance measure, a distance matrix is obtained for protein sequence comparison. Using this distance matrix, phylogenetic trees are drawn by using Molecular Evolutionary Genetics Analysis 11 (MEGA11) software applying the neighbor-joining method. Data sets used in this current work are 9-ND4, 9-ND5, 9-ND6, 24 TF-LF proteins, 27 different viruses and 127 proteins from the protein kinase C (PKC) family. Two sets of phylogenetic trees are obtained - one based on property value of polarity and the other based on property value of molecular weight. They are found to be exactly the same. Similar results also hold for other single property value based representation. The present trees are individually tested for efficiency based on the criterion of rationalized perception and computational time. The results of the present method are compared with those obtained earlier by other methods on the same protein sequences using assessment criteria of Symmetric distance (SD), Correlation coefficient, and Rationalized perception. In all the cases, the present results are found to be better than the results of other methods under comparison.Communicated by Ramaswamy H. Sarma.

Non-Coding RNAs in Oral Cancer: Emerging Roles and Clinical Applications.

Oral cancer (OC) is among the most prevalent cancers in the world. Certain geographical areas are disproportionately affected by OC cases due to the regional differences in dietary habits, tobacco and alcohol consumption. However, conventional therapeutic methods do not yield satisfying treatment outcomes. Thus, there is an urgent need to understand the disease process and to develop diagnostic and therapeutic strategies for OC. In this review, we discuss the role of various types of ncRNAs in OC, and their promising clinical implications as prognostic or diagnostic markers and therapeutic targets. MicroRNA (miRNA), long ncRNA (lncRNA), circular RNA (circRNA), PIWI-interacting RNA (piRNA), and small nucleolar RNA (snoRNA) are the major ncRNA types whose involvement in OC are emerging. Dysregulated expression of ncRNAs, particularly miRNAs, lncRNAs, and circRNAs, are linked with the initiation, progression, as well as therapy resistance of OC via modulation in a series of cellular pathways through epigenetic, transcriptional, post-transcriptional, and translational modifications. Differential expressions of miRNAs and lncRNAs in blood, saliva or extracellular vesicles have indicated potential diagnostic and prognostic importance. In this review, we have summarized all the promising aspects of ncRNAs in the management of OC.

PTGAC Model: A machine learning approach for constructing phylogenetic tree to compare protein sequences.

This work proposes a machine learning-based phylogenetic tree generation model based on agglomerative clustering (PTGAC) that compares protein sequences considering all known chemical properties of amino acids. The proposed model can serve as a suitable alternative to the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), which is inherently time-consuming in nature. Initially, principal component analysis (PCA) is used in the proposed scheme to reduce the dimensions of 20 amino acids using seven known chemical characteristics, yielding 20 TP (Total Points) values for each amino acid. The approach of cumulative summing is then used to give a non-degenerate numeric representation of the sequences based on these 20 TP values. A special kind of three-component vector is proposed as a descriptor, which consists of a new type of non-central moment of orders one, two, and three. Subsequently, the proposed model uses Euclidean Distance measures among the descriptors to create a distance matrix. Finally, a phylogenetic tree is constructed using hierarchical agglomerative clustering based on the distance matrix. The results are compared with the UPGMA and other existing methods in terms of the quality and time of constructing the phylogenetic tree. Both qualitative and quantitative analysis are performed as key assessment criteria for analyzing the performance of the proposed model. The qualitative analysis of the phylogenetic tree is performed by considering rationalized perception, while the quantitative analysis is performed based on symmetric distance (SD). On both criteria, the results obtained by the proposed model are more satisfactory than those produced earlier on the same species by other methods. Notably, this method is found to be efficient in terms of both time and space requirements and is capable of dealing with protein sequences of varying lengths.

Mathematical Approach to Protein Sequence Comparison Based on Physiochemical Properties.

The difficult aspect of developing new protein sequence comparison techniques is coming up with a method that can quickly and effectively handle huge data sets of various lengths in a timely manner. In this work, we first obtain two numerical representations of protein sequences separately based on one physical property and one chemical property of amino acids. The lengths of all the sequences under comparison are made equal by appending the required number of zeroes. Then, fast Fourier transform is applied to this numerical time series to obtain the corresponding spectrum. Next, the spectrum values are reduced by the standard inter coefficient difference method. Finally, the corresponding normalized values of the reduced spectrum are selected as the descriptors for protein sequence comparison. Using these descriptors, the distance matrices are obtained using Euclidian distance. They are subsequently used to draw the phylogenetic trees using the UPGMA algorithm. Phylogenetic trees are first constructed for 9 ND4, 9 ND5, and 9 ND6 proteins using the polarity value as the chemical property and the molecular weight as the physical property. They are compared, and it is seen that polarity is a better choice than molecular weight in protein sequence comparison. Next, using the polarity property, phylogenetic trees are obtained for 12 baculovirus and 24 transferrin proteins. The results are compared with those obtained earlier on the identical sequences by other methods. Three assessment criteria are considered for comparison of the results-quality based on rationalized perception, quantitative measures based on symmetric distance, and computational speed. In all the cases, the results are found to be more satisfactory.

Protective role of host complement system in Aspergillus fumigatus infection.

Invasive aspergillosis (IA) is a life-threatening fungal infection for immunocompromised hosts. It is, therefore, necessary to understand the immune pathways that control this infection. Although the primary infection site is the lungs, aspergillosis can disseminate to other organs through unknown mechanisms. Herein we have examined the in vivo role of various complement pathways as well as the complement receptors C3aR and C5aR1 during experimental systemic infection by Aspergillus fumigatus, the main species responsible for IA. We show that C3 knockout (C3-/-) mice are highly susceptible to systemic infection of A. fumigatus. Intriguingly, C4-/- and factor B (FB)-/- mice showed susceptibility similar to the wild-type mice, suggesting that either the complement pathways display functional redundancy during infection (i.e., one pathway compensates for the loss of the other), or complement is activated non-canonically by A. fumigatus protease. Our in vitro study substantiates the presence of C3 and C5 cleaving proteases in A. fumigatus. Examination of the importance of the terminal complement pathway employing C5-/- and C5aR1-/- mice reveals that it plays a vital role in the conidial clearance. This, in part, is due to the increased conidial uptake by phagocytes. Together, our data suggest that the complement deficiency enhances the susceptibility to systemic infection by A. fumigatus.

Sensing the interactions between carbohydrate-binding agents and N-linked glycans of SARS-CoV-2 spike glycoprotein using molecular docking and simulation studies.

A recent surge in finding new candidate vaccines and potential antivirals to tackle atypical pneumonia triggered by the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) needs new and unexplored approaches in solving this global pandemic. The homotrimeric transmembrane spike (S) glycoprotein of coronaviruses which facilitates virus entry into the host cells is covered with N-linked glycans having oligomannose and complex sugars. These glycans provide a unique opportunity for their targeting via carbohydrate-binding agents (CBAs) which have shown their antiviral potential against coronaviruses and enveloped viruses. However, CBA-ligand interaction is not fully explored in developing novel carbohydrate-binding-based antivirals due to associated unfavorable responses with CBAs. CBAs possess unique carbohydrate-binding specificity, therefore, CBAs like mannose-specific plant lectins/lectin-like mimic Pradimicin-A (PRM-A) can be used for targeting N-linked glycans of S glycoproteins. Here, we report studies on the binding and stability of lectins (NPA, UDA, GRFT, CV-N and wild-type and mutant BanLec) and PRM-A with the S glycoprotein glycans via docking and MD simulation. MM/GBSA calculations were also performed for docked complexes. Interestingly, stable BanLec mutant (H84T) also showed similar docking affinity and interactions as compared to wild-type BanLec, thus, confirming that uncoupling the mitogenic activity did not alter the lectin binding activity of BanLec. The stability of the docked complexes, i.e. PRM-A and lectins with SARS-CoV-2 S glycoprotein showed favorable intermolecular hydrogen-bond formation during the 100 ns MD simulation. Taking these together, our predicted in silico results will be helpful in the design and development of novel CBA-based antivirals for the SARS-CoV-2 neutralization.Communicated by Ramaswamy H. Sarma.

Plant lectins and their usage in preparing targeted nanovaccines for cancer immunotherapy.

Plant lectins, a natural source of glycans with a therapeutic potential may lead to the discovery of new targeted therapies. Glycans extracted from plant lectins are known to act as ligands for C-type lectin receptors (CLRs) that are primarily present on immune cells. Plant-derived glycosylated lectins offer diversity in their N-linked oligosaccharide structures that can serve as a unique source of homogenous and heterogenous glycans. Among the plant lectins-derived glycan motifs, Man9GlcNAc2Asn exhibits high-affinity interactions with CLRs that may resemble glycan motifs of pathogens. Thus, such glycan domains when presented along with antigens complexed with a nanocarrier of choice may bewilder the immune cells and direct antigen cross-presentation - a cytotoxic T lymphocyte immune response mediated by CD8+ T cells. Glycan structure analysis has attracted considerable interest as glycans are looked upon as better therapeutic alternatives than monoclonal antibodies due to their cost-effectiveness, reduced toxicity and side effects, and high specificity. Furthermore, this approach will be useful to understand whether the multivalent glycan presentation on the surface of nanocarriers can overcome the low-affinity lectin-ligand interaction and thereby modulation of CLR-dependent immune response. Besides this, understanding how the heterogeneity of glycan structure impacts the antigen cross-presentation is pivotal to develop alternative targeted therapies. In the present review, we discuss the findings on structural analysis of glycans from natural lectins performed using GlycanBuilder2 - a software tool based on a thorough literature review of natural lectins. Additionally, we discuss how multiple parameters like the orientation of glycan ligands, ligand density, simultaneous targeting of multiple CLRs and design of antigen delivery nanocarriers may influence the CLR targeting efficacy. Integrating this information will eventually set the ground for new generation immunotherapeutic vaccine design for the treatment of various human malignancies.

An Intracellular Tripeptide Arg-His-Trp of Serum Origin Detected in MCF-7 Cells is a Possible Agonist to ß2 Adrenoceptor.

BACKGROUND: The need for agonists and antagonists of ß2 adrenoceptor (ß2AR) is warranted in various human disease conditions, including cancer, cardiovascular and other metabolic disorders. However, the sources of agonists of ß2AR are diverse in nature. Interestingly, there is a complete gap in the exploration of agonists of ß2AR from serum that is a well-known component of culture media that supports growth and proliferation of normal and cancer cells in vitro. METHODS: In this paper, we employed a novel vertical tube gel electrophoresis (VTGE)-assisted purification of intracellular metabolites of MCF-7 cells grown in vitro in complete media with fetal bovine serum (FBS). Intracellular metabolites of MCF-7 cells were then analyzed by LC-HRMS. Identified intracellular tripeptides of FBS origin were evaluated for their molecular interactions with various extracellular and intracellular receptors, including ß2AR (PDB ID: 2RH1) by employing molecular docking and molecular dynamics simulations (MDS). A known agonist of ß2AR, isoproterenol was used as a positive control in molecular docking and MDS analyses. RESULTS: We report here the identification of a few novel intracellular tripeptides, namely Arg-His- Trp, (PubChem CID-145453842), Pro-Ile-Glu, (PubChem CID-145457492), Cys-Gln-Gln, (PubChem CID-71471965), Glu-Glu-Lys, (PubChem CID-11441068) and Gly-Cys-Leu (PubChem CID-145455600) of FBS origin in MCF-7 cells. Molecular docking and MDS analyses revealed that among these molecules, the tripeptide Arg-His-Trp shows a favorable binding affinity with ß2AR (-9.8 Kcal/mol). The agonistic effect of Arg-His-Trp is significant and comparable with that of a known agonist of ß2AR, isoproterenol. CONCLUSION: In conclusion, we identified a unique Arg-His-Trp tripeptide of FBS origin in MCF-7 cells by employing a novel approach. This unique tripeptide Arg-His-Trp is suggested to be a potential agonist of ß2AR and it may have applications in the context of various human diseases like bronchial asthma and chronic obstructive pulmonary disease (COPD).

Identifying Drug Resistant miRNAs Using Entropy Based Ranking.

MicroRNAs play an important role in controlling drug sensitivity and resistance in cancer. Identification of responsible miRNAs for drug resistance can enhance the effectiveness of treatment. A new set theoretic entropy measure (SPEM) is defined to determine the relevance and level of confidence of miRNAs in deciding their drug resistant nature. Here, a pattern is represented by a pair of values. One of them implies the degree of its belongingness (fuzzy membership) to a class and the other represents the actual class of origin (crisp membership). A measure, called granular probability, is defined that determines the confidence level of having a particular pair of membership values. The granules used to compute the said probability are formed by a histogram based method where each bin of a histogram is considered as one granule. The width and number of the bins are automatically determined by the algorithm. The set thus defined, comprising a pair of membership values and the confidence level for having them, is used for the computation of SPEM and thereby identifying the drug resistant miRNAs. The efficiency of SPEM is demonstrated extensively on six data sets. While the achieved F-score in classifying sensitive and resistant samples ranges between 0.31 & 0.50 using all the miRNAs by SVM classifier, the same score varies from 0.67 to 0.94 using only the top 1 percent drug resistant miRNAs. Superiority of the proposed method as compared to some existing ones is established in terms of F-score. The significance of the top 1 percent miRNAs in corresponding cancer is also verified by the different articles based on biological investigations. Source code of SPEM is available at http://www.jayanta.droppages.com/SPEM.html.

Dietary Choices Modulate Colorectal Cancer Stem Cells: A Role of FXR Nuclear Receptor.

Intra- and inter-tumor heterogeneity (TMH) among colorectal cancer patients is considered as major hurdles to develop precise, potent, and personalized cancer therapeutics. The discernible factors that contribute to the existence of TMH and associated problems are suggested as genetic, molecular, epigenetic, and environmental pressures including shifts in trend from high-fiber diet to high-fat/processed sugar diet. In essence, components of high fat/processed sugar diet potentiate metabolic re-programing of inherent cellular heterogeneity of cancer stem cells (CSCs) by genetic and epigenetic pathways intersected by the farnesoid X receptor (FXR) nuclear receptor. Therefore, choices of dietary components shape up protumor or antitumor microenvironment by the modulation of FXR regulated transcriptional and epigenetic events in CSCs. In this article, we highlight the major understanding emanated from preclinical and clinical studies that indicate the potential contribution of high fiber/saturated sugar diet toward carcinogenesis of colorectal cancer.

Metabolic Ink Lactate Modulates Epigenomic Landscape: A Concerted Role of Pro-tumor Microenvironment and Macroenvironment During Carcinogenesis.

Tumor heterogeneity is influenced by various factors including genetic, epigenetic and axis of metabolic-epigenomic regulation. In recent years, metabolic-epigenomic reprogramming has been considered as one of the many tumor hallmarks and it appears to be driven by both microenvironment and macroenvironment factors including diet, microbiota and environmental pressures. Epigenetically, histone lysine residues are altered by various post-translational modifications (PTMs) such as acetylation, acylation, methylation and lactylation. Furthermore, lactylation is suggested as a new form of PTM that uses a lactate substrate as a metabolic ink for epigenetic writer enzyme that remodels histone proteins. Therefore, preclinical and clinical attempts are warranted to disrupt the pathway of metabolic-epigenomic reprogramming that will turn pro-tumor microenvironment into an anti-tumor microenvironment. This paper highlights the metabolicepigenomic regulation events including lactylation and its metabolic substrate lactate in the tumor microenvironment.

Carbohydrate-Binding Agents: Potential of Repurposing for COVID-19 Therapy.

With the emergence of the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the whole world is suffering from atypical pneumonia, which resulted in more than 559,047 deaths worldwide. In this time of crisis and urgency, the only hope comes from new candidate vaccines and potential antivirals. However, formulating new vaccines and synthesizing new antivirals are a laborious task. Therefore, considering the high infection rate and mortality due to COVID-19, utilization of previous information, and repurposing of existing drugs against valid viral targets have emerged as a novel drug discovery approach in this challenging time. The transmembrane spike (S) glycoprotein of coronaviruses (CoVs), which facilitates the virus's entry into the host cells, exists in a homotrimeric form and is covered with N-linked glycans. S glycoprotein is known as the main target of antibodies having neutralizing potency and is also considered as an attractive target for therapeutic or vaccine development. Similarly, targeting of N-linked glycans of S glycoprotein envelope of CoV via carbohydrate-binding agents (CBAs) could serve as an attractive therapeutic approach for developing novel antivirals. CBAs from natural sources like lectins from plants, marine algae and prokaryotes and lectin mimics like Pradimicin-A (PRM-A) have shown antiviral activities against CoV and other enveloped viruses. However, the potential use of CBAs specifically lectins was limited due to unfavorable responses like immunogenicity, mitogenicity, hemagglutination, inflammatory activity, cellular toxicity, etc. Here, we reviewed the current scenario of CBAs as antivirals against CoVs, presented strategies to improve the efficacy of CBAs against CoVs; and studied the molecular interactions between CBAs (lectins and PRM-A) with Man9 by molecular docking for potential repurposing against CoVs in general, and SARSCoV- 2, in particular.

A Leishmania donovani dominant-negative mutant for eIF2α kinase LdeK1 elicits host-protective immune response.

Dominant-negative mutation of LdeK1 gene, an eIF2α kinase from Leishmania donovani, revealed its role in translation regulation in response to nutrient starvation earlier. However, whether the kinase influences the infectivity of the parasites which naturally encounters nutrient deprivation during its life cycle was interesting to investigate. Both in vitro and in vivo experiments resulted in decrease of the parasite burden in peritoneal macrophages and in splenic/ hepatic load, respectively. An insight into the immune response of mice infected with mutant parasite showed enhanced pro-inflammatory cytokines and nitric oxide levels but reduced TH 2 and Treg population. The significantly reduced loss of infectivity of the parasites lacking a functional LdeK1 by modulating the immune response towards host protection makes it a potential vaccine candidate against Leishmaniasis.

Engineering anti-cancer nanovaccine based on antigen cross-presentation.

Dendritic cells (DCs) present exogenous antigens on major histocompatibility complex (MHC) class I molecules, thereby activating CD8+ T cells, contributing to tumor elimination through a mechanism known as antigen cross-presentation. A variety of factors such as maturation state of DCs, co-stimulatory signals, T-cell microenvironment, antigen internalization routes and adjuvants regulate the process of DC-mediated antigen cross-presentation. Recently, the development of successful cancer immunotherapies may be attributed to the ability of DCs to cross-present tumor antigens. In this review article, we focus on the underlying mechanism of antigen cross-presentation and ways to improve antigen cross-presentation in different DC subsets. We have critically summarized the recent developments in the generation of novel nanovaccines for robust CD8+ T-cell response in cancer. In this context, we have reviewed nanocarriers that have been used for cancer immunotherapeutics based on antigen cross-presentation mechanism. Additionally, we have also expressed our views on the future applications of this mechanism in curing cancer.

Extrachromosomal circular DNAs: an extra piece of evidence to depict tumor heterogeneity.

The tumor microenvironment (TME) comprises a heterogeneous number and type of cellular and noncellular components that vary in the context of molecular, genomic and epigenomic levels. The genotypic diversity and plasticity within cancer cells are known to be affected by genomic instability and genome alterations. Besides genomic instability within the chromosomal linear DNA, an extra factor appears in the form of extrachromosomal circular DNAs (eccDNAs; 2-20 kbp) and microDNAs (200-400 bp). This extra heterogeneity within cancer cells in the form of an abundance of eccDNAs adds another dimension to the expression of procancer players, such as oncoproteins, acting as a driver for cancer cell survival and proliferation. This article reviews research into eccDNAs centering around cancer plasticity and hallmarks, and discusses these facts in light of therapeutics and biomarker development.