Cancer immunoinformatics： a new assistant tool for malignant diseaseresearch

Objective To introduce the recent developments in cancer immunoinformatics with an emphasis on the latest trends and future direction.Data sources All related articles in this review were searched from PubMed published in English from 1992 to 2013. The search terms were cancer, immunoinformatics, immunological databases, and computational vaccinology.Study selection Original articles and reviews those were related to application of cancer immunoinformatics about tumor basic and clinical research were selected.Results Cancer immunoinformatics has been widely researched and applied in a series of fields of cancer research, including computational tools for cancer, cancer immunological databases, computational vaccinology, and cancer diagnostic workflows. Furthermore, the improvement of its theory and technology brings an enlightening insight into understanding and researching cancer and helps expound more deep and complete mechanisms of tumorigenesis and progression.Conclusion Cancer immunoinformatics provides promising methods and novel strategies for the discovery and development of tumor basic and clinical research.

Key role of human leukocyte antigen in modulating human immunodeficiency virus progression: An overview of the possible applications

Host and viral factors deeply influence the human immunodeficiency virus(HIV) disease progression. Among them human leukocyte antigen(HLA) locus plays a key role at different levels. In fact, genes of the HLA locus have shown the peculiar capability to modulate both innate and adaptive immune responses. In particular, HLA class Ⅰmolecules are recognized by CD8+ T-cells and natural killers(NK) cells towards the interaction with T cell receptor(TCR) and Killer Immunoglobulin Receptor(KIR) 3DL1 respectively. Polymorphisms within the different HLA alleles generate structural changes in HLA classⅠpeptide-binding pockets. Amino acid changes in the peptide-binding pocket lead to the presentation of a different set of peptides to T and NK cells. This review summarizes the role of HLA in HIV progression toward acquired immunodeficiency disease syndrome and its receptors. Recently, many studies have been focused on determining the HLA binding-peptides. The novel use of immune-informatics tools, from the prediction of the HLA-bound peptides to the modification of the HLAreceptor complexes, is considered. A better knowledge of HLA peptide presentation and recognition are allowing new strategies for immune response manipulation to be applied against HIV virus.

Development and Evaluation of a Promising Biomarker for Diagnosis of Latent and Active Tuberculosis Infection

Background:Diagnosing latent tuberculosis(TB)infection(LTBI)and active TB(ATB)is crucial for preventing disease progression and transmission.However,current diagnostic tests have limitations in terms of accuracy and sensitivity,making it challenging to diagnose these different infection states.Therefore,this study intends to develop a promising biomarker for LTBI and ATB diagnosis to overcome the limitations of the current diagnostic tests.Methods:We developed a novelmultiepitope-based diagnostic biomarker(MEBDB)fromLTBI region of differentiation antigens using bioinformatics and immunoinformatics.Immune responses induced byMEBDM were detected using enzyme-linked immunosorbent spot and cytometric bead assays.This study was conducted from April 2022 to December 2022 in the SeniorDepartment of Tuberculosis at the 8thMedical Center of PLA General Hospital,China.Blood samples were collected from participants with ATB,individuals with LTBI,and healthy controls(HCs).The diagnostic efficacy of MEBDB was evaluated using receiver operating characteristic curves.Results:A novel MEBDB,designated as CP19128P,was generated.CP19128P comprises 19 helper T lymphocyte epitopes,12 cytotoxic T lymphocyte epitopes,and 8 B-cell epitopes.In silico simulations demonstrated that CP19128P possesses strong affinity for Toll-like receptors and elicits robust innate and adaptive immune responses.CP19128P generated significantly higher levels of tumor necrosis factor(TNF-α),interleukin 4(IL-4),and IL-10 in ATB patients(n=7)and LTBI(n=8)individuals compared with HCs(n=62)(P<0.001).Moreover,CP19128P-induced specific cytokines could be used to discriminate LTBI and ATB from healthy subjects with high sensitivity and specificity.Combining IL-2 with IL-4 or TNF-α could differentiate LTBI from HCs(the area under the receiver operating characteristic curve[AUC],0.976[95% confidence interval[CI],0.934-1.000]or 0.986[0.956-1.000]),whereas combining IL-4 with IL-17A or TNF-α could differentiate ATB from HCs(AUC,0.887[0.782-0.993]or 0.984[0.958-1.000]).Conclusions:Our study revealed that CP19128P is a potential MEBDBfor the diagnosis of LTBI andATB.Our findings suggest a promising strategy for developing novel,accurate,and sensitive diagnostic biomarkers and identifying new targets for TB diagnosis and management.

Decoding bovine coronavirus immune targets:an epitope informatics approach

Bovine coronavirus(BCoV)poses a significant threat to the global cattle industry,causing both respiratory and gastrointestinal infections in cattle populations.This necessitates the development of efficacious vaccines.While several inactivated and live BCoV vaccines exist,they are predominantly limited to calves.The immunization of adult cattle is imperative for BCoV infection control,as it curtails viral transmission to calves and ameliorates the impact of enteric and respiratory ailments across all age groups within the herd.This study presents an in silico methodology for devising a multiepitope vaccine targeting BCoV.The spike glycoprotein(S)and nucleocapsid(N)proteins,which are integral elements of the BCoV structure,play pivotal roles in the viral infection cycle and immune response.We constructed a remarkably effective multiepitope vaccine candidate specifically designed to combat the BCoV population.Using immunoinformatics technology,B-cell and T-cell epitopes were predicted and linked together using linkers and adjuvants to efficiently trigger both cellular and humoral immune responses in cattle.The in silico construct was characterized,and assessment of its physicochemical properties revealed the formation of a stable vaccine construct.After 3D modeling of the vaccine construct,molecular docking revealed a stable interaction with the bovine receptor bTLR4.Moreover,the viability of the vaccine’s high expression and simple purification was demonstrated by codon optimization and in silico cloning expression into the pET28a(+)vector.By applying immunoinformatics approaches,researchers aim to better understand the immune response to bovine coronavirus,discover potential targets for intervention,and facilitate the development of diagnostic tools and vaccines to mitigate the impact of this virus on cattle health and the livestock industry.We anticipate that the design will be useful as a preventive treatment for BCoV sickness in cattle,opening the door for further laboratory studies.

Reverse vaccinology assisted designing of multiepitope-based subunit vaccine against SARS-CoV-2

Background:Coronavirus disease 2019(COVID-19)linked with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2)cause severe illness and life-threatening pneumonia in humans.The current COVID-19 pandemic demands an effective vaccine to acquire protection against the infection.Therefore,the present study was aimed to design a multiepitope-based subunit vaccine(MESV)against COVID-19.Methods:Structural proteins(Surface glycoprotein,Envelope protein,and Membrane glycoprotein)of SARS-CoV-2 are responsible for its prime functions.Sequences of proteins were downloaded from GenBank and several immunoinformatics coupled with computational approaches were employed to forecast B-and T-cell epitopes from the SARS-CoV-2 highly antigenic structural proteins to design an effective MESV.Results:Predicted epitopes suggested high antigenicity,conserveness,substantial interactions with the human leukocyte antigen(HLA)binding alleles,and collective global population coverage of 88.40%.Taken together,276 amino acids long MESV was designed by connecting 3 cytotoxic T lymphocytes(CTL),6 helper T lymphocyte(HTL)and 4 B-cell epitopes with suitable adjuvant and linkers.The MESV construct was non-allergenic,stable,and highly antigenic.Molecular docking showed a stable and high binding affinity of MESV with human pathogenic toll-like receptors-3(TLR3).Furthermore,in silico immune simulation revealed significant immunogenic response of MESV.Finally,MEV codons were optimized for its in silico cloning into the Escherichia coli K-12 system,to ensure its increased expression.Conclusion:The MESV developed in this study is capable of generating immune response against COVID-19.Therefore,if designed MESV further investigated experimentally,it would be an effective vaccine candidate against SARS-CoV-2 to control and prevent COVID-19.

A primer on recent developments in cancer immunotherapy, with a focus on neoantigen vaccines

Cancer immunotherapy has now been conclusively shown to be capable of producing durable responses for a substantial number of patients.Adoptive cell transfer and checkpoint blockade therapies in particular both demonstrate that antigen-specific immune responses can be dramatically effective,even in previously refractory late stage disease.Such developments,together with advances in technology,have strongly encouraged revisiting the concept of neoantigen vaccines.Here we introduce basic ideas in the field to allow investigators from diverse backgrounds to understand these developments,grasp current issues,and contribute to further progress.