Evidence map›Paper›PMID 34690620›Full record

ArticleInternational journal of peptide research and therapeutics2021

Implementation of Vaccinomics and In-Silico Approaches to Construct Multimeric Based Vaccine Against Ovarian Cancer.

Muhammad Sufyan, Farah Shahid, Faiza Irshad, Anam Javaid, Muhammad Qasim, Usman Ali Ashfaq

Abstract read
In one paragraph

Article in International journal of peptide research and therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Muhammad SufyanDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.
Farah ShahidDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.
Faiza IrshadEnvironment Biotechnology Lab, Institute of Botany, University of the Punjab, Lahore, Pakistan.
Anam JavaidDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.
Muhammad QasimDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.
Usman Ali AshfaqDepartment of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan.ORCID 0000-0002-5495-805X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One of the most common gynecologic cancers is ovarian cancer and ranked third after the other two most common cancers: cervical and uterine. The highest mortality rate has been observed in the case of ovarian cancer. To treat ovarian cancer, an immune-informatics approach was used to design a multi-epitope vaccine (MEV) structure. Epitopes prediction of the cancer testis antigens (NY-ESO-1), A-Kinase anchor protein (AKAP4), Acrosin binding protein (ACRBP), Piwi-like protein (PIWIL3), and cancer testis antigen 2 (LAGE-1) was done. Non-toxic, highly antigenic, non-allergenic, and overlapping epitopes were shortlisted for vaccine construction. Chosen T-cell epitopes displayed a robust binding attraction with their corresponding Human Leukocyte Antigen (HLA) alleles demonstrated 97.59% of population coverage. The vaccine peptide was established by uniting three key constituents, comprising the 14 epitopes of CD8 + cytotoxic T lymphocytes (CTLs), 5 helper epitopes, and the adjuvant. For the generation of the effective response of CD4 + cells towards the T-helper cells, granulocyte-macrophage-colony-stimulating factor (GM-CSF) was applied. With the addition of adjuvants and linkers, the construct size was 547 amino acids. The developed MEV structure was predicted to be antigenic, non-toxic, non-allergenic, and firm in nature. I-tasser anticipated the 3D construction of MEV. Moreover, disulfide engineering further enhanced the stability of the final vaccine protein. In-silico cloning and vaccine codon optimization were done to analyze the up-regulation of its expression. The outcomes established the vaccine's immunogenicity and safety profile, besides its aptitude to encourage both humoral and cellular immune responses. The offered vaccine, grounded on our in-silico investigation, may be considered for ovarian cancer immunotherapy. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s10989-021-10294-w.

Indexed as

GM-CSFHuman leukocyte antigenImmunotherapyMEVOvarian cancer

Identifiers

PMID34690620
PMCPMC8524215

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.