Construction Of Prediction And Analysis Platform For Individualized Epitope Antigen Of Lung Cancer

Lung cancer is one of the cancer types with the highest morbidity and mortality.Its pathogenic mechanism and treatment methods have been widely concerned by researchers all over the world.Among them,targeted therapy and immunotherapy are hot topics in the treatment of lung cancer.The discovery of cancer driver genes and potential targets is closely related to understanding the causes of lung cancer and the development of targeted drugs,and the research of therapeutic tumor vaccines is also considered to be a new direction for personalized medicine.Therefore,this paper used high-throughput sequencing data to study the driver genes and specific mutations of lung cancer,and then established an epitope antigen prediction and analysis platform based on personalized mutation sequences.This article first reconstructed the analysis process of acquiring individualized mutation sequences of cancer tissues,and analyzed the transcriptome data and all exome data of lung cancer samples.Compared with the existing high-throughput sequencing analysis method,this analysis process replaces a new version of the reference sequence,and introduces a model that corrects the base value of the sequencing alignment file according to the known site,so that the sequencing alignment will be more complete;in terms of mutation comparison,two mainstream software GATK4 and Varscan2 are used for mutation detection,and MuSE is used as auxiliary software to ensure the integrity of the mutation site.And the maf format file output by the analysis process is convenient for further analysis.After that,we continued to analyze the mutation information of the lung squamous cell carcinoma and lung adenocarcinoma samples.In this paper,clustering-based OncodriveCLUST algorithm and pathway-enriched Multi-dendrix algorithm are used to determine the driver genes of cancer.The analysis results showed that the three genes PIK3CA,TP53,NFE2L2 and the two pathways PI3K and TP53 have a great influence on the development of lung squamous cell carcinoma,and the driver genes of lung adenocarcinoma are mainly KRAS and EGFR.Finally,the two algorithms for discovering driver genes are compared,and a new procedure for driver gene analysis is determined.Based on the obtained mutation sequence,this paper completely established the predictive analysis process of individualized epitope antigen.First,we used HLAssign software to determine the HLA type of the patient,then we wrote a program to obtain the peptides of the mutation site based on the standard protein sequence to avoid the misplacement during DNA translation.After that,NetMHCpan4.0 and NetMHCIIpan3.2 were used to analyze the mutated polypeptide fragments to complete epitope prediction.Finally,we screened for new antigens according to the requirements of vaccine production.In summary,this article established a more reasonable analysis platform for obtaining individualized mutation sequences of cancer and epitope antigen prediction,and completed a comparative analysis of the potential driver genes of lung adenocarcinoma and lung squamous cell carcinoma.Finally,we completed a personalized epitope prediction and epitope screening for a lung cancer patient.