Research On Predictive Markers For The Efficacy Of Neoadjuvant Immunotherapy In Non-small Cell Lung Cancer Based On Multi-omics Technology

PurposesNon-small cell lung cancer(NSCLC)is the main pathological type of lung cancer,accounting for about 85%of lung cancers.Neoadjuvant immunotherapy can significantly improve the prognosis of NSCLC patients,but there is a lack of ideal predictive markers for efficacy.At present,most studies on predictive markers of curative effect are based on western populations,and there are large differences in gene spectrum,race,and living habits between Chinese and Western populations,and there will also be differences in the efficacy of neoadjuvant immunotherapy and predictive markers.Based on multi-omics detection technology,this study explores effective predictive markers for the efficacy of neoadjuvant immunotherapy.At the same time,through the comparative analysis of Chinese and Western efficacy predictive markers based on the transcription level,it provides a reference for exploring specific neoadjuvant immune efficacy predictive markers suitable for Chinese people.Content and methodsThis study starts from different levels of gene,transcription,protein,metabolism,etc.,and uses multi-omics detection technology to explore more suitable markers for predicting the efficacy of neoadjuvant immunotherapy for Chinese people.Use targeted DNA sequencing detection technology to explore the function of genetic variation,tumor mutation burden(TMB)and other genetic markers for predicting the efficacy of neoadjuvant immunotherapy.Use the next-generation RNA-seq sequencing detection technology to explore the functions of differentially expressed genes and other transcriptional therapeutic effect prediction markers.Using Dako 22C3 method to detect the expression of programmed death ligand 1(PD-L1)(tumor cell positive proportion fraction[TPS]method),multiplex immunofluorescence(mIF),proteome mass spectrometry and other technologies to explore the function of therapeutic effect prediction markers at protein levels such as PD-L1 expression,cell surface Marker protein expression,and plasma protein expression.Use metabolomics detection technology to explore the function of therapeutic effect prediction markers of metabolic levels such as plasma metabolite content.At the same time,based on the transcriptome level,the Cancer Genome Atlas(TCGA)public database and lung adenocarcinoma transcriptome data in published articles were used to explore the differences in the efficacy markers of neoadjuvant immunotherapy,such as PD-L1 expression,the content of tumor-infiltrating lymphocytes(TILs)and the components of tumor microenvironment(TME),between China and the West.ResultsThe results of multi-omics analysis at different levels of gene,transcription,protein and metabolism showed that NSCLC patients with different neoadjuvant immunotherapy effects had different levels of gene variation profiles,TMB levels,differentially expressed gene profiles,PD-L1 expression,various immune cell marker protein levels in tumors,plasma protein levels,and plasma metabolite levels.The results of comparative analysis of lung adenocarcinoma in China and the West based on the transcriptome level showed that there were differences in the expression levels of common neoadjuvant immunotherapy markers such as PD-L1 expression,TILs content,and TME components between Chinese and Western populations.ConclusionsDifferent levels of indicators based on multi-omics detection technology,such as genes,transcription,proteins,and metabolism,have an acceptable predictive effect on the efficacy of neoadjuvant immunotherapy,and can become suitable predictive markers for the efficacy of neoadjuvant immunotherapy in patients with NSCLC.The results of comparative analysis of common neoadjuvant immunotherapy efficacy predictive markers in Chinese and Western populations based on transcriptomics level showed that there were differences in the efficacy and predictive markers of neoadjuvant immunotherapy between Chinese and Western lung adenocarcinoma populations.This study provides hints and references for exploring and finding specific predictive markers for the efficacy of neoadjuvant immunotherapy in Chinese NSCLC patients.