Tumor Immune Microenvironment Subtyping And Its Multi-omics Molecular Features In The Evaluation Of The Efficacy And Prognosis Of Anti-PD-1/PD-L1 Immunotherapy

Immunotherapy targeting programmed cell death 1(PD-1)and its ligand(PD-L1)has made great progress in a variety of solid tumors.However,the response rate of anti-PD-1/PD-L1 immunotherapy is low and the available studies on prognostic and efficacy predictors are still inadequate.Therefore,there is an urgent need for in-depth studies on biomarkers related to prognosis and efficacy prediction of anti-PD-1/PD-L1 immunotherapy to screen potential beneficiaries.The aim of this study was to develop a tumor immune microenvironment(TIME)typing model and explored biomarker to predict the prognosis and efficacy of anti-PD-1/PD-L1 immunotherapy,based on multi-omics analysis of transcriptomic and genomic data from 33cancers in the TCGA database,one breast cancer transcriptome data in the GEO database,five solid tumor immunotherapy transcriptomic data,and solid tumor immunotherapy genomic data from memorial sloan kettering cancer center(MSKCC).The main findings are as follows.Firstly,the study developed a novel tumor-infiltrating lymphocyte(TIL)score based on the expression profiles of a total of 163 relevant genes in the major histocompatibility complex,checkpoints and immunomodulators,effector and suppressor cells classes.As a result,the mean area under curve(AUC)value is 0.592 in the immunotherapy cohort was slightly better than the CD8A(AUC=0.575)or CD8B(AUC=0.552)gene expression indicators used in previous studies.The result of combining PD-L1 expression with TIL score revealed that the mean AUC is 0.64(0.6,0.722)for the logistic regression predicted probability value of the combined indicators,which was superior to the typing method based on PD-L1 expression,TIL score,CD8A or CD8B gene expression alone.The TIME typing model was constructed by combining PD-L1 expression and TIL scores after determining the quantile threshold by immunotherapy survival analysis.The result showed that it has an ability to effectively predict tumor prognosis(P<0.0001),immunotherapy prognosis(P=0.03)and efficacy(P=0.01146),among them,TIME subtype I(PD-L1 positive/TIL positive)was significantly better than the other three subtypes(response rates of 21%,32%and 36%,respectively)in terms of tumor prognosis,immunotherapy prognosis and efficacy(response rate of 42%).Secondly,through assessing the proportion of immune infiltrating cells based on the CIBERSORT algorithm,it was found that TIME subtype I had the highest proportion of T lymphocytes,CD8~+T cells,a higher proportion of activated NK cells relative to infiltration and the lowest proportion of macrophages and mast cells.The study also found that the proportion of CD8~+T cells was significantly and positively correlated with TIL score(Spearman R=0.24,P<2.2e-16;Spearman R=0.33,P<2.2e-16),and a high proportion of CD8~+T cells was associated with good tumor prognosis(P<0.0001),immunotherapy prognosis(P=0.012)and efficacy(response rate of 41.86%,P=7.137e-06).Pathway enrichment analysis based on differentially expressed genes across TIME subtypes has revealed that TIME subtype I was predominantly enriched in immune activation-related pathways.However,gene set variation analysis(GSVA)results showed that TIME subtype III(PD-L1 positive/TIL negative)generally had higher mean enrichment scores in the cancer hallmark genesets,including glycolysis,and high scores of which were associated with poor prognosis for immunotherapy(P=0.0023).The study further screened 13 TIME subtype I signature genes(T1SGs)associated with tumor prognosis,immunotherapy prognosis and efficacy prediction,including:TPBGL,PSMB9,CD8B,RTBDN,ZNF683,WARS,CTSB,LYPD5,CD7,LGALS2,NKX2-4,HHLA2 and SH2D1A.Moreover,it was found that high T1SGs scores were associated with a good prognosis(P<0.0001)and efficacy of immunotherapy(response rate of 43.26%,P=3.197e-07).Notably,after further integration of transcriptomic characteristics,it was found that patients with all three features,including high T1SGs score,high CD8~+T cells proportion and low glycolysis score had a better outcome(response rate of 48.28%,P=0.01167)than those with any of the them.Finally,a highly significant positive correlation was found between tumor mutation burden(TMB)and predicted neoantigen counts(Spearman R=0.886,P<2.2e-16),with TMB and neoantigen count found to be higher in the TIME subtype III.The study also found that both high TMB and neoantigen counts were associated with poor prognosis of the tumor(both P values<0.0001),while high TMB was associated with a good prognosis of immunotherapy(P=0.0099).In addition,BRAF mutations and KMT2D mutations were identified as characteristic mutated genes for TIME subtype I and BRAF/KMT2D co-mutations were associated with a good prognosis with immunotherapy(P=0.019).In conclusion,this study identified biomarkers associated with prognosis and efficacy prediction of anti-PD-1/PD-L1 immunotherapy in solid tumors based on tumor immune microenvironment subtyping by analysing their multi-omics molecular features.They are the proportion of CD8~+T cells,glycolysis score,13 TIME subtype I signature genes(TPBGL,PSMB9,CD8B,RTBDN ZNF683,WARS,CTSB,LYPD5,CD7,LGALS2,NKX2-4,HHLA2 and SH2D1A)scores and BRAF/KMT2D co-mutations.This study will provide a data base and potential candidate markers for clinical immunotherapy studies,and then provide new insights for screening immunotherapy benefit groups.