The Prognostic Value Of Immune Cells In Tumor Microenvironment Of Patients With Cancer

● Part I The prognostic significance of tumor immune microenvironment of breast cancer patients● Chapter I An immune-related signature to improve prognosis prediction of breast cancerBackground:Increasing evidence suggests that immune cells in tumor microenvironment(TME)play a paramount role in driving poor prognosis.Herein,we aimed to develop a TME-associated,immune-related signature to improve prognosis prediction of Breast Cancer(BRCA).Methods:BRCA_OURS enriched transcriptomic RNA sequencing(RNA-seq)of tumor tissue were acquired from 43 breast cancer patients before any treatment.Based on the immune gene profiles of 43 patients from BRCA_OURS and 932 BRCA patients from The Cancer Genome Atlas(TCGA),we performed consensus clustering to evaluate the immune infiltration of patients,determining a robust immune-related signature that was significantly associated with the overall survival(OS)in the training series.We further confirmed their reproductivity in an external validation series,the Molecular Taxonomy of Breast Cancer International Consortium(METABRIC)cohort.Results:Based on this 10-gene immune-related signature,the training series patients were grouped into the high-risk and low-risk group with significantly OS,progression-free survival and disease-free survival.The high-risk group is likely to have inferior outcomes than the low-risk group.Correspondingly,we found the high-risk score group was related to several important cancer-associated pathways,including deregulation of cellular energetics,genome instability,mobilizing more Golgi vesicle mediated transport and intensive DNA double strand breaking.That holds the key for further growing and metastasizing.Conclusions:Based on the immune infiltration of each BRCA patients,we developed and validated an immune-related signature with the different performance of prognosis prediction.Our results demonstrated immunological heterogeneity within BRCA and provided an efficient stratification tool for clinical prognosis assessment of BRCA patients.● Chapter Ⅱ A novel signature based on TCR repertoire to predict the prognosis and immune response for breast cancerBackground:Breast cancer(BC)is the most common cancer in females.Although immunotherapy has revolutionized the treatment of other intractable cancers,only a partial BC responds to immune checkpoint inhibitors.To better understand the T cells in the immune microenvironment of BC,we collected 43 patients for tumor tissue and peripheral blood to obtain and analyze the transcriptome and TCR repertoire profiling.Methods:We connected TCR diversity with expression profile via correlation analysis and further used the LASSO-COX algorithm to construct a signature to predict the prognosis of BC.Based on the TCR index score,patients were divided into high-and lowrisk groups.Various evaluations for the immune landscape were further used to assess the characteristics of the immune microenvironment in each group both in TCR profile and transcriptome.Results:We constructed a 19-gene TCR-related signature for patients with BC in the transcriptome.TCR index was representative of the reactive CD8+T cell function.Compared to the low-risk group,the patients with the high TCR index had significantly shorter survival indicators,minor immune scores,less TCR diversity,lower clonotypes,and inferior response for the immune checkpoints.Conclusions:Our study,for the first time,integrated tumor TCR profiling with transcriptome and proposed an immune signature that predicted the prognosis and immune response for breast cancer.● Part Ⅱ A signature for pan-cancer prognosis based on neutrophil extracellular trapsBackground:Neutrophil extracellular traps(NETs)were originally thought to be formed by neutrophils to trap invading microorganisms as a defence mechanism.Increasing studies have shown that NETs play a pivotal role in tumor progression and diffusion.In this case,transcriptome analysis provides an opportunity to unearth the association between NETs and clinical outcomes of pan-cancer patients.Methods:The transcriptome sequencing data of TCGA pan-cancer primary focus was obtained from UCSC Xena,and a 19-gene NETs score was then constructed using the LASSO Cox regression model based on the expression levels of 69 NETs initial biomarkers we collected from multi-studies.In addition,10 datasets covering multiple cancer types from other databases were collected and used to validate the signature.Gene ontology enrichment analyses were used to annotate the functions of NETs-related pathways.Immunohistochemistry(IHC)was implemented to evaluate the role of NETsrelated genes in clinical patients across types of tumors,including lung adenocarcinoma(n=58),colorectal carcinoma(n=93),kidney renal clear cell carcinoma(n=90),and triplenegative breast cancer(n=80).Results:The NETs score was calculated based on 19-NETs related genes according to the LASSO Cox model.The NETs scores were considered a hazardous factor in most cancer types,with a higher score indicating a more adverse outcome.In addition,we found that NETs were significantly correlated to various malignant biological processes,such as the epithelial to mesenchymal transition(R=0.7444,p<0.0001),angiogenesis(R=0.5369,p<0.0001),and tumor cell proliferation(R=0.3835,p<0.0001).Furthermore,in IHC cohorts of a variety of tumors,myeloperoxidase,a gene involved in the model and a classical delegate of NETs formation,was associated with poor clinical outcomes.Conclusions:Collectively,these constitutive and complementary biomarkers represented the ability of NETs formation to predict the development of patients’progression.Integrative transcriptome analyses plus clinical sample validation may facilitate the biomarker discovery and clinical application.