The Immune Characterization And Risk Profiling Of Glioma Based On Multi-omics Integrative Analysis

IntroductionGlioma is the most common type of primary tumor in the central nervous system,which accounts for more than 50% of tumor within central nervous system.It is recognized to be with high recurrence rate and high mortality.Current standard of care consists of surgery combined with adjuvant radiation and chemotherapy.However,even under this multiform treatment,the prognosis of glioma is still unsatisfactory,that the most malignant glioblastoma(GBM)patients suffered a median survival of only 14 months.For now,glioma is one of the difficulties in the field of cancer treatment.The central nervous system has long been considered as immune-priviledged.But recent studies found that the central nervous system has specific immunological structure and characteristics.On the other hand,the development of glioma often accompanies with the destruction of the blood-brain barrier.A large amount of peripheral immune cells could infiltrate into glioma tissue to established a suitable microenvironment facilitateing its malignancy.These foundings provide a novel immunologic perspective to understand glioma.Immunotherapy,as a promising stratergy in the precise medicine,has made breakthrough in a variety of tumors.However,its application in glioma is still under an early stage.There are sevaral problems to be explored: the role of immune disorder in facilitating malignant progression and unfavaoable prognosis of glioma;the similarities and differences of immune responses among different subtypes of glioma;and the key driving mechanism of glioma under various immune microenvironment.To investigate the above problems,we applied a stratery of multi-omics integrative analysis combining experimental confirmation based on the project of “Chinese Glioma Genome Atlas” to conduct a series of studies exploring the glioma immunologic problems.Methods(1)Patient data: The traning data was obtained from the CGGA platfrom.The specimens of glioma were collected from the platform paticipants.The samples were obtained directly during surgery and stored in liquid nitrogen.Two independent neuropathologists established the diagnosis and ensured the quality of the tissue for molecular testing.The external validation sets were obtained from The Tumor Genome Atlas(TCGA)and Gene Expression Omnibus(GEO)platform.(2)Patient consents and standard protocol approvals: Collection of tumor tissue and clinicopathologic information was undertaken with informed consent.The study protocol was approved by the ethics committees of participating organizations.(3)Sample preparation: RNA samples were extracted using the mir Vana kit(Ambion).DNA samples were extracted using the QIAamp kit(Qiagen).The sample preparation and quality control were processed according to the manufacturer’s protocol(4)m RNA microarray profiling: Microarray analysis was performed using the Agilent Whole Human Genome Array according to the manufacturer’s instructions.The integrity of total RNA was checked using an Agilent 2100 Bioanalyzer(Agilent).Data were acquired using the Agilent G2565 BA Microarray Scanner System and Agilent Feature Extraction Software(version 9.1).Probe intensities were normalized using Gene Spring GX 11.0.(5)RNA sequencing: The libraries were sequenced on the Illumina Hi Seq 2000 platform using the 101-bp pair-end sequencing strategy.The original image data generated by the sequencing machine were converted into sequence data via base calling(Illumina pipeline CASAVA v1.8.2).Hg 19 Ref Seq(RNA sequences,GRCh37)was downloaded from the UCSC Genome Browser.The gene expression was calculated using the RPKM method(6)Molecular analyses: The statuse of IDH mutation and MGMT promoter methylation were detected by DNA pyrosequencing.(7)Bioinformatic analysis: We carried out principal components analysis with R programming language to explore expression patterns of grouped patients.GSEA was performed to explore whether the identified sets of genes showed statistical differences between 2 groups.Gene sets were submitted to the DAVID website to perform gene ontology and pathway annotation.(8)Cell lines: The human glioma cell line U87,LN229,U251 and H4 were obtained from the Institute of Biochemistry and Cell Biology.The microarray-based expression profle of cell lines was downloaded from Cancer Cell Line Encyclopedia.The data were calculated according to the subtyping scheme and single-sample GSEA algorithm.The result showed that U87 had a predominant feature of mesenchymal tumors.(9)Down-regulation of STAT3 and western blot: Specifc short interfering RNA(si RNA)sequences targeting STAT3 were used to down-regulated STAT3.Western blot was used to test the knockdown effect and the effect of STAT3 on NOCTH pathway activation.(10)Statistical analysis: The differences of the characteristics between groups were tested using Student’s t test or chi-square test.Prognosis differences between groups were assessed by Kaplan-Meier curves and Log-rank test.Univariate and multivariate Cox regression analyzes were used to identify independent factors that influenced prognosis.Pearson test was used to evaluate the correlation between variables.SPSS,Graph Pad Prism6,and R language were used to statistical analysis.ResultsPart 1: We found that the immune response phenotype was affected the malignant grade rather than the histopathologic classificaition.The most malignant GBM exhibited the most enhanced phenotype of local immune response.We profiled the immune-related gene set and identified 8 genes(FOXO3,IL6,IL10,ZBTB16,CCL18,AIMP1,FCGR2 B,and MMP9)with the greatest prognostic value in GBM.A local immune-related risk signature was developed from the genes to distinguish cases as high or low risk of unfavorable prognosis.The scoring value has independent and significant prognostic value in GBMs.Almost all of the high-risk patients were IDH wild-type,belonged to mesenchymal subtype and showed an enhanced local immune response.Part 2: By comparing the transcriptomic data between IDH1 mutant and wild-type LGG,we found that IDH1 mutation is associated with upregulated genes enriched in neurogenesis and downregulated genes enriched in immune response phenotype.In IDH1 mutant LGGs,we found 1245 genes with significant statistical significance.Among the prognostic genes,the risky ones were mainly correlated with the enhancement of immune response.We further established a signature based on regression fitting in IDH1 mutant LGG.The prognostic signature was independently correlated with survival time and was more accurate in predicting 3-year and 5-year survival than the other clinicopathologic features.Moreover,we found that the transcriptomic differences according to IDH1 mutation in GBM was similar to the LGGs.And the prognostic signature remained its prognostic significance in IDH1 mutant GBMs.When combined with malignant grade and IDH1 status,the prognostic signature was a tool that enables precise risk stratification and could improve clinical management.Part 3: We grouped the GBM cases from the TCGA platform according to STAT3 phosphorylation levels.We found that the transcriptional differences associated with STAT3 phosphorylation was different among molecular subtypes.The analyses revealed a prominent role for STAT3 in the mesenchymal but not in other GBM subtypes,which can be used to classify mesenchymal GBMs into 2 groups based on phosphorylated STAT3 level.In mesenchymal subtype,STAT3 phosphorylation specifically activated the Notch pathway which could be valided in a mesenchymal glioma cell line of U87.In addition,we also identified the key nodes of other pathways associated with STAT3 phosphorylation in each subtype and proposed a 17 mi RNA-coexpression network coorperating with STAT3 phosphorylation.Conclusion:Part 1: We found that the local immune response enhanced along with the malignant progression.Eight immune genes with significant prognostic value were identified to develop an immune-related risk signature.This signature could independently correlate with prognosis and indicating intensive local immune response.These foundings suggest that the enhanced immune response is an important factor leading to the malignant progression and poor prognosis of glioma.Part 2: Our results showed that the IDH1 mutation plays a broad and similar role in LGG and GBM,and the immune response was surppressed in IDH1 mutant gliomas.By establishing a prognostic profiling,we found immune disorder is the most important contributor in reducing the survival time of IDH1 mutant gliomas.We developed a risk signature which was equally significant in the IDH1 mutant LGG and GBM.The above study first proposed the immunomodulatory potential of IDH1 and established a novel prognostic marker for IDH1 mutant glioma.Part 3: We identified proteins,m RNAs and mi RNAs associated with the STAT3 signaling pathway in patients with vaiours subtypes of GBM.We found that STAT3,as a pathway hub in multiple tumors,had different upstream and downstream mechnisms among subtypes.STAT3 phosphorylation specifically activated the Notch signaling pathway in mesenchymal GBMs.The above study confirms our hypothesis that the subtype-related microenvironment lead to various intrinsic oncogenic mechanisms among subtypes.