Comprehensive Analysis of Genome-instability Related lncRNAs and Tumor-immune Microenvironment to Discriminate the Prognosis, Immunotherapy and PARP Inhibitor Responses in Patients with Low-grade Glioma

2021 ◽  
Author(s):  
Zijian Zhou ◽  
Bin Lu ◽  
JinHong Wei ◽  
Lei Guo ◽  
ZhongMing He ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Risk Model ◽  
Genome Instability ◽  
Parp Inhibitor ◽  
Comprehensive Analysis ◽  
Low Grade Glioma ◽  
Therapeutic Effects ◽  
Low Grade ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment

Abstract Background: Previous study revealed that Genome-instability was correlated with tumor-immune microenvironment in cancer. We try to discriminate the prognosis, immunotherapy and poly (ADP)-ribose polymerase (PARP) inhibitor responses through comprehensive analysis of genome-instability related lncRNAs and the tumor-immune microenvironment in patients with low-grade glioma (LGG). Methods and Results: RNAseq data, genome variation profiling data and copy number variation (CNV) data were used to evaluate the genomic instability of LGG patients. Genomic unstable-like (GU-like) and genomic stable-like (GS-like) clusters were identified by hierarchical clustering analysis of 102 genome-instability related lncRNAs (GILncRNAs). GS-like cluster had a tendency to receive better clinical outcome. Patients in GU-like cluster were more likely to respond to immunotherapy, especially anti-PD-1/PD-L1 treatment. PARP inhibitors including Rucaparib and Olaparib will get better therapeutic effects for patients in GU-like cluster. Lasso and Cox regression analysis were utilized to construct the risk model based on GILncRNAs. As for the risk model constructed by 9 GILncRNAs, the overall survival, clinical outcome, immunotherapeutic response, and PARP inhibitor sensitivity were significantly different between patients of high and low-risk groups. Conclusions: The genome-instability related lncRNAs signature involved in our risk model had great advantages in predicting prognosis, immunotherapy and PARP inhibitor response.

scholarly journals RNA N6-Methyladenosine Regulators Contribute to Tumor Immune Microenvironment and Have Clinical Prognostic Impact in Breast Cancer

2022 ◽  
Vol 12 ◽  
Author(s):  
Lan-Xin Mu ◽  
You-Cheng Shao ◽  
Lei Wei ◽  
Fang-Fang Chen ◽  
Jing-Wei Zhang
Keyword(s):  
Breast Cancer ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Gene Set Enrichment Analysis ◽  
The Cancer Genome Atlas ◽  
Prognostic Impact ◽  
Immune Microenvironment ◽  
Model Based ◽  
Tumor Immune Microenvironment

Purpose: This study aims to reveal the relationship between RNA N6-methyladenosine (m6A) regulators and tumor immune microenvironment (TME) in breast cancer, and to establish a risk model for predicting the occurrence and development of tumors.Patients and methods: In the present study, we respectively downloaded the transcriptome dataset of breast cancer from Gene Expression Omnibus (GEO) database and The Cancer Genome Atlas (TCGA) database to analyze the mutation characteristics of m6A regulators and their expression profile in different clinicopathological groups. Then we used the weighted correlation network analysis (WGCNA), the least absolute shrinkage and selection operator (LASSO), and cox regression to construct a risk prediction model based on m6A-associated hub genes. In addition, Immune infiltration analysis and gene set enrichment analysis (GSEA) was used to evaluate the immune cell context and the enriched gene sets among the subgroups.Results: Compared with adjacent normal tissue, differentially expressed 24 m6A regulators were identified in breast cancer. According to the expression features of m6A regulators above, we established two subgroups of breast cancer, which were also surprisingly distinguished by the feature of the immune microenvironment. The Model based on modification patterns of m6A regulators could predict the patient’s T stage and evaluate their prognosis. Besides, the low m6aRiskscore group presents an immune-activated phenotype as well as a lower tumor mutation load, and its 5-years survival rate was 90.5%, while that of the high m6ariskscore group was only 74.1%. Finally, the cohort confirmed that age (p < 0.001) and m6aRiskscore (p < 0.001) are both risk factors for breast cancer in the multivariate regression.Conclusion: The m6A regulators play an important role in the regulation of breast tumor immune microenvironment and is helpful to provide guidance for clinical immunotherapy.

Comprehensive analysis of CTLA-4 in the tumor immune microenvironment of 33 cancer types

2020 ◽  
Vol 85 ◽  
pp. 106633
Author(s):  
Chufan Zhang ◽  
Jianing Chen ◽  
Qian Song ◽  
Xiaoyan Sun ◽  
Meijuan Xue ◽  
...  
Keyword(s):  
Comprehensive Analysis ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Cancer Types

scholarly journals PEDT-02 DIAGNOSIS, TREATMENT AND CLINICAL OUTCOME OF ATYPICAL BRAINSTEM TUMOUR IN CHILDHOOD

2019 ◽  
Vol 1 (Supplement_2) ◽  
pp. ii16-ii16
Author(s):  
Takaaki Yanagisawa ◽  
Takaya Honda ◽  
Masatada Yamaoka ◽  
Masaharu Akiyama ◽  
Kohei Fukuoka ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Survival Data ◽  
Treatment Strategy ◽  
Retrospective Chart Review ◽  
Malignant Tumour ◽  
Diffuse Intrinsic Pontine Glioma ◽  
Clinical Findings ◽  
Low Grade Glioma ◽  
Pathological Diagnosis ◽  
Low Grade

Abstract BACKGROUND Brainstem tumours account for 10–15% of brain tumors in childhood. Diffuse intrinsic pontine glioma (DIPG) accounts for 60–80% of them and are diagnosed based on clinical findings and radiologic features. All the rest of tumours excluding DIPG are very rare, heterogeneous group of tumours including low-grade glioma and malignant embryonal tumors. It is often difficult to diagnose and decide treatment strategy for their rarity. METHODS To present our experience with atypical brainstem tumours, a retrospective chart review was conducted to identify eligible cases treated over a ten-year period. All tumors involving brainstem, felt not to be DIPGs for absence of clinical/neuroimaging features were included. Demographic information, pathological findings, neuroimaging characteristics, surgical and nonsurgical management plans, and survival data were collected for analysis. RESULTS Between April 2007 and March 2017, 16 patients (14 initial and 2 recurrent) aged from 3 to 20 years were identified. 14 of them were symptomatic and 4 of them were asymptomatic at reference. Of 10 symptomatic cases, 10 were biopsied and pathological diagnosis was low-grade glioma in 8, glioblastoma in 2 cases. They had treatment depending on the pathological diagnosis. Of 4 asymptomatic cases, one with small focal tumour, with no findings suggesting malignant tumour with 11C-methioninePET or MRS, progressed to show typical clinical and image findings of DIPG in a year. For other three, they remain asymptomatic without progression with no treatment for 25months, 60months, and 65 months respectively. Malignant transformation was observed in one with biopsy-conformed oligoastrocytoma with no K27M-H3 mutations treated with chemotherapy and another with pilocytic astrocytoma treated with chemotherapy and radiotherapy. CONCLUSIONS Though molecular findings such as K27M-H3 mutations can predict clinical outcome in some cases, it still remains difficult to diagnose and find treatment strategy of atypical brainstem tumours. The need and usefulness of nationwide registry study is warranted.

scholarly journals Integrated analysis of microbiome and host transcriptome reveals correlations between gut microbiota and clinical outcomes in HBV-related hepatocellular carcinoma

2020 ◽  
Vol 12 (1) ◽  
Author(s):  
Hechen Huang ◽  
Zhigang Ren ◽  
Xingxing Gao ◽  
Xiaoyi Hu ◽  
Yuan Zhou ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Clinical Outcome ◽  
Gut Microbiota ◽  
Bile Acids ◽  
Clinical Characteristics ◽  
Tumor Burden ◽  
Support Vector ◽  
Immune Microenvironment ◽  
Serum Bile Acids ◽  
Tumor Immune Microenvironment

Abstract Background The gut-liver axis plays a pivotal role in the pathogenesis of hepatocellular carcinoma (HCC). However, the correlations between the gut microbiome and the liver tumor transcriptome in patients with HCC and the impact of the gut microbiota on clinical outcome are less well-understood. Methods Fecal samples collected from HBV-related HCC patients (n = 113) and healthy volunteers (n = 100) were subjected to 16S rRNA sequencing of the microbiome. After a rigorous selection process, 32 paired tumor and adjacent non-tumor liver tissues from the HCC group were subjected to next-generation sequencing (NGS) RNA-seq. The datasets were analyzed individually and integrated with clinical characteristics for combined analysis using bioinformatics approaches. We further verified the potential of the gut microbiota to predict clinical outcome by a random forest model and a support vector machine model. Results We found that Bacteroides, Lachnospiracea incertae sedis, and Clostridium XIVa were enriched in HCC patients with a high tumor burden. By integrating the microbiome and transcriptome, we identified 31 robust associations between the above three genera and well-characterized genes, indicating possible mechanistic relationships in tumor immune microenvironment. Clinical characteristics and database analysis suggested that serum bile acids may be important communication mediators between these three genera and the host transcriptome. Finally, among these three genera, six important microbial markers associated with tumor immune microenvironment or bile acid metabolism showed the potential to predict clinical outcome (AUC = 81%). Conclusions This study revealed that changes in tumor immune microenvironment caused by the gut microbiota via serum bile acids may be important factors associated with tumor burden and adverse clinical outcome. Gut microbes can be used as biomarkers of clinical features and outcomes, and the microbe-associated transcripts of host tumors can partly explain how gut microbiota promotes HCC pathogenesis.

scholarly journals Comprehensive Analysis of Inflammatory Response–Related Genes, and Prognosis and Immune Infiltration in Patients With Low-Grade Glioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Tao Han ◽  
Zhifan Zuo ◽  
Meilin Qu ◽  
Yinghui Zhou ◽  
Qing Li ◽  
...  
Keyword(s):  
Regression Analysis ◽  
High Risk ◽  
Immune Cell ◽  
Risk Model ◽  
Cox Regression ◽  
Risk Group ◽  
High Risk Group ◽  
Low Grade ◽  
Immune Microenvironment ◽  
Cox Regression Analysis

Background: Although low-grade glioma (LGG) has a good prognosis, it is prone to malignant transformation into high-grade glioma. It has been confirmed that the characteristics of inflammatory factors and immune microenvironment are closely related to the occurrence and development of tumors. It is necessary to clarify the role of inflammatory genes and immune infiltration in LGG.Methods: We downloaded the transcriptome gene expression data and corresponding clinical data of LGG patients from the TCGA and GTEX databases to screen prognosis-related differentially expressed inflammatory genes with the difference analysis and single-factor Cox regression analysis. The prognostic risk model was constructed by LASSO Cox regression analysis, which enables us to compare the overall survival rate of high- and low-risk groups in the model by Kaplan–Meier analysis and subsequently draw the risk curve and survival status diagram. We analyzed the accuracy of the prediction model via ROC curves and performed GSEA enrichment analysis. The ssGSEA algorithm was used to calculate the score of immune cell infiltration and the activity of immune-related pathways. The CellMiner database was used to study drug sensitivity.Results: In this study, 3 genes (CALCRL, MMP14, and SELL) were selected from 9 prognosis-related differential inflammation genes through LASSO Cox regression analysis to construct a prognostic risk model. Further analysis showed that the risk score was negatively correlated with the prognosis, and the ROC curve showed that the accuracy of the model was better. The age, grade, and risk score can be used as independent prognostic factors (p < 0.001). GSEA analysis confirmed that 6 immune-related pathways were enriched in the high-risk group. We found that the degree of infiltration of 12 immune cell subpopulations and the scores of 13 immune functions and pathways in the high-risk group were significantly increased by applying the ssGSEA method (p < 0.05). Finally, we explored the relationship between the genes in the model and the susceptibility of drugs.Conclusion: This study analyzed the correlation between the inflammation-related risk model and the immune microenvironment. It is expected to provide a reference for the screening of LGG prognostic markers and the evaluation of immune response.

scholarly journals Inherited defects in natural killer cells shape tumor immune microenvironment, clinical outcome and immunotherapy response

2018 ◽  
Author(s):  
Xue Xu ◽  
Jianqiang Li ◽  
Jinfeng Zou ◽  
Xiaowen Feng ◽  
Chao Zhang ◽  
...  
Keyword(s):  
Clinical Outcome ◽  
Nk Cells ◽  
Natural Killer ◽  
Antigen Processing ◽  
Cell Activation ◽  
Nk Cell ◽  
Tumor Infiltrating Lymphocytes ◽  
Immune Microenvironment ◽  
Tumor Immune Microenvironment ◽  
Cancer Types

AbstractTumor immune microenvironment (TIME) plays an important role in metastasis and immunotherapy. However, it has been not much known how to classify TIMEs and how TIMEs are genetically regulated. Here we showed that tumors were classified into TIME-rich, -intermediate and -poor subtypes which had significant differences in clinical outcomes, abundances of tumor-infiltrating lymphocytes (TILs), the degree of key immune programs’ activation, and immunotherapy response across 13 common cancer types (n= ∼6,000). Furthermore, TIME-intermediate/-poor patients had significantly more inherited genetic defects (i.e., functional germline variants) in natural killer (NK) cells, antigen processing and presentation (APP) and Wnt signaling pathways than TIME-rich patients, and so did cancer patients than non-cancer individuals (n=4,500). These results suggested that individuals who had more inherited defects in NK cells, APP and Wnt pathways had a higher risk of developing cancers. Moreover, in the 13 common cancers the number of inheritably defected genes of NK cells was significantly negative-correlated with patients’ survival, TILs’ abundance in TIMEs and immunotherapy response, suggesting that inherited defects in NK cells alone were sufficient to shape TILs’ recruitment, clinical outcome, and immunotherapy response, highlighting that NK cell activation was required in the 13 cancer types to drive the recruitment of immune troops into TIMEs. Thus, we proposed that cancer was a disease of NK cell inherited deficiencies. These results had implications in identifying of high-risk individuals based on germline genomes, implementing precision cancer prevention by adoptive transfer of healthy NK cells, and improving existing immunotherapies by combining of adoptive NK cell transfer (i.e., converting TIME-intermediate/-poor tumors into TIME-rich tumors) and anti-PD-1 or CAR-T therapy.ContactEW ([email protected])

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