Mutational profiling of low-grade gliomas identifies prognosis and immunotherapy-related biomarkers and tumour immune microenvironment characteristics.
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ABSTRACT:
SUBMITTER: Lin WW
PROVIDER: S-EPMC8572778 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundImmunogenic cell death (ICD) is a form of cell death that elicits immune responses against the antigens found in dead or dying tumor cells. Growing evidence implies that ICD plays a significant role in triggering antitumor immunity. The prognosis for glioma remains poor despite many biomarkers being reported, and identifying ICD-related biomarkers is imminent for better-personalized management in patients with lower-grade glioma (LGG).Materials and methodsWe identified ICD-related differentially expressed genes (DEGs) by comparing gene expression profiles obtained across Genotype-Tissue Expression (GTEx) and The Cancer Genome Atlas (TCGA) cohorts. On the foundation of ICD-related DEGs, two ICD-related clusters were identified through consensus clustering. Then, survival analysis, functional enrichment analysis, somatic mutation analysis, and immune characteristics analysis were performed in the two ICD-related subtypes. Additionally, we developed and validated a risk assessment signature for LGG patients. Finally, we selected one gene (EIF2AK3) from the above risk model for experimental validation.Results32 ICD-related DEGs were screened, dividing the LGG samples from the TCGA database into two distinct subtypes. The ICD-high subgroup showed worse overall survival (OS), greater immune infiltration, more active immune response process, and higher expression levels of HLA genes than the ICD-low subgroup. Additionally, nine ICD-related DEGs were identified to build the prognostic signature, which was highly correlated with the tumor-immune microenvironment and could unambiguously be taken as an independent prognostic factor and further verified in an external dataset. The experimental results indicated that EIF2AK3 expression was higher in tumors than paracancerous tissues, and high-expression EIF2AK3 was enriched in WHO III and IV gliomas by qPCR and IHC, and Knockdown of EIF2AK3 suppressed cell viability and mobility in glioma cells.ConclusionWe established novel ICD-related subtypes and risk signature for LGG, which may be beneficial to improving clinical outcome prediction and guiding individualized immunotherapy.
| S-EPMC10154552 | biostudies-literature
Project description:The preclinical and clinical development of novel immunotherapies for the treatment of central nervous system (CNS) tumors is advancing at a rapid pace. High-grade gliomas (HGG) are aggressive tumors with poor prognoses in both adult and pediatric patients, and innovative and effective therapies are greatly needed. The use of cytotoxic chemotherapies has marginally improved survival in some HGG patient populations. Although several challenges exist for the successful development of immunotherapies for CNS tumors, recent insights into the genetic alterations that define the pathogenesis of HGG and their direct effects on the tumor microenvironment (TME) may allow for a more refined and targeted therapeutic approach. This review will focus on the TME in HGG, the genetic drivers frequently found in these tumors and their effect on the TME, the development of immunotherapy for HGG, and the practical challenges in clinical trials employing immunotherapy for HGG. Herein, we will discuss broadly the TME and immunotherapy development in HGG, with a specific focus on glioblastoma multiforme (GBM) as well as additional discussion in the context of the pediatric HGG diagnoses of diffuse midline glioma (DMG) and diffuse hemispheric glioma (DHG).
| S-EPMC9515652 | biostudies-literature
Project description:Currently, there is no strong evidence of the well-established biomarkers for immune checkpoint inhibitors (ICIs) in nasopharyngeal carcinoma (NPC). Here, we aimed to reveal the heterogeneity of tumour microenvironment (TME) through virtual microdissection of gene expression profiles. An immune-enriched subtype was identified in 38% (43/113) of patients, which was characterized by significant enrichment of immune cells or immune responses. The remaining patients were therefore classified as a non-Immune Subtype (non-IS), which exhibited highly proliferative features. Then we identified a tumour immune evasion state within the immune-enriched subtype (18/43, 42%), in which high expression of exclusion- and dysfunction-related signatures was observed. These subgroups were designated the Evaded and Active Immune Subtype (E-IS and A-IS), respectively. We further demonstrated that A-IS predicted favourable survival and improved ICI response as compared to E-IS and non-IS. In summary, this study introduces the novel immune subtypes and demonstrates their feasibility in tailoring immunotherapeutic strategies.
| S-EPMC7798236 | biostudies-literature
Project description:Despite a generally better prognosis than high-grade glioma (HGG), recurrence and malignant progression are the main causes for the poor prognosis and difficulties in the treatment of low-grade glioma (LGG). It is of great importance to learn about the risk factors and underlying mechanisms of LGG recurrence and progression. In this study, the transcriptome characteristics of four groups, namely, normal brain tissue and recurrent LGG (rLGG), normal brain tissue and secondary glioblastoma (sGBM), primary LGG (pLGG) and rLGG, and pLGG and sGBM, were compared using Chinese Glioma Genome Atlas (CGGA) and Genotype-Tissue Expression Project (GTEx) databases. In this study, 296 downregulated and 396 upregulated differentially expressed genes (DEGs) with high consensus were screened out. Univariate Cox regression analysis of data from The Cancer Genome Atlas (TCGA) yielded 86 prognostically relevant DEGs; a prognostic prediction model based on five key genes (HOXA1, KIF18A, FAM133A, HGF, and MN1) was established using the least absolute shrinkage and selection operator (LASSO) regression dimensionality reduction and multivariate Cox regression analysis. LGG was divided into high- and low-risk groups using this prediction model. Gene Set Enrichment Analysis (GSEA) revealed that signaling pathway differences in the high- and low-risk groups were mainly seen in tumor immune regulation and DNA damage-related cell cycle checkpoints. Furthermore, the infiltration of immune cells in the high- and low-risk groups was analyzed, which indicated a stronger infiltration of immune cells in the high-risk group than that in the low-risk group, suggesting that an immune microenvironment more conducive to tumor growth emerged due to the interaction between tumor and immune cells. The tumor mutational burden and tumor methylation burden in the high- and low-risk groups were also analyzed, which indicated higher gene mutation burden and lower DNA methylation level in the high-risk group, suggesting that with the accumulation of genomic mutations and epigenetic changes, tumor cells continued to evolve and led to the progression of LGG to HGG. Finally, the value of potential therapeutic targets for the five key genes was analyzed, and findings demonstrated that KIF18A was the gene most likely to be a potential therapeutic target. In conclusion, the prediction model based on these five key genes can better identify the high- and low-risk groups of LGG and lay a solid foundation for evaluating the risk of LGG recurrence and malignant progression.
| S-EPMC9168984 | biostudies-literature
Project description:Lower-grade gliomas (LrGG), characterized by invasiveness and heterogeneity, remain incurable with current therapies. Clinicopathological features provide insufficient information to guide optimal individual treatment and cannot predict prognosis completely. Recently, an increasing amount of studies indicate that the tumor microenvironment plays a pivotal role in tumor malignancy and treatment responses. However, studies focusing on the tumor microenvironment (TME) of LrGG are still limited. In this study, taking advantage of the currently popular computational methods for estimating the infiltration of tumor-associated normal cells in tumor samples and using weighted gene co-expression network analysis, we screened the co-expressed gene modules associated with the TME and further identified the prognostic hub genes in these modules. Furthermore, eight prognostic hub genes (ARHGDIB, CLIC1, OAS3, PDIA4, PARP9, STAT1, TAP2, and TAGLN2) were selected to construct a prognostic risk score model using the least absolute shrinkage and selection operator method. Univariate and multivariate Cox regression analysis demonstrated that the risk score was an independent prognostic factor for LrGG. Moreover, time-dependent ROC curves indicated that our model had favorable efficiency in predicting both short- and long-term prognosis in LrGG patients, and the stratified survival analysis demonstrated that our model had prognostic value for different subgroups of LrGG patients. Additionally, our model had potential value for predicting the sensitivity of LrGG patients to radio- and chemotherapy. Besides, differential expression analysis showed that the eight genes were aberrantly expressed in LrGG compared to normal brain tissue. Correlation analysis revealed that the expression of the eight genes was significantly associated with the infiltration levels of six types of immune cells in LrGG. In summary, the TME-related eight-gene signature was significantly associated with the prognosis of LrGG patients. They might act as potential prognostic biomarkers for LrGG patients, offer better stratification for future clinical trials, and be candidate targets for immunotherapy, thus deserving further investigation.
| S-EPMC6872675 | biostudies-literature
Project description:BackgroundThe tumor microenvironment (TME) involves infiltration of multiple immune cell subsets, which could influence the prognosis and clinical characteristics. The increasing evidence on the role of tumor-infiltrating lymphocytes (TILs) in primary and metastatic melanomas supports that the immune system is involved in the progression and outcomes of melanoma. However, the immune infiltration landscape in melanoma has not been systematically elucidated.MethodsIn this study, we used CIBERSORT and ESTIMATE algorithms to analyze immune infiltration pattern of 993 melanoma samples. Then we screened differential expression genes (DEGs) related to immune subtypes and survival. The immune cell infiltration (ICI) score was constructed by using principal-component analysis (PCA) based on immune signature genes from DGEs. Gene set enrichment analysis (GSEA) was applied to explore high and low ICI score related pathways. Finally, the predictive ability of ICI score was evaluated in survival prognosis and immunotherapy benefit.ResultWe identified three ICI clusters and three gene clusters associated with different immune subtypes and survival outcomes. Then the ICI score was constructed, and we found that high ICI score exhibited activated immune characteristics and better prognosis. High ICI score was significantly enriched in immune pathways and highly expressed immune signature genes. More importantly, we confirmed that melanoma patients with high ICI score had longer overall survival and rate of response to immunotherapy.ConclusionWe presented a comprehensive immune infiltration landscape in melanoma. Our results will facilitate understanding of the melanoma tumor microenvironment and provide a new immune therapy strategy.
| S-EPMC8134682 | biostudies-literature
Project description:Tumor microenvironment and alternative polyadenylation (APA) have drawn more attention in cancer research. However, their roles in grade II and III gliomas, termed as lower-grade glioma (LGG) in this study, remain to be fully elucidated. Here, we conducted this study and found that stromal and immune scores were elevated in higher grade and isocitrate dehydrogenase (IDH) wild-type glioma. Besides, higher stromal and immune scores indicated a poor prognosis in patients with LGG. APA events in immune-related genes were associated with overall survival, RNA expression, IDH mutation, and disease-free survival. Patients in the high-risk group had poor prognoses, and the risk score could be used to predict the survival rate. The risk score was positively correlated with the expression of immune checkpoints, inflammatory cytokines, and infiltrated immune cells. Moreover, risk stratification could predict the efficacy of radiotherapy and provide a reference for the treatment of grade III glioma. Our study revealed that immune-related genes with APA events in the microenvironment could predict risk stratification and clinical prognosis in patients with LGG.
| S-EPMC7900014 | biostudies-literature
Project description:The tumour microenvironment is an important factor for colorectal cancer prognosis, affecting the patient's immune response. Immune checkpoints, which regulate the immune functions of lymphocytes, may provide prognostic power. This study aimed to investigate the prognostic value of the immune checkpoints TIM-3, LAG-3 and PD-1 in patients with stage I-III colorectal cancer. Immunohistochemistry was employed to detect TIM-3, LAG-3, PD-1 and PD-L1 in 773 patients with stage I-III colorectal cancer. Immune checkpoint protein expression was assessed in tumour cells using the weighted histoscore, and in immune cells within the stroma using point counting. Scores were analysed for associations with survival and clinical factors. High tumoural LAG-3 (hazard ratio [HR] 1.45 95% confidence interval [CI] 1.00-2.09, p =?0.049) and PD-1 (HR 1.34 95% CI 1.00-1.78, p =?0.047) associated with poor survival, whereas high TIM-3 (HR 0.60 95% CI 0.42-0.84, p =?0.003), LAG-3 (HR 0.58 95% CI 0.40-0.87, p =?0.006) and PD-1 (HR 0.65 95% CI 0.49-0.86, p =?0.002) on immune cells within the stroma associated with improved survival, while PD-L1 in the tumour (p =?0.487) or the immune cells within the stroma (p =?0.298) was not associated with survival. Furthermore, immune cell LAG-3 was independently associated with survival (p =?0.017). Checkpoint expression scores on stromal immune cells were combined into a Combined Immune Checkpoint Stromal Score (CICSS), where CICSS 3 denoted all high, CICSS 2 denoted any two high, and CICSS 1 denoted other combinations. CICSS 3 was associated with improved patient survival (HR 0.57 95% CI 0.42-0.78, p =?0.001). The results suggest that individual and combined high expression of TIM-3, LAG-3, and PD-1 on stromal immune cells are associated with better colorectal cancer prognosis, suggesting there is added value to investigating multiple immune checkpoints simultaneously.
| S-EPMC7869939 | biostudies-literature
Project description:Gliomas, a type of primary brain tumor, have emerged as a threat to global mortality due to their high heterogeneity and mortality. A low-grade glioma (LGG), although less aggressive compared with glioblastoma, still exhibits high recurrence and malignant progression. Ubiquitination is one of the most important posttranslational modifications that contribute to carcinogenesis and cancer recurrence. E3-related genes (E3RGs) play essential roles in the process of ubiquitination. Yet, the biological function and clinical significance of E3RGs in LGGs need further exploration. In this study, differentially expressed genes (DEGs) were screened by three differential expression analyses of LGG samples from The Cancer Genome Atlas (TCGA) database. DEGs with prognostic significance were selected by the univariate Cox regression analysis and log-rank statistical test. The LASSO-COX method was performed to identify an E3-related prognostic signature consisting of seven genes AURKA, PCGF2, MAP3K1, TRIM34, PRKN, TLE3, and TRIM17. The Chinese Glioma Genome Atlas (CGGA) dataset was used as the validation cohort. Kaplan-Meier survival analysis showed that LGG patients in the low-risk group had significantly higher overall survival time than those in the high-risk group in both TCGA and CGGA cohorts. Furthermore, multivariate Cox regression analysis revealed that the E3RG signature could be used as an independent prognostic factor. A nomogram based on the E3RG signature was then established and provided the prediction of the 1-, 3-, and 5-year survival probability of patients with LGGs. Moreover, DEGs were analyzed based on the risk signature, on which function analyses were performed. GO and KEGG analyses uncovered gene enrichment in extracellular matrix-related functions and immune-related biological processes in the high-risk group. GSEA revealed high enrichment in pathways that promote tumorigenesis and progression in the high-risk group. Furthermore, ESTIMATE algorithm analysis showed a significant difference in immune and stroma activity between high- and low-risk groups. Positive correlations between the risk signature and the tumor microenvironment immune cell infiltration and immune checkpoint molecules were also observed, implying that patients with the high-risk score may have better responses to immunotherapy. Overall, our findings might provide potential diagnostic and prognostic markers for LGG patients and offer meaningful insight for individualized treatment.
| S-EPMC9271851 | biostudies-literature
Project description:BackgroundTransient Receptor Potential (TRP) channel is a kind of channel protein widely distributed in peripheral and central nervous system. They can be regulated by natural aromatic substances and serve as a therapeutic target for many diseases. However, the role and function of the TRP family genes in tumours remain unclear.MethodsGene alterations (mutation, copy number, methylation), expression, clinical features, and prognostic value of the TRP family genes were evaluated in pan-cancer using data from The Cancer Genome Atlas and Genotype-Tissue Expression databases. TRP score was calculated by the ssGSEA function of the R package "GSVA". The association of TRP score and the tumour microenvironment (TME), especially the tumour immune microenvironment (TIME), along with immunotherapy response were explored in-depth.ResultsTRP family genes were involved in tumour progression and highly associated with poor prognosis in a variety of cancers. TRP score was positively associated with malignant pathways in pan-cancer, such as IL6-JAK-STAT3 signalling, interferon-gamma response, and inflammatory response. All pathways were closely associated with TIME. Elevated TRP score also correlated with multiple immune-related characteristics of the TIME in pan-cancer. Moreover, the TRP score was a predictive biomarker for immune checkpoint inhibitor (ICI) treatments in patients with tumours.ConclusionsTRP family genes play a key role in pan-cancer and are closely associated with TME. Patients with high TRP scores have excellent immune-activated TIME and immunotherapy sensitivity. Therefore, the TRP score could be a potential biomarker for patients with tumours treated with ICI.
| S-EPMC9043495 | biostudies-literature