Dataset Information

ERNAs Identify Immune Microenvironment Patterns and Provide a Novel Prognostic Tool in Acute Myeloid Leukemia.

ABSTRACT: Background: Enhancer RNAs (eRNAs) play an essential role in tumorigenesis as non-coding RNAs transcribed from enhancer regions. However, the landscape of eRNAs in acute myeloid leukemia (AML) and the potential roles of eRNAs in the tumor microenvironment (TME) remain unclear. Method: Gene expression data collected from The Cancer Genome Atlas (TCGA) project were combined with Histone ChIP-seq so as to reveal the comprehensive landscape of eRNAs. Single-sample gene set enrichment analysis algorithm (ssGSEA) and ESTIMATE were employed to enumerate immune cell infiltration and tumor purity. Results: Most prognostic eRNAs were enriched in immune-related pathways. Two distinct immune microenvironment patterns, the immune-active subtype and the immune-resistant subtype, were identified in AML. We further developed an eRNA-derived score (E-score) that could quantify immune microenvironment patterns and predict the response to immune checkpoint inhibitor (ICI) treatment. Finally, we established a prognostic nomogram combining E-score and other clinical features, which showed great discriminative power in both the training set [Harrell's concordance index (C index): 0.714 (0.651-0.777), p < 0.0001] and validation set [C index: 0.684 (0.614-0.755), p < 0.0001]. Calibration of the nomogram was also validated independently. Conclusion: In this study, we systematically understood the roles of eRNAs in regulating TME diversity and complexity. Moreover, our E-score model provided the first predictive model for ICI treatment in AML.

SUBMITTER: Jiang Z

PROVIDER: S-EPMC9108177 | biostudies-literature | 2022

REPOSITORIES: biostudies-literature

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eRNAs Identify Immune Microenvironment Patterns and Provide a Novel Prognostic Tool in Acute Myeloid Leukemia.

Jiang Ziming Z Long Junyu J Deng Kaige K Zheng Yongchang Y Chen Miao M

Frontiers in molecular biosciences 20220502

<b>Background:</b> Enhancer RNAs (eRNAs) play an essential role in tumorigenesis as non-coding RNAs transcribed from enhancer regions. However, the landscape of eRNAs in acute myeloid leukemia (AML) and the potential roles of eRNAs in the tumor microenvironment (TME) remain unclear. <b>Method:</b> Gene expression data collected from The Cancer Genome Atlas (TCGA) project were combined with Histone ChIP-seq so as to reveal the comprehensive landscape of eRNAs. Single-sample gene set enrichment an ...[more]

PMID: 35586193

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Project description:Simple Summary Despite remarkable progress in the outcome of childhood acute myeloid leukemia (AML), risk of relapse and refractory diseases remains high. Treatment of the chemo-refractory disease is restricted by dose-limiting therapy-related toxicities which necessitate alternative tolerable efficient therapeutic modalities. By disrupting its immune environment, leukemic blasts are known to gain the ability to evade immune surveillance and promote disease progression; therefore, many efforts have been made to redirect the immune system against malignant blasts. Deeper knowledge about immunologic alterations has paved the way to the discovery and development of novel targeted therapeutic concepts, which specifically override the immune evasion mechanisms to eradicate leukemic blasts. Herein, we review innovative immunotherapeutic strategies and their mechanisms of action in pediatric AML. Abstract Acute myeloid leukemia is a life-threatening malignant disorder arising in a complex and dysregulated microenvironment that, in part, promotes the leukemogenesis. Treatment of relapsed and refractory AML, despite the current overall success rates in management of pediatric AML, remains a challenge with limited options considering the heavy but unsuccessful pretreatments in these patients. For relapsed/refractory (R/R) patients, hematopoietic stem cell transplantation (HSCT) following ablative chemotherapy presents the only opportunity to cure AML. Even though in some cases immune-mediated graft-versus-leukemia (GvL) effect has been proven to efficiently eradicate leukemic blasts, the immune- and chemotherapy-related toxicities and adverse effects considerably restrict the feasibility and therapeutic power. Thus, immunotherapy presents a potent tool against acute leukemia but needs to be engineered to function more specifically and with decreased toxicity. To identify innovative immunotherapeutic approaches, sound knowledge concerning immune-evasive strategies of AML blasts and the clinical impact of an immune-privileged microenvironment is indispensable. Based on our knowledge to date, several promising immunotherapies are under clinical evaluation and further innovative approaches are on their way. In this review, we first focus on immunological dysregulations contributing to leukemogenesis and progression in AML. Second, we highlight the most promising therapeutic targets for redirecting the leukemic immunosuppressive microenvironment into a highly immunogenic environment again capable of anti-leukemic immune surveillance.

Project description:High-grade Gastroenteropancreatic Neuroendocrine neoplasms (H-NENs) comprehend well-differentiated tumors (NET G3) and poorly differentiated carcinomas (NEC) with proliferative activity indexes as mitotic count (MC) >20 mitoses/10 HPF and Ki-67 >20%. At present, no specific therapy for H-NENs exists and the several evidences of microenvironment involvement in their pathogenesis pave the way for tailored therapies. Forty-five consecutive cases, with available information about T-cell, immune, and non-immune markers, from surgical pathology and clinical databases of 2 Italian institutions were immunostained for Arginase, CD33, CD163 and CD66 myeloid markers. The association between features was assessed by Spearman's correlation coefficient. A unsupervised K-means algorithm was used to identify clusters of patients according to inputs of microenvironment features and the relationship between clusters and clinicopathological features, including cancer-specific survival (CSS), was analyzed. The H-NEN population was composed of 6 (13.3%) NET G3 and 39 (86.7%) NEC. Overall, significant positive associations were found between myeloid (CD33, CD163 and Arginase) and T/immune markers (CD3, CD4, CD8, PD-1 and HLA-I). Myeloid and T-cell markers CD3 and CD8 identified two clusters of patients from unsupervised K-means analysis. Cases grouped in cluster 1 with more myeloid infiltrates, T cell, HLA and expression of inhibitory receptors and ligands in the stroma (PD-1, PD-L1) had significantly better CSS than patients in cluster 2. Multivariable analysis showed that Ki-67 (>55 vs. <55, HR 8.60, CI 95% 2.61-28.33, p < 0.0001) and cluster (1 vs. 2, HR 0.43, CI 95% 0.20-0.93, p = 0.03) were significantly associated with survival. High grade gastroenteropancreatic neuroendocrine neoplasms can be further classified into two prognostic sub-populations of tumors driven by different tumor microenvironments and immune features able to generate the framework for evaluating new therapeutic strategies.

Project description:BackgroundThe high degree of heterogeneity brought great challenges to the diagnosis and treatment of acute myeloid leukemia (AML). Although several different AML prognostic scoring models have been proposed to assess the prognosis of patients, the accuracy still needs to be improved. As important components of the tumor microenvironment, immune cells played important roles in the physiological functions of tumors and had certain research value. Therefore, whether the tumor immune microenvironment (TIME) can be used to assess the prognosis of AML aroused our great interest.MethodsThe patients' gene expression profile from 7 GEO databases was normalized after removing the batch effect. TIME cell components were explored through Xcell tools and then hierarchically clustered to establish TIME classification. Subsequently, a prognostic model was established by Lasso-Cox. Multiple GEO databases and the Cancer Genome Atlas dataset were employed to validate the prognostic performance of the model. Receiver operating characteristic (ROC) and the concordance index (C-index) were utilized to assess the prognostic efficacy.ResultsAfter analyzing the composition of TIME cells in AML, we found infiltration of ten types of cells with prognostic significance. Then using hierarchical clustering methods, we established a TIME classification system, which clustered all patients into three groups with distinct prognostic characteristics. Using the differential genes between the first and third groups in the TIME classification, we constructed a 121-gene prognostic model. The model successfully divided 1229 patients into the low and high groups which had obvious differences in prognosis. The high group with shorter overall survival had more patients older than 60 years and more poor-risk patients (both P< 0.001). Besides, the model can perform well in multiple datasets and could further stratify the cytogenetically normal AML patients and intermediate-risk AML population. Compared with the European Leukemia Net Risk Stratification System and other AML prognostic models, our model had the highest C-index and the largest AUC of the ROC curve, which demonstrated that our model had the best prognostic efficacy.ConclusionA prognostic model for AML based on the TIME classification was constructed in our study, which may provide a new strategy for precision treatment in AML.

Project description:IntroductionAcute myeloid leukemia (AML) is an aggressive blood cancer with high heterogeneity and poor prognosis. Although the metabolic reprogramming of nicotinamide adenine dinucleotide (NAD) has been reported to play a pivotal role in the pathogenesis of acute myeloid leukemia (AML), the prognostic value of NAD metabolism and its correlation with the immune microenvironment in AML remains unclear.MethodsWe utilized our large-scale RNA-seq data on 655 patients with AML and the NAD metabolism-related genes to establish a prognostic NAD metabolism score based on the sparse regression analysis. The signature was validated across three independent datasets including a total of 1,215 AML patients. ssGSEA and ESTIMATE algorithms were employed to dissect the tumor immune microenvironment. Ex vivo drug screening and in vitro experimental validation were performed to identify potential therapeutic approaches for the high-risk patients. In vitro knockdown and functional experiments were employed to investigate the role of SLC25A51, a mitochondrial NAD+ transporter gene implicated in the signature.ResultsAn 8-gene NAD metabolism signature (NADM8) was generated and demonstrated a robust prognostic value in more than 1,800 patients with AML. High NADM8 score could efficiently discriminate AML patients with adverse clinical characteristics and genetic lesions and serve as an independent factor predicting a poor prognosis. Immune microenvironment analysis revealed significant enrichment of distinct tumor-infiltrating immune cells and activation of immune checkpoints in patients with high NADM8 scores, acting as a potential biomarker for immune response evaluation in AML. Furthermore, ex vivo drug screening and in vitro experimental validation in a panel of 9 AML cell lines demonstrated that the patients with high NADM8 scores were more sensitive to the PI3K inhibitor, GDC-0914. Finally, functional experiments also substantiated the critical pathogenic role of the SLC25A51 in AML, which could be a promising therapeutic target.ConclusionOur study demonstrated that NAD metabolism-related signature can facilitate risk stratification and prognosis prediction in AML and guide therapeutic decisions including both immunotherapy and targeted therapies.

Dataset Information

ERNAs Identify Immune Microenvironment Patterns and Provide a Novel Prognostic Tool in Acute Myeloid Leukemia.

Publications

eRNAs Identify Immune Microenvironment Patterns and Provide a Novel Prognostic Tool in Acute Myeloid Leukemia.

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