Long non-coding RNA-based signatures to improve prognostic prediction of breast cancer

Zhang, Yi; Wang, Yuzhi; Tian, Gang; Jiang, Tianhua

doi:10.1097/md.0000000000022203

Cited by 5 publications

(7 citation statements)

References 36 publications

(33 reference statements)

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“…Time-dependent ROC curve analysis of our signature's ability to predict 3and 5-years RFS yielded AUC values of 0.815 and 0.765, respectively. These values were comparable to those reported for 9-TF [10] AGING and 12-lncRNA [11] signatures, and superior in turn to the AUC values of another four signatures [12][13][14][15].…”

Section: Comparison With Other Prognostic Signaturessupporting

confidence: 85%

Identification and validation of a robust autophagy-related molecular model for predicting the prognosis of breast cancer patients

Liu

et al. 2021

Aging

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Despite a relatively low mortality rate, high recurrence rates represent a significant problem for breast cancer (BC) patients. Autophagy affects the development, progression, and prognosis of various cancers, including BC. The aim of the present study was to identify candidate autophagy-related genes (ARGs) and construct a molecular-clinicopathological signature to predict recurrence risk in BC. A 10-ARG-based signature was established in a training cohort (GEO-BC dataset GSE25066) with LASSO Cox regression and assessed in an independent validation cohort (GEO-BC GSE22219). Significant differences in recurrence-free survival were observed for high-and low-risk patients segregated based on their signature-based risk score. Time-dependent receiver operating characteristic (tdROC) analysis of signature performance demonstrated satisfactory accuracy and predictive power in both the training and validation cohorts. Moreover, we developed a nomogram to predict 3-and 5-year recurrence-free survival by combining the autophagy-related risk score and clinicopathological data. Both the tdROC and calibration curves indicated high discriminating ability for the nomogram. This study indicates that our ARG-based signature is an independent prognostic classifier for recurrence-free survival in BC. In addition, individualized survival risk assessment and treatment decisions might be effectively improved by implementing the proposed nomogram.

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Section: Comparison With Other Prognostic Signaturessupporting

confidence: 85%

Identification and validation of a robust autophagy-related molecular model for predicting the prognosis of breast cancer patients

Liu

et al. 2021

Aging

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“…However, due to the asymptomatic early stages, BC is often diagnosed in the advanced stages, leading to serious outcomes. Early diagnosis and intervention are important for favorable outcomes 4 . Based on genomic and transcriptomic sequences, BC can be allocated into five inherent molecular subtypes, including Luminal A/B, HER-2 enriched, Basal-like and Claudin-low 5 .…”

Section: Introductionmentioning

confidence: 99%

The role of ferroptosis in breast cancer patients: a comprehensive analysis

Tang

et al. 2021

Cell Death Discov.

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Breast cancer (BC) affects the breast tissue and is the second most common cause of mortalities among women. Ferroptosis is an iron-dependent cell death mode that is characterized by intracellular accumulation of reactive oxygen species (ROS). We constructed a prognostic multigene signature based on ferroptosis-associated differentially expressed genes (DEGs). Moreover, we comprehensively analyzed the role of ferroptosis-associated miRNAs, lncRNAs, and immune responses. A total of 259 ferroptosis-related genes were extracted. KEGG function analysis of these genes revealed that they were mainly enriched in the HIF-1 signaling pathway, NOD-like receptor signaling pathway, central carbon metabolism in cancer, and PPAR signaling pathway. Fifteen differentially expressed genes (ALOX15, ALOX15B, ANO6, BRD4, CISD1, DRD5, FLT3, G6PD, IFNG, NGB, NOS2, PROM2, SLC1A4, SLC38A1, and TP63) were selected as independent prognostic factors for BC patients. Moreover, T cell functions, including the CCR score, immune checkpoint, cytolytic activity, HLA, inflammation promotion, para-inflammation, T cell co-stimulation, T cell co-inhibition, and type II INF responses were significantly different between the low-risk and high-risk groups of the TCGA cohort. Immune checkpoints between the two groups revealed that the expressions of PDCD-1 (PD-1), CTLA4, LAG3, TNFSF4/14, TNFRSF4/8/9/14/18/25, and IDO1/2 among others were significantly different. A total of 1185 ferroptosis-related lncRNAs and 219 ferroptosis-related miRNAs were also included in this study. From the online database, we identified novel ferroptosis-related biomarkers for breast cancer prognosis. The findings of this study provide new insights into the development of new reliable and accurate cancer treatment options.

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“…With the same method, and highlighting the importance of the tumor immunology, eight immune-related lncRNAs correlated with OS [245] and a six-lncRNA signature could separate two immune risk subgroups, where cohorts of high risk showed reduced levels of CD8-T cells and the immunity-related signature compared to cohorts of low risk, suggesting a role of CD8-T cells as a prognostic feature [246]. In addition, another ten-lncRNA signature for RFS [247] and an eight-lncRNA signature that can divide a cohort into two risk groups with different survival times [248] have been further validated as independent predictors. A lncRNA signature may help predict the sensitivity and outcome response to chemical treatment, a tamoxifen efficacy-related lncRNA signature (TLS) was obtained to predict the response to tamoxifen of ER + BC patients, demonstrating that patients with increased levels of TLS were more resistant to tamoxifen therapy as these lncRNAs interfered with cell cycle arrest induced by the drug [249].…”

Section: Ncrna Dysregulation In Breast Cancermentioning

confidence: 95%

Epigenetic Regulation in Exposome-Induced Tumorigenesis: Emerging Roles of ncRNAs

et al. 2022

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Environmental factors, including pollutants and lifestyle, constitute a significant role in severe, chronic pathologies with an essential societal, economic burden. The measurement of all environmental exposures and assessing their correlation with effects on individual health is defined as the exposome, which interacts with our unique characteristics such as genetics, physiology, and epigenetics. Epigenetics investigates modifications in the expression of genes that do not depend on the underlying DNA sequence. Some studies have confirmed that environmental factors may promote disease in individuals or subsequent progeny through epigenetic alterations. Variations in the epigenetic machinery cause a spectrum of different disorders since these mechanisms are more sensitive to the environment than the genome, due to the inherent reversible nature of the epigenetic landscape. Several epigenetic mechanisms, including modifications in DNA (e.g., methylation), histones, and noncoding RNAs can change genome expression under the exogenous influence. Notably, the role of long noncoding RNAs in epigenetic processes has not been well explored in the context of exposome-induced tumorigenesis. In the present review, our scope is to provide relevant evidence indicating that epigenetic alterations mediate those detrimental effects caused by exposure to environmental toxicants, focusing mainly on a multi-step regulation by diverse noncoding RNAs subtypes.

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Long non-coding RNA-based signatures to improve prognostic prediction of breast cancer

Abstract: Supplemental Digital Content is available in the text

Cited by 5 publications

References 36 publications

Identification and validation of a robust autophagy-related molecular model for predicting the prognosis of breast cancer patients

Identification and validation of a robust autophagy-related molecular model for predicting the prognosis of breast cancer patients

The role of ferroptosis in breast cancer patients: a comprehensive analysis

Epigenetic Regulation in Exposome-Induced Tumorigenesis: Emerging Roles of ncRNAs

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