Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients

Qi, Tingting; Qu, Jian; Tu, Chao; Lu, Qiong; Li, Guohua; Wang, Jiaojiao; Qu, Qiang

doi:10.3389/fcell.2020.596777

Cited by 14 publications

(17 citation statements)

References 62 publications

(67 reference statements)

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“…Although several new drugs have been introduced into clinical practice, MM is still incurable with dismal clinical outcomes in MM patients [ 18 , 19 ]. Molecular risk stratification basing on hub gene expression of MM has opened an avenue for clinicians to conduct personalized medicine [ 20 , 21 ]. Therefore, it is critical to developing novel molecular biomarkers that are closely related to the clinicopathological characteristics and clinical survival outcomes of MM patients.…”

Section: Discussionmentioning

confidence: 99%

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An interactive nomogram based on clinical and molecular signatures to predict prognosis in multiple myeloma patients

Liu

Dai

et al. 2021

Aging

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Although novel drugs and treatments have been developed and improved, multiple myeloma (MM) is still recurrent and difficult to cure. In the present study, the magenta module containing 400 hub genes was determined from the training dataset of GSE24080 through weighted gene co-expression network analysis (WGCNA). Then, using the least absolute shrinkage and selection operator (Lasso) analysis, a fifteen-gene signature was firstly selected and the predictive performance for overall survival (OS) was favorable, which was identified by Receiver Operating Characteristic (ROC) curves. The risk score model was constructed based on survival-associated fifteen genes from the Lasso model, which classified MM patients into high-risk and low-risk groups. Areas under the curve (AUC) of ROC curve and log-rank test showed that the high-risk group was correlated to the dismal survival outcome of MM patients, which was also identified in testing dataset of GSE9782. The calibration plot, the AUC value of the ROC curve and Concordance-index showed that the interactive nomogram with risk score could favorably predict the probability of multi-year OS of MM patients. Therefore, it may help clinicians make a precise therapeutic decision based on the easy-to-use tool of the nomogram.

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Section: Discussionmentioning

confidence: 99%

“…The risk score for MM patients was calculated and evaluated by Concordance-index (C-index) based on the Cox proportional-hazards model [ 21 , 58 ]. Then all patients were divided into a high-risk group and a low-risk group according to the cut-off value of the risk score.…”

Section: Methodsmentioning

confidence: 99%

An interactive nomogram based on clinical and molecular signatures to predict prognosis in multiple myeloma patients

Liu

Dai

et al. 2021

Aging

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“…LINC00162, an SE lncRNA, was highly expressed in bladder cancer cells and tissues, which can promote progression of bladder cancer [ 106 ]. Our team constructed prognostic models for five -genes associated with SEs for osteosarcoma patients and multiple myeloma patients, which accurately predict the prognosis of these cancer patients [ 107 , 108 ].…”

Section: Structures and Functions Of Sesmentioning

confidence: 99%

Super-enhancers: a new frontier for epigenetic modifiers in cancer chemoresistance

et al. 2021

J Exp Clin Cancer Res

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Although new developments of surgery, chemotherapy, radiotherapy, and immunotherapy treatments for cancer have improved patient survival, the emergence of chemoresistance in cancer has significant impacts on treatment effects. The development of chemoresistance involves several polygenic, progressive mechanisms at the molecular and cellular levels, as well as both genetic and epigenetic heterogeneities. Chemotherapeutics induce epigenetic reprogramming in cancer cells, converting a transient transcriptional state into a stably resistant one. Super-enhancers (SEs) are central to the maintenance of identity of cancer cells and promote SE-driven-oncogenic transcriptions to which cancer cells become highly addicted. This dependence on SE-driven transcription to maintain chemoresistance offers an Achilles’ heel for chemoresistance. Indeed, the inhibition of SE components dampens oncogenic transcription and inhibits tumor growth to ultimately achieve combined sensitization and reverse the effects of drug resistance. No reviews have been published on SE-related mechanisms in the cancer chemoresistance. In this review, we investigated the structure, function, and regulation of chemoresistance-related SEs and their contributions to the chemotherapy via regulation of the formation of cancer stem cells, cellular plasticity, the microenvironment, genes associated with chemoresistance, noncoding RNAs, and tumor immunity. The discovery of these mechanisms may aid in the development of new drugs to improve the sensitivity and specificity of cancer cells to chemotherapy drugs.

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“…Prognostic Values of DEGs were evaluated by univariate Cox analysis, using this approach, 5 genes which had strong association were signi cantly related to the OS of GBM patients were identi ed. To minimize over tting, lasso-penalized Cox regression analysis was applied [17]. Tenfold crossvalidation via minimum criteria were applied to tuning parameter (λ) selection.…”

Section: Data Acquisitionmentioning

confidence: 99%

New prognostic models in glioblastoma: based ferroptosis-related genes and immune scores

Yang

2021

Preprint

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Background: Glioblastoma multiforme (GBM) has a high degree of malignancy and the clinical outcomes is dismal. Ferroptosis is critical to the development and progression of many diseases, such as cancer, cardiovascular diseases and aging. This study was designed to establish a sensitive prognostic model based on ferroptosis-related genes and immune scores to predict overall survival (OS) in patients with GBM. Methods: The expression of genes and associated clinical parameters was obtained from the publicly available TCGA , CGGA and GEO database. According to the immune scores, patient samples were assigned into two groups. Their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by external databases.Results: A total of 4 ferroptosis-related genes (HMOX1,HSPB1,STEAP3,ZEB1)were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in the external datasets of OS (all p < 0.05). Receiver operating characteristic (ROC) curve analysis was conducted. Finding the area under the ROC curves (AUCs) were 0.82 at 1 years, 0.75 at 3 years, 0.67 at 5 years. Functional analysis revealed that immune related processes were different between two risk groups.We also explored its association with immune infiltration.Conclusion: Our study successfully constructed a prognostic model containing 4 hub ferroptosis-related genes for GBM, helping clinicians predict patients’ OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.

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Super-Enhancer Associated Five-Gene Risk Score Model Predicts Overall Survival in Multiple Myeloma Patients

Cited by 14 publications

References 62 publications

An interactive nomogram based on clinical and molecular signatures to predict prognosis in multiple myeloma patients

An interactive nomogram based on clinical and molecular signatures to predict prognosis in multiple myeloma patients

Super-enhancers: a new frontier for epigenetic modifiers in cancer chemoresistance

New prognostic models in glioblastoma: based ferroptosis-related genes and immune scores

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