Prognostic and predictive value of a microRNA signature in adults with T-cell lymphoblastic lymphoma

Tian, Xuefeng; Huang, Wei; Huang, Hui Qiang; Liu, Yan Hui; Wang, Liang; Zhang, Xi; Lin, Tong; Rao, Hui Lan; Li, Mei; Liu, Fang; Zhang, Fen; Zhong, Li Ye; Li, Liang; Lan, Xiao Liang; Li, Juan; Liao, Bing; Li, Zhi Hua; Tang, Qiong; Liang, Qiong; Shao, Chun Kui; Zhai, Qiong Li; Cheng, Run Fen; Sun, Qi; Ru, Kun; Gu, Xia; Lin, Xi; Yi, Kun; Shuang, Yue Rong; Chen, Xiao; Dong, Wei; Sang, Wei; Sun, Cai; Liu, Hui; Zhu, Zhigang; Rao, Jun; Guo, Qiao; Zhou, Ying; Meng, Xiang; Zhu, Yong; Hu, Chang Lu; Jiang, Yi Rong; Zhang, Ying; Gao, Hong; He, Wen; Xia, Zhong Jun; Wu, Cheng-Hung; Zhang, Mei Yin; Wang, Hui Yun; Xie, Dan; Cai, Qing Qing

doi:10.1038/s41375-019-0466-0

Cited by 35 publications

(25 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Overfitting often occurs in selecting prognostic models using higher-dimensional data [ 18 ], here, we chosen the LASSO algorithm, which could eliminate this disadvantage [ 19 ], as the method to select CpG for constructing epigenetic signature. The algorithm of LASSO has been widely used to construct predictive survival models, for instance, colon cancer [ 20 ], gastric cancer [ 21 ], T-cell lymphoblastic lymphoma [ 22 ] and ccRCC [ 9 , 10 , 23 ].…”

Section: Discussionmentioning

confidence: 99%

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

Wang

Chen

et al. 2020

Cancer Cell Int

View full text Add to dashboard Cite

Background Recently, increasing study have found that DNA methylation plays an important role in tumor, including clear cell renal cell carcinoma (ccRCC). Methods We used the DNA methylation dataset of The Cancer Genome Atlas (TCGA) database to construct a 31-CpG-based signature which could accurately predict the overall survival of ccRCC. Meanwhile, we constructed a nomogram to predict the prognosis of patients with ccRCC. Result Through LASSO Cox regression analysis, we obtained the 31-CpG-based epigenetic signature which were significantly related to the prognosis of ccRCC. According to the epigenetic signature, patients were divided into two groups with high and low risk, and the predictive value of the epigenetic signature was verified by other two sets. In the training set, hazard ratio (HR) = 13.0, 95% confidence interval (CI) 8.0–21.2, P < 0.0001; testing set: HR = 4.1, CI 2.2–7.7, P < 0.0001; entire set: HR = 7.2, CI 4.9–10.6, P < 0.0001, Moreover, combined with clinical indicators, the prediction of 5-year survival of ccRCC reached an AUC of 0.871. Conclusions Our study constructed a 31-CpG-based epigenetic signature that could accurately predicted overall survival of ccRCC and staging progression of ccRCC. At the same time, we constructed a nomogram, which may facilitate the prediction of prognosis for patients with ccRCC.

show abstract

Section: Discussionmentioning

confidence: 99%

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

Wang

Chen

et al. 2020

Cancer Cell Int

View full text Add to dashboard Cite

show abstract

“…However, these risk factors have been only studied in small populations, and were not validated in independent centers. A FFPE-based miRNA signature has been developed to increase the predictive value of relapse of adult T-LBL (8). However, the miRNA-based signature would be influenced by tissues-specific dissimilarity.…”

Section: Notch1/fbxw7 (N/f) Mutations N/k-ras Mutations Pten Alteramentioning

confidence: 99%

“…Performance status was assessed using ECOG-PS and clinical stage was defined using the Ann Arbor stage system. We assessed NOTCH1/FBXW7 mutations as previously described (8). We further excluded patients who did not receive CNS prophylaxis with intrathecal chemotherapy (e.g., methotrexate, cytarabine, and corticosteroids), and high-dose systemic chemotherapy (e.g., methotrexate and cytarabine).…”

Section: Baseline Assessmentsmentioning

confidence: 99%

See 1 more Smart Citation

A CpG Methylation Classifier to Predict Relapse in Adults with T-Cell Lymphoblastic Lymphoma

Tian

Wang

et al. 2020

Clinical Cancer Research

Self Cite

View full text Add to dashboard Cite

show abstract

“…In addition, increasing evidences have been revealed demonstrating that the occurrences of many diseases including cancers are closely associated with abnormal expression of specific miRNAs [8], e.g., prostate cancer-associated miR-21 and miR-141 [9], breast cancer-associated miR-155-3p [10], and liver fibrosis-associated miR-378 [11]. Therefore, miRNAs are considered to be promising biomarker candidates in the early diagnosis and prognosis of various cancers [12][13][14]. Quantitative detection of abnormal miRNA expressions in cells, tissues, urine, or blood may have significant applications for clinical diagnosis [15].…”

Section: Introductionmentioning

confidence: 99%

DNA Dumbbell and Chameleon Silver Nanoclusters for miRNA Logic Operations

Jiang

2020

Research

View full text Add to dashboard Cite

Multiplex miRNA analysis is a fundamental issue for exploring a complex biological system and early diagnosis of miRNA-related diseases. Herein, we have developed a series of novel logic gates for miRNA analysis coupling DNA nanostructures and chameleon silver nanoclusters (AgNCs). DNA dumbbell structures are firstly designed with two independent nucleation sequences for AgNCs at the 5′ and 3′ ends, respectively. By introducing different miRNA inputs, separations of two AgNCs are controlled and the fluorescence property of AgNCs changes. By studying the ratiometric fluorescence responses, sensitive and selective analysis of multiple miRNAs can be achieved. The present work provides powerful tools for miRNA diagnostics and may also guide future DNA nanostructure-based logic gates.

show abstract

Prognostic and predictive value of a microRNA signature in adults with T-cell lymphoblastic lymphoma

Cited by 35 publications

References 34 publications

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

Epigenetic signature predicts overall survival clear cell renal cell carcinoma

A CpG Methylation Classifier to Predict Relapse in Adults with T-Cell Lymphoblastic Lymphoma

DNA Dumbbell and Chameleon Silver Nanoclusters for miRNA Logic Operations

Contact Info

Product

Resources

About