A novel miRNA-based signature as predictive tool of survival outcome of colorectal cancer patients

被引:5
|
作者
Zhao, Bochao [1 ]
Wang, Weiqiang [1 ]
Ye, Haikun [1 ]
Wang, Jingchao [1 ]
Meng, Kewei [1 ]
Yang, Tao [1 ]
机构
[1] Tianjin First Cent Hosp, Dept Gastrointestinal Surg, Tianjin, Peoples R China
关键词
colorectal cancer; miRNAs; prognostic; signature; survival prediction; MICRORNA SIGNATURES; TARGET; METASTASIS; CARCINOMA; PROLIFERATION; MIR-193A-3P; ONCOGENE; PACKAGE;
D O I
10.1111/cbdd.14301
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
It is great significance of identifying valuable biomarkers for early diagnosis and prognostic prediction of colorectal cancer (CRC) patients. This study aimed at developing and validating a miRNAs-based signature as prognostic tool for CRC patients. The miRNA expression profile of 624 CRC samples (613 tumor tissues and 11 normal tissues) was analyzed, and 523 differentially expressed miRNAs (DEmiRNAs) were identified, in which 191 were downregulated and 332 were upregulated. All patients were randomly divided into a training cohort (N = 308) and an internal validation cohort (N = 200). Using the least absolute shrinkage and selection operator (LASSO) and Cox regression model, a prognostic signature of 10 miRNAs (hsa-miR-149-5p, hsa-miR-193b-5p, hsa-miR-193a-3p, hsa-miR-3677-3p, hsa-miR-29a-3p, hsa-miR-200c-5p, hsa-miR-200a-5p, hsa-miR-6854-5p, hsa-miR-216a-5p and hsa-miR-891a-5p) was developed in the training cohort. The risk score was calculated by the product of the expression level and the coefficients of each miRNA. The prognostic value of 10 miRNAs-based signature for CRC patients was tested and validated. Survival analysis indicated that high-risk patients (> 1.10) had a worse overall survival (OS) than low-risk (= 1.10) patients (5-year OS rate for training cohort: 59.3% vs. 78.9%, p < .001; validation cohort: 48.3% vs. 69.3%, p = .011). The miRNA-based signature was an independent prognostic factor for CRC patients (HR for training cohort:2.476, 95% CI:1.202-5.098, p = .014; HR for validation cohort:2.050, 95% CI:1.087-3.869, p = .027). The AUC values for 3-year and 5-year OS prediction were 0.718 and 0.784 in the training cohort, 0.659 and 0.614 in the validation cohort, respectively. The 10 miRNAs-based signature provided a proper prognostic stratification for CRC patients, and it might be a promising tool for survival prediction.
引用
收藏
页码:1024 / 1033
页数:10
相关论文
共 50 条
  • [1] A miRNA-based predictive model in prostate cancer patients
    Kirste, S.
    Bell, E. H.
    Fleming, J.
    Stegmaier, P.
    Drendel, V.
    Mo, X.
    Ling, S.
    Fabian, D.
    Jilg, C.
    Schultze-Seemann, W.
    Zynger, D.
    Martin, D.
    White, J.
    Werner, M.
    Chakravarti, A.
    Grosu, A. L.
    RADIOTHERAPY AND ONCOLOGY, 2015, 115 : S361 - S362
  • [2] Novel Multiple miRNA-Based Signatures for Predicting Overall Survival and Recurrence-Free Survival of Colorectal Cancer Patients
    Qian, Jinrong
    Zeng, Lifeng
    Jiang, Xiaohua
    Zhang, Zhiyong
    Luo, Xiaojiang
    MEDICAL SCIENCE MONITOR, 2019, 25 : 7258 - 7271
  • [3] A Novel TCGA-Validated, MiRNA-Based Signature for Prediction of Breast Cancer Prognosis and Survival
    Tian, Baoxing
    Hou, Mengjie
    Zhou, Kun
    Qiu, Xia
    Du, Yibao
    Gu, Yifan
    Yin, Xiaoxing
    Wang, Jie
    FRONTIERS IN CELL AND DEVELOPMENTAL BIOLOGY, 2021, 9
  • [4] Identification of miRNA-Based Signature as a Novel Potential Prognostic Biomarker in Patients with Breast Cancer
    Tang, Jia
    Ma, Wei
    Zeng, Qinlong
    Tan, Jieliang
    Cao, Keshen
    Luo, Liangping
    DISEASE MARKERS, 2019, 2019
  • [5] Genome-wide identification of a novel miRNA-based signature to predict recurrence in patients with gastric cancer
    Yang, Yongmei
    Qu, Ailin
    Zhao, Rui
    Hua, Mengmeng
    Zhang, Xin
    Dong, Zhaogang
    Zheng, Guixi
    Pan, Hongwei
    Wang, Hongchun
    Yang, Xiaoyun
    Zhang, Yi
    MOLECULAR ONCOLOGY, 2018, 12 (12) : 2072 - 2084
  • [6] Development of a miRNA-based signature to predict human cancer metastasis
    Willetts, Lian
    Stoletov, Konstantin
    Jovel, Juan
    Woolner, Emma
    Lewis, John D.
    CANCER RESEARCH, 2017, 77
  • [7] miRNA-based signature for predicting epithelial ovarian cancer recurrence
    De Cecco, Loris
    Bagnoli, Marina
    Canevari, Silvana
    Califano, Daniela
    Perrone, Francesco
    Pignata, Sandro
    Mezzanzanica, Delia
    TRANSLATIONAL CANCER RESEARCH, 2017, 6 : S232 - S234
  • [8] Genomewide Expression Profiling Identifies a Novel miRNA-based Signature for the Detection of Peritoneal Metastasis in Patients With Gastric Cancer
    Shimura, Tadanobu
    Toden, Shusuke
    Kandimalla, Raju
    Toiyama, Yuji
    Okugawa, Yoshinaga
    Kanda, Mitsuro
    Baba, Hideo
    Kodera, Yasuhiro
    Kusunoki, Masato
    Goel, Ajay
    ANNALS OF SURGERY, 2021, 274 (05) : E425 - E434
  • [9] Development of a miRNA-based classifier for molecular colorectal cancer subtypes
    Adam, Ronja S.
    Poel, Dennis
    Moreno, Leandro Ferreira
    Spronck, Joey
    de Back, Tim R.
    Markowetz, Florian
    Wang, Xin
    Verheul, Henk M. W.
    Buffart, Tineke E.
    Vermeulen, Louis
    EUROPEAN JOURNAL OF HUMAN GENETICS, 2022, 30 (SUPPL 1) : 388 - 389
  • [10] A Novel Saliva-Based miRNA Signature for Colorectal Cancer Diagnosis
    Rapado-Gonzalez, Oscar
    Majem, Blanca
    Alvarez-Castro, Ana
    Diaz-Pena, Roberto
    Abalo, Alicia
    Suarez-Cabrera, Leticia
    Gil-Moreno, Antonio
    Santamaria, Anna
    Lopez-Lopez, Rafael
    Muinelo-Romay, Laura
    Mercedes Suarez-Cunqueiro, Maria
    JOURNAL OF CLINICAL MEDICINE, 2019, 8 (12)