Establishment and validation of lncRNA-related prognostic signatures in cholangiocarcinoma

被引:3
|
作者
Li, Fengwei [1 ]
Zhang, JiaNing [2 ]
Zhang, Jinchi [3 ]
Xue, Hui [1 ]
Liu, Liu [1 ]
Yang, Zhao [1 ]
Dong, Hui [4 ,6 ]
Wang, Kui [1 ,5 ]
机构
[1] Naval Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Hepat Surg 2, Shanghai, Peoples R China
[2] Naval Med Univ, Changzheng Hosp, Shanghai, Peoples R China
[3] Xiamen Med Coll, Affiliated Hosp 2, Dept Dermatol, Xiamen, Fujian, Peoples R China
[4] Naval Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Pathol, Shanghai, Peoples R China
[5] Naval Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Hepat Surg 2, 225 Changhai Rd, Shanghai 200438, Peoples R China
[6] Naval Med Univ, Eastern Hepatobiliary Surg Hosp, Dept Pathol, 225 Changhai Rd, Shanghai 200438, Peoples R China
关键词
Cholangiocarcinoma; Long non -coding RNA; Prognosis; MIR4435-2HG; GAPLINC; CELL-PROLIFERATION; CANCER CELL; EXPRESSION; MIGRATION; INVASION;
D O I
10.1016/j.ygeno.2023.110621
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Background: The prognosis of CCA is extremely poor, making it one of the most lethal cancers. Therefore, there is a need to elucidate the pathogenic mechanisms of CCA. In this study, we aimed at identifying lncRNA-related prognostic signatures for CCA through bioinformatics analysis and further validated their functions in CCA tumorigenesis and progression. Methods: The RNA-seq data of CCA were downloaded from public databases. Differentially expressed lncRNAs (DElncRNAs) were screened. Then, candidate OS- and DFS-related DElncRNAs were selected through Kaplan-Meier survival analysis. Furthermore, LASSO regression was performed to establish the OS and DFS signatures, respectively. Multivariate COX models and nomograms for overall survival (OS) and disease-free survival (DFS) were established based on OS/DFS signature and clinical data. Hub lncRNAs were identified and enrichment analyses were performed to explore their potential functions. Finally, in vitro and in vivo models were used to validate the effects of the hub lncRNAs in CCA tumorigenesis and progression. Results: A total of 925 DElncRNAs were selected, of which six candidate OS-related lncRNAs and 15 candidate DFS-related lncRNAs were identified. The OS and DFS signatures were then established using four lncRNAs, respectively. We found that the OS signature and vascular invasion were independent risk factors for the OS of CCA, while the DFS signature, vascular invasion, and CA19-9 were independent risk factors for the DFS of CCA. Then, nomograms were established to achieve personalized CCA recurrence and death prediction. Furthermore, our study uncovered that MIR4435-2HG and GAPLINC might play crucial roles in CCA progression and be selected as hub lncRNAs. GO and KEGG enrichment analyses revealed that the two hub lncRNAs were closely related to CCA tumorigenesis. Finally, we demonstrated that MIR4435-2HG and GAPLINC can stimulate CCA proliferation and migration in vitro and in vivo. Conclusions: The established OS and DFS signatures are independent risk factors for OS and DFS of CCA patients, respectively. MIR4435-2HG and GAPLINC were identified as hub lncRNAs. In vitro and in vivo models revealed that MIR4435-2HG and GAPLINC can prompt CCA progression, which might be novel prognostic biomarkers and therapeutic targets for CCA.
引用
收藏
页数:11
相关论文
共 50 条
  • [21] Construction of a Prognostic Model Based on Cuproptosis-Related lncRNA Signatures in Pancreatic Cancer
    Jiang, Wenkai
    Du, Yan
    Zhang, Wenlong
    Zhou, Wence
    CANADIAN JOURNAL OF GASTROENTEROLOGY AND HEPATOLOGY, 2022, 2022
  • [22] Pyroptosis-related lncRNA prognostic signatures for cutaneous melanoma and tumor microenvironment status
    Deng, Huiling
    Chen, Yuxuan
    An, Ran
    Wang, Jiecong
    EPIGENOMICS, 2023, 15 (12) : 657 - 675
  • [23] Necroptosis-Related LncRNA Signatures for Prognostic Prediction in Uterine Corpora Endometrial Cancer
    Lin, Zhiheng
    Fan, Weisen
    Sui, Xiaohui
    Li, Yalin
    Wang, Juntao
    Zhao, Junde
    REPRODUCTIVE SCIENCES, 2023, 30 (02) : 576 - 589
  • [24] Necroptosis-Related LncRNA Signatures for Prognostic Prediction in Uterine Corpora Endometrial Cancer
    Zhiheng Lin
    Weisen Fan
    Xiaohui Sui
    Juntao Wang
    Junde Zhao
    Reproductive Sciences, 2023, 30 : 576 - 589
  • [25] Identification and validation of fatty acid metabolism-related lncRNA signatures as a novel prognostic model for clear cell renal cell carcinoma
    Cheng Shen
    Zhan Chen
    Jie Jiang
    Yong Zhang
    Xinfeng Chen
    Wei Xu
    Rui Peng
    Wenjing Zuo
    Qian Jiang
    Yihui Fan
    Xingxing Fang
    Bing Zheng
    Scientific Reports, 13
  • [26] Identification and validation of fatty acid metabolism-related lncRNA signatures as a novel prognostic model for clear cell renal cell carcinoma
    Shen, Cheng
    Chen, Zhan
    Jiang, Jie
    Zhang, Yong
    Chen, Xinfeng
    Xu, Wei
    Peng, Rui
    Zuo, Wenjing
    Jiang, Qian
    Fan, Yihui
    Fang, Xingxing
    Zheng, Bing
    SCIENTIFIC REPORTS, 2023, 13 (01)
  • [27] A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma
    Zou, Wenbo
    Wang, Zizheng
    Wang, Fei
    Li, Lincheng
    Liu, Rong
    Hu, Minggen
    BMC CANCER, 2021, 21 (01)
  • [28] A metabolism-related 4-lncRNA prognostic signature and corresponding mechanisms in intrahepatic cholangiocarcinoma
    Wenbo Zou
    Zizheng Wang
    Fei Wang
    Lincheng Li
    Rong Liu
    Minggen Hu
    BMC Cancer, 21
  • [29] Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer
    Pang, Lin
    Wang, Qingqing
    Wang, Lingxiao
    Hu, Zhen
    Yang, Chong
    Li, Yiqun
    Wang, Zhenqi
    Li, Yaoping
    BMC MEDICAL GENOMICS, 2023, 16 (01)
  • [30] Development and validation of cuproptosis-related lncRNA signatures for prognosis prediction in colorectal cancer
    Lin Pang
    Qingqing Wang
    Lingxiao Wang
    Zhen Hu
    Chong Yang
    Yiqun Li
    Zhenqi Wang
    Yaoping Li
    BMC Medical Genomics, 16