Molecular subtypes of pancreatic cancer based on miRNA expression profiles have independent prognostic value

被引:51
|
作者
Namkung, Junghyun [1 ]
Kwon, Wooil [2 ,3 ,4 ]
Choi, Yonwhan [1 ]
Yi, Sung Gon [1 ]
Han, Sangjo [1 ]
Kang, Mee Joo [2 ,3 ,4 ]
Kim, Sun-Whe [2 ,3 ,4 ]
Park, Taesung [5 ]
Jang, Jin-Young [2 ,3 ,4 ]
机构
[1] Seoul Natl Univ, Coll Med, Bioinformat Tech Lab, Healthcare Grp,Future Technol R&D Div SK Telecom, Seoul, South Korea
[2] Seoul Natl Univ, Coll Med, Dept Surg, 101 Daehak Ro, Seoul 110744, South Korea
[3] Seoul Natl Univ, Coll Med, Canc Res Inst, Seoul, South Korea
[4] Sungkyunkwan Univ, Sch Med, Samsung Med Ctr, Dept Surg, Seoul, South Korea
[5] Seoul Natl Univ, Dept Stat, Seoul, South Korea
关键词
miRNA profile; molecular subtype; pancreatic ductal adenocarcinoma; prognosis; MICRORNA BIOMARKERS; ADENOCARCINOMA;
D O I
10.1111/jgh.13253
中图分类号
R57 [消化系及腹部疾病];
学科分类号
摘要
Background and Aim:Altered microRNAs (miRNA) expression, a typical feature of many cancers, is reportedly associated with prognosis according to several studies. Although numerous studies on miRNAs in pancreatic ductal adenocarcinoma have also attempted to identify prognostic biomarkers, more large-scale clinical studies are needed to establish the clinical significance of the results. Present study aimed to identify prognosis-related molecular subtypes of primary pancreas tumors using miRNA expression profiling. Methods:Expression profiles of 1733 miRNAs were obtained by using microarray analysis of 104 pancreatic tumors of Korean patients. To detect subgroups informative in predicting the patient's prognosis, we applied unsupervised clustering methods and then analyzed the association of the molecular subgroups with survival time. Then, we constructed a classifier to predict the subgroup using penalized regression models. Results:We have determined three pancreatic ductal adenocarcinoma tumor subtypes associated with prognosis based on miRNA expression profiles. These subtypes showed significantly different survival time for patients with the same clinical conditions. This demonstrates that our prognostic molecular subgroup has independent prognostic utility. The molecular subtypes can be predicted with a classifier of 19 miRNAs. Of the 19 signature miRNAs, miR-106b-star, miR-324-3p, and miR-615 were related to a p53 canonical pathway, and miR-324, miR-145-5p, miR-26b-5p, and miR-574-3p were related to a Cox-2 centered pathway. Conclusions:Our prognostic molecular subtypes demonstrated that miRNA profiles could be used as prognostic markers. Additionally, we have constructed a classifier that may be used to determine the molecular subgroup of new patient sample data. Further studies are needed for validation.
引用
收藏
页码:1160 / 1167
页数:8
相关论文
共 50 条
  • [1] Prognostic Value of Molecular Subtypes in Pancreatic Cancer
    Bertucci, Francois
    Birnbaum, David J.
    Finetti, Pascal
    Gilabert, Marine
    Poizat, Flora
    Raoul, Jean-Luc
    Birnbaum, Daniel
    Mamessier, Emilie
    PANCREAS, 2017, 46 (04) : E29 - E31
  • [2] Differential Analysis of lncRNA, miRNA and mRNA Expression Profiles and the Prognostic Value of lncRNA in Esophageal Cancer
    Liu, Hongtao
    Zhang, Qing
    Lou, Qianqian
    Zhang, Xin
    Cui, Yunxia
    Wang, Panpan
    Yang, Fan
    Wu, Fan
    Wang, Jing
    Fan, Tianli
    Li, Shenglei
    PATHOLOGY & ONCOLOGY RESEARCH, 2020, 26 (02) : 1029 - 1039
  • [3] RNA Sequencing-Based Immune Signatures Confer Independent Prognostic Value across Molecular Subtypes of Endometrial Cancer
    Joseph, Julia
    Lavasseur, Corinne
    Yang, Xiaohua
    Richardson, Brian
    Cameron, Mark
    Avril, Stefanie
    MODERN PATHOLOGY, 2020, 33 (SUPPL 2) : 1075 - 1075
  • [4] RNA Sequencing-Based Immune Signatures Confer Independent Prognostic Value across Molecular Subtypes of Endometrial Cancer
    Joseph, Julia
    Lavasseur, Corinne
    Yang, Xiaohua
    Richardson, Brian
    Cameron, Mark
    Avril, Stefanie
    LABORATORY INVESTIGATION, 2020, 100 (SUPPL 1) : 1075 - 1075
  • [5] Gene Expression Classification of Colon Cancer into Molecular Subtypes: Characterization, Validation, and Prognostic Value
    Marisa, Laetitia
    de Reynies, Aureline
    Duval, Alex
    Selves, Janick
    Gaub, Marie Pierre
    Vescovo, Laure
    Etienne-Grimaldi, Marie-Christine
    Schiappa, Renaud
    Guenot, Dominique
    Ayadi, Mira
    Kirzin, Sylvain
    Chazal, Maurice
    Flejou, Jean-Francois
    Benchimol, Daniel
    Berger, Anne
    Lagarde, Arnaud
    Pencreach, Erwan
    Piard, Francois
    Elias, Dominique
    Parc, Yann
    Olschwang, Sylviane
    Milano, Gerard
    Laurent-Puig, Pierre
    Boige, Valerie
    PLOS MEDICINE, 2013, 10 (05)
  • [6] Exploration of the molecular mechanism of prostate cancer based on mRNA and miRNA expression profiles
    Zhang, Xing
    Sun, YuYan
    Wang, Peng
    Yang, Changfu
    Li, Shengwei
    ONCOTARGETS AND THERAPY, 2017, 10 : 3225 - 3232
  • [7] Independent prognostic value of inflammation in metastatic pancreatic cancer.
    Oksuzoglu, Berna
    Esin, Ece
    Koksoy, Elif Berna
    Demirci, Nebi Serkan
    Sendur, Mehmet Ali Nahit
    Dede, Isa
    Sezer, Ahmet
    Karci, Ebru
    Yildirim, Nuriye
    Yalcin, Bulent
    Utkan, Gungor
    Urun, Yuksel
    JOURNAL OF CLINICAL ONCOLOGY, 2018, 36 (15)
  • [8] The prognostic value of deep learning based mitotic count for breast cancer molecular subtypes
    Balkenhol, M.
    Mercan, C.
    Tessier, L.
    Tellez, D.
    Niendorf, A.
    Wegscheider, A.
    Bult, P.
    Ciompi, F.
    van der Laak, J.
    VIRCHOWS ARCHIV, 2022, 481 (SUPPL 1) : S57 - S57
  • [9] Refinement of breast cancer molecular classification by miRNA expression profiles
    Sokilde, Rolf
    Persson, Helena
    Ehinger, Anna
    Pirona, Anna Chiara
    Ferno, Marten
    Hegardt, Cecilia
    Larsson, Christer
    Loman, Niklas
    Malmberg, Martin
    Ryden, Lisa
    Saal, Lao
    Borg, Ake
    Vallon-Christerson, Johan
    Rovira, Carlos
    BMC GENOMICS, 2019, 20 (1)
  • [10] Refinement of breast cancer molecular classification by miRNA expression profiles
    Rolf Søkilde
    Helena Persson
    Anna Ehinger
    Anna Chiara Pirona
    Mårten Fernö
    Cecilia Hegardt
    Christer Larsson
    Niklas Loman
    Martin Malmberg
    Lisa Rydén
    Lao Saal
    Åke Borg
    Johan Vallon-Christerson
    Carlos Rovira
    BMC Genomics, 20