miRNA Expression Profiling in G1 and G2 Pancreatic Neuroendocrine Tumors

被引:0
|
作者
Nyiro, Gabor [1 ,2 ,3 ]
Szeredas, Balint Kende [1 ]
Decmann, Abel [4 ]
Herold, Zoltan [5 ]
Vekony, Balint [1 ,2 ]
Borka, Katalin [6 ]
Dezso, Katalin [7 ]
Zalatnai, Attila [7 ]
Kovalszky, Ilona [7 ]
Igaz, Peter [1 ,2 ]
机构
[1] Semmelweis Univ, Fac Med, Dept Endocrinol, Korany Str 2-A, H-1083 Budapest, Hungary
[2] Semmelweis Univ, Fac Med, Dept Internal Med & Oncol, Korany Str 2-A, H-1083 Budapest, Hungary
[3] Semmelweis Univ, Fac Med, Dept Lab Med, Nagyvarad Sq 4, H-1089 Budapest, Hungary
[4] Dr Laszlo Vass Hlth Ctr, Municipal Dist 15, H-1152 Budapest, Hungary
[5] Semmelweis Univ, Dept Internal Med & Oncol, Div Oncol, Baross Str 23-25, H-1082 Budapest, Hungary
[6] Semmelweis Univ, Fac Med, Dept Pathol Forens & Insurance Med, Ulloi Str 93, H-1083 Budapest, Hungary
[7] Semmelweis Univ, Fac Med, Dept Pathol & Expt Canc Res, Ulloi Ut 26, H-1085 Budapest, Hungary
关键词
pancreatic neuroendocrine tumor; grade; microRNA; biomarker; machine learning; formalin-fixed paraffin-embedded; PROLIFERATION; GUIDELINES; CANCER;
D O I
10.3390/cancers16142528
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
Simple Summary Pancreatic neuroendocrine tumors are rare, but their incidence is rising. Several grades exist, and distinguishing between these is pivotal for clinical management. Currently, the grades can only be differentiated by histological analysis requiring invasive sampling. MicroRNAs are short non-protein coding RNA molecules that were shown to be differentially expressed in a wide variety of tumors. Here, we examined whether microRNAs could be exploited to differentiate grade 1 and 2 pancreatic neuroendocrine tumors and established significantly differentially expressed microRNAs.Abstract Pancreatic neuroendocrine neoplasms pose a growing clinical challenge due to their rising incidence and variable prognosis. The current study aims to investigate microRNAs (miRNA; miR) as potential biomarkers for distinguishing between grade 1 (G1) and grade 2 (G2) pancreatic neuroendocrine tumors (PanNET). A total of 33 formalin-fixed, paraffin-embedded samples were analyzed, comprising 17 G1 and 16 G2 tumors. Initially, literature-based miRNAs were validated via real-time quantitative reverse transcription polymerase chain reaction (RT-qPCR), confirming significant downregulation of miR-130b-3p and miR-106b in G2 samples. Through next-generation sequencing, we have identified and selected the top six miRNAs showing the highest difference between G1 and G2 tumors, which were further validated. RT-qPCR validation confirmed the downregulation of miR-30d-5p in G2 tumors. miRNA combinations were created to distinguish between the two PanNET grades. The highest diagnostic performance in distinguishing between G1 and G2 PanNETs by a machine learning algorithm was achieved when using the combination miR-106b + miR-130b-3p + miR-127-3p + miR-129-5p + miR-30d-5p. The ROC analysis resulted in a sensitivity of 83.33% and a specificity of 87.5%. The findings underscore the potential use of miRNAs as biomarkers for stratifying PanNET grades, though further research is warranted to enhance diagnostic accuracy and clinical utility.
引用
收藏
页数:10
相关论文
共 50 条
  • [21] Well-differentiated G1 and G2 pancreatic neuroendocrine tumors: a meta-analysis of published expanded DNA sequencing data
    Andersen, Kirstine Oster
    Detlefsen, Sonke
    Brusgaard, Klaus
    Christesen, Henrik Thybo
    FRONTIERS IN ENDOCRINOLOGY, 2024, 15
  • [22] Development of novel prediction models for nodal and distant metastasis in G1 and G2 colorectal neuroendocrine tumors
    Zhijie Wang
    Qian Liu
    International Journal of Colorectal Disease, 38
  • [23] Development of novel prediction models for nodal and distant metastasis in G1 and G2 colorectal neuroendocrine tumors
    Wang, Zhijie
    Liu, Qian
    INTERNATIONAL JOURNAL OF COLORECTAL DISEASE, 2023, 38 (01)
  • [24] Well-Differentiated G1/G2 Pancreatic NETs Can Evolve Towards G3 Tumors
    Hentic, O.
    Cros, J.
    Rebours, V
    Zappa, M.
    Muller, N.
    Maire, F.
    Levy, P.
    Hammel, P.
    Couvelard, A.
    Levy, P.
    NEUROENDOCRINOLOGY, 2017, 105 : 135 - 135
  • [25] Value of diffusion-weighted magnetic resonance imaging in predicting World Health Organization grade in G1/G2 pancreatic neuroendocrine tumors
    Guo, Chuangen
    Zhuge, Xiaoling
    Chen, Xiao
    Wang, Zhongqiu
    Xiao, Wenbo
    Wang, Qidong
    ONCOLOGY LETTERS, 2017, 13 (06) : 4141 - 4146
  • [26] Predictive value of preoperative MRI features for the Ki-67 index in well-differentiated G1/G2 pancreatic neuroendocrine tumors
    Sun, Haitao
    Zhang, Shilong
    Liu, Kai
    Zhou, Jianjun
    Wang, Xingxing
    Shen, Tingting
    Wang, Xiaolin
    ACTA RADIOLOGICA, 2019, 60 (11) : 1394 - 1404
  • [27] Ki-67 Index of 5% is Better Than 2% in Stratifying G1 and G2 of the World Health Organization Grading System in Pancreatic Neuroendocrine Tumors
    Gao, Shao-Wei
    Huang, Chen-Song
    Huang, Xi-Tai
    Chen, Liu-Hua
    Chen, Wei
    Cai, Jian-Peng
    Yin, Xiao-Yu
    PANCREAS, 2019, 48 (06) : 795 - 798
  • [28] CLEC3A, MMP7, and LCN2 as novel markers for predicting recurrence in resected G1 and G2 pancreatic neuroendocrine tumors
    Miki, Masami
    Oono, Takamasa
    Fujimori, Nao
    Takaoka, Takehiro
    Kawabe, Ken
    Miyasaka, Yoshihiro
    Ohtsuka, Takao
    Saito, Daisuke
    Nakamura, Masafumi
    Ohkawa, Yasuyuki
    Oda, Yoshinao
    Suyama, Mikita
    Ito, Tetsuhide
    Ogawa, Yoshihiro
    CANCER MEDICINE, 2019, 8 (08): : 3748 - 3760
  • [29] Comparative Analysis of Computed Tomography Features in Pancreatic Neuroendocrine Neoplasms (pNENs) with Different Pathological Grade (G1 and G2)
    Tang, J.
    NEUROENDOCRINOLOGY, 2017, 105 : 55 - 55
  • [30] Development of clinically representative patient-derived organoid models for diverse G1/G2 gastroenteropancreatic neuroendocrine tumors
    Zuo, X.
    Liu, Y.
    Maxwelll, J.
    Halperin, D.
    Dasari, A.
    Kopetz, S.
    Cheng, S.
    Yao, J.
    JOURNAL OF NEUROENDOCRINOLOGY, 2024, 36 : 59 - 59