TY - JOUR
T1 - Search for New Target Genes of MicroRNA for Differential Diagnosis of Benign and Malignant Neoplasms of the Thyroid Gland by In Silico Methods
AU - Kononchuk, V. V.
AU - Kopeikina, E. V.
AU - Kalinina, T. S.
AU - Saik, O. V.
AU - Alekseenok, E. Yu
AU - Kolyagina, M. K.
AU - Matashova, V. A.
AU - Shevchenko, S. P.
AU - Gulyaeva, L. F.
AU - Kushlinskii, N. E.
N1 - Publisher Copyright:
© 2022, Springer Science+Business Media, LLC, part of Springer Nature.
PY - 2022/6
Y1 - 2022/6
N2 - Differential diagnosis of thyroid gland neoplasms is an urgent problem in modern oncothyroidology. This is especially true for the diagnosis of follicular thyroid cancer and follicular thyroid adenoma at the preoperative stage. In this study, in silico methods were used to search for potential markers that are microRNA target genes. A list of 19 microRNAs was compiled, the expression of which varies depending on the type of thyroid neoplasms. For these microRNAs, the target genes were selected considering tissue specificity and association with thyroid diseases. We selected 9 target genes (MCM2, RASSF2, SPAG9, SSTR2, TP53BP1, INPP4B, CCDC80, GNAS, and PLK1), which can be considered as promising markers according to published data. Also, 6 new potential markers (CDK4, FGFR1, ERBB3, EGR1, MYLK, and SRC) were found, which make it possible to distinguish between follicular thyroid cancer and follicular thyroid adenoma. The proposed algorithm using various bioinformatics tools allows us to identify potential markers for the differential diagnosis of thyroid neoplasms.
AB - Differential diagnosis of thyroid gland neoplasms is an urgent problem in modern oncothyroidology. This is especially true for the diagnosis of follicular thyroid cancer and follicular thyroid adenoma at the preoperative stage. In this study, in silico methods were used to search for potential markers that are microRNA target genes. A list of 19 microRNAs was compiled, the expression of which varies depending on the type of thyroid neoplasms. For these microRNAs, the target genes were selected considering tissue specificity and association with thyroid diseases. We selected 9 target genes (MCM2, RASSF2, SPAG9, SSTR2, TP53BP1, INPP4B, CCDC80, GNAS, and PLK1), which can be considered as promising markers according to published data. Also, 6 new potential markers (CDK4, FGFR1, ERBB3, EGR1, MYLK, and SRC) were found, which make it possible to distinguish between follicular thyroid cancer and follicular thyroid adenoma. The proposed algorithm using various bioinformatics tools allows us to identify potential markers for the differential diagnosis of thyroid neoplasms.
KW - bioinformatics
KW - follicular adenoma
KW - microRNA
KW - target gene
KW - thyroid cancer
KW - MicroRNAs/genetics
KW - Diagnosis, Differential
KW - Humans
KW - Adaptor Proteins, Signal Transducing/metabolism
KW - Biomarkers, Tumor/genetics
KW - Adenoma/diagnosis
KW - Thyroid Neoplasms/diagnosis
KW - Adenocarcinoma, Follicular
UR - http://www.scopus.com/inward/record.url?scp=85132567742&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/b79f4516-b86b-3a7b-a675-bbf4e5acc523/
U2 - 10.1007/s10517-022-05527-x
DO - 10.1007/s10517-022-05527-x
M3 - Article
C2 - 35737153
AN - SCOPUS:85132567742
VL - 173
SP - 246
EP - 251
JO - Bulletin of Experimental Biology and Medicine
JF - Bulletin of Experimental Biology and Medicine
SN - 0007-4888
IS - 2
ER -