Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
Combined quantitation of HMGA2 mRNA, microRNAs, and mitochondrial-DNA content enables the identification and typing of thyroid tumors in fine-needle aspiration smears. / Titov, Sergei E.; Ivanov, Mikhail K.; Demenkov, Pavel S. и др.
в: BMC Cancer, Том 19, № 1, 1010, 28.10.2019.Результаты исследований: Научные публикации в периодических изданиях › статья › Рецензирование
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TY - JOUR
T1 - Combined quantitation of HMGA2 mRNA, microRNAs, and mitochondrial-DNA content enables the identification and typing of thyroid tumors in fine-needle aspiration smears
AU - Titov, Sergei E.
AU - Ivanov, Mikhail K.
AU - Demenkov, Pavel S.
AU - Katanyan, Gevork A.
AU - Kozorezova, Eugenia S.
AU - Malek, Anastasia V.
AU - Veryaskina, Yulia A.
AU - Zhimulev, Igor F.
PY - 2019/10/28
Y1 - 2019/10/28
N2 - Background: Analysis of molecular markers in addition to cytological analysis of fine-needle aspiration (FNA) samples is a promising way to improve the preoperative diagnosis of thyroid nodules. Nonetheless, in clinical practice, applications of existing diagnostic solutions based on the detection of somatic mutations or analysis of gene expression are limited by their high cost and difficulties with clinical interpretation. The aim of our work was to develop an algorithm for the differential diagnosis of thyroid nodules on the basis of a small set of molecular markers analyzed by real-time PCR. Methods: A total of 494 preoperative FNA samples of thyroid goiters and tumors from 232 patients with known histological reports were analyzed: goiter, 105 samples (50 patients); follicular adenoma, 101 (48); follicular carcinoma, 43 (28); Hürthle cell carcinoma, 25 (11); papillary carcinoma, 121 (56); follicular variant of papillary carcinoma, 80 (32); and medullary carcinoma, 19 (12). Total nucleic acids extracted from dried FNA smears were analyzed for five somatic point mutations and two translocations typical of thyroid tumors as well as for relative concentrations of HMGA2 mRNA and 13 microRNAs and the ratio of mitochondrial to nuclear DNA by real-time PCR. A decision tree-based algorithm was built to discriminate benign and malignant tumors and to type the thyroid cancer. Leave-p-out cross-validation with five partitions was performed to estimate prediction quality. A comparison of two independent samples by quantitative traits was carried out via the Mann-Whitney U test. Results: A minimum set of markers was selected (levels of HMGA2 mRNA and miR-375, - 221, and -146b in combination with the mitochondrial-to-nuclear DNA ratio) and yielded highly accurate discrimination (sensitivity = 0.97; positive predictive value = 0.98) between goiters with benign tumors and malignant tumors and accurate typing of papillary, medullary, and Hürthle cell carcinomas. The results support an alternative classification of follicular tumors, which differs from the histological one. Conclusions: The study shows the feasibility of the preoperative differential diagnosis of thyroid nodules using a panel of several molecular markers by a simple PCR-based method. Combining markers of different types increases the accuracy of classification.
AB - Background: Analysis of molecular markers in addition to cytological analysis of fine-needle aspiration (FNA) samples is a promising way to improve the preoperative diagnosis of thyroid nodules. Nonetheless, in clinical practice, applications of existing diagnostic solutions based on the detection of somatic mutations or analysis of gene expression are limited by their high cost and difficulties with clinical interpretation. The aim of our work was to develop an algorithm for the differential diagnosis of thyroid nodules on the basis of a small set of molecular markers analyzed by real-time PCR. Methods: A total of 494 preoperative FNA samples of thyroid goiters and tumors from 232 patients with known histological reports were analyzed: goiter, 105 samples (50 patients); follicular adenoma, 101 (48); follicular carcinoma, 43 (28); Hürthle cell carcinoma, 25 (11); papillary carcinoma, 121 (56); follicular variant of papillary carcinoma, 80 (32); and medullary carcinoma, 19 (12). Total nucleic acids extracted from dried FNA smears were analyzed for five somatic point mutations and two translocations typical of thyroid tumors as well as for relative concentrations of HMGA2 mRNA and 13 microRNAs and the ratio of mitochondrial to nuclear DNA by real-time PCR. A decision tree-based algorithm was built to discriminate benign and malignant tumors and to type the thyroid cancer. Leave-p-out cross-validation with five partitions was performed to estimate prediction quality. A comparison of two independent samples by quantitative traits was carried out via the Mann-Whitney U test. Results: A minimum set of markers was selected (levels of HMGA2 mRNA and miR-375, - 221, and -146b in combination with the mitochondrial-to-nuclear DNA ratio) and yielded highly accurate discrimination (sensitivity = 0.97; positive predictive value = 0.98) between goiters with benign tumors and malignant tumors and accurate typing of papillary, medullary, and Hürthle cell carcinomas. The results support an alternative classification of follicular tumors, which differs from the histological one. Conclusions: The study shows the feasibility of the preoperative differential diagnosis of thyroid nodules using a panel of several molecular markers by a simple PCR-based method. Combining markers of different types increases the accuracy of classification.
KW - HMGA2
KW - microRNA
KW - molecular markers
KW - preoperative diagnosis
KW - Thyroid carcinoma
KW - INDETERMINATE
KW - EXPRESSION ANALYSIS
KW - PREVALENCE
KW - CANCER
KW - MOLECULAR ANALYSIS
KW - GENE
KW - MUTATION
KW - CARCINOMAS
KW - DIAGNOSTIC UTILITY
KW - FOLLICULAR VARIANT
UR - http://www.scopus.com/inward/record.url?scp=85074233901&partnerID=8YFLogxK
U2 - 10.1186/s12885-019-6154-7
DO - 10.1186/s12885-019-6154-7
M3 - Article
C2 - 31660895
AN - SCOPUS:85074233901
VL - 19
JO - BMC Cancer
JF - BMC Cancer
SN - 1471-2407
IS - 1
M1 - 1010
ER -
ID: 22336051