Evidence map›Paper›PMID 31660895›Full record

ArticleBMC cancer2019

Combined quantitation of HMGA2 mRNA, microRNAs, and mitochondrial-DNA content enables the identification and typing of thyroid tumors in fine-needle aspiration smears.

Sergei E Titov, Mikhail K Ivanov, Pavel S Demenkov, Gevork A Katanyan, Eugenia S Kozorezova, Anastasia V Malek, Yulia A Veryaskina, Igor F Zhimulev

Abstract read
In one paragraph

Article in BMC cancer, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  5. Multiple Myeloma: Genetic and Epigenetic Biomarkers with Clinical Potential.International journal of molecular sciences · 2024
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  8. BRAFMedical journal of the Islamic Republic of Iran · 2024
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  12. Reference Genes for qPCR-Based miRNA Expression Profiling in 14 Human Tissues.Medical principles and practice : international journal of the Kuwait University, Health Science Centre · 2022
    Review
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  16. Review
  17. Association ofPharmacogenomics and personalized medicine · 2021
    Article
4 · The record

Corrections and comments

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5 · Who and what money

Authors and funding

8 authors.

Sergei E TitovInstitute of Molecular and Cellular Biology, Novosibirsk, 630090, Russia. titovse78@gmail.com.ORCID http://orcid.org/0000-0001-9401-5737
Mikhail K IvanovInstitute of Molecular and Cellular Biology, Novosibirsk, 630090, Russia.
Pavel S DemenkovInstitute of Cytology and Genetics, Novosibirsk, 630090, Russia.
Gevork A KatanyanRegional Clinical Hospital No. 2, Krasnodar, 350012, Russia.
Eugenia S KozorezovaSiberian District Medical Center of Federal Medical and Biological Agency, Novosibirsk, 630007, Russia.
Anastasia V MalekN.N. Petrov National Medical Research Center of Oncology, St. Petersburg, 197758, Russia.
Yulia A VeryaskinaInstitute of Molecular and Cellular Biology, Novosibirsk, 630090, Russia.
Igor F ZhimulevInstitute of Molecular and Cellular Biology, Novosibirsk, 630090, Russia.

Funding

Siberian Branch, Russian Academy of Sciences 0310-2018-0007
6 · The paper itself

Abstract

backgroundAnalysis 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.

methodsA 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.

resultsA 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.

conclusionsThe 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.

Indexed as

Decision Support TechniquesAdultAgedAlgorithmsBiomarkers, TumorBiopsy, Fine-NeedleData AccuracyDiagnosis, DifferentialDNA, MitochondrialFeasibility StudiesFemaleGoiterHMGA2 ProteinHumansMaleMicroRNAsBiomarkers, TumorDNA, MitochondrialHMGA2 ProteinHMGA2 protein, humanMicroRNAsRNA, MessengerHMGA2microRNAmolecular markerspreoperative diagnosisThyroid carcinoma

Identifiers

PMID31660895
PMCPMC6819494

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.