Evidence map›Paper›PMID 34208446›Full record

ArticleJournal of clinical medicine2021

Combined Mutational and Clonality Analyses Support the Existence of Intra-Tumor Heterogeneity in Papillary Thyroid Cancer.

Marina Muzza, Gabriele Pogliaghi, Luca Persani, Laura Fugazzola, Carla Colombo

Abstract read
In one paragraph

Article in Journal of clinical medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
–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

5 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Marina MuzzaLaboratory of Endocrine and Metabolic Research, Istituto Auxologico Italiano IRCCS, 20095 Milan, Italy.ORCID 0000-0002-6288-9509
Gabriele PogliaghiLaboratory of Endocrine and Metabolic Research, Istituto Auxologico Italiano IRCCS, 20095 Milan, Italy.
Luca PersaniDivision of Endocrine and Metabolic Diseases, Istituto Auxologico Italiano IRCCS, 20095 Milan, Italy.ORCID 0000-0003-2068-9581
Laura FugazzolaDivision of Endocrine and Metabolic Diseases, Istituto Auxologico Italiano IRCCS, 20095 Milan, Italy.ORCID 0000-0001-5372-0982
Carla ColomboDivision of Endocrine and Metabolic Diseases, Istituto Auxologico Italiano IRCCS, 20095 Milan, Italy.

Funding

Istituto Auxologico italiano IRCCS Ricerca Corrente PTC-array, 05C825_2018Italian Ministry of University and Research PRIN 2017 - 2017YTWKWH
6 · The paper itself

Abstract

Despite its potential clinical impact, intra-tumor genetic heterogeneity (ITH) has been scantly investigated in papillary thyroid cancer (PTC). We studied ITH in PTC by combining, for the first time, data derived from the evaluation of the normalized allelic frequencies (NAF) of the mutation/s, using a customized MassARRAY panel, and those obtained by the HUMARA clonality assay. Among tumors with a single mutation, 80% of cases with NAF 50 ± 5% were clonal, consistent with the presence of a single mutated clone, while 20% of cases showed a polyclonal pattern, suggesting the presence of the same mutation in two or more clones. Differently, all cases with NAF < 45% were polyclonal. Among tumors with double mutation, cases with both mutations showing NAF 50 ± 5% were monoclonal, consistent with the presence of a single clone harboring both mutations. On the other hand, all cases with double mutation at NAF < 45% were polyclonal, indicating the presence of two clones with different mutations. Finally, no significant differences in the clinico-pathological characteristics were found between monoclonal and polyclonal tumors. In conclusion, the present study adds insights into the concept of ITH in PTC, which warrants attention because the occurrence of this phenomenon is likely to affect the response to targeted drugs.

Indexed as

clonalitypapillary thyroid cancertumor heterogeneity

Identifiers

PMID34208446
PMCPMC8234519

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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.