Identification of <scp> <i>BCL2L11</i> </scp> as a Candidate Gene for Hereditary Predisposition to Non‐Medullary Thyroid Cancer Using Familial Whole‐Exome‐Sequencing

Familial non-medullary thyroid cancer, defined as two or more affected first-degree relatives, accounts for 3%-9% of thyroid cancers. It is associated with more aggressive cancer, early age at diagnosis, multifocality, and increased risk of metastasis and recurrence. Although no high penetrance predisposing gene has been identified at present, the estimated contribution of genetics is significant. Our study explored five families presenting FNMTC using Whole-Exome Sequencing and found three candidate genes: TELO2 in one family, UACA and BCL2L11 in another. All of these tumor suppressor genes are expressed in the thyroid, exhibit under-expression in tumor tissue compared to healthy tissue both in silico and in our samples, and two of them are known to be involved in thyroid carcinogenesis via the FOXO3A pathway. Functional analysis to validate these candidate genes in thyroid cancer cells showed that one of the three, BCL2L11, has a tumor suppressor effect on proliferation and apoptosis. Their impact on hereditary predisposition to thyroid cancer, as well as their combined effects, requires further study. Indeed, a case-control study would be essential to determine the diagnostic utility of their routine analysis.

Authors

Institutions

Publication Details

Journal
Clinical Genetics
Published
2025-09-03
DOI
https://doi.org/10.1111/cge.70060
Primary Topic
Thyroid Cancer Diagnosis and Treatment
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Identification of BCL2L11 as a Candidate Gene for Hereditary Predisposition to Non‐Medullary Thyroid Cancer Using Familial Whole‐Exome‐Sequencing

Flora Ponelle‐Chachuat, Yannick Bidet, Mathias Cavaillé, Anne Cayre et al.
1 links
Clinical Genetics
Thyroid Cancer Diagnosis and Treatment
article

Identification of BCL2L11 as a Candidate Gene for Hereditary Predisposition to Non‐Medullary Thyroid Cancer Using Familial Whole‐Exome‐Sequencing

Flora Ponelle‐Chachuat, Yannick Bidet, Mathias Cavaillé, Anne Cayre, Nicolas Sonnier, Nancy Uhrhammer, Duygu Abbasoğlu, Mathis Lepage, Maud Privat, Sandrine Viala
article en

Abstract

Familial non-medullary thyroid cancer, defined as two or more affected first-degree relatives, accounts for 3%-9% of thyroid cancers. It is associated with more aggressive cancer, early age at diagnosis, multifocality, and increased risk of metastasis and recurrence. Although no high penetrance predisposing gene has been identified at present, the estimated contribution of genetics is significant. Our study explored five families presenting FNMTC using Whole-Exome Sequencing and found three candidate genes: TELO2 in one family, UACA and BCL2L11 in another. All of these tumor suppressor genes are expressed in the thyroid, exhibit under-expression in tumor tissue compared to healthy tissue both in silico and in our samples, and two of them are known to be involved in thyroid carcinogenesis via the FOXO3A pathway. Functional analysis to validate these candidate genes in thyroid cancer cells showed that one of the three, BCL2L11, has a tumor suppressor effect on proliferation and apoptosis. Their impact on hereditary predisposition to thyroid cancer, as well as their combined effects, requires further study. Indeed, a case-control study would be essential to determine the diagnostic utility of their routine analysis.

Clinical GeneticsVol. 109(3)
Inserm (FR), Université Clermont Auvergne (FR), Centre Jean Perrin (FR), Clermont Université (FR), Imagerie Moléculaire et Stratégies Théranostiques
Institut National de la Santé et de la Recherche Médicale
Openalex Percentile: Top 68%
Thyroid Cancer Diagnosis and Treatment
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.