Evidence map›Paper›PMID 42074143›Full record

ArticleInternational journal of molecular sciences2026

The Molecular Landscape of CASTLE: A Rare Thymus-like Head and Neck Cancer.

William C Cho, Allen C S Yu, Wah Cheuk, Aldrin K Y Yim, James C H Chow, John K C Chan, Ka M Cheung

Abstract read
In one paragraph

Article in International journal of molecular sciences, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

William C ChoDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, China.ORCID 0000-0003-4174-4586
Allen C S YuCodex Genetics Ltd., Hong Kong, China.ORCID 0000-0002-9568-8316
Wah CheukDepartment of Pathology, Queen Elizabeth Hospital, Hong Kong, China.
Aldrin K Y YimCodex Genetics Ltd., Hong Kong, China.
James C H ChowDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, China.
John K C ChanDepartment of Pathology, Queen Elizabeth Hospital, Hong Kong, China.
Ka M CheungDepartment of Clinical Oncology, Queen Elizabeth Hospital, Hong Kong, China.ORCID 0000-0002-8476-0239

Funding

KCC Research Grant (Kowloon Central Cluster, Hospital Authority, Hong Kong SAR, China) KCC/RC/G/2223-B06
6 · The paper itself

Abstract

Carcinoma showing thymus-like differentiation (CASTLE) is a rare malignancy arising in the thyroid or neck, with an uncertain cellular origin that complicates both diagnosis and treatment. To better understand its molecular underpinnings and identify potential therapeutic avenues, we conducted integrated whole-exome and transcriptome sequencing on six CASTLE and six thymic carcinoma samples. Whole-exome sequencing (WES) was performed on all 12 samples, while RNA sequencing was successful for 1 CASTLE and 6 thymic carcinoma samples. Our analysis included somatic mutation profiling, mutational signature deconvolution, differential gene expression, and characterization of tumor microenvironment for the cases with available data, with comparisons to genomic data from other thyroid cancers. CASTLE tumors demonstrated a higher median tumor mutational burden than thymic carcinoma and lacked the common

Indexed as

Head and Neck NeoplasmsThymomaThymus NeoplasmsThyroid NeoplasmsExome SequencingGene Expression ProfilingGene Expression Regulation, NeoplasticHumansMutationThymus GlandTumor Microenvironmentcarcinoma showing thymus-like differentiation (CASTLE)immunotherapynext-generation sequencing (NGS)thymic carcinomatumor microenvironment (TME)tumor mutational burden (TMB)

Identifiers

PMID42074143
PMCPMC13116657

What OpenQuestion holds

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Registered trials

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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.