Evidence map›Paper›PMID 42052477›Full record

ArticleFrontiers in oncology2026

Thoracic SMARCA4-deficient undifferentiated tumor prone to misdiagnosis as lung adenocarcinoma: a case report and literature review.

Xiuwen Yu, Ying Cai, Haiyan Wu, Hongsheng Liu, Bin Huang

Abstract readCase Reports
In one paragraph

Article in Frontiers in oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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.

Xiuwen YuDepartment of Respiratory Medicine, The First People's Hospital of Xiaoshan District, Hangzhou, Zhejiang, China.
Ying CaiDepartment of Respiratory Medicine, The First People's Hospital of Xiaoshan District, Hangzhou, Zhejiang, China.
Haiyan WuDepartment of Respiratory Medicine, The First People's Hospital of Xiaoshan District, Hangzhou, Zhejiang, China.
Hongsheng LiuDepartment of Pathology, The First People's Hospital of Xiaoshan District, Hangzhou, Zhejiang, China.
Bin HuangDepartment of Pathology, The First People's Hospital of Xiaoshan District, Hangzhou, Zhejiang, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thoracic SMARCA4-deficient undifferentiated tumor (T-SMARCA4-DUT) is a rare neoplastic entity with a high risk of being misdiagnosed. We report the case of a 64-year-old male initially suspected of having mediastinal lymphoma by contrast-enhanced chest computed tomography (CECCT), and pathologically diagnosed with metastatic poorly differentiated lung adenocarcinoma via cervical lymph node biopsy. Initial immunohistochemical (IHC) results showed TTF-1 (clone SPT24) (+), Napsin A (-), p40 (-), and next-generation sequencing (NGS) detected KRAS amplification and TP53 missense mutation. Combined chemotherapy plus immunotherapy initially shrank the tumor, but bilateral axillary lymphadenopathy subsequently developed. Pathological analysis of axillary metastases and supplementary IHC of the original cervical biopsy revealed SMARCA4/Brg1 (-), SOX2 (+) and TTF-1 (clone 8G7G3/1) (-), leading to a revised diagnosis of lymph node-metastatic T-SMARCA4-DUT. This case identifies the non-specific clinical features of T-SMARCA4-DUT and an inadequate initial IHC panel as the core causes for misdiagnosis and confirms that a definitive diagnosis requires testing for SMARCA4/Brg1, SOX2, and the highly specific TTF-1 (clone 8G7G3/1).

Indexed as

lung adenocarcinomamisdiagnosisSMARCA4-deficientthoraxundifferentiated tumor

Identifiers

PMID42052477
PMCPMC13111305

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.