Evidence map›Paper›PMID 42427482›Full record

ReviewMediastinum (Hong Kong, China)2026

Mediastinal epithelial neoplasms with recurrent molecular alterations.

Michael W Mikula, Ezra Baraban

Abstract readReview
In one paragraph

Review in Mediastinum (Hong Kong, China), 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

2 authors.

Michael W MikulaDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.ORCID https://orcid.org/0000-0002-1873-8340
Ezra BarabanDepartment of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A wide variety of benign and malignant epithelial tumors arise in the mediastinum. This review sheds light on recurrent molecular genetic alterations of mediastinal epithelial tumors to help the surgical pathologist become aware of molecularly defined entities that one may encounter in practice and understand relevant genetic underpinnings, with an emphasis on diagnostically useful immunohistochemical targets. We discuss the molecular landscape of thymoma, including World Health Organization (WHO) types as well as micronodular and metaplastic thymoma, and introduce current concepts in the molecular subtyping of thymic carcinoma. We present an overview of proposed molecular classification schemes of thymic epithelial neoplasms that focuses on commonly occurring molecular alterations described in The Cancer Genome Atlas and original data sources, and relate them to longitudinal prognostic and therapeutic implications. Poorly differentiated epithelial neoplasms of the mediastinum defined by recurrent molecular alterations can display diagnostically challenging morphologic and immunohistochemical profiles and are critically important to recognize due to their aggressive behavior. We conclude with a discussion of NUT carcinoma and switch/sucrose non-fermentable (SWI/SNF) complex deficient tumors, including thoracic SMARCA4-deficient undifferentiated tumor, reviewing salient histopathologic and immunohistochemical features that allow their recognition from histologic mimics and tumors with overlapping immunoprofiles. We lastly outline the current understanding of genetic events that give rise to these destructive tumors.

Indexed as

metaplastic thymomamicronodular thymoma with lymphoid stromaNUT carcinomathoracic SMARCA4-deficient undifferentiated tumorThymoma

Identifiers

PMID42427482
PMCPMC13346009

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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.