Evidence map›Paper›PMID 35392240›Full record

ArticleFrontiers in oncology2022

Gene Expression and Mutational Landscape in a PMEC Patient With Low to Intermediate-High Grade Transition.

Weijie Dong, Bing Zhu, Yan You, Bing Wang, Dan Fu, Daoxin Wang, He Li, Changyi Li

Abstract read
In one paragraph

Article in Frontiers in oncology, 2022. 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

8 authors.

Weijie DongDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Bing ZhuDepartment of Thoracic Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Yan YouDepartment of Pathology, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Bing WangDepartment of Thoracic Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Dan FuThe Medical Department, 3D Medicines Inc., Shanghai, China.
Daoxin WangDepartment of Thoracic Surgery, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
He LiDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Changyi LiDepartment of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Primary pulmonary mucoepidermoid carcinoma (PMEC) is a very rare form of lung carcinoma. Due to the low incidence, little is known about its inherent genetic variation characteristics. The uniform treatment for PMEC has not been determined. In this case, we present a 45-year-old male with stage IA PMEC. The surgical specimens contained changes from low- to intermediate-to-high grade. We performed integrative analysis of whole-exome sequencing (WES-seq) and messenger ribonucleic acid sequencing (RNA-seq) to compare the molecular changes in the different lesions. Molecular testing exhibits the specimens harboring CRTC3-MAML2 fusion. The copy number gain of PDPK1 is only present in high-grade regional specimens. We also explored the level of immune infiltration by CIBERSORT. To our knowledge, this is the first report to describe a case of PMEC in the low- to intermediate-high-grade transition with multiomics analysis.

Indexed as

CRTC1-MAML2 and CRTC3-MAML2 fusionPDPK1primary pulmonary mucoepidermoid carcinomaRNA-seqWES-seq

Identifiers

PMID35392240
PMCPMC8980482

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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.