Evidence map›Paper›PMID 34745983›Full record

ArticleFrontiers in oncology2021

PD-L1, Mismatch Repair Protein, and NTRK Immunohistochemical Expression in Cervical Small Cell Neuroendocrine Carcinoma.

Longyun Chen, Fan Yang, Ting Feng, Shafei Wu, Kaimi Li, Junyi Pang, Xiaohua Shi, Zhiyong Liang

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
1.5field-weighted citation impact, top 17% of its field
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

9 citing papers in PubMed, 12 citations in OpenAlex.

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  8. GISTs withCancers · 2022
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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 at 2 institutions in 1 country.

Longyun ChenDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Fan YangDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Ting FengDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Shafei WuDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Kaimi LiDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Junyi PangDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Xiaohua ShiDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Zhiyong LiangDepartment of Pathology, State Key Laboratory of Complex Severe and Rare Disease, Molecular Pathology Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Peking Union Medical College Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCervical small cell neuroendocrine carcinoma (SCNC) is a rare and aggressive disease that lacks a standard treatment strategy or effective methods of targeted therapy. PD-L1 inhibitors for DNA mismatch repair system-deficient (dMMR) tumors and neurotrophin receptor tyrosine kinase (NTRK) inhibitors offer potential pan-cancer treatments.

methodsImmunohistochemistry was employed as the main detection method, and any NTRK positive cases, identified by immunohistochemistry, were further submitted for evaluation by fluorescence

resultsForty-six patients were enrolled. Positive PD-L1 expression was seen in 22 of the 43 patients (51.16%) with an average combined positive score of 6.82. PD-L1-positive patients were more likely to have a higher proliferation rate in the tumor, and they experienced less recurrence and death (p = 0.048 and 0.033, respectively) compared with the patients with negative PD-L1 expression. However, in the multivariate analysis, none of the clinical parameters was associated with the expression of PD-L1. There was no association between PD-L1 expression and disease recurrence or overall survival in the Kaplan-Meier analysis. All cases were found to be MMR-stable and lacked NTRK gene fusion. However, pan-Trk expressed in 14 (32.56%) of the 43 tested cases, but FISH and RT-PCR failed to confirm any positive fusion signals in IHC-positive cases.

conclusionsPD-L1 may be an effective therapeutic target for cervical SCNC. Cervical SCNC is a MMR-stable tumor and lacks NTRK gene fusion. IHC isn't a reliable method in the detection of NTRK gene fusion in cervical SCNC.

Indexed as

Cerviximmune checkpoint inhibitormismatch repair systemNTRK fusionPD-L1small cell neuroendocrine carcinomatargeted therapy

Identifiers

PMID34745983
PMCPMC8566736
OpenAlexW3209846230

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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.