Evidence map›Paper›PMID 37064128›Full record

ArticleFrontiers in oncology2023

Clinical characterization and genomic landscape of gynecological cancers among patients attending a Chinese hospital.

Cen Jiang, Yiyi Lu, Hua Liu, Gang Cai, Zhao Peng, Weiwei Feng, Lin Lin

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 30% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. 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

7 authors at 2 institutions in 1 country.

Cen JiangDepartment of Laboratory Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Yiyi LuDepartment of Laboratory Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Hua LiuDepartment of Obstetrics & Gynecology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Gang CaiDepartment of Laboratory Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Zhao PengGenecast Biotechnology Co., Ltd., Wuxi, China.
Weiwei FengDepartment of Obstetrics & Gynecology, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Lin LinDepartment of Laboratory Medicine, Ruijin Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.
Ruijin Hospital · CNGenecast (China) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gynecological cancers are the most lethal malignancies among females, most of which are associated with gene mutations. Few studies have compared the differences in the genomic landscape among various types of gynecological cancers. In this study, we evaluated the diversity of mutations in different gynecological cancers. Methods: A total of 184 patients with gynecological cancer, including ovarian, cervical, fallopian tube, and endometrial cancer, were included. Next-generation sequencing was performed to detect the mutations and tumor mutational burden (TMB). Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) enrichment analyses were also conducted. Results: We found that 94.57% of patients had at least one mutation, among which single nucleotide variants, insertions and InDels were in the majority. Conclusion: Various gynecological cancer types share similarities and differences both in clinical characterization and genomic mutations. Taken together with the results of TMB and enriched pathways, this study provided useful information on the molecular mechanism underlying gynecological cancers and the development of targeted drugs and precision medicine.

Indexed as

BRCA1BRCA2FGFR3gynecological cancernext-generation sequencingTMB

Identifiers

PMID37064128
PMCPMC10101327
OpenAlexW4361280882

What OpenQuestion holds

Textmetadata
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.