Evidence map›Paper›PMID 39170180›Full record

ArticleHeliyon2024

The combination of exon sequencing and metabolomics to establish a molecular typing system for gastric cancer.

Shanshan Yu, Ming Chen, Xiaohua Zhu, Cheng Chen, Jinxiao Liang, Haiyong Wang, Jun Lu, Yongfeng Ding, Mei Kong, Lisong Teng and 1 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Review
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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

11 authors.

Shanshan YuDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Ming ChenDepartment of Surgical Oncology, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, 310052, China.
Xiaohua ZhuDepartment of Medical Oncology, Shaoxing People's Hospital, Shaoxing, 312000, China.
Cheng ChenDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Jinxiao LiangDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Haiyong WangDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Jun LuDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Yongfeng DingDepartment of Medical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Mei KongDepartment of Pathology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Lisong TengDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.
Donghui ZhouDepartment of Surgical Oncology, The First Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310003, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Gastric cancer (GC) is one of the most common malignant tumors in the world. It has become increasingly difficult to meet the needs of precision therapy using the existing molecular typing system. Therefore, developing a more effective molecular typing system for GC is urgent. Methods: In this study, 100 Chinese GC patients were included. Whole-exome sequencing (WES) and metabolomics analysis were performed to reveal the characteristics of genomic and metabolic changes. Results: In WES, nonsynonymous mutations accounted for the majority. Based on metabolomics, GC has been divided into three subtypes with distinct metabolic features. Importantly, we ultimately divided GC into four subtypes with different metabolic characteristics, genomic alterations, and clinical prognoses by incorporating biomics analysis. Conclusions: Integrating biological features, we constructed a novel molecular system for GC that was closely related to genetics and metabolism, providing new insights for further understanding the heterogeneity and formulating precise treatment strategies.

Indexed as

Gastric cancerHeterogeneityMetabolic dysregulationMolecular classificationWhole-exome sequencing

Identifiers

PMID39170180
PMCPMC11336309

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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.