Evidence map›Paper›PMID 36083304›Full record

ArticleApplied microbiology and biotechnology2022

Characteristics of gastric cancer gut microbiome according to tumor stage and age segmentation.

Changchang Chen, Yaoqiang Du, Yanxin Liu, Yongkang Shi, Yaofang Niu, Gulei Jin, Jian Shen, Jianxin Lyu, Lijun Lin

Abstract read
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In one paragraph

Article in Applied microbiology and biotechnology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 pooled it
1.1field-weighted citation impact, top 23% 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

12 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.

  1. Pooled it
  2. Revisiting multi-region 16S sequencing in gastric cancer.World journal of gastrointestinal oncology · 2026
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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

9 authors at 3 institutions in 1 country.

Changchang Chen *School of Laboratory Medicine, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Yaoqiang Du *Laboratory Medicine Center, Department of Transfusion Medicine, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China.
Yanxin Liu *School of Basic Medicine and Forensic Medicine, Hangzhou Medical College, Hangzhou, Zhejiang, China.
Yongkang ShiGeneral Surgery, Cancer Center, Department of Gastrointestinal and Pancreatic Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China.
Yaofang NiuHangzhou Guhe Information and Technology Company, Hangzhou, Zhejiang, China.
Gulei JinHangzhou Guhe Information and Technology Company, Hangzhou, Zhejiang, China.
Jian ShenDepartment of Medical Administration, Zhejiang Provincial People's Hospital (Affiliated People's Hospital, Hangzhou Medical College), Hangzhou, Zhejiang, China.
Jianxin LyuSchool of Laboratory Medicine, Hangzhou Medical College, Hangzhou, Zhejiang, China. ljx@hmc.edu.cn.
Lijun LinSchool of Basic Medicine and Forensic Medicine, Hangzhou Medical College, Hangzhou, Zhejiang, China. llj0208@hmc.edu.cn.ORCID http://orcid.org/0000-0003-4522-0827
Zhejiang Provincial People's Hospital · CNHangzhou Medical College · CNZhejiang Science and Technology Information Institute · CN

Funding

Natural Science Foundation of Zhejiang Province LQ21H200007Zhejiang Provincial Ten Thousand Plan for Outstanding Talents 00004A51901Zhejiang Xinmiao Talents Program 2022R424B009
6 · The paper itself

Abstract

With the development of 16S rRNA technology, gut microbiome evaluation has been performed in many diseases, including gastrointestinal tumors. Among these cancers, gastric cancer (GC) exhibits high morbidity and mortality and has been extensively studied in its pathogenesis and diagnosis techniques. The current researches have proved that the gut microbiome may have the potential to distinguish GC patients from healthy patients. However, the change of the gut microbiome according to tumor node metastasis classification (TNM) has not been clarified. Besides, the characteristics of gut microbiome in GC patients and their ages of onset are also ambiguous. To address the above shortcomings, we investigated 226 fecal samples and divided them according to their tumor stage and onset age. The findings revealed that surgery and tumor stage can change the characteristic of GC patients' gut microbiota. In specific, the effect of surgery on early gastric cancer (EGC) was greater than that on advanced gastric cancer (AGC), and the comparison of postoperative microflora with healthy people indicated that EGC has more differential bacteria than AGC. Besides, we found that Collinsella, Blautia, Anaerostipes, Dorea, and Lachnospiraceae_ND3007_group expressed differently between EGC and AGC. More importantly, it is the first time revealed that the composition of gut microbiota in GC is different between different onset ages. KEY POINTS: •Gut microbiota of gastric cancer (GC) patients are either highly associated with TNM stage and surgery or not. It shows surgery has more significant changes in early gastric cancer (EGC) than advanced gastric cancer (AGC). •There existed specific gut microbiota between EGC and AGC which may have potential to distinguish the early or advanced GC. •Onset age of GC may influence the gut microbiota: the composition of gut microbiota of early-onset gastric cancer (EOGC) and late-onset gastric cancer (LOGC) is significantly different.

Indexed as

Gastrointestinal MicrobiomeStomach NeoplasmsBacteriaFecesHumansRNA, Ribosomal, 16SRNA, Ribosomal, 16S16S rRNAGastric cancerGut microbiotaOnset ageTumor biomarkersTumor stage

Identifiers

PMID36083304
OpenAlexW4295087994

What OpenQuestion holds

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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.