Evidence map›Paper›PMID 39285924›Full record

ReviewPeerJ2024

The burgeoning spatial multi-omics in human gastrointestinal cancers.

Weizheng Liang, Zhenpeng Zhu, Dandan Xu, Peng Wang, Fei Guo, Haoshan Xiao, Chenyang Hou, Jun Xue, Xuejun Zhi, Rensen Ran

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in PeerJ, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–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

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Review
  4. Article
  5. Review
  6. Review
  7. Review
  8. Review
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

10 authors.

Weizheng Liang *Central Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China.
Zhenpeng Zhu *Department of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China.
Dandan XuCentral Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China.
Peng WangDepartment of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China.
Fei GuoDepartment of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China.
Haoshan XiaoDepartment of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China.
Chenyang HouDepartment of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China.
Jun XueDepartment of Surgery, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei Province, China.
Xuejun ZhiDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China.
Rensen RanCentral Laboratory, The First Affiliated Hospital of Hebei North University, Zhangjiakou, Hebei province, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The development and progression of diseases in multicellular organisms unfold within the intricate three-dimensional body environment. Thus, to comprehensively understand the molecular mechanisms governing individual development and disease progression, precise acquisition of biological data, including genome, transcriptome, proteome, metabolome, and epigenome, with single-cell resolution and spatial information within the body's three-dimensional context, is essential. This foundational information serves as the basis for deciphering cellular and molecular mechanisms. Although single-cell multi-omics technology can provide biological information such as genome, transcriptome, proteome, metabolome, and epigenome with single-cell resolution, the sample preparation process leads to the loss of spatial information. Spatial multi-omics technology, however, facilitates the characterization of biological data, such as genome, transcriptome, proteome, metabolome, and epigenome in tissue samples, while retaining their spatial context. Consequently, these techniques significantly enhance our understanding of individual development and disease pathology. Currently, spatial multi-omics technology has played a vital role in elucidating various processes in tumor biology, including tumor occurrence, development, and metastasis, particularly in the realms of tumor immunity and the heterogeneity of the tumor microenvironment. Therefore, this article provides a comprehensive overview of spatial transcriptomics, spatial proteomics, and spatial metabolomics-related technologies and their application in research concerning esophageal cancer, gastric cancer, and colorectal cancer. The objective is to foster the research and implementation of spatial multi-omics technology in digestive tumor diseases. This review will provide new technical insights for molecular biology researchers.

Indexed as

Gastrointestinal NeoplasmsMetabolomicsProteomicsGenomicsHumansMultiomicsTranscriptomeTumor MicroenvironmentEsophageal cancerGastric cancer and colorectal cancerSpatial metabolomicsSpatial proteomicsSpatial transcriptomics

Identifiers

PMID39285924
PMCPMC11404479

What OpenQuestion holds

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LicenceCC BY
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.