Evidence map›Paper›PMID 39042942›Full record

ReviewCancer science2024

Spatial omics technologies for understanding molecular status associated with cancer progression.

Satoi Nagasawa, Junko Zenkoh, Yutaka Suzuki, Ayako Suzuki

Abstract readReview
In one paragraph

Review in Cancer science, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing 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

11 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Review
  6. Review
  7. Spatial gene expression analysis reveals pathological niches in Japanese encephalitis virus neuroinvasion.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  8. Article
  9. Article
  10. Review
  11. 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

4 authors.

Satoi NagasawaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Junko ZenkohDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Yutaka SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.
Ayako SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Chiba, Japan.ORCID https://orcid.org/0000-0001-9917-2280

Funding

Japan Agency for Medical Research and Development JP23ama221522Japan Society for the Promotion of Science 22H04925
6 · The paper itself

Abstract

Cancer cells are generally exposed to numerous extrinsic stimulations in the tumor microenvironment. In this environment, cancer cells change their expression profiles to fight against circumstantial stresses, allowing their progression in the challenging tissue space. Technological advancements of spatial omics have had substantial influence on cancer genomics. This technical progress, especially that occurring in the spatial transcriptome, has been drastic and rapid. Here, we describe the latest spatial analytical technologies that have allowed omics feature characterization to retain their spatial and histopathological information in cancer tissues. Several spatial omics platforms have been launched, and the latest platforms finally attained single-cell level or even higher subcellular level resolution. We discuss several key papers elucidating the initial utility of the spatial analysis. In fact, spatial transcriptome analyses reveal comprehensive omics characteristics not only in cancer cells but also their surrounding cells, such as tumor infiltrating immune cells and cancer-associated fibroblasts. We also introduce several spatial omics platforms. We describe our own attempts to investigate molecular events associated with cancer progression. Furthermore, we discuss the next challenges in analyzing the multiomics status of cells, including their morphology and location. These novel technologies, in conjunction with spatial transcriptome analysis and, more importantly, with histopathology, will elucidate even novel key aspects of the intratumor heterogeneity of cancers. Such enhanced knowledge is expected to open a new path for overcoming therapeutic resistance and eventually to precisely stratify patients.

Indexed as

Disease ProgressionGene Expression ProfilingGenomicsNeoplasmsTranscriptomeTumor MicroenvironmentGene Expression Regulation, NeoplasticHumansSingle-Cell Analysiscancer progressionmultiomicssingle‐cell resolutionspatial transcriptometumor microenvironment

Identifiers

PMID39042942
PMCPMC11447966

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.