Evidence map›Paper›PMID 36071046›Full record

ArticleNature communications2022

Integrated cohort of esophageal squamous cell cancer reveals genomic features underlying clinical characteristics.

Minghao Li, Zicheng Zhang, Qianrong Wang, Yan Yi, Baosheng Li

Abstract read
In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.

0numbers the graph read from it
0cells of the map it votes in
24citing 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

24 citing papers in PubMed.

  1. Trial
  2. Article
  3. Review
  4. Esophageal cancer: from pathogenesis to precision therapies.Signal transduction and targeted therapy · 2026
    Review
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. EarlybioRxiv : the preprint server for biology · 2025
    Article
  11. Article
  12. Review
  13. Article
  14. Article
  15. Article
  16. Article
  17. Review
  18. Article
  19. Article
  20. 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

5 authors.

Minghao Li *Cheeloo College of Medicine, Shandong University, 250012, Jinan, Shandong, China.
Zicheng Zhang *Department of Radiation Oncology, Shenzhen Traditional Chinese Medicine Hospital, The Fourth Clinical Medical College of Guangzhou University of Chinese Medicine, Shenzhen, China.
Qianrong WangThe Third Affiliated Hospital of Shandong First Medical University, Jinan, Shandong Province, China.
Yan YiShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China.
Baosheng LiCheeloo College of Medicine, Shandong University, 250012, Jinan, Shandong, China. bsli@sdfmu.edu.cn.ORCID http://orcid.org/0000-0002-5390-7269

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Esophageal squamous cell cancer (ESCC) is the major pathologic type of esophageal cancer in Asian population. To systematically evaluate the mutational features underlying clinical characteristics, we establish the integrated dataset of ESCC-META that consists of 1930 ESCC genomes from 33 datasets. The data process pipelines lead to well homogeneity of this integrated cohort for further analysis. We identified 11 mutational signatures in ESCC, some of which are related to clinical features, and firstly detect the significant mutated hotspots in TGFBR2 and IRF2BPL. We screen the survival related mutational features and found some genes had different prognostic impacts between early and late stage, such as PIK3CA and NFE2L2. Based on the results, an applicable approach of mutational score is proposed and validated to predict prognosis in ESCC. As an open-sourced, quality-controlled and updating mutational landscape, the ESCC-META dataset could facilitate further genomic and translational study in this field.

Indexed as

Carcinoma, Squamous CellEsophageal NeoplasmsEsophageal Squamous Cell CarcinomaCarrier ProteinsEpithelial CellsGenomicsHumansNuclear ProteinsCarrier ProteinsIRF2BPL protein, humanNuclear Proteins

Identifiers

PMID36071046
PMCPMC9452532

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.