Evidence map›Paper›PMID 36399488›Full record

ArticleNucleic acids research2023

TIMEDB: tumor immune micro-environment cell composition database with automatic analysis and interactive visualization.

Xueying Wang, Lingxi Chen, Wei Liu, Yuanzheng Zhang, Dawei Liu, Chenxin Zhou, Shuai Shi, Jiajie Dong, Zhengtao Lai, Bingran Zhao and 3 more

Abstract read
In one paragraph

Article in Nucleic acids research, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Chinese journal of cancer research = Chung-kuo yen cheng yen chiu · 2026
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  2. Article
  3. Article
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  5. Article
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  7. Nrf2 Hyperactivation as a Driver of Radiotherapy Resistance and Suppressed Antitumor Immunity in Head and Neck Squamous Cell Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2025
    Article
  8. Article
  9. Article
  10. Article
  11. Review
  12. CD4Science advances · 2025
    Article
  13. Article
  14. Article
  15. Article
  16. Article
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  18. Article
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

13 authors.

Xueying WangDepartment of Computer Science, City University of Hong Kong, Hong Kong, China.ORCID 0000-0001-8979-3737
Lingxi ChenDepartment of Computer Science, City University of Hong Kong, Hong Kong, China.ORCID 0000-0002-5229-7470
Wei LiuDepartment of Computer Science, City University of Hong Kong, Hong Kong, China.
Yuanzheng ZhangSchool of Medicine and Biological Information Engineering, Northeastern University, Shenyang, Liaoning, China.
Dawei LiuSchool of Software, Northeastern University, Shenyang, Liaoning, China.
Chenxin ZhouSchool of Business Administration, Northeastern University, Shenyang, Liaoning, China.
Shuai ShiSchool of Creative Media, City University of Hong Kong, Hong Kong, China.
Jiajie DongDepartment of Computer Science, City University of Hong Kong, Hong Kong, China.
Zhengtao LaiSchool of Business Administration, Northeastern University, Shenyang, Liaoning, China.
Bingran ZhaoSchool of Business Administration, Northeastern University, Shenyang, Liaoning, China.
Wenjingyu ZhangSchool of Business Administration, Northeastern University, Shenyang, Liaoning, China.
Haoyue ChengDepartment of Clinical Pathology, Capital Medical University, Beijing, China.
Shuaicheng LiDepartment of Computer Science, City University of Hong Kong, Hong Kong, China.ORCID 0000-0001-6246-6349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Deciphering the cell-type composition in the tumor immune microenvironment (TIME) can significantly increase the efficacy of cancer treatment and improve the prognosis of cancer. Such a task has benefited from microarrays and RNA sequencing technologies, which have been widely adopted in cancer studies, resulting in extensive expression profiles with clinical phenotypes across multiple cancers. Current state-of-the-art tools can infer cell-type composition from bulk expression profiles, providing the possibility of investigating the inter-heterogeneity and intra-heterogeneity of TIME across cancer types. Much can be gained from these tools in conjunction with a well-curated database of TIME cell-type composition data, accompanied by the corresponding clinical information. However, currently available databases fall short in data volume, multi-platform dataset integration, and tool integration. In this work, we introduce TIMEDB (https://timedb.deepomics.org), an online database for human tumor immune microenvironment cell-type composition estimated from bulk expression profiles. TIMEDB stores manually curated expression profiles, cell-type composition profiles, and the corresponding clinical information of a total of 39,706 samples from 546 datasets across 43 cancer types. TIMEDB comes readily equipped with online tools for automatic analysis and interactive visualization, and aims to serve the community as a convenient tool for investigating the human tumor microenvironment.

Indexed as

NeoplasmsDatabases, FactualHumansSequence Analysis, RNATumor Microenvironment

Identifiers

PMID36399488
PMCPMC9825442

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.