Evidence map›Paper›PMID 36912931›Full record

ArticleCancer immunology, immunotherapy : CII2023

CiTSA: a comprehensive platform provides experimentally supported signatures of cancer immunotherapy and analysis tools based on bulk and scRNA-seq data.

Feng Li, Kejing Dong, Chunlong Zhang, Jingwen Wang, Yongjuan Tang, Ke Xue, Xuan Zheng, Kaiyue Song, Xiaomeng Zhang, Mengyue Li and 5 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Cancer immunology, immunotherapy : CII, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. 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

15 authors.

Feng Li *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Kejing Dong *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Chunlong Zhang *College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Jingwen WangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yongjuan TangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Ke XueCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xuan ZhengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Kaiyue SongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xiaomeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Mengyue LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Rui ZhaoCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Xiaoling ZhongCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China.
Yanjun XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. xuyanjun@hrbmu.edu.cn.
Yunpeng ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. zhangyp@hrbmu.edu.cn.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China. lixia@hrbmu.edu.cn.

Funding

Heilongjiang Province Natural Science Foundation Joint guidance Project LH2022F042National Key R&D Program of China 2018YFC2000100National Natural Science Foundation of China 32070622National Natural Science Foundation of China 62101164National Natural Science Foundation of China 62172131the China Brain Project 2021ZD0202403the China Postdoctoral Science Foundation 2019M661295the China Postdoctoral Science Special Foundation 2020T130162the Doctor Green Seedlings Breaking Ground Project of Harbin Medical University QMPT-2010
6 · The paper itself

Abstract

Immunotherapy has greatly changed the status of cancer treatment, and many patients do not respond or develop acquired resistance. The related research is blocked by lacking of comprehensive resources for researchers to discovery and analysis signatures, then further exploring the mechanisms. Here, we first offered a benchmarking dataset of experimentally supported signatures of cancer immunotherapy by manually curated from published literature works and provided an overview. We then developed CiTSA ( http://bio-bigdata.hrbmu.edu.cn/CiTSA/ ) which stores 878 entries of experimentally supported associations between 412 signatures such as genes, cells, and immunotherapy across 30 cancer types. CiTSA also provides flexible online tools to identify and visualize molecular/cell feature and interaction, to perform function, correlation, and survival analysis, and to execute cell clustering, cluster activity, and cell-cell communication analysis based on single cell and bulk datasets of cancer immunotherapy. In summary, we provided an overview of experimentally supported cancer immunotherapy signatures and developed CiTSA which is a comprehensive and high-quality resource and is helpful for understanding the mechanism of cancer immunity and immunotherapy, developing novel therapeutic targets and promoting precision immunotherapy for cancer.

Indexed as

NeoplasmsSingle-Cell Gene Expression AnalysisHumansImmunotherapyBiomarkersCancer immunotherapyscRNA-seqTumor microenvironment

Identifiers

PMID36912931
PMCPMC10992169

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.