Evidence map›Paper›PMID 37091230›Full record

ArticleiScience2023

Prioritizing exhausted T cell marker genes highlights immune subtypes in pan-cancer.

Chunlong Zhang, Qi Sheng, Xue Zhang, Kang Xu, Xiaoyan Jin, Weiwei Zhou, Mengying Zhang, Dezhong Lv, Changbo Yang, Yongsheng Li and 2 more

Open access · goldAbstract read
In one paragraph

Article in iScience, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
3.5field-weighted citation impact, top 7% of its field
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

14 citing papers in PubMed, 15 citations in OpenAlex.

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  6. KLRG1 defines a distinct tumor-infiltrating granzyme K+ CD8 + T cell population.Journal of cancer research and clinical oncology · 2026
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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

12 authors at 3 institutions in 1 country.

Chunlong ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Qi ShengCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Xue ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Kang XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Xiaoyan JinCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Weiwei ZhouCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Mengying ZhangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Dezhong LvCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Changbo YangCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Yongsheng LiKey Laboratory of Tropical Translational Medicine of Ministry of Education, College of Biomedical Information and Engineering, Hainan Women and Children's Medical Center, Hainan Medical University, Haikou, Hainan 571199, China.
Juan XuCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Xia LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, Heilongjiang 150081, China.
Harbin Medical University · CNHainan Medical University · CNNortheast Forestry University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Exhausted T (TEX) cells are main immunotherapy targets in cancer, but it lacks a general identification method to characterize TEX cell in disease. To assess the characterization of TEX cell, we extract signature of TEX cell from large cancer and chronic infection cohorts. Based on single-cell transcriptomes, a systematic T cell exhaustion prediction (TEXP) model is designed to define TEX cell in cancer and chronic infection. We then prioritize 42 marker genes, including

Indexed as

BioinformaticsCancerImmunologyTranscriptomics

Identifiers

PMID37091230
PMCPMC10119613
OpenAlexW4360602120

What OpenQuestion holds

Textmetadata
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.