Evidence map›Paper›PMID 33585188›Full record

ArticleFrontiers in oncology2020

Immune Cluster and PPI Network Analyses Identified CXCR3 as a Key Node of Immunoregulation in Head and Neck Cancer.

Ping Wang, Yanli Wang, Yuanjun Jiang, Minghong Li, Guang Li, Qiao Qiao

Open access · goldAbstract read
In one paragraph

Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.4field-weighted citation impact, top 39% 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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Targeting CXCL9/10/11-CXCR3 axis: an important component of tumor-promoting and antitumor immunity.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2023
    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

6 authors at 2 institutions in 1 country.

Ping WangDepartment of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China.
Yanli WangDepartment of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China.
Yuanjun JiangDepartment of Urology, The First Hospital of China Medical University, Shenyang, China.
Minghong LiDepartment of Otolaryngology, The First Hospital of China Medical University, Shenyang, China.
Guang LiDepartment of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China.
Qiao QiaoDepartment of Radiation Oncology, The First Hospital of China Medical University, Shenyang, China.
China Medical University · CNFirst Hospital of China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The tumor microenvironment (TME) is significantly associated with clinical outcomes and therapeutic efficacy. However, the landscape of the head and neck cancer (HNC) microenvironment is not fully understood. Therefore, we divided HNCs into three classes according to differences in the TME to determine effective personalized treatments. We explored the immune landscape of head and neck cancer by analysing the gene expression profile of 501 cases from the Cancer Genome Atlas (TCGA) data portal and validated our findings in 270 cases from the Gene Expression Omnibus (GEO) database. The levels of immune components in the tumor microenvironment were evaluated

Indexed as

head and neck cancerprognosissingle-sample gene set enrichment analysisthe Cancer Genome Atlastreatmenttumor microenvironment

Identifiers

PMID33585188
PMCPMC7874192
OpenAlexW3120689639

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.