Evidence map›Paper›PMID 25381064›Full record

ReviewJournal of cancer research and clinical oncology2015

T-cell-associated cellular immunotherapy for lung cancer.

Ke Li, Qing Zhang, Yang Zhang, Jie Yang, Junnian Zheng

Abstract readReview
In one paragraph

Review in Journal of cancer research and clinical oncology, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 2 pooled it
–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

12 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Review
  4. Association between CD4Oncology letters · 2024
    Article
  5. Article
  6. Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Immunotherapy for lung cancer: advances and prospects.American journal of clinical and experimental immunology · 2016
    Review
  12. 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

5 authors.

Ke LiJiangsu Key Laboratory of Biological Cancer Therapy, Xuzhou Medical College, West Huaihai Road 84#, Xuzhou, 221002, Jiangsu, China.
Qing Zhang
Yang Zhang
Jie Yang
Junnian Zheng

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeThe aim of the present study was to discuss recent findings on the role of T cells in lung cancer to provide information on their potential application, especially in cellular immunotherapy.

methodsData on the different types of T cells that are currently used for the treatment of lung cancer were obtained by searching the PUBMED database.

resultsCytotoxic T lymphocytes, natural killer T cells, γδ T cells, lymphokine-activated killer cells, tumor-infiltrating lymphocytes, cytokine-induced killer cells and gene-modified T cells were analyzed to determine the benefits and drawbacks of their application in the treatment of lung cancer. Advances in the study of their antitumor mechanisms and directions for future research were discussed.

conclusionsT cells are critical for tumorigenesis and therefore important targets for the treatment of lung cancer. T-cell-associated cellular immunotherapy opens up a window of opportunity for the development of complementary methods to traditional lung cancer treatments, which warrants further investigation to improve the clinical outcomes of lung cancer patients.

Indexed as

Cytokine-Induced Killer CellsCytotoxicity, ImmunologicHumansImmunotherapy, AdoptiveKiller Cells, Lymphokine-ActivatedKiller Cells, NaturalLung NeoplasmsLymphocytes, Tumor-InfiltratingT-LymphocytesT-Lymphocytes, Cytotoxic

Identifiers

PMID25381064
PMCPMC11823499

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.