Evidence map›Paper›PMID 33854546›Full record

ArticleJournal of oncology2021

CD8

Jialing Jiang, Yi Zhao

Open access · hybridAbstract read
In one paragraph

Article in Journal of oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact, top 99% 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

1 citing paper in PubMed, 1 citations in OpenAlex.

  1. 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

2 authors at 1 institution in 1 country.

Jialing JiangDepartment of Oncology, Shengjing Hospital of China Medical University, Shenyang 110004, China.ORCID https://orcid.org/0000-0001-7715-0945
Yi ZhaoDepartment of Oncology, Shengjing Hospital of China Medical University, Shenyang 110004, China.ORCID https://orcid.org/0000-0003-1755-5582
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeTo identify CD8+ T lymphocyte-related coexpressed genes that increase CD8+ T lymphocyte proportions in breast cancer and to elucidate the underlying mechanisms among relevant genes in the tumor microenvironment.

methodWe obtained breast cancer expression matrix data and patient phenotype following information from TCGA-BRCA FPKM. Tumor purity, immune score, stromal score, and estimate score were calculated using the estimate package in R. The CD8

resultsA breast carcinoma CD8+ T lymphocyte proportion coexpression yellow module was determined. The coexpression genes in the yellow module were determined to increase the CD8+ T lymphocyte proportion levels in breast cancer patients. The yellow module was significantly enriched in the antigen presentation process, cellular response to interferon-gamma, and leukocyte proliferation. Subsequently, we generated CD8+ T cell-related genes lasso regression risk model and robust model, and eight genes were taken into the risk model. The risk score showed significant prognostic ability in various subgroups. Expression levels of proteins, encoded by CD74, were lower in the breast carcinoma samples than in normal tissue, suggesting expression differences at both the mRNA and the protein levels.

conclusionThese eight CD8+ T lymphocyte proportion coexpression genes increase CD8

Identifiers

PMID33854546
PMCPMC8019641
OpenAlexW3126121794

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.