Evidence map›Paper›PMID 31886185›Full record

ArticleBioMed research international2019

Deciphering Immune-Associated Genes to Predict Survival in Clear Cell Renal Cell Cancer.

Daixing Hu, Mi Zhou, Xin Zhu

Abstract read
In one paragraph

Article in BioMed research international, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
51citing papers in PubMed, 1 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

51 citing papers in PubMed, 1 synthesis or guideline pooled it.

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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

3 authors.

Daixing HuDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0001-6175-6694
Mi ZhouDepartment of Respiratory and Critical Care Medicine, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.
Xin ZhuDepartment of Urology, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China.ORCID https://orcid.org/0000-0002-2773-4229

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTo elucidate the correlations between tumor microenvironment and clinical characteristics as well as prognosis in clear cell renal cell cancer (ccRCC) and investigate the immune-associated genes by a comprehensive analysis of The Cancer Genome Atlas (TCGA) database.

methodsWe collected mRNA expression profiles of 537 ccRCC samples from the TCGA database. Immune scores and stromal scores were calculated by applying the ESTIMATE algorithm. We evaluated the correlation between immune/stromal scores and clinical characteristics as well as prognosis. The differentially expressed genes (DEGs) were screened between high immune/stromal score and low immune/stromal score groups by the cutoff of |log (fold change)| > 1,

resultsA higher immune score was associated with T3/4 (vs. T1/2,

conclusionsOur study elucidated tight associations between immune score and clinical characteristics as well as prognosis in ccRCC. Moreover, six DEGs were explored and validated to exert predictive values in overall survival of ccRCC.

Indexed as

Biomarkers, TumorCarcinoma, Renal CellComputational BiologyFemaleGene Expression Regulation, NeoplasticGene Regulatory NetworksHumansKaplan-Meier EstimateMalePrognosisProtein Interaction MapsTumor MicroenvironmentBiomarkers, Tumor

Identifiers

PMID31886185
PMCPMC6925759

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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.