Evidence map›Paper›PMID 33323544›Full record

ArticleAging2020

A TP53-based immune prognostic model for muscle-invasive bladder cancer.

Hongyan Li, Huayi Lu, Wanli Cui, Yufan Huang, Xuefei Jin

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Aging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.6field-weighted citation impact, top 30% 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

9 citing papers in PubMed, 12 citations in OpenAlex.

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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

5 authors at 3 institutions in 1 country.

Hongyan LiJilin Key Laboratory of Urologic Oncology, Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, China.
Huayi LuThe First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, China.
Wanli CuiJilin Key Laboratory of Urologic Oncology, Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, China.
Yufan HuangJilin Key Laboratory of Urologic Oncology, Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, China.
Xuefei JinJilin Key Laboratory of Urologic Oncology, Department of Urology, China-Japan Union Hospital of Jilin University, Changchun, China.
Jilin University · CNUnion Hospital · CNUniversity of Science and Technology of China · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMuscle-invasive bladder cancer (MIBC) patients are subject to unfavorable treatment options and a high recurrence rate. The status of TP53 mutations played an essential role in the progression and the prognosis of MIBC. The present study proposed to investigate the association between TP53 mutations and immunophenotype in MIBC.

resultsWe established an immune prognostic model (IPM) ground on the immune-associated genes derived from variation analysis between wild-type TP53 and mutated TP53 TCGA-MIBC patients, and validated in another cohort from GEO database. Based on IPM, we divided MIBC patients into low and high risk subgroups. The high risk MIBC patients had higher proportions of macrophages M1, and lower proportions of T cells regulatory (Tregs) and activated dendritic cells than the low risk MIBC patients. Moreover, the expression of immune checkpoints genes (PD1, CTLA4, LAG3, HAVCR2 and TIGIT) was higher in the high risk patients than the low risk patients. In clinical application, IPM exhibited better survival prediction than conventional clinical characteristics.

conclusionsOur investigation presented practical prognostic significance for MIBC patients and displayed the overarching landscape of the immune response in the MIBC microenvironment.

methodsData were obtained from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO). Differentially expressed genes (DEGs) analysis between the TP53 mutated and wild-type MIBC patients was conducted. The CIBERSORT algorithm was performed to evaluate the proportion of immune cell types. Gene expression profiles from the TCGA and GEO were used as training and testing cohorts to build and validate an immune-related prognostic model (IPM). Genes in the IPM model were first screened by univariate Cox analysis, then filtered by the least absolute shrinkage and selection operator (LASSO) Cox regression. A nomogram was finally established and evaluated by combining both the IPM and other clinical factors.

Indexed as

Antigens, CDCarcinoma, Transitional CellCTLA-4 AntigenDatabases, GeneticDendritic CellsHepatitis A Virus Cellular Receptor 2HumansKaplan-Meier EstimateLymphocyte Activation Gene 3 ProteinMacrophagesMuscle, SmoothMutationNeoplasm InvasivenessNomogramsPrognosisProgrammed Cell Death 1 ReceptorAntigens, CDCTLA-4 AntigenCTLA4 protein, humanHAVCR2 protein, humanHepatitis A Virus Cellular Receptor 2Lag3 protein, humanLymphocyte Activation Gene 3 ProteinPDCD1 protein, humanProgrammed Cell Death 1 ReceptorReceptors, ImmunologicTIGIT protein, humanTP53 protein, humanTumor Suppressor Protein p53immune checkpointsimmune prognostic modelimmune responseMIBCTP53

Identifiers

PMID33323544
PMCPMC7880361
OpenAlexW3112004314

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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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.