Evidence map›Paper›PMID 34573332›Full record

ArticleGenes2021

Multi-Dimensional Scaling Analysis of Key Regulatory Genes in Prostate Cancer Using the TCGA Database.

Laura Boldrini, Pinuccia Faviana, Luca Galli, Federico Paolieri, Paola Anna Erba, Massimo Bardi

Open access · goldAbstract read
In one paragraph

Article in Genes, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-weighted citation impact, top 35% 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

3 citing papers in PubMed, 3 citations in OpenAlex.

  1. Article
  2. Genes · 2023
    Article
  3. 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

6 authors at 2 institutions in 2 countries.

Laura BoldriniDepartment of Surgical, Medical, Molecular Pathology and Critical Area, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0001-5904-3708
Pinuccia FavianaDepartment of Surgical, Medical, Molecular Pathology and Critical Area, University of Pisa, 56126 Pisa, Italy.ORCID 0000-0003-4283-1083
Luca GalliDepartment of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy.
Federico PaolieriDepartment of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy.
Paola Anna ErbaDepartment of Translational Research and New Technologies in Medicine and Surgery, University of Pisa, 56126 Pisa, Italy.
Massimo BardiDepartment of Psychology & Behavioral Neuroscience, Randolph-Macon College, Ashland, VA 23005, USA.
University of Pisa · ITRandolph–Macon College · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prostate cancer (PC) is a polygenic disease with multiple gene interactions. Therefore, a detailed analysis of its epidemiology and evaluation of risk factors can help to identify more accurate predictors of aggressive disease. We used the transcriptome data from a cohort of 243 patients from the Cancer Genome Atlas (TCGA) database. Key regulatory genes involved in proliferation activity, in the regulation of stress, and in the regulation of inflammation processes of the tumor microenvironment were selected to test a priori multi-dimensional scaling (MDS) models and create a combined score to better predict the patients' survival and disease-free intervals. Survival was positively correlated with

Indexed as

Gene Expression Regulation, NeoplasticAgedCell ProliferationDatabases, GeneticDisease-Free SurvivalDNA RepairHumansMaleMiddle AgedModels, GeneticProstatic NeoplasmsRegression Analysisinflammationproliferationstresssurvival predictionurological cancer

Identifiers

PMID34573332
PMCPMC8468120
OpenAlexW3197937511

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.