Evidence map›Paper›PMID 33563042›Full record

ArticleExperimental biology and medicine (Maywood, N.J.)2021

Identification of 6 gene markers for survival prediction in osteosarcoma cases based on multi-omics analysis.

Runmin Li, Guosheng Wang, ZhouJie Wu, HuaGuang Lu, Gen Li, Qi Sun, Ming Cai

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

Article in Experimental biology and medicine (Maywood, N.J.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 53% 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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Review
  2. Review
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

7 authors at 2 institutions in 1 country.

Runmin LiDepartment of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.
Guosheng WangInstitute of Translational Medicine, Zhejiang University School of Medicine, Hangzhou 310029, China.
ZhouJie WuDepartment of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.
HuaGuang LuDepartment of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.
Gen LiDepartment of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.
Qi SunDepartment of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.
Ming CaiDepartment of Orthopaedics, Shanghai Tenth People's Hospital, Tongji University, School of Medicine, Shanghai 200072, China.ORCID 0000-0002-0020-0585
Tongji University · CNZhejiang University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Multiple-omics sequencing information with high-throughput has laid a solid foundation to identify genes associated with cancer prognostic process. Multiomics information study is capable of revealing the cancer occurring and developing system according to several aspects. Currently, the prognosis of osteosarcoma is still poor, so a genetic marker is needed for predicting the clinically related overall survival result. First, Office of Cancer Genomics (OCG Target) provided RNASeq, copy amount variations information, and clinically related follow-up data. Genes associated with prognostic process and genes exhibiting copy amount difference were screened in the training group, and the mentioned genes were integrated for feature selection with least absolute shrinkage and selection operator (Lasso). Eventually, effective biomarkers received the screening process. Lastly, this study built and demonstrated one gene-associated prognosis mode according to the set of the test and gene expression omnibus validation set; 512 prognosis-related genes (

Indexed as

Basic Helix-Loop-Helix ProteinsBiomarkers, TumorBone NeoplasmsComputational BiologyDNA-Binding ProteinsHumansMatrix Metalloproteinases, SecretedNeoplasm ProteinsOsteosarcomaProportional Hazards ModelsProto-Oncogene Proteins c-mycReceptors, G-Protein-CoupledTranscription FactorsBasic Helix-Loop-Helix ProteinsBiomarkers, TumorCHIC2 protein, humanDNA-Binding ProteinsGPR142 protein, humanLYL1 protein, humanMatrix Metalloproteinases, SecretedMMP27 protein, humanMYC protein, humanNeoplasm ProteinsProto-Oncogene Proteins c-mycReceptors, G-Protein-CoupledTranscription FactorsBioinformaticscopy amount variationgene expression omnibusosteosarcomaprognostic marker

Identifiers

PMID33563042
PMCPMC8283252
OpenAlexW3127720129

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.