Evidence map›Paper›PMID 34527184›Full record

ArticleComputational and structural biotechnology journal2021

Survival analysis across the entire transcriptome identifies biomarkers with the highest prognostic power in breast cancer.

Balázs Győrffy

Abstract read
In one paragraph

Article in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 642 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
642citing 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

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

  1. Pooled it
  2. Trial
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

582 more citing papers are in PubMed but not listed here.

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

1 author.

Balázs GyőrffySemmelweis University Dept. of Bioinformatics, Tűzoltó utca 7-9., 1094 Budapest, Hungary.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionExtensive research is directed to uncover new biomarkers capable to stratify breast cancer patients into clinically relevant cohorts. However, the overall performance ranking of such marker candidates compared to other genes is virtually absent. Here, we present the ranking of all survival related genes in chemotherapy treated basal and estrogen positive/HER2 negative breast cancer.

methodsWe searched the GEO repository to uncover transcriptomic datasets with available follow-up and clinical data. After quality control and normalization, samples entered an integrated database. Molecular subtypes were designated using gene expression data. Relapse-free survival analysis was performed using Cox proportional hazards regression. False discovery rate was computed to combat multiple hypothesis testing. Kaplan-Meier plots were drawn to visualize the best performing genes.

resultsThe entire database includes 7,830 unique samples from 55 independent datasets. Of those with available relapse-free survival time, 3,382 samples were estrogen receptor-positive and 696 were basal. In chemotherapy treated ER positive/ERBB2 negative patients the significant prognostic biomarker genes achieved hazard rates between 1.76 and 3.33 with a p value below 5.8E-04. The significant prognostic genes in adjuvant chemotherapy treated basal breast cancer samples reached hazard rates between 1.88 and 3.61 with a p value below 7.2E-04. Our integrated platform was extended enabling the validation of future biomarker candidates.

conclusionsA reference ranking for all genes in two chemotherapy treated breast cancer cohorts is presented. The results help to neglect those with unlikely clinical significance and to focus future research on the most promising candidates.

Indexed as

BiomarkersBreast cancerChemotherapyKaplan-Meier plotMolecular subtypePrognosisSurvival

Identifiers

PMID34527184
PMCPMC8339292

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.