Evidence map›Paper›PMID 42674823›Full record

ReviewCancer genomics & proteomics

Mutual Information-based Prognostic Biomarker Discovery in Cancer Genomics: Conceptual Framework and Representative Applications of MI-POG.

Kazunori Akimoto, Shoma Tamori, Keiko Sato

Abstract readReview
In one paragraph

Review in Cancer genomics & proteomics. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Kazunori AkimotoDepartment of Medicinal and Life Sciences, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Tokyo, Japan; akimoto@rs.tus.ac.jp.
Shoma TamoriDepartment of Medicinal and Life Sciences, Faculty of Pharmaceutical Sciences, Tokyo University of Science, Tokyo, Japan.
Keiko SatoResearch Division of Medical Data Science, Research Institute for Science and Technology, Tokyo University of Science, Noda, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Mutual information (MI)-based approaches have increasingly been applied to cancer genomics; however, their use for genome-wide prognostic biomarker discovery remains relatively underexplored. The present article summarizes the conceptual workflow of Mutual Information-based Prognostic Omics Gene (MI-POG) based on previously published applications in breast cancer, lower-grade glioma, and other cancer datasets. The framework consists of clinical endpoint discretization, genome-wide MI-based screening, candidate ranking, and downstream validation using conventional survival-analysis approaches. Previous MI-POG applications identified solute carrier family 20 member 1 (

Indexed as

Biomarkers, TumorGenomicsNeoplasmsHumansPrognosisBiomarkers, Tumorcancer genomicsMI-POGMutual informationprecision oncologyprognostic biomarker

Identifiers

PMID42674823
PMCPMC13531165

What OpenQuestion holds

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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.