Evidence map›Paper›PMID 39738156›Full record

ArticleNature communications2024

The Theranostic Genome.

Xiaoying Xu, Pablo Jané, Vincent Taelman, Eduardo Jané, Rebecca A Dumont, Yonathan Garama, Francisco Kim, María Del Val Gómez, Karim Gariani, Martin A Walter

Abstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Applications of artificial intelligence in nuclear medicine.Zeitschrift fur medizinische Physik · 2026
    Review
  2. [ACS omega · 2026
    Article
  3. Article
  4. Article
  5. 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

10 authors.

Xiaoying Xu *University of Lucerne, Lucerne, LU, Switzerland.ORCID 0000-0003-3188-2125
Pablo Jané *University of Geneva, Geneva, GE, Switzerland.ORCID 0000-0002-6723-1108
Vincent Taelman *University of Lucerne, Lucerne, LU, Switzerland.
Eduardo JanéDepartamento de Matemática Aplicada a la Ingeniería Aeroespacial - ETSIAE, Universidad Politécnica de Madrid, 28040, Madrid, Spain.ORCID 0000-0003-2848-3406
Rebecca A DumontUniversity of Lucerne, Lucerne, LU, Switzerland.
Yonathan GaramaUniversity of Lucerne, Lucerne, LU, Switzerland.
Francisco KimUniversity of Lucerne, Lucerne, LU, Switzerland.ORCID 0000-0003-1767-7774
María Del Val GómezServicio de Medicina Nuclear, Hospital Universitario Ramón y Cajal, Madrid, Spain.
Karim GarianiDivision of Endocrinology, Diabetes, Nutrition and Patient Therapeutic Education, Geneva University Hospitals, Geneva, GE, Switzerland.
Martin A WalterUniversity of Lucerne, Lucerne, LU, Switzerland. martin.alexander.walter@gmail.com.ORCID 0000-0001-6487-5349

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Theranostic drugs represent an emerging path to deliver on the promise of precision medicine. However, bottlenecks remain in characterizing theranostic targets, identifying theranostic lead compounds, and tailoring theranostic drugs. To overcome these bottlenecks, we present the Theranostic Genome, the part of the human genome whose expression can be utilized to combine therapeutic and diagnostic applications. Using a deep learning-based hybrid human-AI pipeline that cross-references PubMed, the Gene Expression Omnibus, DisGeNET, The Cancer Genome Atlas and the NIH Molecular Imaging and Contrast Agent Database, we bridge individual genes in human cancers with respective theranostic compounds. Cross-referencing the Theranostic Genome with RNAseq data from over 17'000 human tissues identifies theranostic targets and lead compounds for various human cancers, and allows tailoring targeted theranostics to relevant cancer subpopulations. We expect the Theranostic Genome to facilitate the development of new targeted theranostics to better diagnose, understand, treat, and monitor a variety of human cancers.

Indexed as

Genome, HumanNeoplasmsPrecision MedicineTheranostic NanomedicineDeep LearningHumans

Identifiers

PMID39738156
PMCPMC11686231

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.