Evidence map›Paper›PMID 40830279›Full record

ReviewDiscover oncology2025

Oncogene-driven lung cancer in the era of radiogenomics: current evidence and future developments.

James Ryan, John Kavanagh, Niamh Coleman

Abstract readReview
In one paragraph

Review in Discover oncology, 2025. 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
–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

3 citing papers in PubMed.

  1. Review
  2. Review
  3. 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

3 authors.

James RyanDepartment of Medical Oncology, St. James's Hospital, Dublin, Ireland.
John KavanaghDepartment of Radiology, St. James's Hospital, Dublin, Ireland.
Niamh ColemanDepartment of Medical Oncology, St. James's Hospital, Dublin, Ireland. niacoleman@stjames.ie.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Radiogenomics integrates imaging and genomic data to further refine precision oncology and is of particular interest in oncogene-driven lung cancer. By linking radiologic features with molecular alterations, radiogenomics aims to enable non-invasive tumor characterization, improve diagnostics, treatment planning, and disease monitoring. In oncogene-driven lung cancer, next-generation sequencing (NGS) has uncovered actionable oncogenes such as EGFR, KRAS, ALK, BRAF, MET, HER2, and fusions in ROS1, and NTRK, which have revolutionized the management and outcomes of patients with these alterations. Radiogenomics has the potential to overcome several challenges in the clinic, such as repeat tissue biopsies, which are invasive and may be inadequate due to inherent tumor heterogeneity, by leveraging imaging biomarkers from CT, PET, and MRI to infer genomic profiles. In this review, we discuss the many recent advances in the burgeoning field of radiogenomics. We discuss how specific radiological features in oncogene-driven NSCLC, are starting to aid in mutation prediction and personalized treatment selection, and explore how radiogenomics may enhance treatment response prediction and refine prognostic models beyond traditional staging. Finally, we explore some of the challenges in its clinical implementation, including standardization of imaging protocols, data harmonization, and some of the ethical considerations regarding patient privacy and finally, we evaluate current evidence beyond lung cancer.

Indexed as

Lung cancerOncogenePrecision oncologyRadiogenomicsTargeted therapy

Identifiers

PMID40830279
PMCPMC12364778

What Socratic holds

Textmetadata
LicenceCC BY-NC-ND
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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 Socratic graph.