ArticleNature cancer2025
Prospective validation of ORACLE, a clonal expression biomarker associated with survival of patients with lung adenocarcinoma.
Article in Nature cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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.
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.
Who cites it
11 citing papers in PubMed.
- A multimodal AI biomarker PATH-ORACLE improves prediction of recurrence in stage I lung adenocarcinoma.Immuno-oncology technology · 2026Article
- Genomic instability, postoperative recurrence and therapeutic vulnerabilities in resectable non‑small cell lung cancer (Review).Oncology reports · 2026Review
- Gene Expression Clustering of Lung Adenocarcinoma Tumors as a Prognosis Tool to Infer Progression-Free Survival.JTO clinical and research reports · 2026Article
- Charting intratumor heterogeneity from bench to bedside.Nature cancer · 2026Review
- A machine learning assay to predict disease recurrence in hormone receptor-positive breast cancer.ESMO open · 2026Article
- Integrated Multi-Omics Analysis Constructs an Intratumoral Heterogeneity-Corrected Prognostic Signature for Cervical Cancer.International journal of general medicine · 2026Article
- Lung cancer organoids for functional precision oncology: from disease modeling to clinical decision support.Frontiers in oncology · 2026Review
- Article
- Applications of artificial intelligence in non-small cell lung cancer: from precision diagnosis to personalized prognosis and therapy.Journal of translational medicine · 2025Review
- Conserved sphingolipid metabolism under transcriptomic diversity: a prognostic and therapeutic target in triple-negative breast cancer.Journal of translational medicine · 2025Article
- Transforming Population Health Screening for Atherosclerotic Cardiovascular Disease with AI-Enhanced ECG Analytics: Opportunities and Challenges.Current atherosclerosis reports · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
37 authors.
Funding
Abstract
Human tumors are diverse in their natural history and response to treatment, which in part results from genetic and transcriptomic heterogeneity. In clinical practice, single-site needle biopsies are used to sample this diversity, but cancer biomarkers may be confounded by spatiogenomic heterogeneity within individual tumors. Here we investigate clonally expressed genes as a solution to the sampling bias problem by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. We prospectively validate the survival association of a clonal expression biomarker, Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors, and in stage I disease. We expand our mechanistic understanding, discovering that clonal transcriptional signals are detectable before tissue invasion, act as a molecular fingerprint for lethal metastatic clones and predict chemotherapy sensitivity. Lastly, we find that ORACLE summarizes the prognostic information encoded by genetic evolutionary measures, including chromosomal instability, as a concise 23-transcript assay.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.