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14/04/2025A new study validates the survival association of the clonal expression biomarker ORACLE in patients with lung adenocarcinoma
A new study recently published on Nature Cancer retrospectively validated the clonal expression biomarker Outcome Risk Associated Clonal Lung Expression (ORACLE), in combination with clinicopathological risk factors and in stage I disease, as a survival biomarker in patients with lung adenocarcinoma.
Transcriptomic biomarkers hold the translational potential of capturing features of cancer cell aggressiveness to add a molecular dimension to prognostication, but in lung adenocarcinoma previously suggested biomarkers have failed to refine risk prediction beyond established clinicopathological risk factors, particularly in stage I disease. Authors observed that pervasive intratumor heterogeneity in lung cancer confounded prognostic signatures, with 30–40% of tumors yielding disparate prognostic scores depending upon where the biopsy needle was placed: as a solution to the sampling bias problem authors investigated clonally expressed genes by analyzing multiregion whole-exome and RNA sequencing data for 450 tumor regions from 184 patients with lung adenocarcinoma in the TRACERx study. Results showed the clinical utility of ORACLE: the association between ORACLE and overall survival was prospectively validated and was significant for lung-cancer-specific survival and disease-free survival. «As an RNA marker, ORACLE complemented the use of liquid biopsy (ctDNA) and pathology markers to predict 5-year survival outcomes», authors say. «ORACLE has been designed as a pragmatic solution to the sam- pling bias problem, applied to ‘bulk’ RNA extracted from single-site needle samples in the clinical setting. It has been suggested that, for a subset of tumors, prognosis is inherently difficult to predict due to low-penetrant subclones that are undetectable in bulk profiling. For accurate diagnostic classification in these cases, identifying the lethal subclone may require multiregion or single-cell sampling strategies», authors conclude.





