Identification of Genomic Signatures for Colorectal Cancer Survival Using Exploratory Data Mining

Autor: Justin J. Hummel, Danlu Liu, Erin Tallon, John Snyder, Wesley Warren, Chi-Ren Shyu, Jonathan Mitchem, Rene Cortese
Jazyk: angličtina
Rok vydání: 2024
Předmět:
Zdroj: International Journal of Molecular Sciences, Vol 25, Iss 6, p 3220 (2024)
Druh dokumentu: article
ISSN: 1422-0067
1661-6596
DOI: 10.3390/ijms25063220
Popis: Clinicopathological presentations are critical for establishing a postoperative treatment regimen in Colorectal Cancer (CRC), although the prognostic value is low in Stage 2 CRC. We implemented a novel exploratory algorithm based on artificial intelligence (explainable artificial intelligence, XAI) that integrates mutational and clinical features to identify genomic signatures by repurposing the FoundationOne Companion Diagnostic (F1CDx) assay. The training data set (n = 378) consisted of subjects with recurrent and non-recurrent Stage 2 or 3 CRC retrieved from TCGA. Genomic signatures were built for identifying subgroups in Stage 2 and 3 CRC patients according to recurrence using genomic parameters and further associations with the clinical presentation. The summarization of the top-performing genomic signatures resulted in a 32-gene genomic signature that could predict tumor recurrence in CRC Stage 2 patients with high precision. The genomic signature was further validated using an independent dataset (n = 149), resulting in high-precision prognosis (AUC: 0.952; PPV = 0.974; NPV = 0.923). We anticipate that our genomic signatures and NCCN guidelines will improve recurrence predictions in CRC molecular stratification.
Databáze: Directory of Open Access Journals
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