Abstract
Many studies failed to demonstrate benefit from the addition of targeted agents to current standard adjuvant FOLFOX chemotherapy in stage III colorectal cancer (CRC) patients. Intratumor heterogeneity may foster the resistant subclones and leads to cancer recurrence. Here, we built a cancer evolution model and applied machine learning analysis to identify potential therapeutic targets. Among 78 CRC cases, whole-genome (WGS) and deep targeted sequencing data generated from paired blood and primary tumor were used for phylogenetic tree reconstruction. Genetic alterations in the PI3K/AKT, and RTK oncogenic signaling pathways were commonly detected in founding clones. The dominant subclones frequently exhibited dysregulations in the TP53, FBXW7/NOTCH1 tumor suppression, and DNA repair pathways. Fourteen genetic mutations were simultaneously selected by random forest and LASSO methods. The logistic regression model had better accuracy (79%), precision (70%), and recall (65%) and area under the curve (AUC) (82%) for cancer recurrence prediction. Three genes, including MYO18A in the founding clone, FBXW7, and ATM in the dominant subclone, affected the prognosis were selected simultaneously by different feature sets. The in vitro studies, HCT-116 cells transfected with MYO18A siRNA demonstrated a significant reduction in cell migration activity by 20–40%. These results indicate that MYO18A plays a crucial role in the migration of human CRC cells. The cancer evolution model revealed the critical mutations in the founding and dominant subclones. They can be used to predict clinical outcomes and the development of novel therapeutic targets for stage III CRC.
Highlights
Colorectal cancer (CRC) is the most commonly diagnosed gastrointestinal cancer and is one of the leading causes of cancer-related death worldwide [1]
These four genetic variants were rare and were found only in 1.3% (1/78) of these CRC patients (Supplementary Figure 1C). Targeting these rare mutations does not seem to provide significant improvements in the clinical outcome of stage III CRC. These data imply the limitation of the conventional approach of the analytic sequencing method
By calculating the odds ratio (OD) and hazard ratio (HR), we identified 8 (OD8) and 25 (HR25) genes, respectively, that were significantly associated with recurrence in this CRC cohort (p < 0.05)
Summary
Colorectal cancer (CRC) is the most commonly diagnosed gastrointestinal cancer and is one of the leading causes of cancer-related death worldwide [1]. Adjuvant FOLFOX (5-fluorouracil, leucovorin, and oxaliplatin) chemotherapy benefits stage III CRC patients, recurrence develops in 30–35% of patients [2]. Many studies have tried to assess the addition of targeted therapy, including bevacizumab and cetuximab, to FOLFOX in the adjuvant treatment of stage III CRC. A considerable challenge of recurrent stage III CRC is identifying the critical genetic mutations responsible for tumor metastasis and delivering effective therapeutic strategies [3, 4]. CRC is a highly heterogeneous disease that differs in clinical presentations, molecular characteristics, and responses to treatment and survival. Building the genome evolution model underlying the mechanism of tumor carcinogenesis and biological pathways and identifying genetic markers to predict cancer recurrence is crucial to accelerate and facilitate the development of CRC treatment targets
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