Discovery of Novel Potential Prognostic Markers and Targeted Therapy to Overcome Chemotherapy Resistance in an Advanced-Stage Wilms Tumor.
Pongsakorn ChoochuenNatakorn NokchanNatthapon KhongcharoenWison LaochareonsukSiriporn LalakornThirachit ChotsampancharoenThanit SilaSurasak Sangkhathatnull nullPublished in: Cancers (2024)
Wilms tumor (WT), the most prevalent type of renal cancer in children, exhibits overall survival rates exceeding 90%. However, chemotherapy resistance, which occurs in approximately 10% of WT cases, is a major challenge for the treatment of WT, particularly for advanced-stage patients. In this study, we aimed to discover potential mutation markers and drug targets associated with chemotherapy resistance in advanced-stage WT. We performed exome sequencing to detect somatic mutations and molecular targets in 43 WT samples, comprising 26 advanced-stage WTs, of which 7 cases were chemotherapy-resistant. Our analysis revealed four genes ( ALPK2 , C16orf96 , PRKDC , and SVIL ) that correlated with chemotherapy resistance and reduced disease-free survival in advanced-stage WT. Additionally, we identified driver mutations in 55 genes within the chemotherapy-resistant group, including 14 druggable cancer driver genes. Based on the mutation profiles of the resistant WT samples, we propose potential therapeutic strategies involving platinum-based agents, PARP inhibitors, and antibiotic/antineoplastic agents. Our findings provide insights into the genetic landscape of WT and offer potential avenues for targeted treatment, particularly for patients with chemotherapy resistance.
Keyphrases
- locally advanced
- free survival
- genome wide
- end stage renal disease
- papillary thyroid
- chemotherapy induced
- single cell
- gene expression
- squamous cell carcinoma
- high throughput
- human health
- radiation therapy
- dna damage
- rectal cancer
- chronic kidney disease
- small molecule
- ejection fraction
- copy number
- risk assessment
- oxidative stress
- dna repair
- climate change
- peritoneal dialysis
- bioinformatics analysis
- genome wide identification