Review of Patient Gene Profiles Obtained through a Non-Negative Matrix Factorization-Based Framework to Determine the Role Inflammation Plays in Neuroblastoma Pathogenesis.
Angelina BoccarelliNicoletta Del BuonoFlavia EspositoPublished in: International journal of molecular sciences (2024)
Neuroblastoma is the most common extracranial solid tumor in children. It is a highly heterogeneous tumor consisting of different subcellular types and genetic abnormalities. Literature data confirm the biological and clinical complexity of this cancer, which requires a wider availability of gene targets for the implementation of personalized therapy. This paper presents a study of neuroblastoma samples from primary tumors of untreated patients. The focus of this analysis is to evaluate the impact that the inflammatory process may have on the pathogenesis of neuroblastoma. Eighty-eight gene profiles were selected and analyzed using a non-negative matrix factorization framework to extract a subset of genes relevant to the identification of an inflammatory phenotype, whose targets ( PIK3CG , NFATC2 , PIK3R2 , VAV1 , RAC2 , COL6A2 , COL6A3 , COL12A1 , COL14A1 , ITGAL , ITGB7 , FOS , PTGS2 , PTPRC , ITPR3 ) allow further investigation. Based on the genetic signals automatically derived from the data used, neuroblastoma could be classified according to stage rather than as a "cold" or "poorly immunogenic" tumor.
Keyphrases
- genome wide
- copy number
- oxidative stress
- genome wide identification
- end stage renal disease
- dna methylation
- electronic health record
- primary care
- newly diagnosed
- healthcare
- ejection fraction
- systematic review
- chronic kidney disease
- big data
- genome wide analysis
- squamous cell carcinoma
- peritoneal dialysis
- gene expression
- machine learning
- papillary thyroid
- quality improvement
- bone marrow
- anti inflammatory
- childhood cancer
- middle cerebral artery