Systems medicine dissection of chr1q-amp reveals a novel PBX1-FOXM1 axis for targeted therapy in multiple myeloma.
Nikolaos TrasanidisAlexia KatsarouKanagaraju PonnusamyYao-An ShenIoannis V KostopoulosBien BergoniaKeren KerenPaudel ReemaXiaolin XiaoRichard M SzydloPierangela M R SabbattiniIrene A G RobertsHolger W AunerKikkeri N NareshAristeidis ChaidosTian-Li WangLuca MagnaniValentina S CaputoAnastasios KaradimitrisPublished in: Blood (2022)
Understanding the biological and clinical impact of copy number aberrations (CNAs) on the development of precision therapies in cancer remains an unmet challenge. Genetic amplification of chromosome 1q (chr1q-amp) is a major CNA conferring an adverse prognosis in several types of cancer, including in the blood cancer multiple myeloma (MM). Although several genes across chromosome 1 (chr1q) portend high-risk MM disease, the underpinning molecular etiology remains elusive. Here, with reference to the 3-dimensional (3D) chromatin structure, we integrate multi-omics data sets from patients with MM with genetic variables to obtain an associated clinical risk map across chr1q and to identify 103 adverse prognosis genes in chr1q-amp MM. Prominent among these genes, the transcription factor PBX1 is ectopically expressed by genetic amplification and epigenetic activation of its own preserved 3D regulatory domain. By binding to reprogrammed superenhancers, PBX1 directly regulates critical oncogenic pathways and a FOXM1-dependent transcriptional program. Together, PBX1 and FOXM1 activate a proliferative gene signature that predicts adverse prognosis across multiple types of cancer. Notably, pharmacological disruption of the PBX1-FOXM1 axis with existing agents (thiostrepton) and a novel PBX1 small molecule inhibitor (T417) is selectively toxic against chr1q-amp myeloma and solid tumor cells. Overall, our systems medicine approach successfully identifies CNA-driven oncogenic circuitries, links them to clinical phenotypes, and proposes novel CNA-targeted therapy strategies in MM and other types of cancer.
Keyphrases
- copy number
- genome wide
- papillary thyroid
- transcription factor
- mitochondrial dna
- multiple myeloma
- dna methylation
- squamous cell
- small molecule
- gene expression
- lymph node metastasis
- protein kinase
- squamous cell carcinoma
- genome wide identification
- dna damage
- childhood cancer
- machine learning
- emergency department
- young adults
- deep learning
- oxidative stress
- artificial intelligence
- data analysis
- heat stress
- bioinformatics analysis