Project description:Multiple myeloma is a malignancy of antibody-secreting plasma cells. Most patients benefit from current therapies, however, 20% of patients relapse or die within two years. To better understand and identify these ‘high-risk’ cases, we analyzed the translocation landscape of myeloma from 795 newly-diagnosed patients by whole genome sequencing from the CoMMpass study. Translocations involving the immunoglobulin lambda (IgL) locus were identified in 10% of patients, and were indicative of poor prognosis. Importantly, 70% of IgL translocations co-occurred with hyperdiploid disease, a marker of standard risk, potentially resulting in the misclassification of IgL-translocated myeloma. Most IgL-translocations coincided with focal amplifications that were centered on the 3’ enhancer. Patients with IgL-translocations failed to benefit from immunomodulatory imide drugs (IMiDs), which target the lymphocyte-specific transcription factor IKZF1 that is bound to the IgL 3’ enhancer at some of the highest levels in the myeloma epigenome. These data implicate IgL-translocation as a driver of poor prognosis which may be due in part to IMID resistance.
Project description:Cancer tissue specimens from ARID1Ahigh and good prognosis and ARID1Alow and poor prognosis of patients with advanced gastric cancer were extracted and analyzed.
Project description:Myeloma is a clonal malignancy of plasma cells. Poor prognosis risk is currently identified by clinical and cytogenetic features. However, these indicators do not capture all prognostic information. Gene expression analysis can be used to identify poor prognosis patients and this can be improved by combination with information about DNA level changes. Using SNP-based gene mapping in combination with global gene expression analysis we have identified homozygous deletions in genes and networks that are relevant to myeloma. From these, we have generated an expression-based signature associated with shorter survival in 247 patients and confirmed this signature in data from 2 independent groups totalling 800 patients. We identified 170 genes with homozygous deletions and corresponding loss of expression. Deletion within the “Cell Death” network was over-represented and cases with these deletions have impaired overall survival. We defined a gene expression signature of 97 cell death genes that reflects prognosis confirmed this in two independent data sets. We developed a simple 6-gene expression signature from the 97-gene signature that can be used to identify poor prognosis myeloma in the clinical environment. The signature can form the basis of future trials aimed at improving the outcome of poor prognosis myeloma.