Clinical impact of chromothriptic complex chromosomal rearrangements in newly diagnosed multiple myeloma
| Autor: | Lata Rani, Anubha Gupta, Ritu Gupta, Nitin Mathur, Lalit Kumar, Vishwajeet Singh, Gurvinder Kaur, Om Dutt Sharma, Atul Sharma |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Oncology
Adult Male Cancer Research medicine.medical_specialty DNA Copy Number Variations Kaplan-Meier Estimate Genome Polymorphism Single Nucleotide Translocation Genetic 03 medical and health sciences 0302 clinical medicine Internal medicine medicine Humans Clinical significance Copy-number variation Multiple myeloma Aged Proportional Hazards Models Aged 80 and over Chromothripsis Comparative Genomic Hybridization Proportional hazards model business.industry Hematology Chromoplexy Middle Aged medicine.disease Prognosis Chromosome 17 (human) 030220 oncology & carcinogenesis Disease Progression Female business Multiple Myeloma 030215 immunology |
| Zdroj: | Leukemia research. 76 |
| ISSN: | 1873-5835 |
| Popis: | Complex Chromosomal Rearrangements (CCRs) are increasingly being reported as genetic risk factors of clinical significance in cancer owing to their identification using high resolution whole genome profiling technologies. This study employed high resolution CGH + SNP microarrays for whole genome copy number variations (CNV) profiling and identified CCRs in 11/107(10%) newly diagnosed Multiple Myeloma (MM) patients. Six patients exhibited Chromothripsis (CTH) among seven chromosomes that were confirmed with automated CTLPscanner web tool and; five cases displayed chromoplexy (CPL) which involved multiple chromosomes. Presence of chromothripsis in chromosome 17 in three out of six patients indicate a link between TP53 aberrations and incidence of CTH. Multivariable Cox regression model demonstrated a significant association of CTH with poor PFS (HR = 3.09, p = 0.010) and OS (HR = 3.31, p = 0.024) which suggests that CTH is an additional independent prognostic marker in multiple myeloma. Addition of CTH in risk stratification models in clinical setting in multiple myeloma may help in upfront identification of high risk patients for suitable customized therapy. |
| Databáze: | OpenAIRE |
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