Clinical Utility of a Diagnostic Approach to Detect Genetic Abnormalities in Multiple Myeloma: A Single Institution Experience
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Background: The identification of genetic abnormalities in patients with multiple myeloma (MM) has gained emphasis because genetics-based risk stratification significantly affects overall survival (OS). We investigated genetic abnormalities using conventional cytogenetics and FISH and analyzed the prognostic significance of the identified additional abnormalities in MM. Methods: In total, 267 bone marrow samples were collected from February 2006 to November 2013 from patients who were newly diagnosed as having MM in a tertiary-care hospital in Korea. The clinical and laboratory data were retrospectively obtained. Cox proportional hazard regression was used to examine the relationship between clinical/genetic factors and survival outcome, using univariate and multivariate models. Results: Using conventional cytogenetic analysis and FISH, 45% (120/267) and 69% (183/267) patients, respectively, were identified to harbor genetic abnormalities. In the univariate analysis, the following genetic variables were identified to affect OS: abnormal karyotype (P <0.001), aneuploidy (P =0.046), -13 or del(13q) (P =0.002), 1q amplification (P <0.001), and t(4;14) (P =0.020). In the multivariate analysis, the presence of -13 or del(13q) was the only significant genetic factor affecting OS (P =0.012) with a hazard ratio (HR) of 2.131 (95% confidence interval [CI], 1.185–3.832) in addition to the clinical factor of age (>65 years) (P =0.013) with an HR of 2.505 (95% CI, 1.218–5.151). Conclusions: Our findings highlight the importance of applying a comprehensive approach for detecting genetic abnormalities, which could be closely associated with the prognostic significance of MM.
Abstract
Background: The identification of genetic abnormalities in patients with multiple myeloma (MM) has gained emphasis because genetics-based risk stratification significantly affects overall survival (OS). We investigated genetic abnormalities using conventional cytogenetics and FISH and analyzed the prognostic significance of the identified additional abnormalities in MM. Methods: In total, 267 bone marrow samples were collected from February 2006 to November 2013 from patients who were newly diagnosed as having MM in a tertiary-care hospital in Korea. The clinical and laboratory data were retrospectively obtained. Cox proportional hazard regression was used to examine the relationship between clinical/genetic factors and survival outcome, using univariate and multivariate models. Results: Using conventional cytogenetic analysis and FISH, 45% (120/267) and 69% (183/267) patients, respectively, were identified to harbor genetic abnormalities. In the univariate analysis, the following genetic variables were identified to affect OS: abnormal karyotype (P <0.001), aneuploidy (P =0.046), -13 or del(13q) (P =0.002), 1q amplification (P <0.001), and t(4;14) (P =0.020). In the multivariate analysis, the presence of -13 or del(13q) was the only significant genetic factor affecting OS (P =0.012) with a hazard ratio (HR) of 2.131 (95% confidence interval [CI], 1.185–3.832) in addition to the clinical factor of age (>65 years) (P =0.013) with an HR of 2.505 (95% CI, 1.218–5.151). Conclusions: Our findings highlight the importance of applying a comprehensive approach for detecting genetic abnormalities, which could be closely associated with the prognostic significance of MM.
참고문헌 (20)
- Swerdlow SH, "WHO classification of tumours of haematopoietic and lymphoid tissues", International Agency for Research on Cancer, 200~207 (2008)
- Chng WJ, "IMWG consensus on risk stratification in multiple myeloma", Leukemia, 28, pp.269~277 (2014)[DOI]
- Fonseca R, "International Myeloma Working Group molecular classification of multiple myeloma: spotlight review", Leukemia, 23, pp.2210~2221 (2009)[DOI]
- Munshi NC, "Consensus recommendations for risk stratification in multiple myeloma: report of the International Myeloma Workshop Consensus Panel 2", Blood, 117, pp.4696~4700 (2011)[DOI]
- Bergsagel PL, "Chromosome translocations in multiple myeloma", Oncogene, 20, pp.5611~5622 (2001)[DOI]
- Avet-Loiseau H, "Genetic abnormalities and survival in multiple myeloma: the experience of the Intergroupe Francophone du Myelome", Blood, 109, pp.3489~3495 (2007)[DOI]
- Bergsagel PL, "Molecular pathogenesis and a consequent classification of multiple myeloma", J Clin Oncol, 23, pp.6333~6338 (2005)[DOI]
- Calasanz MJ, "Cytogenetic analysis of 280 patients with multiple myeloma and related disorders: primary breakpoints and clinical correlations", Genes Chromosomes Cancer, 18, pp.84~93 (1997)[DOI]
- Dong H, "Risk stratification of plasma cell neoplasm: insights from plasma cell-specific cytoplasmic immunoglobulin fluorescence in situ hybridization (cIg FISH) vs. conventional FISH", Clin Lymphoma Myeloma Leuk, 12, pp.366~374 (2012)[DOI]
- Gersen SL, "The Principles of Clinical Cytogenetics. 2nd ed.", pp.64~65 (2004), Humana Press
- Wolff DJ, "Guidance for fluorescence in situ hybridization testing in hematologic disorders", J Mol Diagn, 9, pp.134~143 (2007)[DOI]
- 이지원, "다발골수종 환자의 염색체 이상과 예후관련 검사항목과의 연관성-단일 기관 연구", Annals of Laboratory Medicine, 28(6), pp.413~418 (2008), 대한진단검사의학회
- 제갈동욱, "Impact of Genetic Abnormalities on the Prognoses and Clinical Parameters of Patients with Multiple Myeloma", Annals of Laboratory Medicine, 33(4), pp.248~254 (2013), 대한진단검사의학회
- Bang SM, "Identification of 13q deletion, trisomy 1q, and IgH rearrangement as the most frequent chromosomal changes found in Korean patients with multiple myeloma", Cancer Genet Cytogenet, 168, pp.124~132 (2006)[DOI]
- Lim JH, "Cytogenetic classification in Korean multiple myeloma patients: prognostic significance of hyperdiploidy with 47-50 chromosomes and the number of structural abnormalities", Eur J Haematol, 92, pp.313~320 (2014)[DOI]
- Jacobus SJ, "Impact of high-risk classification by FISH: an eastern cooperative oncology group (ECOG) study E4A03", Br J Haematol, 155, pp.340~348 (2011)[DOI]
- Durie BG, "A clinical staging system for multiple myeloma. Correlation of measured myeloma cell mass with presenting clinical features, response to treatment, and survival", Cancer, 36, pp.842~854 (1975)[DOI]
- 최정혜, "Clinical Value of New Staging Systems for Multiple Myeloma", Cancer Research and Treatment, 39(4), pp.171~174 (2007), 대한암학회
- Avet-Loiseau H, "Combining fluorescent in situ hybridization data with ISS staging improves risk assessment in myeloma: an International Myeloma Working Group collaborative project", Leukemia, 27, pp.711~717 (2013)[DOI]
- Oh S, "Chromosome 13 deletion and hypodiploidy on conventional cytogenetics are robust prognostic factors in Korean multiple myeloma patients: web-based multicenter registry study", Ann Hematol, 93, pp.1353~1361 (2014)[DOI]
