MCL1 gene co‐expression module stratifies multiple myeloma and predicts response to proteasome inhibitor‐based therapy

Multiple myeloma (MM) is the second most common hematologic cancer, characterized by abnormal accumulation of plasma cells in the bone marrow. The extensive biological and clinical heterogeneity of MM hinders effective treatment and etiology research. Several molecular classification systems of prog...

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Veröffentlicht in:Genes chromosomes & cancer 2018-08, Vol.57 (8), p.420-429
Hauptverfasser: Samo, Ayaz Ali, Li, Jiuyi, Zhou, Min, Sun, Yingyu, Yang, Yuan, Zhang, Yunqiu, Li, Jing, van Duin, Mark, Lu, Xuzhang, Fan, Xiaolong
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Sprache:eng
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Zusammenfassung:Multiple myeloma (MM) is the second most common hematologic cancer, characterized by abnormal accumulation of plasma cells in the bone marrow. The extensive biological and clinical heterogeneity of MM hinders effective treatment and etiology research. Several molecular classification systems of prognostic impact have been proposed, but they do not predict the response to treatment nor do they correlate to plasma cell development pathways. Here we describe the classification of MM into two distinct subtypes based on the expression levels of a gene module coexpressed with MCL1 (MCL1‐M), a regulator of plasma cell survival. The classification system enabled prediction of the prognosis and the response to bortezomib‐based therapy. Moreover, the two MM subtypes were associated with two different plasma cell differentiation pathways (enrichment of a preplasmablast signature versus aberrant expression of B cell genes). 1q gain, harboring 63 of the 87 MCL1‐M members including MCL1, was found in about 80% of the MM with upregulated MCL1‐M expression. Clonal analysis showed that 1q gain tended to occur as an early clonal event. Members of MCL1‐M captured both MM cell‐intrinsically acting signals and the signals regulating the interaction between MM cells with bone marrow microenvironment. MCL1‐M members were co‐expressed in mouse germinal center B cells. Together, these findings indicate that MCL1‐M may play previously inadequately recognized, initiating role in the pathogenesis of MM. Our findings suggest that MCL1‐M signature‐based molecular clustering of MM constitutes a solid framework toward understanding the etiology of this disease and establishing personalized care. Article Summary: A pathogenic mechanism‐guided molecular classification would facilitate treatment decision and etiology research of multiple myeloma. On the basis of the expression levels of a gene module coexpressed with MCL1, we have established a classification scheme assigning multiple myeloma into two subtypes with distinct prognosis, treatment responses and pathogenic backgrounds.
ISSN:1045-2257
1098-2264
DOI:10.1002/gcc.2