Gene expression profiles of tumor biology provide a novel approach to prognosis and may guide the selection of therapeutic targets in multiple myeloma.
OBJECTIVE
Monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM) comprise heterogeneous disorders with incompletely understood molecular defects and variable clinical features. We performed gene expression profiling (GEP) with microarray data to better dissect the molecular phenotypes, sensitivity to particular chemotherapeutic agents, and prognoses of these diseases.


METHODS
Using gene expression and clinical data from 877 patients ranging from normal plasma cells (NPC) to relapsed MM (RMM), we applied gene expression signatures reflecting deregulation of oncogenic pathways and tumor microenvironment to highlight molecular changes that occur as NPCs transition to MM, create a high-risk MGUS gene signature, and subgroup International Staging System (ISS) stages into more prognostically accurate clusters of patients. Lastly, we used gene signatures to predict sensitivity to conventional cytotoxic chemotherapies among identified clusters of patients.


RESULTS
Myc upregulation and increasing chromosomal instability (CIN) characterized the evolution from NPC to RMM (P < .0001 for both). Studies of MGUS revealed that some samples shared biologic features with RMM, which comprised the basis for a high-risk MGUS signature. Regarding MM, we subclassified ISS stages into clusters based on shared features of tumor biology. These clusters differentiated themselves based on predictions for prognosis and chemotherapy sensitivity (eg, in ISS stage I, one cluster was characterized by increased CIN, cyclophosphamide resistance, and a poor prognosis).


CONCLUSIONS
GEP provides insight into the molecular defects underlying plasma cell dyscrasias that may explain their clinical heterogeneity. GEP also may also refine current prognostic and therapeutic models for MGUS and MM.
Anguiano
Ariel
A
Institute for Genome Sciences and Policy, Duke University, Durham, NC 27708, USA.
Tuchman
Sascha A
SA
Acharya
Chaitanya
C
Salter
Kelly
K
Gasparetto
Cristina
C
Zhan
Fenghuang
F
Dhodapkar
Madhav
M
Nevins
Joseph
J
Barlogie
Bart
B
Shaughnessy
John D
JD
Potti
Anil
A
D000328:Adult; D000368:Aged; D000970:Antineoplastic Agents / Q000627:therapeutic use*; D014408:Biomarkers, Tumor / Q000235:genetics*; D043171:Chromosomal Instability; D016000:Cluster Analysis; D019992:Databases as Topic; D018572:Disease-Free Survival; D005260:Female; D020869:Gene Expression Profiling / Q000379:methods*; D015972:Gene Expression Regulation, Neoplastic; D005838:Genotype; D006801:Humans; D053208:Kaplan-Meier Estimate; D008297:Male; D008875:Middle Aged; D009101:Multiple Myeloma / Q000188:drug therapy / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D009367:Neoplasm Staging; D020411:Oligonucleotide Array Sequence Analysis; D010265:Paraproteinemias / Q000188:drug therapy / Q000235:genetics* / Q000401:mortality / Q000473:pathology; D018579:Patient Selection; D010641:Phenotype; D011237:Predictive Value of Tests; D011379:Prognosis; D016271:Proto-Oncogene Proteins c-myc / Q000235:genetics; D018570:Risk Assessment; D013997:Time Factors
D000970:Antineoplastic Agents; D014408:Biomarkers, Tumor; C489427:MYC protein, human; D016271:Proto-Oncogene Proteins c-myc