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. 2018 Jul 26;132(4):413-422.
doi: 10.1182/blood-2018-03-838136. Epub 2018 May 16.

A gene signature that distinguishes conventional and leukemic nonnodal mantle cell lymphoma helps predict outcome

Guillem Clot  1   2 , Pedro Jares  1   2   3 , Eva Giné  1   2   4 , Alba Navarro  1   2 , Cristina Royo  1   2 , Magda Pinyol  1   2 , David Martín-Garcia  1   2 , Santiago Demajo  1 , Blanca Espinet  5 , Antonio Salar  6 , Ana Ferrer  6 , Ana Muntañola  7 , Marta Aymerich  2   3 , Hilka Rauert-Wunderlich  8   9 , Elaine S Jaffe  10 , Joseph M Connors  11 , Randy D Gascoyne  11 , Jan Delabie  12 , Armando López-Guillermo  1   2   4 , German Ott  13 , George W Wright  9 , Louis M Staudt  9 , Andreas Rosenwald  8   9 , David W Scott  11 , Lisa M Rimsza  14 , Sílvia Beà  1   2 , Elías Campo  1   2   3
Affiliations

A gene signature that distinguishes conventional and leukemic nonnodal mantle cell lymphoma helps predict outcome

Guillem Clot et al. Blood. .

Abstract

Mantle cell lymphoma (MCL) is an aggressive B-cell malignancy, but some patients have a very indolent evolution. This heterogeneous course is related, in part, to the different biological characteristics of conventional MCL (cMCL) and the distinct subgroup of leukemic nonnodal MCL (nnMCL). Robust criteria to distinguish these MCL subtypes and additional biological parameters that influence their evolution are not well defined. We describe a novel molecular assay that reliably distinguishes cMCL and nnMCL using blood samples. We trained a 16-gene assay (L-MCL16 assay) on the NanoString platform using 19 purified leukemic samples. The locked assay was applied to an independent cohort of 70 MCL patients with leukemic presentation. The assay assigned 37% of cases to nnMCL and 56% to cMCL. nnMCL and cMCL differed in nodal presentation, lactate dehydrogenase, immunoglobulin heavy chain gene mutational status, management options, genomic complexity, and CDKN2A/ATM deletions, but the proportion with 17p/TP53 aberrations was similar in both subgroups. Sequential samples showed that assay prediction was stable over time. nnMCL had a better overall survival (OS) than cMCL (3-year OS 92% vs 69%; P = .006) from the time of diagnosis and longer time to first treatment. Genomic complexity and TP53/CDKN2A aberrations predicted for shorter OS in the entire series and cMCL, whereas only genomic complexity was associated with shorter time to first treatment and OS in nnMCL. In conclusion, the newly developed assay robustly recognizes the 2 molecular subtypes of MCL in leukemic samples. Its combination with genetic alterations improves the prognostic evaluation and may provide useful biological information for management decisions.

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Conflict of interest statement

Conflict-of-interest disclosure: E.C. has received research funding from and has been an expert witness for Gilead Sciences. E.S.J., J.M.C., R.D.G., J.D., G.O., G.W.W., L.M.S., A.R., D.W.S., L.M.S., and E.C. are named inventors on 2 patents filed by the National Cancer Institute: “Methods for selecting and treating lymphoma types” licensed to NanoString Technologies and “Evaluation of mantle cell lymphoma and methods related thereof.” The remaining authors declare no competing financial interests.

Figures

None
Graphical abstract
Figure 1.
Figure 1.
Gene-expression–based L-MCL16 scores in the validation cohort. L-MCL16 score for each validation sample in ascending order (top panel) and associated probability of membership in the nnMCL subgroup (middle panel). L-MCL16 signature heat map (13 upregulated genes in cMCL and 3 upregulated genes in nnMCL) (bottom panel); genes are shown in rows, and cases are shown in columns (red indicates high expression). Two clear gene expression patterns can be observed, with high scores corresponding to cMCL samples (blue) and low scores corresponding to nnMCL samples (red). Only 5 samples have an intermediate gene-expression pattern and are considered Undetermined (gray).
Figure 2.
Figure 2.
Intra- and interlaboratory reproducibility of the L-MCL16 assay. L-MCL16 scores of RNA from blood samples run in duplicate or triplicate in Barcelona (Spain) or from RNA aliquots run and analyzed in Scottsdale (AZ) and Würzburg (Germany). The x-axis corresponds to the average L-MCL16 score of the replicates of the same patient, whereas the y-axis corresponds to the score of each replicate. Samples with a score between the dashed lines are considered Undetermined (1 case).
Figure 3.
Figure 3.
L-MCL16 scores of RNA from sequential samples of 9 nnMCL patients and 2 cMCL patients. The x-axis corresponds to the time (in years) between the sample collections, and the y-axis corresponds to the L-MCL16 scores. The arrows start at the first sample and are directed to the sequential ones. The signature was stable over time in all cases.
Figure 4.
Figure 4.
Molecular features of the 70 leukemic MCL samples in the validation cohort. Features are shown as rows, and samples are shown as columns. Samples are ordered according to the L-MCL16 score. IGHV mutations are in yellow, and 17p/TP53, 9p/CDKN2A, and 11q alterations are in green. The number of CNAs in each sample is shown in the bar graph.
Figure 5.
Figure 5.
Prognostic impact of the L-MCL16 assay in the validation cohort. KM curves of TTT (A) and OS (B) from diagnosis date of the nnMCL and cMCL subgroups identified by the L-MCL16 assay. KM curves of the OS from sampling date according to the presence of 17p/TP53 and/or 9p/CDKN2A alterations (C) and number of CNAs (D) for the nnMCL and cMCL subgroups. The number of CNAs was associated with OS as a continuous variable.
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References

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