Растворимый антиген созревания клеток B в качестве биомаркера развития и лечения у пациентов с прекурсорами миэломы.

TO THE EDITOR:

B-cell maturation antigen (BCMA) is encoded by the tumor necrosis factor receptor superfamily member 17 gene. 1 It is predominantly expressed on the surface of late-stage B cells, plasmablasts, and terminally differentiated plasma cells (PCs) and is essential for B-cell proliferation and survival and PC differentiation. 2 , 3 BCMA is generally expressed at higher levels on neoplastic vs normal PCs in patients with monoclonal gammopathy of undetermined significance (MGUS), smoldering myeloma (SMM), and active multiple myeloma (MM). 4 , 5 Soluble BCMA (sBCMA) is shed from membrane-bound BCMA through the activity of the γ-secretase complex, a membrane-embedded aspartyl protease. 6 , 7 , 8 MGUS and SMM are myeloma precursor diseases with different progression rates to active MM, 9 , 10 , 11 , 12 which has prompted significant interest in early intervention. Therefore, it is important to identify patients at a higher risk of progression who could be considered for early treatment to avoid end-organ damage. 13 In a study of 283 patients with MGUS and SMM, sBCMA proved to be a promising biomarker to identify those who were at an increased risk of progression. 14 A second study of 149 patients, of whom 8 had MGUS or SMM, supported the possibility that sBCMA was a marker of treatment response. 15 However, these prior reports were retrospective and involved samples collected outside formal trials, indicating a need for further validation, especially in the precursor setting. Here, we aimed to prospectively investigate whether sBCMA levels could serve as a marker for monitoring disease progression and assessing treatment response in patients with myeloma precursor disease.

Patients with MGUS and SMM diagnosed based on the International Myeloma Working Group criteria at The University of Texas MD Anderson Cancer Center from 2015 to 2024 were included in this study. They provided informed consent in accordance with the Declaration of Helsinki for protocols approved by our institutional review board. These included the Observational Prospective Research Study In Monoclonal Gammopathies Leading to Myeloma (ORIGIN; ClinicalTrials.gov identifier: NCT02726750 ) study, 16 an interventional study of pembrolizumab (a pilot single-arm, single-center, open-label trial of pembrolizumab in patients with intermediate- and high-risk SMM; ClinicalTrials.gov identifier: NCT02603887 ), and a second interventional study, ISAMAR (phase 2 trial of isatuximab without or with lenalidomide in patients with high-risk SMM; ClinicalTrials.gov identifier: NCT02960555 ). 17 In the current effort, our goals were to first compare baseline sBCMA levels between 58 patients with MGUS and 149 patients with SMM from these studies. Among these samples, 58 MGUS and 76 SMM baseline serum samples are from the ORIGIN study, 13 SMM serum samples are from the pembrolizumab study, and 60 SMM baseline serum samples are from the ISAMAR study. Subsequently, we sought to evaluate sBCMA levels in 40 patients with MGUS and 76 patients with SMM from the ORIGIN study with available longitudinal samples at baseline, 1, and/or 3 years of follow-up or the time to progression. Finally, we sought to evaluate the association between sBCMA levels and treatment response from 24 patients who received single-agent isatuximab (cohort 1) and 36 who received isatuximab/lenalidomide (cohort 2) in the ISAMAR trial. We classified patients into “responder” (partial response or better) and “nonresponder” (less than partial response) groups according to the International Myeloma Working Group criteria. 18 , 19 Monoclonal protein (M-protein) levels and the difference between serum involved and uninvolved free light chains were used as reference parameters. Additional information can be found in supplemental Materials .

Among 207 patients with myeloma precursors, 194 (54 MGUS and 140 SMM) underwent positron emission tomography/computed tomography or magnetic resonance imaging to exclude bony lesions; other characteristics are summarized in Table 1 . Baseline sBCMA levels in 58 patients with MGUS were significantly lower than in 149 patients with SMM ( P < .001; Figure 1 A). In the prospective study, patients with MGUS who progressed to SMM (n = 4) showed a trend toward higher sBCMA levels than 36 nonprogressors at baseline and at 1 year, which reached significance at 3 years ( P = .021; Figure 1 B). However, sBCMA levels did not correlate with serum M-protein levels or bone marrow PC percentage (BMPC%; supplemental Table 1 ), likely because of the small number of progressors and the low tumor burden. When comparing sBCMA levels among patients with SMM, sBCMA was significantly higher in those progressing to active MM (n = 13) than in 63 nonprogressors at all time points ( P < .050; Figure 1 C). In addition, sBCMA levels showed a positive correlation with serum M-protein levels at all time points and with BMPC% at baseline ( P < .050; supplemental Table 1 ) but not at 3 years, when only 5 of the 10 progressors had available BMPC% data. These data support that sBCMA, a noninvasive marker, reflects tumor progression in myeloma precursor disease, especially in SMM. We also evaluated the relationship between sBCMA levels and the Mayo Clinic (2/20/20) model 20 in patients with SMM from ORIGIN at baseline (n = 76). First, the receiver operating characteristic analysis demonstrated good/acceptable discriminatory performance for sBCMA (area under the curve [AUC] = 0.846; 95% confidence interval [CI], 0.751-0.935), Mayo Score (AUC = 0.774; 95% CI, 0.641-0.891), and a combined model (AUC = 0.841; 95% CI, 0.736-0.926) in supplemental Figure 1 . Second, in univariable logistic regression analyses, both higher sBCMA level and Mayo Score were significantly associated with progression ( P < .050). In model 3 with multivariable logistic regression analysis, only the Mayo Score remained statistically significant ( P < .050), whereas sBCMA level was not ( P > .050; supplemental Table 2 ); sBCMA also increased from the low- to high-risk group identified by the Mayo Clinic model ( P < .050; supplemental Figure 2 ). Based on these data, sBCMA levels demonstrate a promising signal in predicting disease progression among patients with SMM with a minimally invasive assay; however, because of our limited sample size, these findings need to be validated in future studies.

Table 1. Baseline characteristics of analyzed patients with myeloma precursor conditions Characteristic MGUS (n = 58) SMM (n = 149) Sex, n (%)  Female 31 (53) 78 (52)  Male 27 (47) 71 (48) Age, median (IQR), y 68 (64-72) 66 (56-72) Race, n (%)  White 50 (86) 127 (85)  African American 2 (3.4) 10 (6.7)  Other 6 (10) 12 (8.1) Biomarkers, median (IQR)  M-protein, g/dL 0.5 (0.3-1.1) 1.7 (1.1-2.6)  Serum iFLC, mg/L 30.6 (18.8-79.9) 87.8 (27.5-202.9)  BMPC% 5.0 (4.0-6.3) 20 (12.5-30) Light chain, n (%)  κ 34 (59) 93 (62)  γ 24 (41) 56 (38) Other markers, median (IQR)  Hemoglobin, g/dL 13.3 (12.5-14.3) 12.9 (12.1-13.9)  Calcium, mg/dL 9.4 (9.1-9.7) 9.6 (9.1-9.8)  Creatinine, mg/dL 0.83 (0.74-0.98) 0.93 (0.74-1.14) BMPC, bone marrow plasma cell; iFLC, involved free light chain; IQR, interquartile range.

Baseline characteristics of analyzed patients with myeloma precursor conditions

BMPC, bone marrow plasma cell; iFLC, involved free light chain; IQR, interquartile range.

sBCMA levels during progression in patients with precursors and in patients with high-risk SMM treated with isatuximab alone or with lenalidomide. (A) Baseline sBCMA levels in patients with SMM and MGUS. Serum sBCMA levels were detected in 58 patients with MGUS (median, 44.34 ng/mL [IQR, 21.41-65.17]) and 149 patients with SMM (median, 109.02 ng/mL [IQR, 75.44-179.94]). (B) Serum sBCMA levels were detected in patients with MGUS with progression to SMM and those without progression at baseline (62.83 [IQR, 50.33-130.08] vs 43.17 [IQR, 14.25-58.83] ng/mL; n = 4 vs n = 36), 1 year (81.33 [IQR, 43.48-153.99] vs 36.95 [IQR, 15.82-58.69] ng/mL; n = 4 vs n = 35), and 3 years/time to progression; 139.53 [IQR, 131.72-222.55] vs 43.87 [IQR, 33.57-73.99] ng/mL; n = 3 vs n = 19). (C) Serum sBCMA levels were detected in patients with SMM with progression to active MM and those without progression at baseline (220.64 [IQR, 180.50-294.53] vs 100.96 [IQR, 75.97-136.26] ng/mL; n = 13 vs n = 63), 1 year (314.88 [IQR, 229.84-383.84] vs 62.48 [IQR, 46.44-101.71] ng/mL; n = 10 vs n = 53), and 3 years, or at the time of progression (340.98 [IQR, 221.61-450.15] vs 97.48 [IQR, 49.37-262.62] ng/mL; n = 10 vs n = 24). (D) Serum sBCMA levels were detected in responders vs nonresponders in cohort 1 at baseline (82.15 [IQR, 72.12-152.58] vs 134.39 [IQR, 82.73-196.50] ng/mL; n=15 vs n=9), the 6th cycle (16.32 [IQR, 10.66-23.13] vs 124.62 [IQR, 89.50-168.61] ng/mL; n = 15 vs n = 8), and the 18th cycle (14.71 [IQR, 10.56-26.39] vs 155.30 [IQR, 97.48-176.33] ng/mL; n = 15 vs n = 3). (E) Serum sBCMA levels were detected in responders vs nonresponders in cohort 2 at baseline (122.03 [IQR, 75.44-179.94] vs 189.73 [IQR, 137.52-204.68] ng/mL; n = 33 vs n = 3), the 6th cycle (16.53 [IQR, 13.36-41.36] vs 62.64 [IQR, 48.37-83.22] ng/mL; n = 33 vs n = 3), the 18th cycle (14.70 [IQR, 8.43-36.22] vs 108.20 [IQR, 81.33-135.06] ng/mL; n = 32 vs n = 2), and the 30th cycle (n = 26 vs n = 1). (F) ROC curve of sBCMA in cohort 2 of ISAMAR. Serum M-protein level was used as the reference response parameter, with an AUC of 1. IQR, interquartile range; ROC, receiver operating characteristic.

To further evaluate the predictive value of sBCMA in the setting of treatment of precursors, we examined its levels in the context of the ISAMAR trial, with patient characteristics shown in supplemental Table 3 . In cohort 1, sBCMA levels decreased significantly at the 6th and 18th cycles in 15 responders to single-agent isatuximab compared with 9 nonresponders ( P < .050; Figure 1 D). In cohort 2, 33 responders to isatuximab and lenalidomide had substantially lower sBCMA levels at both the 6th and 18th cycles than 3 nonresponders ( P < .050; Figure 1 E). In both cohorts, sBCMA levels correlated with serum M-protein levels at the 6th and 18th cycles ( P < .050; supplemental Table 4 ). Based on these findings, we assessed the predictive ability of sBCMA for treatment response using receiver operating characteristic analysis, with the serum M-protein level as a reference response parameter. In cohort 1, the AUC for sBCMA levels was estimated at 0.875 (95% CI, 0.692-0.992); in cohort 2, the AUC increased to 0.946 (95% CI, 0.857-1.000), as shown in Figure 1 F. These results suggest that sBCMA could also be a valuable biomarker for assessing treatment response.

In summary, our data, obtained from prospective clinical studies, support the possibility that baseline and longitudinal monitoring of sBCMA levels could serve as both a biomarker to risk stratify patients with precursors and to monitor their responses to treatment. Given the recent approval of daratumumab for patients with high-risk SMM from the AQUILA trial, 21 this could give clinicians an additional tool to identify at-risk patients. Moreover, sBCMA measurements performed with enzyme-linked immunosorbent assays may represent a relatively low-cost approach to monitoring vs M-protein measurements by serum electrophoresis and immunofixation. Finally, sBCMA testing could be especially valuable for the small proportion of patients who have oligo-secretory or nonsecretory precursor conditions. Future prospective studies with larger patient populations are necessary to validate these findings and hypotheses.

Conflict-of-interest disclosure: R.Z.O. has received research funding unrelated to this work from Heidelberg Pharma AG, Asylia Therapeutics, and Biotheryx; has served on advisory boards for Amgen, Inc, Bristol Myers Squibb, Celgene, EcoR1 Capital, LLC, Forma Therapeutics, Genzyme, GSK Biologicals, Ionis Pharmaceuticals, Inc, Janssen Biotech, Juno Therapeutics, Kite Pharma, Legend Biotech USA, Molecular Partners, Sanofi-Aventis, Servier, and Takeda Pharmaceuticals North America Inc; and is a founder of Asylia Therapeutics, Inc, with an equity interest. H.C.L. has provided consultancy services (paid to the institution) to AbbVie, Alexion Pharmaceuticals, Allogene Therapeutics, AstraZeneca, Bristol Myers Squibb, GSK, Janssen, Legend Biotech, Pfizer, Predicta Biosciences, Regeneron, Roche/Genentech, Sanofi, and Takeda. K.K.P. has received research support from Celgene. S.J. has received support from Bristol Myers Squibb, Janssen, Genmab, GSK, Sanofi, Takeda, Roche, Regeneron, and Caribou. The remaining authors declare no competing financial interests.

The current affiliation for H.C.L. is Sarah Cannon Research Institute, Nashville, TN.

The current affiliation for E.E.M. is Regeneron, Warren, NJ.

Acknowledgments

Acknowledgments: The authors thank Madison Semro (associate scientific editor) and Joe Munch (senior scientific editor) in the Research Medical Library at The University of Texas MD Anderson Cancer Center and their colleagues, Maria Jose Acevedo Calado and Upasana Ray, for word editing assistance.

This work was supported by the Miriam and Sheldon G. Adelson Medical Research Foundation (R.Z.O., E.E.M., and K.K.P.), the Riney Family Multiple Myeloma Research Fund at MD Anderson from the Paula and Rodger Riney Foundation (R.Z.O., E.E.M., H.C.L., and K.K.P.), The Reynolds & Reynolds Company, the Leukemia & Lymphoma Society (SCOR-12206-17) (R.Z.O., E.E.M., and H.C.L.), the MD Anderson High-Risk Multiple Myeloma Moon Shot (R.Z.O. and E.E.M.), the Brock Family Myeloma Research Fund (R.Z.O.), the Yates Ortiz Myeloma Fund (R.Z.O.), the Diane & John Grace Family Foundation (R.Z.O.), and The University of Texas MD Anderson Cancer Center Cancer Center Support Grant (P30CA016672).

Contribution: W.T. contributed to the methodology, validation, formal analysis, investigation, writing, editing, and visualization; S.L. contributed to the formal analysis, software, and writing, reviewing, and editing the manuscript; J.D. contributed to the software; D.A.B.N., M.H., and A.U.V. contributed to the data curation; I.K. contributed to the resources; R.Z.O. contributed to the formal analysis, supervision, writing, reviewing and editing the manuscript, and funding acquisition; E.E.M. contributed to the formal analysis, project administration, funding acquisition, conceptualization, and writing, reviewing, and editing the manuscript; C.K. contributed to writing, reviewing, and editing the manuscript and interpreting the data; and M.B., H.C.L., K.K.P., S.K.T., Z.L.-B., O.P., N.S.K., S.J., and O.L. contributed to the writing, reviewing, and editing the manuscript.

Footnotes

E.E.M. and R.Z.O. contributed equally to this study as senior authors.

Data are available from the corresponding author, Robert Z. Orlowski ( rorlowski@mdanderson.org ), on request.

The full-text version of this article contains a data supplement.

Supplementary Material

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References

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