Review Reports - How Laboratory Innovations Are Shaping the Future of Multiple Myeloma Care

Round 1

Reviewer 1 Report

Comments and Suggestions for Authors

The manuscript “How Laboratory Innovations Are Shaping the Future of Multiple Myeloma Carcinoma” reviews current and emerging methods for diagnosing and monitoring multiple myeloma. The manuscript is generally well organized, but there are several issues that should be addressed before publication.
- The manuscript mainly focuses on advantages of new techniques but does not sufficiently discuss their limitations (e.g. cost, availability, need for standardization, limited validation in large clinical trials, regulatory challenges, etc.) Please add a section discussing limitations, barriers and bottlenecks for each method.
- The manuscript often presents new methods as if they are already ready for routine clinical use. For example, mass spectrometry is described as potentially replacing current standard methods, and MRD-guided strategies are presented as future standard without enough caution. I recommend the use of more cautious language like “promising”, “under invertigation”, or simply “not yet standard practice”.
- The statement “CR and sCR… now achieved by most patients” is not universally accurate. It depends on transplant eligibility, regimen, or risk group. Please replace with something similar to "increasing proportion of patients" and provide quantitative ranges & citation.
- There are some inconsistencies like MRD vs minimal/measurable residual disease, or CTC vs circulating tumor plasma cells. Please use consistent terminology throughout the manuscript.
- Table 2 includes important clinical trials such as PERSEUS and MASTER; however, the main text does not provide a meaningful discussion of their results. In addition, the “Main Outcome” column is too brief (e.g., “ongoing evaluation”), which limits the usefulness of the table. The authors should expand both the table and the corresponding text to better summarize key findings and clinical implications of these studies.
- In the AI section, the manuscript refers to the use of artificial intelligence in “gating strategies” in flow cytometry. For a general oncology audience, this concept may not be familiar. Please add a brief explanation of what gating is, and why it can be subjective and operator-dependent.
- There is also a need to clarify the discussion around MRD sensitivity thresholds. The manuscript notes that both NGF and NGS achieve the International Myeloma Working Group-recommended sensitivity of 10⁻⁵, but then suggests that 10⁻⁶ has greater clinical value. It should be explicitly stated that 10⁻⁶ is increasingly considered the preferred target in high-quality studies to more accurately define MRD negativity.
- Figure 1 appears to contain a typographical error, with a sensitivity range reported as 10¹⁵–10¹⁶. This should likely read 10⁻⁵-10⁻⁶ and needs correction.
- The liquid biopsy section would benefit from expansion. Given the forward-looking nature of the review, the authors should include a more detailed comparison between circulating cell-free DNA (cfDNA) and circulating tumor cells (CTCs), particularly in the context of capturing spatial heterogeneity. A focused subsection outlining the advantages and limitations of each approach would add significant value.
- Minor error typo: Food and Drug Administration (FNA) should be FDA

Author Response

Reviewer 1

Comment 1: The manuscript mainly focuses on advantages of new techniques but does not sufficiently discuss their limitations (e.g. cost, availability, need for standardization, limited validation in large clinical trials, regulatory challenges, etc.) Please add a section discussing limitations, barriers and bottlenecks for each method.

Response 1: Thank you for this important comment. We agree that, in addition to highlighting the advantages of emerging laboratory technologies, it is essential to discuss their current limitations, barriers to implementation, and the need for further validation. The discussion of limitations has been further strengthened in the revised manuscript. We have introduced in the revised manuscript a dedicated subsection (“Challenging to Clinical Implementation”) for each technique, aiming to provide a more balanced and realistic overview of the clinical applicability of these technologies. This addition complements the existing discussion of analytical and biological limitations.

Comment 2: The manuscript often presents new methods as if they are already ready for routine clinical use. For example, mass spectrometry is described as potentially replacing current standard methods, and MRD-guided strategies are presented as future standard without enough caution. I recommend the use of more cautious language like “promising”, “under invertigation”, or simply “not yet standard practice”.

Response 2: Thank you for this important and constructive comment. The manuscript has been revised to adopt a more cautious and balanced tone regarding the clinical implementation of emerging technologies. In the specific case of the Mass Spectrometry section, statements suggesting replacement of conventional techniques have been refined to better reflect its current role, emphasizing that MS is an evolving approach that is being progressively integrated into clinical practice rather than universally implemented. More cautious wording has been introduced throughout this section (e.g., “promising”, “may”, “currently being integrated”) to more accurately represent the current level of evidence and real-world applicability.

Comment 3: The statement “CR and sCR… now achieved by most patients” is not universally accurate. It depends on transplant eligibility, regimen, or risk group. Please replace with something similar to "increasing proportion of patients" and provide quantitative ranges & citation.

Response 3: We thank the reviewer for this comment and have made the correction accordingly.

Comment 4: There are some inconsistencies like MRD vs minimal/measurable residual disease, or CTC vs circulating tumor plasma cells. Please use consistent terminology throughout the manuscript.

Response 4: Thank you for bringing this to our attention. We revised the manuscript and made the necessary corrections.

Comment 5: Table 2 includes important clinical trials such as PERSEUS and MASTER; however, the main text does not provide a meaningful discussion of their results. In addition, the “Main Outcome” column is too brief (e.g., “ongoing evaluation”), which limits the usefulness of the table. The authors should expand both the table and the corresponding text to better summarize key findings and clinical implications of these studies.

Response 5: Thank you for this insightful suggestion. In the first draft version of the manuscript, we had a more detailed description of the key clinical studies. To reduce the length of the text, we opted to include just a table summarizing them. As per the reviewer’s suggestion, we included the expanded text and improved Table 2 to better represent the MRD-based strategy and implications of the clinical trials mentioned in the text.

Comment 6: In the AI section, the manuscript refers to the use of artificial intelligence in “gating strategies” in flow cytometry. For a general oncology audience, this concept may not be familiar. Please add a brief explanation of what gating is, and why it can be subjective and operator-dependent.

Response 6: Thank you for this helpful suggestion. A brief explanation of gating in flow cytometry has been added in the Artificial Intelligence section to improve clarity for a broader audience. Specifically, gating is now defined as the process of identifying and classifying cell populations based on marker expression, and its operator-dependent nature and potential variability are explicitly acknowledged.

Comment 7: There is also a need to clarify the discussion around MRD sensitivity thresholds. The manuscript notes that both NGF and NGS achieve the International Myeloma Working Group-recommended sensitivity of 10⁻⁵, but then suggests that 10⁻⁶ has greater clinical value. It should be explicitly stated that 10⁻⁶ is increasingly considered the preferred target in high-quality studies to more accurately define MRD negativity.

Response 7: We appreciate the insightful comment by the reviewer. Indeed, we agree that the addition of 10⁻⁶ as the preferred target to define MRD negativity more accurately is relevant. As such, we have included a statement in that regard in the revised manuscript.

Comment 8: Figure 1 appears to contain a typographical error, with a sensitivity range reported as 10¹⁵–10¹⁶. This should likely read 10⁻⁵-10⁻⁶ and needs correction.

Response 8: We thank the reviewer for his comment. We understand that it might not be visible due to the font size. As such, the figure was altered to improve clarity.

Comment 9: The liquid biopsy section would benefit from expansion. Given the forward-looking nature of the review, the authors should include a more detailed comparison between circulating cell-free DNA (cfDNA) and circulating tumor cells (CTCs), particularly in the context of capturing spatial heterogeneity. A focused subsection outlining the advantages and limitations of each approach would add significant value.

Response 9: Thank you for this valuable suggestion. We agree that a more detailed comparison between circulating cell-free DNA (cfDNA) and circulating tumor cells (CTCs), particularly regarding their ability to capture spatial heterogeneity, would strengthen the liquid biopsy section. In response to this comment, we have included a more detailed discussion of the advantages and limitations of each. To keep in line with the structure of the manuscript (a suggestion by the other reviewer to improve readability), we opted not to create a specific comparative subsection but included the discussion in each of the approaches. Furthermore, we also added a new table (Table 3) showing a synthesized and focused comparison.

Comment 10: Minor error typo: Food and Drug Administration (FNA) should be FDA

Response 10: The typo error was corrected.

Reviewer 2 Report

Comments and Suggestions for Authors

The authors provide a comprehensive review of cutting-edge technological advances in the laboratory diagnosis, monitoring, and personalized treatment of multiple myeloma. The content is broad in scope and closely aligned with current developments in the field, yet some issues remain that could be addressed by considering the following suggestions for improvement.

Comment 1

The manuscript suffers from structural redundancy and inconsistent formatting. Notably, certain detection technologies include separate subsections entitled "Challenges to Clinical Implementation and Future Perspectives," while others do not, contributing to unnecessary length and a lack of uniformity. It is recommended to standardize the structure to improve readability.

Comment 2

While the article reviews various laboratory innovative technologies for the diagnosis and treatment of multiple myeloma, it fails to conduct a stratified analysis in conjunction with the complete clinical course of the disease, targeting distinct disease stages including the precursor stage (MGUS/SMM), newly diagnosed multiple myeloma (NDMM), relapsed/refractory multiple myeloma (RRMM), and post-transplantation period. It lacks a systematic elaboration and definition of the adaptability, optimal application scenarios, specific detection thresholds, and stage-specific clinical value of different technologies at each stage.

Comment 3

Although the article provides a detailed description of the analytical performance and assessment advantages of various novel technologies, most of the discussion remains at the level of "technologies can optimize assessment." It does not adequately provide direct evidence of improvements in clinical endpoints (such as time to relapse detection, progression-free survival, overall survival, and treatment response rate) following the application of these technologies. The lack of such critical data weakens the persuasiveness of the clinical value of these novel technologies.

Comment 4

The article primarily discusses the analytical performance of various emerging technologies in the context of common subtypes of multiple myeloma. However, it lacks analysis of the detection efficacy and limitations of these technologies in special subtypes and vulnerable populations, such as oligosecretory myeloma, extramedullary myeloma, and myeloma with renal impairment. Rare subtypes are often difficult to accurately assess due to insufficient sensitivity of conventional detection methods or the presence of comorbidities; precisely these subtypes require highly sensitive and specific novel detection approaches, which may offer unique advantages in evaluating such cases.

Comment 5

The manuscript has the following issues regarding detail standardization: (1) Inconsistent formatting of sensitivity thresholds, with "10-5" and "10-6" appearing in the main text instead of superscript format. Consistent formatting is recommended throughout. (2) Some abbreviations are not defined at first use, such as "MinimuMM-seq", "MRD-SURE" in Table 2. A systematic review of abbreviation usage is recommended.

Comment 6

The article involves several core concepts and emerging terms, but some are vaguely defined: (1) the definitional boundaries, equivalency, and clinical positioning of "serum-based MRD" versus "bone marrow MRD" are not clarified; (2) terms such as "black box models" and "explainable AI" are mentioned in the artificial intelligence section without basic explanations, making them difficult for non-specialist readers to understand. It is recommended to supplement the conceptual clarification of these terms to improve readability.

Author Response

Comment 1: The manuscript suffers from structural redundancy and inconsistent formatting. Notably, certain detection technologies include separate subsections entitled "Challenges to Clinical Implementation and Future Perspectives," while others do not, contributing to unnecessary length and a lack of uniformity. It is recommended to standardize the structure to improve readability.

Response 1: We thank the reviewer for this observation. The original structure reflected a deliberate distinction between established methodologies (NGF, NGS), for which clinical implementation is already recognized, and emerging technologies (CTC, cfDNA/cfRNA, MS, novel molecular biomarkers, AI/ML), for which barriers to clinical translation remain an active area of discussion. We recognize, however, that this distinction was not explicitly communicated and resulted in structural inconsistency that affects readability. We have revised the manuscript to standardize the structure across all sections addressing emerging technologies, ensuring that each now includes a dedicated subsection titled "Challenges to Clinical Implementation". The sections addressing established methodologies retain their original structure, as the asymmetry is now explicitly justified in the introductory text.

Comment 2: While the article reviews various laboratory innovative technologies for the diagnosis and treatment of multiple myeloma, it fails to conduct a stratified analysis in conjunction with the complete clinical course of the disease, targeting distinct disease stages including the precursor stage (MGUS/SMM), newly diagnosed multiple myeloma (NDMM), relapsed/refractory multiple myeloma (RRMM), and post-transplantation period. It lacks systematic elaboration and definition of adaptability, optimal application scenarios, specific detection thresholds, and stage-specific clinical value of different technologies at each stage.

Response 2: We thank the reviewer for this important and constructive observation. We acknowledge that the manuscript, in its current form, does not systematically stratify the clinical utility of each technology according to disease stage. While the scope of this review was intentionally focused on MM diagnosis and response evaluation, primarily in the NDMM and RRMM settings, we agree that a more explicit stage-specific framework would substantially improve the manuscript's clinical utility and rigor. In response, we have made the following revisions: (1) we have added a summary table (Table 3) mapping MS, CTC, cfDNA/RNA to the relevant disease stage, including available detection thresholds, optimal application scenarios, and limitations; (2) where data exist, we have addressed performance differences across disease stages; (3) we added the potential role of key technologies in precursor disease monitoring, acknowledging this as an emerging area warranting dedicated future investigation. We believe these additions directly address the reviewer's concern while preserving the primary focus of the manuscript.

Comment 3: Although the article provides a detailed description of the analytical performance and assessment advantages of various novel technologies, most of the discussion remains at the level of "technologies can optimize assessment." It does not adequately provide direct evidence of improvements in clinical endpoints (such as time to relapse detection, progression-free survival, overall survival, and treatment response rate) following the application of these technologies. The lack of such critical data weakens the persuasiveness of the clinical value of these novel technologies.

Response 3: We thank the reviewer for this important observation, which touches on a fundamental distinction between demonstrating that a laboratory technology correlates with clinical outcomes, and that clinical decisions guided by them improve those outcomes. We acknowledge that, for several of the technologies reviewed, robust prospective interventional data directly linking their clinical application to improve endpoints such as OS, PFS, or time to relapse are not yet available. This reflects the current state of the field, and we have revised the manuscript to make this distinction explicit. A statement that most technologies discussed are at the stage of prognostic biomarker validation, but not all have been prospectively tested as decision-making tools (Section 6). That said, we wish to highlight that the manuscript was improved to more explicitly indicate in the revised text, for each section and when available, such as prospective MRD-guided trials, data demonstrating that undetectable CTC by NGF is associated with PFS and OS with independent prognostic value confirmed in multivariate analysis, a meta-analysis confirming higher ctDNA levels are associated with significantly worse PFS and OS, or Mass-Fix positivity post-treatment independently predicting PFS and OS. We agree with the reviewer that for emerging technologies, including cfRNA, novel molecular biomarkers, and AI/ML tools, prospective clinical endpoint data are currently limited, and the evidence base remains largely exploratory. We have revised the relevant sections to be transparent about this limitation.

Comment 4: The article primarily discusses the analytical performance of various emerging technologies in the context of common subtypes of multiple myeloma. However, it lacks analysis of the detection efficacy and limitations of these technologies in special subtypes and vulnerable populations, such as oligosecretory myeloma, extramedullary myeloma, and myeloma with renal impairment. Rare subtypes are often difficult to accurately assess due to insufficient sensitivity of conventional detection methods or the presence of comorbidities; precisely these subtypes require highly sensitive and specific novel detection approaches, which may offer unique advantages in evaluating such cases.

Response 4: We thank the reviewer for this clinically important observation. We agree that special subtypes such as oligosecretory and non-secretory MM, extra medullary (EM) disease, and MM complicated by renal impairment represent precisely the clinical contexts where the sensitivity and spatial coverage limitations of conventional laboratory methods are most acutely felt, and where novel technologies may offer their greatest added value. In response, we have made the following targeted revisions to the manuscript: 1) For oligosecretory and non-secretory MM, within the MS section we address that these patients are underserved by conventional serological monitoring (SPE, sIFE, sFLC), and that MS offers specific advantages in this subtype. The value of BM-independent and serology-independent approaches in patients with minimal or absent M-protein secretion is now explicitly stated as well in CTC enumeration, and cfDNA/cfRNA analysis. 2) For EM MM, we have strengthened discussion, particularly in the CTC and cfDNA sections to explicitly frame the spatial coverage advantage in this subtype. The correlation between high ctDNA levels and PET/CT-detected EM and PS lesions is also cited in the cfDNA section, to make its specific relevance to EM disease more evident. 3) For MM with renal impairment, we acknowledge the reviewer's point and have added a brief discussion in the MS section, noting that renal dysfunction affects sFLC interpretation and may confound some serological endpoints. We have also been transparent in indicating that dedicated published evidence for performance of novel laboratory technologies in these patients remains limited in the other sections. We have also added a brief line explicitly identifying these populations as major areas for future technology validation studies, given that these are the settings where the clinical need for highly sensitive and spatially comprehensive assessment is greatest. We believe these revisions address the reviewer's concern while remaining within the scope and evidence base of the current manuscript.

Comment 5: The manuscript has the following issues regarding detail standardization: (1) Inconsistent formatting of sensitivity thresholds, with "10-5" and "10-6" appearing in the main text instead of superscript format. Consistent formatting is recommended throughout. (2) Some abbreviations are not defined at first use, such as "MinimuMM-seq", "MRD-SURE" in Table 2. A systematic review of abbreviation usage is recommended.

Response 5: We thank the reviewer for this observation. We have revised the manuscript and made the necessary corrections.

Comment 6: The article involves several core concepts and emerging terms, but some are vaguely defined: (1) the definitional boundaries, equivalency, and clinical positioning of "serum-based MRD" versus "bone marrow MRD" are not clarified; (2) terms such as "black box models" and "explainable AI" are mentioned in the artificial intelligence section without basic explanations, making them difficult for non-specialist readers to understand. It is recommended to supplement the conceptual clarification of these terms to improve readability.

Response 6: Thank you for this important comment. We agree that the distinction between serum-based MRD and BM MRD requires clearer definition and clinical contextualization. We have added a clarification of those concepts to facilitate understanding for a broader audience.

Round 2

Reviewer 1 Report

Comments and Suggestions for Authors

No further comments.