Periodic Reporting for period 4 - bECOMiNG (spontaneous Evolution and Clonal heterOgeneity in MoNoclonal Gammopathies: from mechanisms of progression to clinical management)
Período documentado: 2023-09-01 hasta 2025-02-28
Multiple myeloma (MM), a blood cancer caused by the abnormal proliferation of plasma cells, arises from asymptomatic conditions such as monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM). These conditions may be detected incidentally years before clinical MM is diagnosed. However, many individuals with early-stage MM never progress to symptomatic disease. This raises two critical questions: i) from a biological standpoint, can we improve our understanding of what drives disease initiation and progression, and ii) can we better predict which patients will transition from asymptomatic stages to overt MM? Importantly, being diagnosed with an asymptomatic or pre-cancerous condition may induce psychological stress and reduce quality of life, making accurate risk stratification essential.
Our project focused on providing clinicians with more precise tools to evaluate disease trajectory. Existing clinical scores are largely based on indirect surrogate markers of tumor burden. Our goal was to identify more accurate molecular and cellular biomarkers associated with aggressive disease behavior, ultimately improving the accuracy of prognostic assessments. Patients with biologically high-risk disease could be monitored more intensively or treated earlier, while those without adverse features could be spared unnecessary anxiety and interventions.
We tackled prognostication from multiple complementary angles: biochemical analyses, whole-genome sequencing, and single-cell analysis of tumor cells and the bone marrow (BM) microenvironment. Our genomic studies demonstrated that the mutational landscape of progressive versus non-progressive cases is fundamentally different. Specific genetic alterations were exclusively observed in cases that eventually progressed to symptomatic MM. These insights support a redefinition of what constitutes indolent versus aggressive disease. These findings are now being assessed in a larger international study involving extensive patient cohorts.
In parallel, we contributed samples to a collaborative effort evaluating the prognostic value of serial biochemical markers. Early results suggest certain changes, such as declining hemoglobin levels, can serve as useful indicators of progression. These data are being incorporated into a dynamic risk scoring model for clinical use and will be publicly available soon.
Our single-cell work has also yielded novel insights. We developed a high-resolution pipeline to distinguish tumoral from non-tumoral plasma cells in patients with asymptomatic MM. This enabled the first in-depth profiling of “normal” plasma cells in these individuals. While these cells are not clonal, they nonetheless show altered function, implying that the tumor microenvironment (TME) exerts broader immunological disruption. Such dysfunction may play a role in disease progression and patient susceptibility to infection.
Our project focused on providing clinicians with more precise tools to evaluate disease trajectory. Existing clinical scores are largely based on indirect surrogate markers of tumor burden. Our goal was to identify more accurate molecular and cellular biomarkers associated with aggressive disease behavior, ultimately improving the accuracy of prognostic assessments. Patients with biologically high-risk disease could be monitored more intensively or treated earlier, while those without adverse features could be spared unnecessary anxiety and interventions.
We tackled prognostication from multiple complementary angles: biochemical analyses, whole-genome sequencing, and single-cell analysis of tumor cells and the bone marrow (BM) microenvironment. Our genomic studies demonstrated that the mutational landscape of progressive versus non-progressive cases is fundamentally different. Specific genetic alterations were exclusively observed in cases that eventually progressed to symptomatic MM. These insights support a redefinition of what constitutes indolent versus aggressive disease. These findings are now being assessed in a larger international study involving extensive patient cohorts.
In parallel, we contributed samples to a collaborative effort evaluating the prognostic value of serial biochemical markers. Early results suggest certain changes, such as declining hemoglobin levels, can serve as useful indicators of progression. These data are being incorporated into a dynamic risk scoring model for clinical use and will be publicly available soon.
Our single-cell work has also yielded novel insights. We developed a high-resolution pipeline to distinguish tumoral from non-tumoral plasma cells in patients with asymptomatic MM. This enabled the first in-depth profiling of “normal” plasma cells in these individuals. While these cells are not clonal, they nonetheless show altered function, implying that the tumor microenvironment (TME) exerts broader immunological disruption. Such dysfunction may play a role in disease progression and patient susceptibility to infection.
1. Understanding MM Initiation (Preclinical Phase):
We examined bone marrow samples from healthy individuals to investigate whether MM shares origins with other clonal blood disorders like CHIP (Clonal Hematopoiesis of Indeterminate Potential). Our findings showed that while CHIP is common in older individuals, it does not share a progenitor with plasma cell neoplasms, suggesting separate evolutionary trajectories. Additionally, by using mutational timing analyses, we estimated that the earliest genetic lesions leading to MM can arise decades before diagnosis, although these early cells are extremely rare and currently difficult to detect.
2. Monitoring Early Disease (Smoldering Myeloma Studies):
We assembled and analyzed samples from patients with high-risk MGUS, SMM, and overt MM. Genomic and single-cell analyses showed that while some initiating mutations are shared, those driving progression are distinct and often involve complex genetic changes, including chromothripsis and aberrant DNA repair signatures. These alterations are frequently missed by standard diagnostic methods. We are working with collaborators to develop clinical-grade tools to detect such changes. This work is being supported by a European Research Council “Proof of Concept” grant. One consistent clinical observation was that a decline in hemoglobin often precedes progression—this is now being validated in risk models.
3. Single-Cell Studies:
Using a novel B-cell receptor (BCR) barcoding strategy, we successfully distinguished malignant plasma cells from normal ones at the single-cell level. Surprisingly, even non-clonal plasma cells displayed abnormal gene expression patterns, particularly in pathways related to immune function. These findings may explain the impaired immune responses observed in MM patients, even at asymptomatic stages. We are currently analyzing how these cellular states evolve over time and contribute to immune suppression and progression.
4. Targeting Disease Drivers and Testing New Drugs:
We found KRAS mutations to be enriched in progressive MM cases. In collaboration with partners, we tested KRAS-targeting compounds in cell models. We also developed a computational framework that links patient-derived molecular profiles with known cell lines to predict treatment responses. This led to identification of biomarkers for sensitivity to venetoclax, an emerging therapy for MM patients with specific genetic subtypes. We further studied FAM46C, a tumor suppressor gene often inactivated in MM, and demonstrated its role in regulating plasma cell proliferation and drug target gene expression, underscoring its potential as a therapeutic target.
5. 3D Disease Modeling:
To better replicate the bone marrow niche, we created a 3D culture system using silk-based scaffolds that support the survival and function of patient-derived plasma cells and other BM components. This model allows for more realistic in vitro study of disease biology and drug responses. Initial results are promising, and we plan to scale this platform for broader functional and therapeutic screening.
We examined bone marrow samples from healthy individuals to investigate whether MM shares origins with other clonal blood disorders like CHIP (Clonal Hematopoiesis of Indeterminate Potential). Our findings showed that while CHIP is common in older individuals, it does not share a progenitor with plasma cell neoplasms, suggesting separate evolutionary trajectories. Additionally, by using mutational timing analyses, we estimated that the earliest genetic lesions leading to MM can arise decades before diagnosis, although these early cells are extremely rare and currently difficult to detect.
2. Monitoring Early Disease (Smoldering Myeloma Studies):
We assembled and analyzed samples from patients with high-risk MGUS, SMM, and overt MM. Genomic and single-cell analyses showed that while some initiating mutations are shared, those driving progression are distinct and often involve complex genetic changes, including chromothripsis and aberrant DNA repair signatures. These alterations are frequently missed by standard diagnostic methods. We are working with collaborators to develop clinical-grade tools to detect such changes. This work is being supported by a European Research Council “Proof of Concept” grant. One consistent clinical observation was that a decline in hemoglobin often precedes progression—this is now being validated in risk models.
3. Single-Cell Studies:
Using a novel B-cell receptor (BCR) barcoding strategy, we successfully distinguished malignant plasma cells from normal ones at the single-cell level. Surprisingly, even non-clonal plasma cells displayed abnormal gene expression patterns, particularly in pathways related to immune function. These findings may explain the impaired immune responses observed in MM patients, even at asymptomatic stages. We are currently analyzing how these cellular states evolve over time and contribute to immune suppression and progression.
4. Targeting Disease Drivers and Testing New Drugs:
We found KRAS mutations to be enriched in progressive MM cases. In collaboration with partners, we tested KRAS-targeting compounds in cell models. We also developed a computational framework that links patient-derived molecular profiles with known cell lines to predict treatment responses. This led to identification of biomarkers for sensitivity to venetoclax, an emerging therapy for MM patients with specific genetic subtypes. We further studied FAM46C, a tumor suppressor gene often inactivated in MM, and demonstrated its role in regulating plasma cell proliferation and drug target gene expression, underscoring its potential as a therapeutic target.
5. 3D Disease Modeling:
To better replicate the bone marrow niche, we created a 3D culture system using silk-based scaffolds that support the survival and function of patient-derived plasma cells and other BM components. This model allows for more realistic in vitro study of disease biology and drug responses. Initial results are promising, and we plan to scale this platform for broader functional and therapeutic screening.
Our research has significantly advanced the field in multiple ways:
• We demonstrated that MM-initiating mutations can occur decades before clinical symptoms, emphasizing the long preclinical phase of disease.
• We confirmed that MM arises independently from CHIP, challenging earlier assumptions about shared clonal origins in aging bone marrow.
• We identified genetic signatures that distinguish patients likely to progress from those who remain stable, contributing to a more refined classification system for asymptomatic MM.
• Our single-cell work uncovered widespread immune dysfunction, even in non-malignant cells, providing insight into why MM patients are prone to infections.
• The new 3D scaffold-based BM model offers a more physiologically relevant platform for studying MM and testing drugs, moving us closer to personalized therapeutic strategies.
These findings not only enhance our understanding of MM biology and progression but also provide tangible clinical tools that may soon influence diagnostics, patient monitoring, and treatment decisions. Data and materials generated from this project are being shared with international partners and will contribute to large-scale efforts to redefine clinical management of asymptomatic myeloma.
• We demonstrated that MM-initiating mutations can occur decades before clinical symptoms, emphasizing the long preclinical phase of disease.
• We confirmed that MM arises independently from CHIP, challenging earlier assumptions about shared clonal origins in aging bone marrow.
• We identified genetic signatures that distinguish patients likely to progress from those who remain stable, contributing to a more refined classification system for asymptomatic MM.
• Our single-cell work uncovered widespread immune dysfunction, even in non-malignant cells, providing insight into why MM patients are prone to infections.
• The new 3D scaffold-based BM model offers a more physiologically relevant platform for studying MM and testing drugs, moving us closer to personalized therapeutic strategies.
These findings not only enhance our understanding of MM biology and progression but also provide tangible clinical tools that may soon influence diagnostics, patient monitoring, and treatment decisions. Data and materials generated from this project are being shared with international partners and will contribute to large-scale efforts to redefine clinical management of asymptomatic myeloma.