WO2023107473A1 - Identifying monoclonal gammopathies in a high-risk population for hematological malignancies - Google Patents

Abstract

Provided herein are methods and immune biomarkers that identify progression and treatment options for hematological malignancies such as monoclonal gammopathy of indeterminate potential (MGIP), any precursor of multiple myeloma (MM), MM, and a B cell Lymphoproliferative Disorder. Also provided are materials and methods for the prognosis, staging, and monitoring of MGIP, MGUS, any precursor of MM, MM, and/or a B cell Lymphoproliferative Disorder based on the presence of the M-protein in a sample and include methods of determining a subject as being at risk of developing multiple myeloma (MM) or a B cell Lymphoproliferative Disorder, the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L to 0.2 g/L in the sample. The methods provided herein provide several advantages over invasive biopsies.

Description

IDENTIFYING MONOCLONAL GAMMOPATHIES IN A HIGH-RISK POPULATION FOR HEMATOLOGICAL MALIGNANCIES

CROSS-REFERENCE TO RELATED APPLICATION

This application claims the benefit of priority of U.S. Provisional Appl. No. 63/286,978 filed December 7, 2021. This priority application is incorporated by reference herein in its entirety.

TECHNICAL FIELD

This disclosure relates generally to the screening, detection, prognosis, and treatment of subjects having monoclonal gammopathy (M-protein) in high-risk populations using highly sensitive and high-throughput methods.

BACKGROUND

Plasma cell dyscrasias are disorders of plasma cells. Multiple Myeloma (MM) is a plasma cell dyscrasia characterized by patchy bone marrow infiltration leading to multiple bone lytic lesions and cytopenias at the time of diagnosis. Bone marrow biopsies are limited in that sampling allows assessment of only one site where the tumor clones and their immune microenvironment can be different from those present in other areas of the bone marrow and may not be reflective of the total disease heterogeneity. It is also a painful procedure for patients and patients with precursor state monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM) do not have bone marrow biopsies performed regularly, which precludes regular assessment of their progression risk.

MM is an incurable plasma cell malignancy that resides in the bone marrow and is preceded by asymptomatic conditions. Identifying the patients — particularly those in high- risk groups — who will benefit the most from early intervention remains an unmet clinical need. All approaches described to date relied on identification of the M-protein and the involved isotype at protein detection levels of approximately greater than 0.2 g/L per sample. There remains a need to develop highly sensitive detection methods in high-risk populations for early detection of MM or its precursors.

SUMMARY

Provided herein are non-invasive methods (e.g., a blood biopsy) to identify progression and clonal evolution of plasma cell dyscrasias, including early detection of precursors of multiple myeloma, monitoring progression of disease, and detecting earlier M-proteins to serve as biomarkers of immune dysregulation, decreased overall survival and association with a variety of clinical comorbidities. Also provided are materials and methods for the diagnosis, prognosis, staging, and monitoring of plasma cell dyscrasias based on the presence of a biomarker (i.e., M-protein) in a blood biopsy, as well as methods for monitoring the progression of a plasma cell dyscrasia (e.g., MM or its precursors), determining the efficacy of a therapeutic agent, determining a targeted therapy for a plasma cell dyscrasia, and/or treating a plasma cell dyscrasia, and earlier detection of immune dysregulation, and other clinical comorbidities. Also, provided herein is a novel method that allows for detection of low-level monoclonal proteins that show a clinical association with other common clinical comorbidities not related to MM, such as myocardial infarct and other.

The current standard of care does not include routine screening for MM precursor disease in high-risk individuals. Identified herein are early methods of detection, including detection of M-protein in populations. The presently disclosed methods include highly sensitive technology for screening individuals at high risk of disease (e.g., developing MM) to intercept disease earlier to prevent progression to overt symptomatic myeloma through clinical follow-up and early therapeutic intervention when applicable, and the detection of M-proteins as a biomarker for other etiologies including but not limited to, immune dysregulation, hematologic malignancies, and other comorbidities.

Current monitoring of response to therapy and assessment of measurable residual disease (MRD) relies on the quantification of M-protein in the peripheral blood of treated individuals. Using this same approach in the setting of precursor disease here presents a less-invasive testing method that could be used more often for closer monitoring with similar results.

Herein, the prevalence and clinical significance of small amounts of M-proteins were readily detected by screening high-risk individuals using a sensitive high-throughput quantitative MS approach. These data are positioned to unveil more precise estimates of disease and outcomes across racial and family-history-based risk groups, and reveal the clinical significance of low concentration M-proteins detected by the ultra-sensitive MS (i.e., MALDI-TOF) screening approach. This disclosure provided herein improves our understanding of the significance of early detection of monoclonal gammopathies, including a subgroup — monoclonal gammopathy of indeterminate potential (MGIP) — which is disclosed herein for the first time.

Applicant has identified methods that include the use of mass spectrometry screening and early detection using the high-sensitivity approach for a M-protein as a potential biomarker of hematologic malignancies, as an example multiple myeloma and its precursor conditions. The methods can be used in a patient with MM-precursor conditions using the high-sensitivity approach allows for tracking progression and clinical F/U for the prediction of progression from earlier stages to more advanced overt malignancy (MM). The methods can further be used in the aging population blood testing using MS allows for the detection of monoclonal gammopathies as a biomarker of underlying immune dysregulation and other diseases autoimmune diseases, myocardial infarct, and hematologic malignancies, namely Hodgkin’s lymphoma and decreased overall.

Thus, provided herein is a method of determining a subject as having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample. Also provided is a method of determining a subject as having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and 30 g/L in the sample. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG.

A second feature provided herein includes a method of determining a subject as having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; and (b) detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG. Also provided herein includes a method of determining a subject as having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; and (b) detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and 30 g/L in the sample. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM.

A third feature provided herein includes a method of monitoring a subject having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample; and (c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months. In some instances, for example where there is a persistence of the M protein in serial samples from the subject, the method further involves treating the subject with a therapeutically effective amount of a treatment for the hematological malignancy. Persistence of the M-protein detected at baseline is defined as the presence of the same isotype M protein in a serial sample and within +/- 5 mass to charge ratio on mass spectra. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG. Also provided herein includes a method of monitoring a subject having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and 30 g/L in the sample; and (c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM.

Also provided herein includes a method of monitoring a subject having, or being at risk of developing, a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of greater than or equal to 0.2 g/L but less than 30g/L in the sample; and (c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM. In some instances, for example where there is a persistence of the M protein in serial samples from the subject, the method further involves treating the subject with a therapeutically effective amount of a treatment for the hematological malignancy. In some instances, the treatment includes one or more of an immunotherapeutic vaccine, one or more bispecific antibodies, CAR-T therapy, lenalidomide, daratumumab, isatuximab, bortezomib, carfilzomib, and dexamethasone.

A fourth feature provided herein includes a method of treating a subject having an increased risk of developing a hematological malignancy (e.g., multiple myeloma (MM) or any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample; and (c) providing a therapeutically effective amount of a treatment for the hematological malignancy to the subject. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG. In some instances, the treatment includes one or more of an immunotherapeutic vaccine, one or more bispecific antibodies, CAR-T therapy, lenalidomide, daratumumab, isatuximab, bortezomib, carfilzomib, and dexamethasone. In some instances, the disclosure features a method of treating a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising administering to the subject a therapeutically effective amount of a treatment for the hematological malignancy, wherein the subject was previously determined to have an M- protein concentration of between 0.015 g/L and less than 0.2 g/L in a sample obtained from the subject who was identified as having a risk factor for developing the hematological malignancy. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG. In some instances, the treatment includes one or more of an immunotherapeutic vaccine, one or more bispecific antibodies, CAR-T therapy, lenalidomide, daratumumab, isatuximab, bortezomib, carfilzomib, and dexamethasone.

Also provided herein is a method of treating a subject having an increased risk of developing a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising: (a) identifying the subject as having a risk factor for developing the hematological malignancy; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and 30 g./L in the sample; and (c) providing a therapeutically effective amount of a treatment for the hematological malignancy to the subject. In some instances, the disclosure features a method of treating a hematological malignancy (e.g., multiple myeloma (MM), any precursor of MM), the method comprising administering to the subject a therapeutically effective amount of a treatment for the hematological malignancy, wherein the subject was previously determined (e.g., by mass spectrometry, MALDI-TOF) to have an M-protein concentration of between 0.2 g/L and 30 g/L in a sample obtained from the subject who was identified as having a risk factor for developing the hematological malignancy. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM. In some instances, the treatment includes one or more of an immunotherapeutic vaccine, one or more bispecific antibodies, CAR-T therapy, lenalidomide, daratumumab, isatuximab, bortezomib, carfilzomib, and dexamethasone.

In particular, disclosed herein is a method of determining a subject as being at risk of developing multiple myeloma (MM), the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by e.g., mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample. In some instances, this subject has MGIP. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG

Also disclosed herein is a method of determining a subject as having, or being at risk of developing, multiple myeloma (MM), the method comprising: (a) identifying the subject as having a risk factor for developing MM; and (b) detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample. In some instances, this subject has MGIP. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG

Also disclosed herein is a method of monitoring a subject having, or being at risk of developing, multiple myeloma (MM), the method comprising: (a) identifying the subject as having a risk factor for developing MM; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample; and (c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months. In some instances, this subject has MGIP. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG

Also disclosed herein is a method of treating a subject having an increased risk of developing multiple myeloma (MM), the method comprising: (a) identifying the subject as having a risk factor for developing MM; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample; and (c) providing an therapeutically effective amount of a treatment to the subject. In some instances, this subject has MGIP. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M- protein is IgG. In some instances, the treatment includes one or more of an immunotherapeutic vaccine, one or more bispecific antibodies, CAR-T therapy, lenalidomide, daratumumab, isatuximab, bortezomib, carfilzomib, and dexamethasone.

Also disclosed herein is a method of determining a subject as having, or being at risk of developing, multiple myeloma (MM), the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample. In some instances, this subject has MGUS. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM.

Also disclosed herein is a method of determining a subject as having, or being at risk of developing, multiple myeloma (MM), the method comprising: (a) identifying the subject as having a risk factor for developing MM; and (b) detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample. In some instances, this subject has MGUS. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM.

Also disclosed herein is a method of monitoring a subject having, or being at risk of developing, multiple myeloma (MM), the method comprising: (a) identifying the subject as having a risk factor for developing MM; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample; and (c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months. In some instances, this subject has MGUS. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM.

Also disclosed herein is a method of treating a subject having an increased risk of developing multiple myeloma (MM), the method comprising: (a) identifying the subject as having a risk factor for developing MM; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample; and (c) providing an therapeutically effective amount of a treatment to the subject. In some instances, this subject has MGUS. In some instances, the M-protein is IgG. In some instances, the M-protein is IgA. In some instances, the M-protein is IgM. In some instances, the treatment includes one or more of an immunotherapeutic vaccine, one or more bispecific antibodies, CAR-T therapy, lenalidomide, daratumumab, isatuximab, bortezomib, carfilzomib, and dexamethasone.

In some instances, the subject is over 18 years old. In some instances, the subject is between the ages of 40 and 75. In some instances, the subject has a family history of one or more plasma cell dyscrasias. In some instances, the subject is Black. In some instances, the subject has Black ancestry. In some instances, the subject has a family history of a hematologic malignancy. In some instances, the subject has a family history of a hematologic malignancy. In some instances, the subject has a family history of multiple myeloma or a precursor condition to MM. In some instances, the subject has a first-degree relative diagnosed with one or more plasma cell dyscrasias. In some instances, the subject has more than one first-degree relative with one or more plasma cell dyscrasias. In some instances, the one or more plasma cell dyscrasias comprises MM. In some instances, the subject has not been diagnosed with any one or more of monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), MM, or Waldenstrom’s Macroglobulinemia. In some instances, the M-protein is not detected using serum protein electrophoresis (SPEP) and/or immunofixation (IFX).

In some instances, the M-protein is also detected using serum protein electrophoresis (SPEP) and/or immunofixation (IFX).

In some instances, the method further includes quantifying the concentration of one or more of Immunoglobulin G (IgG), Immunoglobulin A (IgA), Immunoglobulin (IgM), and serum free light chain (sFLC) in the sample. In some instances, the serum free light chain is Kappa free light chain or Lambda free light chain.

In some instances, the mass spectrometry is matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry.

In some instances, the sample is a blood sample. In some instances, the sample is a sample of isolated DNA, serum, bone marrow, or plasma.

In some instances, the concentration of the M-protein in the sample is increased compared to concentration of M-protein in a reference sample. In some instances, the reference sample is the first sample obtained from the subject. In another instance, the reference sample is a sample obtained from a similar subject (e.g., age-matched and/or race-matched) who is known to not have or suffer from a hematological malignancy.

In some instances, the reference sample is from a subject having low risk of developing MM. In some instances, the subject having low risk of developing MM is less than 30 years old. In some instances, the subject having low risk of developing MM is not Black or African American. In some instances, the subject having low risk of developing MM is White. In some instances, the subject having low risk of developing MM has no family history of MM. In some instances, the subject having low risk of developing MM is age-matched to the subject.

In some instances, the risk factor comprises that the subject is over 18 years old. In some instances, the risk factor comprises that the subject is between the ages of 40 and 75. In some instances, the risk factor comprises that the subject has a family history of one or more plasma cell dyscrasias. In some instances, the risk factor comprises that the subject has a first-degree relative diagnosed with one or more plasma cell dyscrasias. In some instances, the risk factor comprises that the subject has more than one first-degree relative with one or more plasma cell dyscrasias.

In some instances, the one or more plasma cell dyscrasias comprises MM. In some instances, the risk factor comprises that the subject identifies as Black or of African descent.

In some instances, the subject has not been diagnosed with any one or more of monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), MM, or Waldenstrom’s Macroglobulinemia.

In some instances, detecting the M-protein is also performed using SPEP and/or IFX.

In some instances, the subject is undergoing no treatment for one or more plasma cell dyscrasias. In some instances, the subject is undergoing treatment for one or more plasma cell dyscrasias.

In some instances, the treatment comprises an immunomodulating agent, a proteasome inhibitor, a chemotherapy agent, a histone deacetylase, a monoclonal antibody against CD38, an antibody against SLAMF7, an antibody-drug conjugate, a nuclear export inhibitor, a steroid, a bisphosphonate, a CAR-T cell therapy, multispecific antibodies, and any combination thereof.

In some instances, the methods disclosed herein further include administering to the subject an immunomodulating agent, a proteasome inhibitor, a chemotherapy agent, a histone deacetylase, a monoclonal antibody against CD38, an antibody against SLAMF7, an antibody-drug conjugate, a nuclear export inhibitor, a steroid, a bisphosphonate, a CAR- T cell therapy, multispecific antibodies, and any combination thereof.

In some instances, prevalence of detection of the risk of developing multiple myeloma is increased compared to prevalence of detection of the risk of developing multiple myeloma quantified by mass spectrometry at a concentration greater than 0.2 g/L in the sample. In some instances, the prevalence of detection of the risk of developing multiple myeloma is increased compared to prevalence of detection of the risk of developing multiple myeloma determined using SPEP and/or IFX.

In some instances, the prevalence of detection of the risk of developing multiple myeloma is increased compared to prevalence of detection of the risk of developing multiple myeloma determined using SPEP and/or IFX by at least two-fold, at least threefold, or at least four-fold.

In some instances, the methods further include monitoring progression of developing MM, monoclonal gammopathy of undetermined significance (MGUS), and/or smoldering multiple myeloma (SMM). In some instances, the monitoring progression of developing MM, MGUS, or SMM includes detecting the M-protein in a follow-up sample from the human subject quantified by mass spectrometry at the concentration of between 0.015 g/L and less than 0.2 g/L in the sample every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months. In some instances, the monitoring progression of developing MM, MGUS, or SMM includes detecting the M-protein in a follow-up sample from the human subject quantified by mass spectrometry at the concentration of between 0.2 g/L and less than 30 g/L in the sample every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months.

In another aspect, the disclosure features a method of determining if a subject is likely to develop a B cell Lymphoproliferative Disorder. The method comprises obtaining a sample from the subject and determining that the sample contains a monoclonal paraprotein (M-protein) at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample. In some instances, the determining is by mass spectrometry (e.g., MALDL TOF). In some instances, the sample is a serum sample (e.g., a peripheral serum sample). In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG. In some instances, the subject is a human subject. In some instances, the subject is one who is determined to have a risk of developing a B cell Lymphoproliferative Disorder. In some instances, the method further comprises performing single-cell RNA sequencing and/or B cell receptor (BCR) sequencing on CD 19+ B cells and CD 138+ plasma cells and determining clonal B cell expansions. In some instances, the B cell Lymphoproliferative Disorder is a myeloma, CLL, or a post- germinal center lymphoma. In some cases, the post-germinal center lymphoma comprises activated B cell-like diffuse large B cell lymphoma (ABC-DLBCL), marginal zone lymphoma (MZL) or lymphoplasmacytic lymphoma (LPL). In some instances, these methods further comprise administering a treatment for the B cell Lymphoproliferative Disorder. In some instances, the treatment includes any one or more of a chimeric antigen receptor (CAR) T-cell therapy (such as brexucabtagene autoleucel (Tecartus)), axicabtagene ciloleucel, tisagenlecleucel, lisocabtagene maraleucel, natural killer cell therapy, monoclonal antibodies such as rituximab, polatuzumab vedotin-piiq (Polivy), brentuximab vedotin, blinatumomab, tafasitamab, and/or mosunetuzumab; radiation therapy, surgical procedures (e.g., transplantations or tumor excision), hematopoietic cell transplantation, stem cell transplantation; cyclophosphamide, doxorubicin, vincristine, prednisone, dexamethasone, methotrexate, cytarabine, obinutuzumab, chlorambucil, fludarabine, bendamustine, bortezomib (Velcade), cladribine, fludarabine, lenalidomide, ibrutinib (Imbruvica), acalabrutinib (Calquence), zanubrutinib (Brukinsa), venetoclax (Venclexta), idelalisib (Zydelig), cladribine (2-CdA), pentostatin. In some instances, chemotherapeutic regimens can be used to treat a B cell Lymphoproliferative Disorder. Some examples of chemotherapeutic regimens used for B cell indications include Hyper-CVAD (cyclophosphamide, vincristine, doxorubicin [Adriamycin], and dexamethasone), alternating with methotrexate and cytarabine (ara-C); CODOX-M (cyclophosphamide, vincristine [Oncovin], doxorubicin, and high-dose methotrexate), alternating with IV AC (ifosfamide, etoposide [VP- 16], and cytarabine [ara-C]); or EPOCH (etoposide, prednisone, vincristine [Oncovin], cyclophosphamide, and doxorubicin).

In yet another aspect, the disclosure provides a method of treating a B cell Lymphoproliferative Disorder. The method comprises administering to a subject whose sample (e.g., serum sample (e.g., peripheral serum sample)) contains a monoclonal paraprotein (M-protein) at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample, a therapeutically effective amount of a treatment for the B cell Lymphoproliferative Disorder. In some instances, the M-protein is IgM. In some instances, the M-protein is IgA. In some instances, the M-protein is IgG. In some instances the concentration is determined by MALDI-TOF. In some instances, the method further involves finding that single-cell RNA sequencing and/or B cell receptor (BCR) sequencing on CD 19+ B cells and CD 138+ plasma cells from the subject show clonal B cell expansions. In some instances, the subject is a human. In some instances, the subject is one who is determined to have a risk of developing a B cell Lymphoproliferative Disorder. In some instances, the treatment includes any one or more of a chimeric antigen receptor (CAR) T-cell therapy (such as brexucabtagene autoleucel (Tecartus)), axicabtagene ciloleucel, tisagenlecleucel, lisocabtagene maraleucel, natural killer cell therapy, monoclonal antibodies such as rituximab, polatuzumab vedotin-piiq (Polivy), brentuximab vedotin, blinatumomab, tafasitamab, and/or mosunetuzumab; radiation therapy, surgical procedures (e.g., transplantations or tumor excision), hematopoietic cell transplantation, stem cell transplantation; cyclophosphamide, doxorubicin, vincristine, prednisone, dexamethasone, methotrexate, cytarabine, obinutuzumab, chlorambucil, fludarabine, bendamustine, bortezomib (Velcade), cladribine, fludarabine, lenalidomide, ibrutinib (Imbruvica), acalabrutinib (Calquence), zanubrutinib (Brukinsa), venetoclax (Venclexta), idelalisib (Zydelig), cladribine (2-CdA), pentostatin. In some instances, chemotherapeutic regimens can be used to treat a B cell Lymphoproliferative Disorder. Some examples of chemotherapeutic regimens used for B cell indications include Hyper-CVAD (cyclophosphamide, vincristine, doxorubicin [Adriamycin], and dexamethasone), alternating with methotrexate and cytarabine (ara-C); CODOX-M (cyclophosphamide, vincristine [Oncovin], doxorubicin, and high-dose methotrexate), alternating with IV AC (ifosfamide, etoposide [VP-16], and cytarabine [ara-C]); or EPOCH (etoposide, prednisone, vincristine [Oncovin], cyclophosphamide, and doxorubicin). All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, patent application, or item of information was specifically and individually indicated to be incorporated by reference. To the extent publications, patents, patent applications, and items of information incorporated by reference contradict the disclosure contained in the specification, the specification is intended to supersede and/or take precedence over any such contradictory material.

Where values are described in terms of ranges, it should be understood that the description includes the disclosure of all possible sub-ranges within such ranges, as well as specific numerical values that fall within such ranges irrespective of whether a specific numerical value or specific sub-range is expressly stated.

The term “each,” when used in reference to a collection of items, is intended to identify an individual item in the collection but does not necessarily refer to every item in the collection, unless expressly stated otherwise, or unless the context of the usage clearly indicates otherwise.

Various embodiments of the features of this disclosure are described herein. However, it should be understood that such embodiments are provided merely by way of example, and numerous variations, changes, and substitutions can occur to those skilled in the art without departing from the scope of this disclosure. It should also be understood that various alternatives to the specific embodiments described herein are also within the scope of this disclosure.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows the PROMISE study workflow.

FIG. 2 shows the matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry (MS) screening assay workflow.

FIG. 3 shows the cohorts of individuals used for the PROMISE and MGBB studies.

HM: hematological malignancy. FIG. 4A shows patient sera containing monoclonal immunoglobulins (8-2000 mg/L paraprotein by SPEP value) were serially diluted in normal human serum (IgG = 8.3g/L, IgA = 1.7g/L, IgM = 0.7g/L, total K = 7.7g/L, total X = 3.7g/L) and analyzed by capillary zone electrophoresis (CZE), immunofixation electrophoresis (IFE) and quantitative immunoprecipitation mass spectrometry (QIP-MS). Each dilution was scored according to whether the M-protein was detected (+), equivocally detected (+/-), or absent (-)•

FIG. 4B shows results of a MALDI-TOF MS linearity assay for IgG, IgA, and IgM across a 0.015 to approximately lOOg/L dynamic range using a 10% non-linearity acceptance limit.

FIG. 5 is a scatter plot showing the correlation of monoclonal immunoglobulin concentrations between assays of FIG. 4A.

FIG. 6 is a series of boxplots showing quantification of MS monoclonal immunoglobulins in SPEP/IFX positive and negative samples.

FIGs. 7A-7C show the frequency of monoclonal proteins detected at different concentrations cut points with each dot on the figure representing the highest concentration monoclonal protein detected per participant (FIG. 7A), the relative density isotype distribution of the highest concentration monoclonal protein detected per participant by concentration (FIG. 7B), and results for repeat testing in 58 participants with monoclonal proteins detected at baseline and serial samples available (FIG. 7C). The median time between the baseline screen sample and the latest sample available was 299.5 days (range, 86 to 864 days) for those with MGIP and 235 days (range, 36 to 905 days) for those with MGUS. Rates of persistence were 35% and 93.7% for MGIP and MGUS, respectively. MGIP: monoclonal gammopathy of indeterminate potential; MGUS: monoclonal gammopathy of undetermined significance; MS-MGUS: MGUS by mass spectrometry

FIGs. 8A-8D show reference serum free light chain ranges for a racially diverse screened population (FIGs. 8A-8B) For kappa serum free light chain (sFLC, FIG. 8 A) and lambda sFLC (FIG. 8B), boxplot and violin plots depicting overall range of concentration across self-reported race in individuals with normal kidney function estimated by estimated Glomerular Filtration Rate (eGFR) above 90 mL/min/1.73m2 (Black, n=721, White, n=1042, or Other/Unknown, n=42, see Supplemental Methods). Also shown are comparisons of Kappa (FIG. 8C) and Lambda (FIG. 8D) sFLC values with standard manufacturer ranges (horizontal dashed lines, kappa 3.3 to 19.4 mg/L, lambda 5.71 to 26.3 mg/L), and with this study’s reference ranges (kappa 8.93 to 39.2 mg/L, lambda 7.26 to 30.3 mg/L). Vertical dashed lines separates individuals by kidney function (eGFR<90 or >90 mL/min/1.73m2).

FIGs. 9A-9B show light chain MGUS definition in a racially diverse screened population. FIG. 9A shows distribution of serum free light chain ratio in our study’s population with eGFR available. Each black (i.e., not gray) dot represents a patient if screened positive for light chain MGUS (LC-MGUS) with this study’s reference ranges. Horizontal dashed lines represent manufacturer standard ranges for sFLCr. Plain black horizontal lines represent renal reference (eGFR<90, 0.37 to 3.17) or this studies sFLC range (eGFR>90, 0.713 to 2.02). FIG. 9B shows a comparison of LC-MGUS positivity rate in Black and White individuals from this study (with 95% confidence interval) using standard manufacturer ranges for light chains (left) and using this study’s reference ranges (right).

FIGs. 10A-10B show curves representing the rates of monoclonal gammopathies detected by age (FIG. 10A). The panel on the left represents the rates of MS-MGUS only. The panel on the right represents the rates of MS-MGUS and MGIP. FIG. 10B shows rates of all three sub-types of monoclonal gammopathies in bar graphs by age, gender, and MM risk group from left to right.

FIGs. 11A-11B show MGIP (FIG. 11A) and MGUS (FIG. 11B) detected in our entire cohort by age, gender, race, family history, and MM risk groups.

FIG. 12 shows overall prevalence of MGUS and MGIP across populations by different testing methods. Bar plots represents the percentage of patients positive by SPEP/IFX in the general population over 50 (left) and in a high-risk population (center, results from the PROMISE study). Higher prevalence of MGUS by mass spectrometry (MS-MGUS) displayed on the right in a high-risk population over the age of 50. Two bars on the far right bars represent the prevalence of MGIP across disease risk groups in participants over 50.

FIG. 13 shows prevalence of all three sub-types of monoclonal gammopathies in bar graphs by age, gender and MM risk group from left to right, in participants aged 50 years of age and above.

FIGs. 14A-14D show prevalence of MGIP and MGUS detected by age class in bar graphs for risk group Black (FIG. 14A), risk group FH (FIG. 14B), risk group control (FIG. 14C) and risk group unknown (FIG. 14D), in our entire cohort.

FIGs. 15A-15C show a multi-variable regression model for predictors of (FIG. 15A) all monoclonal gammopathies compared to negative and (FIG. 15B) MGIP (FIG. 15C) MGUS compared to negative, accounting for age, gender, and MM risk group. The label “Non-Black, no family history” refers to Control group in the text. Likewise, “Black” refers to Black, “Non-Black, family history” refers to FH, and Unknown refers to Unknown in the text.

FIGs. 16A-16C show a multi-variable regression model for predictors of (FIG. 16A) all monoclonal gammopathies (FIG. 16B) MGIP and (FIG. 16C) MGUS accounting for race and family history as separate variables in our entire cohort.

FIGs. 17A-17D are Kaplan-Meier curves showing the association of all monoclonal gammopathies detected in our cohort by age groups on overall survival from all-cause mortality: (FIG. 17A) entire cohort, (FIG. 17B) age at screening <50, (FIG. 17C) age at screening 50-64, (FIG. 17D) age at screening 65 and above. CI: Confidence interval, HR: Hazard ratio, MS: Mass spectrometry

FIG. 17E shows a multivariable Cox proportional-hazard model for any monoclonal gammopathy detected in all screened participants on overall survival, adjusted for age, sex, risk group and Charlson co-morbidity Index.

FIGs. 18A-18D show Kaplan-Meier survival curves showing the effect of monoclonal gammopathies on all-cause mortality in patients from the MGBB.

FIGs. 19A-19B show results from Cox proportional-hazards for all-cause mortality among all participants (FIG. 19A) in patients >50 years of age (FIG. 19B) with a monoclonal gammopathy, MGUS versus MGIP versus Negative, adjusted for age, gender, risk classification, and Charlson comorbidity index.

FIGs. 20A-20B show results from Cox proportional-hazards for all-cause mortality among all participants (FIG. 20A) and in patients participants >50 years of age (FIG. 20B) with any monoclonal gammopathy detected adjusted for age, gender, race, family history of HM, and Charlson comorbidity index.

FIGs. 21A-21B show results from Cox proportional-hazards for all-cause mortality among all participants (FIG. 21A) or in patients >50 years of age (FIG. 21B) with a monoclonal gammopathy, MGUS versus MGIP versus Negative, adjusted for age, gender, race, family history of HM, and Charlson comorbidity index.

FIG. 22 shows age-adjusted logistic regression models evaluating associations of monoclonal gammopathies with comorbidities diagnosed at any point in a participant’s lifetime. Includes participants from MGBB cohort only. CAD: coronary artery disease, CI: confidence interval, CLL: chronic lymphocytic leukemia, ISTR: ischemic stroke, Lymphoid HM: Lymphoid hematologic malignancies, Lymphoid Leuk: lymphoid leukemia, MI: myocardial infarction, NHL: Non-Hodgkin lymphoma, OR: odds ratio, RA: rheumatoid arthritis, SLE: systemic lupus erythematosus, T2DM: type 2 diabetes mellitus, UC: ulcerative colitis. *Lymphoid Leuk includes CLL and acute lymphoblastic leukemia **Lymphoid HM includes lymphoid leuk, Hodgkin’s lymphoma, and NHL.

FIGs. 23A-23B show Kaplan-Meier curves showing time to event analysis for participants with positive result at screening who developed any hematologic malignancy at least 6 months after the screen date. FIG. 23A shows the curves for any monoclonal gammopathy detected compared to negative. FIG. 23B shows the curves for MGUS and MGIP compared to negative. All patients with a diagnosis of a hematologic malignancy at any point prior to the 6 months post-screening time point were excluded.

FIGs. 24A-24B show age-adjusted logistic regression models evaluating associations of monoclonal gammopathies with a diagnosis of a hematologic malignancy at least 6 months after screen date. FIG. 24A shows the model for any monoclonal gammopathy detected compared to negative. FIG. 24B shows the model for MGUS and MGIP compared to negative. All patients with a diagnosis of a hematologic malignancy at any point prior to the 6 months post-screening time point were excluded.

FIG. 25 shows graphs display evolution of concentration over time compared to initial concentration at screening (Y axis = 1) in subjects of FIG. 7C with longitudinally maintained monoclonal peaks.

FIGs. 26A-26B shows longitudinal analysis of M-proteins by MS in participants with positive results at baseline screening. Each row represents one participant. Left panels show results from testing by MALDI-TOF MS. Right panels show results from testing by LC-MS. Filled-in dots indicate a persisting M-protein detected by MALDI-TOF MS. Open circles indicate a persisting M-protein detected by LC-MS. Circles having a cross indicate undetectable B-protein on repeat testing.

FIG. 27 shows results from clinical testing of cases with increasing M-protein concentration.

FIG. 28A shows proportion of B cell expansion in six individuals. HD: healthy donors.

FIG. 28B shows a plot of distinct modes (shown by squares and circles) indicating possible phenotypic expansion.

FIG. 28C shows mean expression of lymphocytic-related genes in a UBCL (undetermined B cell lymphoma) sample and a CLL (chronic lymphocytic leukemia) sample.

FIG. 28D shows a plot of three regions of observed copy number variation (CNV) in one clone with UBCL. Rectangles indicate areas of CNV changes

DETAILED DESCRIPTION

This disclosure describes a novel method and biomarkers to identify progression and clonal evolution of plasma cell dyscrasias, include from MGIP to multiple myeloma (MM). More specifically, the present disclosure provides materials and methods for the screening, diagnosis, prognosis, staging, and monitoring of plasma cell dyscrasias and other HMs based on the presence of the biomarkers in a blood biopsy. This disclosure also provides methods for monitoring the progression of a plasma cell dyscrasia, determining the efficacy of a therapeutic agent, and/or determining a targeted therapy related to a plasma cell dyscrasia. This disclosure also provides methods for the detection of monoclonal gammopathies as biomarkers of immune dysregulation, autoimmune diseases, cardiovascular diseases, aging, and decreased survival. This disclosure also provides methods for treating a human subject having, or at risk of developing, a plasma cell dyscrasia based on the presence of the biomarkers in a blood biopsy.

The data in the Examples section herein demonstrate methods having better characterization of early monoclonal gammopathies and further understanding their clinical impact on progression to overt disease or other HMs and any other potential phenotypic implications.

The data in the Examples section herein demonstrate methods for screening high- risk individuals in the clinic for early disease detection and clinical follow-up/intervention when needed with the purpose of preventing progression to overt clinical myeloma, which remains not curable to date.

The data in the Examples section herein demonstrate methods useful for clinical monitoring for measurable residual disease (MRD) in patients being treated for their precursor condition to more easily and accurately evaluate response to therapy at various time points. This will help optimize treatment regimens in the precursor setting and further individualize therapeutic approaches.

Monoclonal Gammopathy of Indeterminate Potential (MGIP), Monoclonal Gammopathy of Undetermined Significance (MGUS) and Multiple Myeloma

Disclosed herein are methods for diagnosing and treating subjects with monoclonal gammopathy of indeterminate potential (MGIP), monoclonal gammopathy of undetermined significance (MGUS) and multiple myeloma (MM). MGUS is a precursor of MM. As used herein, MGIP is defined as having M-protein detection below the current clinical level of detection of IFX (i.e., between 0.015 g/L and less than 0.2 g/L in a sample), which is differentiated from other precursors such as MS-MGUS (i.e., above this threshold). In some instances, MGIP is characterized by blood M protein between 0.015 g/L and less than 0.2 g/L g/L. In some instances, MGIP presents with IgM as the most common isotype.

In some instances, MGIP was associated with increasing age. In some instances, a subject having MGIP is above 40 years old (e.g., about 40, about 45, about 50, about 55, about 60, about 65, about 70 years old or older).

In some instances, MGUS was associated with increasing age. In some instances, a subject having MGUS is above 40 years old (e.g., about 40, about 45, about 50, about 55, about 60, about 65, about 70 years old or older).

MGIP and MGUS can be readily detected in various subjects (e.g., human subjects). In some instances, the subject is at high risk for MGIP. High risk subjects include, but are not limited to, individuals who are: (1) Black or of African descent, and/or (2) non-Black with a family history of hematological malignancy (HM) or MM precursor condition.

Multiple myeloma (MM; also known as plasma cell myeloma, myelomatosis, or Kahler's disease) is a cancer of plasma cells, a type of white blood cell normally responsible for producing antibodies. In MM, collections of abnormal plasma cells accumulate in the bone marrow, where they interfere with the production of normal blood cells.

Recent studies have shown that MM is consistently preceded by a precursor state such as monoclonal gammopathy of undetermined significance (MGUS) or smoldering multiple myeloma (SMM) (Landgren et al., 2009 Blood 113:5412-5417; Weiss et al., 2009 Blood 113:5418-5422). MGUS is characterized by blood M protein <30 g/L (i.e., above 0.2 g/L and below 30 g/L), bone marrow plasma cells <10%, and no myeloma-related organ or tissue impairment. MGUS is observed for progression, but is typically not treated. SMM is characterized by blood M protein >30 g/L, bone marrow plasma cells >10%, and myeloma-related organ or tissue impairment. SMM is typically observed and not treated. The presence of serum M-protein >2 g/dL together with involved to uninvolved sFLC ratio >20 and bone marrow plasma cell infiltration >20% (see, e.g., Mateos et al., Blood Cancer Journal, 10(102): (2020); Rajkumar SV, et al., Blood 125:3069-3075 (2015), which are incorporated by reference herein in their entirety) are independent risk factors of progression that can be used to identify subjects with SMM at high risk of progression. High risk for progression can also be assessed separately or in combination by the Kyle et al. model, the PETHEMA model, or the “20-2-20” model.

Some subjects progress from MGUS to overt MM (progressors) with a rate of progression of 1% per year, while others remain indolent with minimal progression (non- progressors) over the same time period. The current prognostic factors used to assess progression are based on tumor burden markers including the level of monoclonal spike, free light chains, and/or percent of plasma cells in the bone marrow.

As used herein, unless otherwise indicated, MM refers to any stage of MM except for MGIP, MGUS, or SMM. Thus, stages of MM include MM defined by the presence of myeloma-defining events, as defined by the International Myeloma Working Group (such as bone marrow infiltration >= 60%, FLC ratio >= 100 and more than 1 focal lesion on MRI) (see, e.g., Rajkumar SV, American Society of Clinical Oncology Educational Book 2016 :36, e418-e423, which is incorporated by reference herein in its entirety), and plasma cell leukemia (PCL; the most aggressive plasma cell disorder), but do not include MGIP, MGUS, and SMM. Thus, in some instances, a subject is considered to have progressed to MM when said subject has the presence of one or more myeloma-defining event or plasma cell leukemia. MM is characterized by the presence of plasma cells >10% in bone marrow or in any quantity in other tissues (plasmacytoma) and at least one myeloma-defining event (see, e.g., Rajkumar SV, American Society of Clinical Oncology Educational Book 2016 :36, e418-e423, which is incorporated by reference herein in its entirety). Thus, in some instances, a subject is considered to have progressed to MM when said subject has hypercalcemia (e.g., a serum calcium level greater than 0.25 mmol/L above the upper limit of normal or a level that is greater than 2.75 mmol/L), renal or kidney problems (e.g., a creatinine greater than 173 mmol/L), anemia (e.g., a low hemoglobin level, e.g., 2 g/dL below the lower limit of normal or a hemoglobin level that is less than 10 g/dL), and/or bone pain or lesions (e.g., lytic lesions, osteoporosis, or compression fraction of the spine). Other myeloma-defining events indicating a subject has progressed to MM include: more than 60% of the cells in the bone marrow are plasma cells, symptomatic hyperviscosity of the blood, amyloidosis, repeated serious bacterial infections (i.e., more than 2 episodes in a 12 month time-frame), bone lesions seen on MRI or PET-CT imaging, and an involved-to-uninvolved free light chain ratio of greater than 100 (based on serum testing), with an absolute value greater than 100 mg/L or lOmg/dL. Methods of staging MM are known in the art (see, e.g., the International Staging System for Multiple Myeloma (Greipp et al., Journal of Clinical Oncology, 2005, 23(15):3412-3420, which is incorporated by reference herein in its entirety, and any updates thereto)).

In some instances, low-level monoclonal gammopathy detected through MALDI- TOF (i.e., those having MGIP levels as disclosed herein; e.g., between 0.015 g/L and up to 0.2 g/L) on peripheral blood serum may indicate that a subject has a B cell lymphoproliferative disorder. B cell lymphoproliferative disorders include but not limited to myeloma, CLL, and post-germinal center lymphomas, like Activated B Cell-like Diffuse Large B cell Lymphoma (ABC-DLBCL), marginal zone lymphoma (MZL), and lymphoplasmacytic lymphoma (LPL).

MGIP, MGUS, SMM, or MM can be treated. Treatment for MGIP or MM includes, for example, the following therapeutic agents: an immunomodulating agent (e.g., Empliciti™ [elotuzumab], Thalomid® [thalidomide], Pomalyst™ [pomalidomide], or Revlimid® [lenalidomide]), a proteasome inhibitor (e.g., Velcade® [bortezomib], Ninlaro™ [ixazomib] or Kyprolis™ [carfilzomib]), a chemotherapy agent (e.g., Doxil® [doxorubicin], cyclophosphamide, etoposide, liposomal doxorubicin, melphalan, melphalan flufenamide, bendamustine), a histone deacetylase (e.g., Farydak™ [panobinostat]), a monoclonal antibody against CD38 (e.g., Darzalex™ [daratumumab], Sarclisa™ [isatuximab]), an antibody against SLAMF7 (e.g., Empliciti™ [elotuzumab]), an antibody-drug conjugate (e.g., Blenrep™ [belantamab mafodotin-blmf]), a nuclear export inhibitor (e.g., Xpovio [selinexor]), a steroid (e.g., a corticosteroid, e.g., dexamethasone or prednisone), a bisphosphonate (for individuals with osteolytic lesions, osteoporosis, or osteopenia), a CAR-T cell therapy such as CAR-T cells for BCMA (e.g., Abecma® [idecabtagene vicleucel]) or GPRC5D), multispecific antibodies (e.g., targeting BCMA), other such as vaccines under development and any combination thereof.

Therapeutic agents for treatment of MGIP, MGUS, SMM, or MM include any therapeutic agent approved (e.g., by the US Food and Drug Administration or the European Medicines Agency), or any combination thereof, for the treatment of MGIP or MM. In some instances, a treatment used in the methods described herein comprises a therapeutically effective amount of one or more (e.g., 1, 2, 3, 4) therapeutic agents used to treat MGIP or MM. In addition, any therapeutic agent may be used alone or in combination with other therapies. In some instances, the treatment comprises bortezomib, lenalidomide, and dexamethasone. In some instances, the treatment comprises bortezomib, lenalidomide, dexamethasone, and daratumumab. In some instances, the treatment comprises autologous stem cell transplantation (ASCT). In some instances, the treatment comprises CAR-T cells for BCMA. In some instances, the treatment comprises an immunotherapy. In some instances, the treatment comprises an immunotherapy and a proteasome inhibitor, optionally also CAR-T cells for BCMA. In some instances, the treatment comprises an immunotherapy and an immunomodulating agent. In some instances, the treatment comprises an immunotherapy, an immunomodulating agent, and a proteasome inhibitor, optionally also CAR-T cells for BCMA. In some instances, the treatment comprises an immunotherapy and a steroid. In some instances, the treatment comprises an immunotherapy, an immunomodulating agent, and a steroid, optionally also CAR-T cells for BCMA. In some instances, the treatment comprises an immunotherapy, an immunomodulating agent, a steroid, and a proteasome inhibitor. In some instances, the treatment comprises an immunotherapy, an immunomodulating agent, a steroid, a proteasome inhibitor, and CAR-T cells for BCMA. For instance, a subject (e.g., human) described herein (e.g., a subject having MGIP or MM) may be administered an immunotherapy (e.g., an anti-SLAMF7 antibody, e.g., elotuzumab), an immunomodulatory imide drug (e.g., lenalidomide), and a steroid (e.g., dexamethasone). In some instances, a subject (e.g., human) described herein (e.g., a subject having MGIP or MM) may be administered elotuzumab, lenalidomide, and dexamethasone.

M-Protein Bio marker

The methods disclosed herein identify the concentration of M-protein, a biomarker, in a sample of the subject. A biomarker described herein are detectable using a blood biopsy. A biological marker, or “biomarker,” as used herein refers to a measurable genetic abnormality that is an indicator of some biological state or condition. Provided herein are biomarkers useful for screening, diagnosis, prognosis, staging, monitoring, and/or personalization or therapy related to plasma cell dyscrasias and other HMs. Provided herein are biomarkers useful for the detection of aging, immune dysregulation, decreased overall survival, and clinical comorbidities such as cardiovascular disease, autoimmune diseases, and HMs. Biomarkers useful for the diagnosis, prognosis, staging, monitoring, and/or personalization or therapy related to MM are also referred to as MM biomarkers. Biomarkers are detectable in a blood biopsy from a subject having, or at risk of developing, a plasma cell dyscrasia, but are not detectable in a healthy (e.g., not having a plasma cell dyscrasia) subject. In some instances — usually in the instance of MM, M-protein is found in the blood and/or urine.

MM results from the malignant proliferation of plasma cells which produces in most but not all the cases a clonal immunoglobulin, the so called M-protein (also called interchangeably any one of monoclonal protein, monoclonal paraprotein, M component, M spike, spike protein, or paraprotein throughout). MM is characterized by skeletal destruction, hypocalcaemia, bone marrow and renal failure. In some instances, M-protein is an antibody or fragment thereof from any one of IgA, IgD, IgE, IgG, and/or IgM. M- proteins may consist of both heavy and light chains or of only one type of chain.

Monoclonal gammopathies gather a complex array of ailments that have in common clonal proliferations of plasma cells that can usually be detected by finding their products in serum or urine. The products are monoclonal immunoglobulin proteins (M- proteins) that may consist of intact immunoglobulin molecules and/or fragments such as free light chains (FLC). The detection, characterization, and measurement of M-proteins help in initial diagnosis of the disorders, stratification of risk progression, and monitoring response to therapy. As is evident herein, cases of MM begin with very little M-protein that may be present in serum prior to diagnosis of MM. As is evident herein, the use of M-proteins as a biomarker may have implications for a variety of clinical applications.

Characterization of the M-protein by immunofixation, immunosubtraction (ISUB), or an immunochemical method (isotype class, free light chain, or heavy /light chain) is needed for prognosis and to follow patients before and after therapy. The isotype can affect the likelihood of progressing. For instance, individuals with non-IgG M-proteins have a greater likelihood of developing MM than those with IgG M-proteins. Beyond identification of isotype and electrophoretic position, key aspects of prognosis and follow-up of monoclonal gammopathies rely upon obtaining a reproducible, accurate quantification of M-proteins. As disclosed herein, the methods provide early detection, particularly for high risk populations, of M-protein in the setting of the newly-described MGIP.

Method of Detecting M-Protein

Disclosed herein are methods of detecting M-protein in a biological sample. In some instances, the methods include using mass spectroscopy. Mass spectrometry is an analytical technique in which chemical compounds are ionized into charged molecules and ratio of their mass to charge (m/z) is measured. The development of matrix assisted laser desorption ionization (MALDI) increased the applicability of MS to large biological molecules such as proteins. In MALDI, peptides are converted into ions by either addition or loss of one or more than one protons. MALDI is based on “soft ionization” methods where ion formation does not lead to a significant loss of sample integrity.

Generally, a sample for analysis by MALDI MS is prepared by mixing or coating with solution of an energy-absorbent, organic compound called matrix. When the matrix crystallizes on drying, the sample entrapped within the matrix also co-crystallizes. The sample within the matrix is ionized in an automated mode with a laser beam. Desorption and ionization with the laser beam generates singly protonated ions from analytes in the sample. The protonated ions are then accelerated at a fixed potential, where these separate from each other on the basis of their mass-to-charge ratio (m/z). The charged analytes are then detected and measured using different types of mass analyzers like quadrupole mass analyzers, ion trap analyzers, time of flight (TOF) analyzers etc. For microbiological applications mainly TOF mass analyzers are used. During MALDI-TOF analysis, the m/z ratio of an ion is measured by determining the time required for it to travel the length of the flight tube. A few TOF analyzers incorporate an ion mirror at the rear end of the flight tube, which serves to reflect back ions through the flight tube to a detector. Thus, the ion mirror not only increases the length of the flight tube, it also corrects small differences in energy among ions. Based on the TOF information, a characteristic spectrum called peptide mass fingerprint (PMF) is generated for analytes in the sample. Identification of microbes by MALDI-TOF MS is done by either comparing the PMF of unknown organism with the PMFs contained in the database, or by matching the masses of biomarkers of unknown organism with the proteome database. Additional disclosure on MALDI-TOF MS can be found in Singhal et al., Front Microbiol. 2015 Aug 5;6:791, which is incorporated by reference in its entirety.

The methods provided herein include detection of M-protein using both MALDI- TOF and a turbidimetric and nephelometric automated analyzer. Briefly, for example, in some instances, a venous blood sample can be drawn from all qualifying individuals, and the serum portion of whole blood can be collected from all samples after allowing the blood to clot. Serum from participants can be re-aliquoted into adequate cryovials and can be used as input into the Exent® MALDI-TOF MS technology. Serum from the same blood draw can be re-aliquoted into similar cryovials to be tested using the Optilite® technology. Data output from both technologies can be analyzed using the Binding Site Group’s proprietary software. Results can include immunoglobulins quantification for IgG, IgA, and IgM, quantification of serum free light chain lambda and serum free light chain kappa, qualitative detection of the presence of monoclonal protein, identification of monoclonal protein isotype, and quantification of monoclonal protein concentration, if detected. Positive results as defined above can be sub-categorized into clinical categories such as MGIP, MGUS and MM. MGIP and MGUS patients can have the opportunity to monitor their disease by re-screening and use results for clinical follow-up with specialized hematologists/oncologists. This allows for closer clinical follow-up of patients with precursor conditions and offer an opportunity for early intervention to prevent progression to malignancy as seen fit by caregivers.

Serial testing will allow for tracking M-protein levels, detecting the appearance of new clones or disappearance of baseline clones, and quantifying tumor burden based on monoclonal protein quantification.

In some instances, the sample can be a fluid sample, such as a blood sample, urine sample, or saliva sample. The sample can be a skin sample, a colon sample, a cheek swab, a histology sample, a histopathology sample, a plasma or serum sample, a tumor sample, living cells, cultured cells, a clinical sample such as, for example, whole blood or blood-derived products, blood cells, or cultured tissues or cells, including cell suspensions. Cell-free biological samples can include extracellular polynucleotides. Extracellular polynucleotides can be isolated from a bodily sample, e.g., blood, plasma, serum, urine, saliva, mucosal excretions, sputum, stool, and tears.

Methods of Identifying Subjects for Treatment, Methods of Monitoring Progression of Disease, and Methods of Treatment

The disclosure features methods of treatment described herein for the prevention and/or treatment of a MGIP, MGUS and/or MM. The terms "treat" or "treating," as used herein, refers to alleviating, inhibiting, or ameliorating the disease from which the subject (e.g., human) or other species (e.g., pets; farm animals; domestic animals) is suffering. In some instances, the subject is an animal. In some embodiments, the subject is a mammal such as a non-primate (e.g., cow, pig, horse, cat, dog, rat, etc.) or a primate (e.g., monkey or human). In some instances, the subject is a domesticated animal (e.g., a dog or cat). In some instances, the subject is a human. In certain embodiments, such terms refer to a non-human animal (e.g., a non-human animal such as a pig, horse, cow, cat or dog). In some embodiments, such terms refer to a pet or farm animal. In some embodiments, such terms refer to a human.

In instances in which the subject is a human, the subject is a member of a high- risk group (i.e., at higher risk of developing MM compared to a reference group). In some instances, the subject is over 18 years old. In some instances, the subject is above age 40. In some instances, the subject has a family history of one or more plasma cell dyscrasias (e.g., MM) or other HM. In some instances, the subject has a first-degree relative diagnosed with one or more plasma cell dyscrasias or other HMs. In some instances, the subject has more than one first-degree relative with one or more plasma cell dyscrasias or other HMs. In some instances, the one or more plasma cell dyscrasias comprises MM. In some instances, the subject identifies as Black or of African descent. In some instances, the subject has not been diagnosed with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), MM, or Waldenstrom’s Macroglobulinemia.

A subject can be compared to a reference sample from a reference subject. In some instances, the reference sample is from a subject having low risk of developing MM. In some instances, the subject having low risk of developing MM is less than 30 years old. In some instances, the subject having low risk of developing MM is not Black or African American. In some instances, the subject having low risk of developing MM is White. In some instances, the subject having low risk of developing MM has no family history of MM. In some instances, the subject having low risk of developing MM is age- matched to the test subject at higher risk.

Immune biomarkers (e.g., M-protein) levels can be used to identify subjects (e.g., humans) with MGIP or MGUS that would benefit from early treatment (i.e., before progression to MM). Patients with MM can also present with an increased immune reactivity and, thus, are also more likely to respond to treatment with, e.g., immunotherapy. Thus, prior to undergoing treatment for MGIP or MGUS or MM, subjects (e.g., human) with MGIP having M-protein levels that are detectable between 0.015 g/L and less than 0.2 g/L in a tested sample. In some instances, subjects having MGIP are predicted to have significantly longer progression-free survival upon treatment (e.g., with immunotherapy) and are, thus, predicted to benefit from treatment (e.g., treatment for MM subjects or early treatment for MGIP subjects, i.e., treatment before progression from MGIP to SMM or MGUS to MM). Accordingly, provided herein is a method for identifying a human subject having MGIP or MGUS or MM that would benefit from treatment, the method comprising determining that a sample (e.g., mononuclear cells obtained from a blood sample, CD 138- mononuclear cells obtained from a bone marrow sample or a blood sample, or a bone marrow tissue section) obtained from the human subject has a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample, wherein the sample is obtained prior to treatment. In some instances, the method comprises obtaining the sample from the human subject. In some instances, the human subject has not or is not currently undergoing treatment for MGIP, SMM, MGUS, or MM at the time the sample is obtained from the human subject.

Detection of M-protein (between 0.015 g/L and less than 0.2 g/L) as described herein can be used to monitor the response to treatment (e.g., immunotherapy) in a subject (e.g., human) with MGIP or MM and determine which subjects with MGIP or MM should be treated with a different, e.g., more intensive regimen. Detection of M- protein (at between 0.015 g/L and less than 0.2 g/L) as described herein can be used to monitor the response to treatment (e.g., immunotherapy) in a subject (e.g., human) with MGIP or MM and determine which subjects with MGIP or MM should be treated with the same treatment (e.g., immunotherapy).

Detection of M-protein (between 0.015 g/L and less than 0.2 g/L) as described herein can be used to determine the response to treatment (e.g., immunotherapy) in a subject (e.g., human) with MGIP or MM who has undergone or is undergoing (e.g., received 1, 2, 3, or more doses of a treatment for SMM, MGUS, or MM, e.g., immunotherapy) treatment for MGIP or MM and determine which subjects with MGIP or MM are predicted to have prolonged or shortened biochemical progression-free survival. Biochemical progression free survival includes both clinical and biochemical progression. In some instances, biochemical progression free survival comprises (i) a significant increase in tumor burden (e.g., as determined by M-spike levels or free light chain (FLC) ratio) during treatment (ii) in the absence of a myeloma-defining event (e.g., as described above).

Immune biomarkers described herein can be used identify subjects (e.g., humans) with MGIP or MM who have undergone (e.g., received 1, 2, 3, or more doses) treatment for MGIP or MM (e.g., immunotherapy) that would benefit from termination or modification of treatment.

Subjects who have low-level monoclonal gammopathy as detected through MALDI-TOF (i.e., MGIP) on samples (e.g., peripheral blood serum) are likely to have or develop a B cell Lymphoproliferative Disorder, including but not limited to myeloma, CLL and post-germinal center lymphomas, like ABC-DLBCL, MZL, and LPL. In some instances the subject has MGIP. In some instances, the subject has an M-protein concentration of between 0.015 g/L and 0.2 g/L. In some instances, the subject is determined to be one who is at risk of developing a B cell Lymphoproliferative Disorder. In some instances, the subject is a human. In some instances, the M-protein concentration is determined by mass spectrometry (e.g., MALDI-TOF). Such subjects can be treated with a therapeutically effective amount of a suitable treatment for the B cell Lymphoproliferative Disorder. In some instances, the treatment includes one or more of a chimeric antigen receptor (CAR) T-cell therapy (such as brexucabtagene autoleucel (Tecartus)), axicabtagene ciloleucel, tisagenlecleucel, lisocabtagene maraleucel, natural killer cell therapy, monoclonal antibodies such as rituximab, polatuzumab vedotin-piiq (Polivy), brentuximab vedotin, blinatumomab, tafasitamab, and/or mosunetuzumab; radiation therapy, surgical procedures (e.g., transplantations or tumor excision), hematopoietic cell transplantation, stem cell transplantation; cyclophosphamide, doxorubicin, vincristine, prednisone, dexamethasone, methotrexate, cytarabine, obinutuzumab, chlorambucil, fludarabine, bendamustine, bortezomib (Velcade), cladribine, fludarabine, lenalidomide, ibrutinib (Imbruvica), acalabrutinib (Calquence), zanubrutinib (Brukinsa), venetoclax (Venclexta), idelalisib (Zydelig), cladribine (2-CdA), pentostatin. In some instances, chemotherapeutic regimens can be used to treat a B cell Lymphoproliferative Disorder. Some examples of chemotherapeutic regimens used for B cell indications include Hyper-CVAD (cyclophosphamide, vincristine, doxorubicin [Adriamycin], and dexamethasone), alternating with methotrexate and cytarabine (ara-C); CODOX-M (cyclophosphamide, vincristine [Oncovin], doxorubicin, and high-dose methotrexate), alternating with IV AC (ifosfamide, etoposide [VP-16], and cytarabine [ara-C]); or EPOCH (etoposide, prednisone, vincristine [Oncovin], cyclophosphamide, and doxorubicin).

The disclosure will be further described in the following examples, which do not limit the scope of the disclosure described in the claims.

EXAMPLES

Example 1.

Methods

Study participants

PROMISE Study

In February 2019, the Predicting Progression of Developing Myeloma in a High- Risk Screened Population (PROMISE) study (NCT03689595) was initiated as the first nationwide screening study for individuals at high risk of MM to identify population(s) that may benefit the most from screening and early intervention of MM precursor conditions. The PROMISE study invited healthy individuals who are at high risk for MM to enroll and screen for monoclonal gammopathy. Eligible participants include individuals who are: (1) Black or of African descent or (2) non-Black but with a family history of hematological malignancy (HM) or HM precursor condition. These high-risk individuals were eligible to enroll at age 40 and above, although those with more than one first-degree relative with HM or HM precursor condition were eligible at age 18 and above. Individuals who had a prior diagnosis of a plasma cell disorder, including MGUS, SMM, MM, and Waldenstrom’s Macroglobulinemia, or other malignancies requiring active therapy were excluded. Eligible individuals were invited to enroll either online or at participating study sites. Informed consent was available online or in-person, and qualified study staff was available to review the consent process and answer any questions.

All PROMISE participants received a screening kit at their home address. Blood was drawn at local phlebotomy sites and underwent SPEP, IFX, and sFLCs testing in a CLIA environment and results were returned to participants. Individuals who screened positive for an M-protein by conventional methods were referred to a local hematologist or oncologist and invited to provide an additional informed consent for the submission of samples for research tissue banking at regular intervals. A study workflow is provided as FIG. 1. 500pL of the remaining serum collected at baseline and follow-up intervals were reserved for screening by MS as described herein.

Mass General Brigham Biobank

A second cohort — individuals from the Mass General Brigham Biobank (MGBB) who were identified as at high risk for MGUS and MM with serum available for testing — was evaluated. Briefly, the second cohort consists primarily of volunteers who have consented to the large research program designed to better understand how individuals' health is affected by their genes, lifestyle, and environment. Participants provided informed consent and had the choice of contributing health-related information via a short survey and/or blood samples. From this participant pool, individuals aged 18 years and older who met high-risk criteria were selected. Family history of HM was ascertained based on health survey information. A group of low-risk individuals (non-Black, no family history of HM) to serve as negative controls in the setting of testing a new screening assay (henceforth, control group) were also identified. Finally, a fourth group of individuals of mostly White individuals with an unknown family history who had exome sequencing data available was also tested (henceforth, unknown risk group). All participants with a diagnosis of MM prior to the serum draw date were excluded.

This study was conducted upon approval of protocols 18-370 and 2021P001703 by the Institutional Review Boards of Dana-Farber Cancer Institute and the Mass General Brigham, respectively.

MALDI-TOF mass spectrometry

All serum samples (500pL) were tested using the EXENT® matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry for the detection and quantification of M-proteins (Binding Site Group Ltd.) and Optilite® free light assay for the quantification of IgG, IgA, IgM, and serum free light chains (sFLC). EXENT® software was used for the quantitative analysis of the M-proteins detected. An overview is shown in FIG. 2.

M-protein studies with MALDI-TOF MS were carried out using the automated EXENT® system (The Binding Site Group Ltd., Birmingham, UK) using sheep polyclonal antibodies (anti-human IgG, IgA, IgM, total K and total X light chains) separately immobilized on to paramagnetic microparticles. Immunoglobulin purification was performed on the system’s automated liquid handler. Briefly, participant samples were equally divided into 5 aliquots, each individually incubated with isotype-specific beads. The beads were then washed using magnetic precipitation and buffer exchanges and treated with 20mM Tris[2-carboxyethyl] phosphine (TCEP) in 5% (v/v) ac/etic acid to reduce patient immunoglobulin heavy and light chain disulfide bonds. Eluates were subsequently mixed with a-cyano-4-hydroxy cinnamic acid (HCCA) matrix, spotted onto MALDI plates, and allowed to co-crystallize on the plate surface. Sample spots were analyzed on a MALDI-TOF Microflex LT smart system (Bruker, CA, US). LC mass spectra were acquired in positive ion mode covering the m/z range of 4,990 to 32,100, which includes the singly charged (+1, m/z 23,330 to 24,650) and doubly charged (+2, m/z 11,168 to 12,401) ions. LC m/z distributions from each reaction (IgG, IgA, IgM, total K and total A) were simultaneously interrogated using the EXENT® software. Monoclonal peak picking was achieved following a proprietary algorithm trained against clinical data developed by Indigo Bioautomation. Briefly, after finding the local y-maxima a spline model was used to assess the goodness of fit. Spline model is necessary for MALDI-TOF data obtained using HCCA matrix to accommodate the matrix adduct peak present at a regularly defined distance from the monoclonal peak. Polyclonal peak modeling was achieved using a Gaussian fit. The area under the curve for the +2 charge state was calculated using the trapezoidal rule to account for the area above the baseline. Quantification of total immunoglobulin levels was determined by turbidimetry on an Optilite® instrument (The Binding Site Group Ltd.).

The analytical performance of the EXENT® system has previously been verified for linearity, precision, reference interval, interference, and stability. EXENT®’ s limit of quantification (LoQ) was 15 mg/L for all specificities, with a limit of detection (LoD) of <5 mg/L dependent on the polyclonal background. Published Hevylite® (The Binding Site Group Ltd.) reference intervals have been verified for each specificity. The assay demonstrated acceptable 20-day total precision values for polyclonal samples (<7%) and for two monoclonal samples (~1 g/L and 10 g/L; <15% and <10%, respectively), with between laboratory precision <8% for all samples. The assay was linear for all three major isotypes (IgG, IgA, or IgM) across a 0.015 to 100 g/L dynamic range.

Confirmatory testing by liquid chromatography-mass spectrometry (LC-MS) was performed on samples with M-protein concentration between 0.015 g/L and less than 0.2 g/L to confirm the results obtained at low concentrations by MALDI-TOF MS and to avoid false-positivity. The LC gradient was 25 minutes long at a flow rate of 25 pL/min using mobile phase A consisting of water + 0.1% formic acid and mobile phase B consisting of 90% acetonitrile and 10% n-propanol + 0.1% formic acid. The LC column was a HALO column: 1,000 A Diphenyl, 2.7 um particle size, 1.0 x 50 mm. The mass spectrometer was a SCIEX 6600 Triple-TOF Q-TOF mass spectrometer. The acquisition method acquired spectra over an m/z range of 600 to 2,500. Raw data collected by LC-MS were analyzed using PeakView® version 2.2.0.11391, by AB SCIEX. The molecular masses and peak areas of monoclonal LCs observed by LC-MS were determined using the multiply charged deconvolution algorithm within Bio Tool Kit version 2.2.0.11391 run as a plug-in through PeakView®.

Examination was limited to M-proteins that were above the lower limit of the quantification (0.015 g/L) of the assay. Additional filtering relied on the validated machine- learning-based algorithm that was trained using a panel of normal and samples from overt MM patients (Sakrikar D, Marrot N, North S, et al. Multi-Site Verification of the Automated EXENT® MALDI-TOF-MS System and Immunoglobulin Isotypes Assay for the Identification and Quantification of Monoclonal Immunoglobulins. In; 2021. Accessed October 7, 2021. abstractsonline.com/pp8/#!/9313/presentation/23). HC-LC pairing was defined as the detection of an HC and LC monoclonal protein on mass spectra within +/-3 m/z. Among the HC M-proteins detected, some were found to be paired with an LC, while others were impaired. Generally, HC-LC paired monoclonal proteins detected had a higher concentration than HC-only monoclonal proteins (P<0.001).

Extraction and analysis of clinical data from the MGBB

This source data is available for approved researchers through the MGBB. Participant-level MGBB data is available at personalizedmedicine.partners.org/Biobank/Default.aspx, and access was conditional upon IRB approval (2021P001703). Clinical diagnoses were extracted and identified utilizing pheCodes (PheCode Map version 1.2, phewascatalog.org/phecodes), hierarchical groupings of International Classification of Diseases, Ninth and Tenth Versions (ICD- 9/ICD-10) codes. PheCodes were originally developed for phenome-wide association studies of large electronic health record (EHR)-linked databases and shown to more accurately align with diseases mentioned in clinical practice, compared to ICD codes alone (PMID Nos.: 24270849, 31553307, 28686612). Vital status, recorded as alive or deceased, and the last date of encounter filed in the EHR for all screened participants were also extracted. “Encounter” in the EHR was generally defined as a record of contact (or healthcare-related activity) for a patient, such as an outpatient clinic visit, inpatient or ED admission, virtual interaction (e.g., telephone call, telemedicine visit, direct electronic messages), or new clinical lab orders.

Statistical Analyses Quantitative bio-clinical variables were described with median, interquartile range (IQR), and median absolute deviation (MAD), or with mean and standard deviation. Significance of average difference between groups was assessed with Kruskal-Wallis method for multiple group testing, and/or Wilcoxon test for 2 groups. Multiple group testing was followed by Dunn’s post hoc tests when the result was significant. Qualitative variables were described using the frequency of their respective modalities. Significance of difference between frequencies between groups was assessed with Pearson’s test (or Fisher’s exact test if appropriate) and followed by pairwise Fisher’s exact test when significant. For survival analysis, time-to-event was calculated from the date of serum draw to the event date, i.e., death from any cause for overall survival, date of initial clinical diagnosis for diseases, or to the date of the most recent encounter for patients reported as alive as extracted from the MGBB. Hazard ratios (HR) between groups were calculated using univariable and multivariable Cox models (with adjusted covariates listed when appropriate). Concentration of proteins is log-normal and was log-transformed in linear models. HR ratios were reported with their 95% confidence intervals (CI). Survival curves were calculated using the Kaplan-Meier method and groups were compared using a Logrank test. P values were corrected for multiple testing with the Benjamini -Hochberg method. Adjusted p values under 0.05 were considered significant. All calculations were done using R software (version 4.4.1).

Results

Analytic Cohort

Serum from 7,622 individuals was analyzed. Of the 7,622 individuals, 6,305 (2,211 from PROMISE study cohort and 4,094 from MGBB cohort) had self-reported high-risk features for MM: (1) 2,439 self-identified as Blacks (risk group Black) and (2) 3,866 reported a family history (FH) of hematologic malignancies (risk group FH). Serum samples were also analyzed for individuals in the comparison control groups gathered from the MGBB, consisting of (3) 631 in the control group and (4) 686 with missing family history data in the unknown risk group (FIG. 3). The median age of participants included in the study at the time of screening was 56 years (range, 18 to 95). 5,013 (66%) of participants were females. Tables 1 and 2 below show the demographics distribution of participants by study cohort and risk group, respectively. Table 1. Population demographics by cohort.

Table 2. Population demographics by risk group.

Sensitivity ofMALDI-TOFMS and SPEP/IFX

The lower limit of detection was identified for conventional gel-based methods in MS-positive samples of around 0.2 g/L (0.02 g/dL) from both serial dilution sensitivity testing and results from the PROMISE study sub-cohort with results from capillary zone electrophoresis (CZE), immunofixation electrophoresis (IFE) and quantitative immunoprecipitation mass spectrometry (QIP-MS). As shown in FIG. 4A, each dilution was scored according to whether the M- protein was detected (+) equivocally detected (+/- ) or absent (-).

Serial dilution sensitivity testing results provided by the manufacturer showed MALDI-TOF MS detected all conventional gel-based assays’ positive calls. The lower limit of detection for capillary zone electrophoresis (CZE), when supplemented with IFX in MS-positive samples, was around 0.2 g/L (0.02 g/dL) (FIG. 4A). Further, in a subset of 2,192 participants from the PROMISE study that had SPEP/IFX results available at the time of analysis, 112 participants (5.1%; 95% CI, 4.3 to 6.2%) were positive for an M- protein by SPEP/IFX. Overall, 98.1% of samples with monoclonal protein detected on SPEP/IFX were replicated by MALDI-TOF MS. From 110 (5.1%; 95% CI, 4.3 to 6.2%) participants who screened positive by SPEP/IFX in our PROMISE cohort, 96 (87.2%) had an isotype-matched HC-LC M-protein by MALDI-TOF MS, 5 (4.5%) had an isotype- matched unpaired HC and LC abnormalities detected, 7 (6.3%) had isotype-matched HC abnormalities only detected. The consistency of M-protein concentration estimates between SPEP and MALDI-TOF MS was assessed in 44/112 (39%) samples with values reported by both techniques. A correlation of 0.95 (R²=0.90) was seen in the quantification of the monoclonal abnormality between both methods (FIG. 5).

FIG. 6 shows a series of graphs showing quantification of MS monoclonal immunoglobulins in SPEP/IFX positive and negative samples. For each isotype (IgA: left, IgG: middle, IgM: right), boxplots depicts median ± interquartile range (IQR) of peak concentration quantified by mass spectrometry depending on SPEP/IFX result (positive or negative). Participants who screened positive for an HC-LC pair or an HC-only monoclonal protein by MALDI-TOF MS but negative by SPEP/IFX (N=151, 6.8%) had a significantly lower estimated concentration of M-protein compared to participants with positive screen results from both assays (FIG. 6). The vast majority (96.3%) of isotype-matched M- proteins detected by MALDI-TOF MS and SPEP/IFX, had an M-protein concentration of >0.2 g/L (>0.02 g/dL) as estimated by MALDI-TOF MS except for one sample with an IgM M-protein with hypogammaglobulinemia at the time of testing.

MS-MGUS was defined by the presence of any heavy-chain (HC) monoclonal protein greater than or equal to 0.2 g/L. As supported by the SPEP/IFX data available, HC- LC pairing was not used to restrict the detection of HC-MGUS using the assay. In particular, serial dilution sensitivity testing results provided by the manufacturer showed MALDI-TOF MS detected all conventional gel-based assays’ positive calls. The lower limit of detection for SPEP when supplemented with IFX in MS-positive samples was around 0.2 g/L (0.02 g/dL) (see FIGs. 4A-4B). Further, in a subset of 2,192 participants from the PROMISE study that had SPEP/IFX results available at the time of analysis, 112 participants (5.1%; 95% CI, 4.3 to 6.2%) were positive for an M-protein by SPEP/IFX. Overall, in 98.1% of samples with monoclonal protein detected on SPEP/IFX were replicated by MALDI-TOF MS. From 110 (5.1%; 95% CI, 4.3 to 6.2%) participants who screened positive by SPEP/IFX in our PROMISE cohort, 96 (87.2%) had an isotype- matched HC-LC M-protein by MALDI-TOF MS, 5 (4.5%) had an isotype-matched unpaired HC and LC abnormalities detected, 7 (6.3%) had isotype-matched HC abnormalities only detected. Consistency of M-protein concentration estimates between SPEP and MALDI-TOF MS was assessed in 44/112 (39%) samples with values reported by both techniques. A correlation of 0.95 (R²=0.90) was seen in quantification of the monoclonal abnormality between both methods (FIG. 5). Participants who screened positive for an HC-LC pair or an HC only monoclonal protein by MALDI-TOF MS but negative by SPEP/IFX (N=151, 6.8%) had a significantly lower estimated concentration of M-protein compared to participants with positive screen results from both assays (FIG. 6). The vast majority (96.3%) of isotype-matched M-proteins detected by MALDI-TOF MS and SPEP/IFX, had an M-protein concentration of >0.2 g/L (>0.02 g/dL) as estimated by MALDI-TOF MS except for one sample with an IgM M-protein with hypogammaglobulinemia at the time of testing. All remaining HC related monoclonal proteins between 0.015 g/L and less than 0.2 g/L were named as a new entity, “monoclonal gammopathy of indeterminate potential” (MGIP), to be conservative and not refer to the lower-level monoclonal proteins below 0.2g/L as MGUS and preserve the naming of the entity described by Kyle et al. (PMID: 16571879) (FIG. 7A).

As shown in FIG. 7B, IgM was the most common highest-concentration isotype per participant between 0.015 g/L and less than 0.2 g/L followed by IgA and IgG. At 0.2g/L and above IgG was the most common followed by IgA and IgM.

LC-MGUS

Serum free light chain (sFLC) levels for the diagnosis of light-chain only MGUS (LC-MGUS) was then analyzed. In the absence of reference sFLC ranges for non-White individuals, this study’s data to propose reference values in individuals of racially diverse background was used. A total of 7,616 individuals had kappa and lambda LCs measured. The median free kappa LC was 16.8 mg/L with a median absolute deviation (MAD) of 6.56 mg/L. The median free lambda LC was 14.0 mg/L (MAD 5.26 mg/L). Serum free kappa light chain levels were significantly higher in Blacks compared to non-Black participants even in the absence of abnormal kidney function (Blacks versus Whites: +35%, P<1E-15; Black versus other races/non-reported race: +22%, P=7E-4, (FIGs. 8A-8D). Further, the majority of Black individuals with normal kidney function (54%) had kappa sFLC above the manufacturer reference value (19.3mg/L). Manufacturer and renal reference ranges for the sFLC ratio led to 81% false-positive discovery of LC-MGUS in Blacks with estimated glomerular filtration rate available (potential prevalence, 6.9%; 95% CI, 5.5 to 8.6%).

Novel reference ranges for serum free light chain concentration (sFLC) and kappa over lambda ratio (sFLCr) in a racially diverse population were defined using 95% central intervals in individuals from our study with normal kidney function and who screened negative for monoclonal gammopathies. Normal kidney function was predicted by an estimated Glomerular Filtration Rate (eGFR) over 90 mL/min/1.73m2. eGFR was calculated with the CKD-EPI 2021 formula (please cite https://www.nejm.org/doi/full/10.1056/NEJMoa2102953) using serum creatinine levels, age and sex. Finally, a total of 1,805 individuals (including 39.9% who self-reported as Black) with eGFR over 90 and who also screened negative for any monoclonal gammopathy by mass spectrometry in our study were considered to define reference ranges. This study’s reference range for Kappa sFLC was 8.93 to 39.2 mg/L, lambda sFLC range was 7.26 to 30.3 mg/L, and kappa/lambda sFLCr was 0.713 to 2.02. For individuals with abnormal kidney function predicted by eGFR<90, the renal reference sFLCr range was used (sFLCr 0.37 to 3.17) with this study’s kappa and lambda sFLC concentration ranges. For individuals without eGFR available in our study, the novel references were considered. Finally, light chain MGUS (LC-MGUS) was defined by an abnormal sFLCr with abnormal involved sFLC concentration in the absence of heavy-chain abnormality detected by mass spectrometry.

These results justified the need for novel reference ranges in a racially diverse population. Using sFLC data from 1,805 individuals (including 39.9% who self-reported as Black) with normal kidney function, who also screened negative for a monoclonal gammopathy by MS, a novel reference kappa over lambda sFLC ratio of 0.713 to 2.02 was defined, with abnormal kappa involvement above 39.2 mg/L (+102% compared to manufacturer reference) and abnormal lambda involvement above 30.3 mg/L (+15% compared to manufacturer reference) (FIGs. 9A-9B). Overall, LC-MGUS defined by an abnormal sFLC ratio with abnormal involved light chain was found in 0.66% (95% CI, 0.49 to 0.86%) of participants, with comparable prevalence in Blacks and Whites after accounting for kidney function (P=0.7) (FIGs. 9A-9B). For participants with abnormal kidney function (estimated glomerular filtration rate <90 mL/min/1.73m2 within 6 months of screened serum draw date), the published renal reference range (0.37-3.1) for evaluating the sFLC ratio was used for the diagnosis of LC-MGUS (PMID: 32234026).

Prevalence ofMS-MGUS, LC-MGUS andMGIP in the total cohort In the total screened cohort of 7,622 participants, a monoclonal gammopathy was detected in 36.2%. MGIP was detected in 1,952 (25.6%) and MS-MGUS was detected in 755 (9.9%) by MALDI-TOF MS. LC-MGUS was detected in 50 (0.66%) of the entire cohort (FIGs. 10A-10B). Hereon, LC-MGUS will be included in MS-MGUS prevalence calculations.

In the total cohort, the prevalence of MGIP and MS-MGUS, (HC-MGUS and LC- MGUS), increased significantly with age (P<0.001) (FIGs. 10A-10B). In 2,564 participants below 50 years of age, MGIP and MGUS were less frequent and detected in 19.0% and 5.0%, respectively. In 5,059 participants 50 years of age and above, prevalence of MGIP and MGUS increased to 28.9% and 13.4%, respectively. In 946 participants 70 years and above, prevalence of MGIP and MGUS were 36.7% and 18.2%, respectively. The prevalence of MGIP did not differ significantly across gender groups, MGUS was more common in males (P<0.001) (FIGs. 11A-11B).

The MS-MGUS and MGIP prevalence increased with age in the entire cohort (P<0.001) (FIGs. 7D and 7E). For age groups <50, >50, and >70 years, MS-MGUS prevalence was 5%, 13%, and 18%, respectively, and MGIP prevalence was 19%, 29%, and 37%, respectively. MS-MGUS was more common in males (P<0.001), while MGIP did not differ significantly by gender.

Higher Prevalence of heavy-chain MGUS detected by SPEP/IFX and MS-MGUS in high- risk participants in the PROMISE screening study compared to the general population

Among 2,192 high-risk participants from the PROMISE study screened by both SPEP/IFX and MALDI-TOF MS, MGUS was detected by SPEP/IFX in 5.2% (95% CI, 4.3 to 6.2%) and by MALDI-TOF MS in 10% (95% CI, 9.5 to 12). In a subset from this same high-risk cohort tested by both methods aged 50 and above, MGUS was detected in 5.8% (95% CI, 4.7 to 7.0%) and 12.6% (95% CI, 10.9 to 14.0%) by SPEP/IFX and MALDI-TOF MS, respectively. Compared to the prevalence of ~3% described in the general population at age 50, the data shows significantly higher prevalence of MGUS in high-risk individuals by the same conventional testing method of SPEP/IFX (5.8%) and even higher prevalence of MS-MGUS (12.4%) (FIG. 12).

Prevalence ofMGIP andMGUS (MS-MGUS and LC-MGUS) across risk groups

In 6,305 high-risk participants from the entire cohort, all MGs were detected in 36.5%. The rate ofMGIP was higher in risk group Black (N=665/2,439, 27.3%), compared to risk group FH (N=944/3,866, 24.4%; P=0.01) and control group (N=152/631, 24.0%; P=0.12) (FIG. 11A). The prevalence of MGUS was higher in risk group Black (N=283/2,439, 11.6%), compared to risk group FH (N=412/3,866, 10.7%; P=0.25) and control group (N=48/631, 7.6%; P=0.004) (FIG. 11B). Compared to the control group, risk group FH had a higher prevalence ofMGIP and MGUS among the entire cohort, although not reaching statistical significance in either comparison. In the unknown risk group, the prevalence of MGIP was 27.8% (N=191/686), and the prevalence of MGUS was 9.0% (N=62/686). When restricting the cohort to individuals aged 50 years and above, the prevalence patterns remained similar across risk groups, though statistical significance varied among comparisons and risk group FH had a significantly higher prevalence of MGUS compared to the control group (P<0.001) (FIG. 13). MGIP and MGUS were more common in the high-risk groups compared to controls, across age decades (FIGs. 14A- 14D)

Predictors of prevalence ofMGIP andMGUS

Predictors of screening positive for monoclonal gammopathies were evaluated in a multivariable logistic regression model adjusting for age, gender and risk group. Age (OR, 1.82; 95% CI, 1.72 to 1.93, p<0.001) and risk group Black (OR, 1.44; 95% CI, 1.18 to 1.75, p<0.001) were statistically significant predictors of all MGs (FIG. 15A). Age was the only significant predictor for MGIP alone in the cohort (OR, 1.45; 95% CI, 1.36 to 1.54) (FIG. 15B). For MGUS, age (OR, 2,28; 95% CI, 2.06 to 2.51), and risk group Black (OR, 1.79; 95% CI, 1.29 to 2.52) were independent predictors. Male sex (OR, 1.16; 95% CI 0.99 to 1.36) was also weakly associated with MGUS but the association was not statistically significant. Risk group FH was modestly associated with MGUS, but the association was not statistically significant (OR, 1.27; 95% CI, 0.94 to 1.76) (FIG. 15C). Increasing age, male sex, risk group Black and risk group FH were all significantly associated with MGUS on univariable analysis. In addition, FIGs. 16A-16C show all multivariable regression models reproduced accounting for race and family history as separate variables.

Age-related monoclonal gammopathies are associated with worse overall survival

Given that MGBB is a maturing prospective cohort, the associations of MG with overall survival was examined. In the MGBB cohort the median follow-up time of all participants after screening was 4.5 years (range, 0 - 11 years). In a multivariable Cox proportional-hazard model of all screened participants from the MGBB adjusted for age, sex, risk group and Charlson comorbidity Index, any monoclonal gammopathy detected using the assay was significantly associated with increased risk of all-cause mortality (HR, 1.55; 95% CI, 1.16 to 2.08), compared to no monoclonal gammopathy. When the cohort was restricted to participants of age 50 and above, the hazard ratio for all-cause mortality for any monoclonal gammopathy detected using the assay was 1.68 (HR, 1.68; 95% CI, 1.68 to 2.31) (FIGs. 17A-17E).

MS-MGUS was significantly associated with increased all-cause mortality (HR, 2.18; 95% CI, 1.51 to 3.13), compared to having no MG. In participants age >50, HRs of MS-MGUS and MGIP for all-cause mortality were 2.35 (95% CI, 1.59 to 3.47) and 1.38 (95% CI, 0.96 to 1.98) (FIGs. 17A-17E).

When monoclonal gammopathy thresholds were examined separately, MGUS was significantly associated with increased risk of all-cause mortality (HR, 2.32; 95% CI, 1.61 to 3.35), compared to no monoclonal gammopathy. MGIP was near significant for an increased risk for all-cause mortality (HR, 1.34; 95% CI, 0.95 to 1.88) compared to no monoclonal gammopathy (FIGs. 18A-18D and FIGs. 19A-19B). Further, FIGs. 20A-20B and FIGs. 21A-21B show all Cox proportional-hazard models for survival reproduced accounting for race and family history as separate variables. Comorbidities and outcomes associated with MGUS andMGIP in the MGBB cohort

Age-adjusted logistic regression models evaluated the associations of monoclonal gammopathies and various comorbidities diagnosed at any point in the participants’ lifetimes. The corresponding odds ratios and 95% confidence intervals are shown in FIG. 22. MGUS was associated with myocardial infarction, hematological malignancies and specific subtypes of HM including lymphoid leukemia, chronic lymphocytic leukemia, Hodgkin’s lymphoma, and non-Hodgkin’s lymphoma. It was also associated with systemic lupus erythematosus, and ulcerative colitis. MGUS was also modestly associated with coronary artery disease, although the latter association was not statistically significant. MGIP was associated with myocardial infarction and Hodgkin’s lymphoma. MGIP was also modestly associated with coronary artery disease, rheumatoid arthritis, systemic lupus erythematosus, though these associations were not statistically significant.

In sensitivity analyses excluding all patients with a diagnosis of a hematologic malignancy prior to the 6 months post-screening time point, having a monoclonal gammopathy was associated with an increased likelihood of developing a hematologic malignancy at least 6 months after screen date, compared to no monoclonal gammopathy (OR, 3.03, 95% CI, 1.95 to 4.79) (FIGs. 23A-23B and FIGs. 24A-24B). MGUS at the time of screening was significantly associated with a nearly 8-fold likelihood of being diagnosed with a hematologic malignancy at least 6 months after screen date (OR, 8.31, 95% CI, 5.10 to 13.66, p<0.001) compared to no monoclonal gammopathy, whereas MGIP was associated with modest increase in likelihood of hematologic malignancy diagnosis at least 6 months after screening date (OR, 1.29, 95% CI, 0.71 to 2.30, p=0.40) (FIGs. 24A-24B).

Outcomes MGUS and MM

Medical records were available for MGBB participants. The charts of all MGBB participants in the cohort who screened-positive for MGIP and subsequently received a diagnosis of MGUS by SPEP during routine clinical care were reviewed. Four participants were identified, 3 of whom screened positive for IgM MGIP isotype. Their ages at time of screening were 33, 57, and 63 years old, and time from screening to MGUS diagnosis by SPEP were 8.1, 1.6, and 9.1 years, respectively. Review of SPEP/IFX data showed that they developed IgG and/or IgA MGUS. The fourth participant was 82 years old when screening positive for IgA MGIP and was subsequently diagnosed with IgG MGUS by SPEP/IFX 2.4 years from the time of screening. There were no MGIP cases that subsequently developed MM in the MGBB cohort. The median follow-up period was 4.5 years (range, 0 - 11 years).

Persistence of monoclonal gammopathy on serial testing

Serial samples were available for testing for 58 participants with an M-protein identified at baseline screening. The median time between the baseline screen sample and the latest sample available was 300 days (range, 86 to 864 days) for those with MGIP and 235 days (range, 36 to 905 days) for those with MGUS. Persistence of the M-protein was defined as the identification of the same isotype M-protein within +/- 7 m/z on serial testing. Serial sampling of 26 participants who primarily screened positive for MGIP at baseline was positive again in 50% of cases (13 out of 26) with at least one month between replicates. Further, 35% (9 out of 26) had their latest MGIP screening still positive with a maximum of 2.5 years. See FIGs. 7C and 25. For this latter case, the participant had negative follow-up testing on days +589 and +689 and tested positive again at +864 days with the same monoclonal peak. Among 32 participants with MGUS at baseline and serial serum samples available, the M-protein was detected on repeat testing in 94% of them (30 out of 32), consistent with the maintenance of MGUS over time (FIG. 7C). Of note, with these criteria, no IgM MGIP progressed to a monoclonal gammopathy of IgG or IgA isotype. Instead, most MGUS (65%) consistently increased in peak concentration, including one participant who progressed to SMM, and two IgM MGIP participants had their peak concentration reaching the definition of IgM MGUS.

The cohort was expanded from 58 individuals to 102 participants in an additional study. In total, 262 multi-point samples were collected in the 102 collective participants. The study had a median follow-up of 336 days (Range 36-1,240; IQR 141-737). The median age at screening was 60.8 years; 65 (64%) participants were female; 9 (9%) selfidentified as Black, and 93 (91%) were non-Black and reported a family history of hematologic malignancy. At baseline, 66 (65%) participants had MGIP (M-protein between 0.015 g/L and less than 0.2 g/L) and 36 (35%) had MGUS (M-protein >=0.2/L) measured by MALDI-TOF MS.

Table 3. Population demographics and diagnoses at baseline.

For all 102 cases, their most recent serial samples were tested by MALDI- TOF MS or LC-MS. 60/66 (91%) of the MGIP cases were confirmed on serial sampling, with a median follow-up time of 504 days (Range 41 - 1,240; IQR 149 - 888). As for MGUS, 36/36 (100%) of cases detected at baseline persisted on serial sampling, with a median follow-up time of 239 days (Range 36 - 1105; IQR 103 - 628) (FIGs. 26A-26B). Time from baseline to serial sampling was not associated with persistence. In twelve participants so far, M-proteins detected by MS were seen to persist for more than three years after baseline testing. In five of the MGIP cases, M-protein concentration measured by MALDITOF MS increased from MGIP level to above the MGUS threshold. See FIG. 27. These participants had a median baseline M-protein concentration of 0.14 g/L (Range 0.13 - 0.17 g/L; IQR 0.13 - 0.14), which was in the upper MGIP concentration level, and had a median followup time of 532 days (Range 171 - 1,127; IQR 302 - 570). Of these, three persisted as IgG, 1 IgA, and 1 IgM isotypes.

This study provides the first longitudinal analysis of M-proteins detected by MS, including those below the threshold of detection of gel -based assays, in a US populationbased screening study. The results confirm the persistence of 91% of MGIP and 100% of MGUS cases detected by MS.

Discussion

Prior estimates of MGUS prevalence are based on SPEP/IFX and predominantly White study populations. Utilizing an MS-based approach screening of individuals at risk for developing myeloma, the data here provide the largest screening study for sensitive serum monoclonal proteins across concentration gradients and in the most racially diverse cohort examined to date. The study identifies a very high prevalence of all MGs of >40% in high-risk individuals aged >50. Compared to the prevalence of 3% detected by SPEP/IFX in the general population aged >50 years, high-risk individuals in our cohort from the same age group were found to have an MGUS prevalence that is over four times higher (13%) by MS. The identified prevalence rates here exceeded expectations and point to an early disease entity, namely MGIP that needs further evaluations in these high-risk individuals. Prior studies have shown that mass spectrometry detected higher rates of monoclonal proteins for the diagnosis of MGUS, however, such findings were limited by a few hundred participants from the Olmsted County study being tested and showed a prevalence of MGUS of around 5% only and it used a qualitative testing approach. The findings here are distinct in that a much higher prevalence of MS-MGUS and other MGs was detected. MGs in the present study were quantifiable, allowing for stratification of outcomes, risk estimates, and clinical associations based on concentration cut points and accurate comparison to currently widely available methods. These MS-MGUS patients identified by this targeted screening approach had significantly worse survival compared to low-risk patients, even when accounting for age, gender, risk group, and CCI. This finding builds on prior studies of more racially homogeneous populations in Sweden and southeastern Minnesota that found shorter overall and MM-specific survival in individuals diagnosed with MGUS. Our results show that the novel pool of MS-MGUS and MGIP-H detected by this new screening approach and not previously identified, both show a strong association with decreased OS from all-cause mortality. These results, therefore, continue to motivate efforts to prospectively follow and screen a high-risk population to explore the clinical benefit of active, targeted screening strategies.

MS has allowed for the quantification of MGs at lower concentration levels than what was previously possible by SPEP/IFX, providing a new opportunity to explore their uncertain significance in the malignant and non-malignant clonal expansion of plasma cells. Unlike in MGUS, where the prevalence was expectedly greater in high-risk groups, the prevalence of these low-level MGs, which is termed MGIP, did not differ significantly by race and family history, suggesting that these host factors may be permissive in the further clonal expansion of MGIP to MGUS stage. The association of MGIP with increasing age could also be analogous to age-associated clonal hematopoiesis of indeterminate potential (CHIP), motivating the future evaluation of sequencing plasma cells of cohort participants22-24. Indeed, it is hypothesized that in a subset of individuals, MGIP may have etiologic implications in the development of MGUS under the influence of certain host and environmental factors, such as race, inflammation, and genetic predisposition. However, it is not believed that all MGIP cases are of malignant phenotype as transient M-proteins have been described in the setting of immune-related disorders, infections, allogeneic hematopoietic stem cell transplant, and solid organ transplant. Further, a similar association to that of MS-MGUS with worse OS was seen for participants with MGIP-H, noting that varying biology might be spanning the continuum of MGs identified between 0.015 g/L and less than 0.2 g/L, with the MGs at the upper limit of MGIP (MGIP-H) potentially sharing biologic similarities with MS-MGUS.

Furthermore, the results from a racially diverse study cohort necessitated an adjusted reference range for sFLC ratio. After adjusting for kidney function, the analysis provides a proof-of-concept for defining population-specific reference ranges when evaluating sFLC.

In summary, there was a high >40% prevalence of MGs when utilizing MS to screen a predominantly high-risk population, defined by self-reported Black race and family history of HM. The study demonstrated that MGs are significantly associated with worse overall survival and the development of HMs. A new clinical entity of low- concentration MGs (i.e., MGIP) that had a high prevalence of approximately 25% was defined, a notably different risk factor profile than MGUS, and associations with age and MI. This study highlights the clinical significance of MGs.

Example 2.

To explore whether monoclonal immunoglobulin peaks correspond to clonal B cell lymphoproliferative processes, single-cell RNA sequencing, coupled with B cell receptor (BCR) sequencing, was performed on magnetically sorted CD19⁺ B cells and CD138⁺ plasma cells from six individuals whose serum had been profiled by MALDI-TOF. Specifically, this cohort included two healthy individuals without Monoclonal Gammopathy of Indeterminate Potential (MGIP; i.e., between 0.015 g/L and less than 0.2 g/L of M-protein), two individuals with Monoclonal Gammopathy of Undetermined Significance (MGUS; e.g., between 0.2 g/L and less than 30 g/L), one of whom also had a secondary MGIP peak, and two individuals with MGIP, one with a single peak and another with two distinct peaks.

Strikingly, clonal B cell expansions (>1% of B cell repertoire) by single-cell BCR sequencing was observed only in individuals with MGIP peaks (FIG. 28A). By integrating RNA and BCR sequencing data, two distinct modes of clonal B cell processes in the three positive samples were observed (FIG. 28B): mode 1 (rectangles), corresponding to possible malignancies, as hypothesized based on the clones’ immunophenotype (FIG. 28C) as well as the fact they clustered separately than normal B cells in the RNA space; and mode 2 (circles), corresponding to possible physiologic expansions, as hypothesized based on the fact that the clones exhibited a phenotype consistent with marginal zone B cells (cells known to mediate acute antibody-secreting reactions) and clustered together with normal B cells. To confirm the malignant status of one clone with undetermined B cell lymphoma (UBCL) phenotype, copy number variants were inferred using Numbat, a haplotype-aware copy number caller, and observed amplification of chr3q and chrl8 indicated by rectangles (FIG. 28D). This copy number profile is most consistent with that of a post-germinal center lymphoma, like Activated B Cell-like Diffuse Large B cell Lymphoma (ABC-DLBCL), marginal zone lymphoma (MZL) or lymphoplasmacytic lymphoma (LPL). Lastly, based on the presence of a typical immunophenotype alone, another B cell clone was classified as a Chronic Lymphocytic Leukemia (CLL) clone (CD5+ CD23+ CD43+ CD200+ LEF1+ ZAP70+) (FIG. 28C).

Taken together, these data demonstrates that low-level monoclonal gammopathy detected through MALDLTOF on peripheral blood serum may reflect the presence of a B cell Lymphoproliferative Disorder, including but not limited to myeloma, CLL and post- germinal center lymphomas, like ABC-DLBCL, MZL, and LPL.

References Siegel RL, Miller KD, Jemal A. Cancer statistics, 2020. CA Cancer J Clin. 2020;70(l):7- 30. doi: 10.3322/caac.21590 Kyle RA, Themeau TM, Rajkumar SV, et al. Prevalence of monoclonal gammopathy of undetermined significance. N Engl J Med. 2006;354(13): 1362-1369. doi: 10.1056/NEJMoa054494 SEER Cancer Statistics Review, 1975-2013. National Cancer Institute. Bethesda, MD. Published April 2016. https://seer.cancer.gov/archive/csr/1975_2013/ Landgren O, Kyle RA, Pfeiffer RM, et al. Monoclonal gammopathy of undetermined significance (MGUS) consistently precedes multiple myeloma: a prospective study. Blood. 2009;113(22):5412-5417. doi: 10.1182/blood-2008-12-194241 Nowell PC. The clonal evolution of tumor cell populations. Science. 1976;194(4260):23- 28. doi: 10.1126/science.959840 Landgren O. Monoclonal gammopathy of undetermined significance and smoldering multiple myeloma: biological insights and early treatment strategies. Hematology. 2013;2013(l):478-487. doi : 10.1182/asheducation-2013.1.478 Kyle RA, Larson DR, Themeau TM, et al. Long-Term Follow-up of Monoclonal Gammopathy of Undetermined Significance. N Engl J Med. 2018;378(3):241-249. doi: 10.1056/NEJMoal 709974 Kyle RA, Remstein ED, Therneau TM, et al. Clinical Course and Prognosis of Smoldering (Asymptomatic) Multiple Myeloma. N Engl J Med. 2007;356(25):2582- 2590. doi: 10.1056/NEJMoa070389 Cohen HJ, Crawford J, Rao MK, Pieper CF, Currie MS. Racial differences in the prevalence of monoclonal gammopathy in a community-based sample of the elderly. Am JMed. 1998;104(5):439-444. doi: 10.1016/s0002-9343(98)00080-l Landgren O, Katzmann JA, Hsing AW, et al. Prevalence of monoclonal gammopathy of undetermined significance among men in Ghana. Mayo Clin Proc. 2007;82(12): 1468- 1473. doi: 10.1016/S0025-6196(l 1)61089-6 11. Landgren O, Gridley G, Turesson I, et al. Risk of monoclonal gammopathy of undetermined significance (MGUS) and subsequent multiple myeloma among African American and white veterans in the United States. Blood. 2006;107(3):904. doi: 10.1182/blood-2005-08-3449

E2. Landgren O, Graubard BI, Kumar S, et al. Prevalence of myeloma precursor state monoclonal gammopathy of undetermined significance in 12372 individuals 10-49 years old: a population-based study from the National Health and Nutrition Examination Survey . Blood Cancer J. 2017;7(10):e618. doi: 10.1038/bcj.2017.97

13. Hari P, Majhail NS, Hassebroek A, Zhang M-J, Siddiqui F, Mehta P. Similar Outcomes0 among African-Americans (AA) and Whites after Autologous Hematopoietic-Cell Transplantation (Auto HCT) for Multiple Myeloma (MM). Blood. 2008; 112(11):740. doi: 10.1182/blood. VI 12.11.740.740

14. Landgren O, Kristinsson SY, Goldin LR, et al. Risk of plasma cell and lymphoproliferative disorders among 14621 first-degree relatives of 4458 patients with5 monoclonal gammopathy of undetermined significance in Sweden. Blood.

2009; 114(4): 791 -795. doi : 10.1182/blood-2008- 12-191676

15. Vachon CM, Kyle RA, Therneau TM, et al. Increased risk of monoclonal gammopathy in first-degree relatives of patients with multiple myeloma or monoclonal gammopathy of undetermined significance. Blood. 2009;l 14(4):785. doi: 10.1182/blood-2008-12-192575D6. Schinasi LH, Brown EE, Camp NJ, et al. Multiple myeloma and family history of lymphohaematopoietic cancers: Results from the International Multiple Myeloma Consortium. Br J Haematol. 2016; 175(l):87-101. doi: 10.1111/bjh.14199

17. Lynch HT, Ferrara K, Barlogie B, et al. Familial Myeloma. N Engl J Med.

2008;359(2): 152-157. doi: 10.1056/NEJMoa0708704 E8. Sigurdardottir EE, Turesson I, Lund SH, et al. The Role of Diagnosis and Clinical Follow-up of Monoclonal Gammopathy of Undetermined Significance on Survival in Multiple Myeloma. JAMA Oncol. 2015; 1 (2): 168- 174. doi:10.1001/jamaoncol.2015.23 Go RS, Gundrum JD, Neuner JM. Determining the clinical significance of monoclonal gammopathy of undetermined significance: a SEER-Medicare population analysis. Clin Lymphoma Myeloma Leuk. 2015;15(3): 177-186. e4. doi: 10.1016/j.clml.2014.09.004 Goyal G, Rajkumar SV, Lacy MQ, et al. Impact of Prior Diagnosis of Monoclonal Gammopathy on Outcomes in Newly Diagnosed Multiple Myeloma. Leukemia. 2019;33(5): 1273-1277. doi: 10.1038/s41375-019-0419-7 van de Donk NWCJ, Palumbo A, Johnsen HE, et al. The clinical relevance and management of monoclonal gammopathy of undetermined significance and related disorders: recommendations from the European Myeloma Network. Haematologica. 2014;99(6):984-996. doi:10.3324/haematol.2013.100552 Bird J, Behrens J, Westin J, et al. UK Myeloma Forum (UKMF) and Nordic Myeloma Study Group (NMSG): guidelines for the investigation of newly detected M-proteins and the management of monoclonal gammopathy of undetermined significance (MGUS). Br J Haematol. 2009;147(l):22-42. doi: 10.1111/j.1365-2141.2009.07807.x Berenson JR, Anderson KC, Audell RA, et al. Monoclonal gammopathy of undetermined significance: a consensus statement. Br J Haematol. 2010;150(l):28-38. doi: 10.1111/j.1365-2141.2010.08207.x Mateos M-V, Hernandez M-T, Giraldo P, et al. Lenalidomide plus Dexamethasone for High-Risk Smoldering Multiple Myeloma. N Engl J Med. 2013;369(5):438-447. doi: 10.1056/NEJMoal300439 Lonial S, Jacobus S, Fonseca R, et al. Randomized Trial of Lenalidomide Versus Observation in Smoldering Multiple Myeloma. J Clin Oncol. 2020;38(l 1): 1126. doi: 10.1200/JCO.19.01740 Landgren CO, Chari A, Cohen YC, et al. Daratumumab monotherapy for patients with intermediate-risk or high-risk smoldering multiple myeloma: a randomized, open-label, multicenter, phase 2 study (CENTAURUS). Leukemia. 2020;34(7): 1840-1852. doi : 10.1038/s41375-020-0718-z Sakrikar D, Marrot N, North S, et al. Multi-Site Verification of the Automated EXENT® MALDI-TOF-MS System and Immunoglobulin Isotypes Assay for the Identification and Quantification of Monoclonal Immunoglobulins. In: ; 2021. Accessed October 7, 2021. https://www.abstractsonline.eom/pp8/#l/9313/presentation/23 Willrich MAV, Murray DL, Kyle RA. Laboratory testing for monoclonal gammopathies: Focus on monoclonal gammopathy of undetermined significance and smoldering multiple myeloma. Clin Biochem. 2018;51 :38-47. doi: 10.1016/j.clinbiochem.2017.05.001 Dimopoulos M, Kyle R, Fermand J-P, et al. Consensus recommendations for standard investigative workup: report of the International Myeloma Workshop Consensus Panel 3. Blood. 2011;117(18):4701-4705. doi: 10.1182/blood-2010-10-299529 Zajec M, Langerhorst P, VanDuijn MM, et al. Mass Spectrometry for Identification, Monitoring, and Minimal Residual Disease Detection of M-Proteins. Clin Chem. 2020;66(3):421-433. doi:10.1093/clinchem/hvz041 Murray DL, Seningen JL, Dispenzieri A, et al. Laboratory persistence and clinical progression of small monoclonal abnormalities. Am J Clin Pathol. 2012;138(4):609-613. doi : 10.1309/AJCPT6OWWMHIT Al Y Bamidge DR, Dasari S, Botz CM, et al. Using mass spectrometry to monitor monoclonal immunoglobulins in patients with a monoclonal gammopathy. J Proteome Res.

2014;13(3): 1419-1427. doi: 10.1021/pr400985k Chapman JR, Thoren KL. Tracking of low disease burden in multiple myeloma: Using mass spectrometry assays in peripheral blood. Best Pract Res Clin Haematol . 2020;33(l): 101142. doi: 10.1016/j.beha.2020.101142 Murray D, Kumar SK, Kyle RA, et al. Detection and prevalence of monoclonal gammopathy of undetermined significance: a study utilizing mass spectrometry-based monoclonal immunoglobulin rapid accurate mass measurement. Blood Cancer J.

2019;9( 12): 1 -7. doi : 10.1038/s41408-019-0263 -z

Claims

What is claimed is:

1. A method of determining a subject as being at risk of developing multiple myeloma (MM), the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample.

2. A method of determining a subject as being at risk of developing multiple myeloma (MM), the method comprising:

(a) identifying the subject as having a risk factor for developing MM; and

(b) detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample.

3. A method of monitoring a subject being at risk of developing multiple myeloma (MM), the method comprising:

(a) identifying the subject as having a risk factor for developing MM;

(b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample; and

(c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months.

4. A method of treating a subject having an increased risk of developing multiple myeloma (MM), the method comprising:

(a) identifying the subject as having a risk factor for developing MM;

(b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample; and (c) providing a therapeutically effective amount of a treatment to the subject.

5. A method of determining a subject as being at risk of developing multiple myeloma (MM), the method comprising detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample.

6. A method of determining a subject as being at risk of developing multiple myeloma (MM), the method comprising:

(a) identifying the subject as having a risk factor for developing MM; and

(b) detecting a monoclonal paraprotein (M-protein) in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample.

7. A method of monitoring a subject being at risk of developing multiple myeloma (MM), the method comprising:

(a) identifying the subject as having a risk factor for developing MM;

(b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample; and

(c) repeating step (b) about every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months, or at least 42 months.

8. A method of treating a subject having an increased risk of developing multiple myeloma (MM), the method comprising:

(a) identifying the subject as having a risk factor for developing MM; (b) detecting an M-protein in a sample from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample; and

(c) providing a therapeutically effective amount of a treatment to the subject.

9. The method of any one of the preceding claims, wherein the M-protein is not detected using serum protein electrophoresis (SPEP) and/or immunofixation (IFX).

10. The method of any one of the preceding claims, further comprising quantifying the concentration of Immunoglobulin G (IgG), Immunoglobulin A (IgA), Immunoglobulin (IgM), and serum free light chain (sFLC) in the sample.

11. The method of claim 10, wherein the serum free light chain is Kappa free light chain or Lambda free light chain.

12. The method of any one of the preceding claims, wherein mass spectrometry is matrix-assisted laser desorption ionization-time of flight (MALDI-TOF) mass spectrometry.

13. The method of any one of the preceding claims, wherein the sample is a blood sample.

14. The method of any one of the preceding claims, wherein the sample is a sample of isolated DNA, serum, bone marrow, or plasma.

15. The method of any one of the preceding claims, wherein the concentration of the M-protein in the sample is increased compared to concentration of M-protein in a reference sample.

16. The method of claim 15, wherein the reference sample is from a subject having low risk of developing MM.

17. The method of claim 16, wherein the subject having low risk of developing MM is less than 30 years old.

18. The method of claim 16 or 17, wherein the subject having low risk of developing MM is not Black or African American.

19. The method of any one of claims 16 to 18, wherein the subject having low risk of developing MM is White.

20. The method of any one of claims 16 to 19, wherein the subject having low risk of developing MM has no family history of MM.

21. The method of any one of claims 16 to 20, wherein the subject having low risk of developing MM is age-matched to the subject.

22. The method of any one of claims 2 to 4 or 6 to 21, wherein the risk factor comprises that the subject is over 18 years old.

23. The method of any one of claims 2 to 4 or 6 to 18, wherein the risk factor comprises that the subject is between the ages of 40 and 75.

24. The method of any one of claims 2 to 4 or 6 to 23, wherein the risk factor comprises that the subject has a family history of one or more plasma cell dyscrasias.

25. The method of any one of claims 2 to 4 or 6 to 24, wherein the risk factor comprises that the subject has a first-degree relative diagnosed with one or more plasma cell dyscrasias.

26. The method of any one of claims 2 to 4 or 6 to 25, wherein the risk factor comprises that the subject has more than one first-degree relative with one or more plasma cell dyscrasias.

27. The method of any one of claims 24 to 26, wherein the one or more plasma cell dyscrasias comprises MM.

28. The method of any one of claims 2 to 4 or 6 to 27, wherein the risk factor comprises that the subject identifies as Black or of African descent.

29. The method of any one of the preceding claims, wherein the subject has not been diagnosed with monoclonal gammopathy of undetermined significance (MGUS), smoldering multiple myeloma (SMM), MM, or Waldenstrom’s Macroglobulinemia.

30. The method of any one of claims 1-4 and 9-29, wherein the subject has MGIP.

31. The method of any one of claims 5-29, wherein the subject has MGUS.

32. The method of any one of claims 1 to 8 or 10 to 25, wherein detecting the M- protein is performed using SPEP and/or IFX.

33. The method of any one of the preceding claims, wherein the subject is undergoing no treatment for one or more plasma cell dyscrasias.

34. The method of any one of claims 1 to 26, wherein the subject is undergoing treatment for one or more plasma cell dyscrasias.

35. The method of claim 4 or 8, wherein the treatment comprises an immunomodulating agent, an immunotherapeutic vaccine, a proteasome inhibitor, a chemotherapy agent, a histone deacetylase, a monoclonal antibody against CD38, an antibody against SLAMF7, an antibody-drug conjugate, a nuclear export inhibitor, a steroid, a bisphosphonate, a CAR-T cell therapy, multispecific antibodies, and any combination thereof.

36. The method of any one of claims 1 to 3, 5 to 7, and 9 to 34, further comprising administering to the subject an immunomodulating agent, an immunotherapeutic vaccine, a proteasome inhibitor, a chemotherapy agent, a histone deacetylase, a monoclonal antibody against CD38, an antibody against SLAMF7, an antibody-drug conjugate, a nuclear export inhibitor, a steroid, a bisphosphonate, a CAR-T cell therapy, multispecific antibodies, and any combination thereof.

37. The method of any one of the preceding claims, wherein prevalence of detection of the risk of developing multiple myeloma is increased compared to prevalence of detection of the risk of developing multiple myeloma quantified by mass spectrometry at a concentration greater than 0.2 g/L in the sample.

38. The method of any one of the preceding claims, wherein prevalence of detection of the risk of developing multiple myeloma is increased compared to prevalence of detection of the risk of developing multiple myeloma determined using SPEP and/or IFX.

39. The method of any one of the preceding claims, wherein prevalence of detection of the risk of developing multiple myeloma is increased compared to prevalence of detection of the risk of developing multiple myeloma determined using SPEP and/or IFX by at least two-fold, at least three-fold, or at least four-fold.

40. The method of any one of the preceding claims, further comprising monitoring progression of developing MM, monoclonal gammopathy of undetermined significance (MGUS), and/or smoldering multiple myeloma (SMM).

41. The method of claim 40, wherein monitoring progression of developing MM, MGUS, or SMM includes detecting the M-protein in a follow-up sample or samples from the human subject quantified by mass spectrometry at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months or at least 42 months.

42. The method of claim 40, wherein monitoring progression of developing MM, MGUS, or SMM includes detecting the M-protein in a follow-up sample or samples from the human subject quantified by mass spectrometry at a concentration of between 0.2 g/L and less than 30 g/L in the sample every at least 6 months, at least 12 months, at least 18, months, at least 24 months, at least 30 months, at least 36 months or at least 42 months.

43. A method of determining if a subject is likely to develop a B cell Lymphoproliferative Disorder, the method comprising obtaining a sample from the subject and determining by mass spectrometry that the sample contains a monoclonal paraprotein (M-protein) at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample.

44. The method of claim 43, wherein the sample is a serum sample.

45. The method of claim 43, wherein the subject is a human subject.

46. The method of any one of claims 43 to 45, further comprising performing singlecell RNA sequencing, and/or with B cell receptor (BCR) sequencing, on CD19⁺ B cells and CD138⁺ plasma cells and determining clonal B cell expansions.

47. The method of any one of claims 43 to 46, wherein the B cell Lymphoproliferative Disorder is a myeloma, chronic lymphocytic leukemia (CLL), and a post-germinal center lymphoma.

48. The method of claim 47, wherein the post-germinal center lymphoma comprises activated B cell-like diffuse large B cell lymphoma (ABC-DLBCL), marginal zone lymphoma (MZL) or lymphoplasmacytic lymphoma (LPL).

49. The method of any one of the preceding claims, further comprising administering a treatment for the B cell Lymphoproliferative Disorder.

50. A method of treating a B cell Lymphoproliferative Disorder, the method comprising administering to a subject whose serum sample contains a monoclonal paraprotein (M-protein) at a concentration of between 0.015 g/L and less than 0.2 g/L in the sample, a therapeutically effective amount of a treatment for the B cell Lymphoproliferative Disorder.

51. The method of claim 50, wherein single-cell RNA sequencing and/or B cell receptor (BCR) sequencing on CD 19+ B cells and CD 138+ plasma cells from the subject shows clonal B cell expansions.

52. The method of claim 50 or 51, wherein the subject is a human.

53. The method of any one of claims 49-52, wherein the treatment is comprises chimeric antigen receptor (CAR) T-cell therapy, axicabtagene ciloleucel, tisagenlecleucel, lisocabtagene maraleucel, natural killer cell therapy, monoclonal antibodies such as rituximab, polatuzumab vedotin-piiq, brentuximab vedotin, blinatumomab, tafasitamab, and/or mosunetuzumab; radiation therapy, surgical procedures, hematopoietic cell transplantation, stem cell transplantation; cyclophosphamide, doxorubicin, vincristine, prednisone, dexamethasone, methotrexate, cytarabine, obinutuzumab, chlorambucil, fludarabine, bendamustine, bortezomib, cladribine, fludarabine, lenalidomide, ibrutinib, acalabrutinib, zanubrutinib, venetoclax, idelalisib, cladribine, pentostatin.

54. The method of any one of claims 43-53, wherein the M-protein is IgM.

55. The method of any one of claims 43-53, wherein the M-protein is IgA.

56. The method of any one of claims 43-53, wherein the M-protein is IgG.