Methods for characterizing and treating multiple myeloma

Abstract

Provided are methods for treating an individual diagnosed with multiple myeloma (MM) by administering to the individual a therapeutically effective amount of a C-X-C motif chemokine receptor 2 (CXCR2) inhibitor to thereby inhibit progression of the MM. Combining CXCR2 blockade with standard of care agents has a synergistic anti-MM effect. Also provided are characterizations of MM patient neutrophils with identification of markers that reveal distinct subsets of neutrophils found in bone marrow and focal lesions of MM patients.

Description

[0001] METHODS FOR CHARACTERIZING AND TREATING MULTIPLE MYELOMA

[0002] CROSS-REFERENCE TO RELATED APPLICATIONS

[0003] This application claims the benefit of U.S. provisional patent application no. 63 / 546,962, filed November 2, 2023, the entire disclosure of which is incorporated herein by reference.

[0004] BACKGROUND

[0005] Cancer cells can suppress immune cell activity, evading destruction, significantly impacting cancer research and therapy. Treatments including chemotherapy, checkpoint inhibitors and adoptive cellular therapies are standard for many solid tumors and hematologic malignancies. While much research has focused on immune factors such as T-cell exhaustion and immunosuppressive macrophages in the tumor microenvironment (TME), a detailed understanding of the role of neutrophils in cancer-induced immunosuppression remains elusive. There is accordingly an ongoing and unmet need for increased understanding the role of neutrophils, and new treatments based on such understanding, particularly for hematologic malignancies such as multiple myeloma (MM). In particular, a deeper understanding of neutrophil dynamics and functions at the single cell level at multiple tumor locations within the TME is urgently needed to develop new therapeutic strategies. The present disclosure is pertinent to these needs.

[0006] BRIEF SUMMARY

[0007] This disclosure provides a method for treating an individual diagnosed with MM by administering to the individual a therapeutically effective amount of a C-X-C motif chemokine receptor 2 (CXCR2) inhibitor to thereby inhibit progression of the MM. Data presented herein also demonstrate that CXCR2 inhibition enhances the response to combination therapy. In examples, the disclosure provides a method comprising comprises administering a CXCR2 inhibitor and a chemotherapy, immunotherapy, or targeted therapy to an individual diagnosed with MM. In an example, use of a CXCR inhibitor in combination with one or more anti-MM agents promotes a synergistic anti-MM progression effect.

[0008] In non-limiting examples, the CXCR2 inhibitor is selected from the group consisting of CXCR2-IN-1, SB 265601, AZD5069, SCH-527123 (Navaxarin), SB225002, GSK1325456 (Danirixin), Reparixin, SX-682, or a combination thereof.

[0009] In examples, neutrophils from the individual exhibit higher expression of at least one marker selected from the group consisting of CD10, TNFAIP-3, CXCL8, CXCR2, LCN2, TREM1, resistin, or a combination thereof, relative to expression of said marker by neutrophils from an individual who does not have MM.

[0010] In an example, neutrophils from the individual exhibit higher expression the CXCR2, relative to CXCR2 expression by neutrophils obtained from an individual who does not have MM. In examples, the neutrophils are present in focal lesions or bone marrow.

[0011] In an aspect, the disclosure provides a method comprising analyzing a biological sample from an individual who has been diagnosed with MM, said biological sample comprising neutrophils, wherein the analyzing comprises testing the neutrophils for increased expression of at least one marker selected from the group consisting of CD10, TNFAIP-3, CXCL8, CXCR2, LCN2, TREM1, resistin, or a combination thereof. This increased expression is relative to expression of the markers by neutrophils from an individual who does not have MM. The increased the increased expression indicates the individual is a candidate for MM therapy by treatment with a CXCR2 inhibitor. In examples, the biological sample comprises a sample of bone marrow or a focal lesion. In examples, the method comprises administering to the individual the CXCR2 inhibitor, optionally in combination with chemotherapy, immunotherapy, or targeted therapy.

[0012] BRIEF DESCRIPTION OF THE FIGURES

[0013] Figures 1A-1D: CDllb+myeloid cells from MM patient bone marrow and osteolytic lesions and healthy donor bone marrow. A.) Samples from newly diagnosed multiple myeloma (NDMM) (n=7), relapsed refractory MM (RRMM) (n=6) patients’ (bone marrow (BM) and focal lesions (FL)) and healthy donor BM (HBM) (n=3) are shown in the UMAP representation of 105,192 CDllb+cells captured with 10X V3 5’ scRNA-seq. See Materials and Methods for complete details. Nine clusters observed were, 1 : TNFAIP+MME+ mature neutrophils, 2: S100A8+ CD 14+ macrophages, 3: S100A8 / 9+ MMP9+ immature neutrophils, 4: LTF+ CAMP+ immature neutrophils, 5: S100A8+ LTF+ immature neutrophils, 6: TNFAIP+ MME- mature neutrophils, 7: TNFAIP- MME- mature neutrophils, 8: Mki67+ DEFA3+ pre-neutrophils, and 9: HLA-DR+ CD16+ macrophages. Bottom panels represent cell contributions from healthy (left), NDMM (middle), and RRMM (right). B.) UMAP representation of CDllb+cells observed. In blue, the contribution of BM- derived cells (n = 59,861 cells). In red, the contribution of FL-derived cells (n = 45,331 cells). C.) Scaled bar graph representation of each cell type contribution (y - axis) from healthy donors and MM patients (x - axis) (n = 16). Color convention as per (1 A). Top panel, cell type distribution from BM cells. Bottom panel, cell type distribution from FL (one sample without cells). D.) Scaled normalized heatmap of top 10 transcripts associated with each cluster. Sample downsized to 5000 cells per cluster. Blue represents downregulated genes and red represents upregulated (Log2 fold change (L2FC)) genes in cell types shown at top.

[0014] Figures 2A-2F: Neutrophils associated with focal lesions acquire a pro-tumor phenotype. A.) RNA velocity of the re-analyzed neutrophil data set excluding macrophages. UMAP embeddings from 84,616 cells. Color convention as per figure (1 A). The visual representation of neutrophil maturation from healthy donor bone marrow (HDM) (left), newly diagnosed multiple myeloma (NDMM) (middle), and relapse refractory MM (RRMM) (right). Scaled bar graphs below healthy donor and patient specific UMAP represent scaled contribution of immature (grey) and mature (blue) neutrophils. B.) UMAP representation of neutrophils observed. In blue, the contribution of BM cells (n = 49,016 cells). In red, the contribution of FL cells (n = 35,600 cells). C.) Clusters scored against mature neutrophil signature (see Materials and Methods for details). High scores represent transcripts within clusters most like mature neutrophils. D.) Highly variable features associated with neutrophil maturity in single cell data. Data is organized by early to late neutrophil development. Blue indicates BM and red indicates FL cells. E.) Differentially expressed transcripts in neutrophils between BM (left - blue) and FL (right - red). Features were selected to emphasize proinflammatory or immunosuppressive phenotypes. F.) Paired gene ontogeny (GO) analysis of mature neutrophils from BM or FL. Colors indicate BM and FL and the height the GO differential.

[0015] Figures 3A-3F: Mature neutrophils representation at sites of osteolytic lesions. A.) The mature neutrophils were re-clustered and represented using highly variable features. UMAP is plotted in the second and third dimension for visual optimization. Bottom panels represent cell contributions from healthy (left), NDMM (middle), and RRMM (right). B.) UMAP representation of re-clustered mature neutrophils observed. In blue, the contribution of cells derived from bone marrow (BM) (n = 11,935 cells). In red, the contribution of cells from sites of focal lesions (FL) (n = 23,913 cells). C.) Dot Plot depicting the top 8 transcripts from each mature neutrophil cluster. The radius of each circle represents percent of cells expressing feature within cluster and color represents average log2 fold-change. D.) Schematic of CXCR2+ neutrophil developmental trajectories in MM patients. E.) FACS gating strategy for CDllb+neutrophil and CD88+ selection, then CXCR2+ and CXCL8+ selection then gating the 3 CXCR2+ neutrophil clusters by CD 10 and TNFAIP3 gates. F.) Confocal IF images of CXCR2+neutrophils with markers associated with subset features identified in scRNA-seq (right) and CXCR2- neutrophils with decreased marker expression (right).

[0016] Figures 4A-4C: Visualization of heterogeneity of CXCR2+neutrophil infiltration in MM BM and FL. Vectra Polaris staining was applied to FFPE sections from 12 patient samples (BM n = 12; paired FL n = 12). Representative Vectra images from 3 individual patient samples (Top rows in A, B and C, original magnification lOx) (Bottom rows in A, B and C) original magnification 30x). Differential marker and cell distribution of CD138+tumor cells and CD 16+ cells. A) The absence of CXCR2+cells in BM with < 1% malignant plasma cells (CD138+). (B) Accumulation of CXCR2+neutrophils along with an increase of CD 138+ cells in BM. (C) Extensive intratumoral infiltration of CXCR2+neutrophils with increased CD 138+ cells.

[0017] Figures 5A-5I: FL late-stage neutrophils are inflammatory and immunosuppressive and immature to mature gene signature ratios are survival. A.) The percentage of CXCR2+CD10+neutrophils in MM patient BM and FL (MMBM and MMFL respectively) and Healthy donor BM (HBM). CD138 CD3 CD56 CSF1R' CDllb+CD10+CXCR2+C5ARl+were characterized as mature neutrophils. CXCR2+CD10+neutrophils were accumulated in MMBM and MMFL samples. B.) Confocal microscopy of CXCR2' and CXCR2+neutrophils from MM microenvironment, CXCR2+neutrophils were mature with increased nuclear segmentation (lobulation) and CXCR2' neutrophils were immature cells with nuclear hypo-lobulation. CXCR2 was marked by FITC anti-CXCR2 (Green), while nucleus was stained with NucSpot 750 / 780 (red). C.) CDllb+C5AR1+CXCR2‘ (immature) and CDllb+C5AR1+CXCR2+(mature) neutrophils were isolated from MM BM and MM FL. Sorted neutrophils were cultured in complete media for 24, 48, and 72 hours. Cells were harvested and stained for Annexin V at each time point. CXCR2+cells had significantly shorter survival compared to CXCR2' cells. D.) CD138 CD3' CD56 CSFlR CDllb+CD10+CXCR2+C5ARl+neutrophils isolated from healthy donor BM (HDM) (n=l), MM BM (n=l) and MM FL (n=l). Sorted neutrophils were cultured in complete media for 24 hours and supernatants were collected (See Materials and Methods for details). Multiplex ELISA protein measurement was performed on collected supernatants. Several markers of inflammation were elevated in FL compared to BM and HDM. CXCL10 was elevated in HDM. E and F.) HDM, MM BM and MM FL neutrophils were cocultured (1 :4 ratio of neutrophils to T cells) with healthy CSFE stained T cells activated with CD28 / CD3 antibodies in presence of IL-2. On day 4, T cell activation was analyzed using CFSE dilution by flow cytometry. E). Representative flow cytometry histograms of T cell proliferation F). FL neutrophils showed significantly higher immunosuppressive capabilities on T cell proliferation compared to BM neutrophils from the same (paired) MM patient. G.) Kaplan-Meier curves of Overall Survival (OS) (left) and Progression Free Survival (PFS) (right) for MM patients from MMRF COMmPass dataset stratified by the “Immature neutrophil” signature. H.) OS (left) and PFS (right) curves for MM patients from the same dataset stratified by the “Mature neutrophil” signature. I.) T cell activation and exhaustion signatures were calculated the MMRF CoMMpass dataset and compared based on the ratio of “high immature neutrophils” and “low immature neutrophil” signatures. An exhausted T cell signature was significantly associated with the “high mature” signature. One-way ANOVA with Tukey multiple comparison tests were used to test significant differences between groups in A and C. One-way analysis of variance (ANOVA) with Kruskal-Wallis multiple comparisons test was used to compare means between groups in (F); statistics were derived from three patients per group performed in triplicates in D and F. In all experiments *P < 0.05 and **P < 0.01. Data is presented as mean ± SD.

[0018] Figures 6A-6C: CXCR2 blockade promotes MM control in murine MM models. Vkl2653 multiple myeloma (MM) cell lines were injected into recipients for different in vivo tumor models. See Materials and Methods for full details. For the newly diagnosed MM (NDMM) model (tumor cell injection without irradiation, n=40 from two experiments) or relapsed / refractory MM (RRMM) model (tumor cells injection, followed by total body lethal irradiation, 1,000 cGy, followed by syngeneic (autologous) stem cell transplantation, n=40 from two experiments). Progression of MM was confirmed by weekly serum protein electrophoresis (SPE) measurement of the monoclonal protein (M-spike) to albumin ratio in the NDMM model. In RRMM model, the mice were classified as MM-relapsed or MM- remission based on the M-spike to albumin ratio. Recipient BM was harvested and stained with appropriate antibodies. Results were analyzed via flow cytometry. A.) Gating strategy and quantification of frequency and number of target neutrophil clusters from the samples of healthy bone marrow (HBM) (no tumor injection), low tumor burden bone marrow (LTB), and high tumor burden bone marrow (HTB), the latter two based on SPE measurements. B.) Illustration of the NDMM model experimental design, quantitation of M-spike development, and survival curve. C.) Illustration of the RRMM model experimental design, quantitation of M-spike development, survival curve, and CD8+ T cell cytokine expression of IFN-y and TNF-a. Data represent mean ± SEM. *, P <0.05, **, P< 0.01, ***, P <0.001.

[0019] Figures 7A-7C: BM and FL sampling, CDllb+myeloid cell flow cytometry sorting and single cell RNA sequencing strategy for MM patients’ A.) CT Scan strategy for MM patient bone marrow (BM) and focal lesions (FL). Healthy donor BM (HDM) was sampled without CT scan guidance. Samples were processed for flow cytometry. CDllb+CD138-, CD56- and CD3- cells underwent droplet based single cell RNA sequencing. B.) Representative FACS gating strategy for single cells captured from FL and BM. C.) Table representing HD and MM patient study IDs, diagnosis and sites from where single cell libraries were made, n = 13 patients, Newly Diagnosed MM (NDMM) patients (n=7) and Relapsed / Refractory MM (RRMM) patients (n=6), HDM (n=3). All NDMM patients had paired BM and FL samples. One of the RRMM patients had BM only with an inadequate FL sample for analysis.

[0020] Figures 8A-8E: Trajectory analysis of neutrophils. A.) Cell scoring was calculated by concatenating a list of genes associated with the pre-neutrophil expression profile and subtracting 100 randomly sampled features per cluster to calculate expression enrichment of test versus control features. As explained in Tirosh et.al. 2018. B.) Pseudo-time reconstruction was performed with monocle3 using the pre-neutrophil signature to develop a directed minimum spanning tree with each branch representing trajectories of development. Color scale represents proximity in pseudo-time between early (purple) and late (yellow). C.) Tl, T2, and T3 signature from across our CD llb+neutrophil cells. D.) Violin plot demonstrating comparative expression of Tl, T2, and T3 signature compared to bone marrow (BM) and focal lesions (FL) within clusters identified with scRNA-seq. E.) Volcano plot of mature neutrophil differential expression analysis identifying genes significantly upregulated (right) and down regulated (left) in focal lesions compared to bone marrow (Log2 fold change (L2FC) > 1.15, p-value < 10e-50).

[0021] Figures 9A-9D: Mature neutrophil representation at sites of focal lesions. A-C.) Biological process Gene Ontogeny (GO) analysis of all transcripts Log2 fold change (L2FC) > 1.15 False Discovery Rate. Gene ratio calculated by number of transcripts identified that belong to that module. The size of circle is independently scaled for number of features represented in a GO term. Color indicates FDR adjusted p-value (q-value). All samples are scaled to their independent queries. D.) Scaled heatmap demonstrating top 20 differentially expressed features when comparing the three clusters of mature neutrophils sampled from patients. Color heat correlates to expression pattern of transcripts. Blue represents downregulated genes and red represents upregulated (L2FC) genes in cell types shown at top.

[0022] Figures 10A and 10B: A.) Gating strategy to sort late-stage neutrophil. CD138 CD3' CD56 CSFlR CDllb+CD10+CXCR2+C5ARl+neutrophils isolated from BM and FL of MM microenvironment for functional studies. B.) Hematoxylin and eosin (H&E) staining of CXCR2' and CXCR2+neutrophils from MM microenvironment, CXCR2+neutrophils were highly matured neutrophils while CXCR2' neutrophils were immature neutrophils evident by level of nuclear lobulation.

[0023] Figure 11: Multiplex ELISA actual data. To test the ability of late-stage neutrophils sorted from bone marrow (BM) or focal lesions (FL) in the MM microenvironment to release chemokines, cytokines and immunosuppressive molecules based on their gene expression signature. Sorted neutrophils were cultured in complete media for 24 hours and the supernatants in different groups were collected and multiplex ELISA assays were performed. The actual data for each test were presented.

[0024] DETAILED DESCRIPTION

[0025] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0026] Every numerical range given throughout this specification includes its upper and lower values, as well as every narrower numerical range that falls within it, as if such narrower numerical ranges were all expressly written herein.

[0027] As used in the specification and the appended claims, the singular forms “a” "and” and “the" include plural referents unless the context clearly dictates otherwise. Ranges may be expressed herein as from “about” one particular value, and / or to “about” another particular value. When such a range is expressed, another embodiment includes from the one particular value and / or to the other particular value. Similarly, when values are expressed as approximations, by the use of the antecedent “about” it will be understood that the particular value forms another embodiment. The term “about” in relation to a numerical value is optional and means for example + / -10%.

[0028] The disclosure relates in general to determining neutrophil profiles in individuals diagnosed with MM, and methods of treating individuals diagnosed with MM.

[0029] MM is the second most common hematologic malignancy, shares features with solid tumors and blood cancers. These include bone marrow (BM) infiltration and focal lesions (FL) manifesting as osteolytic lesions (OL) and plasmacytomas / extramedullary disease (EMD). OL are present in over 80% of patients at diagnosis and can be associated with more aggressive disease, leading to complications such as pathologic fractures and spinal cord compression. Both OL and EMD are linked to MM progression, yet the underlying mechanisms driving FL progression has previously remained poorly understood. The TME may play a key role in the disease’s heterogeneity.

[0030] Effective MM treatments depend on an intact immune system, but immune dysregulation in the TME is common. This includes alterations in cytokine release, signaling pathways, and the populations of T cells, natural killer (NK) cells, and macrophages. Malignant plasma cells further induce immunosuppression through the accumulation of regulatory T cells, myeloid-derived suppressor cells, dysfunctional NK cells, and tumor- associated macrophages, promoting angiogenesis, chemotherapy resistance, and tumor progression. While most immune cell phenotyping data has come from stored BM samples, there has previously been no information on neutrophil function in FL of MM patients due to their fragility during collection and storage. The present disclosure addresses this gap and shed lights on the complex immunosuppressive landscape of MM and informs more effective treatment approaches, as further described herein.

[0031] This disclosure employs single-cell transcriptomics and functional assays to explore the diversity of MM neutrophil populations. By sorting myeloid cells from fresh samples, we enhanced the viability of polymorphonuclear cells during isolation, enabling a more detailed analysis of myeloid cell heterogeneity. The disclosure reveals that the myeloid cell composition, particularly neutrophils, in FL differs from those in the MM BM and markedly from Healthy Donor BM (HDM). We observed a significant accumulation of mature neutrophils in MM FL. Functional assays demonstrated that these FL neutrophils are markedly immunosuppressive.

[0032] The described results as presented in the Examples below provide a detailed characterization of the transcriptional, compositional, and functional changes in the myeloid cell compartment of the MM BM and in particular FL. Blocking neutrophil activity in a relevant MM model, using a CXCR2 inhibitor significantly improved OS, showing that these cells serve as important biomarkers for risk assessment and provide targets for therapeutic interventions to enhance patient outcomes.

[0033] As discussed herein, the disclosure includes treating individuals with MM. In examples, the individual has been diagnosed with any type of MM. In examples, the MM is Hyperdiploid (HMM) or Non-hyperdiploid or hypodiploid. In examples, the individual has been diagnosed with Light Chain Myeloma, Non-secretory Myeloma, Solitary Plasmacytoma, Extramedullary Plasmacytoma, Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), Immunoglobulin D (IgD) Myeloma, or Immunoglobulin E (IgE) Myeloma. In examples, the individual treated according to a described method is only treated for MM. In examples, the individual has not been diagnosed with a cancer that is not MM when the individual is treated. In examples, the individual has been diagnosed with newly diagnosed NDMM) or relapsed / refractory MM (RRMM).

[0034] As discussed herein, the individual is treated with at least a CXCR2 inhibitor. In examples, the CXCR2 inhibitor is a small molecule drug. Representative examples of CXCR2 inhibitors include CXCR2-IN-1, SB 265601, AZD5069, SCH-527123 (Navaxarin), SB225002, GSK1325456 (Danirixin), Reparixin, and SX-682. The structures of each of these compounds are known in the art, as are alternative names for the compounds. In examples, an anti-CXCR2 inhibiting antibody or CXCR2 antigen inhibiting binding fragment thereof can be used. In examples, the only CXCR chemokine receptor inhibitor used in a described method is a CXCR2 inhibitor.

[0035] In examples, a CXCR2 inhibitor may be combined with another therapy, such as standard of care approaches for treating MM. In examples, a CXCR2 inhibitor may be used with chemotherapy, immunotherapy, or targeted therapy. In examples, the disclosure thus comprises administering to an individual in need thereof a CXCR2 inhibitor and at least one additional agent to provide an additive effect, or a greater than additive effect such as a synergistic result. In examples, combining a CXCR2 inhibitor with another agent as described herein produces a synergistic anti-MM effect. In an example, combining a described CXCR2 inhibitor with bortezomib and dexamethasone (BTZ / DEX) results in a synergistic anti-MM effect.

[0036] In examples, a therapeutically effective amount described agent(s) is administered to an individual who has been diagnosed with MM. In examples, a therapeutically effective amount is an amount that reduces one or more signs or symptoms of MM, and / or reduces the severity of the MM. A therapeutically effective amount may also inhibit or prevent MM relapse, MM progression, MM-related tumor formation, inhibit the growth of MM cells and / or an MM related tumor. A precise dosage of each agent can be selected by the individual physician in view of the patient to be treated. Dosage and administration can be adjusted to provide sufficient levels of the CXCR2 inhibitor and other described agents if also administered to maintain the desired effect. Additional factors that may be taken into account include the severity and type of the MM, the age, weight, and gender of the patient, desired duration of treatment, method of administration, time and frequency of administration, drug combination(s), reaction sensitivities, and / or tolerance / response to therapy. A composition of this disclosure, such as a pharmaceutical formulation, can contain only one, or more than CXCR2 inhibitor.

[0037] A described CXCR2 inhibitor and pharmaceutical compositions comprising it can be administered to an individual using any suitable route, examples of which include intravenous, intramuscular, subcutaneous, intraperitoneal, oral, intra-tumoral, topical, or inhalation routes. A compositions comprising a CXCR2 inhibitor may be introduced as a single administration or as multiple administrations or may be introduced in a continuous manner over a period of time. For example, the administration(s) can be a pre-specified number of administrations or daily, weekly, or monthly administrations, which may be continuous or intermittent, as may be therapeutically indicated. The same approach applies to the described standard of care agents, which may be administered concurrently or sequentially, using any therapeutically effective amount and route of delivery.

[0038] In examples, any result obtained by practice a method of this disclosure can be compared to a reference value, such as any suitable control. In examples, the reference value is a numerical threshold, any statistical value, a receiver operating characteristic (ROC), an area under a curve (AUC), or any value obtained from repeated measurements. In examples, a described method produced an improved MM result compared a reference value obtained using a CXCR2 inhibitor as a monotherapy, or a current standard of care MM treatment, such as BTZ / DEX treatment.

[0039] In examples, the disclosure includes selecting an MM patient for treatment with a CXCR2 inhibitor or a described combination of agents that includes the CXCR2 inhibitor. In examples, the individual is selected based on a neutrophil profile. In examples, the neutrophil profile is determined from a biological sample obtained from the individual. In examples, the biological sample is a sample of bone marrow or a focal lesion. In examples, the biological sample is obtained from an MM-related tumor. In examples, the neutrophil profile that indicates the individual is a candidate to receive a described treatment includes increased expression of any of CD10, TNFAIP-3, CXCL8, CXCR2, LCN2, TREM1, resistin. In examples, expression of at least CXCR2 is determined. Increased expression can be determined using any known technique, including but not limited to RNA sequencing, such as single cell RNA sequencing, and detecting proteins expressed by cells, such as by cell sorting based on differential expression of a described marker(s). In examples, increased expression means increased expression relative to expression of the same marker(s) in neutrophils obtained from an individual who does not have MM. Alternatively, the increased expression may be relative to expression of the same marker(s) in neutrophils that are not present in a tumor microenvironment in the MM patient. In examples, increased expression comprises at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 times the expression of the reference value. In examples, increased expression means at least 20-99% greater than the reference value, inclusive, and including all integers and ranges there between. In examples, a neutrophile profile comprises determining an amount and / or ratio of types of neutrophils. In examples, a neutrophil profile is determined from a gene signature.

[0040] In examples, the amount of mature neutrophil signal is determined, as further described below. In examples, the amount immature neutrophil signal is determined, as further described below. In examples, the disclosure permits use of the described markers to determine the development of neutrophils into a pathological mature neutrophil type.

[0041] The disclosure includes using the described marker measurements to determine the presence of neutrophil subtypes, as further described herein.

[0042] In examples, based at least in part on a determination of a described neutrophil profile, the individual is designated a candidate to receive a described MM therapy. In an example, the candidate is administered the described MM therapy.

[0043] The following Examples are intended to illustrate but not limit the disclosure.

[0044] Examples

[0045] High throughput scRNA-seq identifies distinct neutrophil subsets in MM focal lesions

[0046] To investigate the alterations in myeloid cell populations within the TME of MM patients, we collected fresh biopsy samples from patients with a clinical need for biopsy, as well as from BM from three healthy donors (HDM), after written informed consent. To capture the range of disease phenotypes and genotypes, parallel patient samples were obtained simultaneously from FL and pelvic BM without a FL detected by imaging. We analyzed approximately 120,237 myeloid cells with 10X Genomics Chromium V3 5’ chemistry (see methods). Cells were isolated by flow cytometry, sorted based on their side scatter / forward scatter (SSC / FSC) profiles and identified as CD3 CD56 CD I 38 CD I Ib cells. The samples were collected from the FL and paired BM of twelve MM patients. (A thirteenth patient provided a BM sample only) (Figure 7C). NK cell populations were excluded as we concentrated on myeloid cells, focusing on neutrophils. After quality control, we assessed 105,192 CD I Ib CD3 CD56 CD I 38 cells from the MM TME, including 59,861 cells from BM and 45,331 cells from FL, Samples were obtained newly diagnosed MM (NDMM, n = 6) and relapsed / refractory MM (RRMM, n = 7) patents. We obtained 10,086 cells from healthy donor HDM (n = 3).

[0047] We identified nine major myeloid cell subtypes (Figure 1 A). To further explore the heterogeneity of FL myeloid cells, we utilized uniform manifold approximation and projection (UMAP) to project cells into two dimensions and clustered them using approximate nearest neighbor (ANNOY) analysis, along with differential gene expression profiling. Cells were normalized by modeling RNA expression as regularized negative binomial distribution with the SCTransform. Dimensionality reduction was derived from using principal components from the SCTransform-normalized data. This revealed two distinct subsets of FL macrophages: S100A8+CD14+macrophages and HLA-DR+CD16+macrophages. Additionally, we identified seven neutrophil clusters within the FL, including TREM1+MME+mature neutrophils, S100A8 / 9+MMP9+immature neutrophils, LTF+CAMP+immature neutrophils, S100A8+LTF+immature neutrophils, TNFAIP-3+CXCL8+mature neutrophils, RETN+LCN2+mature neutrophils, and Mki67+DEFA3+pre-neutrophils (Figure lA and D).

[0048] When integrating these results with a previously published dataset of healthy neutrophils from BM tissues no new developmental clusters or trajectories were observed in MM-associated neutrophils, suggesting that neutrophils follow a single developmental trajectory in both healthy and MM-affected tissues (Figure 1 A, B, and D). However, MM (tumor)-associated neutrophils (TANs) acquired distinct transcriptional profiles within the BM, forming three unique clusters (RETN+LCN2+, TREM1+MME+, and TNFAIP-3+CXCL8+mature neutrophils) distinct from those in HDM.

[0049] Neutrophils Exhibit a Unique Transcriptional State in Multiple Myeloma Patients

[0050] In this dataset, TANs demonstrated an altered phenotype within myeloid cells in MM TME. The TREM1+MME+, TNFAIP-3+CXCL8+, and RETN+LCN2+mature neutrophil populations were enriched within FL when compared to the paired BM biopsies (Figure 2A and B). In the UMAP analysis neutrophils from the MM samples clustered by developmental stages, starting from (Mki67+DEFA3+pre-neutrophils) to (LTF+CAMP+immature neutrophils S100A8+LTF+immature neutrophils S100A8 / 9+MMP9+immature neutrophils) then to (RETN+LCN2+mature neutrophils — TREM1+MME+mature neutrophils — TNFAIP- 3+CXCL8+mature neutrophils) (Figure 2A). We therefore analyzed these populations. To explore potential links between neutrophil clusters in the MM BM and FL TME, we employed an RNA velocity approach. This technique estimates the rate of gene expression changes over time, preserving differentiation trajectories. The RNA velocity analysis revealed a progression of trajectory from Mki6+DEFA3+ pre-neutrophils to TNFAIP+MME- mature neutrophil. Immature neutrophils develop into two distinct mature subsets: TREM1+MME+and TNFAIP3+CXCL8+neutrophils (Figure 2A and B). This implies that these mature neutrophils arise from immature precursors in the BM. RETN+LCN+neutrophils have an intermediate maturation score between immature and mature neutrophils (Figure 2C). This suggests that they represent a transitional admixture of S1008 / 9+MMP9+immature neutrophils and TREM1+MME+mature neutrophils. Consistent with this, we observed velocity vectors originating from both immature and mature neutrophil subsets terminating in the RETN+LCN+cluster (Figure 2A). This analysis suggests that the RETN+LCN+and TREM1+MME+subsets remain capable of further differentiation into TNFAIP3+CXCL8+neutrophils supporting the transitional nature of these stages.

[0051] We then evaluated the relationship between the maturation and functional states of the mature neutrophil populations. Using a modified neutrophil maturation gene signature, we scored each neutrophil cluster in the dataset according to maturation. As expected, TREM1+MME+ neutrophils have a maturation neutrophil score while RETN+LCN+ neutrophils are intermediate, reflecting the mixed status between immature and mature states (cluster 6 - Figure 2C). TNFAIP3+CXCL8+ neutrophils, expressed the highest maturation score likely representing the terminally differentiated neutrophil population in MM.

[0052] To identify pre-neutrophils within our dataset we used an available expression signature. Our analysis captured the entire neutrophilic lineage, starting from Mki67+ pre- neutrophils and MMP9+ immature neutrophils to CXCR2+ mature neutrophils (Figure 2D and Figure 8 A). As an orthogonal approach to analyze developmental trajectories we used monocle3 to generate minimum spanning trees across the continuum of our neutrophil dataset. We used the pre-neutrophil signature to determine root node for the random walks (Figure 8B). Because we saw an overall increase in mature neutrophil representation in samples derived from FL, we analyzed differences in the mature neutrophils between HDM and FL. We found divergent expression profiles in the mature neutrophils Additionally, we compared gene expression between neutrophils in the paired MM FL and BM. Inflammatory mediators including S100A12, MMP8, and MMP9 were enriched in MM BM neutrophils, while immunosuppressive and protumor genes such as CXCL8, VEGFFA, and TP 11 were more prominent in FL neutrophils (Figure 2E). Biological process enrichment analysis revealed that mature FL neutrophils were specifically enriched in cytokine production, inflammatory response, and chemotaxis signaling pathways (Figure 2F). These data indicate that neutrophils in FL transform into inflammatory neutrophils with a heightened capacity to release cytokines.

[0053] We next compared the MM neutrophil subset findings to recently published scRNA- seq data from preclinical, solid tumor models. In a pancreatic cancer murine model, scRNA- seq identified three primary TAN populations — Tl, T2, and T3 — where T1 and T2 represent transitional states that eventually differentiate into T3, the terminally differentiated neutrophil population. The data show that the Tl signature is enriched in TREM1+MME+ and TNFAIP3+CXCL8+ mature neutrophils (Figure 8C and D), while the T2 signature is enriched in the immature subsets (Figure 8C and D). The T3 signature, representing terminally differentiated neutrophils, predominates in the TNFAIP3+CXCL8+ subset (Figure 8C and D). In distinction to the murine model, MM immature and mature neutrophil subsets were also identified in HDM. However, the TNFAIP3+CXCL8+ subset appears to be a unique population in MM patients. The RETN+LCN+ subset also is a distinct neutrophil population not reported in previous MM studies or in preclinical pancreatic cancer models. These results indicate that in the MM TME, neutrophils undergo additional differentiation steps, leading to the emergence of new subsets with distinct transcriptional signatures.

[0054] CD10 and TNFAIP3 Distinguish Three Distinct Subpopulations of Mature Neutrophils in Multiple Myeloma Patients

[0055] After demonstrating that distinct mature neutrophil subsets accumulate in the BM and especially the FL of MM patients, we evaluated these subsets for differential protein expression. This was performed because increased neutrophil RNA expression often precedes protein expression, particularly for neutrophil developmental genes. We re-clustered the mature neutrophil subset using the highly variable features within the dataset. Cells were then clustered and projected in low dimensional space using UMAP (Figure 3 A). The TREM1+MME+ and TNFAIP3+CXCL8+ neutrophil subsets were predominantly concentrated in FL, while the RETN+LCN2+ subset was found in the BM and FL of MM patients (Figure 3B). During differential expression analysis of the 3 mature neutrophil clusters we identified differences in both intra and extracellular proteins, suggesting distinct populations could be identified with specific intracellular and surface marker proteins. (Figure 3C and Figure 9D). Gene Ontogeny (GO) enrichment analysis revealed that the TREM+MME+ subset is enriched for the NF-KB pathway and active inflammatory responses, indicating this subset is in an activated state Figure 9A). In TNFAIP3+CXCL8+ neutrophils, the predominant pathways were metabolic reprogramming towards glycolysis and increased intrinsic apoptotic signaling, both of which are key features of long-lived tumor-infiltrating neutrophils (Figure 9B). The RETN+ LCN2+ subset is enriched in pathways related to cytoplasmic transition and RNA processing, signatures of transitioning neutrophils. These results indicate that mature neutrophils undergo a continuous maturation process within the TME consistent with a dynamic progression in development as seen in Figure 3D. We employed a multicolor flow cytometry approach to test this hypothesis. Live CD138-CDl lb+ cells from MM FL were screened for differentially expressed markers. These included C5AR1, a pan neutrophil marker, CXCR2, a mature neutrophil marker, and TNFAIP3 and MME (CD 10), which discriminate between neutrophil subsets. Flow cytometry confirmed the expression of CD 10 (MME) and TNFAIP3 in Cluster 1, while the RETN+LCN2+ subset was negative for both CD10 and TNFAIP3, consistent with the scRNA-seq data (Figure 3E). To orthogonally validate the scRNA-seq data, we used confocal microscopy to visualize all three neutrophil subsets based on specific markers. We sorted C5AR1+CXCR2+ and C5AR1+CXCR2- neutrophils from FL. We then stained immature and mature neutrophils based on specific differentially expressed markers identified in the scRNA-seq analysis (Figure 3D). These included CD10 (MME), TREM1, Resistin (RETN), Lipocalin-2 (LCN2), CXCL8, and TNFAIP3. We were able to detect the three distinct subsets of CXCR2+ mature neutrophils. As expected, the RETN+LCN2+ subset demonstrated a less mature cell type, evidenced by nuclear hyposegmentation (hypolobulated cells) (Figure 3F). In contrast, the TREM1+CD10+ and CXCL8+TNFAIP3+ neutrophils exhibited multi-lobed nuclei, a hallmark of mature neutrophils. Thus, the expression of CXCR2, CD 10, and TNFAIP3 allows for the phenotypic division of mature neutrophils in MM into three distinct populations, aligning with the subpopulations defined in the transcriptomic analyses.

[0056] Without intended to be constrained by any particular theory, it is considered that these data demonstrate for the first time that CXCR2+ mature neutrophils in MM patients include diverse subsets. This shows the heterogeneity of mature neutrophils in MM and the benefit of the presently employed both transcriptomic and protein-based approaches to characterize these populations.

[0057] Microscopic Imaging Reveals the Accumulation of CXCR2+ Neutrophils with Increasing Malignant Plasma Cells

[0058] To further analyze the accumulation and spatial distribution of CXCR2+mature neutrophils and their association with disease burden, we employed multiplex immunofluorescence (mIF) using Vectra Polaris to study paired BM and FL samples. A distinct feature of MM is the patchy accumulation of tumor, forming focal clusters (Figure 4).

[0059] HDM (with less than 1% CD138+ cells) showed no significant accumulation of CXCR2+neutrophils (Representative sample, Figure 4A). In MM patient BM, we observed infiltration of CXCR2+neutrophils, particularly near malignant plasma cells (Representative sample, Figure 4B). CXCR2+neutrophil accumulation was more pronounced in the FL, corroborating our scRNA seq data (Representative sample, Figure 4C.

[0060] Together, these results demonstrate that CXCR2+neutrophils accumulate within the MM TME, particularly in FL, and localize within malignant plasma cell clusters. This indicates that CXCR2+neutrophils contribute to MM disease progression both directly through localized production and indirectly, by suppressing anti-tumor immune responses.

[0061] FL Mature Neutrophils Exhibit Potent Immunosuppressive Activity Compared to BM Neutrophils in Multiple Myeloma scRNA-seq data and spatial imaging showed the accumulation of mature neutrophils in MM TME. We analyzed the CXCR2+neutrophil phenotype, cytokine production and immunomodulatory functions. We utilized multi-color flow cytometry to analyze the accumulation and function of CXCR2+neutrophils in MM patient BM and FL. Our scRNA- seq and Vectra imaging analysis revealed that CXCR2+TREM1+CD1O+neutrophils were the predominant mature neutrophil subset. Therefore, we stained BM and FL samples for key markers, including C5AR1, CSF1R, CDllb, CD10, CXCR2, and CD10 (Figure 10). Flow cytometry showed that when compared to HDM, CXCR2+neutrophils were significantly more abundant in the BM and FL of MM patients, with a higher accumulation in FL compared to paired BM samples (Figure 5A). To confirm the phenotypic differences between FL and BM neutrophils, we sorted CXCR2+mature neutrophils from both compartments in MM patients. Confocal microscopy confirmed that CXCR2+neutrophils were mature as evidenced by more nuclear lobulation (Figure 5B). In vitro culture of these cells showed that 70-80% were alive at 24 hours, but survival dropped to 30-40% after 72 hours. In contrast, CXCR2' neutrophils exhibited significantly higher survival in culture (Figure 5C).

[0062] We assessed the functional differences by measuring the ability of CXCR2+CD10+ neutrophils from MM patient BM and FL to release chemokines, cytokines, and immunosuppressive molecules based on their gene expression profiles (Figure 5D, Figure 11). Sorted neutrophils from HDM, MM patient BM and FL were cultured for 24 hours, and supernatants were analyzed via multiplex ELISA assays. FL mature neutrophils produced significantly higher levels of chemokines involved in neutrophil chemotaxis and migration, including the CXCL8 family members (CXCL1, CXCL2, and CXCL8), proinflammatory cytokines (CCL3 and CCL4), compared to MM BM neutrophils (Figure 5D). This supports the interpretation that FL neutrophils create a positive feedback loop through the CXCL8- CXCR2 axis, recruiting more CXCR2+ neutrophils to FL. FL mature neutrophils released more inflammatory and immunosuppressive cytokines, including IL-6, IL- la, IL- 10, IFN-a2, IL-ip, Flt-3L, and G-CSF, compared to their BM counterparts (Figure 5D). The expression of the anti -turn or cytokine IP- 10 (CXCL10) was significantly downregulated in MM BM and FL neutrophils and upregulated in HDM (Figure 5D). There were no significant differences in the production of GM-CSF, IL-12, CCL19, or CD40L between neutrophils from healthy BM, MM BM, and MM FL (Data not shown). CCL-20, EGF, Granzyme B, IFN-y, IL- 13, IL- 17, and VEGF were not detectable.

[0063] To continue analyzing the neutrophil immunosuppressive function on T cell proliferation following activation, we co-cultured freshly isolated neutrophils from HDM, MM BM, and MM FL with CD3 / CD28-activated allogeneic T cells with IL-2. FL neutrophils significantly suppressed both CD4+ and CD8+ T cell proliferation compared to MM BM and HDM neutrophils (Figure 5E, F). Mature neutrophils in FL are more immunosuppressive, creating a microenvironment suppressing anti-tumor immune responses and likely factor in MM progression.

[0064] We then examined two distinct gene signatures based on MM BM and FL neutrophils, categorized as "immature" and "mature" based on low and high gene expression. Patient data were divided into “immature neutrophil” high and low groups and “mature neutrophil” high and low groups using a higher tertile cutoff. Using neutrophil signature genes for immature neutrophils (Figure 5G and H). To explore the role of neutrophil gene expression in MM progression, we utilized the MMRF CoMMpass NDMM patient database (portal. gdc. cancer.gov / proj ects / MMRF-COMMPASS), to determine the impact of neutrophil gene expression and overall and progression free survival (OS and PFS). This database contains NDMM BM samples at diagnosis along with clinical outcomes. Our analysis found that a high “immature” neutrophil signature was significantly associated with improved OS and PFS (Figure 5G). A high “mature” neutrophil signature was associated with an inferior OS and no difference in PFS (Figure 5H). We examined the “mature” and “immature” signatures in by T cell activated and exhausted gene expression in the CoMMpass dataset. NDMM patients with a high “mature” neutrophil signature had a significantly increased exhausted T cell signature and not an activated one (Figure 51). These results indicate that the shift from a normal to a pathological mature neutrophil signature in MM, especially in FL significantly suppresses effective anti-tumor immune responses, promoting tumor progression in MM.

[0065] CXCR2 blockade synergistically increased the efficacy of bortezomib and dexamethasone (BTZ / DEX) in murine model of MM.

[0066] We have demonstrated three distinct subsets of CXCR2+mature TANs with immunosuppressive properties in the MM TME, and neutrophil gene signature associations with outcome. We then targeted CXCR2+neutrophils in vivo to suppress MM growth and to enhance standard-of-care (SOC) therapy in an animal MM model.

[0067] We used the VK12653 (VK*MYC) murine model of MM to study the effect of CXCR2 inhibition on the TME and malignant plasma cell growth. To confirm the MM patient findings, VK*MYC malignant plasma cells were injected into host mice. Using flow cytometry for CD121b (IL-1R2) and CXCR2, we confirmed that cells expressing both markers increased from controls (no tumor), to low and, to high tumor burden (Figure 6A). The VK*MYC cells were used in two settings: (1) NDMM) (Figure 6B) and (2) RRMM (Figure 6C). In both settings, treatment began when the plasma IgG monoclonal protein (M- spike) to albumin ratio exceeded 0.28. This is approximately equivalent to 10 g / L in a MM patient. CXCR2 inhibitor (CXCR2-IN, also known CXCR2-IN-1 and SB-332235) treatment as a single agent significantly reduced tumor burden and improved overall survival (OS) in the NDMM model when compared to PBS controls. A similar effect was seen with SOC bortezomib / dexamethasone (BTZ / DEX). Both effects were synergistically enhanced when CXCR2 inhibition was combined with (BTZ / DEX) (Figure 6B).

[0068] We analyzed the impact of the CXCR2-IN in the RRMM model. VK*MYC cells were injected prior to total body irradiation (the anti-VK*MYC treatment) followed by autologous (syngeneic) stem cell transplantation (auto-ASCT). The recipient plasma was monitored for disease progression and treatment was started. As in the NDMM model, the CXCR2-IN monotherapy significantly reduced tumor burden and improved OS. When combined with BTZ / DEX, the effects were more pronounced along with a significant increase in the percentage of IFN-y+and TNF-a+CD8+T cells, important anti-tumor cytokines.

[0069] These results demonstrate the role of CXCR2+neutrophils in suppressing anti-tumor immunity in MM. Blocking CXCR2 not only reduces tumor burden but also improves the efficacy of SOC therapy, demonstrating an aspect of this disclosure for treating MM by targeting CXCR2+neutrophils in MM. Discussion of Examples

[0070] Neutrophils are among the most abundant immune cells in the BM, constituting over 50% of leukocytes in the TME and up to 70% of the BM population. Within the BM, neutrophils typically exist in an immature state and undergo further maturation upon entering circulation and infiltrating inflammatory sites. This disclosure uses single-cell RNA sequencing (scRNA-seq) and functional assays on freshly prepared patient samples from FL and paired BM to investigate the transcriptomic changes in neutrophils of MM patients across different morphologic sites (BM and FL).

[0071] By analyzing BM and FL samples immediately after collection, we successfully recovered granulocytic myeloid populations that are often lost in frozen samples due to deterioration from freezing and thawing. Sorting myeloid cells prior to sequencing allowed us to uncover small, labile subpopulations that are challenging to detect when sequencing entire CD45+leukocyte populations. As such, the disclosure includes a method for preparing myeloid cells for analysis of neutrophil profiles, as described herein. Additionally, incorporating paired FL samples enabled a more comprehensive characterization of myeloid cell behavior. The disclosure reveals a continuum of neutrophil maturation from immature (PreNeu) to mature neutrophils within FL, with the majority of neutrophils being mature. This suggests that neutrophils may mature within the FL, likely influenced by the presence of tumor cells or other elements in the TME, such as mesenchymal stem cells, which may drive neutrophils to adopt a pro-angiogenic and pro-tumor phenotype. It is possible that neutrophils are recruited from circulation to the FL by tumor cells through the CXCL8-CXCR2 pathway.

[0072] The described results also showed that FL neutrophils express and release substantial amounts of CXCL8 (IL-8), a chemokine that recruits CXCR2-positive neutrophils to inflammatory sites. This creates a positive feedback loop, leading to neutrophil accumulation and promoting an inflammatory TME. Similarly, the data from MM patients indicate that mature neutrophils undergo extensive TME reprogramming, resulting in terminal differentiation and acquiring pro-inflammatory and immunosuppressive functions.

[0073] Previously, CXCR2+neutrophils were considered a homogeneous population typically found in circulation or peripheral tissues. However, the present disclosure reveals what are considered to be at least two new findings. Without intending to be constrained by any particular interpretation, it is first considered that CXCR2+neutrophils are not homogeneous but include three distinct subsets, each at different maturation stages. Second, we the disclosure reveals significant accumulation of CXCR2+neutrophils in the MM TME, particularly in FL. Spatial analysis showed that neutrophils are in close contact with tumor cells, suggesting direct interactions between the two. The disclosure reveals a subset of neutrophils expressing RETN+LCN+. These cells have a low maturation score but still express CXCR2, indicating an incomplete maturation process, which is commonly seen in infectious diseases. This indicates that MM not only alters the TME but also significantly impacts granulopoiesis.

[0074] We also compared the behavior and maturation pathways of neutrophils in FL and BM, revealing distinct genetic signatures and functional properties between the two environments. Despite these differences, the maturation trajectory of neutrophils within FL remains consistent, implying that alterations in neutrophil progenitors likely occur within the TME itself rather than outside it. This suggests that the TME plays a central role in driving the development of pro-tumor neutrophil populations. The results indicate that recruited neutrophils can adapt to the TME, ultimately fostering a pro-tumoral state. This adaptation is believed to form a feedback loop that sustains the production and differentiation of pro- angiogenic, immunosuppressive neutrophils, thus promoting tumor growth. Additionally, tumor location appears to induce uniform neutrophil behavior locally to support tissue homeostasis, which malignant plasma cells exploit to sustain abnormal tumor growth.

[0075] Our bioinformatic analysis of myeloid populations in the MM TME showed a significant enrichment of mature neutrophils with immunosuppressive and pro-inflammatory signatures. This phenotype in FL neutrophils was independent of tumor location (osteolytic versus soft tissue lesions), tumor burden, tumor stage, FL number, or MM genetic abnormalities, and it correlated with patient outcomes in the MMRF COMPASS dataset. Two pathways, "Response to cytokine" and "Response to wounding," were highly activated in FL neutrophils. Neutrophils at wound sites typically exhibit a pro-inflammatory phenotype, releasing growth factors and pro-angiogenic factors. This indicates that the expansion of mature neutrophils with pro-inflammatory and pro-angiogenic transcriptomes might either be a response to, or a cause of, FL bone destruction.

[0076] The disclosure demonstrates that blocking mature neutrophils via CXCR2 inhibition significantly enhances the response to chemotherapy by boosting immune activity. Although immune checkpoint blockade, either alone or in combination with chemotherapy, has shown limited success in MM, the present data indicate that enhancing immune responses by targeting the TME could be an effective therapeutic strategy. This approach is supported by recent studies demonstrating that targeting T cells through anti-TIGIT alone or in combination with lenalidomide significantly improves tumor burden and OS, reinforcing the potential of targeting immune cells or the TME in MM treatment.

[0077] Materials and methods

[0078] Mice

[0079] C57BL / 6 wild-type (WT) mice were obtained from the Jackson Laboratory. The mice were bred and housed at Roswell Park Comprehensive Cancer Center and used for experiments between the ages of 8 and 20 weeks. All experimental procedures were conducted with the approval of the Roswell Park Comprehensive Cancer Center Animal Ethics Committee.

[0080] Preclinical MM models

[0081] The Vk*MYC myeloma clone, Vkl2653, derived from VkMYC transgenic mice, was expanded in C57BL / 6 mice. Two weeks before undergoing stem cell transplantation (SCT), recipient mice received an intravenous injection of Vkl2653 cells (1 x 106CD I 38 CD I 9 cells), establishing multiple myeloma (MM). The transplantation procedures were performed using known approaches and illustrated in Figure 6C and D. Serum samples were collected from these MM-bearing mice every two weeks, and M-band levels were measured using the Helena QuickGel manual electrophoresis system. In this process, Helena QuickGel was stained with amido black, scanned via an onboard densitometer, and the y and albumin fractions were quantified to calculate the y / albumin ratio (G / A), known as the M-band. Mice were monitored daily for up to 120 days post-SCT, and those developing hindlimb paralysis or clinical scores >638were euthanized. In certain experiments, mice were treated with anti- CXCR2 antibodies or corresponding appropriate controls.

[0082] Patient and healthy samples

[0083] A total of 13 patients underwent biopsy: 10 had osteolytic lesions (OL) and 2 had extramedullary disease. These are grouped together as FL because the genetic analysis was the same for both populations. One OL had no cells recovered. BM from healthy donors and BM or FL samples from MM patients were freshly collected using either standard blind aspiration (from healthy volunteers) or CT guided biopsy and aspiration (from patients) at the Roswell Park Comprehensive Cancer Center. The study was approved by the Roswell Park Institutional Review Board (protocol # I 66418). Informed consent was obtained from all patients and healthy volunteers before sampling. Ammonium-chloride-potassium (ACK) lysing buffer was used to exclude red blood cells (RBCs). CDllb+CD3 CD56 CD138‘ myeloid cells were freshly isolated using a SONY flow sorter. Selected cells were immediately used for scRNA-seq.

[0084] Imaging guided biopsy

[0085] The CT scan-based biopsy was performed using established techniques. Briefly, patients underwent an imaging-guided aspirates of FL after written informed consent was signed. During the same procedure a diagnostic BM aspirate from the iliac crest was obtained. Patients with a history of another systemic malignancy were excluded. scRNA sequencing using the lOx Genomics platform

[0086] Fresh myeloid cells were sorted in complete RPMI1640 media supplemented with 100 Uml-1 of penicillin-streptomycin (Gibco), 10% fetal calf serum (Gibco) and 2 mM of 1- glutamine (Gibco). Single cell libraries were generated using the 10X Genomics platform. Cell suspensions were first assessed with Trypan Blue using a Countess FL automated cell counter (ThermoFisher), to determine concentration, viability, and the absence of clumps and debris that could interfere with single cell capture. Cells are loaded into the Chromium Controller (10X Genomics) where they are partitioned into nanoliter-scale Gel Beads-in- emulsion with a single barcode per cell. Reverse transcription is performed, and the resulting cDNA is amplified. The full-length amplified cDNA is used to generate gene expression libraries by enzymatic fragmentation, end-repair, a-tailing, adapter ligation, and PCR to add Illumina compatible sequencing adapters. The resulting libraries are evaluated on DI 000 screentape using a TapeStation 4200 (Agilent Technologies), and quantitated using Kapa Biosystems qPCR quantitation kit for Illumina. They are then pooled, denatured, and diluted to 300pM with 1% PhiX control library added. The resulting pool is then loaded into the appropriate NovaSeq Reagent cartridge and sequenced on a NovaSeq6000 following the manufacturer’s recommended protocol (Illumina Inc.). A minimum of 20,000 reads per cell were generated and data was analyzed using 10X cell ranger software.

[0087] Preprocessing of scRNA-seq data

[0088] Samples were demultiplexed and aligned to the hg38 genome using the cellranger pipeline (version 5.1.0). Raw counts were generated using cellranger count. Downstream analysis was performed using the Seurat R package (v5.0.3). Genes that were not found expressed in a minimum of 5 cells and cells with less than 200 mapped transcripts were excluded from downstream analysis. Cells with higher than 5% mitochondrial transcripts relative to all transcripts were also excluded from downstream analysis. Dimensionality reduction was performed using principal component analysis (PCA) and Uniform Manifold Approximation & Projection (UMAP) as implemented in Seurat functions RunPCA, FindNeighbors, and RunUMAP with parameters dims = 1 : 15 and reduction = ‘pea. Clustering analysis was performed using approximate nearest neighbor algorithm (ANNOY) using Seurat function FindClusters with resolution = 0.25.

[0089] Differential Expression

[0090] Differentially expressed genes were identified using Find AllMarkers and FindMarker functions from the Seurat R package with default parameters. Markers of each cell population were determined by setting an appropriate contrast with respect to other cell population. For these analyses log2 fold change cutoff > 1.2 and adjusted p-value < le-3 were used to determine significance.

[0091] RNA Velocity Analysis

[0092] RNA velocity was performed using the velocyto pipeline (vO.17.17). Initially, BAM files generated by were processed into .loom files using velocyto. py to obtain annotated spliced and unspliced matrices. Neutrophils were down sampled in interest in conservation of computational power while conserving generalizability within the data (downsample = 2500 cells / cluster). For downstream analysis, spliced and unspliced counts were imported into the velocyto. R package (v0.6) for modeling the RNA velocity of neutrophils across maturation states. Cell distances were calculated using principal components using as.dist(l - armaCor(t(neuts@reductions$pca@cell. embeddings) function native to velocyto. R. RNA velocity was calculated using gene.relative.velocity.estimates function with deltaT = 1, kCells = 200, and fit.quantile = 0,2 on 8 cores of a Rocky Linux 8.9 intel CPU. Embeddings were visualized using the show.velocity.on. embedding. cor function with n centroids = 100, scale = “sqrt”. Detailed analysis can be seen on github.com / jriv724 / CDll-b scRNAseq.

[0093] Pseudo-time single cell trajectory

[0094] Pseudo-time analysis was performed using the R package Monocle3 (vl.3.7) (https: / / doi.org / 10.1038 / s41586-019-0969-x). Single cell trajectories were generated using the order cells (reduction = UMAP) function with root cells = NULL instead substituting pre-neutrophil expression signature for heuristic classification of pre-neutrophils in our dataset as point of origin for trajectories. Multi-color immunofluorescence (mIF) Vectra Polaris imaging

[0095] Formalin-fixed, paraffin-embedded (FFPE) samples were sectioned at a thickness of 4 pm and mounted on charged slides. The slides were dried at 65°C for a minimum of 2 hours before being processed. For staining, the slides were placed into a BOND RXm Research Stainer (Leica Biosystems) and deparaffmized using the BOND Dewax solution (AR9222, Leica Biosystems). The multispectral immunofluorescence (mIF) staining protocol, developed by Akoya Biosciences, was applied using Opal reagents. The staining procedure involved sequential applications of various solutions for each biomarker, including epitope retrieval solutions ER1 (citrate buffer, pH 6, AR996, Leica Biosystems) or ER2 (Tris-EDTA buffer, pH 9, AR9640, Leica Biosystems), blocking buffer (Akoya Biosciences), a primary antibody, PowerVision Poly-HRP (Leica Biosystems) secondary antibody, and Opal fluorophore (Akoya Biosciences). After staining, Spectral DAPI (Akoya Biosciences) was manually applied, and slides were mounted with ProLong Diamond Antifade Mountant (ThermoFisher Scientific) under glass coverslips for preservation.

[0096] The mIF panel included the following biomarkers: Ab. The slides were imaged using the PhenoImager™ HT (AKOYA Biosciences). Further analysis was conducted using inForm® Software v2.6.0 (AKOYA Biosciences). Initially, whole slides were scanned in an unmixed view, after which representative regions of interest (ROIs) were selected for higher- resolution imaging, guided by a pathologist. These ROIs were re-scanned for full spectral unmixing. A subset of these unmixed ROIs was used to train tissue and cell segmentation models. Subsequently, a machine learning algorithm was developed, where positive and negative cells were identified for each marker. This algorithm was then batch-applied across additional ROIs selected for further analysis. Phenotype counts were extracted from the resulting data tables using the phenoptrReports plugin for RStudio.

[0097] Flowcytometry analysis

[0098] Antihuman antibodies against CD138 (clone: MH 5), CD56 (clone: HCD56), CD3 (clone: HIT3a), CDllb (clone: ICRF44), CXCR2 (clone: 5E8 / CXCR2), CD10 (clone: HITlOa), CSF1R (clone: 9-4D2-1E4), and C5AR1 (clone: S5 / 1) were purchased from BioLegend. Antibodies were used for fluorescence-activated cell sorting (FACS) analyses. The LIVE / DEAD Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific) was used for excluding dead cells. Data from the stained samples was acquired using a SONY sorter. The results were analyzed using FlowJo V 10.8.0. Neutrophil culture and suppression assay

[0099] Late-stage neutrophils (Live CD138 CD3 CD56 CSFlR CDllb+CD10- / dimCXCR2+C5ARl+) were sorted from the FL and peer BM of MM patients. To examine cytokine production capacity of neutrophils, 5>< 105 / ml sorted cells were cultured in 96-well, round-bottom plates (Coming), with 100 pl of RPMI 1640 medium (Gibco) supplemented with 100Uml-l of penicillin-streptomycin (Gibco), 10% fetal calf serum (Gibco) and 2 mM of 1-glutamine (Gibco) for 24 hrs. at 37 °C and 5% CO2. Supernatants were collected, and cytokine levels were measured using the Human XL Cytokine Luminex® Performance Panel Premixed Kit (38-Plex) (R&D Systems) per vendor’s instructions. Fluorescent bead reading was performed in 96-well plates with 80 pl Sheath Fluid per well on a Luminex 200 bead array analyzer (Luminex Corporation). Supernatants were diluted 1 :2 before multiplex assay. Fluorescent intensity was calibrated with a standard curve of 38 cytokine standards. Assay performance was validated using internal quality controls provided with the kit.

[0100] The immunosuppressive capacity of sorted mature neutrophils was examined by coculture of neutrophils with stimulated allogenic T cells in 96-well, round-bottom plates (Corning). Plates were coated with 5 pg / ml of anti-human CD3 antibody (clone OKT3, BioLegend), overnight at 4 °C. Sorted neutrophils from MM patients and healthy donors were co-cultured with CFSE labeled T cells in a 1 :4 ratio (Neut:T = 1.25>< 104:5* 104) in presence of 5 pg / ml soluble anti-human CD28 antibody (clone CD28.2, BioLegend) and 100 ng of recombinant human IL-2 (PeproTech) for 72 hrs. After 72 hrs., cells were collected and stained with PE / Cyanine7 anti-human CD4 Antibody (clone OKT4; BioLegend); Brilliant Violet 421™ anti-human CD8a Antibody (RPA-T8; BioLegend). The LIVE / DEAD™ Fixable Aqua Dead Cell Stain Kit (Thermo Fisher Scientific) was used to gate out the dead cells. Samples were run by BD LSRFortessa™ cell analyzer (BD Biosciences) and T cell proliferation was determined by calculating proliferation index using FlowJo VIO software.

[0101] Multiple Myeloma Data Analysis

[0102] Gene expression and clinical data of Multiple Myeloma Research Foundation (MMRF) CoMMpass dataset (IA17) were downloaded through MMRF website (https: / / portal.gdc.cancer.gov / projects / MMRF-COMMPASS). In this cohort, The BM samples from the NDMM patients underwent bulk whole exome sequencing. The BM populations were not analyzed separately and contain TME populations in addition to malignant plasma cells. We selected and analyzed 767 total cases from 903 MM BM cases. Our analysis specifically focused on the results of initial biopsies only. These 767 patients had undergone a diagnostic BM biopsy. The patient data were divided into “immature neutrophil” high and low groups and “mature neutrophil” high and low groups using a higher tertile cutoff. Using neutrophil signature genes for immature neutrophils ("TFF3", "PLCG2", "CRISP3", "LTF", "LCN2", "RPL27", "RPL35A", "CAMP", "RPS14", "RPS8", "CD24", "ANXA1", "RAB27A", "ITGB2", "ANXA3“) and mature neutrophils (“IL18RAP”, “IL1RAP”, “LUCAT1”, “AQP9”, “CNTNAP3”, “AC092746.1”, “ALPL”, “DAAM2”, “IL1R1”, “IL18R1”, “CXCR2”, “SULF2”, “NAMPT”, “NEAT1”, “PHOSPHO1”, “ZNF608”), Gene Set Enrichment Analysis (GSEA) was carried out, comparing transcriptomic profiles between immature and mature high and low groups through software provided by the Broad Institute (www.gsea-msigdb.org / gsea / index.jsp). Activated T cell signature44(“0DC1”, “WARSI”, “PYCR1”, “TNF”, “NME1”, “LGALS3”, “GZMB”, “IFNG”, “XCL1”, “XCL2”) genes and exhausted T cell signature (“CD8A”, “GZMK”, “TIGIT”, “EOMES”, “CD 160”) were compared between mature neutrophil high and low signature. Analyses were carried out using R software together with Bioconductor.

[0103] Statistical analysis of in vivo and in vitro studies

[0104] An unpaired Student’s t-test was used to compare two independent groups. One-way analysis of variance (ANOVA) and Kruskal Wallis comparison test were used when three or more independent groups were compared. P < 0.05 was considered statistically significant.

[0105] Statistics and reproducibility

[0106] No statistical method was used to predetermine sample size. In initial analysis, bioinformaticians were blinded to the study of human sequencing data. Samples with insufficient numbers of cells or library complexity were excluded from the analyses. All the statistical analysis were done using GraphPad Prism 6 (GraphPad) and Excel software.

Claims

What is claimed is:

1. A method for treating an individual diagnosed with multiple myeloma (MM), comprising administering to the individual a therapeutically effective amount of a C-X-C motif chemokine receptor 2 (CXCR2) inhibitor to thereby inhibit progression of the MM.

2. The method of claim 1, further comprising administering to the individual a chemotherapy, immunotherapy, or targeted therapy.

3. The method of claim 1, further comprising administering to the individual cyclophosphamide, dexamethasone, bortezomib or a combination thereof.

4. The method of claim 3, wherein a combination of bortezomib and dexamethasone (BTZ / DEX) is administered to the individual.

5. The method of claim 4, wherein administering the inhibitor CXCR2 and the BTZ / DEX promotes a synergistic anti-MM progression effect.

6. The method of any one of claims 1-5, wherein the CXCR2 inhibitor is selected from the group consisting of CXCR2-IN-1, SB 265601, AZD5069, SCH-527123 (Navaxarin), SB225002, GSK1325456 (Danirixin), Reparixin, SX-682, or a combination thereof.

7. The method of any one of claims 1-5, wherein neutrophils from the individual exhibit higher expression of at least one marker selected from the group consisting of CD 10, TNFAIP-3, CXCL8, CXCR2, LCN2, TREM1, resistin, or a combination thereof, relative to expression of said marker by neutrophils from an individual who does not have MM.

8. The method of claim 6, wherein neutrophils from the individual exhibit higher expression the CXCR2, relative to CXCR2 expression by neutrophils obtained from an individual who does not have MM.

9. The method claim 7, wherein the neutrophils are present in focal lesions or bone marrow.

10. The method claim 8, wherein the neutrophils are present in focal lesions or bone marrow.

11. The method of claim 9, wherein the neutrophils are present in the focal lesions.

12. The method of claim 10, wherein the neutrophils are present in the focal lesions.

13. A method comprising analyzing a biological sample from an individual who has been diagnosed with MM, said biological sample comprising neutrophils, wherein the analyzing comprises testing the neutrophils for increased expression of at least one marker selected from the group consisting of CD10, TNFAIP-3, CXCL8, CXCR2, LCN2, TREM1, resistin, or a combination thereof, relative to expression of said at least one marker by neutrophils from an individual who does not have MM, and wherein the increased expression indicates the individual is a candidate for MM therapy by treatment with a CXCR2 inhibitor.

14. The method of claim 13, wherein the biological sample comprises a sample of bone marrow or a focal lesion.

15. The method of claim 14, wherein the biological sample comprises the sample of a focal lesion.

16. The method of any one of claims 13-14, wherein expression of the CXCR2 is increased.

17. The method of claim 16, further comprising administering to the individual the CXCR2 inhibitor, optionally in combination with chemotherapy, immunotherapy, or targeted therapy.

18. The method of claim 17, wherein the CXCR2 inhibitor is selected from the group consisting of CXCR2-IN-1, SB 265601, AZD5069, SCH-527123 (Navaxarin), SB225002, GSK1325456 (Danirixin), Reparixin, SX-682, or a combination thereof.

19. The method of claim 18, further comprising administering to the individual cyclophosphamide, dexamethasone, bortezomib or a combination thereof.

20. The method of claim 19, wherein a combination of bortezomib and dexamethasone (BTZ / DEX) is administered to the individual.

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