Composition for cancer prevention, comprising statin

Abstract

The present invention relates to a composition for cancer prevention, comprising a statin-based drug as an active ingredient, and disclosed is that a statin drug known for hyperlipidemia treatment may effectively prevent cancer progression. More specifically, a novel use of rosuvastatin is provided so as to enable providing a composition for multiple myeloma (MM) prevention for inhibiting progression from monoclonal gammopathy of undetermined significance (MGUS) to MM. In addition, the composition may exhibit a greater tumor growth inhibition effect when bortezomib and rosuvastatin are co-administered compared to when each medicine is administered alone.

Description

Cancer prevention composition containing statins

[0001] The present invention relates to a cancer prevention composition comprising a statin as an active ingredient. More specifically, the present invention relates to a cancer prevention composition comprising a statin as an active ingredient, which is a drug widely used in the treatment of dyslipidemia and hyperlipidemia and exhibits excellent safety even with long-term administration.

[0002] Changes in the immune system and systemic inflammation play a significant role in the progression of malignant cancer, and regulating them is known as a mechanism of action for treating malignant cancer (J Clin Oncol. 2016 Nov 20;34(33):4008-4014). In addition, some drugs used for the treatment and prevention of chronic metabolic diseases such as diabetes, hyperlipidemia, and ischemia are known to improve systemic inflammation. Consequently, research is being conducted on whether drugs used to treat the aforementioned diseases can exert anticancer effects or enhance the effects of existing anticancer drugs. Among drugs targeting chronic metabolic diseases that have shown promising effects in anticancer treatment, acetylsalicylic acid, angiotensin converting enzyme inhibitors (ACEIs) / angiotensin II receptor blockers (ARBs), metformin, and statins are included.

[0003] Multiple myeloma (MM) is a disease in which plasma cells, which produce immune antibodies in the body, transform into cancer cells and proliferate primarily in the bone marrow. Cancer cells in multiple myeloma secrete abnormal monoclonal proteins (protein M) instead of healthy antibodies. In the early stages of the disease, only a small amount of abnormal protein M is secreted, and if there are no symptoms, it is called Monoclonal Gammopathy of Undetermined Significance (MGUS). If the number of malignant plasma cells or protein M is elevated but there are no symptoms of multiple myeloma, it is classified as Smoldering Multiple Myeloma. Approximately 1% of cases progress from MGUS to multiple myeloma each year.

[0004] Among blood cancers occurring in adults, the incidence of multiple myeloma is increasing most rapidly in conjunction with the aging population. While multiple myeloma is a type of blood cancer that primarily originates in the bone marrow, it can occasionally manifest as a plasmacytoma—a solid tumor—in the bones surrounding the bone marrow or in various other organs. Invasion of the bones is particularly common, and in such cases, it can cause spinal pain, compression fractures, and neurological symptoms such as paralysis of the lower limbs. Although symptoms vary among patients, the most common representative symptoms include bone lesions, anemia, bone pain, elevated kidney enzyme levels, and hypercalcemia. Anemia is caused by the proliferation of plasma cells, which are the cause of multiple myeloma, within the bone marrow, and this can lead to symptoms such as fatigue, dizziness, and shortness of breath.

[0005] The treatment of multiple myeloma relies on chemotherapy, radiation therapy, and hematopoietic stem cell transplantation. Alkylating agents are the first-line chemotherapy agents for multiple myeloma treatment, and while therapy based on melphalan and prednisone regimens has been attempted, immunomodulators such as thalidomide and lenalidomide, as well as proteosome inhibitors like bortezomib, are widely used in clinical practice. However, these drugs destroy normal hematopoietic stem cells or inhibit their function, causing serious side effects such as peripheral neuropathy, embolism / thrombosis, and the development of heterogeneous primary tumors, in addition to pancytopenia. Furthermore, multiple myeloma cannot be cured with monotherapy, such as combination therapies or antibody treatments with new mechanisms of action, and mortality rates are increasing significantly along with rising drug resistance.

[0006] Therefore, active multiple myeloma, which is known to progress from the prodromal disease MGUS to latent multiple myeloma, urgently needs treatment techniques that can inhibit the progression from the prodromal disease to active multiple myeloma.

[0007] In addition, the biological validity of drugs targeting metabolic chronic diseases that have shown promising effects in anticancer therapy (acetylsalicylic acid, ACEI, ARB, metformin, statins, etc.) preventing the progression of multiple myeloma is supported by evidence that systemic inflammation may contribute to the malignant transformation of plasma cell disorders. However, the specific association between these commonly prescribed drugs and the progression from MGUS to MM has not been systematically evaluated.

[0008] Accordingly, the present invention discloses that a statin drug known for treating hyperlipidemia can effectively prevent cancer progression, and more specifically, discloses that rosuvastatin is effective in inhibiting the progression of multiple myeloma.

[0009] The objective of the present invention is to provide a composition for the prevention of multiple myeloma that inhibits the progression from monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) by providing a new use for rosuvastatin.

[0010] To solve the above objective, the present invention provides a pharmaceutical composition for cancer prevention comprising a statin as an active ingredient. More specifically, the statin is rosuvastatin, and the cancer is a blood cancer. More specifically, the blood cancer is multiple myeloma.

[0011] In one embodiment of the present invention, a pharmaceutical composition for inhibiting progression to multiple myeloma in monoclonal gamma of unknown semantic significance (MGUS) is provided, comprising a statin as an active ingredient. More specifically, the statin is rosuvastatin.

[0012] In one embodiment of the present invention, a pharmaceutical composition for inhibiting progression from smoldering multiple myeloma (SMM) to multiple myeloma is provided, comprising a statin as an active ingredient. More specifically, the statin is rosuvastatin.

[0013] In one embodiment of the present invention, a health functional food composition for cancer prevention comprising a statin as an active ingredient is provided. More specifically, the statin is rosuvastatin, and the cancer is multiple myeloma.

[0014] In one embodiment of the present invention, a health functional food composition for inhibiting progression from monoclonal gamma of unknown semantic significance (MGUS) to multiple myeloma is provided, comprising a statin as an active ingredient. More specifically, the statin is rosuvastatin.

[0015] In one embodiment of the present invention, a health functional food composition for inhibiting progression from smoldering multiple myeloma (SMM) to multiple myeloma is provided, comprising a statin as an active ingredient. More specifically, the statin is rosuvastatin. The present invention provides a method for preventing cancer comprising the step of administering a pharmaceutically effective amount of statin to an individual. In one embodiment of the present invention, the statin is rosuvastatin, and in another embodiment of the present invention, the individual is a patient, and the patient is a patient suffering from a metabolic disease and / or a patient diagnosed with monoclonal gammopathy of unknown significance (MGUS) and / or a patient diagnosed with smoldering multiple myeloma (SMM), and in yet another embodiment of the present invention, the cancer is multiple myeloma.

[0016] In addition, the present invention provides a composition further comprising a pharmaceutically acceptable salt of the rosuvastatin.

[0017] In addition, the above administration may be oral administration, and the present invention may provide a composition that is a formulation for oral administration. The formulation may be one or more forms selected from the group consisting of tablets, pills, powders, granules, capsules, suspensions, liquids, emulsions, and syrups.

[0018] In one embodiment of the present invention, the composition is provided, wherein the administration is characterized by long-term administration. The long-term administration may be 90 days or more. The present invention provides a pharmaceutical composition for the prevention of multiple myeloma in individuals with metabolic disease comprising rosuvastatin.

[0019] The present invention provides a pharmaceutical composition or a health functional food composition for inhibiting progression to multiple myeloma in monoclonal gamma of unknown significance (MGUS) in individuals with metabolic diseases, comprising rosuvastatin.

[0020] The present invention provides a pharmaceutical composition or a health functional food composition comprising rosuvastatin for inhibiting progression from smoldering multiple myeloma (SMM) to multiple myeloma in individuals with metabolic diseases.

[0021] The present invention provides a pharmaceutical composition for co-administration comprising a statin as an active ingredient. More specifically, the statin is rosuvastatin, and the statin may be co-administered with bortezomib.

[0022] In one embodiment of the present invention, a pharmaceutical composition for co-administration is provided for inhibiting progression from monoclonal gamma of unknown significance (MGUS) to multiple myeloma, comprising a statin as an active ingredient. More specifically, the statin may be co-administered with bortezomib.

[0023] In one embodiment of the present invention, a pharmaceutical composition for co-administration is provided for inhibiting progression from smoldering multiple myeloma (SMM) to multiple myeloma, comprising a statin as an active ingredient. More specifically, the statin may be co-administered with bortezomib.

[0024] In one embodiment of the present invention, a pharmaceutical composition for co-administration for the prevention of multiple myeloma in individuals with metabolic disease is provided, comprising rosuvastatin. More specifically, the rosuvastatin may be co-administered with bortezomib.

[0025] In one embodiment of the present invention, a pharmaceutical composition for co-administration is provided for inhibiting progression to multiple myeloma in individuals with metabolic disease, comprising rosuvastatin, in cases of monoclonal gammopathy of unknown significance (MGUS). More specifically, the rosuvastatin may be co-administered with bortezomib.

[0026] In one embodiment of the present invention, a pharmaceutical composition for co-administration comprising rosuvastatin is provided to inhibit progression from smoldering multiple myeloma (SMM) to multiple myeloma in individuals with metabolic disease. More specifically, the rosuvastatin may be co-administered with bortezomib.

[0027] The cancer prevention composition according to the present invention has a preventive and / or delaying effect against blood cancer, particularly multiple myeloma, by reducing the rate of progression from MGUS or SMM to MM or delaying the onset of MM to extend the MGUS stage.

[0028] In addition, the present invention opens the way for further research and development in related fields by proposing the effect of rosuvastatin on inhibiting the progression of multiple myeloma, and can present a new pathway for cancer prevention through metabolic intervention.

[0029] In addition, the present invention can provide a basis for developing targeted therapeutic strategies for the prevention of MM through ribosome biosynthesis, translation, and oxidative phosphorylation processes identified through transcriptome analysis.

[0030] Figure 1 shows a flowchart of the study group.

[0031] Figure 2 is a plot showing the cumulative incidence rate of the statin administration group and the non-administration group.

[0032] Figure 3 is a plot showing the cumulative incidence rates of the long-term administration group, short-term administration group, and non-administration group of statins.

[0033] Figure 4 is a plot showing the cumulative incidence rate of the long-term statin administration group and all other administration groups.

[0034] Figure 5 is a graph showing the cumulative incidence of multiple myeloma progression following cumulative statin exposure to any statin.

[0035] Figure 6 is a graph showing the cumulative incidence rate of multiple myeloma progression following cumulative statin exposure to atorvastatin.

[0036] Figure 7 is a graph showing the cumulative incidence rate of multiple myeloma progression following cumulative statin exposure to rosuvastatin.

[0037] Figure 8 is a plot showing the cumulative incidence rates of the rosuvastatin administration group and the non-administration group.

[0038] Figure 9 is a plot showing the cumulative incidence rates of the long-term administration group, short-term administration group, and non-administration group of rosuvastatin.

[0039] Figure 10 is a plot showing the cumulative incidence rate of the long-term administration group of rosuvastatin and all other administration groups.

[0040] Figure 11 is a plot showing the cumulative incidence rate of the atorvastatin administration group and the non-administration group.

[0041] Figure 12 is a plot showing the cumulative incidence rates of the long-term administration group, short-term administration group, and non-administration group of atorvastatin.

[0042] Figure 13 is a plot showing the cumulative incidence rate of the long-term administration group of atorvastatin and all other administration groups.

[0043] Figure 14 is a plot showing the cumulative incidence rate of the simvastatin administration group and the non-administration group.

[0044] Figure 15 is a plot showing the cumulative incidence rates of the long-term administration group, short-term administration group, and non-administration group of simvastatin.

[0045] Figure 16 is a plot showing the cumulative incidence rate of the long-term administration group of simvastatin and all other administration groups.

[0046] Figure 17 shows the dose-response curves and IC50 of rosuvastatin and atorvastatin in MM cells after 24 hours of culture. 50 This is a graph showing the values.

[0047] Figure 18 shows the dose-response curves and IC50 of rosuvastatin and atorvastatin in MM cells after 48 hours of culture. 50 This is a graph showing the values.

[0048] Figure 19 shows the dose-response curves and IC50 of rosuvastatin and atorvastatin in MM cells after 72 hours of culture. 50 This is a graph showing the values.

[0049] Figure 20 shows mice transplanted with RPMI 8226 xenografts (top panel) and resected tumors (bottom panel) after 3 weeks of treatment. The red arrow indicates the subcutaneous tumor, and the scale bar is 5 mm.

[0050] Figure 21 is a graph showing the mouse body weight during the treatment period.

[0051] Figure 22 is a graph showing longitudinal measurements of tumor volume.

[0052] Figure 23 is a graph showing the final tumor weight at the time of autopsy.

[0053] Figure 24 shows the results of immunohistochemical staining for the proliferation marker Ki67 in tumor sections. The scale bar is 500 μm.

[0054] Figure 25 is a graph showing the results of quantifying the proportion of Ki67-positive (Ki67+) nuclei in tumor sections of each group (control group, bortezomib group, rosuvastatin group, atorvastatin group).

[0055] Figure 26 is a heatmap showing the results of hierarchical cluster analysis for differentially expressed genes (DEGs).

[0056] Figure 27 is a volcanic map of DEGs derived from a comparison of rosuvastatin (RSV) versus a control group. Significantly upregulated genes (red) and downregulated genes (blue) were identified using the criteria of change rate > 1.1 and p < 0.05.

[0057] Figure 28 is a Venn diagram showing the filtering strategy used to isolate rosuvastatin-specific DEG signatures.

[0058] Figure 29 shows the results of gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis for rosuvastatin-specific DEGs, where the bar graph indicates terms that are significantly enriched for biological processes (BP), cellular components (CC), molecular functions (MF) categories, and KEGG pathways.

[0059] Figure 30 is a Venn diagram showing the filtering strategy applied to define the specific DEG signature for rosuvastatin-bortezomib combination therapy.

[0060] Figure 31 shows the gene ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) enrichment analysis of rosuvastatin-bortezomib combination therapy-specific DEGs, where the bar graph indicates terms significantly enriched in the categories of biological processes (BP), cellular components (CC), molecular functions (MF), and KEGG pathways.

[0061] Hereinafter, the present invention will be described in detail with reference to the attached drawings. However, the following embodiments are presented as examples of the present invention, and if it is determined that a detailed description of a technology or configuration well known to those skilled in the art may unnecessarily obscure the essence of the present invention, such detailed description may be omitted, and the present invention is not limited by this. The present invention may be modified and applied in various different forms within the scope of the claims set forth below and the equivalent scope interpreted therefrom, and is therefore not limited to the embodiments described herein.

[0062] Furthermore, the terminology used in this specification is used to appropriately describe preferred embodiments of the present invention, and may vary depending on the intent of the user or operator, or the conventions of the field to which the present invention belongs. Accordingly, the definitions of these terms should be based on the content throughout this specification. Throughout the specification, when a part is described as “comprising” a certain component, it means that, unless specifically expected otherwise, it does not exclude other components but may include additional components.

[0063] All technical terms used in this invention, unless otherwise defined, are used in the sense generally understood by those skilled in the art in the relevant field of this invention. Additionally, while preferred methods or samples are described herein, similar or equivalents are also included within the scope of this invention. The contents of all publications cited as references in this specification are incorporated into this invention.

[0064] The terms used herein are for describing specific embodiments and are not intended to limit the invention. As used herein, the singular form may include the plural form unless the context clearly indicates otherwise. Additionally, as used herein, "comprise" and / or "comprising" specify the presence of the mentioned features, numbers, steps, actions, parts, elements, and / or groups thereof, and do not exclude the presence or addition of one or more other features, numbers, actions, parts, elements, and / or groups.

[0065] To solve the above problem, the present invention provides a composition for preventing multiple myeloma comprising rosuvastatin as an active ingredient.

[0066] In this invention, through a screening process utilizing a nationwide database, we identified an association between a commonly prescribed drug with reported anticancer effects and the risk of progression from MGUS to MM, and performed preclinical validation including RNA sequencing. Population-based data analysis confirmed that rosuvastatin use was associated with a reduced risk of MM progression even after adjusting for demographic characteristics, comorbidities, concomitant drugs, and co-administration of other statins, including atorvastatin, and also observed an association based on cumulative exposure. Subsequent preclinical studies verified protective effects, including rosuvastatin monotherapy and synergistic effects, and demonstrated the robustness of the results and the importance of further targeted research by presenting significant pathways.

[0067] The anti-inflammatory and immunomodulatory properties of statins are receiving increasing attention in cancer research. Observational studies have reported associations between statin use and reduced incidence or improved prognosis in specific malignancies, but results have been inconsistent depending on the cancer type. In the case of multiple myeloma (MM), a population-based cohort study by Sanfilippo et al. demonstrated that statin use was associated with a 21% reduction in overall mortality and a 24% reduction in MM-specific mortality in newly diagnosed MM patients. Furthermore, preclinical studies have explored potential anticancer mechanisms, including statin-induced apoptosis, apoptosis, regulation of autophagy, and modulation of the tumor microenvironment. In vitro studies showed that pravastatin and simvastatin exert cytotoxic effects on MM cell lines, supporting the potential direct antitumor activity of statins against MM. This invention presents evidence that statin use can prevent progression from MGUS to overt MM, demonstrating that the effects of statins may extend to early plasma cell dysplasia.

[0068] Among the two most commonly prescribed statins, atorvastatin and rosuvastatin, only rosuvastatin demonstrated a statistically significant reduction in the risk of progression to multiple myeloma associated with cumulative exposure. This invention is consistent with previous findings that not all statins exhibit equivalent anticancer effects and suggests that heterogeneity among statins should be considered when evaluating their role in cancer prevention. These differences may be attributed to variations in physicochemical properties, pharmacokinetics, and molecular structure among statin subclasses. Rosuvastatin is a hydrophilic statin with unique structural features, including a sulfonamide group. The potential role of the sulfonamide group as a tyrosine kinase modulator with anticancer activity has been recognized. Rosuvastatin also exhibits high hepatic selectivity and potent HMG-CoA reductase inhibition, forming a unique pharmacodynamic profile. The preclinical results of this invention provide strong biological evidence supporting clinical findings and present novel mechanistic insights. In a multiple myeloma xenograft model, rosuvastatin has been demonstrated to directly inhibit tumor growth and reduce cell proliferation, unlike atorvastatin. This supports the specificity observed in population-level data. Furthermore, transcriptome analysis revealed that the antitumor effect of rosuvastatin is mediated through the selective downregulation of key cellular pathways. Specifically, significant inhibition of genes related to ribosomal biosynthesis, translation, and oxidative phosphorylation was confirmed. Progression from MGUS to MM is characterized by high demands for protein synthesis (M proteins) and energy production to support rapid clonal proliferation. By disrupting these fundamental biosynthetic and bioenergetic programs, rosuvastatin can effectively induce metabolic bottlenecks that hinder the malignant progression of plasma cells through mechanisms not observed with atorvastatin. These molecular findings provide compelling grounds for the differential effects observed in the clinical and preclinical studies of the present invention.

[0069] A rosuvastatin exposure threshold of 365 cDDD or higher associated with reduced risk of multiple myeloma progression provides important clinical context. Considering the standardized DDD of rosuvastatin (10 mg / day), this exposure level is equivalent to a regimen of 2 years at 5 mg / day, 1 year at 10 mg / day, 6 months at 20 mg / day, and 3 months at 40 mg / day. These calculations demonstrate the range of different dosing patterns that achieved the exposure threshold associated with reduced risk of progression in the analysis of observational studies. These results imply that long-term treatment may be required rather than short-term therapy to achieve potential preventive effects, offering implications for clinical practice given that MGUS patients generally have cardiovascular comorbidities that may require separate statin therapy. The convergence of cardiovascular disease prevention and potential cancer prevention effects can inform treatment decisions in this patient population, particularly in that the exposure threshold associated with reduced multiple myeloma progression aligns with the durations typically used for cardiovascular protection.

[0070] The compounds and additional substances described herein, e.g., immune checkpoint inhibitors, may be administered as pharmaceutical compositions or agents for therapeutic or prophylactic treatment, and may be administered in the form of any suitable pharmaceutical composition that may include a pharmaceutically acceptable carrier and optionally one or more adjuvants, stabilizers, etc. In one embodiment, the pharmaceutical composition is intended for use in therapeutic or prophylactic treatment, for example, to treat or prevent diseases such as cancer, such as those described herein.

[0071] The terms “pharmaceutical composition,” “pharmaceutical composition,” and “pharmaceutical composition” are used interchangeably, and a pharmaceutical composition relates to a formulation comprising a therapeutically effective substance, preferably together with a pharmaceutically acceptable carrier, diluent, and / or excipient. The pharmaceutical composition is useful for reducing, preventing, or treating the severity of a disease or disorder by administering the pharmaceutical composition to an individual. Pharmaceutical compositions are also known in the art as pharmaceutical formulations. In the context of the present invention, a pharmaceutical composition comprises compounds, peptides, proteins, polypeptides, RNA, RNA particles, immune effector cells, and / or additional substances as described herein.

[0072] The pharmaceutical compositions of this specification may comprise one or more adjuvants or may be administered together with one or more adjuvants. The term “adjuvant” refers to a compound that prolongs, enhances, or accelerates an immune response. Adjuvants include a heterogeneous group of compounds such as oil emulsions (e.g., Freund adjuvants), mineral compounds (e.g., alum), bacterial products (e.g., pertussis toxins), or immunostimulatory complexes. Examples of adjuvants include, but are not limited to, LPS, GP96, CpG oligodeoxynucleotides, growth factors, and cytokines such as monokines, lymphokines, interleukins, and chemokines. Cytokines may be IL1, IL2, IL3, IL4, IL5, IL6, IL7, IL8, IL9, IL10, IL12, IFNα, IFNγ, GM-CSF, and LT-α. Additional known adjuvants are oils such as aluminum hydroxide, Freund adjuvants, or Montanide® ISA51.

[0073] The aforementioned multiple myeloma refers to a blood cancer that occurs when plasma cells, a type of white blood cell responsible for the immune system in the bone marrow, abnormally differentiate and proliferate. Plasma cells are primarily found in the bone marrow and play a vital role in the immune system by producing immunoglobulins in the body. Abnormal proteins produced by the neoplastic proliferation of these plasma cells are called abnormal serum proteins, and are also referred to as M proteins, signifying myeloma or malignancy. M proteins are found in the blood or urine. Representative diseases caused by plasma cell abnormalities include multiple myeloma, as well as Monoclonal Gammopathy of Undetermined Significance (MGUS), Smoldering Multiple Myeloma (SMM), Nonsecreting Myeloma, Plasmacytoma, Amyloidosis, POEMS Syndrome, and Plasma Cell Leukemia. The aforementioned MGUS is a disease characterized by the presence of a small number of abnormal plasma cells (myeloma cells) in the bone marrow and the detection of slight M protein in the blood or urine, but without symptoms. If the number of malignant plasma cells or M protein is elevated but there are no symptoms of multiple myeloma, it is classified as Smoldering Myeloma. In some cases, SMM is monitored rather than being treated immediately. Furthermore, although MGUS is not a target for treatment, it can progress to multiple myeloma in approximately 1% of patients annually; since progression to multiple myeloma inevitably involves passing through MGUS, regular examinations and monitoring are necessary. Multiple myeloma does not suddenly become cancer but progresses through a precancerous stage. That is, it may develop from the early stage of MGUS to MM, or progress through the early stage of MGUS and SMM to finally develop into MM. Multiple myeloma accounts for 1–2% of all tumors and is a representative hematological malignancy, along with leukemia and lymphoma.In Korea, about 1,500 patients are diagnosed annually. The incidence rate is slightly higher in men, and increases with age, with patients in their 60s and 70s accounting for about 60% of the total.

[0074] Multiple myeloma is characterized by infiltrating and dissolving bones, making them brittle, and invading and reducing the bone marrow. A decrease in the counts of white blood cells, red blood cells, and platelets can lead to infections, anemia, and bleeding. While multiple myeloma is associated with immune system abnormalities, genetic factors, and exposure to radiation and chemicals, the exact pathogenesis remains unclear. To diagnose multiple myeloma, bone marrow aspiration and biopsy are necessary to identify abnormally increased plasma cells, and blood and urine tests are required to determine the types and forms of immunoglobulins. Bone X-rays, computed tomography (CT), and magnetic resonance imaging (MRI) may also be performed to assess the degree of bone dissolution, tumor size, and extent of invasion. The most basic treatment for multiple myeloma is chemotherapy, which is administered differently depending on the severity and condition of the patient. Radiation therapy may also be used to treat multiple myeloma. In the case of solitary myeloma, radiation therapy can eliminate lesions, but there is a high risk of recurrence. Other treatment methods include autologous hematopoietic stem cell transplantation or receiving hematopoietic stem cells from a donor with matching human leukocyte antigens (HLA). Drugs primarily used to treat multiple myeloma include cytotoxic anticancer agents, steroids, proteasome inhibitors, immunomodulatory agents, and monoclonal antibodies.

[0075] In this invention, "statin" refers to a drug that acts by inhibiting HMG-CoA reductase, which plays a pivotal role in cholesterol production; also known as HMG-CoA reductase inhibitors, it refers to a group of antihyperlipidemic agents whose names end in "-statin." Statins are widely used drugs for dyslipidemia and hyperlipidemia and are the most commonly used cholesterol-lowering agents. It is known that the aforementioned statins significantly reduce cardiovascular abnormalities and mortality caused by dyslipidemia and hyperlipidemia. These effects have also been demonstrated in the preventive treatment of patients with cardiovascular disease and in high-risk patients without cardiovascular disease. Low-density lipoprotein (LDL), one of the cholesterol carriers, plays a key role in the development of atherosclerosis and coronary artery disease through a mechanism called the Lipid Hypothesis. Statins are effective in lowering the aforementioned LDL cholesterol. Therefore, they are widely used for the primary prevention of patients at high risk of developing cardiovascular disease or for the secondary prevention of patients who have already developed the disease. Side effects of statins include muscle pain, an increased risk of diabetes, and abnormally elevated liver function test results; although rare, severe side effects such as muscle damage have also been reported. Currently available statins include atorvastatin, fluvastatin, pitavastatin, lovastatin, simvastatin, rosuvastatin, and pravastatin. Other drugs, such as ezetimibe / simvastatin, are also used in combination with statins. Simvastatin, a statin, is included in the WHO Essential Medicines List, and its sales in the United States reached $18.7 billion as of 2005. In 2003, atorvastatin was named the best-selling drug in history.

[0076] In the present invention, “Rosuvastatin” is a statin drug sold under the product name Crestor, etc., used for the prevention of high-risk cardiovascular disease and the treatment of dyslipidemia, and is an oral drug. Like other statins, Rosuvastatin inhibits HMG-CoA reductase, an enzyme that produces cholesterol in the liver. Rosuvastatin has a structure similar to synthetic statins such as atorvastatin, cerivastatin, and pitavastatin. However, unlike other statins, Rosuvastatin contains sulfur within a sulfonyl functional group.

[0077] In this invention, the “defined daily dose (DDD)” refers to the average daily maintenance dose administered to treat the primary indication in adults. The DDD is a unit of measurement, and the dose for each patient and patient group is based on individual characteristics (e.g., age and weight) and pharmacokinetic considerations. The DDD is the result of a compromise based on a review of various available information regarding doses used in multiple countries. The DDD may even be a dose that is rarely prescribed, as it is the average of two or more commonly used doses. Ideally, drug usage figures should be expressed as the daily DDD per 1,000 population, or as the DDD per 100 days of hospitalization when considering drug use for hospitalized patients. For anti-infectives or other drugs typically used for short periods, it is generally considered most appropriate to express the value of drug usage as the annual DDD per capita.

[0078] The WHO standard DDD for statins is 20 mg for atorvastatin, 60 mg for fluvastatin, 2 mg for pitavastatin, 30 mg for simvastatin, 30 mg for pravastatin, 45 mg for lovastatin, and 10 mg for rosuvastatin, respectively.

[0079] In the present invention, "cumulative defined daily dose (cDDD) is a cumulative value calculated by converting the amount of drug actually consumed by an individual or group during a specific period into DDD units and summing them up, based on the standard daily dose (DDD) presented by the World Health Organization (WHO). cDDD is an indicator that expresses the total amount of drug exposure (cumulative exposure) over a certain period in a standardized form. Since cDDD simultaneously reflects the intensity and duration of drug use, it is useful for quantitatively evaluating the degree of cumulative drug exposure compared to indicators that consider only whether a prescription was given or the duration."

[0080] In this invention, "landmark analysis" is a statistical analysis method designed to evaluate the influence of time-dependent variables in survival analysis or cohort studies. Landmark analysis defines a specific point in time, after a certain period has elapsed since the start of the study, as the "landmark time," and is performed by analyzing the risk of subsequent events by including only subjects who have survived or maintained follow-up up to the said time.

[0081] In landmark analysis, exposure status or variable values ​​are defined based on a predetermined landmark point, utilizing information up to that point. Subsequently, only subjects who survived up to that point are selected for analysis, and the occurrence of events or survival periods from the landmark point onward are compared. The primary purpose of landmark analysis is to reduce time-dependent bias or immortal time bias.

[0082] When simply comparing the survival rates of individuals who have taken a drug for a specific period, a bias may occur where only those who survived during that period are included in the group. Landmark analysis is designed to prevent this problem by evaluating only the occurrence of events after a specific point in time, thereby allowing for a more accurate reflection of the impact of exposure factors that change over time. Therefore, landmark analysis is a useful method for quantitatively evaluating the effects of time-varying factors and fairly comparing their association with survival or event occurrence.

[0083] In the present invention, population-based drug screening is a research method that evaluates the efficacy, safety, and responsiveness of a drug in relation to a specific disease or physiological condition in a large population. It is an approach that explores drug responses using actual data or biological samples from a broad group of subjects, rather than simply testing the drug in cells or a small group of patients. More specifically, the specific disease may be MGUS.

[0084] In the present invention, the nationwide database is integrated data related to medical care, health, population, insurance, disease, etc., collected from an entire country or a large population group. It is characterized by including data that encompasses the entire population, rather than specific regions or small groups. More specifically, the nationwide database may be the Health Insurance Review & Assessment Service (HIRA) database.

[0085] In the present invention, the composition for preventing multiple myeloma may be a pharmaceutical composition.

[0086] The above pharmaceutical composition comprises the rosuvastatin active ingredient and may include a pharmaceutically acceptable carrier. The pharmaceutically acceptable carrier is one commonly used in formulations and includes, but is not limited to, saline solution, sterile water, Ringer's solution, buffered saline, cyclodextrin, dextrose solution, maltodextrin solution, glycerol, ethanol, liposomes, etc., and may additionally include other conventional additives such as antioxidants and buffers as needed. Additionally, diluents, dispersants, surfactants, binders, lubricants, etc., may be added to formulate the composition into injectable formulations such as aqueous solutions, suspensions, and emulsions, or into pills, capsules, granules, or tablets. Regarding suitable pharmaceutically acceptable carriers and formulations, the composition may be preferably formulated according to each component using the method disclosed in Remington's literature (Remington's Pharmaceutical Sciences, 19th edition, 1995). The composition of the present invention is not subject to any particular restrictions on the formulation, but can be formulated into injectables, inhalants, topical skin preparations, or oral preparations.

[0087] The routes of administration of the above pharmaceutical composition are not limited to these but include oral, intravenous, intramuscular, intra-arterial, intramedullary, intradural, intracardiac, transdermal, subcutaneous, intraperitoneal, intranasal, intestinal, topical, sublingual, ophthalmic, or rectal. Oral administration is preferred. Solid dosage forms for oral administration include tablets, pills, powders, granules, capsules, etc., and these solid dosage forms are prepared by mixing at least one excipient, such as starch, calcium carbonate, sucrose or lactose, gelatin, etc., with the above extract. In addition to simple excipients, lubricants such as magnesium styrate and talc are also used. Liquid dosage forms for oral administration include suspensions, liquids, emulsions, syrups, etc., and may include various excipients, such as humectants, sweeteners, flavorings, and preservatives, in addition to commonly used simple diluents such as water and liquid paraffin. Preparations for parenteral administration include sterile aqueous solutions, non-aqueous solvents, suspensions, emulsions, lyophilized preparations, and suppositories. As non-aqueous solvents and suspensions, propylene glycol, polyethylene glycol, vegetable oils such as olive oil, and injectable esters such as ethyl oleate may be used. As bases for suppositories, witepsol, macrogol, tween 61, cacao oil, laurin oil, glycerogelatin, etc. The above pharmaceutical compositions are not limited to these but may be administered orally in any orally acceptable dosage form, including capsules, tablets, aqueous suspensions, and solutions. If necessary, sweeteners and / or flavorings and / or colorings may be added.

[0088] In the present invention, the composition may be formulated or used in combination with one or more agents selected from the group consisting of calcium channel blockers, antioxidants, glutamate antagonists, anticoagulants, antihypertensive agents, antithrombotic agents, antihistamines, anti-inflammatory analgesics, anticancer agents, and antibiotics.

[0089] The dosage of the composition of the present invention varies depending on the patient's condition and body weight, the severity of the disease, the form of the drug, the route of administration, and the time of administration, but can be appropriately selected by those skilled in the art. In the present invention, "pharmaceutical effective dose" refers to an amount sufficient to treat a disease with a reasonable benefit / risk ratio applicable to medical treatment, and the effective dose level may be determined based on factors including the type and severity of the patient's disease, drug activity, sensitivity to the drug, time of administration, route of administration and elimination rate, duration of treatment, concurrently used drugs, and other factors well known in the medical field. The composition according to the present invention may be administered as an individual therapeutic agent or in combination with other therapeutic agents, may be administered sequentially or simultaneously with conventional therapeutic agents, and may be administered as a single or multiple doses. It is important to administer an amount that obtains maximum effect with a minimum amount without side effects by considering all of the above-mentioned factors, and this can be easily determined by those skilled in the art.

[0090] The materials, compositions, and methods described herein may be used to prevent the occurrence of diseases, for example, diseases characterized by the presence of cells that express an antigen. A particularly preferred disease is cancer. For example, if the antigen is derived from a virus, the materials, compositions, and methods may be useful for treating viral diseases caused by said virus. If the antigen is a tumor antigen, the materials, compositions, and methods are useful for treating cancer, where cancer cells express said tumor antigen.

[0091] The term "disease" refers to an abnormal pathological condition affecting an individual's body. Disease is often interpreted as a medical state associated with specific symptoms and signs. Diseases can be caused by factors originating from external sources, such as infectious diseases, or by internal dysfunction, such as autoimmune diseases. In humans, "disease" is used in a broader sense to refer to any pathological condition that, upon contact with an individual, causes pain, dysfunction, distress, social problems, or death or similar issues in the ailing individual. In a broader sense, this sometimes includes injury, incapacitation, disability, syndrome, infection, solitary symptoms, deviant behavior, and structural and functional atypical alterations, which can be considered distinct categories in different contexts and for different purposes. Diseases generally affect an individual not only physically but also emotionally, as living with various diseases can alter an individual's perspective on life and personality.

[0092] As used in the present invention, the term “prevention” refers to devising means to prevent a disease in advance by predicting its occurrence. Here, prevention is understood as managing and caring for an individual for the purpose of combating a disease, pathological condition, or disorder, and includes the administration of an active compound to prevent the onset of symptoms or complications. Prevention includes primary prevention, which involves discovering and eliminating the etiology, and secondary prevention, which involves detecting the disease early and treating it in a timely manner. More specifically, in the present invention, prevention refers to inhibiting the progression to multiple myeloma (MM) in patients with metabolic diseases, patients with monoclonal gammopathy of unknown significance (MGUS), or patients with asymptomatic multiple myeloma (SMM).

[0093] The term "preventive treatment" or "preventive treatment" refers to any treatment intended to prevent the occurrence of disease in an individual. The terms "preventive treatment" or "preventive treatment" are used interchangeably herein.

[0094] The terms “individual” and “entity” are used interchangeably herein. These terms refer to a human or other mammal (e.g., mouse, rat, rabbit, dog, cat, cattle, pig, sheep, horse, or primate) that may or may not have a disease or disorder (e.g., cancer), but may or may not have a disease or disorder. In many embodiments, the entity is a human. Unless otherwise specified, the terms “individual” and “entity” do not imply a specific age and thus encompass adults, the elderly, children, and newborns. In embodiments of this specification, the “entity” or “individual” is a “patient.”

[0095] The term "patient" refers to an individual or entity requiring treatment, specifically an individual or entity suffering from a disease.

[0096] The term "cancer disease" or "cancer" refers to or means a pathological condition characterized by uncontrolled cell proliferation in an individual. As per this specification, the term "cancer" also includes cancer metastasis.

[0097] In cancer treatment, a combination strategy may be suitable due to the synergistic effects achieved, which may be considered superior to the effects of a monotherapy. In one embodiment, a pharmaceutical composition is administered together with an immunotherapeutic agent. As used herein, "immunotherapeutic agent" means any substance that may be involved in activating a specific immune response and / or immune effector function(s). This specification considers the use of antibodies as immunotherapeutic agents. Although not intended to be theoretical, antibodies may achieve therapeutic effects against cancer cells through various mechanisms, including inducing apoptosis, blocking components of signaling pathways, or inhibiting the proliferation of tumor cells. In certain embodiments, the antibody is a monoclonal antibody. Monoclonal antibodies may induce apoptosis through antibody-dependent cell-mediated cytotoxicity (ADCC) or bind to complement proteins to induce direct cytotoxicity known as complement-dependent cytotoxicity (CDC). Non-limiting examples of anticancer antibodies and potential antibody targets (in parentheses) that may be used in combination with the present invention include abagovomab (CA-125), abciximab (CD41), adecatumumab (atumumab) (EpCAM), afutuzumab (CD20), alacizumab pegol (VEGFR2), altumomab pentetate (CEA), amatuximab (MORAb-009), anatumomab mafenatox (TAG-72), apolizumab (HLA-DR), arcitumomab (CEA), and atezolizumab. (PD-L1), Bavituximab (phosphatidylserine), Bectumomab (CD22),Belimumab (BAFF), Bevacizumab (VEGF-A), Bivatuzumab mertansine (CD44 v6), Blinatumomab (CD19), Brentuximab vedotin (CD30 TNFRSF8), Cantuzumab mertansin (mucin CanAg), Cantuzumab ravtansine (MUC1), Capromab pendetide (prostate carcinoma cells), Carlumab (CNT0888), Catumaxomab (EpCAM, CD3), Cetuximab (EGFR), Cetuximab VOGATOX (Citatuzumab bogatox) (EpCAM), Cisutumumab (IGF-1 receptor), Claudiximab (Claudin), Clivatuzumab tetraxetan (MUC1), Conatumumab (TRAIL-R2), Dasetuzumab (CD40), Dalotuzumab (Insulin-like growth factor I receptor), Denosumab (RANKL), Detumomab (B-lymphoma cells), Drozitumab (DR5), Ecromeximab (GD3 ganglioside), Edrecolomab (EpCAM), Elotuzumab (SLAMF7), Enavatuzumab (PDL192), Ensituximab (NPC-1C), Epratuzumab (CD22), Ertumaxomab (HER2 / neu, CD3), Etaracizumab (integrin αγβ3),Farletuzumab (Follate Receptor 1), FBTA05 (CD20), Ficlatuzumab (SCH 900105), Figitumumab (IGF-1 Receptor), Flanvotumab (Glycoprotein 75), Fresolimumab (TGF-β), Galiximab (CD80), Ganitumab (IGF-I), Gemtuzumab ozogamicin (CD33), Gevokizumab (IL1β), Girentuximab (Carbonic Anhydrase 9 (CA-IX)), Glembatumumab vedotin (GPNMB), Ibritumomab tiuxetan (CD20), Icrucumab (VEGFR-1), Igovoma (CA-125), Indatuximab ravtansine (SDC1), Intetumumab (CD51), Inotuzumab ozogamicin (CD22), Ipilimumab (CD 152), Iratumumab (CD30), Labetuzumab (CEA), Lexatumumab (TRAIL-R2), Libivirumab (Hepatitis B surface antigen), Lintuzumab (CD33), Lorvotuzumab mertansine (CD56), Lucatumumab (CD40), Lumiliximab (CD23), Mapatumumab (TRAIL-R1), Matuzumab (EGFR), Mepolizumab (IL5), Milatuzumab (CD74),Mitumomab (GD3 ganglioside), Mogamulizumab (CCR4), Moxetumomab pasudotox (CD22), Nacolomab tafenatox (C242 antigen), Naftumomab estafenatox (5T4), Namatumab (RON), Necitumumab (EGFR), Nimotuzumab (EGFR), Nivolumab (IgG4), Ofatumumab (CD20), Olaratumab (PDGF-RA), Onartuzumab (human scatter factor receptor kinase kinase), Oportuzumab monatox (EpCAM), Oregovomab (CA-125), Oxelumab (OX-40), Panitumumab (EGFR), Patritumab (HER3), Pemtumoma (MUC1), Pertuzuma (HER2 / neu), Pintumomab (Adenocarcinoma Antigen), Pritumumab (Vimentin), Racotumomab (N-Glycolylneuraminic Acid), Radretumab (Fibronectin Extra Domain-B), Rafivirumab (Rabies Virus Glycoprotein), Ramucirumab (VEGFR2), Rilotumumab (HGF), Rituximab (CD20), Robatumumab (IGF-1 receptor), Samalizumab (CD200), Sibrotuzumab (FAP),Siltuximab (IL6), Tabalumab (BAFF), Tacatuzumab tetraxetan (α-fetoprotein), Tapitumomab paptox (CD 19), Tenatumomab (Tenacin C), Teprotumumab (CD221), Ticilimumab (CTLA-4), Tigatuzumab (TRAIL-R2), TNX-650 (IL13), Tositumomab (CD20), Trastuzumab (HER2 / neu), TRBS07 (GD2), Tremelimumab (CTLA-4), Tucotuzumab selmolukin Includes Tucotuzumab (celmoleukin) (EpCAM), Ublituximab (MS4A1), Urelumab (4-1 BB), Volociximab (integrin α5β1), Votumumab (tumor antigen CTAA 16.88), Zalutumumab (EGFR), and Janolimumab (CD4).

[0098] In the present invention, the term “health functional food composition” refers to a food manufactured and processed using raw materials or ingredients having functional properties useful to the human body as defined in Article 6727 of the Health Functional Foods Act, and means consuming it for the purpose of obtaining effects useful for health purposes, such as regulating nutrients or physiological actions regarding the structure and function of the human body.

[0099] The health functional food of the present invention may be manufactured and processed in the form of tablets, capsules, powders, granules, liquids, pills, etc., and may contain conventional food additives. Unless otherwise specified, suitability as a food additive is determined in accordance with the specifications and standards for the relevant item in accordance with the general provisions and general test methods of the food additive code approved by the Korea Food and Drug Administration.

[0100] Items listed in the aforementioned 'Food Additives Codex' include, for example, chemically synthesized compounds such as ketones, glycine, calcium citrate, nicotinic acid, and cinnamon acid; natural additives such as persimmon dye, licorice extract, crystalline cellulose, sorghum dye, and guar gum; and mixed preparations such as L-sodium glutamate preparations, alkaline noodle additives, preservative preparations, and tar dye preparations. For example, a health functional food in tablet form may be produced by granulating a mixture of the active ingredient of the present invention with an excipient, a binder, a disintegrant, and other additives using a conventional method, and then adding a lubricant or the like and compression molding, or by directly compression molding the mixture. Additionally, the health functional food in tablet form may contain a binder or the like as needed. Among the health functional foods in capsule form, hard capsules can be manufactured by filling a conventional hard capsule with a mixture in which the active ingredient of the present invention is mixed with additives such as excipients, and soft capsules can be manufactured by filling a capsule base such as gelatin with a mixture in which the active ingredient of the present invention is mixed with additives such as excipients. The soft capsules may contain plasticizers such as glycerin or sorbitol, coloring agents, preservatives, etc., as needed. The health functional food in pill form can be prepared by molding a mixture of the active ingredient of the present invention with excipients, binders, disintegrants, etc., using a previously known method, and may be coated with sucrose or other coating agents as needed, or the surface may be coated with a substance such as starch or talc. The health functional food in granule form can be manufactured into a granular form using a previously known method, by mixing a mixture of the active ingredient of the present invention with excipients, binders, disintegrants, etc., and may contain flavoring agents, stimulating agents, etc., as needed.

[0101] References to the literature and research referenced herein are not intended as an acknowledgment that any of the foregoing content is related to the prior art. All references to the contents of these documents are based on information available to the applicant and are not to be construed as any acknowledgment regarding the accuracy of the contents of these documents.

[0102] The following description is provided to enable those skilled in the art to create and use various embodiments. Descriptions of specific devices, techniques, and uses are provided merely as examples. Various modifications to the examples described herein will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other examples and uses without departing from the spirit and scope of the various embodiments. Accordingly, various embodiments are not intended to be limited to the examples described and shown herein, but are intended to be consistent with the scope of the claims.

[0103] The present invention identified drugs associated with reducing progression from MGUS to MM through population-based screening and conducted a two-stage translational study to evaluate anti-myeloma activity through a preclinical model.

[0104] In the first step, population-based pharmacoepidemiological screening was performed using the Health Insurance Review & Assessment Service (HIRA) database, which contains medical data for the entire Korean population. With 6 months post-MGUS diagnosis set as a landmark, the association between five candidate drug classes (statins, angiotensin-converting enzyme inhibitors / angiotensin receptor blockers, ezetimibe, aspirin, and metformin) and MM progression was evaluated. Drug exposure was assessed as cumulative defined daily doses over the period from 12 months prior to 6 months post-MGUS diagnosis, and baseline characteristics were balanced using inverse probability of treatment weighting. For drug classes showing a significant protective association, cumulative exposure was classified into three groups (no exposure to low, moderate, and high exposure) to investigate the relationship between exposure levels and MM progression, and individual drugs within each group were evaluated. The robustness of the study results was verified through sensitivity analysis using alternate exposure periods.

[0105] In the second step, preclinical validation was performed on drugs with established epoxygical associations using MM cell lines and xenograft mouse models, and the affected pathways were identified through transcriptome analysis and the synergistic effect with bortezomib was evaluated.

[0106]

[0107] Examples

[0108] Example 1. Method

[0109] 1.1 Design of a Population-Based Drug Screening Study

[0110] As shown in Figure 1, 9,946 patients diagnosed with MGUS (ICD10: D47.2) as the primary diagnosis between 2010 and 2022 were initially identified from a database of 51 million people nationwide, and the final cohort consisted of 5,131 newly diagnosed MGUS patients. Applying a landmark analysis design with 6 months after MGUS diagnosis as a landmark, drug exposure was evaluated over an 18-month period from 12 months prior to 6 months after MGUS diagnosis. The associations among five candidate drug classes (statins, ACE inhibitors / ARBs, ezetimibe, aspirin, and metformin) regarding progression from MGUS to MM were investigated. Exposure was classified as the corresponding drug if the cumulative duration of administration within the exposure period exceeded 365 days.

[0111] After selecting drug groups associated with MM progression, a detailed analysis was performed on significant associations. For these drug groups, exposure was quantified using the cumulative defined daily dose (cDDD), and patients were classified into three exposure levels (no exposure to low, medium, and high exposure). Subgroup analyses were conducted to evaluate drug-specific effects through comparisons between individual agents within the significant drug groups. Treatment inverse probability weights (IPTW) were applied to balance baseline characteristics between the exposed and non-exposed groups.

[0112] 1.2 Establishing a Selective Research Environment through a Nationwide Database

[0113] The baseline date was defined as the date of the initial MGUS diagnosis. The exposure evaluation period was set from one year prior to the baseline date to six months later, considering existing literature and biological processes indicating that at least one year of drug exposure is required for cancer prevention effects. A landmark analysis was performed at the six-month mark after diagnosis, and only patients who were progression-free at this point were included in the survival analysis. To evaluate the robustness of the results, a sensitivity analysis was conducted using alternate exposure periods (6, 12, 24, and 36 months). Multiple myeloma progression was defined as a composite indicator of multiple myeloma diagnosis and the initiation of first-line treatment using drugs covered by the National Health Insurance. The aforementioned diagnosis refers to a diagnosis of multiple myeloma corresponding to ICD-10: C90.0 in the ICD-10, a system established by the World Health Organization (WHO) based on the 10th Revision of the International Classification of Diseases that classifies diseases, symptoms, causes of death, and medical procedures using standardized codes.

[0114] Underlying comorbidities were evaluated using the Charlson Comorbidity Index (CCI) based on ICD-10 codes. The CCI is designed to predict future mortality risk or prognosis by scoring the types and severity of a patient's comorbidities. A higher total CCI score indicates a higher risk of death and a higher likelihood of complications. Five candidate drug classes (statins, ACE inhibitors / ARBs, aspirin, ezetimibe, and metformin) were identified using HIRA drug codes mapped to the WHO-ATC classification. Drug exposure was quantified as the cumulative defined daily dose (cDDD), which was calculated by standardizing the total amount of drug administered during the exposure period to the WHO defined DDD (assumed mean maintenance dose for major indications in adults). This index integrates both dose intensity and duration, providing a more comprehensive measure of exposure than considering only the duration of prescription.

[0115] 1.3 In vitro cell proliferation analysis

[0116] To evaluate cell proliferation, RPMI 8226 human multiple myeloma cells (3 × 10⁴ cells / well) were seeded into 96-well plates and treated with rosuvastatin or atorvastatin at various concentrations (6.25, 12.5, 25, 50, 100, and 200 μM) for 24, 48, or 72 hours. After the specified treatment periods, 20 μL of CCK-8 reagent (Dojindo Molecular Technologies) was added to each well and incubated at 37°C for 2 hours. Subsequently, absorbance was measured at 450 nm using a microplate reader (BioTek, Winooski, VT, USA). Cell viability was expressed as a percentage relative to the control group. The concentration of rosuvastatin or atorvastatin that reduces cell viability by 50% (IC10) 50 ) was determined through nonlinear regression analysis of the dose-response curve.

[0117] 1.4 In vivo xenotransplantation model

[0118] All procedures related to animal experiments were approved following review by the Animal Ethics Committee of the Catholic University of Korea (Approval No. 2023-029404). Male BALB / c nude mice (5 weeks old) were purchased from Orient Bio (Seongnam-si, South Korea) and reared under standardized conditions (22 ± 2 °C, 60% relative humidity, 12-hour d-dark cycle) with free access to food and water. To establish a multiple myeloma xenograft model, 5 × 10⁶ [units] suspended in a solution of 0.1 ml Matrigel and culture medium mixed in a 1:1 ratio were placed in the right forelimbs of 6-week-old mice. 6RPMI 8226 human MM cells were injected subcutaneously. RPMI 8226 human multiple myeloma cells were cultured in RPMI-1640 medium (Gibco) supplemented with 10% heat-treated fetal bovine serum (Gibco) and 100 U / ml penicillin-streptomycin (Gibco) at 37°C in a humid environment with 5% CO₂. Seven days after transplantation, mice were randomized into six treatment groups (n=5 per group): the six treatment groups were a control group (solvent administration), bortezomib (BTZ; Sigma-Aldrich, 504314; 1 mg / kg, administered intraperitoneally twice a week), rosuvastatin (RSV; Sigma-Aldrich, 18813; 10 mg / kg, administered intraperitoneally daily), atorvastatin (ATV; Sigma-Aldrich, 10483; 10 mg / kg, administered intraperitoneally daily), and a combination of BTZ and RSV. Treatment was administered for 19 consecutive days. Tumor size was measured three times a week using a digital caliper, and tumor volume was calculated using the formula V = (length × width²) / 2.

[0119] 1.5 Immunohistochemistry

[0120] For histological analysis, resected tumor tissues were fixed in 10% neutral buffered formalin, embedded in paraffin, and 4 μm thick sections were prepared. Heat-mediated antigen retrieval was performed after deparaffinization and rehydration. To evaluate cell proliferation, sections were cultured with anti-Ki67 antibody (Abcam, ab15580) after blocking endogenous peroxidase activity and non-specific binding. Immunological responses were visualized using the VECTASTAIN® Elite ABC kit (Vector Laboratories), and nuclei were counterstained with hematocillin. The proportion of Ki67-positive cells was quantified from digital images using ImageJ software (NIH).

[0121] 1.6 RNA Sequencing and Bioinformatics Analysis

[0122] Total RNA was extracted from xenograft tumor tissues using the PureLink RNA Mini Kit (Invitrogen), and RNA quality was verified prior to library preparation. Transcriptome profiling was performed using QuantSeq 3′ mRNA sequencing. Differentially expressed genes (DEGs) were identified using ExDEGA software (E-biogen) by applying criteria of fold change > 1.1 and p < 0.05. To identify rosuvastatin-specific transcription signatures, DEGs that showed significant changes in RSV / control comparisons but no changes in ATV / control or BTZ / control comparisons were selected. Gene Ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) enrichment analyses were performed on this filtered set of genes. To identify transcriptional changes specific to rosuvastatin-bortezomib combination therapy, DEGs derived from the BTZ+RSV / BTZ comparison were analyzed after excluding genes also present in the RSV / control dataset. This filtering step eliminated the effects of monotherapy to derive a set of genes exhibiting combination-specific antitumor responses, which were then applied to GO and KEGG abundance analyses.

[0123] 1.7 Statistical Analysis

[0124] In the screening stage, the incidence rates of MM progression were compared using a weighted cumulative occurrence function. Subsequently, the hazard ratio (HR) was estimated by applying a weighted cause-specific Cox proportional hazard model. The incidence rate was calculated as the incidence rate per 100,000 person-years by dividing the number of MM progression events by the total person-years exposed to risk and multiplying by 100,000. The aforementioned person-years is the sum of the total time the study subjects were observed, and can be calculated using the same criteria even for subjects with different observation periods.

[0125] Weights based on categorical treatment exposure were derived using the Inverse Treatment Probability Weighting (IPTW) method, and covariates such as age, sex, comorbidities, and concomitant medications were adjusted. To ensure appropriate variance estimation and reduce the impact of extreme values, weights were stabilized and truncated at the 99.9th percentile. Variables with a Standardized Mean Difference (SMD) exceeding 0.1 were double-adjusted during the hazard ratio (HR) estimation process. All time-to-event analyses included a follow-up period of up to 6 years, determined as twice the median follow-up period observed in the study cohort, to assess progression to multiple myeloma. Methodological robustness was evaluated through sensitivity analysis incorporating various weight truncation parameters, exposure windows with alternative exposure thresholds, and Fine-Gray hazard modeling. Additionally, E-values ​​were calculated to quantify how strong unmeasured confounding variables must be to nullify observed associations. Statistical significance was defined as a two-sided P-value < 0.05, and all statistical analyses and figure generation were performed using R statistical software version 3.5.1 (R Foundation for Statistical Computing, Vienna, Austria).

[0126] Example 2. Results

[0127] 2.1 Patient Characteristics

[0128] The median follow-up period was 37.5 months (95% confidence interval, 36.5–38.7). During the observation period, 184 patients (3.6%) progressed from MGUS to multiple myeloma. Over the 6 years following the diagnosis of MGUS, total deaths occurred in 898 patients (17.5%). As summarized in Table 1, 62.6% of the patients were male, the mean age of the cohort was 68.0 ± 12.4 years, and patients aged 70 years or older accounted for 50.3%. The cumulative incidence of progression to multiple myeloma was 1.1% (95% CI, 0.8-1.4) at 1 year, 2.4% (95% CI, 2.0-2.9) at 2 years, 4.2% (95% CI, 3.5-4.8) at 4 years, and 5.0% (95% CI, 4.3-5.8) at 6 years, and the median time to progression from MGUS in 184 patients who progressed to multiple myeloma was 18.8 months (95% confidence interval, 15.8-22.8).

[0129] Epidemiological Characteristics Total (N=5,131) Median follow-up period, months (95% CI) 37.5 (36.5, 38.7) Events, n (%) Termination 4,049 (78.9) Multiple myeloma 184 (3.6) Death 898 (17.5) Gender, n (%) Male 3,212 (62.6) Female 1,919 (37.4) Age, mean (standard deviation) 68.0 (12.4) Age, n (%) <601,209 (23.6) 60 ~ 691,343 (26.2) >= 702,579 (50.3) Underlying Diseases, n (%) Myocardial infarction 126 (2.5) Chronic heart failure 574 (11.2) Peripheral vascular disease 767 (14.9) Cerebrovascular disease 1,001 (19.5) Dementia 130 (2.5) Chronic lung disease 1,973 (38.5) Rheumatic disease 316 (6.2) Gastric ulcer disease 1,226 (23.9) Liver disease 1,031 (20.1) Diabetes 1,837 (35.8) Hemiplegia or quadriplegia 97 (1.9) Kidney disease 1,198 23.3() Cancer 627 (13.1) AIDS / HIV 0 (0.0) Targeted drug group exposure, n(%) 1Statin 1,311 (25.6) ACE inhibitor / ARB 1,518 (29.6) Aspirin 596 (11.6) Ezetimib 171 (3.3) Metformin 511 (10.0) 1 Accumulated prescriptions for more than one year

[0130] 2.2 Through exploratory analysis of selected statins, ACE inhibitors / ARBs, aspirin, ezetimibe, and metformin based on association results from a national database, the potential association with the risk of multiple myeloma (MM) progression was evaluated. As summarized in Table 2, statin use for more than one year during the exposure period indicated a significant reduction in the risk of MM progression (unadjusted hazard ratio: 0.59, 95% confidence interval: 0.40–0.88; adjusted hazard ratio: 0.51, 95% confidence interval: 0.33–0.78). In contrast, ACE inhibitors / ARBs, aspirin, and metformin did not show a significant association with the risk of multiple myeloma progression. Consistently similar results were observed in sensitivity analyses using various exposure periods and corresponding thresholds.

[0131] drugs 1 Univariate Hazard Ratio (HR) (95% Confidence Interval) Age- and Gender Adjusted Hazard Ratio (HR) (95% Confidence Interval) Multivariate HR (95% Confidence Interval) 2 Statins 0.59 (0.40, 0.88) 0.59 (0.40, 0.87) 0.61 (0.41, 0.91) ACE Inhibitors / ARBs 0.93 (0.67, 1.28) 0.87 (0.63, 1.21) 0.93 (0.66, 1.30) Aspirin 0.95 (0.60, 1.50) 0.86 (0.54, 1.38) 1.02 (0.64, 1.65) Metformin 1.40 (0.91, 2.17) 1.40 (0.90, 2.16) 1.42 (0.75, 2.72) 1 Accumulated prescriptions for more than one year 2Age, sex, myocardial infarction, chronic heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic lung disease, rheumatic disease, gastric ulcer, liver disease, diabetes, hemiplegia or quadriplegia, kidney disease, cancer, and drug exposure are adjusted in the regression model.

[0132] 2.3 Association between Cumulative Statin Exposure and Multiple Myeloma Progression Based on the significant results regarding statins, the association between cumulative statin use and the progression of multiple myeloma was further investigated by quantifying cumulative drug exposure using cDDD. The study cohort was classified according to cDDD into three exposure levels: no to low exposure (cDDD ≤ 30 days), moderate exposure (31–365 days), and high exposure (cDDD ≥ 366 days), or into three exposure levels: cDDD ≤ 90 days, 31–365 days, and cDDD ≥ 366 days. For the study cohort classified into the three exposure levels of cDDD ≤ 90 days, 31–365 days, and cDDD ≥ 366 days, the exposure period was defined as from 2 years prior to the diagnosis of MGUS to 3 months thereafter, and statin use was defined as receiving a prescription for statin drugs for at least 24 months during the aforementioned exposure period. The above statins included prescriptions for atorvastatin, rosuvastatin, simvastatin, lovastatin, fluvastatin, pravastatin, and pitavastatin, while pravastatin, lovastatin, and fluvastatin, which are rarely prescribed, were excluded from the regression analysis.

[0133] Table 3 summarizes the incidence of multiple myeloma progression for each of the three cumulative statin exposure groups by comparing baseline characteristics among the three groups. Among the exposure groups, 104 patients (3.9%) in the group with no or low exposure progressed to multiple myeloma, 63 patients (3.7%) in the intermediate exposure group progressed, and 17 cases (2.3%) were observed in the high exposure group.

[0134] The graphs shown in Figures 2 to 4 and Figures 8 to 16 represent the results of evaluating the association between statin administration and disease progression using cumulative incidence curves and Gray's test. Figure 2 is a graph comparing disease progression between statin users and non-users. Statin users had a lower cumulative incidence of disease progression compared to non-users, but it was not significant (P = 0.06). Figures 3 and 4 are graphs evaluating the effect of statin cumulative DDD (cDDD) on disease progression, and patients were classified based on cDDD into < 90 days, < 365 days, and ≥ 365 days. As shown in Figure 3, among the cDDD < 90, cDDD < 365, and cDDD ≥ 365 groups, the rate of disease progression was lower only in the long-term statin group (P = 0.03), and as shown in Figure 4, disease progression was significantly reduced in long-term statin users in the cDDD < 365 and cDDD ≥ 365 groups, and the difference between the statin group and the non-statin group was greater (P = 0.01). These results suggest that long-term statin administration with a high cumulative dose of 365 days or more is associated with a reduction in the risk of disease progression.

[0135] As shown in Figure 5, when the cohort was classified into three exposure levels based on cDDD—no to low exposure (cDDD ≤ 30 days), moderate exposure (31–365 days), and high exposure (cDDD ≥ 366 days)—the cumulative incidence of MM progression over time was also lower in the high-exposure group than in the low-exposure and moderate-exposure groups. However, as summarized in Table 4, this difference was not statistically significant after adjustment (weighted hazard ratio, 0.66 [95% confidence interval, 0.34–1.30]).

[0136] Characteristics Groups by Cumulative Statin Exposure P-value Low (N=2,676) Medium (N=1,717) High (N=738) Median follow-up period, months (95% CI) 40.4 (38.7, 42.7) 35.8 (33.7, 37.8) 33.2 (30.1, 35.8) Events within 6 years, n(%) 0.082 Censored 2078 (77.7) 1.372 (79.9) 599 (81.2) Multiple Myeloma 104 (3.9) 63 (3.7) 17 (2.3) Death 494 (18.5) 282 (16.4) 122 (16.5) Gender, n(%) 0.415 Male 1,668 (62.3) 1,066 (62.1) 478 (64.8)Female 1,008 (37.7)651 (37.9)260 (35.2)Age, Mean (Standard Deviation)66.2 (13.5)69.5 (11.0)71.3 (10.3)<0.001Age, n (%)<0.001<608 14 (30.4)299 (17.4)96 (13.0)60 ~ 696 49 (24.3)491 (28.6)203 (27.5)>= 701 213 (45.3)927 (54.0)439 (59.5)Underlying Diseases, n(%)Myocardial Infarction 16 (0.6)44 (2.6)66 (8.9)<0.001Chronic Heart Failure 246 (9.2)208 (12.1)120 (16.3)<0.001 Peripheral Vascular Disease 344 (12.9)277 (16.1)146 (19.8)<0.001 Cerebrovascular Disease 375 (14.0)389 (22.7)237 (32.1)<0.001 Dementia 60 (2.2)46 (2.7)24 (3.3)<0.001 Chronic Lung Disease 1,009 (37.7)649 (37.8)315 (42.7)0.038 Rheumatic Disease 182 (6.8)90 (5.2)44 (6.0)0.108 Gastric Ulcer Disease 624 (23.3)411 (23.9)191 (25.9)0.351 Liver Disease 561 (21.0)338 (19.7)132 (17.9)0.159 Diabetes 2,402 (42.6)1,204 (34.9)1,198 (54.7)<0.001 Hemiplegia or quadriplegia 39 (1.5)32 (1.9)26 (3.5)0.001 Kidney disease 411 (15.4)506 (29.5)281 (38.1)<0.001 Cancer 368 (13.8)206 (12)98 (13.3)0.240AIDS / HIV0 (0.0)0 (0.0)0 (0.0)-Concurrently administered drugs, n(%). 1 ACE Inhibitor / ARB 523 (19.5) 636 (37.0) 359 (48.6) <0.001 Aspirin 166 (6.2) 237 (13.8) 193 (26.2) <0.001 Ezetimibe 2 (0.1) 117 (6.8) 52 (7.0) <0.001 Metformin 156 (5.8) 233 (13.6) 122 (16.5) <0.001 CDDD of statins, days, mean (standard deviation) Atorvastatin 0.6 (3.4) 97.5 (100.8) 194.8 (304.6) <0.001 Fluvastatin 0 (0.0) 1.0 (14.2) 10.6 (76.9) <0.001 Lovastatin 0 (0.0)0.1 (4.3)0 (0.6)0.376 Pitavastatin 0.1 (1.4)10.3 (46.6)74.2 (197.8)<0.001 Pravastatin 0.0 (0.8)7.0 (39.7)22.7 (107.4)<0.001 Rosuvastatin 0.3 (2.2)57.9 (94.5)256.1 (285.2)<0.001 Simvastatin 0.1 (1.0)16.8 (58.2)3.6 (31.5)<0.001 1 Accumulated prescriptions for more than one year

[0137] Drug group 1 Number of patient investigation cases (%) person-year incidence rate 2 (95% CI) Adjusted Risk Ratio 3 (95% CI) Statins Low 2,676 104 (3.9%) 864 1.4 120 3.5 (983.4, 1458.3) 1 Medium 1,717 63 (3.7%) 504 4.9 124 8.8 (959.6, 1597.8) 0.98 (0.70, 1.37) High 738 17 (2.3%) 205 3.5 827.9 (482.3, 1325.5) 0.66 (0.34, 1.30) Atorvastatin 4Low 3,821,133 (3.5%) 118,34.8 112,38 (9,40.9, 1,331.8) Medium 1,085,42 (3.9%) 3,284.7 12,78.7 (9,21.5, 1,728.4) 1.13 (0.78, 1.65) High 2,259 (4%) 6,20.3 145,10 (6,63.5, 2,754.4) 1.53 (0.53, 4.38) Rosuvastatin Low 4,171,164 (3.9%) 132,68.8 123,600 (1,054.1, 1,440.3) Medium 631,15 (2.4%) 1,583.1 947.5 (5,30.3, 1562.8)0.75(0.42, 1.35)High 3295 (1.5%)887.9563.1(182.8, 1314.2)0.29(0.10, 0.88) 1 Low exposure: Cumulative daily defined dose (cDDD) ≤ 30 days; Medium exposure: 31 < cDDD ≤ 365 days; High exposure (cDDD ≥ 366 days). 2 Incidence rate, per 100,000 people per year 3 Age, sex, myocardial infarction, chronic heart failure, peripheral vascular disease, cerebrovascular disease, dementia, chronic lung disease, rheumatic disease, gastric ulcer disease, liver disease, diabetes mellitus, hemiplegia or paraplegia, kidney disease, cancer, and exposure factors such as angiotensin-converting enzyme inhibitors / angiotensin II receptor blockers, aspirin, and metformin are adjusted using an inverse probability of treatment weighting model. 4 Age, chronic heart failure, peripheral vascular disease, cerebrovascular disease, diabetes mellitus, use of angiotensin II receptor blockers, aspirin use, and metformin use (all SMD > 0.1) were double-adjusted as covariates for the risk estimation of atorvastatin.

[0138] 2.4 Subgroup Analysis by Specific Statin: Atorvastatin and Rosuvastatin The specific associations of atorvastatin and rosuvastatin with MM progression were evaluated in the MGUS. For both drugs, patients in the high-exposure group were older and had more comorbidities and concomitant drug use. In the case of atorvastatin, as shown in Table 4, the incidence of multiple myeloma progression in the high-exposure group was 1,451.0 cases per 100,000-year (95% CI: 663.5–2,754.4), which was slightly higher than in the low-exposure group (1,123.8 cases per 100,000-year, 95% CI: 940.9–1,331.8). As shown in Figure 6 (Figure 2B), in the TW-adjusted analysis, the weighted risk ratio (HR) for MM progression relative to the low-exposure group was 1.13 (95% CI, 0.787–1.65) in the medium-exposure group and 1.53 (95% CI, 0.534–38) in the high-exposure group. However, these increases did not show a statistically significant difference, meaning that atorvastatin did not show a cumulative exposure association with multiple myeloma progression. In addition, when patients were classified into three exposure groups based on cumulative rosuvastatin exposure, the incidence of multiple myeloma progression in the high-exposure group was 563.1 cases per 100,000-year (95% CI, 182.8–1,314.2), which was significantly lower than that of the low-exposure group, which was 1,236.0 cases per 100,000-year (95% CI, 1,054.1–1,440.3). Furthermore, as shown in Figure 7, the weighted hazard ratio (HR) was 0.29 (95% confidence interval, 0.10–0.88), and the cumulative incidence of multiple myeloma progression over time was significantly lower in the high-exposure group. This association was statistically significant in several analysis models, including Gray's test (P = 0.002) and the weighted Fine-Gray risk model (weighted hazard ratio, 0.30; 95% confidence interval, 0.10–0.88). This association persisted even after adjusting for prior atorvastatin exposure (weighted hazard ratio, 0.22; 95% confidence interval, 0.07–0.76).The results for rosuvastatin remained consistent and robust in sensitivity analyses using various weighted truncation methods. The calculated E-value to assess the potential impact of unmeasured confounding factors was 6.35, suggesting that a risk-ratio association of ≥6.35 for both high-dose rosuvastatin exposure and multiple myeloma progression is required for unmeasured confounding factors to invalidate these results, implying that moderate levels of confounding factors alone are insufficient to invalidate them. Collectively, these results provide strong evidence for a cumulative exposure-dependent association of rosuvastatin with MM progression in MGUS.

[0139] Additionally, when the cohort was classified into three exposure levels—cDDD ≤ 90 days, 91–365 days, and cDDD ≥ 366 days—further analysis was performed on individual statin components with an administration frequency of 5% or higher. Figure 8 compares disease progression between rosuvastatin recipients and non-recipients. Rosuvastatin recipients had a lower cumulative incidence of disease progression compared to non-recipients (P < 0.01). Figures 9 and 10 illustrate the effect of rosuvastatin's cDDD on disease progression; disease progression was significantly reduced in long-term recipients in the cDDD ≤ 365 and cDDD ≥ 366 groups, and the difference from non-recipients was more pronounced (P = 0.01). These results demonstrate that long-term administration of rosuvastatin with high cumulative doses of 365 days or more is associated with a reduced risk of disease progression. However, as shown in Figures 11 to 16, atorvastatin and simvastatin did not show a significant effect on disease progression.

[0140] 2.5 Comparison of the preventive effects of rosuvastatin and other drugs

[0141] As shown in Table 5, a comparison of the preventive effects of rosuvastatin and other drugs revealed that rosuvastatin provided a stronger protective effect against disease progression compared to other treatments. In the cause-specific analysis, the hazard ratio (HR) of rosuvastatin was 0.496 (95% CI: 0.263, 0.937), which was a statistically significant reduction compared to metformin (HR: 0.742, 95% CI: 0.484, 1.137), aspirin (HR: 0.706, 95% CI: 0.485, 1.028), and other statins (HR: 0.749, 95% CI: 0.540, 1.039). In the analysis considering competitive risk in the Fine-Gray model, rosuvastatin showed a hazard ratio of 0.495 (95% CI: 0.262, 0.935), demonstrating a more protective effect compared to metformin (HR: 0.723, 95% CI: 0.472, 1.106), aspirin (HR: 0.690, 95% CI: 0.474, 1.003), ARB or ACEI (HR: 0.967, 95% CI: 0.717, 1.306), and general statin use (HR: 0.755, 95% CI: 0.544, 1.046). These results suggest that rosuvastatin has a more pronounced preventive effect compared to the other treatments evaluated.

[0142] The aforementioned metformin is one of the drugs targeting chronic metabolic diseases; it is used as a treatment for diabetes because it has the effect of preventing glucose production in the liver, reducing glucose absorption in the intestines, and improving insulin sensitivity. The aforementioned aspirin has antipyretic, anti-inflammatory, and analgesic effects at high doses, so the 500mg product is used for arthritis, fever caused by the common cold, muscle pain, etc.; at low doses, it has a thrombopreventive effect, so low-dose products of 100mg or less are used for purposes such as reducing cardiovascular risk caused by blood clots. The aforementioned ezetimibe prevents dietary cholesterol from being reabsorbed into the body in the small intestine, thereby lowering lipid-related levels in the blood; thus, it is used as an adjunct to dietary therapy for cholesterol reduction in patients with hyperlipidemia. The aforementioned ezetimibe is generally used in combination with statins, so if statins alone cannot sufficiently lower blood LDL-C levels, ezetimibe can be added to lower the levels. The aforementioned angiotensin II receptor blockers (ARBs) or angiotensin converting enzyme inhibitors (ACEIs) belong to the category of drugs used to treat chronic metabolic diseases, and more specifically, are used to treat hypertension.

[0143] Drug Cause-specific Fine-Gray Metformin 0.742 (0.484, 1.137) 0.723 (0.472, 1.106) Aspirin 0.706 (0.485, 1.028) 0.690 (0.474, 1.003) Ezetimibe 1.128 (0.752, 1.681) 1.153 (0.748, 1.778) ARB or ACEI 0.972 (0.719, 1.313) 0.967 (0.717, 1.306) Statin 0.749 (0.540, 1.039) 0.755 (0.544, 1.046) Rosuvastatin 0.422 (0.210, 0.863)0.401 (0.180, 0.862)

[0144] 2.6 Preclinical Verification of the Antitumor Activity of Rosuvastatin To investigate the potential antitumor efficacy of rosuvastatin, its cytotoxic effects were first evaluated in the human multiple myeloma cell line RPMI-8226. Cells were treated with increasing concentrations of rosuvastatin or atorvastatin (0, 6.25, 12.5, 25, 50, 100, and 200 μM) for 24, 48, and 72 hours, and cell viability was assessed using the CCK-8 assay. As shown in Figures 17 to 19, both statins exhibited growth inhibitory effects, with cell viability significantly decreasing in a dose- and time-dependent manner. IC50 at the 48-hour time point 50 The values ​​were approximately 119.7 μM for rosuvastatin and 77.14 μM for atorvastatin, showing similar cytotoxic efficacy. Atorvastatin had a slightly lower IC50. 50 Despite showing [unclear], rosuvastatin exhibited a reproducible and sustained inhibitory effect at all test concentrations and time points. These results indicate that rosuvastatin exerts a reproducible cytotoxic effect on multiple myeloma cells and demonstrate the need for further in vivo validation.

[0145] 2.7 Inhibition of Tumor Growth by Rosuvastatin in a Multiple Myeloma Xenograft Model

[0146] To determine whether the clinical association between the use of rosuvastatin and the reduction of multiple myeloma progression corresponds to direct antitumor activity, the effects of this drug in a xenograft mouse model were evaluated as shown in Figures 20 to 25. After 3 weeks of administration, no significant changes in body weight were observed across the treatment groups, confirming excellent tolerability. The rosuvastatin treatment group showed a significant reduction in both tumor volume and weight compared to the control group, whereas atorvastatin monotherapy did not cause significant changes in tumor growth. Bortezomib, the positive control, significantly inhibited tumor growth, validating the experimental model. In particular, the combination of bortezomib and rosuvastatin showed a greater tumor growth inhibitory effect than the administration of each drug alone. To further evaluate tumor cell proliferation, immunohistochemical staining for the cell proliferation marker Ki67 was performed. Tumors in the rosuvastatin-treated group showed a significantly lower proportion of Ki67-positive cells compared to the control group, which is consistent with reduced proliferative activity. In summary, these results demonstrate that rosuvastatin exerts a direct antitumor effect in MM xenograft models, unlike atorvastatin, and support its potential as a therapeutic or chemopreventive agent.

[0147] 2.8 Confirmation of Rosuvastatin-Specific Protein Synthesis and Mitochondrial Pathway Downregulation via Transcriptome Profiling

[0148] As shown in Figures 26 and 27, transcriptome profiling of xenograft tumor tissues was performed to elucidate the mechanism of the antitumor activity of rosuvastatin. Hierarchical clustering analysis of differentially expressed genes (DEGs) confirmed the reliability of the data, as tumors treated with rosuvastatin and bortezomib showed distinct gene expression patterns that clustered separately from the control group. Through volcanic map analysis, 1,311 genes with different expression levels (703 upregulated, 608 downregulated) were identified between the rosuvastatin group and the control group, confirming a significant transcriptome effect.

[0149] As illustrated in Figures 28 and 29, to identify the rosuvastatin-specific antitumor mechanism distinct from lipid metabolism regulation, we focused on non-lipid biological processes, excluding lipid metabolism-related GO terms and pathways that appeared in upstream enrichment due to the standard effects of statins. We analyzed a subset of genes within the region marked by red circles in the Venn diagram, representing genes that are exclusively regulated by rosuvastatin but not by atorvastatin or bortezomib. Analysis of GO and KEGG enrichment revealed dominant enrichment in DNA repair, mRNA processing, protein phosphorylation, and apoptosis, implying the activation of nuclear and protein stability stress adaptations. These genes are primarily associated with localization functions in the nucleus, cytoplasm, mitochondria, and Golgi apparatus, suggesting extensive intracellular reorganization. Enriched molecular activities, including protein / RNA binding and kinase-related functions, further supported the modulation of signaling and transcriptional regulation. Consistently, KEGG pathway mapping confirmed MAPK and TNF signaling, apoptosis, senescence, autophagy, and endocellular uptake, highlighting that rosuvastatin exerts multiple anticancer effects beyond lipid-lowering action through the coordinated regulation of nuclear stress and apoptosis pathways.

[0150] As illustrated in Figures 30 and 31, to further elucidate the specific antitumor mechanism of the combination of rosuvastatin and bortezomib, GO and KEGG abundance analyses were performed on genes (crossed regions indicated by red circles in the Venn diagram) that are commonly regulated during combination therapy but not observed in monotherapy. In the Biological Process (BP) category, in addition to terms related to transcription, translation, and DNA repair observed in rosuvastatin monotherapy, pathways related to protein folding, stabilization, and vesicle-mediated transport were newly enriched. These results imply that combination therapy entails enhanced protein homeostatic regulation and stress-adapting processes. In the Cellular Components (CC) analysis, enrichment of terms related to ribosomes, nucleoli, and ribonucleoprotein complexes was confirmed, in addition to components related to the nucleus, cytoplasm, mitochondria, Golgi apparatus, and organelles identified in monotherapy. This implies extensive intracellular reorganization, including the ribosome-organelle-Golgi apparatus axis, during combination therapy. In the molecular function (MF) category, activities such as ATPase, GTPase, and metal ion binding were additionally enriched, complementing the protein / RNA binding and kinase activities observed with rosuvastatin monotherapy. Consistently, KEGG pathway analysis showed that, in addition to the MAPK, TNF, apoptosis, and senescence pathways enriched by rosuvastatin monotherapy, combination therapy additionally activated ribosomal, ER protein processing, proteasome, RNA degradation, and cell cycle pathways.

[0151] Taken together, these results show that combination therapy with rosuvastatin and bortezomib induces more extensive transcriptomic and proteostatic alterations compared to monotherapy, which implies a broader stress response network associated with enhanced antitumor effects.

[0152] The present invention relates to a cancer prevention composition comprising a statin as an active ingredient.

Claims

1. A pharmaceutical composition for cancer prevention comprising a statin as an active ingredient.

2. A pharmaceutical composition according to claim 1, wherein the statin is rosuvastatin.

3. A pharmaceutical composition according to claim 1, wherein the cancer is multiple myeloma.

4. A pharmaceutical composition containing a statin as an active ingredient for inhibiting progression to multiple myeloma in monoclonal gamma of unknown significance (MGUS).

5. A pharmaceutical composition according to claim 4, wherein the statin is rosuvastatin.

6. A pharmaceutical composition containing a statin as an active ingredient for inhibiting progression from smoldering multiple myeloma (SMM) to multiple myeloma.

7. A pharmaceutical composition according to claim 6, wherein the statin is rosuvastatin.

8. A pharmaceutical composition for the prevention of multiple myeloma in individuals with metabolic disease, comprising rosuvastatin.

9. A pharmaceutical composition comprising rosuvastatin for inhibiting progression to multiple myeloma in monoclonal gammopathy of unknown significance (MGUS) in individuals with metabolic disease.

10. A pharmaceutical composition comprising rosuvastatin for inhibiting progression from smoldering multiple myeloma (SMM) to multiple myeloma in individuals with metabolic disease.

11. A pharmaceutical composition for co-administration comprising a statin as an active ingredient.

12. A pharmaceutical composition for co-administration according to claim 11, wherein the statin is rosuvastatin.

13. A pharmaceutical composition for co-administration, wherein the statin is administered in combination with bortezomib, according to claim 11.

14. A pharmaceutical composition for co-administration containing a statin as an active ingredient to inhibit progression to multiple myeloma in monoclonal gammopathy of unknown significance (MGUS).

15. A pharmaceutical composition for co-administration, wherein the statin is administered in combination with bortezomib, according to claim 14.

16. A pharmaceutical composition for co-administration containing a statin as an active ingredient to inhibit progression from smoldering multiple myeloma (SMM) to multiple myeloma.

17. A pharmaceutical composition for co-administration, wherein the statin is administered in combination with bortezomib according to claim 16.

18. A pharmaceutical composition for co-administration of the prophylaxis of multiple myeloma in individuals with metabolic disease, comprising rosuvastatin.

19. A pharmaceutical composition for the co-administration of multiple myeloma prevention, wherein the rosuvastatin of claim 18 is administered in combination with bortezomib.

20. A pharmaceutical composition for co-administration containing rosuvastatin to inhibit progression to multiple myeloma in monoclonal gammopathy of unknown significance (MGUS) in individuals with metabolic disease.

21. A pharmaceutical composition for co-administration, wherein the rosuvastatin is administered in combination with bortezomib in accordance with claim 20.

22. A pharmaceutical composition for co-administration containing rosuvastatin to inhibit progression from smoldering multiple myeloma (SMM) to multiple myeloma in individuals with metabolic disease.

23. A pharmaceutical composition for co-administration, wherein the rosuvastatin is administered in combination with bortezomib according to claim 22.

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