Cancer treatment using DRQ polypeptides

Abstract

A method is provided for treating a subject with cancer using a recombinant polypeptide comprising a DRα1 domain containing a glutamine residue at the position corresponding to amino acid 45 of SEQ ID NO: 1 or SEQ ID NO: 2, or an antigenic peptide covalently bound to a portion thereof. In some cases, the subject has a tumor that is resistant to immune checkpoint blockade treatment and / or does not express a BRAF mutation. The present invention provides, for example, a method for treating a subject with cancer, comprising administering to the subject a therapeutically effective amount of a recombinant polypeptide comprising a DRα1 domain containing a glutamine residue at the position corresponding to amino acid 50 of SEQ ID NO: 1 or SEQ ID NO: 2, or an antigenic peptide covalently bound to a portion thereof; or a nucleic acid encoding the recombinant polypeptide.

Description

[Technical Field]

[0001] Cross-reference of related applications This application claims the benefit and priority of U.S. Provisional Application No. 63 / 469,261, filed on 26 May 2023, the entire contents of which are thus incorporated herein by reference.

[0002] field This application relates to a method for treating cancer using an antigenic peptide and a DRQ polypeptide containing a modified DRα1 domain.

[0003] Approval of government support This invention was made with government support under AI122574, issued by the National Institutes of Health. The government has certain rights in this invention.

[0004] Sequence List The sequence listing was submitted as an XML file in the form of a file named "Sequence.xml" (7,000 bytes) created on May 24, 2024, and is incorporated herein by reference. [Background technology]

[0005] background Melanoma is a deadly skin cancer, and its incidence is increasing. Novel therapies, including immune checkpoint blockades (ICBs), have improved survival, but these ICB therapies are only 30-40% effective as monotherapy. Overall survival improves to 57% with anti-PD-1 plus anti-CTLA-4, but this comes with serious side effects that are not tolerable for all patients. The remaining patients either do not respond (primary resistance) or initially respond but stop (secondary resistance). Secondary resistance affects 22-60% of initial responders. Novel drugs and personalized vaccines are being developed, but these patients, especially those without BRAF mutations, have no other good treatment options.

[0006] Glioblastoma (GBM) is the most common, highly invasive, and aggressive primary brain tumor, and the prognosis for patients with glioblastoma is extremely poor, with an average overall survival of 8 to 15 months. The current course of treatment involves maximum safe resection followed by radiotherapy and a 6 to 12 month course of chemotherapy with the alkylating agent temozolomide. This treatment has only slightly improved median survival by approximately 2 months in people aged 40 or older. In addition, treatment with intravascular coagulation (ICB) has not demonstrated activity or efficacy in primary malignant gliomas.

[0007] Breast cancer (BC) is the most common malignant disease affecting women worldwide.[1] BC is a heterogeneous disease comprised of different subtypes. Classification of BC depends on the expression of three biomarkers: estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2). BC that is negative for ER, PR, and HER2 is known as triple-negative breast cancer (TNBC).[2] TNBC is considered the most invasive BC subtype, and its clinical features include high invasiveness, high metastatic potential, recurrence tendency, and poor prognosis.[3, 4] TNBC has been shown to feature a distinctive microenvironment (ME). TNBC cells manipulate their ME to be immunosuppressive, making this tumor a good candidate for immunotherapy.[5] Dendritic cells (DCs) are antigen-presenting cells (APCs) essential for regulating innate and adaptive immune responses. The multiple functions of dendritic cells (DCs) in immunomodulation reflect their complexity, as well as their heterogeneous subsets with different lineages, locations, phenotypes, and functional plasticity [6]. DCs play a crucial role in tumor immunity, capable of cross-presenting tumor-associated antigens (TAAs) to T cells. By manipulating their microenvironment, tumor cells may disrupt DC function, reduce T cell activation, and potentially induce T cell tolerance to TAAs [7]. Tumors can also enhance immunomodulatory transcriptional programs that limit the production of pro-inflammatory cytokines mediated by DCs and increase the release of IL-10 and indoleamine dioxygenase-1 (IDO1), which promote immunosuppression. IL-10-producing DCs force T cell anergy and are called tol-DCs. IL-10 expression in DCs is considered a tolerogenic signature that leads to Treg induction [8]. B cells also play an important role in tumor ME. In addition to their roles in regulating humoral immune responses and their ability to produce antibodies and cytokines, certain B cell populations known as Bregs possess regulatory properties that are important for maintaining immune tolerance.[9] Bregs exert their functions primarily through the release of IL-10.The immunosuppressive function of Bregs is involved in multiple mechanisms, including the tilting of T cell differentiation, induction and maintenance of Tregs, and suppression of pro-inflammatory cells

[10] .

[0008] CD74(chain II) is a non-polymorphic type II transmembrane protein primarily expressed on the surface of APCs and was initially thought to function solely as an MHC class II chaperone

[11] . A small portion of the CD74 molecule undergoes posttranslational modification, enabling its cell surface expression

[12] . Cell surface CD74 functions as a receptor for ligands of the macrophage migration inhibitory factor (MIF) family, including the cytokines MIF-1 (MIF) and MIF-2 / D-dopachrome tautomerase (DDT)

[13] . Upon MIF binding, CD74 forms a cell surface complex with CD44, which is essential for the MIF-induced signaling cascade. The signaling pathway involves Syk tyrosine kinase and PI3K / Akt activation, leading to intramembrane cleavage of CD74 and release of the CD74 intracellular domain (CD74-ICD). CD74-ICD translocates to the nucleus, where it induces B cell proliferation and survival [14-20]. Interestingly, both MIF and CD74 are associated with tumor progression and metastasis. MIF mRNA has been reported to be overexpressed in a variety of tumors [21, 22], and MIF is also associated with malignant cell growth

[23] . Numerous studies have demonstrated that CD74 expression is upregulated in a variety of cancers, including chronic lymphocytic leukemia (CLL) [30, 31] [24-29], and correlates with poor prognosis. In particular, CD74 expression is upregulated in patients with TNBC compared to other breast cancer subtypes, is associated with lymph node metastasis, and leads to poor overall survival [32, 33]. CD74 expression has also been suggested to function as a prognostic factor in many of these cancers, with higher relative expression of CD74 acting as a marker of tumor progression

[34] . While it is well known that CD74 plays an important role in hematological malignancies such as CLL

[35] , and that its expression correlates with poor prognosis, its function and mechanisms in TNBC are not fully understood.

[0009] Therefore, improved treatments remain needed for melanoma, glioblastoma, breast cancer, and other cancers, particularly for tumors that do not respond to or are resistant to ICB therapy. [Overview of the Initiative] [Means for solving the problem]

[0010] overview Methods for treating cancer using DRQ polypeptides or nucleic acids, and compositions comprising DRQ polypeptides or nucleic acids are provided herein. In some embodiments, the method comprises administering a therapeutically effective amount of a recombinant polypeptide comprising an antigenic peptide covalently bound to a DRα1 domain or a portion thereof, which includes a glutamine residue at the position corresponding to amino acid 50 of SEQ ID NO: 1 or SEQ ID NO: 2, or a nucleic acid encoding the recombinant polypeptide, to a subject having cancer. In some examples, the recombinant polypeptide further comprises a linker or spacer between the antigenic peptide and the DRα1 domain. In one example, the linker comprises a first glycine-serine spacer, a thrombin cleavage site, and a second glycine-serine spacer.

[0011] In some embodiments, the antigenic peptide is myelin oligodendrocyte glycoprotein (MOG)-35-55, for example, human MOG-35-55 or mouse MOG-35-55. In some examples, the recombinant polypeptide contains or comprises the amino acid sequence of SEQ ID NO: 1 or SEQ ID NO: 2.

[0012] In some embodiments, subjects are administered recombinant polypeptides at a dose of approximately 0.1 mg / kg to approximately 10 mg / kg. In additional embodiments, the cancer is a solid tumor, such as melanoma, glioblastoma, or breast cancer. In further embodiments, the cancer of the subject does not express the BRAF V600 mutation, or the subject with cancer is resistant to immune checkpoint blockade therapy, or both.

[0013] The disclosed method may further include a step of administering one or more additional treatments. In some examples, one or more additional treatments include one or more of surgery, radiation, chemotherapy, and immunotherapy. In certain examples, immunotherapy includes immune checkpoint blockade therapy.

[0014] The aforementioned and other features of this disclosure will become more apparent from the following detailed description, which will proceed with reference to the attached figures. [Brief explanation of the drawing]

[0015] [Figure 1] Figure 1 is a Kaplan-Meier plot showing reduced overall survival in a sample of patients with advanced melanoma exhibiting higher MIF expression. [Figure 2] Figure 2 shows a graph illustrating the reduced MIF production in B16F10 cells grown with DRmQ compared to the vehicle control. [Figure 3] Figure 3 shows the growth lines of intradermal B16F10 mouse melanoma models treated with vehicle control or DRmQ (P<0.05 by unpaired two-sided t-test). [Figure 4] Figure 4 shows micrographs illustrating the effect of DRQ treatment on immune infiltration in B16F10 melanoma tumors. [Figure 5] Figure 5 presents a plot illustrating that, as measured by TRP2-PE tetramer, DRQ (top) increases the infiltration of TRP2-reactive CD8+ cells compared to vehicle control (bottom). [Figure 6] Figure 6 presents Western blots showing pSTAT3, pAKT, and pERK in B16F10 cells incubated with no tx (no tx), vehicle, or 50 μg of DRQ for 1 hour. [Figure 7A] Figure 7A presents line and bar graphs of 5-day measurements of tumor progression adjusted for CD74. [Figure 7B-C]Figure 7B shows a photograph of tumors excised and measured from mice euthanized after 21 days of growth. Figure 7C shows a bar graph plotting tumor volume, with each point representing an excised tumor. [Figure 7D-E] Figure 7D shows a bar graph plotting the mean and SD percentage of dendritic cells (DCs) in the tumor site (WT n=11; CD74- / - n=8). Figure 7E shows a bar graph plotting CD80+ DCs as a percentage of all DCs (WT n=11; CD74- / - n=8). [Figure 7F-G] Figure 7F shows a bar graph plotting tolerance-genic DCs analyzed for IL-10 among all DCs. Figure 7G shows a graph showing the mean and SD percentage of FOXP3+ T cells among all CD4+ T cells (WT n=8; CD74KO n=8). [Figure 7H-I] Figure 7H shows a graph of the mean and SD percentage of IL-10+ B cells among all B cells (WT n=8; CD74 KO n=7). Figure 7I shows a graph of the mean and SD percentage of IFN-γ+ T cells among all CD8+ T cells (WT n=5; CD74 KO n=4). [Figure 7J-K] Figure 7J shows a photograph of the tumor measured after 21 days of growth. Figure 7K shows a graph of the tumor volume measured after 21 days of growth. [Figure 7L-M] Figure 7L presents a graph showing IL-10+ DCs as a percentage of all DCs (n=8 for PBS; n=8 for DRQ). Figure 7M presents a graph showing IL-12+ DCs as a percentage of all DCs (n=4 for PBS; n=4 for DRQ). [Figure 7N-O] Figure 7N shows graphs representing the mean and SD percentage of IL-10+ B cells among all B cells (n=7 for PBS; n=8 for DRQ). Figure 7O shows graphs representing the mean and SD percentage of Treg cells among all CD4+ cells (n=7 for PBS; n=8 for DRQ). [Figure 8A-B] Figure 8A shows a graph illustrating the MIF-CD74 axis regulation of tol-DC and Breg expansion. Figure 8B shows a graph illustrating the fold change of Breg expansion in B cells under different culture conditions (WT n=21; CD74KO n=21). [Figure 8C-D] Figure 8C shows graphs of the mean and SD percentage of IL10+ DCs among all dendritic cells (WT+PBS n=12; WT+MIF n=13). Figure 8D shows graphs of the mean and SD percentage of Bregs among B cells (WT+PBS n=12; WT+MIF n=12). [Figure 8E-F] Figure 8E shows a graph of MIF mRNA levels analyzed by qRT-PCR. The graph shows the polyploidy changes (siRNA / siCtrl) of the selected genes (n=3). Figure 8F shows graphs of the mean and SD percentage of IL10+DCs among all dendritic cells (WT+Sico E0771 n=13; WT+siMIF n=13). [Figure 8G] Figure 8G presents bar graphs showing the mean and SD percentage of Breg cells (WT+Sico E0771 n=14; WT+siMIF n=14). [Figure 9A-B] Figure 9A provides a graph of tumor size (n=22) measured and recorded at 21 days. Figure 9B provides a graph of IL-10+ DCs analyzed as a percentage of all DCs (n=8 for WT; n=7 for conditional CKO). [Figure 9C-D] Figure 9C provides graphs of the mean and SD percentage of IL-12+ dendritic cells among all DCs (n=5 for WT; n=5 for CKO). Figure 9D provides graphs of the mean and SD percentage of IL-10-B cells among all CD19+ cells (n=6 for WT; n=6 for CKO). [Figure 9E] Figure 9E provides graphs showing the mean and SD percentage of IL10+ DCs among all dendritic cells (WT n=5; CKO n=5). [Figure 9F] Figure 9F provides a graph showing the mean and SD percentage of Breg cells among B cells (WT n=7; CKO n=7). [Figure 10A] Figure 10A provides a line graph of tumor sizes recorded every 5 days from 6-week-old female CD11c-Cre×CD74flox×CD74 flox mice after injection of 5*10⁵ E0771 cells into each of the fourth mammary gland pads. [Figure 10B-C] Figure 10B presents photographs of tumor sizes (n=44) measured and recorded 21 days later. Figure 10C presents a graph of tumor volume, where each point represents an individual tumor. [Figure 10D-E] Figure 10D shows a graph of IL-10+ DCs analyzed as a percentage of all DCs (WT n=13; conditional CKO n=12). Figure 10E shows graphs of the mean and SD percentage of IL-10+ B cells among all B cells (WT n=12; CKO n=11). [Figure 10F-G] Figure 10F shows graphs of the mean and SD percentage of Treg cells among all CD4+ cells (WT n=13; CKO n=10). Figure 10G shows graphs of the mean and SD percentage of tumor-infiltrating CD8+ T cells among all CD3+ T cells (WT n=13; CKO n=12). [Figure 10H-I] Figure 10H shows graphs of the mean and SD percentage of IFN-γ-releasing T cells among all CD8+ T cells (WT n=4; CKO n=4). Figure 10I shows graphs of the mean and SD percentage of PD1+ T cells among all CD8+ T cells (WT n=4; CKO n=4). [Figure 10J] Figure 10J presents graphs of the mean and SD percentage of IL10+ DCs among all dendritic cells (WT n=8; conditional CD74 KO n=8). [Figure 10K] Figure 10K shows graphs of the mean and SD percentage of Breg cells among B cells (WT n=8; conditional CD74- / - n=8). [Figure 11A-B]Figure 11A shows graphs of the mean and SD percentage of IL10+ dendritic cells among all dendritic cells under different culture conditions (WT DC+WT B cells n=8; CD75T4 KO DC+WT B cells n=8; WT DC+CD74 KO B cells n=8; CD74- / -DC+CD74 KO B cells n=8). Figure 11B shows graphs of the mean and SD percentage of IL10+ B cells among all B cells under different culture conditions (WT DC+WT B cells n=8; CD74 KO DC+WT B cells n=8; WT DC+CD74 KO B cells n=8; CD74 KO DC+CD74 KO B cells n=8). [Figure 11C-D] Figure 11C presents graphs showing the mean and SD percentage of IL10+ B cells among all B cells (B cells + WT DC CM n=10; B cells + CD74 cKO DC CM n=10). Figure 11D presents graphs showing the mean and SD percentage of IL10+ dendritic cells among all DCs (IGg-treated DC + B cells n=8; LN-2-treated DC + B cells n=8). [Figure 11E-F] Figure 11E presents graphs showing the mean and SD percentage of proliferative CD8+ T cells under different culture conditions (WT n=14; CD74 KO n=15). Figure 11F presents graphs showing the mean and SD percentage of FOXP3+CD4+ T cells under the indicated culture conditions (WT n=9; CD74- / - n=11). [Figure 11G] Figure 11G presents a graph showing the percentage of IFN-γ+CD8+ T cells (WT n=14; CD74 KO n=15). [Figure 12A-B] Figure 12A presents a graph showing the multiplicative change in SP1 mRNA levels after injection of 5*10⁵ E0771 cells into each of the fourth mammary pads of 6-week-old female C57BL / 6 mice. Figure 12B presents a graph showing the multiplicative change in IL1β mRNA levels after injection of 5*10⁵ E0771 cells into each of the fourth mammary pads of 6-week-old female C57BL / 6 mice. [Figure 12C-D]Figure 12C shows a graph illustrating the multiplicative change of SP1 in WT and CD74 KO mice (n=6). Figure 12D shows a graph illustrating the multiplicative change of IL1β in WT and CD74 KO mice (n=6). [Figure 13A-B] Figure 13A presents graphs showing the mean and SD percentage of IL10+ dendritic cells among all DCs (DC + vehicle = 18; DC + IL1β n = 20). Figure 13B presents graphs showing the mean and SD percentage of IL10+ B cells among all B cells and IL10+ DCs among all dendritic cells (PBS-treated B cells + DC, n = 5; IL-1β-treated B cells + DC, n = 5). [Figure 13C-D] Figure 13C presents graphs showing the mean and SD percentage of IL10+ B cells out of all B cells (PBS-treated B cells n=10; IL-1β-treated B cells n=10; PBS-treated B cells + DC n=10; IL-1β-treated B cells + DC n=10). Figure 13D presents graphs showing the percentage of enrichment relative to the input (the amount of DNA pulled down by using the target antibody in the ChIP reaction relative to the amount of starting material - input sample) (n=44). [Figure 14A-B] Figure 14A shows a graph illustrating the multiplicative change in the expansion of IL10+ dendritic cells among all DCs (DC+DMSO=10; DC+MIT n=10), with each point representing a mouse. Figure 14B shows a graph illustrating the multiplicative change in IL10+ B cells among all B cells and IL10+ DCs among all dendritic cells (DMSO-treated B cells n=5; mitramycin-treated B cells n=5). [Figure 14C-D] Figure 14C presents graphs showing the mean and SD percentage of IL10+ B cells out of all B cells (DMSO-treated B cells n=10; MIT-treated B cells n=10; DMSO-treated B cells + DC n=10; MIT-treated B cells + DC n=10). Figure 14D presents graphs showing the percentage of enrichment relative to the input (amount of DNA pulled down by CD74 antibody in the ChIP reaction relative to the amount of starting material - input sample) (n=5). [Figure 14E-F] Figure 14E presents a graph showing the binding of CD74-ICD in DCs activated with mrMIF (n=5). Figure 14F presents a graph showing the percentage of enrichment relative to the input in DCs activated with mrMIF, DRQ, or vehicle (the amount of DNA pulled down by using the SP1 antibody in the ChIP reaction relative to the amount of starting material - input sample) (n=14). [Figure 14G] Figure 14G presents graphs showing the mean and SD percentage of IL-1β+ DCs among all DCs (8 DCs treated with DMSO, 8 DCs treated with MIT). [Figure 15A] Figure 15A presents a box plot analysis showing the relative expression levels of CD74 in several immune cell populations. [Figure 15B-C] Figure 15B presents graphs showing the mean and SD percentage of CD74 expression on B cells in the spleen and TME (B cells in the spleen n=4; B cells in the TME n=4). Figure 15C presents graphs showing the mean and SD percentage of CD74 expression on dendritic cells in the spleen and TME (dendritic cells in the spleen n=4; dendritic cells in the TME n=4). [Figure 16A-B] Figure 16A shows the analysis of CD11c expression in DC cells after excluding LY6-C+, F4 / 80+, and CD19. B cells were analyzed for CD19 after excluding LY6-C+, F4 / 80+, and CD11c. Figure 16B provides a plot showing the analysis of IL-10+ expression on DCs, measured by comparing inactivated (mono WT) 1,24 with PIM-activated IL-10+ on DCs. [Figure 16C-D] Figure 16C provides a plot showing the analysis of IL-10+ expression on DCs, measured by comparing inactivated (WT) 52,6 with PIM-activated IL-10+. Figure 16D provides a plot showing the analysis of IL-10+ expression on DCs, measured by comparing inactivated (mono cKO) 1,22 with PIM-activated IL-10+. [Figure 16E-F] Figure 16E provides a plot showing the analysis of IL-10+ expression on DCs, measured by comparing inactive (CKO) 3,13 with PIM-activated IL-12+ expression on DCs. Figure 16F provides a plot showing IL-12+ expression on DCs, measured by comparing inactive (mono WT) 6,89 with PIM-activated IL-12+ expression on sample subsets. [Figure 16G-H] Figure 16G provides a plot showing IL-12+ expression on DCs, measured by comparing inactivated (WT) 7,95 with PIM-activated 7,95 for a sample subset. Figure 16H provides a plot showing IL-12+ expression on DCs, measured by comparing inactivated (mono KO) 7,33 with PIM-activated 7,33 for a sample subset. [Figure 16I-J] Figure 16I provides a plot representing IL-12+ expression on DCs, measured by comparing inactivated (KO) 13,9 for sample subsets with those activated by PIM. Figure 16J provides a plot representing IL-10+ expression on B cells, measured by comparing inactivated IL-10+ for either WT or CD74- / - samples with those activated by PIM. [Figure 16K-L] Figure 16K provides a plot representing IL-10+ expression on B cells, measured by comparing inactivation with PIM-activated IL-10+ in either WT or CD74- / - samples. Figure 16L provides a plot representing IL-10+ expression on B cells, measured by comparing inactivation with PIM-activated IL-10+ in either WT or CD74- / - samples. [Figure 16M] Figure 16M provides a plot representing IL-10+ expression on B cells, measured by comparing inactivation with PIM-activated IL-10+ for either WT and CD74- / - samples. [Figure 17A-B]Figure 17A shows a graph representing the frequency of IL-10+ B cells among all B cells (WT n=8; CD74- / - n=7). Figure 17B shows a graph representing the frequency of IL-10+ DCs in tumor sites relative to DC cells, after excluding LY6-C+, F4 / 80+, and CD19+ cells, and analyzing CD45, CD11c, and IL-10 expression (WT n=14; CD74- / - n=11). [Figure 17C-D] Figure 17C shows a graph representing the frequency of IL-10+ macrophages after excluding monocytes and DCs (WT n=5; CD74- / - n=5). Figure 17D shows a graph representing the frequency of CD4+ T cells (WT n=9; CD74- / - n=8). [Figure 17E-F] Figure 17E shows a graph representing the frequency of CD8+ T cells (WT n=9; CD74- / - n=8). Figure 17F shows a graph representing the frequency of IFN-γ+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=4). [Figure 17G-H] Figure 17G shows a graph representing the frequency of IFN-γ+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=4). Figure 17H ​​shows a graph representing the frequency of PD1+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=4). [Figure 17I] Figure 17I shows a graph representing the frequency of CD62L+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=5). [Figure 18A] Figure 18A shows a graph representing the frequency of IL-10+ B cells among all B cells (PBS n=7; DRQ n=8). [Figure 18B-C] Figure 18B shows a graph representing the frequency of IL-10+ DCs in the tumor site (PBS n=8; DRQ n=8). Figure 18C shows a graph representing the frequency of CD4+ T cells (PBS n=4; DRQ n=5). [Figure 18D-E]Figure 18D shows a graph representing the frequency of FOXP3+ T cells among all CD4+ T cells (PBS n=4; DRQ n=5). Figure 18E shows a graph representing the frequency of CD8+ T cells (PBS n=4; DRQ n=5). [Figure 19A-B] Figure 19A shows graphs representing the mean and SD percentage of monocytes among all living cells (WT n=5, cKO n=5). Figure 19B shows graphs representing the mean and SD percentage of macrophages among all living cells (WT n=5, cKO n=5). [Figure 19C-D] Figure 19C shows graphs representing the average and SD percentage of B cells among all viable cells (WT n=5, cKO n=5). Figure 19D shows graphs representing the DC / viable cell percentage. [Figure 19E-F] Figure 19E shows graphs representing the mean and SD percentage of CD74 expression on monocytes. Figure 19F shows graphs representing the mean and SD percentage of CD74 expression on macrophages. [Figure 19G-H] Figure 19G shows graphs representing the mean and SD percentage of CD74 expression on B cells. Figure 19H shows graphs representing the mean and SD percentage of CD74 expression on DCs. [Figure 19I-J] Figure 19I shows graphs representing the mean and SD percentage of CD4+ T cells among all living cells (WT n=6; cKO n=6). Figure 19J shows graphs representing the mean and SD percentage of CD8+ T cells among all living cells (WT n=6; cKO n=6). [Figure 19K-L] Figure 19K shows graphs representing the mean and SD percentage of CD62L+ T cells out of all CD4+ T cells (WT n=6; cKO n=6). Figure 19L shows graphs representing the mean and SD percentage of CD103+ T cells out of all CD8+ T cells (WT n=6; cKO n=6). [Figure 19M-N]Figure 19M shows a graph representing the mean and SD percentage of FOXP3+ T cells among all CD4+ T cells (WT n=4; cKO n=4). Figure 19N shows a graph representing CD74 expression in the CD4+ population. [Figure 19O] Figure 19O shows a graph representing CD74 expression in the C84+ population. [Figure 20A] Figure 20A presents a plot showing dead cells excluded from the analysis by Zombie live / dead staining. [Figure 20B-C] Figure 20B presents a plot showing that macrophages and monocytes were gated against F4 / 80 and LY-6c, respectively. Figure 20C presents a plot showing that the double-negative population was analyzed against CD19 and CD11c to detect DCs and B cells. [Figure 20D-E] Figure 20D presents a plot showing the analysis of dendritic cells (DCs) obtained in Figure 20C for CD26. Figure 20E presents a plot showing that the CD45+ population was gated for CD26 as a dendritic cell marker. [Figure 20F-G] Figure 20F shows a plot illustrating that the CD45+ population was gated against CD26 as a dendritic cell marker. Figure 20F also shows a plot illustrating that CD26+ DCs were analyzed against F4 / 80. Figure 20G shows a plot illustrating that CD26+ DCs were analyzed against LY-6c. [Figure 20H-I] Figure 20H presents a plot showing that CD26+DCs were analyzed against CD19. Figure 20I presents a plot showing that the CD45+ population was gated against CD64 as a macrophage marker. [Figure 20J] Figure 20J presents a plot showing the analysis of CD64+ macrophages against CD19 and LY-6c expression. [Figure 21A-B]Figure 21A presents graphs showing the mean and SD percentage of IL-10+ monocytes out of total monocytes at day 21 after injection of 5*10⁵ E0771 cells into each of the fourth mammary pads of 6-week-old female CD23-Cre×CD74flox×CD74flox mice (WT n=4, cKO n=4). Figure 21B presents graphs showing the mean and SD percentage of IL-12+ monocytes out of the entire population (WT n=4, cKO n=4). [Figure 21C-D] Figure 21C shows graphs representing the mean and SD percentage of IL-10+ macrophages among all macrophages (WT n=4, cKO n=4). Figure 21D shows graphs representing the mean and SD percentage of IL-12+ macrophages among all macrophages (WT n=4, cKO n=4). [Figure 22A-B] Figure 22A shows a graph representing the frequency of IL-10+ B cells among all B cells 21 days after injection of 5*10⁵ E0771 cells into each of the fourth mammary pads of 6-week-old female CD23-Cre×CD74flox×CD74flox mice (WT n=7; cKO n=7). Figure 22B shows a graph representing the frequency of IL-10+ DCs in the tumor site (WT n=8; CD74 cKO n=7). [Figure 22C-D] Figure 22C shows a graph representing the frequency of CD4+ T cells (WT n=7; CD74 cKO n=8). Figure 22D shows a graph representing the frequency of FOXP3+ T cells among all CD4+ T cells (WT n=4; CD74 cKO n=4). [Figure 22E-F] Figure 22E shows a graph representing the frequency of CD8+ T cells (WT n=8; CD74 cKO n=7). Figure 22F shows a graph representing the frequency of PD1+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). [Figure 22G-H]Figure 22G shows a graph representing the frequency of IFN-γ+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). Figure 22H shows a graph representing the frequency of CD103+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). [Figure 22I] Figure 22I shows a graph representing the frequency of CD62L+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). [Figure 23A] Figure 23A shows a visualization of Ingenuity Pathway Analysis (IPA), where related pathways are ordered according to their significance (p-value) calculated in IPA using right-tailed Fisher's exact t-test. [Figure 23B] Figure 23B shows the IPA Upstream Regulator Analysis used to predict the upstream regulators involved in the observed changes in gene expression. [Figure 23C] Figure 23C illustrates a gene interaction in which some genes are upregulated and others are repressed. [Modes for carrying out the invention]

[0016] array Any nucleic acid and amino acid sequences listed herein are indicated using standard single-letter abbreviations for nucleotide bases and amino acids, as defined in 37 C.FR §1.822. In at least some cases, only a single strand of each nucleic acid sequence is shown, but any reference to the shown strand is understood to include a complementary strand.

[0017] Sequence ID 1 is the amino acid sequence of an exemplary DRhQ polypeptide. DRhQ contains the antigenic peptide human MOG-35-55 (bold), a spacer (underlined), and a modified DRα1 domain (italicized). The L50Q mutation in the DRα1 portion is shown in bold italics: [ka]

[0018] Sequence ID 2 is the amino acid sequence of an exemplary DRmQ polypeptide. DRmQ contains the antigenic peptide mouse MOG-35-55 (bold), a spacer (underlined), and a modified DRα1 domain. The L50Q mutation in the DRα1 portion is shown in bold italics: [ka]

[0019] Sequence ID 3 is an exemplary nucleic acid encoding the DRhQ polypeptide: [ka] [ka]

[0020] Sequence ID 4 is an exemplary nucleic acid encoding the DRmQ polypeptide: [ka]

[0021] Sequence ID 5 is myelin basic protein (MBP) peptide 85-99: PVVHFFKNIVTPRT

[0022] Detailed explanation CD74 is a highly conserved molecule with multiple functions. The CD74 "CLIP" peptide plays a crucial role in the loading of antigenic peptides onto class II MHC molecules within cells. The macrophage migration inhibitory factor (MIF) binding domain for CD74 is extracellular, does not overlap with CLIP, and can be expressed by multiple cell types, including melanoma, independently of its role within the MHC II complex. Upon binding to MIF, CD74 undergoes phosphorylation of its cytoplasmic domain, initiating downstream signal transduction by activating Lck protein tyrosine kinase, followed by activation of MAPK kinase (MEK), which leads to phosphorylation of ERK1 / 2. In addition, the AKT and PI3K pathways can be upregulated by MIF.

[0023] CD74 expression is significantly upregulated in different cell types across various cancers [24–29] and correlates with tumor progression. MIF, a pro-inflammatory cytokine that functions as a ligand for CD74, has previously been shown to be required for immunosuppressive ME in melanoma and glioblastoma [48, 49]. It has been found to be overexpressed in several tumor types, including TNBC

[50] . The MIF-CD74 axis has been shown to play a crucial role not only in initiating oncogenic signaling pathways but also in inducing inflammatory responses, thereby promoting tumor growth and an immunosuppressive environment [51–53]. However, the function of CD74 in the immune cellular environment of TNBC ME has not been reported, and the functions of DCs and Bregs in this context have also not been analyzed.

[0024] This disclosure demonstrates that TNBC cells secrete MIF, which binds to CD74 expressed on DCs and B cells, inducing a phenotypic shift from immunogenic to tolerogenic. Blocking CD74 leads to a reduction in tumor burden due to increased activity of tumor-infiltrating immune cells. This antitumor phenotype is primarily caused by a decrease in IL-10 secretion, resulting in an overall reduction in suppressive Bregs, Tregs, and tol-DCs in the TME.

[0025] Bregs and tol-DCs in TNBC MEs can influence each other, enhancing IL-10 release via a positive feedback loop

[54] . Feedback loops between tol-DCs and Bregs have been previously demonstrated in several processes, including T cell clonal anergy and Treg expansion, highlighting the complexity of mediators involved in the development and maintenance of tolerance. This crosstalk can be a double-edged sword, for example, beneficial in autoimmune cases but detrimental in cancer cases [55-57].

[0026] This disclosure shows that DCs significantly dominate Breg expansion via the CD74 induction pathway. However, Bregs cannot control DC differentiation, supporting the hypothesis that DCs play a major role among tumor-infiltrating immune cells. Tumor-infiltrating immune cells communicate among themselves and have synergistic effects.

[58]

[0027] This disclosure also demonstrates that DCs regulate B cells and induce their immunosuppressive phenotype by modulating the expression of several genes involved in the immune response, resulting in upregulation of IL-10 expression. Activation of CD74 leads to the binding of CD74-ICD, which functions as a transcription regulator, to the SP1 and IL-1β promoters in DCs [20, 47], increasing their mRNA expression and suggesting that CD74-ICD functions as a transcription regulator in DCs, in addition to its role in B cells. Higher levels of SP1 expression

[43] reduce the expression of the pro-inflammatory cytokine IL-1β

[59] , and increased IL-10 secretion from the DC population is associated with immunosuppression in TNBCs. Thus, these DCs are less immunogenic and enhance the expansion of immunosuppressive cells

[46] .

[0028] Embodiments of this disclosure define the role of IL-1β, particularly in DC populations within the tumor microenvironment, where IL-1β is known to modulate their inflammatory activity through IL-12 production. CD74-deficient DCs can promote immunogenic responses via IL-1β release, leading to inhibition of Breg growth. According to this disclosure, the effect of DC-mediated IL-1β secretion appears to outweigh its direct effect on the B cells themselves, suggesting that IL-1β-releasing DCs hinder the growth of the Breg population. While studies on the role of IL-1β in regulatory B cells have been conducted primarily in autoimmune diseases, the environment and cytokines are quite different from those in TMEs

[60] . Cytokines are known to have different functions in different contexts and cells, and therefore it is suggested that IL-1β may function differently within immune cells in autoimmune or cancer contexts.

[0029] Therefore, blocking the CD74 induction pathway leads to downregulation of SP1 expression in DCs and upregulation of IL-1β secretion, which in turn strongly reduces Breg expansion and activates the immune response. More IL-1β secretion from DCs is determined by both the direct action of CD74 on its promoter and the indirect action of the MIF-CD74-SP1 axis. Thus, CD74 may function as a novel therapeutic target in melanoma and triple-negative breast cancer.

[0030] A method for treating cancer using a class of peptide agents that block extracellular signaling by MIF by binding to CD74 and partially blocking downstream signaling via phosphorylated extracellular-associated kinases (pERK1 / 2) is disclosed herein. The agent, called DRQ, is a partial MHC class II protein construct linked to a myelin oligodendrocyte glycoprotein peptide (MOG-35-55). DRQ binds to CD74 and competitively inhibits MIF signaling (Meza-Romero et al., Metab Brain Dis. 34:153-164, 2019). Preliminary data suggest that DRQ at test doses can selectively modulate the tumor microenvironment (TME) to enhance antitumor activity with substantially no impact on other functions. Blocking the CD74 / MIF axis has been proposed in cancer (Kang et al., Nat. Rev. Rheumatol. 15:427-437, 2019), but many of the molecules evaluated exhibited dose-limiting toxicity. The main advantage of DRQ is that it lacks this dose-limiting toxicity up to the maximum viable dose. As demonstrated herein, DRQ has potent antitumor effects, and while other MIF activities exist besides binding to CD74, the primary effect of DRQ is on CD74 / MIF signaling. Therefore, DRQ can provide an alternative treatment for individuals that have failed with currently approved treatments, particularly those with BRAF wild-type.

[0031] I. Terminology Unless otherwise noted, technical terms are used according to their conventional usage. Definitions of many common terms in molecular biology can be found in Krebs et al. (eds.), Lewin's genes XII, published by Jones & Bartlett Learning, 2017. As used herein, the singular forms “a,” “an,” and “the” refer to both singular and plural forms unless the context clearly indicates otherwise. For example, the term “polypeptide” includes one or more polypeptides and can be considered equivalent to the expression “at least one polypeptide.” As used herein, the term “comprises” means “includes.” Furthermore, it should be understood that any and all base sizes or amino acid sizes, as well as all molecular weight or molecular mass values ​​given for nucleic acids or polypeptides, are approximate and provided for illustrative purposes unless otherwise indicated. Many methods and materials similar or equivalent to those described herein can be used, but particularly appropriate methods and materials are described herein. In case of any conflict, this specification, including the definitions of terms, shall prevail. Furthermore, the materials, methods, and examples are illustrative and not intended to be limiting.

[0032] To facilitate an overview of various aspects, the following terms are provided:

[0033] Antigen: A compound, composition, or substance, including compositions injected or absorbed into an animal, that can stimulate antibody production or a T-cell response in an animal. Antigens react with certain humoral or cellular immune products, including those induced by heterologous immunogens. The term “antigen” includes all relevant antigenic epitopes. “Epitope,” “antigenic determinant,” or “antigenic peptide” refers to a site on an antigen to which B cells and / or T cells respond. In one embodiment, T cells respond to an epitope when it is presented together with an MHC molecule. Epitopes can be formed from both consecutive amino acids or discontinuous amino acids juxtaposed by tertiary folding of proteins. Epitopes formed from consecutive amino acids are typically retained upon exposure to denaturing solvents, while epitopes formed by tertiary folding are typically lost upon treatment with denaturing solvents. Epitopes typically contain at least three, and more commonly, at least eight, amino acids (e.g., approximately 8–50 or 8–23 amino acids) in a specific spatial conformation. Methods for determining the spatial conformation of an epitope include, for example, X-ray crystallography and two-dimensional nuclear magnetic resonance.

[0034] Antigens can be tissue-specific antigens or disease-specific antigens. These terms are not mutually exclusive, as tissue-specific antigens can also be disease-specific antigens. Tissue-specific antigens are expressed in a limited number of tissues, such as a single tissue. Tissue-specific antigens can also be expressed in two or more tissues, such as antigens expressed in the central nervous system or the peripheral nervous system.

[0035] BRAF: B-Raf proto-oncogene, also known as serine / threonine kinase. A member of the RAF family of serine / threonine kinases involved in regulating the MAP kinase / ERK signaling pathway. Mutations in BRAF (e.g., V600E or V600K) are most frequently identified in melanoma and also occur in other cancers such as colorectal cancer, thyroid cancer, and non-small cell lung cancer. Nucleic acid and protein sequences for BRAF are publicly available. For example, GenBank accessions NM_004333 and NM_001374258 disclose exemplary human BRAF nucleic acid sequences, and GenBank accessions NP_004324 and NP_001361187 disclose exemplary human BRAF amino acid sequences. Each of these sequences is incorporated herein by reference as presented in GenBank on May 26, 2023.

[0036] CD74: Also known as the CD74 molecule, major histocompatibility complex class II invariant chain, or MHC class II gamma chain, or Ii. CD74 is a chaperone that modulates antigen presentation. It is also a cell surface receptor for macrophage migration inhibitory factors (MIFs). Nucleic acid and protein sequences for CD74 are publicly available. For example, GenBank accessions NM_001025158, NM_004355, and NM_001025159 disclose exemplary human CD74 nucleic acid sequences, and GenBank accessions NP_001020329, NP_004346, and NP_001020330 disclose exemplary human CD74 amino acid sequences. Similarly, GenBank accession numbers NM_001042605 and NM_010545 disclose exemplary mouse CD74 nucleic acid sequences, and GenBank accession numbers NP_001036070 and NP_034675 disclose exemplary mouse CD74 amino acid sequences. Each of these sequences is incorporated herein by reference as presented in GenBank on May 26, 2023.

[0037] Control: A control refers to a sample or standard used for comparison with an experimental sample. In some embodiments, the control is a sample obtained from a healthy subject or a population of healthy subjects. In other embodiments, the control is a historical control or a standard reference value or range of values ​​(e.g., a previously tested control sample, e.g., a group of samples representing baseline or normal values). In further examples, the control is derived from a subject before treatment (e.g., before treatment with DRQ polypeptide).

[0038] Domain: A separate portion of the amino acid sequence of a polypeptide or protein that can be considered equivalent to a specific function. For example, the α and β polypeptides that make up MHC class II molecules are recognized to each have two domains, α1, α2, and β1, β2, respectively. The various domains are typically joined by linked amino acid sequences. In one embodiment, the entire domain sequence is included in a recombinant molecule by extending the sequence to include all or part of the linker or adjacent domains. For example, when selecting the α1 domain of an MHC class II molecule, the selected sequence may be extended from amino acid residue number 1 of the α chain, through the entire α1 domain, to amino acid 84 at the carboxyl terminus of the α1 domain. The exact number of amino acids in various MHC molecular domains differs between mammalian species and classes of genes within a species. The selection of sequences for use in recombinant molecules requires the preservation of domain function rather than precise structural definition based on the number of amino acids. Those skilled in the art will understand that domain function can be preserved even when using a portion of the amino acid sequence of the selected domain that is somewhat less than the entire sequence. For example, some amino acids at either the amino or carboxyl terminus of the α1 domain can be omitted without affecting domain function. In other examples, amino acid substitutions within a domain can increase or decrease the domain's binding affinity. For instance, the substitution of leucine with glutamine at position 50 of the DRhQ construct can increase its binding affinity to CD74.

[0039] Immune checkpoint blockade: Cancer immunotherapy that targets immune system regulators that suppress the immune response. Examples of checkpoint proteins found on T cells or cancer cells include PD-1, PD-L1, CTLA-4, BTLA, and TIM-3. These proteins inhibit T cells from killing cancer cells. Checkpoint inhibitors include drugs that target molecules such as lymphocyte activation gene 3 (LAG3), T-cell immunoglobulin and mucin domain-3 (TIM-3), CTLA-4 (e.g., ipilimumab, YERVOY®), PD-1 (e.g., nivolumab, OPDIVO®, and pembrolizumab, KETRUDA®), and PD-L1.

[0040] Disease Inhibition or Treatment: “Inhibiting” a disease means preventing the complete onset of a disease in a person known to have a predisposition to the disease, such as cancer. Disease inhibition can range from partial to substantially complete inhibition of a disease in a person who has the disease or disability, or is at risk of developing the disease or disability. In some cases, the term “inhibiting” means reducing or delaying the onset or progression of the disease. “Treatment” a disease means a therapeutic intervention that improves the signs or symptoms of a disease or pathological condition, such as the signs or symptoms of cancer. Subjects to be administered an effective dose of a pharmaceutical compound to inhibit or treat a disease or disability may be identified by standard diagnostic techniques for such a disorder, such as symptoms, evidence of family history, or risk factors for developing the disease or disability.

[0041] Linker: A molecule that covalently bonds two molecules (such as two polypeptides). Linkers (such as peptide linkers or chemical linkers) may be included in the recombinant MHC polypeptides of this disclosure, for example, between the α1 domain and the antigenic peptide. Generally, peptide linker sequences with amino acid lengths between 2 and 25 (e.g., 5-10, 10-15, 15-20, or 20-25 amino acids) include, but are not limited to, the glycine(4)-serine spacers described by Chaudhary et al. (Nature 339:394-397, 1989). Similarly, chemical linkers (such as thiol bonds or crosslinkers) may also be used.

[0042] MHC Class II: MHC class II molecules are formed from two non-covalently associated proteins, an α chain and a β chain. The α chain contains α1 and α2 domains, and the β chain contains β1 and β2 domains. The gap into which the antigen fits is formed by the interaction of the α1 and β1 domains. The α2 and β2 domains are transmembrane Ig fold-like domains that tether the α and β chains to the cell membrane of the APC. When the MHC class II complex associates with an antigen (and in the presence of appropriate co-stimulatory signals), it stimulates CD4 T cells. The primary functions of CD4 T cells are to initiate inflammatory responses, modulate other cells in the immune system, and provide support to B cells for antibody synthesis.

[0043] Pharmacologically acceptable carrier: Remington: The Science and Practice of Pharmacy, Adejare (Ed.), Academic Press, London, United Kingdom, 23 rdEdition (2021) describes compositions and formulations suitable for the pharmaceutically active delivery of polypeptides and nucleic acids disclosed herein. Generally, the properties of the carrier depend on the specific mode of administration employed. For example, parenteral formulations typically contain an injectable fluid as a vehicle, such as water, saline, equilibrium salt solution, aqueous dextrose, trehalose, or glycerol, which are pharmaceutically and physiologically acceptable fluids. For solid compositions (e.g., in the form of powders, pills, tablets, or capsules), conventional non-toxic solid carriers may include, for example, pharmaceutical-grade mannitol, trehalose, lactose, starch, or magnesium stearate. In addition to a biologically neutral carrier, the administered pharmaceutical composition may contain small amounts of non-toxic adjuncts, such as wetting or emulsifying agents, preservatives, and pH buffering agents, such as sodium acetate or sorbitan monolaurate.

[0044] Recombinant: Recombinant nucleic acids or polypeptides are nucleic acids or polypeptides that have sequences that do not exist in nature, or sequences that are created by artificial combinations of two or more sequence segments that have been otherwise fragmented. These non-natural sequences or artificial combinations are often achieved by chemical synthesis or by artificial manipulation of isolated nucleic acid segments, such as by genetic engineering techniques.

[0045] Sequence Identity: The similarity between two nucleic acid sequences or two amino acid sequences is expressed in terms of sequence similarity and is otherwise referred to as sequence identity. Sequence identity is often measured in terms of a percentage of identity (or similarity or homology), with a higher percentage indicating greater similarity between the two sequences. Polypeptides or their domains that have the same or similar amounts of sequence identity and function as each other (e.g., the same protein in different species) can be called "homologs." Methods for aligning sequences for comparison are well known in the art. Various programs and alignment algorithms are described in Smith & Waterman, Adv. Appl. Math. 2: 482, 1981; Needleman & Wunsch, J. Mol. Biol. 48: 443, 1970; Pearson & Lipman, Proc. Natl. Acad. Sci. USA 85: 2444, 1988; Higgins & Sharp, Gene, 73: 237-244, 1988; Higgins & Sharp, Comput. Appl. Biosci. 5: 151-153, 1989; Corpet et al., Nucl. Acids Res. 16, 10881-90, 1988; Huang et al., Comput. Appl. Biosci. 8, 155-65, 1992; and Pearson, Methods. This is described in Mol. Biol. 24:307-331, 1994. Altschul et al. (J. Mol. Biol. 215:403-410, 1990) present detailed considerations of sequence alignment methods and homology calculations. The NCBI Basic Local Alignment Search Tool (BLAST) is available from several providers, including the National Center for Biotechnology Information (NCBI, Bethesda, MD), and on the internet for use in conjunction with the sequence analysis programs blastp, blastn, blastx, tblastn, and tblastx.

[0046] Even nucleic acid sequences that do not exhibit a high degree of sequence identity may encode similar amino acid sequences due to the degeneracy of the genetic code. It is understood that by using this degeneracy to alter nucleic acid sequences, it is possible to create multiple nucleic acid molecules that all encode substantially the same protein.

[0047] Target: Living multicellular vertebrates, a category that includes both humans and non-human mammals.

[0048] Therapeutic effective dose: The amount of a particular substance sufficient to achieve the desired effect in the subject being treated. For example, this may be the amount required to inhibit or suppress tumor growth. In one embodiment, the therapeutic effective dose is the amount required to eliminate a tumor, reduce its size, prevent tumor metastasis, or extend the progression-free survival and / or overall survival of the subject. When administered to a subject, the dose that has been shown to achieve the desired in vitro or in vivo effect (e.g., in animal models or clinical trials) and that achieves the target tissue concentration (e.g., in a tumor) is commonly used.

[0049] II. Overview Clause 1: A method for treating a subject having cancer, comprising administering a therapeutically effective dose of a recombinant polypeptide comprising an antigenic peptide covalently bound to a DRα1 domain or a portion thereof, which contains a glutamine residue at the position corresponding to amino acid 50 of SEQ ID NO: 1 or SEQ ID NO: 2; or a nucleic acid encoding a recombinant polypeptide.

[0050] Clause 2: The method according to Clause 1, wherein the recombinant polypeptide further comprises a linker between the antigenic peptide and the DRα1 domain.

[0051] Clause 3: The method according to Clause 2, wherein the linker comprises a first glycine-serine spacer, a thrombin cutting site, and a second glycine-serine spacer.

[0052] Clause 4: The method according to any one of Clauses 1 to 3, wherein the antigenic peptide is myelin oligodendrocyte glycoprotein (MOG)-35-55 or myelin basic protein (MBP)-85-99.

[0053] Clause 5: The method according to Clause 4, wherein MOG-35-55 is human MOG-35-55 or mouse MOG-35-55.

[0054] Clause 6: The method according to any one of Clauses 1 to 5, wherein the recombinant polypeptide comprises or comprises the amino acid sequence of SEQ ID NO: 1 or SEQ ID NO: 2.

[0055] Clause 7: The method according to any one of Clauses 1 to 6, wherein the subject is administered a recombinant polypeptide at a dose of approximately 0.1 mg / kg to approximately 10 mg / kg.

[0056] Clause 8: The method according to any one of Clauses 1 to 7, wherein the cancer is a solid tumor or a hematological malignancy.

[0057] Clause 9: The method according to Clause 8, wherein the solid tumor is melanoma, glioblastoma, or breast cancer.

[0058] Clause 10: The method according to any one of Clauses 1 through 9, wherein the target cancer does not express a BRAF mutation.

[0059] Clause 11: The method according to Clause 10, wherein the cancer in question does not express the BRAF V600 mutation.

[0060] Clause 12: A method according to any one of Clauses 1 through 11, wherein a subject with cancer is resistant to immune checkpoint blockade therapy.

[0061] Clause 13: The method according to any one of Clauses 1 to 12, further comprising administering the treatment for one or more additional therapies.

[0062] Clause 14: The method according to Clause 13, wherein one or more additional treatments include one or more of surgery, radiation, chemotherapy, and immunotherapy.

[0063] Clause 15: The method described in Clause 14, wherein immunotherapy includes immune checkpoint blockade therapy.

[0064] III. Methods for treating cancer using DRQ A method is provided for treating subjects with cancer using a DRQ polypeptide or nucleic acid. The DRQ polypeptide comprises an antigenic peptide covalently bound to an MHC class II DRα1 domain or a fragment thereof, but does not contain an MHC class II α2, β1, or β2 domain, and includes a substitution of leucine (L) to glutamine (Q) at the amino acid position corresponding to amino acid 50 of SEQ ID NO: 1 or SEQ ID NO: 2. In some embodiments, the antigenic peptide contained in the DRQ polypeptide is MOG-35-55. In specific examples, MOG-35-55 is human MOG-35-55 and the DRQ polypeptide is referred to as DRhQ, or MOG-35-55 is mouse MOG-35-55 and the DRQ polypeptide is referred to as DRmQ. In other examples, the antigenic peptide contained in the DRQ polypeptide is myelin basic protein (MBP) 85-99 (e.g., SEQ ID NO: 5). Therefore, in some cases, the MOG-35-55 peptide (e.g., amino acids 1-21 of SEQ ID NO: 1 or SEQ ID NO: 2) is replaced with the MBP-85-99 peptide of SEQ ID NO: 5.

[0065] In some embodiments, the DRQ polypeptide has at least 95% identity to the amino acid sequence of SEQ ID NO: 1 or SEQ ID NO: 2 (e.g., at least 95%, 96%, 97%, 98%, 99%, or higher identity). In other embodiments, the DRQ polypeptide comprises or consists of the amino acid sequence of SEQ ID NO: 1 or SEQ ID NO: 2. In other embodiments, the DRQ polypeptide is encoded by a nucleic acid having at least 90% identity to the nucleic acid sequence of SEQ ID NO: 3 or SEQ ID NO: 4 (e.g., at least 90%, 91%, 92%, 93%, 94%, 95%, 96%, 97%, 98%, 99%, or higher identity). In other embodiments, the DRQ polypeptide is encoded by a nucleic acid comprising or consisting of the nucleic acid sequence of SEQ ID NO: 3 or SEQ ID NO: 4.

[0066] In some embodiments, recombinant polypeptides (e.g., SEQ ID NO: 1 or SEQ ID NO: 2) can be expressed in prokaryotic or eukaryotic cells from a nucleic acid construct encoding the recombinant polypeptide (e.g., a nucleic acid construct containing SEQ ID NO: 3 or SEQ ID NO: 4). The nucleic acid construct encoding the recombinant polypeptide (e.g., an expression construct) may also include regulatory elements such as promoters, enhancers, and / or 3' regulatory regions, the choice of which is determined based on the cell type in which the protein will be expressed. The construct is introduced into a vector suitable for expressing the recombinant polypeptide in the selected cell type.

[0067] Many prokaryotes and eukaryotes are known for polypeptide expression and purification. For example, heterologous polypeptides can be produced in prokaryotic cells by placing a potent, regulated promoter and an efficient ribosome binding site upstream of the polypeptide-encoding construct. Suitable promoter sequences include beta-lactamase, tryptophan (trp), phage T7, and lambda P. L Promoters are one example. Methods and plasmid vectors for producing heterologous proteins in bacterial or mammalian cells are known to those skilled in the art.

[0068] Suitable prokaryotic cells for high-volume protein expression include Escherichia coli and Bacillus subtilis. Often, highly expressed proteins are found in insoluble inclusions; methods for extracting proteins from these aggregates are known to those skilled in the art. Alternatively, recombinant expression of recombinant polypeptides in prokaryotic cells can be readily obtained using commercially available systems designed for optimal expression and purification of fusion proteins. Such fusion proteins typically include tags to facilitate purification. Examples of such systems include the pMAL protein fusion and purification system (New England Biolabs, Inc., Beverly, MA); the GST gene fusion system (Amersham Pharmacia Biotech, Inc., Piscataway, NJ); and the pTrcHis expression vector system (Invitrogen, Carlsbad, CA). Further systems include His6-tags (e.g., Roche Applied Science, Mannheim, Germany) or streptavidin-binding peptides (e.g., Sigma-Aldrich, St. Louis, MO). For example, the pMAL expression system utilizes a vector to which a maltose-binding protein is attached to the protein to be expressed. The fusion protein is expressed in E. coli and purified from crude cell extracts using an amylose column. If necessary, the maltose-binding protein domain can be cleaved from the fusion protein by treatment with a suitable protease such as factor Xa. The maltose-binding fragment can then be removed from the preparation by passing it through a second amylose column.

[0069] Recombinant polypeptides can also be expressed in eukaryotic expression systems, including those produced by Invitrogen (Carlsbad, CA), such as Pichia pastoris, Drosophila, baculovirus, and / or Sindobis expression systems. Eukaryotic cells such as Chinese hamster ovary (CHO), monkey kidney (COS), HeLa cells, 293 cells, Spodoptera frugiperda, and Saccharomyces cerevisiae can also be used to express recombinant polypeptides. Suitable regulatory regions for use in these cells include viral promoters, e.g., CMV, adenovirus, or SV40-derived promoters, for mammalian cells, and promoters for 3-phosphoglycerate kinase or alcohol dehydrogenase, for yeast cells.

[0070] Vectors can be introduced into recipient cells (such as eukaryotic cells) as pure DNA (transfection) by methods such as precipitation with calcium phosphate or strontium phosphate, electroporation, lipofection, DEAE dextran, microinjection, protoplast fusion, or microprojectile gun. Alternatively, nucleic acid molecules can be introduced by infection using viral vectors. For example, systems using retroviruses, adenoviruses, or herpesviruses have been developed.

[0071] Pharmaceutical compositions comprising recombinant polypeptides or nucleic acids disclosed herein (such as effective amounts of disclosed recombinant polypeptides or nucleic acids) may be formulated with appropriate solid or liquid carriers depending on a selected specific mode of administration. Examples of pharmaceutically acceptable carriers and excipients useful in this disclosure include those known to those skilled in the art. For example, Remington: The Science and Practice of Pharmacy, Adejare (Ed.), Academic Press, London, United Kingdom, 23 rdSee Edition (2021). For example, parenteral formulations typically contain an injectable fluid, which is a pharmaceutically and physiologically acceptable fluid vehicle such as water, saline, other equilibrium salt solutions, aqueous dextrose, or glycerol. For solid compositions (e.g., in the form of powders, pills, tablets, or capsules), conventional non-toxic solid carriers may include, for example, pharmaceutical-grade mannitol, lactose, starch, or magnesium stearate.

[0072] In addition to a biologically neutral carrier, the administered pharmaceutical composition may contain trace amounts of non-toxic adjuncts, such as humectants or emulsifiers, preservatives, pH buffers, cyclodextrins, and sugars that are cryoprotectants, such as trehalose, sodium acetate, or sorbitan monolaurate. Additives that may be included are other proteins, such as human serum albumin or plasma preparations. The dosage form of the pharmaceutical composition is determined by the chosen mode of administration. For example, in addition to injectable fluids, topical preparations, inhalation preparations, oral preparations, and suppository preparations may be available. Topical preparations may include eye drops, ointments, sprays, patches, etc. Inhalation preparations may be liquids (e.g., solutions or suspensions), and may include mists, sprays, etc. Oral preparations may be liquids (e.g., syrups, solutions, or suspensions) or solids (e.g., powders, pills, tablets, or capsules). Suppository preparations may also be in the form of solids, gels, or suspensions. Practical methods for preparing such dosage forms are either known to or obvious to those skilled in the art.

[0073] In some cases, pharmaceutical compositions may be administered in any form that achieves their intended purpose. The amount and regimen for administering recombinant polypeptides or portions thereof (or nucleic acids encoding such polypeptides) may be determined by the attending clinician. Effective doses for therapeutic application vary depending on the nature and severity of the condition being treated, the patient's age and condition, and other clinical factors. Typically, the dose range is about 0.1 mg / kg body weight to about 10 mg / kg body weight. Other appropriate ranges include about 0.1 mg / kg to about 5 mg / kg body weight, about 0.25 mg / kg to about 2.5 mg / kg body weight, or about 1 mg / kg to about 5 mg / kg body weight, for example, doses of about 0.1 mg / kg, about 0.25 mg / kg, about 0.5 mg / kg, about 0.75 mg / kg, about 1 mg / kg, about 1.5 mg / kg, about 2 mg / kg, about 2.5 mg / kg, about 3 mg / kg, about 4 mg / kg, or about 5 mg / kg.

[0074] Pharmaceutical compositions containing DRQ polypeptides or nucleic acids can be formulated into unit dosage forms suitable for individual administrations of precise dosages. In one particular non-limiting example, a unit dosage may contain approximately 10 mg to approximately 1 g of recombinant polypeptide (e.g., approximately 10 mg to approximately 50 mg, approximately 25 mg to approximately 250 mg, approximately 50 mg to approximately 500 mg, or approximately 100 mg to approximately 1 g). The amount of active compound administered depends on the target being treated, the severity of the disorder being treated, and the mode of administration. Within these boundaries, the administered formulation contains a certain amount of the active ingredient in an amount effective to achieve the desired effect in the target being treated.

[0075] The medication schedule can vary from daily to once every month, depending on several clinical factors, such as the patient's condition and sensitivity to the administered composition. Examples of medication schedules include daily, every other day, three times a week, every other week, weekly, twice a month (e.g., every two weeks), monthly (e.g., every four weeks), every six weeks, or every eight weeks. In some cases, the treatment period is approximately six months, one year, eighteen months, two years, or longer. In other cases, the treatment period continues until the patient no longer responds to treatment, for example, until the patient shows disease progression.

[0076] Recombinant DRQ polypeptides or nucleic acids can be administered to human or other animal tissues in various ways, for example, topically, orally, intravenously, intramuscularly, intraperitoneally, intranasally, intradermally, intrathecally, subcutaneously, by inhalation, or by suppositories. In one example, the compound is administered intravenously to the target.

[0077] In some embodiments, compositions comprising DRQ polypeptides or nucleic acids are administered to subjects with cancer; for example, subjects with solid tumors. Examples of solid tumors include sarcomas (e.g., fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic sarcoma, and other sarcomas), synoviomas, mesothelioma, Ewing's sarcoma, leiomyosarcoma, rhabdomyosarcoma, colon cancer, colorectal cancer, peritoneal cancer, esophageal cancer, pancreatic cancer, and breast cancer (e.g., basal cell carcinoma). Examples include carcinoma, ductal carcinoma, lobular breast carcinoma, or triple-negative breast cancer, lung cancer, ovarian cancer, prostate cancer, liver cancer (e.g., hepatocellular carcinoma), gastric cancer, squamous cell carcinoma (e.g., head and neck squamous cell carcinoma), basal cell carcinoma, adenocarcinoma, sweat gland carcinoma, medullary thyroid carcinoma, papillary thyroid carcinoma, pheochromocytoma, sebaceous gland carcinoma, papillary carcinoma, papillary adenocarcinoma, medullary carcinoma, bronchogenic carcinoma, hepatocellular carcinoma, cholangiocarcinoma, choriocarcinoma, Wilms' tumor, cervical cancer, fallopian tube cancer, testicular tumor, seminoma, bladder cancer, kidney cancer (e.g., renal cell carcinoma), melanoma, and CNS tumors (e.g., glioma, glioblastoma, astrocytoma, medulloblastoma, craniopharyngioma, ependymoma, pineal glandoma, hemangioblastoma, acoustic neuroma, oligodendroglioma, meningioma, neuroblastoma, and retinoblastoma). Solid tumors also include tumor metastases (e.g., metastases to the lungs, liver, brain, or bones). In specific cases, the subjects may have melanoma, glioblastoma, breast cancer, colon cancer, or lung cancer.

[0078] In other embodiments, compositions comprising DRQ polypeptides or nucleic acids are administered to subjects with hematological malignancies. Examples of hematological malignancies include acute leukemia (e.g., 11q23-positive acute leukemia, acute lymphoblastic leukemia, acute myeloid leukemia, acute myeloid leukemia, and myeloblastic leukemia, promyelocytic leukemia, myelomonocytic leukemia, monocytic leukemia, and erythroleukemia), leukemia including chronic leukemia (e.g., chronic myeloid (granulocytic) leukemia, chronic myeloid leukemia, and chronic lymphocytic leukemia), polycythemia vera, lymphoma, Hodgkin's disease, non-Hodgkin lymphoma (low- and high-grade forms), multiple myeloma, Waldenström macroglobulinemia, heavy chain disease, myelodysplastic syndromes, hairy cell leukemia, and spinal dysplasia.

[0079] In some embodiments, subjects with cancer are those who have not responded to or are no longer responding to one or more cancer therapies (e.g., they are resistant or have developed resistance). In some cases, subjects are resistant to or have developed resistance to immune checkpoint blockade therapy (e.g., therapy with one or more of ipilimumab, nivolumab, and pembrolizumab), and, for example, experience disease progression after therapy with one or more immune checkpoint blockade therapies. Resistance may be primary resistance (e.g., the subject does not respond) or secondary resistance (the subject initially responded but subsequently progressed). In some cases, immune checkpoint blockade therapy was the first-line treatment.

[0080] In other cases, the subject (e.g., the tumor in question) does not have a mutation in the BRAF gene (e.g., it is BRAF wild-type). BRAF mutations are most frequently found in melanoma, but are also found in colorectal cancer, lung cancer, thyroid cancer, ovarian cancer, and brain cancer. BRAF mutations are well known in the art and are described in Smiech et al., (Genes (Basel) 11:1342, 2020). In some cases, BRAF mutations include class I mutations (V600 mutations, e.g., V600E, V600K, V600D, V600R, or V600M), which account for about 90% of all mutations. In other cases, BRAF mutations include class II or class III mutations, which account for the remaining mutations. Therefore, in some cases, the subject does not have a BRAF V600 mutation (e.g., their tumors do not express the BRAF V600 mutation). In other cases, the subjects do not have class II or class III BRAF mutations (for example, their tumors do not express BRAF class II or class III mutations).

[0081] In additional embodiments, the method includes selecting subjects that have primary or secondary resistance to immune checkpoint blockade, subjects that do not have the BRAF mutation, or both. In some examples, the method further includes determining whether tumor samples from the subjects express the BRAF V600 mutation. Subjects whose tumors do not express the BRAF V600 mutation may be selected for treatment.

[0082] In some embodiments, treatment with DRQ results in, for example, extended progression-free survival, extended overall survival, or both, compared to subjects not treated with DRQ. In other embodiments, progression-free survival is at least 2 months, at least 4 months, at least 6 months, at least 9 months, at least 12 months, at least 15 months, at least 18 months, at least 2 years, or longer. In additional embodiments, overall survival is at least 6 months, at least 9 months, at least 12 months, at least 15 months, at least 18 months, at least 2 years, or longer. In other embodiments, treatment with DRQ results in, for example, a reduction in tumor size, a reduction in the number of tumors, or a reduction in metastases, compared to subjects not treated with DRQ.

[0083] In some embodiments, DRQ polypeptides or nucleic acids are administered to the subject as monotherapy for cancer. In other embodiments, additional agents, such as chemotherapeutic agents or immune checkpoint blockers, may be administered to the subject. These may be included in the disclosed pharmaceutical composition or administered separately. In additional embodiments, surgical procedures and / or radiation may be administered to the subject. The administration of additional treatments may be sequential or concurrent. An experienced clinician may select additional treatments to be administered based, for example, the cancer being treated, the subject's response to prior treatment, the subject's condition, and other factors.

[0084] Examples of chemotherapeutic agents used in the disclosed method include alkylating agents, antimetabolites, natural products, or hormones and their antagonists. Examples of alkylating agents include nitrogen mustards (e.g., mechloretamine, cyclophosphamide, melphalan, uracil mustard, or chlorambucil), alkyl sulfonates (e.g., busulfan), and nitrosoureas (e.g., carmustine, lomustine, semustine, streptozocin, or dacarbazine). Examples of antimetabolites include folate analogs (e.g., methotrexate), pyrimidine analogs (e.g., 5-FU or cytarabine), and purine analogs such as mercaptopurine or thioguanine. Examples of natural products include vinca alkaloids (e.g., vinblastine, vincristine, or vindesine), epipodophyllotoxins (e.g., etoposide or teniposide), antibiotics (e.g., dactinomycin, daunorubicin, doxorubicin, bleomycin, plicamycin, or mitomycin C), and enzymes (e.g., L-asparaginase). Examples of various pharmaceuticals include platinum coordination complexes (e.g., cis-diamine-dichloroplatinum II, also known as cisplatin), substituted ureas (e.g., hydroxyurea), methylhydrazine derivatives (e.g., procarbazine), and adrenocortical suppressants (e.g., mitotane and aminoglutethimide). Examples of hormones and antagonists include corticosteroids (e.g., prednisone), progestins (e.g., hydroxyprogesterone caproate, medroxyprogesterone acetate, and magestrol acetate), estrogens (e.g., diethylstilbestrol and ethinylestradiol), antiestrogenic agents (e.g., tamoxifen), and androgens (e.g., testosterone propionate and fluoxymesterone).Examples of the most commonly used chemotherapy drugs include Adriamycin, Alkeran, Ara-C, BiCNU, Busulfan, CCNU, Carboplatinum, Cisplatinum, Cytoxane, Daunorubicin, DTIC, 5-FU, Fludarabine, Hydrea, Idarubicin, Ifosfamide, Methotrexate, Mitramycin, Mitomycin, Mitoxantrone, Nitrogen Mustard, Taxol (or other taxanes such as Docetaxel), Vervan, Vincristine, VP-16, Gemcitabine, Herceptin, Irinotecan, Leustatin, Navelbine, Rituxan STI-571, Taxotere, Topotecan, Capecitabine), Zevelin, and Calcitriol. Non-exclusive examples of immunomodulatory agents that can be used include AS-101, bropyrimin, gamma interferon, GM-CSF (granulocyte-macrophage colony-stimulating factor), IL-2, human immunoglobulin, IMREG, SK&F 106528, and TNF (tumor necrosis factor).

[0085] In other embodiments, the additional chemotherapeutic agent may be an antibody. Exemplary monoclonal antibody therapies include trastuzumab, alemtuzumab, atezolizumab, avelumab, bevacizumab, blinatumomab, cetuximab, daratumumab, ipilimumab, nivolumab, ofatumumab, panitumumab, pembrolizumab, pertuzumab, and rituximab. In specific cases, the antibody may be an immune checkpoint inhibitor, such as an antibody that specifically binds to PD-1, PD-L1, TIM-3, or CTLA-4.

[0086] Treatment regimens may also include surgery, chemotherapy, radiation, or combinations with other immunoablative agents such as CAMPATH, anti-CD3 antibodies or other antibody therapies, cytoxin, fludarabine, cyclosporine, FK506, rapamycin, mycophenolate, steroids, FR901228, cytokines, and irradiation. Exemplary chemotherapeutic agents include anthracyclines (e.g., doxorubicin (e.g., liposomal doxorubicin)), vinca alkaloids (e.g., vinblastine, vincristine, vindesine, vinorelbine), alkylating agents (e.g., cyclophosphamide, decarbazine, melphalan, ifosfamide, temozolomide), immune cell antibodies (e.g., alemtuzumab, gemtuzumab, rituximab, tositumomab), and metabolites. Immunomodulators include antagonists (e.g., folate antagonists, pyrimidine analogs, purine analogs, and adenosine deaminase inhibitors (e.g., fludarabine)), mTOR inhibitors, TNFR glucocorticoid-inducible TNFR-related protein (GITR) agonists, proteasome inhibitors (e.g., acrasinomycin A, gliotoxin, or bortezomib), and thalidomide or thalidomide derivatives (e.g., lenalidomide). [Examples]

[0087] The following embodiments are provided to illustrate certain features of certain aspects of the present disclosure, but the scope of the present disclosure should not be limited to those illustrated features.

[0088] (Example 1) Experimental procedure and diagram details Figure 1 shows a Kaplan-Meier plot illustrating reduced overall survival in a sample of patients with advanced melanoma exhibiting higher MIF expression. Data are from the TCGA skin cancer melanoma dataset (n=459, p=0.024 by log-rank test).

[0089] Figure 2 is a graph showing the reduced MIF production in B16F10 cells grown with DRmQ compared to the vehicle control.

[0090] Figure 3 shows the growth curves of intradermal B16F10 mouse melanoma models treated with vehicle control or DRmQ (P<0.05 by unpaired two-sided t-test).

[0091] Figure 4 shows the effect of DRQ treatment on immunoinfiltration in B16F10 melanoma tumors. The image is a micrograph illustrating the significant immunoinfiltration observed in B16F10 melanoma tumors treated with DRQ (20x magnification, scale bar = 50 μm). Based on flow cytometry analysis, significant immunoinfiltration was observed within the entire tumor cell population of the DRQ-treated tumors (CD45+ and CD45+CD8+ double positive).

[0092] Figure 5 illustrates that, as measured by TRP2-PE tetramer, DRQ (top) increases the infiltration of TRP2-responsive CD8+ cells compared to the vehicle control (bottom).

[0093] Figure 6 shows Western blots of pSTAT3, pAKT, and pERK in B16F10 cells incubated with no tx (no tx), vehicle, or 50 μg of DRQ for 1 hour.

[0094] Figures 7A–7O illustrate how CD74 modulates tumor progression. Figures 7A–7I show a 6-week-old C57BL / 6 and CD74. - / - For the female mouse, 5 * 10 5Indicates that E0771 cells were injected. Tumor growth was measured every 5 days in Figure 7A. After 21 days, the mice were euthanized, the tumors were excised, and measured in Figures 7B - 7C; (n = 34), each point on the graph represents a tumor. Figures 7D - 7I show that total PBMCs from the tumor site were activated with (PMA (phorbol 12 - myristate 13 - acetate), ionomycin, monensin) PIM and then analyzed by flow cytometry. Dead cells were excluded from the analysis by Zombie live / dead staining. LY6 - C + , F4 / 80 + , and CD19 + After excluding cells, DC cells were analyzed for the expression of CD45, CD11c, and CD80. The graph in Figure 7D shows the mean and SD percentages of DCs at the tumor site (WT n = 11; CD74 - / - n = 8). In Figure 7E, CD80 - DCs were analyzed as a percentage of total DCs (WT n = 11; CD74 - / - n = 8). In Figure 7F, tolerogenic DCs were analyzed for IL - 10 among total DCs. The graph shows the mean and SD percentages of IL - 10 + DCs among total DC cells (WT n = 11; CD74KO n = 8). The graph in Figure 7G shows the mean and SD percentages of FOXP3 + T cells among total CD4 + T cells (WT n = 8; CD74KO n = 8). The graph in Figure 7H shows the mean and SD percentages of IL - 10 + B cells among total B cells (WT n = 8; CD74 KO n = 7). The graph in Figure 7I shows the mean and SD percentages of IFN - γ + T cells among total CD8 + T cells (WT n = 5; CD74KO n = 4). Figures 7J - 7O show that in female 6 - week - old C57BL / 6 mice, 5 * 10 5This shows that individual E0771 cells were injected, and DRQ was administered intravenously on days 10, 11, 12, 13, and 14 after tumor development. After 21 days, tumor size was measured and recorded in Figures 7J-7K (n=29). Figure 7L shows IL-10 - DCs were analyzed as a percentage of all DCs (n=8 for PBS; n=8 for DRQ). In Figure 7M, IL-12 + DCs were analyzed as a percentage of all DCs (n=4 for PBS; n=4 for DRQ). The graph in Figure 7N shows IL-10 of all B cells. + The mean and SD percentage of B cells are shown (n=7 for PBS; n=8 for DRQ). The graph in Figure 70 shows the total CD4 + The mean and SD percentage of Treg cells are shown (n=7 for PBS; n=8 for DRQ). * p<0.05, ** p<0.005, *** p<0.0005, **** p < 0.00005.

[0095] Figures 8A-8G illustrate how the MIF-CD74 axis adjusts tol-DC and Breg expansion. Figures 8A-8B show a naive C57BL / 6 mouse and CD74. - / - B cells and dendritic cells (DCs) were isolated from mouse spleens and cultured either alone or co-cultured with E0771 cells in a ratio of 1:5 (B cells:E0771) or 1:3 (DCs:E0771). After 24 hours, B cells or DCs were harvested and analyzed by flow cytometry for LY6-C + F4 / 80 + , and CD19 + After excluding the cells, the expression of CD19 and IL-10, or CD11c and IL-10, was analyzed. Cells were activated with PIM before FACS staining. Dead cells were excluded from the analysis by Zombie live / dead staining. Figure 8A shows the IL-10 expression of all dendritic cells under different culture conditions. +Figure 8B shows the multiplicative changes in DC expansion (WT n=15; CD74KO n=15), with each point representing a mouse. Figure 8B shows the multiplicative changes in Breg expansion among B cells under different culture conditions (WT n=21; CD74KO n=21). In Figures 8C-8D, spleen B cells and DCs were purified from IL-10 vert-x mice and cultured with E0771 cells in a 1:5 ratio for 24 hours in or without mrMIF. The graph in Figure 8C shows the multiplicative changes in IL10 among all dendritic cells. + Figure 8D shows the mean and SD percentage of DCs (WT+PBS n=12; WT+MIF n=13). The graph in Figure 8D shows the mean and SD percentage of Bregs among B cells (WT+PBS n=12; WT+MIF n=12). In Figures 8E-8G, E0771 cells were transfected with siRNA MIF or siCtrl. Spleen B cells and DCs were purified from IL-10 vert-x mice and added to transfected E0771 cells in a ratio of 1:5 or 1:3 for 24 hours. In Figure 8E, MIF mRNA levels were analyzed by qRT-PCR. The graph shows the polyploidy change (siRNA / siCtrl) for selected genes (n=3). The graph in Figure 8F shows IL10 levels among all dendritic cells. + The mean and SD percentage of DCs are shown (WT+Sico E0771 n=13; WT+siMIF n=13). The bar graph in Figure 8G represents the mean and SD percentage of Bregs among B cells (WT+Sico E0771 n=14; WT+siMIF n=14). * p<0.05, ** p<0.005, *** P<0.0005, **** p < 0.00005.

[0096] Figures 9A-9F illustrate that CD74 deficiency in mature B cells does not affect tumor growth. Figures 9A-9D show 5 cells each in the fourth mammary pad of 6-week-old female CD23-Cre×CD74flox×CD74flox mice. * 10 5This shows that individual E0771 cells were injected. After 21 days, tumor size was measured and recorded in Figure 9A (n=22). Mice were euthanized, tumors were collected, processed into single-cell suspensions, and all PBMCs were isolated from the tumor site. The cells were then activated with PIM and analyzed by flow cytometry. Dead cells were excluded from the analysis by Zombie live / dead staining. LY6-C + F4 / 80 + , and CD19 + After excluding certain cells, DC cells were analyzed for CD45, CD11c, and IL-10 expression. Breg cells were analyzed for CD19 and IL-10. In Figure 9B, IL-10 + DCs were analyzed as a percentage of all DCs (n=8 for WT; n=7 for conditional CKO). The graph in Figure 9C shows the percentage of IL-12 among all DCs. + The mean and SD percentage of dendritic cells are shown (n=5 for WT; n=5 for CKO). The graph in Figure 9D shows the total CD19 + IL-10 in cells + The mean and SD percentage of B cells are shown (n=6 for WT; n=6 for CKO). In Figures 9E-9F, spleen B cells and dendritic cells were cultured with E0771 cells in a 1:5 ratio for 24 hours. The graph in Figure 9E shows IL10 of all dendritic cells. + The mean and SD percentage of DCs are shown (WT n=5; CKO n=5). The graph in Figure 9F shows the mean and SD percentage of Bregs among B cells (WT n=7; CKO n=7). The histograms represent the expression of CD74 in the DC and B cell populations. ns p>0.05. * p<0.05, ** p<0.005, *** p<0.0005.

[0097] Figures 10A-10K illustrate how CD74 deficiency in dendritic cells reduces tumor growth by activating the immune response. Figures 10A-10I show that 5 cells were injected into each of the fourth mammary pads of 6-week-old female CD11c-Cre×CD74flox×CD74flox mice. * 105 Figure 10A shows that individual E0771 cells were injected. Tumor size was recorded every 5 days. After 21 days, tumor size was measured and recorded in Figures 10B-10C (n=44); each point represents a tumor. Figure 10D shows IL-10 + DCs were analyzed as a percentage of all DCs (WT n=13; conditional CKO n=12). The graph in Figure 10E shows IL-10 of all B cells. + The mean and SD percentage of B cells are shown (WT n=12; CKO n=11). The graph in Figure 10F shows all CD4 + The mean and SD percentage of Treg cells are shown (WT n=13; CKO n=10). The graph in Figure 10G shows the total CD3 + Tumor-infiltrating CD8 T cells + The mean and SD percentage of T cells are shown (WT n=13; CKO n=12). The graph in Figure 10H shows all CD8 + The mean and SD percentage of IFN-γ-releasing T cells among T cells are shown (WT n=4; CKO n=4). The graph in Figure 10I shows all CD8 + Among T cells, PD1 + The mean and SD percentage of T cells are shown (WT n=4; CKO n=4). In Figures 10J-10K, spleen B cells and DCs were cultured with E0771 cells in a 1:5 ratio. The graph in Figure 10J shows IL10 of all dendritic cells. + The mean and SD percentage of DCs are shown (WT n=8; conditional CD74 KO n=8). The graph in Figure 10K shows the mean and SD percentage of Bregs among B cells (WT n=8; conditional CD74 - / - n=8). The histogram shows the expression of CD74 in DC and B cell populations. ns p>0.05, * p<0.05, *** P<0.0005, **** p < 0.00005.

[0098] Figures 11A-11G illustrate how CD74 mediates crosstalk between DCs and B cells, enhancing immunosuppression in tumor mesenteric neuropathy (ME). Figures 11A-11B show naive C57BL / 6 mice and CD74. - / - B cells and DCs were isolated from mouse spleens and cultured in a 1:1 ratio; E0771 cells were added in a 1:5 ratio. After 24 hours, B cells or DCs were harvested and analyzed by flow cytometry. PIM activation was performed before FACS staining. Dead cells were excluded from the analysis by Zombie live / dead staining. The graph in Figure 11A shows IL10 of all dendritic cells under different culture conditions. + The mean and SD percentage of dendritic cells are shown (WT DC+ WT B cells n=8; CD75T4 KO DC+ WT B cells n=8; WT DC+ CD74 KO B cells n=8; CD74 - / - DC+ CD74 KO B cells (n=8). The graph in Figure 11B shows IL10 of all B cells under different culture conditions. + The mean and SD percentage of B cells are shown (WT DC+ WT B cells n=8; CD74 KO DC+ WT B cells n=8; WT DC+ CD74 KO B cells n=8; CD74 KO DC+ CD74 KO B cells n=8). In Figure 11C, spleen DCs were purified from CD11c-Cre×CD74flox×CD74flox mice and activated with E0771 for 24 hours. Naive spleen B cells were purified from C57BL / 6 mice and incubated in fresh medium in WT or CD74 - / - DCs were activated for 24 hours. The bar graph shows the IL10 of all B cells. + The mean and SD percentage of B cells are shown (B cells + WT DC CM n=10; B cells + CD74 cKO DC CM n=10). In Figure 11D, spleen B cells were purified from C57BL / 6 mice, activated with E0771, and incubated with anti-CD74 blocking antibody (LN-2) or isotype control antibody for 24 hours. Naive spleen DCs were purified from C57BL / 6 mice and cultured together with B cells treated in fresh medium. The bar graph shows IL10 of all DCs. +The mean and SD percentage of dendritic cells are shown (DC+B cells treated with IGg, n=8; DC+B cells treated with LN-2, n=8). In Figures 11E-11G, spleen DCs were treated with C57BL / 6 and CD74. - / - CD3 was purified from mice using magnetic beads and co-cultured with E0771 in a 1:3 ratio for 24 hours. CD3 was obtained from naive spleen of C57BL / 6 mice. + T cells were purified and stained with cell proliferation dye (CPD) to determine their proliferative capacity. After co-culturing with E0771, DCs were cultured with T cells in a 1:1 ratio in the presence of IL-2 in the culture medium for 72 hours. T cells were analyzed for CD8, FOXP3, and INF-γ. Dead cells were excluded from the analysis by Zombie live / dead staining. The graph in Figure 11E shows the proliferative capacity of CD8 under different culture conditions. + The mean and SD percentage of T cells are shown (WT n=14; CD74 KO n=15). The graph in Figure 11F shows FOXP3 under the culture conditions shown. + CD4 + The mean and SD percentage of T cells are shown (WT n=9; CD74) - / - n=11). The graph in Figure 11G shows IFN-γ + CD8 + The percentage of T cells is shown (WT n=14; CD74 KO n=15).

[0099] Figures 12A-12D illustrate how CD74 deficiency in dendritic cells induces a pro-inflammatory pathway that enhances the anti-tumor immune response. Six-week-old female C57BL / 6 mice were given 5 samples to each of the fourth mammary gland pads. * 10 5E0771 cells were injected. DRQ was intravenously injected on days 10, 11, 12, 13, and 14 after tumor development. Tumor size was measured after 21 days, and the mice were euthanized. Tumors were processed into single-cell suspensions, and DCs were selected from the tumor microenvironment of mice treated with either PBS or DRQ. Four copies were analyzed for each group. Based on heatmaps of disease, impairment, and biological function generated for all differentially expressed genes from DRQ vs. PBS RNA-seq data, genes involved in cancer progression were downregulated in DRQ-treated samples, while genes related to immune transport, cell migration, and inflammatory responses were upregulated. In Figures 12A–12B, mRNA levels of SP1 and IL1β were validated by qRT-PCR. The graphs show the ploidy changes of selected genes in PBS-treated and DRQ-treated DCs (n=6). Figures 12C-12D show the multiplicative changes in SP1 and IL1β in WT and CD74 KO mice (n=6). *** p<0.0005, **** p < 0.00005.

[0100] Figures 13A-13D illustrate how CD74-ICD binds to the IL-1β promoter in DCs and promotes their tolerogenic phenotype. In Figures 13A-13C, spleen dendritic cells were isolated from vert-x mice and cultured in a 1:3 ratio in the presence of E0771. IL-1β agonists or vehicles were added to the cells for 48 hours. The graph in Figure 13A shows the IL1β ratio among all DCs. + The mean and SD percentage of dendritic cells are shown (DC + vehicle = 18; DC + IL1β n = 20). Each point represents a mouse. In Figure 13B, spleen DCs were purified from C57BL / 6 mice and activated with E0771 for 24 hours in the presence of an IL-1β agonist or PBS control. Naive spleen B cells were purified from C57BL / 6 mice and added to DCs in fresh medium for 24 hours. The bar graph shows IL1β of all B cells. + IL10 in B cells and all dendritic cells +Shows the mean and SD percentage of DCs (B cells + DCs treated with PBS, n = 5; B cells + DCs treated with IL-1β, n = 5). In Fig. 13C, splenic B cells were purified from C57BL / 6 mice and activated for 24 hours alone or with purified DCs by E0771 cells in the presence of IL-1β or vehicle. The bar graph shows IL10 among all B cells + Shows the mean and SD percentage of B cells (B cells treated with PBS, n = 10; B cells treated with IL-1β, n = 10; B cells + DCs treated with PBS, n = 10; B cells + DCs treated with IL-1β, n = 10). Fig. 13D shows that female 6-week-old C57BL / 6 mice received 5 * 10 5 E0771 cells were injected into each of the fourth mammary pads. After 21 days, the mice were euthanized. Tumors were processed into single cell suspensions and DCs were sorted from the tumor microenvironment. ChIP analysis was performed. Binding of CD74-ICD to the promoter region of the IL-1β gene was determined by qPCR. The graph represents the percentage of enrichment relative to input (amount of DNA pulled down in the ChIP reaction using the antibody of interest relative to the amount of starting material - input sample) (n = 4). ns p > 0.05, * p < 0.05, **** p < 0.00005.

[0101] Figs. 14A - 14G show that SP1 binds to the IL-1β promoter on DCs via the MIF-CD74 axis and induces their tolerogenic phenotypes. In Figs. 14A - 14C, splenic dendritic cells were isolated from vert-x mice and cultured at a ratio of 1:3 in the presence of E0771 cells. An SP1 blocker (MIT) or DMSO was added to the cells for 48 hours. Fig. 14A shows IL10 among all DCs +Showing the fold change of dendritic cell expansion (DC + DMSO = 10; DC + MIT n = 10). Each point represents a mouse. In Figure 14B, spleen DCs were purified from C57BL / 6 mice and activated with E0771 for 24 hours in the presence of DMSO or MIT. Naive spleen B cells were purified from C57BL / 6 mice, and after changing the medium, they were added to DCs for 24 hours. The bar graph shows IL10 among all B cells + IL10 among B cells and all dendritic cells + Showing the fold change of DCs (B cells treated with DMSO n = 5; B cells treated with mitomycin n = 5). In Figure 14C, spleen B cells were purified from C57BL / 6 mice and activated with E0771 cells alone or purified DCs in the presence of MIT or DMSO for 24 hours. The bar graph shows IL10 among all B cells + Showing the mean and SD percentage of B cells (B cells treated with DMSO n = 10; B cells treated with MIT n = 10, B cells treated with DMSO + DC n = 10; B cells treated with MIT + DC n = 10). Figures 14D - 14E show that female 6 - week - old C57BL / 6 mice were injected with 5 * 10 5 E0771 cells into each of the fourth mammary pads. After 21 days, the tumor size was measured and the mice were euthanized. The tumors were processed into single - cell suspensions, and DCs were sorted from the tumor microenvironment. The sorted DCs were activated with mrMIF or vehicle for 1 hour, and chip - qPCR was performed for the SP1 promoter. The graph in Figure 14D represents the percentage of enrichment relative to the input (the amount of DNA pulled down by the CD74 antibody in the ChiP reaction relative to the amount of starting material - input sample) (n = 5). The graph in Figure 14E shows the binding of CD74 - ICD in DCs activated with mrMIF (n = 5). Figure 14F shows that female 6 - week - old C57BL / 6 mice were injected with 5 * 10 5The image shows that individual E0771 cells were injected. After 21 days, tumor size was measured and the mice were euthanized. The tumors were processed into single-cell suspensions, and DCs were sorted from the tumor microenvironment. The sorted DCs were activated for 1 hour with either mrMIF, DRQ, or a vehicle, and ChIP-qPCR was performed for the IL-1β promoter. The graph shows the percentage of enrichment relative to the input in DCs activated with mrMIF, DRQ, or a vehicle (amount of DNA pulled down by using SP1 antibody in the ChIP reaction relative to the amount of starting material - input sample) (n=14). In Figure 14G, DCs were purified from C57BL / 6 mice and seeded together with E077 in or without MIT. The graph shows IL-1β of all DCs. + This shows the mean and standard deviation percentages of DCs (DCs processed with DMSO = 8, DCs processed with MIT = 8). p > 0.05, * p<0.05, ** P<0.005, *** P<0.0005, **** p < 0.00005.

[0102] Figures 15A-15C illustrate the upregulation of CD74 expression in tolerogenic DCs and B cells. Six-week-old C57BL / 6 female mice were given 5 samples each to the fourth mammary pad (two mammary pads in total per mouse). * 105 E0771 cells were injected. Mice were euthanized, and all PBMCs from the tumor site and spleen were activated with PIM and then analyzed by flow cytometry. Dead cells were excluded from the analysis by Zombie live / dead staining. Figure 15A shows a box plot analysis of the relative expression levels of CD74 in several immune cell populations. The graph in Figure 15B shows the mean and SD percentage of CD74 expression on B cells in the spleen and TME (B cells in the spleen n=4; B cells in the TME n=4). The graph in Figure 15C shows the mean and SD percentage of CD74 expression on dendritic cells in the spleen and TME (dendritic cells in the spleen n=4; dendritic cells in the TME n=4). * p<0.05, **p<0.005.

[0103] Figures 16A–16M illustrate gating strategies for IL-10+ DCs and B cells, as well as IL-12+ DCs. PBMCs from tumor sites were activated with PIM and then analyzed by flow cytometry. Dead cells were excluded from the analysis by Zombie live / dead staining. In Figure 16A, after excluding LY6-C+, F4 / 80+, and CD19, DC cells were analyzed for CD11c expression. After excluding LY6-C+, F4 / 80+, and CD11c, B cells were analyzed for CD19. In Figures 16B–16E, IL-10+ expression on DCs was measured by comparing inactivated cells (WT and CD74- / - samples) with those activated with PIM. In Figures 16F–16I, IL-12+ expression on DCs was measured by comparing inactivated cells (WT and CD74- / - samples) with those activated with PIM. In Figures 16J-16M, IL-10+ expression on B cells was measured by comparing deactivation with PIM-activated IL-10+ in either WT or CD74- / - samples.

[0104] Figures 17A–17I show that CD74 regulates the accumulation of tolerogenic immune cells in TME. Six-week-old C57BL / 6 and CD74- / - female mice were given 5 doses each to the fourth mammary pad (two mammary pads in total per mouse). *105 E0771 cells were injected. Figure 17A shows the frequency of IL-10+ B cells among all B cells (WT n=8; CD74- / - n=7). In Figure 17B, after excluding LY6-C+, F4 / 80+, and CD19+ cells, DC cells were analyzed for CD45, CD11c, and IL-10 expression. The graph shows the frequency of IL-10+ DCs in the tumor site (WT n=14; CD74- / - n=11). Figure 17C shows the frequency of IL-10+ macrophages after excluding monocytes and DCs (WT n=5; CD74- / - n=5). Figure 17D shows the frequency of CD4+ T cells (WT n=9; CD74- / - n=8). Figure 17E shows the frequency of CD8+ T cells (WT n=9; CD74- / - n=8). Figure 17F shows the frequency of FOXP3+ T cells among all CD4+ T cells (WT n=9; CD74- / - n=8). Figure 17G shows the frequency of IFN-γ+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=4). Figure 17H ​​shows the frequency of PD1+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=4). Figure 17I shows the frequency of CD62L+ T cells among all CD8+ T cells (WT n=5; CD74- / - n=5). ns p>0.05, * p<0.05, ** p<0.005, **** p < 0.00005.

[0105] Figures 18A-18E illustrate how the CD74 inhibitor DRQ restores the immunogenicity of TME. Six-week-old female C57BL / 6 mice were given 5 of each of the fourth mammary pads (two mammary pads in total per mouse). *105 E0771 cells were injected. DRQ was administered intravenously on days 10, 11, 12, 13, and 14 post-tumor transplantation. Figure 18A shows the frequency of IL-10+ B cells among all B cells (PBS n=7; DRQ n=8). In Figure 18B, after excluding LY6-C+, F4 / 80+, and CD19+ cells, DC cells were analyzed for CD45, CD11c, and IL-10 expression. The graph shows the frequency of IL-10+ DCs at the tumor site (PBS n=8; DRQ n=8). Figure 18C shows the frequency of CD4+ T cells (PBS n=4; DRQ n=5). Figure 18D shows the frequency of FOXP3+ T cells among all CD4+ T cells (PBS n=4; DRQ n=5). Figure 18E shows the frequency of CD8+ T cells (PBS n=4; DRQ n=5). ns p>0.05, * p<0.05, ** p<0.005.

[0106] Figures 19A-19O illustrate how CD74 deficiency in DCs specifically affects the dendritic cell population. Six-week-old female CD11c-Cre×CD74flox×CD74flox mice were sacrificed, their spleens were harvested, processed into single-cell suspensions, and all PBMCs were isolated. The graph in Figure 19A shows the mean and SD percentage of monocytes among all viable cells (WT n=5, cKO n=5). The graph in Figure 19B shows the mean and SD percentage of macrophages among all viable cells (WT n=5, cKO n=5). The graph in Figure 19C shows the mean and SD percentage of B cells among all viable cells (WT n=5, cKO n=5). The graph in Figure 19D shows the mean and SD percentage of dendritic cells among all viable cells (WT n=5; CKO n=5). The graphs in Figures 19E-19H show the mean and SD percentage of CD74 expression on monocytes (Figure 19E), macrophages (Figure 19F), B cells (Figure 19G), and DCs (Figure 19H) (WT n=6; cKO n=6). The graph in Figure 19I shows the mean and SD percentage of CD4+ T cells among all living cells (WT n=6; cKO n=6). The graph in Figure 19J shows the mean and SD percentage of CD8+ T cells among all living cells (WT n=6; cKO n=6). The graph in Figure 19K shows the mean and SD percentage of CD62L+ T cells among all CD4+ T cells (WT n=6; cKO n=6). The graph in Figure 19L shows the mean and SD percentage of CD103+ T cells among all CD8+ T cells (WT n=6; cKO n=6). The graph in Figure 19M shows the mean and SD percentage of FOXP3+ T cells among all CD4+ T cells (WT n=4; cKO n=4). Figures 19N-19O show CD74 expression in the CD4+ (Figure 19N) and CD8+ (Figure 19O) populations. ns p>0.05. ** P<0.005, *** p<0.0005.

[0107] Figures 20A–20J illustrate that CD26 and CD68 are not specific markers for DCs or macrophages. PBMCs from the spleen of naive mice were analyzed by flow cytometry. Figure 20A shows that dead cells were excluded from the analysis by Zombie live / dead staining. Figure 20B shows that macrophages and monocytes were gated to F4 / 80 and LY-6c, respectively. Figure 20C shows that the double-negative population was analyzed for CD19 and CD11c to detect DCs and B cells. In Figure 20D, the DCs obtained in Figure 20C were analyzed for CD26. Figures 20E–20F show that the CD45+ population was gated to CD26 as a dendritic cell marker. Figures 20G–20H show that CD26+ DCs were analyzed for F4 / 80, LY-6c, and CD19. Figure 20I shows that the CD45+ population was gated to CD64 as a macrophage marker. In Figure 20J, CD64+ macrophages were analyzed for the expression of CD19 and LY-6c.

[0108] Figures 21A-21D illustrate how conditional knockout of CD74 in mature B cells affects IL-10 release from monocytes and macrophages. Six-week-old female CD23-Cre×CD74flox×CD74flox mice were given 5 injections into each of the fourth mammary pads. *105 E0771 cells were injected. After 21 days, the mice were euthanized, the tumors were harvested, processed into single-cell suspensions, and all PBMCs were isolated from the tumor sites. The cells were then activated with PIM and analyzed by flow cytometry. The graph in Figure 21A shows the mean and SD percentage of IL-10+ monocytes out of all monocytes (WT n=4, cKO n=4). The graph in Figure 21B shows the mean and SD percentage of IL-12+ monocytes out of the entire population (WT n=4, cKO n=4). The graph in Figure 21C shows the mean and SD percentage of IL-10+ macrophages out of all macrophages (WT n=4, cKO n=4). The graph in Figure 21D shows the mean and SD percentage of IL-12+ macrophages out of all (WT n=4, cKO n=4). (ns)p>0.05, ( * P<0.05.

[0109] Figures 22A-22I illustrate that conditional knockout of CD74 in mature B cells reduces the frequency of tumor-infiltrating immunosuppressive cells. Six-week-old female CD23-Cre×CD74flox×CD74flox mice were given 5 cells each in the fourth mammary pad. *105 E0771 cells were injected. After 21 days, the mice were euthanized, the tumors were harvested, processed into single-cell suspensions, and all PBMCs were isolated from the tumor site. The cells were then activated with PIM and analyzed by flow cytometry. Figure 22A shows the frequency of IL-10+ B cells among all B cells (WT n=7; cKO n=7). Figure 22B shows the frequency of IL-10+ DCs in the tumor site (WT n=8; CD74 cKO n=7). Figure 22C shows the frequency of CD4+ T cells (WT n=7; CD74 cKO n=8). Figure 22D shows the frequency of FOXP3+ T cells among all CD4+ T cells (WT n=4; CD74 cKO n=4). Figure 22E shows the frequency of CD8+ T cells (WT n=8; CD74 cKO n=7). Figure 22F shows the frequency of PD1+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). Figure 22G shows the frequency of IFN-γ+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). Figure 22H shows the frequency of CD103+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). Figure 22I shows the frequency of CD62L+ T cells among all CD8+ T cells (WT n=4; CD74 cKO n=4). ns p>0.05, * p<0.05, **** p < 0.00005.

[0110] Figures 23A-23C show that downregulation of CD74 in DCs induces a pro-inflammatory pathway, and the results of RNA-seq analysis are shown. Six-week-old female C57BL / 6 mice were given 5 samples to each of the fourth mammary gland pads (a total of two mammary gland pads per mouse). *105 E0771 cells were injected. Ten days later, DRQ was intravenously injected for four consecutive days (days 10-13). After 21 days, tumor size was measured and the mice were euthanized. The tumors were processed into single-cell suspensions, and DCs were selected from the tumor microenvironment of mice treated with either PBS or DRQ. Four replicas were used from each group. Figure 23A shows a visualization of Ingenuity Pathway Analysis (IPA), where relevant pathways are ordered by significance (p-value) calculated in IPA by right-hand Fisher's exact t-test. Pro-inflammatory pathways show positive z-scores, indicating increased pathway activity in DRQ compared to PBS-treated mice. Figure 23B shows the use of IPA Upstream Regulator Analysis to predict upstream regulators involved in the observed changes in gene expression. IL-10 receptor is shown to be downregulated in DRQ-treated DCs. Figure 23C shows gene interactions in which some genes are upregulated while others are repressed. Genes associated with the immunogenic response of DCs are increased in DRQ compared to mice treated with PBS.

[0111] (Example 2) The effect of DRQ in melanoma In patients with advanced melanoma, higher MIF expression is associated with a worsening of the outcome. Analysis of the publicly available The Cancer Genome Atlas (TCGA) dataset revealed that in a cohort of cutaneous melanoma (SKCM) patients, high MIF expression was associated with a shortened overall survival (Figure 1). In a cohort of TCGA melanoma patients after any treatment, MIF expression levels were significantly higher in patients with a worse outcome compared to those who responded. Furthermore, queries in SKCM patients treated with anti-PD-1 demonstrated that high MIF expression was associated with reduced survival (de Azevedo et al. Oncoimmunology 9(1):1846915, 2020).

[0112] MIF is expressed by tumor cells and downregulated by DRQ. B16F10 cells were incubated for 48 hours with either a vehicle control (Tris-HCl pH 8.5 + 8.5% sucrose) or 25 μg or 50 μg of DRQ, and the supernatant was collected. As determined by ELISA, MIF expression was increased in the control group but, as expected, dose-dependently decreased in the DRQ-treated group (p<0.01, Figure 2).

[0113] DRQ controls tumor growth in a focal intradermal tumor model. In 8-week-old C57BL / 6 mice, 5 × 10¹⁶ sphincters were administered on day 1. 5 Individual B16F10 mouse melanoma cells were injected intradermally. Mice were then treated with DRQ (100 μg dose) or a vehicle control three times a week for two weeks, starting from the first visible tumor (day 5). Tumors were harvested to a diameter of 2 cm according to IACUC requirements. DRQ demonstrated a statistically significant survival benefit compared to the vehicle control in these localized tumors (Figure 3).

[0114] DRQ increases immune infiltration into the tumor microenvironment. Microscopic images of intradermal B16F10 melanoma tumors from mice treated with DRQ demonstrated active immune infiltration within the tumors compared to vehicle controls (Figure 4). The tumors were deaggregated and then analyzed by flow cytometry. Flow data demonstrated a significant infiltrating immune population, with approximately 11% of the immune population consisting of CD8+ T lymphocytes; in contrast, similar tumor samples from vehicle controls had significantly fewer immune cells identifiable by flow cytometry.

[0115] DRQ increases the proportion of TRP2-reactive CD8+ cells in B16F10 tumors. B16F10 tumors from mice treated with DRQ and those treated with vehicle controls were incubated with TRP2-PE tetramer and analyzed by flow cytometry (Figure 5). DRQ resulted in a significant increase (30.8%) of TRP2-reactive CD8+ infiltrating lymphocytes in the tumors compared to the vehicle control (2.7%).

[0116] RNA-Seq data demonstrate that DRQ reduces ERK expression in B16F10 cells. Bulk RNA sequencing was performed on DRQ-treated B16F10 cells and controls to confirm that DRQ functions by reducing ERK expression and to identify other differentially expressed genes. Read counts were analyzed and differences in gene expression between populations were assessed using DEseq2. Multiple comparisons were controlled by fitting count data to a negative binomial generalized linear model and performing Benjamini-Hochberg correction. In particular, DRQ samples had significantly reduced levels of MAPK1 (ERK2) compared to controls (p<0.05). DRQ also downregulates TLR-2 and TLR-4, as well as other pro-inflammatory messengers that play important roles in the inflammatory response.

[0117] DRQ downregulated the expression of pERK and pSTAT3. B16F10 cells were grown in culture and then incubated with either a vehicle or 50 μg of DRQ for 1 hour. 500,000 cells were rotated and lysed from each condition. The lysates were collected and subjected to SDS-PAGE in a 10–20% gradient gel under reducing conditions. After electrophoresis, proteins were transferred to PVDF to evaluate phosphorylated ERK1 / 2 (pERK1 / 2) and pSTAT3. DRQ downregulated phosphorylated pERK1 / 2 and pSTAT3 (Figure 6).

[0118] Toxicity Assessment: Formal toxicity studies were conducted. The maximum feasible dose (MFD) of 25 mg / kg was well tolerated when administered intravenously daily for 7 days to male and female C57BL / 6 mice. There were no clinical signs, no effects on body weight, and no lesions were observed on macroscopic autopsy.

[0119] (Example 3) Determination of the minimum effective and optimal dose of DRQ We will conduct studies to determine the minimum effective and optimal doses of DRQ (DRhQ or DRmQ) in BRAF wt mouse melanoma models B16F10 and YUMM4.1. The minimum effective dose is the dose that shows the least tumor growth with acceptable toxicity. In this model, animals will be thoroughly evaluated for signs of toxicity.

[0120] Mice will be observed at least daily for their condition, weight, and food intake. A complete autopsy will be performed at the time of animal death or at the study endpoint, including organ weight, histopathology, hematology, and clinical chemistry. Two mouse melanoma models will be used in the optimal dose and dose range finding study (B16F10 and YUMM4.1). 1 × 10⁶ doses will be injected into the flanks of 8-9 week old male and female C57BL / 6 mice. 5 Nine mouse melanoma cells are injected intradermally. Upon detection of engraftment and visible tumors, mice are treated with either DRQ iv (1 μg, 10 μg, 25 μg, 50 μg, 100 μg, 250 μg, and 500 μg (500 μg is MFD) or a vehicle control three times a week for two weeks. Tumor growth is monitored daily with conventional calipers, and mice are euthanized when the tumor diameter reaches 2 cm. The tumors are harvested and subjected to cyclic multiplexed immunofluorescence (CQ) imaging. FFPE slides are prepared for immunofluorescence (cycIF), flow cytometry, and protein and transcriptional analysis. Cells are sorted into CD45+ fraction (immune cells) and tumor fraction (CD45- cells). Each fraction is then analyzed by Western blotting for the expression of CD74, CD44, PD-L1, PD-L2, HIF1a, MIF, and pERK1 / 2. Soluble CD74 (sCD74) in plasma at the time of sacrifice is also measured.

[0121] (Example 4) Evaluation of mechanisms related to sustained tumor control by DRQ Male and female 8-9 week old C57BL / 6 mice were given 1 x 10⁶ injections into their flanks.5 Individual mouse melanoma cells were intradermally injected, and upon engraftment and detection of visible tumors, the mice were treated with 1) vehicle control or 2) DRQ (DRhQ or DRmQ) three times a week for two weeks: (2 experimental groups × 2 cell lines × 10 mice / group × 2 sexes = 80 mice) for each mouse background. Tumors were harvested in 2 cm diameter portions; some were used for FFPE slides for cycIF, and the remainder were dissociated. Cells were sorted into CD45+ fraction and tumor fraction as in Example 2. Specific antitumor immunity was measured by tetramer staining between CD8+ T cells using flow cytometry. TRP1, TRP2, and gp100 are melanoma-specific antigens for which tetramers are available (Immudex). In addition, the number of invasive CD8+ T cells, CD4+ T cells, MDSCs, NK cells, and Tregs was assessed using flow cytometry. Cell surface expression of CD74, CD44, PD-L1, and PD-L2 will be evaluated by flow cytometry. pERK1 / 2, MIF, and all CD74 will be analyzed by Western blotting. Single-cell RNA-seq (scRNA-seq) will be performed on representative mice from each group. cycIF and RNA-seq experiments will allow for the identification of the effects of DRQ on all immune cells.

[0122] Multiplex Immunofluorescence: Cyclic multiplex immunofluorescence (CycIF) utilizes in situ hybridization of complementary oligonucleotides for labeling, facilitating sequential round tagging and signal removal for imaging. Therefore, CycIF allows for the visualization of endogenous protein expression while maintaining spatial context in situ. This can potentially enable simultaneous imaging of more than 20 unique epitopes (see Table 1 for targets). [Table 1-1] [Table 1-2]

[0123] Image Processing, Data, and Statistical Analysis: Multiplexed images are processed and analyzed using the FCS Express 6 Image Cytometry software package. Wilcoxon's signed-rank test is used to determine statistically significant differences between paired datasets, followed by Spearman's correlation coefficient to assess correlations between cell percentages and densities across cell lineages. Spatial analysis utilizes Ripley's K, a point pairwise correlation function, to determine spatial correlations between immune cell subtypes. P-values ​​are corrected for multiple comparisons using Benjamini and Hochberg's false detection rate (FDR).

[0124] Overview of the single-cell approach: scRNA-seq profiling assigns high-resolution molecular identity by generating highly reliable gene expression levels. Each single cell is also evaluated for 32 proteins by epitopes (Table 1) and matched to a standard immune class. The BD Rhapsody single-cell platform is used, followed by standard Illumina sequencing. The BD Rhapsody pipeline is used for initial quality control and filtering, batch correction, and read alignment to generate gene and protein epitope count matrices. The Seurat R bioinformatics package is used for more detailed analyses, including subpopulation clustering / identification.

[0125] Single-cell preparation: Tumor tissue is dissociated using collagenase IV and hyaluronidase for 1 hour. The resulting cells are stained with a cocktail of anti-CD45 antibody and AbSeq antibody (BD AbSeq; BD Bioscience, Table 1). Cells are stained with the 7-AAD survival marker and CD45+ and tumor fractions are sorted. A total of approximately 10,000 cells are then loaded from each sorted flow sample into a BD Rhapsody cartridge for single-cell capture: 5,000 CD45+ immune cells and 5,000 tumor cells.

[0126] cDNA library preparation and sequencing: The BD Rhapsody system is used for single-cell capture, as well as cDNA preparation and amplification. The pooled final libraries are sequenced on a NovaSeq 6000 sequencer to a sequencing depth of 100,000 reads per cell for the WTA mRNA library and 32,000 reads per cell for the AbSeq library (1,000 reads per cell per antibody with 32 antibodies) (100 bp paired ends).

[0127] Data Analysis and QC: Raw single-cell RNA-seq FASTQ files are processed according to the BD Biosciences Rhapsody pipeline, which uses Bowtie2 to align reads to a reference genome and generate gene and protein epitope count matrices. Distribution-based error correction (DBEC) corrected molecular counts are used for all analyses using the R package Seurat3.0. Expression matrices are log-normalized. Uniform manifold approximation and projection is used for dimensionality reduction. Negative binomial generalized linear models are implemented using the sc transform in the Seurat R package.

[0128] Detection of transcription markers: Once the immune population is determined, differential gene expression (DE) is performed on subpopulations applied to mean gene expression values ​​appropriately weighted relative to cell number using the R package Seurat. Co-regulated genes are identified by constructing gene co-expression networks based on mutual information (MI) criteria.

[0129] (Example 5) Materials and methods for evaluating CD74 as a therapeutic target in triple-negative breast cancer Mice: In this study, C57BL / 6, CD74 - / -Vert-x, CD23-cre×CD74-flox, and CD11c×CD74-flox mice were used. Vert-x mice were provided by C. Mauri, UCL. All animals were used at 6-8 weeks of age. Only females were used in the breast cancer model, and groups were matched for age and sex in each experiment. All animal procedures were approved by the Animal Experimentation Committee of the Weizmann Institute of Science. To produce Cre-CD23×flox-CD74 littermates, Cre-CD23 and flox-CD74 mice were mated, and the genotypes of CD74 and CD23 were screened by PCR. To produce Cre-CD11c×flox-CD74 littermates, Cre-CD11c and flox-CD74 mice were mated, and the genotypes of CD74 and CD11c were screened by PCR.

[0130] Breast cancer induction: Cells from the E0771 cell line were grown in complete RPMI medium containing 10% fetal bovine serum. For the tumor model, each of the fourth mammary gland pads (total of 2 mammary gland pads / mouse) of 6-8 week old C57BL / Vert-x competent female mice was given 5 PBS. * 10 5 Individual cells were injected via sc.

[0131] Tumor load measurement: Tumor size was evaluated by externally measuring the tumor length (L) and width (W) in two dimensions using calipers. Tumor volume (V, mm) 3 The value expressed as (V) was calculated using the following equation: V = (L × W, where W is the measurement of the shorter dimension and L is the measurement of the longer dimension) 2 (2).

[0132] Preparation of tumor-infiltrating lymphocytes (TILs): Tumor tissue was collected 21 days post-transplantation, cut into small pieces, and incubated in a digestion buffer (1 mg / ml collagenase A, 0.15 mg / ml hyaluronidase, 10% FBS, 1% P / S) in a 37°C incubator with gentle shaking for 45 minutes. The tumor tissue was then passed through a 100 μm cell strainer and washed three times with PBS. The dissociated tumor was then suspended in 8 ml of 44% Percoll solution and loaded onto a 5 ml 67% Percoll cushion. The sample was centrifuged at 1000 RCF for 20 minutes at room temperature without a brake. The intermediate fraction containing infiltrating mononuclear cells was collected and washed twice with PBS.

[0133] B cell isolation from spleen and bone marrow: Mouse spleens were post-mortem dissected and recovered in PBS. The organs were processed through a 100 μm cell strainer, and erythrocytes were lysed in erythrocyte lysis buffer for 5 minutes. Next, the cells were washed with PBS and processed through a 40 μm cell strainer. Finally, B cells were purified by positive B cell selection using B220 magnetic beads.

[0134] Immune cell isolation from the spleen: Mouse spleens were post-mortem dissected and recovered in PBS. The organs were processed through a 100 μm cell strainer and treated with erythrocyte lysis buffer for 3 minutes. The cells were then washed with PBS and processed through a 40 μm cell strainer.

[0135] Activation of regulatory B cells: For detection of IL-10 on B cells, 2.5 × 10⁶ units in complete ISCOVE medium. 6 B cells at a concentration of 100 cells / ml were cultured for 5 hours with PMA (100 ng / ml), ionomycin (1 μg / ml), monensin (1 μg / ml), and LPS (10 μg / ml).

[0136] Activation of tolerogenic DC cells: For detection of IL-10 on DC cells, 2.5 × 10⁶ units in complete ISCOVE medium were used. 6DC cells at a concentration of 100 cells / ml were cultured for 5 hours with PMA (100 ng / ml), ionomycin (1 μg / ml), monensin (1 μg / ml), and LPS (10 μg / ml).

[0137] Co-culture: E0771 cancer cells were seeded in 12-well plates. The following day, B cells were purified from splenocytes by positive B cell selection using B220 magnetic beads. The B cells were then cultured alone or co-cultured for 24 hours in 12-well plates in complete ISCOVE medium containing 10% FBS at a B cell / E0771 cell ratio of 1:5. Similarly, DCs were purified from splenocytes using a positive Mojosort mouse pan-dendritic cell isolation kit and added to E0771 or cultured alone for 24 hours in 12-well plates in complete RPMI medium containing 10% FBS at a ratio of 1:3. Under all conditions, the total number of cells in each well was 2.5. * 10 6 There were [number] cells. During the last 5 hours of culture, the cells were activated with PMA, ionomycin, monensin, and LPS.

[0138] Flow cytometry staining: FACS analysis was performed using FACS Canto. FACS data analysis was performed using FlowJo software. The antibodies are listed in Table 2 below. After staining the cells with specific antibodies against surface markers as previously described, they were fixed and permeabilized using the BD Cytofix / Cytoperm commercial kit or the eBioscience Transcription Factor Staining Buffer Set. The cells were then stained with intracellular antibodies.

[0139] In vivo CD74 blockade with DRQ-2: In vivo CD74 blockade was performed using DRQ in saline and 20 mM TRIS buffer (pH 8.5) as controls. Treatment with DRQ or PBS was initiated on day 10 after tumor cell administration and continued for 5 consecutive days. The inhibitor or control was injected into the tail vein (100 μg / 100 μl per mouse).

[0140] In vitro blockade of CD74 by LN-2 antibody: B cells were treated with LN-2 blocking antibody or IgG isotype control (150 μg / ml) for 24 hours. Under all conditions, the total number of cells in each well was 5. * 10 6 There was one.

[0141] MIF activation: 5×10 6 Cell cultures were activated for 24 hours with 150 ng / ml of MIF activator in 1 ml of culture medium in a 24-well plate.

[0142] In vitro DC suppression assay: Positive Mojosort mouse pandendritic cell isolation kit for WT and CD74 - / - DCs were isolated from mouse spleens. The isolated DCs were co-cultured with E0771 cancer cells in a 1:3 ratio for 24 hours. CD3 + Spleen CD3 using a mouse positive selection kit + T cells were isolated. The T cells were labeled with carboxyfluorescein succinimimidyl ester (CFSE) and seeded with DCs in a 1:1 ratio for 72 hours in the presence of anti-CD3 binding beads. The cells were then harvested, and T cell proliferation was analyzed by FACS.

[0143] In vitro SP1 blockade: E0771 cancer cells were seeded in 12-well plates. The following day, dendritic cells (DCs) were purified from splenocytes and then co-cultured with tumor cells in a 1:3 E0771 / DC cell ratio. Cells were cultured for 48 hours in complete RPMI medium + 10% FBS in the presence of 20 μM mitramycin or DMSO as a negative control. Under all conditions, the total number of cells in each well was 2.5. * 10 6 There was one.

[0144] In vitro IL-1β activation: E0771 cancer cells were seeded in 12-well plates. The following day, dendritic cells (DCs) were purified from splenocytes and then co-cultured with cancer cells in a 1:3 E0771 / DC cell ratio. Cells were cultured for 48 hours in complete RPMI medium + 10% FBS in the presence of 20 nM recombinant IL-1β antibody or PBS as a negative control. Under all conditions, the total number of cells in each well was 2.5. * 10 6 There was one.

[0145] RNA extraction for high-throughput experiments and RNA sequencing: Tumor-infiltrating DCs were sorted from dissociated TMEs. mRNA was extracted from these cells using the Dynabead mRNA purification kit, and an Illumina library was constructed from total mRNA using a bulk adaptation of the MARS-Seq protocol for Illumina TruSeq RNA sample preparation v2 (catalog no. RS-122-2002, Illumina)

[61] , according to the manufacturer's instructions. Indexed samples were sequenced in single-read mode on an Illumina NextSeq High output HiSEq 2500 instrument. Reads were aligned to the Mus_musculus genome (GRCm39) and the human genome (hg19) using STAR (2.7.3a)TopHat (v2.0.10). For the hg19 RefSeq gene, read counts based on annotations downloaded from Ensembl (release 106) were performed using HTSeq-Count (version 0.11.2) (v0.6.1p1). Differentially expressed genes were identified using DESeq2 with betaPrior, cooksCutoff, and independent filtering parameters set to False. Raw p-values ​​were corrected for multiple testing using the Benjamini and Hochberg procedures. Differentially expressed genes were determined by p-adj < 0.05, absolute multiplicative change < 1.5, and maximum raw count < 10.

[0146] RNA extraction and cDNA synthesis for RT-qPCR: Total RNA was isolated from cells using TRI Reagent® RNA isolation reagent according to the manufacturer's instructions. For cDNA synthesis, 500 ng or 1 μg of mRNA was used with the qScript® cDNA synthesis kit according to the manufacturer's instructions.

[0147] qRT-PCR: qRT-PCR was performed using a Lightcycler 480. The program used was as follows: 10' at 95°C, followed by 45 cycles of amplification (10'' at 95°C, 10'' at 60°C, 10'' at 72°C), followed by cooling to 4°C. The primers are listed in Table 3.

[0148] siRNA transfection: siRNA was introduced into 100 μl of OptiMem medium using a 2 mm gap cuvette containing 20 μg of siRNA at 225 mV and 5 msec, via electroporation with a Nepagene (Ichikawa, Chiba, Japan) Super Electroporator NEPA21 Type II. After transfection, cells were resuspended in RPMI 1% FCS medium and incubated for 24 hours.

[0149] ChIP qPCR:ChIP-seq was performed as previously described

[20] . For each sample, 5 × 10⁶ 5 Individual tumor-infiltrating DC cells were selected, activated with rmMIF or vehicle for 1 hour, then crosslinked with DSG (disuccinimidyl glutarate) and fixed. Chromatin was immunoprecipitated with anti-CD74 or anti-SP1 antibody and treated with ChIP-DNA. Samples were analyzed by qPCR for SP1 or IL-1β promoter.

[0150] Statistical Analysis: Data analysis was performed using GraphPad Prism (version 7.0f, GraphPad Software, Inc., La Jolla, CA, USA). For most experiments, the mean is provided along with SEM or SD. To determine the significance of the differences, two-way ANOVA and one-sided, two-sided, and two-way Student's t-tests were used as appropriate for each experiment. A p-value of 0.05 or less was considered statistically significant. [Table 2] [Table 3]

[0151] (Example 6) CD74 regulates tumor burden by controlling immunosuppressed populations in TNBC mouse models. To determine the in vivo role of CD74 in the mesenteric neuropathy (ME) of TNBC, E0771 mouse TNBC cells were introduced from C57BL / 6 or CD74-deficient (CD74 - / - Mice were orthotopically injected with CD74. Tumor size was monitored every 5 days from the injection day, and mice were sacrificed on day 21. As shown in Figures 7A-7C, the absence of CD74 significantly reduced tumor development and growth. Next, we analyzed CD74 expression on cells in the TNBC microenvironment. CD74 was widely expressed on immune cells, but its expression was upregulated in the tolerogenic population of DCs and B cells (Figure 15A). Furthermore, CD74 expression on tumor-infiltrating B cells and DCs was significantly higher than its level in the peripheral spleen population (Figures 15B-15C), suggesting a role of CD74 in the TNBC microenvironment.

[0152] Next, we determined the role of CD74 in cells derived from the tumor microenvironment. TNBC cells reprogram their microenvironments into an immunosuppressive phenotype by inducing IL-10 secretion in various immune cell populations [5]. Therefore, we analyzed antigen-presenting cells (APCs) and T cells in TMEs derived from WT and CD74-deficient mice.

[0153] DCs positively or negatively modulate the antitumor immune response depending on the expression of released cytokines and costimulatory molecules (which can bind to their T cell counterparts to induce their priming)

[36] . Therefore, DCs in the tumor microenvironment of WT and CD74-deficient mice were analyzed for their number and functionality by FACS analysis. As shown in Figure 7D, a significantly high percentage of CD74-deficient DCs were observed in the TME. These accumulated cells expressed higher levels of CD80 (Figure 7E) and lower percentages of IL-10 (Figure 7F; Figure 17B), suggesting that CD74-deficient DCs in the TME were more immunogenic and less tolerogenic (gating strategies are seen in Figures 16A-16I). Furthermore, Breg (gating strategies are seen in Figures 16J-16M; frequency is seen in Figure 17A), IL-10 + Macrophages, regulatory T cells, CD4 + T cells and CD8 + The percentage and frequency of wasted T cells were downregulated. CD8 + T cells or CD8 + CD62 + No difference was detected in T cell frequency, but CD8 was detected in TME of CD74 KO mice. + T cell cytotoxicity was induced (Figures 17C-17I).

[0154] CD74 deficiency affects mature B cells and CD4 +Because this results in a decrease in the number of T cells

[37] , we then determined whether the reduction in tumor burden detected in CD74-deficient mice was due to its function as an MIF receptor or to its role in controlling the number of T cells. To address this issue, we blocked the function of CD74 in C57BL / 6 mice and analyzed the infiltration and activity of immune cells. For this purpose, TNBC cells were injected into the mice. Starting on day 10, the mice were treated intravenously for 5 consecutive days (days 10–14) with either a partial MHC class II construct (DRQ) that inhibits ligand binding to CD74

[38] or a vehicle (saline) control. Blocking CD74 reduced tumor growth and tumor volume (Figures 7J–7K). Analysis of immune cells in TME showed that this treatment increased the percentage of immunogenic DCs, resulting in tolerogenic IL-10 in TME. + Downregulation of DC cells (tol-DC; Figure 7L; Figure 18B) and upregulation of IL-12-expressing DCs (Figure 7M) occurred. Furthermore, a decrease in infiltrating Breg and Treg cells was observed in mice treated with DRQ (Figures 7N-7O; Figures 18A, 18C, 18D), and CD8 + Upregulation of T cell frequency was also observed (Figure 18E). These results suggest that MIF positively modulates tumor suppressor ME in TNBCs by binding to CD74.

[0155] (Example 7) MIF induces CD74 immunosuppression in TME cells. Co-culture experiments were conducted to determine whether CD74 can induce in vitro expansion of tol-DCs and Bregs in the presence of cancer cells. Purified splenocytes from naive WT and CD74 KO mice were cultured either alone or in the presence of E0771 cells. After 24 hours, the cells were analyzed by FACS. The presence of cancer cells induced expansion of both tol-DCs (Figure 8A) and Breg populations (Figure 8B). This expansion disappeared in the presence of immune cells lacking CD74, highlighting the importance of CD74 as an immunosuppressive oncogenic factor.

[0156] Since MIF is a ligand for CD74, we then determined whether MIF secreted from TNBC cells contributes to the expansion of immunosuppressive DCs and Bregs. Purified DCs or B cells were cultured separately in the presence of E0771 cells and activated with recombinant mouse MIF (rmMIF) or vehicle for 24 hours. As shown in Figures 8C–8D, MIF induced mild expansion of IL-10-positive tol-DCs (Figure 8C) and Bregs (Figure 8D). Since cancer cells endogenously produce and release MIF, we directly determined whether MIF derived from malignant cells modulates the expansion of immunosuppressive cells. For this purpose, MIF expression in E0771 cells was knocked down with MIF siRNA (Figure 8E). Cancer cells expressing low or high levels of MIF were then cultured with DCs or B cells, and their phenotypes were analyzed. Downregulation of MIF expression significantly reduced the expansion of tol-DCs (Figure 8F) and Bregs (Figure 8G). Therefore, MIF secreted from malignant cells plays a crucial role in regulating the expansion of tol-DCs and Breg cells.

[0157] (Example 8) The effect of CD74 on tumor growth is specific to dendritic cells. To determine which antigen-presenting cells (B cells or DCs) lacking CD74 regulate tumor growth, conditional CD74 - / - Using Cre-flox mice (cKO), CD74 was exclusively downregulated in mature B cells and DCs. Specifically, CD23 + WT mice that specifically lack CD74 in mature B cells, and CD11c +Mice lacking CD74 in their dendritic cell population were injected with E0771 tumor cells, tumor size was monitored weekly, and the mice were sacrificed on day 21. The absence of CD74 in mature B cells did not affect tumor load (Figure 9A) or the phenotype of invasive DCs. Similar levels of IL-10 (Figure 9B) and IL-12 (Figure 9C) were detected in DCs from both wild-type mice and animals lacking CD74 in their B cell populations. However, CD74 deficiency in mature B cell populations resulted in a significant decrease in Bregs in the TME (Figure 9D), suggesting a direct role of CD74 in Breg regulation. + To further investigate the role of CD74 knockdown in mature B cells, in vitro co-cultures of WT or CD23 cKO-derived spleen DC cells with or without E0771 cells were performed. CD74 deficiency in the mature B cell population did not affect IL-10 release from naive or cancer-activated DCs (Figure 9E), but co-culture of B cells with E0771 cells resulted in weaker induction of Breg (Figure 9F).

[0158] To track the role of CD74 in dendritic cells (DCs), CD74 expression was downregulated in CD11C+ cells. The specificity of CD74 deletion to DCs was first examined by analyzing the accumulation of CD11c-expressing populations and their CD74 expression (Figures 19A-19H), and by evaluating the effects of cKO on T cell populations in naive mice (Figures 19I-19O). Downregulation of CD74 expression was specific to the DC population (gating strategies in Figures 19H and 20A-20K). In contrast to the limited effect of CD74 deficiency in B cells on tumor burden, CD74 deficiency in DCs significantly reduced tumor growth. Mice deficient in CD74 in the CD11c population developed significantly smaller tumors compared to WT mice (Figures 10A-10C). DCs lacking CD74 in TME showed reduced IL-10 levels (Figure 10D, Figure 22B), demonstrating a direct role of CD74 in regulating the tolerogenic DC phenotype. In addition, these mice showed reduced IL-10 levels.+ Reduction in the accumulation of single cells and macrophages, and no difference in their IL-12 release (Figs. 21A - 21D), Breg (Fig. 10E, Fig. 22A), and Treg (Fig. 10F, Fig. 22D), and a CD8 + T cell increase (Fig. 10G, Fig. 22E) in the TME characterized by a more cytotoxic and less exhausted phenotype (Figs. 10H - 10I, Figs. 22F - 22G). No difference was detected in the frequency of CD4 + T cells (Fig. 22C) and the frequency of CD8+CD103+ or CD8+CD62L+ cells (Figs. 22H - 22I).

[0159] To further verify the effect of CD74 knockdown in DCs on B cells, in - vitro co - cultures were performed. Splenic DCs or B cells purified from CD11c cKO mice and cultured with the E0771 cell line revealed a reduction in both tol - DC (Fig. 10J) and Breg (Fig. 10K), and this effect was not observed in CD23 CKO mice. Thus, blockade of CD74 in CD11c + cells reduced the levels of tol - DC, Breg, and Treg and their immunosuppressive functions in vivo and in vitro. Taken together, these results suggest that CD74 expressed in DCs, rather than B cells, is crucial for regulating immune cell suppression at the tumor site.

[0160] (Example 9) CD74 expressed in DCs mediates crosstalk with Breg To further evaluate the CD74-mediated crosstalk between tol-DC and Breg, WT, CD74-deficient DC, and B cells were cultured together in vitro in the presence of E0771 cells. CD74 deficiency in both cell types synergistically reduced the expansion of tol-DC (Figure 11A) and Breg (Figure 11B). However, the absence of CD74 in the B cell population did not affect either Breg or tolerogenic DC, but DC lacking CD74 reduced not only the expansion of tol-DC (Figure 11A) but also the expansion of Breg (Figure 11B), suggesting the role of CD74 in governing Breg expansion. To determine whether DC directly regulates Breg expansion, WT and CD74 - / - DC were cultured with E0771 cells for 24 hours. Then, naive B cells were seeded together with pre-activated DC. As shown in Figure 11C, the absence of CD74 in DC strongly reduced IL-10 release in B cells, further supporting the role of CD74 on DC in mediating Breg expansion.

[0161] To understand whether B cells can affect the phenotype of DC, B cells were incubated with anti-CD74 blocking, LN-2, or IgG control antibody and activated with E0771 cells for 24 hours. Then naive DC were seeded together with pre-activated B cells with cancer. CD74 inhibition did not regulate the expansion of tol-DC (Figure 11D).

[0162] To further confirm the immunosuppressive role of CD74 in DC activation, their functions in T cell proliferation and suppression were analyzed. WT naive spleen CD3 + T cells were stained with cell proliferation dye (CPD) and then co-cultured with WT or CD74 KO spleen DC pre-activated with E0771 cells. Downregulation of CPD expression in T cells correlates with the proportion of dividing cells. Induced CD8 +T cell proliferation was detected in cells incubated with CD74 KO DCs (Figure 11E). Furthermore, lower levels of Treg were observed in the presence of CD74 KO DCs, further supporting the immunosuppressive role of CD74 expressed in DCs in the context of TNBC (Figure 11F). In addition, CD8 + T cell cytotoxicity was evaluated by analyzing interferon-γ (IFN-γ) protein levels. Elevated levels of IFN-γ were detected in T cells co-cultured with CD74-deficient dendritic cells (DCs), indicating more potent cytotoxicity (Figure 11G). Therefore, CD74 modulates DC functionality in TME.

[0163] (Example 10) CD74 binds to the IL-1β and SP1 promoters, which then regulate the expansion of tol-DC and Breg. The mechanism of action of CD74 expressed on dendritic cells (DCs) was investigated. TNBC cells were injected into mice. Starting on day 10, mice were intravenously treated with either PBS or DRQ for 5 consecutive days (days 10–14). DCs were sorted from TME, and purified RNA was then analyzed by RNA-seq. Inhibition of CD74 resulted in more potent DC activation, as seen in the upregulation of major pathways in the antitumor immune response, such as crosstalk between DCs and NK cells [39, 40] or classical markers of macrophage activation essential for the antitumor response

[41] . Furthermore, pathways involved in metabolic signaling crucial for cancer progression, such as the PPAR cascade, were downregulated

[42] (Figure 23A).

[0164] Furthermore, as predicted, upstream regulators involved in gene expression changes were observed in mice treated with DRQ. The IL-10 receptor was downregulated in DCs treated with a CD74 inhibitor (Figure 23B). Analysis of downstream events showed an elevated pro-inflammatory response, mainly regulated by the release of pro-inflammatory cytokines from DRQ-treated DCs (Figure 23C). In addition, blocking CD74 resulted in downregulation of cancer-related diseases and activation of immune cell migration and interaction. Among the differentially expressed genes in DRQ-treated DCs, SP1 was downregulated, as confirmed by RT-qPCR (Figure 12A), while IL-1β mRNA levels were upregulated under these conditions (Figure 12B). The same effect was observed in CD74-deficient DCs (Figures 12C-12D).

[0165] SP1 is associated with immunosuppression in several cancer types, including TNBC [43, 44], and IL-1β is involved in the activation of pro-inflammatory pathways. IL-1β expression in TME is associated with cancer progression

[45] , but IL-1β-expressing DCs are more immunogenic and reduce the proliferation of immunosuppressive cells

[46] .

[0166] To verify that IL-1β controls IL-10 expression and immunosuppressive ME in DCs, WT DCs were cultured in the presence of E0771 cells and incubated with either IL-1β or PBS. IL-1β controls IL-10 expression. +DC expansion was inhibited (Figure 13A). Furthermore, to determine whether IL-1β-stimulated DCs modulate Breg expansion, B cells were cultured with DCs pre-activated with E0771 and treated with either IL-1β or the vehicle. As shown in Figure 13B, IL-1β treatment of DCs reduced Breg expansion, confirming that IL-1β treatment makes DCs more immunogenic and consequently reduces their ability to induce Breg. Therefore, DCs have a direct effect on Breg expansion, a process attenuated by IL-1β release. Furthermore, to evaluate whether B cells are directly affected by IL-1β, B cells were cultured in the presence of E0771 and treated with either IL-1β or the vehicle. As shown in Figure 13C, IL-1β only slightly reduced Breg expansion. To determine whether this effect is DC-mediated, DCs were added to B cell cultures containing E0771 cells. The presence of dendritic cells (DCs) together with B cells strongly upregulated IL-10 release, suggesting that DCs strongly controlled Breg expansion in the presence of cancer cells, and that IL-1β played a crucial role in reducing IL-10 release (Figure 13C).

[0167] CD74-ICD is a transcriptional regulator in both healthy states and diseased states [20, 47]. To determine whether CD74 attenuates IL-1β expression in DCs, DCs derived from TMEs were screened, and the binding of CD74-ICD to the IL-1β promoter region was analyzed by chromatin immunoprecipitation qPCR (ChIP-qPCR). Significant enrichment of CD74-ICD binding to the IL-1β promoter region was detected in DCs (Figure 13D), and therefore, this regulates its transcription.

[0168] Next, we investigated the role of SP1 in an immunosuppressive environment. To verify that SP1 contributes to IL-10 secretion by DCs, WT DCs were cultured in the presence of E0771 cells and incubated with either mitramycin (MIT) or DMSO, both SP1 inhibitors. MIT treatment was used to reduce IL-10 secretion. +This eliminated the DC expansion and suggested a direct correlation between SP1 and IL-10 release (Figure 14A).

[0169] To determine whether SP1 can directly induce Breg expansion via DCs, B cells were cultured with DCs pre-activated with E0771 and treated with either MIT or DMSO control (Figure 14B). DCs treated with MIT adversely affected Breg expansion, indicating that DCs control Breg expansion, a process enhanced by SP1. To evaluate the role of SP1 on B cells, these cells were cultured in the presence of E0771 and treated with either MIT or DMSO. Blocking SP1 in B cells alone did not affect Breg expansion. However, the addition of DCs to this culture increased the percentage of Bregs and thus promoted the effect of MIT on IL-10 release (Figure 14C). Finally, to determine whether CD74 regulates SP1 transcription in DCs, DCs sorted from TME were activated with either PBS or MIF for 1 hour, and the binding of CD74-ICD to the SP1 promoter region was determined by ChIP-qPCR analysis (Figure 14D). MIF activation induced a significant enrichment of CD74-ICD binding to the SP1 promoter region, demonstrating a direct impact on SP1 transcriptional regulation via the MIF-CD74 axis (Figure 14E). Since IL-1β transcription is inhibited by CD74, we determined whether SP1 as a transcription factor regulates IL-1β expression in a MIF-CD74-dependent manner. As shown in Figure 14F, SP1 as a transcription factor has the ability to bind to the IL-1β promoter upon MIF activation and downregulate its transcription. Blocking SP1 resulted in upregulation of IL-1β (Figure 14G). These results suggest that CD74-ICD in DCs binds to the SP1 promoter, which regulates the release of IL-1β and IL-10, and subsequently governs the expansion of the Breg population.

[0170] [ka] [Chemical] [Chemical] [Chemical] [Chemical] [Chemical] [Chemical] [Chemical] [Chemical]

[0171] It will be apparent that the exact details of the methods or compositions described can be changed or modified without departing from the spirit of the described aspects of the present disclosure. The inventors claim all such modifications and variations that fall within the scope and spirit of the following claims. [Table 4-1] [Table 4-2] [Table 4-3]

Claims

1. A method for treating a subject with cancer, wherein the therapeutically effective amount A recombinant polypeptide containing an antigenic peptide covalently bound to a DRα1 domain or a portion thereof, which contains a glutamine residue at the position corresponding to amino acid 50 of SEQ ID NO: 1 or SEQ ID NO: 2; or Nucleic acid encoding the recombinant polypeptide A method comprising administering the above to the subject.

2. The method according to claim 1, wherein the recombinant polypeptide further comprises a linker between the antigenic peptide and the DRα1 domain.

3. The method according to claim 2, wherein the linker comprises a first glycine-serine spacer, a thrombin cleavage site, and a second glycine-serine spacer.

4. The method according to claim 1, wherein the antigenic peptide is myelin oligodendrocyte glycoprotein (MOG)-35-55 or myelin basic protein (MBP)-85-99.

5. The method according to claim 4, wherein the MOG-35-55 is human MOG-35-55 or mouse MOG-35-55.

6. The method according to claim 1, wherein the recombinant polypeptide comprises or comprises the amino acid sequence of SEQ ID NO: 1 or SEQ ID NO:

2.

7. The method according to claim 1, wherein the subject is administered approximately 0.1 mg / kg to approximately 10 mg / kg of the recombinant polypeptide.

8. The method according to claim 1, wherein the cancer is a solid tumor or a hematological malignancy.

9. The method according to claim 8, wherein the solid tumor is melanoma, glioblastoma, or breast cancer.

10. The method according to claim 1, wherein the cancer in question does not express a BRAF mutation.

11. The method according to claim 10, wherein the cancer in question does not express the BRAF V600 mutation.

12. The method according to claim 1, wherein the subject having cancer is resistant to immune checkpoint blockade therapy.

13. The method according to claim 1, further comprising administering one or more additional treatments to the subject.

14. The method according to claim 13, wherein the one or more additional treatments include one or more of surgery, radiation, chemotherapy, and immunotherapy.

15. The method according to claim 14, wherein the immunotherapy includes immune checkpoint blockade therapy.

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