WO2016168607A1 - Compositions and methods of muc13 antibodies for cancer treatment and diagnosis - Google Patents

Abstract

The present disclosure provides an antibody, or a binding fragment thereof, is provided. The antibody, or a binding fragment thereof, binds specifically to a mucin 13 (MUC13) protein expressed on the surface of a cancer cell. In another embodiment, a pharmaceutical composition is provided. The pharmaceutical composition comprises the antibody, or binding fragment thereof, and a pharmaceutically acceptable carrier, excipient, or diluent. In another embodiment, a method of treating a cancer in a patient is provided. In yet another embodiment, a method of diagnosing a cancer in a patient is provided. In another embodiment, a diagnostic kit is provided, wherein the kit comprises the antibody. In various aspects, the antibody binds to a domain of the MUC13 protein.

Description

COMPOSITIONS AND METHODS OF MUC13 ANTIBODIES FOR CANCER

TREATMENT AND DIAGNOSIS

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit under 35 USC § 119(e) of U.S. Provisional

Application Serial No 62/147,800, filed on April 15, 2015, the entire disclosure of which is incorporated herein by reference.

SEQUENCE LISTING

The instant application contains a Sequence Listing which has been submitted electronically in ASCII format and is hereby incorporated by reference in its entirety. Said ASCII copy, created on April 13, 2016, is named 65022_252163_SL.txt and is 31,504 bytes in size.

TECHNICAL FIELD

The invention relates to an antibody, or a binding fragment thereof, which binds specifically to a MUC13 protein. The invention includes compositions, methods, and kits comprising the antibody for the treatment and diagnosis of disease in patients.

BACKGROUND AND SUMMARY OF THE INVENTION

Cancer is a disease that manifests in over 100 different forms. Some of the most difficult forms of cancer to treat include pancreatic cancer, colorectal cancer, stomach cancer, and ovarian cancer. For example, pancreatic cancer (PanCa) is the fourth leading cause of cancer related deaths in the United States due to very limited therapeutic options. Only 10- 20% of patients appear with localized disease that is suitable for resection. Moreover, postoperative disease recurrence is very common in PanCa patients.

Additionally, resistance to conventional chemotherapy drugs further limits therapeutic outcome of PanCa patients. Gemcitabine (GEM), a deoxycytidine nucleoside analog, is considered to be the most effective therapy for PanCa; however, it shows only a marginal survival benefit (6 months) in patients. This poor drug response has been attributed to desmoplasia, which is characterized by excessive fibrosis and extracellular matrix deposition. Desmoplasia causes suboptimal drug delivery, alters tumor microenvironment (TME) and induces chemo-resistance in tumors. Certain signaling pathways, such as Sonic Hedgehog,

(SHH) CXCL12/CXCR4, and microRNA-21 (miR-21) are known to be involved in alterations of TME, cancer progression and development of drug-resistance. In addition, abnormal tumor cell membrane lipid structure/composition and restricted drug uptake due to overexpression of drug efflux associated proteins also lead to ca ncer progression/metastasis and drug resistance. To overcome these existing issues associated with chemotherapy, the identification and development of novel therapeutic modalities are highly desirable. Furthermore, earlier diagnosis of cancers can lead to a drastically improved therapeutic outcome as less aggressive cancers are generally easier to treat.

Therefore, there exists a need for new compositions and methods that provide for treatment and diagnosis methods of patients with cancer. Accordingly, the present disclosure provides compositions, methods, and kits comprising an antibody, or a binding fragment thereof, which binds specifically to a MUC13 protein for the treatment and diagnosis of disease in patients.

A recently FDA approved combination treatment regimen [nab-nanoparticles (i.e., paclitaxel nanoparticles, Abraxane®) plus GEM] has slightly improved (-1.8 months) PanCa patient's survival (8.5 months vs. 6.7 months with GEM alone). Studies have shown that paclitaxel (PTX) altered TME and desmoplasia by unknown mechanisms and thus improved GEM uptake in pancreatic tumors. However, PTX mediated therapeutic outcome can likely be further improved by using a targeted PTX nanoparticle formulation.

Unique Pluronic F127 coated paclitaxel loaded nanoparticles (PPNPs) formulation have recently been developed (U.S. Patent Application No. 62/030,971) and effectively inhibit the growth of PanCa cells. In this formulation, F127 polymer was used due to its promising role in the reversal of drug resistance. Data demonstrate that antibody conjugation of such NPs formulation(s) very effectively and efficiently target solid tumors. Based on this compelling evidence, an antibody-guided, tumor specific targeted delivery of PPNPs will further enhance the bioavailability of PTX in pancreatic tumors to attenuate tumor growth and sensitize tumor cells to GEM via decreased desmoplasia, altered tumor

microenvironment (TME) and SHH/CXCL12/CXCR4, and miR-21 signaling pathways.

Recent studies suggest a major role for cross-talk between tumor and stromal cells in the pathobiology of PanCa. Further evidence delineates the role of MUC13 in PanCa tumorigenesis. For example, MUC13 is highly expressed in 74% of PanCa tumors and thus might have a significant role in development of MUC13 antibody targeted treatment modality for PanCa, as well as many other types of cancer such as colorectal, stomach, and ovarian cancer. In general, mucins are highly attractive and validated targets for cancer diagnosis and treatment. Thus, MUC13 targeted PPNPs can improve the efficacy of combination treatment resulting from the synergistic action provided by targeted PTX and GEM. The present disclosure describes the cellular/molecular effects of these PPNPs formulation on tumor- stromal cross -talk, TME and tumor growth. Role of TME and SHH in PanCa: Pancreatic tumors are comprised of various distinct cell types, including tumor cells, cancer initiating/stem cells (CICs) and stromal cells. Tumor stroma consists of fibrotic tissue with extracellular matrices, blood vessels, fibroblasts, and immuno-inflammatory cells. Therefore, the tumor stroma is emerging as an attractive therapeutic target for efficient PanCa treatment. Thus, a number of agents based on SHH inhibitors, PDGF receptor (PDGFR) inhibitors, agonist CD40 antibodies, hyaluronidase, and nab-paclitaxel have been evaluated in clinical trials. Among these targets, SHH is highly relevant to collectively target tumor cells, stroma and CICs. Therefore, our interest is to repress this pathway by utilizing our novel MUC13 antibody targeted PPNPs alone and in combination with GEM in PanCa model systems. Typically, SHH related signaling pathways are involved in embryonic development and organogenesis. However, inappropriate activation of SHH pathways in adults leads to cancer progression, metastasis and drug resistance. Thus, strategic suppression of this signaling pathway provides a unique opportunity to develop novel therapies for cancer treatment. Binding of SHH with its receptor (patched, PTCH) removes the inhibition of patched on SMO, a transmembrane protein which leads to the nuclear translocation of Gli transcription factor(s) and upregulation of oncogenic target genes. Taken together, the inappropriate operation of these pathways is critical in PanCa development and progression and their targeted repression and important for PanCa treatment.

Gemcitabine (GEM) and Abraxane® plus GEM therapy and its limitations:

GEM is one gold standard chemotherapy for PanCa treatment. However, its therapeutic efficacy is underscored due to excessive fibrosis and extracellular matrix development

(desmoplasia). Under such conditions, PanCa cells overexpress ATP-binding cassette (ABC) membrane transporters, such as P-glycoprotein (Pgp) and multidrug-resistance (MDR) related protein- 1 and -2, which actively expel GEM from cancer cells. Therefore, identification of therapeutic approaches that can aid current GEM therapy via suppression or reversal of these signaling pathways are highly awaited. Toward this, many GEM combinational regimens were investigated which showed a modest improvement in patient survival. However, these combination therapies also induced severe systemic toxicity. A newly FDA-approved treatment, Abraxane® (nab- paclitaxel nanoparticles), plus GEM treatment marginally improved overall survival of PanCa patients. Although this regimen showed a slight improvement in patient survival, it caused 5% more adverse reactions such as neutropenia, fatigue, peripheral neuropathy, and nausea. Additionally, incidences of sepsis and pneumonitis were reported in 4- 5% of patients. Thus, the efficient targeting of PTX to tumors may significantly improve the efficacy of this combination (PTX+GEM) therapy and patient survival. The MUC13 antibodies described in the present disclosure can effectively target pancreatic tumors/metastatic lesions that may help to improve therapy response rate and patient survival (see Fig. 1).

Nanotechnology for Improved and Sustained Delivery of Drugs: In the last two decades, nanomedicine has allowed researchers to develop new strategies for sustained drug delivery. Nanoscale drug delivery systems, including liposomes, polymers, and other nanoparticles (NPs), have provided prospective approaches for improved anti-cancer drug delivery. Different types of NP-drug formulations are being investigated for anti-cancer drug delivery efficacy. Nanoparticles preferentially accumulate in tumor tissue(s) due to leaky vasculature and the Enhanced Permeation and Retention (EPR) effect (see Fig. 1, top). Thus, nanotherapy approaches have superior outcomes over traditional chemotherapy in clinical oncology. As a result, several nanoparticle formulations with traditional anti-cancer drugs such as Abraxane, Doxil, Genexol-PM, CALAA-01, MCC-465, MBP-426, and BIND-014 have been generated and approved by FDA for clinical use.

Polymeric NPs employing poly lactide-co-glycolide (PLGA) have shown promising results in both in vitro and preclinical studies. Studies have also shown that PLGA- NPs have outstanding capability to effectively encapsulate anti- cancer drugs. One formulation, a paclitaxel (PTX) loaded nanoparticle formulation (PPNPs), is composed of a PLGA core that is subsequently coated with poly(vinyl alcohol) (PVA), poly(l-lysine) (PLL) and pluronic polymer (F127) for efficient drug delivery and active targeting of tumors. This formulation has several unique properties: (a) the PLGA core is capable of loading paclitaxel and its sustained release (b) pluronic polymer layer coating provides stability to the nanoformulation and also reverses multi-drug resistance protein in cancer cells (c) the polyethylene glycol chains of pluronic F127 polymer act as a stealth polymer which diminishes the nonspecific uptake of formulation, and (d) amine functional groups on NPs (PLL) are useful for antibody/aptamer conjugation through a PEG-linker (N-Hydroxysuccinimide (NHS) group) for targeting tumor/cancer cells. Therefore, PPNP formulations may be used for targeted paclitaxel delivery to PanCa. Preliminary studies suggest that PPNPs exhibit potent anti-cancer activity against PanCa cells and also enhance efficacy of GEM treatment. Therefore, this advanced delivery technology will facilitate tumor-stromal targeted delivery of therapeutics. Furthermore, delivery of PTX to PanCa tumors can be significantly enhanced by our novel anti-MUC13 MAb conjugation to PPNPs, while advantageously sparing normal cells/tissues.

MUC13, a Unique Target for PanCa: Antibodies against the tumor antigens can specifically target cancer cells while sparing normal cells/tissues. Mucins are glycoproteins whose large extracellular domain is heavily glycosylated with O-linked oligosaccharides providing protection for tissues lined by epithelial cells under normal conditions. Recent identification of a novel transmembrane mucin, MUC13, demonstrates that the protein is aberrantly expressed in PanCa but not in the normal pancreas. In cancer cells, the TR domain of mucins is usually aberrantly glycosylated (hypo-glycosylated) compared to normal epithelial cells. Therefore, antibodies against TR domain will preferentially target tumor cells due to higher/aberrant expression, localization (all over the cell surface) and glycosylation of MUC13 in cancer cells compared to normal cells (see Figs. 2-3). The anti-MUC13 monoclonal and humanized antibodies of the present disclosure specifically detect PanCa tumors in xenograft mouse model, and thus can be utilized for targeted PanCa therapy (see Figs. 25-26). Since MUC13 is highly overexpressed in PanCa, the anti-MUC13 antibody can be used for conjugating to PPNPs to achieve superior therapeutic efficacy alone and in combination with GEM.

Mouse Models for PanCa: Recently, patient derived xenograft (PDX) mouse models of PanCa have been generated for therapy and molecular analysis studies (Jackson Laboratory). This model, comprised of all components of tumors such as tumor cells, stroma, and cancer stem- like cells, is an ideal model to conduct PK/PD studies with PPNPs and GEM, and to delineate signaling pathways affected by them. Conventionally, xenograft models using human PanCa cell lines have been used in a number of studies. HPAF-II (MUC13+) and Panc-1 (MUC13-) xenograft mouse models will be used to test efficiency of MUC13 targeted PPNPs. We will combine these cells with human fibroblasts in order to mimic human pancreatic tumor (with stromal component). The xenograft mouse model is well suited to evaluate therapeutic efficacy of MUC13 targeted PPNPs plus GEM regimen because this model generates tumors of approximately the same size and at the same time (within 2 weeks). Additionally, a transgenic (PDA.MUCl.Tg) mouse model will be utilized to investigate PanCa treatments and diagnoses.

In addition, MUC13 is highly over-expressed/aberrantly localized in colorectal cancer (CRC) and is involved in its pathogenesis. Moreover, spliced variants of MUC13 and its polymorphisms have been shown to be associated with susceptibility to diseases including cancer in mouse and pig models. MUC13, a membrane bound mucin, is expressed at low levels on the apical surface of the epithelial cells in gastrointestinal, respiratory and reproductive tracts. However, dysregulated expression of MUC13 exists in ovarian, pancreatic, gastric and colon cancers. MUC13 is predicted to contain an extracellular a-subunit that comprises the tandem repeat (TR) domain, three epidermal growth factor like (EGFI-III) domains, and a Sea urchin sperm protein enterokinase arginine (SEA) domain. The intracellular β-subunit consists of the transmembrane domain (TM) and a cytoplasmic tail (CT). The TR domain, a hallmark of the mucin family, provides a scaffold to build oligosaccharide structures in which extensive O and N glycosylation occurs. The 69 amino acid cytoplasmic tail of MUC13 consists of two tyrosine and eight serine/threonine phosphorylation residues, and a PKC phosphorylation consensus motif (see Fig. 2). These phosphorylation motifs are predicted to play a critical role in tumorigenesis via signal transduction mechanisms. MUC13 over- expression is responsible for enhancing tumorigenic features in ovarian and pancreatic cancers, in both in vitro and in vivo models. Furthermore, MUC13 is known to be over-expressed and aberrantly localized in colon cancer tissues.

In addition, the exogenous expression of MUC13 enhances tumorigenic features such as cell growth, colony formation, cell migration and invasion of colon cancer cells. In contrast, these tumorigenic features are reduced by suppression of MUC13. These phenotypic changes correlate with the modulation of SHH, BMI-I, TERT, GATAl, HER2, P- ERK2 and p53 protein expression. Moreover, MUC13 expression is regulated by IL6 via JAK2/STAT5 signaling pathway.

The following numbered embodiments are contemplated and are non-limiting:

1. An antibody, or a binding fragment thereof, which binds specifically to a MUC13 protein expressed on the surface of a cancer cell.

2. The antibody of clause 1, wherein the antibody is a monoclonal antibody.

3. The antibody of clause 1, wherein the antibody is a chimeric antibody.

4. The antibody of clause 1, wherein the antibody is a humanized antibody.

5. The antibody of any one of clauses 1 to 4, wherein the antibody binds to a domain of the MUC13 protein.

6. The antibody of clause 5, wherein the domain of the MUC13 protein is the a domain.

7. The antibody of clause 5, wherein the domain of the MUC13 protein is the β domain.

8. The antibody of clause 5, wherein the domain of the MUC13 protein is the SEA domain.

9. The antibody of clause 5, wherein the domain of the MUC13 protein is the tandem repeat domain.

10. The antibody of clause 5, wherein the domain of the MUC13 protein is the EGF-like 1 domain.

11. The antibody of clause 5, wherein the domain of the MUC13 protein is the EGF-like 2 domain.

12. The antibody of clause 5, wherein the domain of the MUC13 protein is the EGF-like 3 domain. 13. The antibody of clause 5, wherein the domain of the MUC13 protein is the transmembrane domain.

14. The antibody of any one of clauses 1 to 13, wherein the antibody comprises one or more sequences selected from the group consisting of SEQ ID NO: l, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12.

15. The antibody of any one of clauses 1 to 13, wherein the antibody consists of one or more sequences selected from the group consisting of SEQ ID NO: l, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12.

16. The antibody of any one of clauses 1 to 15, wherein the antibody is labeled with a detectable moiety.

17. The antibody of clause 16, wherein the detectable moiety is selected from the group consisting of a fluorophore, a chromophore, a radionuclide, a chemiluminescent agent, a bioluminescent agent and an enzyme.

18. The antibody of any one of clauses 1 to 17, wherein the antibody is bound to a solid matrix.

19. The antibody of any one of clauses 1 to 17, wherein the antibody is bound to a paclitaxel loaded nanoparticle (PPNP) composition.

20. The antibody of clause 19, wherein the PPNP composition comprises pluronic F127.

21. The antibody of clause 19 or clause 20, wherein the PPNP composition comprises poly(l-lysine).

22. The antibody of any one of clauses 19 to 21, wherein the PPNP composition comprises a PLGA core.

23. The antibody of any one of clauses 19 to 22, wherein the PPNP composition comprises a PEG linker.

24. A pharmaceutical composition comprising the antibody, or binding fragment thereof, according to clause 1, and a pharmaceutically acceptable carrier, excipient, or diluent.

25. A pharmaceutical composition comprising the antibody, or binding fragment thereof, of clause 1, and a therapeutic agent.

26. A method of treating a cancer in a patient, the method comprising the step of administering a composition comprising the antibody of any one of clauses 1 to 23 to the patient. 27. The method of clause 26, wherein the composition is administered in conjunction with one or more additional therapeutic agents or treatments.

28. The method of clause 27, wherein the one or more additional therapeutic agents or treatments is a cancer therapeutic agent.

29. The method of clause 27, wherein the one or more additional therapeutic agents or treatments is selected from the group consisting of taxotere, carboplatin, trastuzumab, epirubicin, cyclophosphamide, cisplatin, docetaxel, doxorubicin, etoposide, 5-FU, gemcitabine, methotrexate, and paclitaxel, mitoxantrone, epothilone B, epidermal-growth factor receptor (EGFR) -targeting monoclonal antibody 7A7.27, vorinostat, romidepsin, docosahexaenoic acid, bortezomib, shikonin, daunorubicin, oxaliplatin, ormeloxifene, curcumin, and an oncolytic virus.

30. The method of clause 27, wherein the one or more additional therapeutic agents or treatments is gemcitabine.

31. The method of any one of clauses 26 to 30, wherein the cancer is pancreatic cancer.

32. The method of any one of clauses 26 to 30, wherein the cancer is colorectal cancer.

33. The method of any one of clauses 26 to 30, wherein the cancer is stomach cancer.

34. The method of any one of clauses 26 to 30, wherein the cancer is ovarian cancer.

35. A method of diagnosing a cancer in a patient, the method comprising the steps of reacting a biological sample from the patient with the antibody of any one of clauses 1 to 23, and diagnosing the cancer in the patient.

36. The method of clause 35, wherein the cancer is pancreatic cancer.

37. The method of clause 35, wherein the cancer is colorectal cancer.

38. The method of clause 35, wherein the cancer is stomach cancer.

39. The method of clause 35, wherein the cancer is ovarian cancer.

40. A method of detecting a MUC13 protein in a biological sample, the method comprising the steps of reacting the biological sample with the antibody of any one of clauses 1 to 23, and detecting the MUC13 protein in the biological sample.

41. The method of clause 40, wherein the detection is performed via radiolabeled imaging.

42. The method of clause 40 or clause 41, wherein the biological sample comprises a biological fluid. 43. The method of

44. The method of

is a spliced variant.

45. The method of

contains one or more SNPs.

46. The method of

is on the surface of a cancer cell.

47. The method of

48. The method of

49. The method of

cell.

50. The method of

resistant cancer cell.

51. A method of detecting a MUC13 protein in a biological sample, the method comprising the steps of a) providing a biological sample; b) extracting proteins from the biological sample to obtain a plurality of proteins; c) separating the proteins; d) interacting the separated proteins with the antibody of any one of clauses 1 to 23; and e) detecting the presence of the MUC13 protein in the sample.

52. The method of clause 51, wherein the biological sample comprises a biological fluid.

53. The method of clause 51 or clause 52, wherein the biological fluid is blood.

54. The method of any one of clauses 51 to 53, wherein the MUC13 protein is a spliced variant.

55. The method of any one of clauses 51 to 53, wherein the MUC 13 protein contains one or more SNPs.

56. The method of any one of clauses 51 to 55, wherein the MUC13 protein is on the surface of a cancer cell.

57. The method of any one of clauses 51 to 56, wherein the cancer cell is a tumor cell.

58. The method of clause 57, wherein the cancer cell is a stromal cell.

59. The method of clause 57, wherein the cancer cell is a metastatic cancer cell.

60. The method of clause 57, wherein the cancer cell is a gemcitabine- resistant cancer cell. 61. A diagnostic kit comprising the antibody of any one of clauses 1 to 23.

62. The antibody of any one of clauses 1 to 17, wherein the antibody is bound to a magnetic nanoparticle (MNP).

63. The antibody of clause 62, wherein the MNP comprises:

(a) a core MNP;

(b) first layer of cyclodextrin over the core MNP; and

(c) a second layer of a pluronic polymer over the cyclodextrin layer.

64. The antibody of clause 63, wherein the core MNP comprises iron, nickel, cobalt, or derivatives thereof.

65. The antibody of clause 63, wherein the core MNP comprises iron oxide.

66. The antibody of any one of clauses 63 to 65, wherein the core MNP is between about 5 nm and about 30 nm in diameter.

67. The antibody of any one of clauses 63 to 66, wherein the cyclodextrin is selected from the group consisting of a-cyclodextrin, β-cyclodextrin, and γ-cyclodextrin, and derivatives thereof.

68. The antibody of any one of clauses 63 to 66, wherein the cyclodextrin comprises β-cyclodextrin, or derivatives thereof.

69. The antibody of any one of clauses 63 to 68, wherein the MNP comprises a molar ratio of between about 1:40 to 1:300 cyclodextrin:metal ion in the core MNP.

70. The antibody of any one of clauses 63 to 69, wherein the pluronic polymer comprises an ethylene oxide/propylene oxide block copolymer.

71. The antibody of any one of clauses 63 to 70, wherein the MNP comprises a molar ratio of between about 1: 1 and 1: 10 cyclodextrin:pluronic polymer.

72. The antibody of any one of clauses 63 to 71, wherein the MNP further comprises a therapeutic loaded into or onto the MNP, a cell-targeting compound bound to the

MNP, and/or a photosensitizer loaded into or onto the MNP.

73. The antibody of clause 62, wherein a plurality of MNPs is present in an

MNP cluster.

74. The antibody of clause 73, wherein the MNP cluster is between about 50 nm and about 200 nm in diameter.

75. The antibody of clause 73, wherein the MNP cluster is between about 75 nm and about 150 nm in diameter. BRIEF DESCRIPTION OF THE DRAWINGS

FIGURE 1A shows the schematic representation of non-targeted and antibody- targeted nanoparticle accumulation and internalization in tumors and tumor cells; and FIGURE IB shows the schematic representation and composition of our newly engineered targeted PPNPs.

FIGURE 2 shows a schematic diagram and annotated amino acid sequence of MUC13. Left: a schematic diagram showing the structural features of MUC13. The signal peptide, mucin repeat domain, SEA module, EGF-like domains, transmembrane region and the cytoplasmic domain are shown from top - N-terminal, to bottom C-terminal. Right: The amino acid sequence of MUC13 indicating amino acid residues for predicted post-translational modification (O-glycosylation, N-glycosylation and disulfide bonds) (SEQ ID NO: 13).

FIGURE 3 shows images from normal pancreas tissue and PanCa tissue analyzed for MUC13 expression by IHC. Arrows indicate MUC13 staining. Original magnifications: Insets 40x, upper panel lOOx; lower panel 400x.

FIGURES 4A-G show a comparative study of expression and localization of

MUC13 in non-metastatic colon cancer and metastatic colon cancer with liver metastasis.

Figures 4A-E show MUC13 expression and localization patterns: Membranous, cytoplasmic, and nuclear MUC13 localization is shown by a black arrow, white arrowhead, and red arrow, respectively. *p<0.05. Figure 4F shows the mean composite score (MCS) of MUC13 staining as calculated based on total immunoreactivity or immunoreactivity localized to the membrane, cytoplasm, or nucleus as scored by independent pathologists. Figure 4G shows the distribution of membranous, cytoplasmic, and nuclear MUC13 expression in tissues of non- metastatic colon and metastatic colon cancer with liver metastasis.

FIGURES 5A1-A5 and 5B 1-5B5 show MUC13 expression enhances the tumorigenic features of colon cancer cells. Figures 5A1 and 5A2 show cell proliferation and cell doubling time of SW480 cells transfected with GFP tagged full length MUC13 (SW480 M130E) and Vector control (SW480 Vector) cells. Figures 5B 1 and 5B2 show cell

proliferation and cell doubling time of MUC13 knockdown SW620 cells (SW620 M13KD, transduced with MUC13 specific shRNA lentiviral particles) and vector control (SW620 Vector) cells. Selected cell populations were screened for MUC13 by immunofluorescence (Figures 5A1 and 5B 1, top) and confirmed by Western blot (Figures 5A1 and 5B 1, bottom). Colony formation (Figures 5A3 and 5B3, top and bottom), cell migration (Figures 5A4 and 5B4), and cell invasion (Figures 5A5 and 5B5) assays were also performed with MUC13 over- expressing and MUC13 knock-down cells. Bar indicates the mean, error bar indicates the SEM, N=3, * P<0.05. FIGURES 6A-B show a comparison of MUC13 expression and miR-145 expression. The upper panel of Figure 6A depicts MUC13 expression through IHC and the lower panel depicts miR-145 expression through ISH. Figure 6B shows that miR-145 inhibits MUC13 in cancer cells.

FIGURES 7A-C show the biochemical, molecular, and immunological characteristics of MUC13 MAb. Figure 7A shows RT-PCR analysis of human cancer cell lines for MUC13 mRNA expression. Primers specific for MUC13 were used for 30 cycles of PCR reaction with cDNAs of each cell. GAPDH was used as an internal control. Figure 7B shows Western Blot analysis of the same cell lines. MUC13 expression was detected by MUC13 MAb C18. β-actin was used as a loading control. Figure 7C shows immunoprecipitation of MUC13 by anti-MUC13 MAb. Membrane lysates of two MUC 13 -positive (T84 and HPAFII) and two MUC 13 -negative (MiaPaca and Panc-1) cell lines were immunoprecipitated using 1 μg of C14 MUC 13 -specific MAb per IP reaction and analyzed by Western Blotting, β-actin was used as a loading control

FIGURE 8 shows use of MUC 13 MAb for Western blotting of transfected cell lines. Total cell lysate of transfected cell lines were separated in SDS-PAGE gel under reducing conditions. The proteins were transferred to a PVDF membrane and probed with anti- MUC13 MAb. All three MAb (C14, C18 and SEA113) were specific to MUC13. β-actin was used a control.

FIGURES 9A-B shows use of MUC 13 MAbs in ELISA. Figure 9A shows

MUC 13 antibody titer in Mouse serum. Balb/c mice were repeatedly immunized with MUC 13 peptide. Antibody titer was checked using ELISA. GST13 and His 14 are peptides against MUC13. His and GST were controls. Figure 9B shows as ELISA for the detection of MUC13. Plates were coated with capture antibody: MUC 13 (CI 8), blocked, and incubated with antigen (cell line supernatant concentrated to 200X). The plate was then incubated with detection antibody: biotin-labeled MUC13 (C14), washed, and incubated with HRP- Strep tavidin. After final washes, reactions were developed using TMB substrate. Signal was read at 450nm.

FIGURES 10A-D shows the immunoreactivity of novel anti-MUC13 antibodies. Figure 10A shows the immunoreactivity of C14 anti-MUC13 MAb with exogenous full length MUC 13 expressing 293T cells and endogenous in a Western blot analysis. Figure 10B shows the immunoreactivity of C14 anti-MUC13 MAb in IHC analysis in MUC 13 positive (HPAF-II, OMC3) and negative (SKOV-3) cells. Figure IOC shows the immunoreactivity of C14 anti- MUC13 MAb with non-fixed cells in flow cytometric analyses. Figure 10D shows the immunoreactivity of C14 anti-MUC13 MAb with fixed cells in confocal microscope analyses. Original Magnifications 200X. FIGURES 11A-B shows use of MUC13 MAb in Flow Cytometry and

Immunofluorescence. Figure 11A shows FACS analysis of 8 human cancer cell lines (ovarian cancer: OMC-3 and SKOV-3; pancreatic cancer: HPAFII, MiaPaca, Capan-1, and Panc-1; Colon cancer: T84 and SW-480). Cells were stained with anti-MUC13 MAb C14. Histogram versus log fluorescence (grey line) with negative control (black line) without primary antibody. Figure 11B shows confocal photomicrograph demonstrating expression of MUC13 in the same cell lines used in Flow cytometry. Cell lines positive in FACS also showed staining for MUC13 (left panels) with immunofluorescence. Original magnification 400x.

FIGURES 12A-B shows IHC analysis of MUC13 using C18 MAb. Tumors known to express high levels of MUC13 were stained with MUC13 MAb. Figure 12A shows that mucinous type of epithelial ovarian cancer (Al) appeared positive for MUC13 expression, whereas non- neoplastic ovarian sample (A2) was negative. In a similar way, well- differentiated pancreatic adenocarcinoma (A3) and well- differentiated colon adenocarcinoma (A5) appeared MUC13 positive and the corresponding non-neoplastic tissues (A4 and A6) appeared negative. Original magnification 200x. Figure 12B shows a summary of applications of MUC13 MAb.

FIGURE 13 shows patterns of MUC13 expression in PanlNs and ductal adenocarcinoma showing less or no expression in chronic pancreatitis and adjacent normal pancreatic tissues.

FIGURE 14 shows C18 neoplastic test slide.

FIGURE 15 shows C18 pancreas tissue test slide.

FIGURE 16 shows SEA113 non-neoplastic test slide.

FIGURE 17 shows SEA113 pancreas tissue test slide.

FIGURE 18 shows chimeric MAb production

FIGURE 19 shows Biacore results of chimeric MAbs of Fig 18.

FIGURES 20A-C shows the Optimization of PPNPs (unique PLGA modified NPs) for paclitaxel delivery. Figure 20A shows the formulation composition and structure of the NPs. Figure 20B shows the PPNPs (PLGA NPs with PVA, F127 and F68, HC, GA, Dex and CH) in aqueous medium. Figure 20C shows the TEM image of PPNPs (PLGA-F 127 -PTX NPs). Figure 20D shows that the control PPNPs (No PTX drug) exhibit cyto-compatibility in cancer cells. Guam acacia stabilizer shows toxicity.

FIGURE 21 shows the comparative anti-cancer activity of PPNPs and

Abraxane® in GEM sensitive (top) and resistant (bottom) PanCa cells using an MTS assay. FIGURES 22A-B shows characterization of the PPNPs. Figure 22A diagrams the MUC13 targeted PPNPs and Figure 22B shows the MUC13 conjugated PPNPs recognition using SDS PAGE.

FIGURE 23 shows cellular uptake of PPNPs in PanCa cells and their co- localization with mitochondrial (MITO), endosomal (ENDO) and lysosomal (LYSO) markers.

FIGURES 24A-C shows the effect of PPNPs on pancreatic CSCs. Figure 24A shows the internalization of NP-Drug in CD133+/CD44+ in pancreatic CSCs. Cells were treated with NP-Drug for 24 hrs and then stained with Prussian blue (Right). Dark staining indicates presence of NP-Drug internalization. Figures 24B and C show the difference between un-treated cells (Figure 24B, bigger mammospheres) compared to NP-Drug treated cells (Figure 24C). Mag. 200X.

FIGURES 25A-C shows pancreatic tumor targeting using anti-MUC13 C14 MAb with comparative accumulation of 1131 labeled (25 μοϊ) plain anti- MUC13 MAb (C14 MAb) and curcumin loaded PLGA nanoparticle coupled anti-MUC13 MAb (PLGA-NP- MUC13 MAb) in pancreatic tumors at 168 h after intraperitoneal (ip) injection. Figures 25A-B shows in vivo imaging. Figure 25C shows ex vivo imaging of excised vital organs including tumors. Note: MUC13 MAb and PLGA-NP-MUC13 MAb treated tumors showed intense signal specifically in tumors.

FIGURES 26A-C show in vivo imaging. Figure 26A shows accumulation of 1311 labeled (25 μοΐ) anti-MUC13 MAb (C14 MAb) in tumors at 168 hours after ip injection

(left two mice), while a nonspecific antibody (CI 8) did not show any tumor accumulation (right two mice) (upper panel). The lower panel shows the ex vivo imaging of excised vital organs including tumors. Figure 26B shows the biodistribution of C14 (specific) and C18 (nonspecific) radiolabeled MAbs (n=6). Figure 26C shows the tumor growth inhibitory effect of C14 MAb (n=6). Note: C14 MUC13 MAb treated mice showed intense signal in tumors and effectively inhibited tumor growth.

FIGURES 27A-B show the superior uptake of MUC13 targeted PPNPs in HPAF-II (MUC13+) vs. Panc-1(MUC13-) PanCa cells. Figures 27C-D show MUC13 targeted NPs effectively target HPAF-II tumors in vivo imaging (27C) and in biodistribution (27D) analysis in mice. These data indicate specific targeting of MUC13 conjugated NPs.

FIGURE 28 shows the sequence listings (SEQ ID NOS:) for the various sequences of the present disclosure. DETAILED DESCRIPTION

Various embodiments of the invention are described herein as follows. In one embodiment described herein, an antibody, or a binding fragment thereof, is provided. The antibody, or a binding fragment thereof, binds specifically to a MUC13 protein expressed on the surface of a cancer cell.

In another embodiment, a pharmaceutical composition is provided. The pharmaceutical composition comprises the antibody, or binding fragment thereof, and a pharmaceutically acceptable carrier, excipient, or diluent.

In yet another embodiment, a second pharmaceutical composition is provided. The pharmaceutical composition comprises the antibody, or binding fragment thereof, and a therapeutic agent.

In another embodiment, a method of treating a cancer in a patient is provided. The method comprises the step of administering a composition comprising the antibody to the patient.

In yet another embodiment, a method of diagnosing a cancer in a patient is provided. The method comprises the steps of reacting a biological sample from the patient with the antibody, and diagnosing the cancer in the patient.

In another embodiment, a method of detecting a MUC13 protein in a biological sample is provided. The method comprises the steps of reacting the biological sample with the antibody, and detecting the MUC13 protein in the biological sample.

In yet another embodiment, a method of detecting a MUC13 protein in a biological sample is provided. The method comprises the steps of a) providing a biological sample; b) extracting proteins from the biological sample to obtain a plurality of proteins; c) separating the proteins; d) interacting the separated proteins with the antibody; and e) detecting the presence of the MUC13 protein in the sample.

In another embodiment, a diagnostic kit is provided. The diagnostic kit comprises the antibody.

In the various embodiments, the antibody, or a binding fragment thereof, binds specifically to a MUC13 protein expressed on the surface of a cancer cell. In some

embodiments, the antibody is a monoclonal antibody. In other embodiments, the antibody is a chimeric antibody. In yet other embodiments, the antibody is a humanized antibody.

In various aspects, the antibody binds to a domain of the MUC13 protein. In some embodiments, the domain of the MUC13 protein is the a domain. In other embodiments, the domain of the MUC13 protein is the β domain. In yet other embodiments, the domain of the MUC13 protein is the SEA domain. In some embodiments, the domain of the MUC13 protein is the tandem repeat domain. In other embodiments, the domain of the MUC13 protein is the EGF-like 1 domain. In yet other embodiments, the domain of the MUC13 protein is the EGF-like 2 domain. In some embodiments, the domain of the MUC13 protein is the EGF-like 3 domain. In other embodiments, the domain of the MUC13 protein is the transmembrane domain.

In certain aspects, the antibody comprises one or more sequences selected from the group consisting of SEQ ID NO: l, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12. In other aspects, the antibody consists of one or more sequences selected from the group consisting of SEQ ID NO: 1, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12. In other aspects, the antibody consists essentially of one or more sequences selected from the group consisting of SEQ ID NO: l, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12. In certain aspects, the MUC13 protein comprises a sequence selected from SEQ ID NO: 13 and SEQ ID NO: 14. In certain aspects, the MUC13 protein consists of a sequence selected from SEQ ID NO: 13 and SEQ ID NO: 14. In certain aspects, the MUC13 protein consists essentially of a sequence selected from SEQ ID NO: 13 and SEQ ID NO: 14. The above-noted sequences listings are found in Figure 28 of the present disclosure and are incorporated into this description in their entirety.

Table 1 provides a description of the various sequences. In particular, Table 1 describes anti-MUC13 MAbs identified as C4, C7, C14 and C18 (composed on a heavy chain and a light chain), and the CDR region when available.

Table 1

8 C18 mature light chain variable domain protein 24-39 55-61 94-102 sequence

9 C14 chimeric mature heavy chain protein sequence

10 C14 chimeric mature light chain protein sequence

1 1 C18 chimeric mature heavy chain protein sequence

12 C18 chimeric mature light chain protein sequence

13 MUC13 protein sequence (NP_149038)

14 Mature MUC13 extracellular domain-rabbit Fc fusion

protein used as immunogen

In various embodiments of the present disclosure, the antibody is labeled with a detectable moiety. The term "detectable moiety" is well known to the skilled artisan and has the accepted definition in the art. In some embodiments, the detectable moiety is selected from the group consisting of a fluorophore, a chromophore, a radionuclide, a chemiluminescent agent, a bioluminescent agent and an enzyme. In other embodiments, the antibody is bound to a solid matrix.

In certain aspects, the antibody is bound to a paclitaxel loaded nanoparticle

(PPNP) composition. For example, PPNP compositions are described in (U.S. Patent

Application No. 62/030,971), herein incorporated in its entirety to the present disclosure. Any of the PPNP compositions described in (U.S. Patent Application No. 62/030,971) can be utilized with the invention described herein. In some aspects, the PPNP composition comprises pluronic F127. In various aspects, the PPNP composition comprises poly(l-lysine). In other aspects, the PPNP composition comprises a PLGA core. In yet other aspects, the PPNP composition comprises a poly(ethylene) glycol (PEG) linker. Multiple PEGs of varying molecular weights are known in the art. In some embodiments, the PEG may have an average molecular weight of about, e.g., 500, 1000, 2000, 3000, 3350, 3500, 4000, 4500, 5000, 6000, 8000, 10,000, or 100,000 Daltons (Da), or an average molecular weight ranging from, e.g., about 100 Da to about 100,000 Da, about 100 Da to about 6,000 Da, about 500 Da to about 5000 Da, about 1000 Da to about 4000 Da, about 2000 Da to about 4000 Da, about 2000 Da to about 6000 Da, about 1000 Da to about 10,000 Da, or about 3000 Da to about 4000 Da.

In other aspects, antibody is bound to a magnetic nanoparticle (MNP). In some embodiments, the MNP comprises: (a) a core MNP; (b) first layer of cyclodextrin over the core MNP; and (c) a second layer of a pluronic polymer over the cyclodextrin layer. In various embodiments, the core MNP comprises iron, nickel, cobalt, or derivatives thereof. In certain embodiments, the core MNP comprises iron oxide. In various aspects, the core MNP is between about 5 nm and about 30 nm in diameter. In some aspects, the cyclodextrin is selected from the group consisting of a-cyclodextrin, β-cyclodextrin, and γ-cyclodextrin, and derivatives thereof. In other aspects, the cyclodextrin comprises β-cyclodextrin, or derivatives thereof. In various embodiments, the MNP comprises a molar ratio of between about 1:40 to 1:300 cyclodextrin:metal ion in the core MNP. In other embodiments, the pluronic polymer comprises an ethylene oxide/prop ylene oxide block copolymer. In yet other embodiments, the MNP comprises a molar ratio of between about 1: 1 and 1: 10 cyclodextrin:pluronic polymer. In other aspects, the MNP further comprises a therapeutic loaded into or onto the MNP, a cell- targeting compound bound to the MNP, and/or a photosensitizer loaded into or onto the MNP. In some embodiments, a plurality of MNPs is present in an MNP cluster. In one aspect, the MNP cluster is between about 50 nm and about 200 nm in diameter. In another aspect, the MNP cluster is between about 75 nm and about 150 nm in diameter. As skilled artisan may apply the disclosure of PCT Application No. PCT/US2011/063723 (WO/2012078745; herein incorporated by reference in its entirety) to the embodiments to described herein which include a magnetic nanoparticle (MNP).

In another embodiment of the present disclosure, a pharmaceutical composition is provided. The pharmaceutical composition comprises the antibody, or binding fragment thereof, and a pharmaceutically acceptable carrier, excipient, or diluent. As used herein, the term "carrier" refers to a vehicle within which the antibody, or binding fragment thereof may be administered to a patient. As used herein, the term "excipient" refers to inert substances including but not limited to polymers (e.g., polyethylene glycol), carbohydrates (e.g., starch, glucose, lactose, sucrose, cellulose, etc.), and alcohols (e.g., glycerol, sorbitol, xylitol, etc.). As used herein, the term "diluent" refers to liquids, optionally sterile liquids, such as sterile water, saline solutions, and buffers (e.g., phosphate, tris, borate, succinate, histidine, etc.). The previously described embodiments of the antibody, or binding fragment thereof, are also applicable to the pharmaceutical composition.

In another embodiment of the present disclosure, a second pharmaceutical composition is provided. The pharmaceutical composition comprises the antibody, or binding fragment thereof, and a therapeutic agent. The additional therapeutic agent can be one or more additional therapeutic agents or treatments, for example an anti-cancer therapeutic agent or treatments. The previously described embodiments of the antibody, or binding fragment thereof, are also applicable to the second pharmaceutical composition.

In another embodiment of the present disclosure, a method of treating a cancer in a patient is provided. The method comprises the step of administering a composition comprising the antibody to the patient. As used herein, the term "administering" refers to a parenteral administration. The term "parenteral administration" refers to a formulation suitable for the administration of the composition via injection under or through one or more layers of skin or mucus membranes of an animal, such as a human. Standard parenteral injections are given into the intravenous, intradermal, subcutaneous, or intramuscular region of an animal.

In certain aspects, the composition is administered in conjunction with one or more additional therapeutic agents or treatments. In some embodiments, the one or more additional therapeutic agents or treatments is a cancer therapeutic agent. In certain

embodiments, the one or more additional therapeutic agents or treatments is selected from the group consisting of taxotere, carboplatin, trastuzumab, epirubicin, cyclophosphamide, cisplatin, docetaxel, doxorubicin, etoposide, 5-FU, gemcitabine, methotrexate, and paclitaxel, mitoxantrone, epothilone B, epidermal-growth factor receptor (EGFR)-targeting monoclonal antibody 7A7.27, vorinostat, romidepsin, docosahexaenoic acid, bortezomib, shikonin, daunorubicin, oxaliplatin, ormeloxifene, cucumin, and an oncolytic virus. In one embodiment, the one or more additional therapeutic agents or treatments is gemcitabine.

In some aspects, the composition is administrated to treat a cancer wherein the cancer is pancreatic cancer. In other aspects, the composition is administrated to treat a cancer wherein the cancer is colorectal cancer. In various aspects, the composition is administrated to treat a cancer wherein the cancer is stomach cancer. In some aspects, the composition is administrated to treat a cancer wherein the cancer is ovarian cancer. The previously described embodiments of the antibody, or binding fragment thereof, and the pharmaceutical

compositions are also applicable to the method of treating a cancer.

In yet another embodiment of the present disclosure, a method of diagnosing a cancer in a patient is provided. The method comprises the steps of reacting a biological sample from the patient with the antibody, and diagnosing the cancer in the patient. In some aspects, the composition is administrated to diagnose a cancer wherein the cancer is pancreatic cancer. In other aspects, the composition is administrated to diagnose a cancer wherein the cancer is colorectal cancer. In various aspects, the composition is administrated to diagnose a cancer wherein the cancer is stomach cancer. In some aspects, the composition is administrated to diagnose a cancer wherein the cancer is ovarian cancer. The previously described embodiments of the antibody, or binding fragment thereof, and the pharmaceutical compositions are also applicable to the method of diagnosing a cancer.

In another embodiment of the present disclosure, a method of detecting a MUC13 protein in a biological sample is provided. The method comprises the steps of reacting the biological sample with the antibody, and detecting the MUC13 protein in the biological sample. In certain aspects, the detection is performed via radiolabeled imaging. In other aspects, the biological sample comprises a biological fluid. As used herein, the term "biological fluid" refers to any biological fluid in which determinations may be carried out such as blood, serum, plasma, lymphatic fluid, tissue extracts, enzyme preparations or the like.. In certain embodiments, the biological fluid is blood.

In some embodiments, the MUC13 protein is a spliced variant. The term

"spliced variant" is known to the skilled artisan and has the general meaning in the art. In other embodiments, the MUC13 protein contains one or more single nucleotide polymorphisms (SNPs). The term "SNPs" is known to the skilled artisan and has the general meaning in the art.

In other embodiments, the MUC13 protein is on the surface of a cancer cell. In some embodiments, the cancer cell is a tumor cell. In other embodiments, the cancer cell is a stromal cell. In yet other embodiments, the cancer cell is a metastatic cancer cell. In some embodiments, the cancer cell is a gemcitabine-resistant cancer cell. The previously described embodiments of the antibody, or binding fragment thereof, the pharmaceutical compositions, and the methods of using the antibody are also applicable to the method of detecting a MUC13 protein in a biological sample.

In yet another embodiment of the present disclosure, a method of detecting a MUC13 protein in a biological sample is provided. The method comprises the steps of a) providing a biological sample; b) extracting proteins from the biological sample to obtain a plurality of proteins; c) separating the proteins; d) interacting the separated proteins with the antibody; and e) detecting the presence of the MUC13 protein in the sample. The previously described embodiments of the antibody, or binding fragment thereof, the pharmaceutical compositions, and the methods of using the antibody are also applicable to the instant method of detecting a MUC13 protein in a biological sample.

In another embodiment, a diagnostic kit is provided. The diagnostic kit comprises the antibody. The previously described embodiments of the antibody, or binding fragment thereof, the pharmaceutical compositions, and the methods of using the antibody are also applicable to the diagnostic kit. EXAMPLE 1

MUC13, an Antibody Target for PanCa

To investigate if MUC13 could be a target for antibody guided therapy, the expression pattern of MUC13 in a normal/benign pancreas and in PanCa tissue samples was examined. The expression profile of MUC13 was determined by immunohistochemical (IHC) analysis of PanCa tissue microarrays containing 50 cancer and 8 non-neoplastic samples (Fig. 3). Compared to the normal pancreas, MUC13 was expressed at a significantly higher level in PanCa samples (p<0.005). Preliminary studies also provide evidence of the tumor specific tumor targeting capability of our radiolabeled anti-MUC13 monoclonal antibody (C-14 MAb) in PanCa xenograft mouse model, while nonspecific MAb (C-18) did not exhibit tumor targeting (Fig. 26A). The disclosed C-14 MAb also showed higher tumor uptake and tumor growth inhibition in biodistribution and therapy studies compared to C-18 MAb (Fig. 26 B, C). These data suggest that antibody conjugation will improve the bioavailability of PTX in tumors, thereby enhancing the therapeutic efficacy and chemo- sensitization of PPNPs in animal models. This technology is thus highly suitable for targeting PanCa using anti-MUC13 MAb.

EXAMPLE 2

MUC13 as a diagnostic/prognostic marker of cancer

The expression profile of MUC13 in colon cancer using a novel anti- MUC13 monoclonal antibody (MAb, clone ppz0020) has been investigated by immunohistochemical (IHC) analysis. Tissue microarrays (TMAs) containing adjacent normal, colon cancer, metastasized colon cancer, liver metastasis tissues and a cohort of clinical samples were utilized to investigate the expression pattern of MUC13, its significance as a potential

diagnostic/prognostic marker and indicator of colon cancer metastasis. IHC analysis revealed a significantly higher (p<0.001) MUC13 expression in colon cancer samples compared to faint or very low expression in adjacent normal tissues (see Fig. 4). Interestingly, metastasized colon cancer and liver metastasis tissue samples demonstrated significantly (p<0.05) higher cytoplasmic and nuclear MUC13 expression compared to non-metastatic colon cancer and adjacent normal colon samples. Moreover, a high cytoplasmic and nuclear MUC13 expression was correlated with larger and poorly differentiated tumors. Four of six tested colon cancer cell lines also demonstrated MUC13 expression at RNA and protein levels. Overall, these studies demonstrate a correlation between aberrant MUC13 expression/localization with colon cancer and colon cancer metastasis. Overall, the utility of MUC13 as a diagnostic/prognostic marker of cancer, for example CRC metastasis, has been shown. EXAMPLE 3

MUC13 enhances tumorigenic features of colon cancer cells To determine the effects of MUC13 expression on tumorigenic characteristics, MUC13 over-expressing and MUC13 knock-down cells were utilized. Significantly higher (P<0.05) cell growth was observed in MUC13 over-expressing cells (SW480 M130E) compared to SW480 Vector control cells at 96 hrs (see Fig. 5, A2, top). Likewise, MUC13 over-expression decreased the cell doubling time in SW480 M130E (29.4 hrs) compared to SW480 Vector control (38 hrs) cells (see Fig. 5, A2, bottom). Conversely, significantly lower (P<0.05) cell growth was observed in MUC13 knock-down cells (SW620 M13KD) compared to SW620 Vector control cells at 96 hrs (see Fig. 5, B2, top). Additionally, SW620 M13KD cells showed an increase in cell doubling time (20.5 hrs) compared to SW620 Vector control cells (duplication time 20.1 hrs) (see Fig. 5, B2, bottom). Moreover, MUC13 over-expressing cells (SW480 M130E) had a significantly (P<0.05) increased ability to form colonies compared to SW480 Vector control cells (see Fig. 5, A3, top and bottom). MUC13 knock-down cells (SW620 M13KD) revealed a significant (P<0.05) decrease in total number of colonies compared to SW620 Vector control cells (see Fig. 5, B3, top and bottom). To assess the role of MUC13 expression on metastatic phenotypes (migration/invasion) in colon cancer cells, migration and invasion assays were performed. A higher number of MUC13 over-expressing cells (SW480 M130E) moved through the membrane compared to SW480 Vector control cells in both migration and invasion assays (P<0.05) (see Fig. 5 A4 and A5, respectively).

Conversely, significantly fewer MUC13 knock-down (SW620 M13KD) cells moved through the membrane compared to SW620 Vector control cells in both migration and invasion assays (P<0.05) (Fig. 5, B4 and B5, respectively). These results demonstrate that MUC13 expression is associated with increased cellular growth, CRC progression, and metastasis.

EXAMPLE 4

MUC13 modulates multiple cancer associated pathways in cancer cells To investigate if MUC13 modulates the expression of genes known to be involved in cancer progression and metastasis, the expression of several pathways known to be dysregulated in cancer was compared using an RT-PCR array. Q-RT-PCR analysis, comparing MUC13 over-expressing cells (SW480 M130E) and the SW480 Vector control, showed a significant change in the expression of multiple genes. Among the up-regulated 6 genes, telomerase reverse transcriptase (TERT) was the most up- regulated gene (4.2 fold).

Interestingly, p53 was the most down-regulated gene (3.04 fold). To confirm the change in TERT expression, Western blot analysis performed in MUC13 over- expressing and knockdown cells showed increased TERT expression in MUC13 over-expressing cells compared to vector cells. Conversely, MUC13 knock-down cells (SW620 M13KD) showed decreased TERT expression compared to SW620 vector cells. Similarly, the effects of MUC13 expression on p53 expression were also investigated by Western blot analysis. This analysis confirmed that p53 expression was indeed modulated by MUC13 expression. To further explore the influence of MUC13 on cell signaling, the effect of MUC13 expression on multiple proteins was examined, including sonic hedgehog (SHH), which is predicted to be upstream of TERT, and known to be involved in cell growth and survival. Western blot analysis suggested that SHH was up-regulated in MUC13 over-expressing cells compared to vector control cells. Conversely, down regulation of SHH was observed in MUC13 knock-down cells. B cell lymphoma murine integration site-1 (BMI-1) is a member of the polycomb ring finger oncogene family. Interestingly, BMI-1 is downstream of SHH signaling. Interestingly, MUC13 over-expression positively correlated with BMI-1 expression. GATA binding proteins (GATA) are transcription factors that regulate multiple steps of the cell cycle and are predicted to be downstream targets of BMI-1. Our immunoblot analysis revealed higher GATA1 expression in MUC13 over-expressing cells compared to vector control cells however it was reduced upon MUC13 knock-down. B cell lymphoma (Bcl-xl) is an anti-apoptotic protein known to be a downstream target of GATA1. MUC13 expression also influenced the expression of Bcl-xl in our MUC13 over-expressing and knock-down colon cancer cell lines. Epidermal growth factor receptors (EGFR) are involved in colon cancer carcinogenesis. The up-regulation of HER2 has been reported in breast, pancreatic and colon carcinogenesis. Since MUC13 contain 3 EGF-like domains; we sought to determine if MUC13 increases tumorigenesis via modulation of HER2 expression. Western blot analysis revealed that the total level of HER2 was influenced by

MUC13 over-expression and MUC13 knockdown in colon cancer cells. MUC13 expression also modulated the expression of HER2 downstream signaling cascade such as P-ERK. All together these data suggest that MUC13 expression increases tumorigenesis via influencing the expression of multiple oncogenic proteins.

EXAMPLE 5

STAT5 binds to MUC13 promoter and regulates its expression:

In silico analysis was performed to identify potential transcription factors that may regulate MUC13 expression. More than 11 potential transcription factors were identified and subsequently, multiple cell lines were screened by Q-RT-PCR analysis to identify cell lines with high endogenous MUC13 expression. Of these, the colon cancer cell line T84 and pancreatic cancer cell line HPAFII showed the highest expression levels of MUC13 mRNA transcripts. Thus, T84 and HPAFII cell lines were selected for further MUC13 regulation analysis. Q-RT-PCR analysis also revealed that STAT5 is the most highly expressed transcription factor in both T84 and HPAFII cell lines. The predicted promoter of MUC13 contains the STAT5 binding site (GTAGTTCTGAGAATCC (SEQ ID NO: 15)). To determine if STAT5 binds to the MUC13 promoter, ChIP assays were performed. Compared to negative control non-immune IgG antibody, ChIP analysis in T84 and HPAFII cells revealed

approximately 2-2.4 fold enrichment of MUC13 with the STAT5 antibody compared to negative control IgG antibody. Enrichment of the MUC13 gene was further confirmed by Q- PCR in T84 and HPAFII cells. This data suggests that STAT5 directly binds to the predicted promoter of MUC13 and may regulate its expression in these cancer cells.

EXAMPLE 6

IL6 enhances MUC13 expression via JAK2/STAT5 pathway To determine the effects of IL6 and STAT5 activation on MUC13 regulation, colon cancer cells (HT29) (which express a moderate level of endogenous MUC13 expression and express JAK2) were treated with variable doses of IL6 (25-300 ng/ml). Our Q-RT-PCR analysis revealed MUC13 expression increased in a dose dependent manner in response to IL6 treatment. This observation was further confirmed by Western blot and confocal microscopy analyses. IL6 treatment also increased the expression of P- J AK2 and P-STAT5. In addition, increased nuclear localization of P-STAT5 was observed when cells were treated with IL6 compared to DMSO control. To further confirm the involvement of JAK2/STAT5, JAK2 and

STAT5 were suppressed using JAK2 (AG490) and STAT5 inhibitors. Western blot analyses indicated that JAK2 and STAT5 inhibitors substantially decreased MUC13 expression, in the presence of IL6, in a dose dependent manner. Our IHC analysis also showed that both MUC13 and P-STAT5 were up-regulated in non-metastatic colon cancer compared to adjacent normal tissue. Additionally, metastatic colon cancer and liver metastasis showed significantly higher MUC13 (cytoplasmic and nuclear) and P-STAT5 expression compared to adjacent normal colon tissue.

Data show that 1) over-expression of MUC13 can be an indicator of tumorigenesis and metastasis in CRC; 2) increased cytoplasmic MUC13 expression in colon cancer tissues with liver metastases as compared to colon cancer that had not metastasized; 3) MUC13 increases cell motility and invasion in cancer cells via modulating adhesion to proteins such as fibronectin, basement membrane complex (BMC), collagen IV, laminin and changing the expression of metastasis associated proteins (S 100A4). Thus the over-expression and aberrant localization of mucins, such as MUC13, may block cell-cell and cell-extracellular matrix adhesion and thereby facilitate cellular migration and invasion of cancer cells, suggesting that MUC13 may play a pivotal role in colon cancer metastasis. Although much of the mucin glycoprotein is extra-cellular, mucins still have the ability to modulate cell signaling events. Studies have shown that MUC13 influences the expression of multiple proteins, including SHH, TERT, BMI-1, GATA1, and Bcl-xl, all of which are involved in colon cancer progression and metastasis. MUC13 also increases HER2 and P-ERK expression in ovarian and pancreatic cancers, indicating that MUC13 affects the HER2/MAPK signaling pathway in these cancer cells. Together these findings suggest that MUC13 may influence CRC

tumorigenesis and metastasis via multiple oncogenic proteins.

Moreover, IL6 regulates MUC13 via the JAK2/STAT5 signaling pathway. IL6 activates STAT5 in colon epithelial cells and high levels of IL6 are reported in CRC and gastric cancers. Increased expression of IL6 is associated with enhanced tumorigenesis and IL6 signaling is also correlated with development of colitis induced premalignant lesions in colon epithelial cells in a murine model. A prognostic indicator itself, P-STAT5 (phospho-STAT5) is over-expressed in CRC and is associated with poor prognosis. MicroRNAs (miRNAs) have been reported to be involved in the regulation of various genes including the mucins. However, there are no reports on regulation of MUC13 through miRNAs in CRC. MiRNAs can regulate CRC growth via regulation of the MUC13 gene. These miRNAs may include both tumor suppressor and oncogenic miRNAs. Our studies show down-regulation of MUC13 through binding of miR-145 and miR-132 to its 3'UTR region. Additionally, our preliminary data suggest a marked differential expression/localization pattern of MUC13 in CA versus AA CRC tissues. Aberrant localization of MUC13 in cytoplasm/nucleus in addition to membrane expression is associated with and metastasis. As mentioned above, studies have also shown the presence of MUC13 spliced variants. Thus, we hypothesize that the differential/aberrant expression of MUC13 and/or MUC13 variants are underlying factors associated with CRC health disparity. In addition, we hypothesize this differential MUC13 expression is regulated by certain microRNAs (miR-145 and miR-132) and inflammatory mediators produced by the tumor microenvironment (e.g. interleukin-6 mediated STAT5B phosphorylation) resulting in malignant CRC phenotypes among AA population.

Colonoscopy is currently the most robust screening tool for colorectal cancer

(CRC) and the removal of neoplastic adenomatous polyps reduces the incidence of colon cancer. However, in both hereditary and sporadic cases of CRC, neoplastic polyps can re-occur and additional research is needed to understand the biological mechanisms which drive the development and progression of neoplastic polyps into CRC. The 5 year survival rate is only 10% in patients diagnosed with advanced stage CRC, highlighting the importance of early detection and better understanding of the disease process. While increased use of

colonoscopies has decreased CRC, the required follow-up places an enormous strain on medical resources and additional strategies are needed for more cost-effective screening, follow-up and treatment of adenomas and CRC. While inflammation is thought to play a role in pre-cancer and cancer development/progression, the molecular players associated with the inflammatory response are not well understood and additional research, especially regarding the development of polyps, is needed. MUC13 is a newly identified transmembrane mucin that is aberrantly expressed in ovarian and gastro-intestinal cancers. The clinical significance, function, and regulation of MUC13 expression in neoplastic polyps and CRC are not fully known. In recent years we have developed unique reagents related to MUC13 research including highly specific novel anti- MUC13 monoclonal antibodies (clone C14 and C18). These antibodies are well characterized for MUC13 specificity, immunoreactivity and affinity in different assays (IF, IB, IP, Flow cytometry, IHC and Biacore analyses) (see Figs. 9-19). Recently, we have also shown that MUC13 mucin is aberrantly expressed in colon cancer. Additionally, preliminary (IHC) studies with novel anti-MUC13 MAb (Clone C14) also demonstrate a differential expression profile of MUC13 in AA, AI versus CA CRC tissue samples. MUC13 expression was markedly higher in AA and AI samples more especially in nucleus (~5 fold) compared to CA samples. Understanding the regulation and functional roles of aberrant MUC13 expression may identify novel strategies for CRC detection and intervention. The overall goal of this specific aim is to investigate the differential expression profile/patterns of MUC13 in a larger cohort of

CA, AI and AA CRC samples and to correlate with disease stage, progression metastasis and patient survival. In this aim we hypothesize that MUC13 will be differentially over-expressed and/or aberrantly localized in AA neoplastic polyps, CRC, and metastatic lesions tissue samples compared to CA samples and healthy, non-malignant tissues. These studies will provide data regarding the role of MUC13 in CRC development and will identify targets for reversing the growth of adenomatous polyps and CRC progression. Proposed studies will also provide data regarding MUC13 as a molecular marker for screening, diagnosis, metastasis and prognosis of CRC.

EXAMPLE 7

Differential expression analysis of MUC13 in AA, AI and CA CRC samples

Collection of CRC Tissue Samples: For the instant example, 150 age and stage matched (age 40-90 yrs; stage TNM I-IV) CRC samples will be used (see Table 2). Self- reported and/or ancestry marker typed samples will be utilized in this study. Computer databases of participating pathology labs will be acquired for CRC reports. These computer generated reports will then be reviewed to identify cases from AA, AI, and CA patients using name, location, and ethnicity, as available. The original hematoxylin and eosin-stained microscope slides and accompanying paraffin blocks with residual tissue will then be retrieved and examined to ensure the presence of malignancy and an adequate amount of remaining tissue and to ensure selection of appropriate paraffin blocks for the study. Tissue sections from each case will be obtained, mounted on glass slides, and serially numbered. The numbered slides will then be obtained for analysis. A modified pathology report containing only the patient's age, gross description of the submitted specimen, and the pathologic diagnosis will be included. The accompanying reports will be devoid of any other demographic or identifying information. Identification logs correlating the numbered tissue samples with the patients will be maintained for possible future reference or follow up studies. For each group (AI, AA, CA), 150 age matched samples (30-90 year olds) will be collected and examined.

Table 2. Demographic and samples stratification information for CRC

IHC Procedure: Clinically proven CRC samples of AA, AI and CA men and women will be processed for MUC13 IHC analysis. MUC13 expression will be evaluated in non-malignant, malignant polyps and different stages of CRC samples. The pattern of MUC13 expression will be examined in relation to the disease stage and tumor size, depth of invasion, differentiation and patient prognosis. Up-regulation of MUC13 will also predict which pre- malignant lesions will become malignant and which will remain dormant. The intensity and extent of staining will be graded.

Pathological Analysis of CRC Tissue Samples: Stained samples will be analyzed for the presence of benign and cancerous glands, and will be graded as necessary. Slides will be digitally analyzed for MUC13 staining. The intensity (graded 0-4, none-very intense) and extent of staining (no staining, <25%, 25-50%, 51-75% or >75%) will be graded. Finally, the intensity (0-4) and extent of staining (0-4) scores will be multiplied to obtain the composite score (MCS) with the maximum value being 16. The mean of three readings will be used for calculations.

EXAMPLE 8

To determine the relationship between MUC1 expression with pSTAT5 and IL-6, and Ki-67 expression in AA, AI and CA CRC samples

The expression of MUC13 is regulated by IL-6 and STAT5. The expression of MUC13 and its aberrant localization has also been implicated in CRC metastasis and subsequent prognosis. Therefore, the expression pattern of these antigens with MUC13 expression will be investigated by using a double and triple antigen staining procedure.

Double or triple antigen labeling Double antigen staining will be performed. The tissue slides will be deparaffinized and rehydrated using graded alcohols. Subsequent to washing and antigen retrieval, slides will be incubated with a primary antibody cocktail containing a 1: 1000 dilution of MUC13 antibody (MAb) and a 1:250 dilution of STAT5 or IL-6 or Ki-67 antibody (PAb) at room temperature for 1 hour. After washing, the slides will be incubated with the secondary antibody cocktail containing anti-mouse-HRP and anti- rabbit- ALP (both included with the Biocare Double Stain kit) at room temperature for 45 min. The HRP reaction color will be developed with the 3, 3-diaminobenzidine (DAB) substrate

(Betazoid DAB kit, Biocare Medical, Concord, CA) as per the manufacturer's instructions. Following a wash in water, the slides will be incubated with Vulcan Fast Red (Biocare Medical) to develop the reaction color from the ALP. Slides will then be rinsed with water, counter stained with hematoxylin, dehydrated and mounted with Vectamount permanent mounting media.

Scoring criteria: The intensity of immunoreactivity will be scored. The intensity (0-4) and extent of staining (0-4) scores will be multiplied to obtain the composite score (MCS) with the maximum value being 16. The expression of MUC13 and STAT5/IL-6/Ki-67 will be correlated with disease progression and patient survival using Kaplan Meier analysis.

Statistical methods and power analysis: Group differences (AA, AI, CA) will be examined, by categorizing MCS into high (MCS>8) or low expression (MCS<8). Survival methods (Kaplan-Meier), regression methods, and other appropriate techniques will be used and will include an interaction between groups and MUC13 expression.

In addition to standard methods, the regulatory pathway notions will be used to define a structural equation model, which will be evaluated separately for the different racial groups. The analysis is complex, and thus the power analysis concentrates on the most important component, the test of differences for the 3 groups. Assuming that MUC13 values are similar to previously observed values (% High CA: 60%, AA: 80%, AI: 80%).

EXAMPLE 9 To investigate the presence of MUC13 spliced variants/single nucleotide polymorphisms (SNPs) and their association with chemoresistance, metastasis and CRC health disparity.

Mucins are highly glycosylated proteins produced by secretory epithelial cells for the lubrication and protection of ducts and lumen. They contain a high percentage of serine, threonine, proline, alanine, and glycine residues, and are heavily glycosylated (O-linked). The mucins differ greatly in their structure, however, they share a common feature; sequences repeated in tandem. But there are no similarities in the repeat units of the different mucins. The number of repetitions may vary from one individual to another. Consequently, mucins show a high level of variable number of tandem repeat (VNTR) polymorphisms. Alternative splicing is a phenomena where one gene locus can express multiple isoforms. The diversity in the transcript levels leads to plastic transcriptional networks in cancer which are eventually responsible for the unusual properties of cancer cells. Alternative spliced variants of MUC13 have been found in pig and chicken genomes. In pig, the variants have been shown to be associated with susceptibility towards enterotoxigenic Escherichia coli F4ac (ETEC F4) diarrhea. Persistent Helicobacter pylori infection has been found to be a major risk factor for CRC in humans. It is possible that this changed in risk factor is due to the differential expression of MUC13 or its variants (VNTR)/spliced variants. Single nucleotide

polymorphisms (SNPs) are variations in DNA sequence of the genome at a single nucleotide level between the two pairs of chromosomes in humans or the biological species. SNPs have been associated with increased risk of cancer incidence or fatality. However, no study has been done to identify MUC13 SNPs/ variants and their role in CRC risk and survival in different ethnic groups. There are 28 MUC13 SNPs cluster IDs known which have been submitted to the NCBI database. Out of these 28 known MUC13 SNPs cluster IDs, five have been chosen for association studies. These are (dbSNP rs# cluster ID) rsl 127233, rsl47099165, rsl40633855, rsl6836185 and rsl44481864. The basis on which these cluster IDs are chosen is that they have been sequenced in the 1000 Genome project and are validated by frequency or genotype data: minor alleles observed in at least two chromosomes. Additionally, preliminary RNA seq analysis has indicated the presence of alternative spliced variants of MUC13 in tumor tissues (pooled samples; n=5) as compared to pooled cell lines (HPAF-II and Capan-1). Based on the above rationale, different MUC13 spliced variants may be present in CRC and the presence of these spliced variants and the known SNPs is associated with chemoresistance, metastasis and CRC health disparity.

EXAMPLE 10

To investigate the presence of MUC13 variants (VNTRVspliced variants Library preparation, sequencing and analysis: Total RNA will be extracted from CA, AI and AA patient sample tissues according to the manufacturer's protocol (Life

Technologies, CA). For mRNA-sequence sample preparation, the Illumina standard kit will be used (Illumina, CA). The cDNA preparation will be done using Applied Biosystems kits and the libraries will be created through the AB Library Builder System. The libraries will be sequenced using the ABI 5500XL next generation sequencers (Applied Biosystems, CA).

Libraries from CA, AI and AA CRC tissue samples will be analyzed using the software Partek Genomics Suite (PGS) 6.6 (Partek Incorporated, MO). Briefly, PGS will first align the sequence reads with the UCSC H. Sapiens reference genome (build hgl9) through the Partek FlowTM. The aligned reads will be visualized through the RefSeq Transcripts (PGS 6.6).

Differentially expressed genes will be analyzed by performing mRNA quantification. The raw and normalized reads are also reported for each sample. The normalization method used by PGS software is Reads Per Kilobase of exon model per Million mapped reads (RPKM). Reads will be assigned to individual transcripts of a gene based on the Expectation/Maximization algorithm.

Differential expression of genes will be done using the Partek ANOVA method (PGS 6.6). The list of differentially expressed and alternatively spliced transcripts will be used for Gene Ontology Enrichment Analysis using the PGS 6.6. Functional enrichment analysis of differentially expressed genes: The Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 is a set of web-based functional annotation tools. The unique lists of differentially expressed genes and all the expressed genes (RPKM .0 in any sample) will be submitted to the web interface as the gene list and background, respectively. The cut-off of the False Discovery Rate (FDR) will be set at 5%.

EXAMPLE 11

To investigate the presence of MUC13 single nucleotide polymorphisms (SNPs)

Genotyping: Patient samples (case and normal) CA, AI and AA sample sets will be used. DNA will be extracted from CRC tissue samples using QIAmp (Qiagen, CA) kit and genotyping will be performed. Genotyping of MUC13 (dbSNP rs# cluster ID; rs 1127233, rsl47099165, rsl40633855, rsl6836185, rsl44481864) will be performed using 5' nuclease assays (Taqman®). Primers, probes, and conditions for genotyping assays will be designed.

Replicates of 10% of the samples will be included for quality control. Control status and the location of quality controls will be cased. Validation of SNPs will be done in an independent data set, based on preliminary data. SNPs showing significant frequency in diseased samples will be analyzed for association with cancer incidence, chemoresistance, metastasis and survival in both ethnic groups using histological studies. All medical records and computerized laboratory reports for our samples will be reviewed. MUC13 values will be abstracted for samples whose levels had been measured prior to surgery and/or neoadjuvant chemotherapy.

EXAMPLE 12

To investigate the presence of MUC13 single nucleotide polymorphisms (SNPs)

In vitro tumorigenic studies: The identified spliced variants and SNPs will be characterized using in vitro and in vivo models. Briefly, the identified variants and SNPs will be and the functional roles of these constructs will be assessed by stably transfecting them in CRC cells (SW480 and SW620; paired cell line model, T84, LoVo and HT29). Assays such as cell proliferation, colony formation, cell cycle and apoptosis analysis and invasion and migration assays will be used.

Cell morphology: The effects of different MUC13 spliced variants and SNPs on alterations in cellular morphology and growth pattern in cell culture will be investigated. After 48 hours, phase-contrast pictures will be taken and cell morphology and growth patterns will be compared between vector control and variants/SNP transfected groups.

Cell motility: Cell migration assays in the MUC13 spliced variants and SNPs over-expressing will be performed and compared to vector control treated cells. Briefly, cells (1.0 x 10⁵) will be trypsinized and mixed into a 0.2% low melting point agarose solution.

Cell/agarose suspension (30 μΐ) will be plated onto fibronectin/BSA coated six-well plates, covered with growth medium and cultured at 34 °C with 5% C0₂. Cells will be photographed under a phase contrast microscope at 24, 48, 72 and 96 hours.

Cell proliferation: Cell proliferation assays will be performed. Briefly, variants/SNPs over-expressing and vector control cells will be grown complete growth medium for 24, 48, 72 and 96 hours. Cell proliferation will be assayed by cell counting (Coulter counter) and/or by MTS assay using CellTiter96AQueous One Solution Proliferation Assay (Promega Corp).

In vivo tumorigenic studies: These studies will be done by creating stable cell lines by transfecting the generated MUC13 spliced variants and SNP constructs in CRC cell lines and subsequently injecting them in athymic nude mice and assessing their tumorigenic potential. Briefly, 1 x 10⁶ cells (SW480 or SW620; a paired cell line model) will be suspended in diluted Matrigel 1:3 (BD Biosciences, MA) and injected (volumes of 50 μί) for generating the CRC xenograft mouse model using nude mice (nu/nu, 4-6 weeks old, Charles River, MA). Mice will develop tumors within 7-10 days. 10 mice per group will be used to achieve a statistically significant result. Following tumor development, at bi-weekly intervals, the animals will be weighed and the tumor growth and volume (with a formula: volume=4/3x π x (x/2) x (y/2)2) will be measured bi-dimensionally with the help of a digital Vernier caliper. At the time of sacrifice (day 40-50), the tumor load will be determined. Tumors will be dissected and fixed for immunohistochemical (IHC) analysis. The expression of MUC 13 target genes and cell proliferation markers (PCNA, ki67) will be determined. Differences between groups will be analyzed by the log-rank test for survival and an ANOVA model for tumor volume at 28 days after injections. Mice will be sacrificed during the experiment if tumor volume/weight reaches more than 10% of body weight (-1.5-2.0 gram) or if mice lose more than 10% of their total body weight. Mice which do not meet aforementioned conditions will be sacrificed on day 50.

EXAMPLE 13

Association of MUC13 spliced variants/SNPs with chemoresistance and metastasis

The expression of spliced variants and SNPs will be compared to clinical and histopathologic parameters. The association of the expression of MUC13 splice variants with the response to chemotherapy and patient survival analyses will be determined. Expression of MUC13 splice variants will be correlated with the presence of malignancy. Significant differences in genotype frequencies will be investigated between controls and cases, and their association with CRC. Additionally, the effects of the expression of MUC 13 splice

variants/SNPs on the responsiveness (chemoresistance) of 5'FU (5-30 μΜ) and oxaplatin (5-40 μΜ) (two main drugs used for CRC treatment), cellular motility and invasion using cell line models (SW480 and SW620; paired cell line model) will be determined.

Statistical Analysis: Chi- square tests to assess Hardy-Weinberg Equilibrium (HWE) for each SNP among controls will be used. Geometric mean MUC 13 values by genotype will be calculated for each MUC13 polymorphism. Analyses will use general linear regression, adjusted for age, race, and time between MUC 13 expression and diagnosis (<30 days, >30 days, missing), using continuous log transformed MUC13 levels and a variable that represents increasing variant alleles for each polymorphism (0, 1, 2). Analyses will be performed using SAS v 9.3 (SAS, Cary, North Carolina).

EXAMPLE 14

Epigenetic mechanisms of MUC13 regulation in CRC

The characterization of the 5 '-flanking region of MUC13 shows that it is GC rich and the analysis of the genomic DNA sequence (gene bank accession numbers: NC_000003.11, NC_018914.1) indicates the presence of numerous CpG islands. The epigenetic changes of MUC13 may be of importance for diagnosis of carcinogenic risk and prediction of outcome for CRC patients. Methylation of cytosine in genomic DNA and histone modification both play an important role in gene regulation and especially in gene silencing.

DNA methylation studies on MUC 13 promoter CpG island: To elucidate the epigenetic mechanisms regulating MUC13 in CA, AI and AA populations, the methylation status of the 5' upstream region of the MUC13 gene through bisulphite modification of DNA using the Epi-Tect Bisulphite kit (Qiagen) will be analyzed. DNA from CRC cell lines

(SW480, SW620, T84, LoVo and HT29), 20 samples each of normal colon and CRC tissues of CA/AA/AI, will be extracted using DNeasy Tissue System (Qiagen). Primers for bisulphite genomic sequencing PCR will be designed using the online program MethPrimer. All reactions for tissue samples will be subjected to two rounds of amplifications using a nested primer approach. Bisulphite-modified DNA (1 ml) will be amplified using a primer pair in a total volume of 20 ml. Aliquots (2 ml) of the first PCR reactions will be subjected to second round amplifications using a pair of nested primers in a total volume of 30 ml. The amplification products will be confirmed by electrophoresis on a 2% agarose gel and sequenced directly by an outside vendor.

Histone modification analysis MUC13 promoter: Epigenetic regulation of the MUC13 gene, will be examined by investigating histone H3-K9 modifications in CRC cell lines using a Chromatin Immunoprecipitation (ChIP) assay (Epigentek, Inc. NY).

Immunoprecipitated DNA will be amplified by PCR using a Fast Cycling PCR kit (Qiagen). The ChIP primers will be designed and the amplified products will be subjected to 1.5% agarose gel electrophoresis. This ChIP analysis will reveal whether the MUC13 promoter undergoes histone H3-K9 demethylation in non-neoplastic colon and CRC tissues of CA populations or histone H3-K9 acetylation in CRC tissues. MUC 13 (-) and MUC13 (+) CRC cells (SW480/SW620) will also be incubated with 100 μιηοΙ/L of DNA methylation inhibitor, 5-aza-2'-deoxycytidine (5-AzadC) and 500 nmol/L of histone deacetylase inhibitor, trichostatin A, or both 5-AzadC/TSA for 5 days. mRNA will be extracted, and quantitative RT-PCR will be performed for the detection of relative changes in MUC 13 expression. These analyses will elucidate the differential patterns of DNA methylation and histone modifications occurring in CA, AI and AA populations, which might be responsible for causing CRC health disparity.

EXAMPLE 15

Determine the regulatory effect of microRNAs on MUC 13 in various stages of CRC miR- 145 and miR- 132 are involved in the regulation of MUC13 expression (Fig. 6). Thus, the correlation of MUC 13 with miR- 145/132 in CRC will be investigated. The expression of miR-145/132 will be evaluated in normal colon, benign, adenomatous polyps and different stages of CRC tissue samples (CA, AI and AA, see Table 2) using in situ hybridization (ISH). Briefly, in situ hybridization using Digoxingenin (DIG) labeled probes will be done using the ISH kit (BioChain Ins. Inc. CA). The tissue samples will be deparaffinized, prehybridized and hybridized with DIG labeled probes overnight. After stringent washes, DIG probes will be immunocytochemically detected using an alkaline phosphatase conjugated anti- DIG antibody. Additionally, the real time PCR (Roche, IN) results will be confirmed using Taqman probes. For that, total RNA from tissue samples will be isolated using Trizol and

CDNA will be prepared using RT kit (Life Tech). The observations will be correlated with the disease stage and patients prognosis. Data obtained from ISH analysis will be correlated with the pattern of MUC13 expression (IHC). These results will implicate the correlation of MUC13 with miR-145/132 in different stages of CRC in CA, AI and AA populations. Further, it will predict their association with CRC occurrence, metastatic potential and patient' s prognosis.

EXAMPLE 16

Regulation of MUC 13 by transcription factors and cytokines in CRC Mechanisms causing MUC13 over-expression in CRC remains unknown.

Experiments will be done to investigate MUC 13' s distinctive regulatory mechanism through its binding with transcription factors and inflammatory mediators like IL6/JAK2/STAT5 pathways in AA, AI and CA populations that leads to CRC disparity. To evaluate the binding of CREB, Spzl and HNF-4al/2 to the MUC13 promoter, ChIP assays in CRC cells (SW480, SW620, T84, and HT29) using ChIP kit will be done. Additionally, to further confirm the binding of transcription factors to MUC 13 promoter, lucif erase reporter assays will be done using gene specific luciferase reporters (STAT5, CREB, Spzl and HNF-4al/2) and a Dual-Glo Luciferase kit. CRC cells will be transfected with luciferase reporters for 24 hrs and then investigated for MUC 13 transcriptional activation. This analysis will reveal the binding transcriptional regulation of MUC 13 in CRC.

EXAMPLE 17

Engineering PPNPs: Formulation and its anti-cancer effects in PanCa cells

1. Synthesis and characterization of PPNPs: To optimize an efficient targeted nanoparticle formulation for PTX, a nanoprecipitation technique using various polymer

(stabilizer) compositions was employed. All tested formulations (Fig. 20A) contain 90 mg of PLGA, 10 mg of PLL and various polymers as stabilizers [1% solutions of poly(vinyl alcohol) (PVA), Pluronic polymers (F127 and F68) or hydroxyl cellulose (HC), gum acacia (GA), dextran (Dex), and chitosan (CH)]. PVA, F127, and F68, and GA polymer stabilization provide smaller particles compared to other polymer stabilizers such as Dex, HC and CH. Unique nontoxic, biocompatible PLGA nanoparticle formulations composed of PVA, F127 and F68 (Fig. 20B-C) were identified. Furthermore, PPNPs composed of F127 and F68 exhibited lower binding efficiency with human serum albumin (HSA), indicating these PPNPs have superior bioavailability. Further, transmission electron microscopy (TEM) data suggest that the disclosed F127 containing PTX loaded PPNPs (PLGA-F127-PTX) provide the optimal size (<100 nm) (Fig. 20C) and low +ve zeta potential (2 mV). Empty NPs of this formulation did not exhibit any toxicity in cancer cells (Fig. 20D).

2. Anti-cancer and molecular effects of PPNPs: PVA is the most commonly used stabilizer for nanoformulations. F127 polymer is considered a good stealth stabilizer and has also shown a potent role in reversal of drug resistance. Therefore, PVA and F127 stabilized PPNPs (PLGA- PVA-PTX or PLGA-F 127-PTX) were examined for anti-cancer efficacy in PanCa cell lines. The cytotoxicity profiles of the PPNPs (PLGA-PVA-PTX or PLGA-F 127 -PTX) (cyan or magenta) were more pronounced compared to free PTX in solution (blue color lines) at tested doses (1-100 nM). Overall, PTX loading efficiency in this formulation was 92-95%, which showed slow and sustained release over a period of three weeks. Empty PPNPs (no PTX drug) did not affect cell growth at any concentrations (black, red, and green lines).

PLGA-F127-PTX exhibited superior dose-dependent anti-cancer effect in BxPC- 3, HPAF-II and Panc-1 PanCa cells compared to PLGA-PVA-PTX or free PTX treatment (4-5 times lower IC50 compared to PLGA-PVA-PTX or free PTX). This difference can be explained by higher cellular uptake of PLGA- F127-PTX compared to PLGA-PVA-PTX formulation. Therefore, PLGA-F 127- PTX nanoparticle formulation as PPNPs were selected for future experiments. The disclosed PPNP formulation significantly down- regulates multidrug resistance (MDR) protein (MDR-ABC-1) and cleaves PARP (indicator of apoptosis). PPNPs also cause down-regulation of Collagen-I (restricts drug penetration in tumors), GLI1 (protein involved in SHH pathway) proteins and miR-21. These data suggest that F127 stabilized PPNPs exhibit superior anti-cancer potential capable of regulating MDR proteins, GLI, miR-21 and inducing apoptosis which can lead to improved sensitivity to GEM.

Chemo-sensitization efficacy of PPNPs was evaluated in BXPC-3 Panc-1 cell lines (resistant to GEM) by colony formation assays. Colony formation assays provide the ability to evaluate long-term anti-cancer efficacy of the developed drug(s) or drug formulations. To prove the disclosed PPNPs plus GEM formulation has greater effects in long-term anti-cancer efficacy assays, free-GEM, PPNPs and PPNPs+GEM were studied. No significant inhibition of clonogenic potential of PanCa cells was observed in cells treated with 2 nM PPNPs or 5-10 nM GEM alone; however, a significant inhibition was surprisingly observed upon a combination (2 nM PPNPs+5-10 nM GEM) treatment. This data suggests that PPNPs in combination with GEM can effectively eliminate GEM resistant cells.

EXAMPLE 18

To determine cellular fate of PPNPs in PanCa cells

The disclosed PPNPs effectively internalize into PanCa cells and induce anti- cancer activity and chemo-sensitization. However, exact molecular mechanisms of

internalization and intracellular fate of this formulation are not known. Thus, endosomal transport of the disclosed PPNPs via multiple heterotypic or homotypic endocytic fusion events that are regulated by a diverse set of endosomal proteins and different cell signaling cascades is examined.

Cellular uptake and PPNPs association and dissociation from lysosome and endosomes using flow cytometry and confocal microscopy will be examined. Green fluorescence will be used to track the PPNPs (dye loaded NPs) in the cellular environment. Lysosome and endosomes will be tracked by LysoTracker® Deep Red and LysoTracker® Blue DND-22 (Life Technologies) and used for PPNPs co-localization (Fig. 23). Cellular uptake and retention of PPNPs in GEM- resistant (Pane- 1 and BxPC-3) and GEM-sensitive (HPAF-II,

MiaPaca-1) PanCa cell lines will be examined over a period of 30 min, 1 hr, 3 hr, 6 hr, 24 hr, 48 hr and 72 hr. 1-500 nM PTX or 1-500 nM PPNPs (for resistant cell lines) and 1-5 nM PTX or 1-5 nM PPNPs (for sensitive cell lines) will be used for these studies because higher concentrations may kill the cells over longer time periods. This uptake study will also be conducted in the presence of calcimycin, niclosamide, bafilomycin, rottlenrin, ionomycin and genistein which are inhibitors of endocytosis pathways.

EXAMPLE 19

Cell Proliferation Assays

In preliminary studies, PPNPs exhibit superior anti-cancer potential in PanCa cells and induce sensitization to GEM treatment. Therefore, to further evaluate the therapeutic efficacy of PPNPs in a panel of clinically relevant PanCa cell lines (MiaPaca, Panc-1, HPAFII, Capan-1, BxPC3, or SW1990) is proposed. Cell proliferation assays using various doses (1-50 nM) of free PTX and equivalent doses of the PPNPs will be performed. Colony Forming Assays: Slow and sustained PTX release from MNP

formulations may have long term inhibitory effects on cells that will be reflected by colony forming ability of cells. For colony forming assays, 1000 PanCa cells will be seeded in a 75 mm Petri dish and assayed. Differences in cell proliferation and colony formation between the control and treatment groups will be assessed with analysis of variance (ANOVA) models and independent t-test.

Cell Cycle and Apoptosis Assays: Propidium iodide (PI), Annexin V staining and TdT-mediated dUTP Nick-End Labeling (TUNEL) will be performed for analyzing cell cycle and apoptosis. PanCa cells will be treated with various concentrations of free PTX and PPNPs for 48-72 hours. TUNEL assays will be performed to detect fragmented DNA of apoptotic cells using the Apo-direct kit (BD Biosciences, CA). Cells will be analyzed for cell cycle and apoptosis using Flow Cytometry.

EXAMPLE 20

Effects of PPNPs on Lipid Prolife, Ionic Channels/Ion Transporters, and Modulation of chemo- sensitization

Biologically active lipids and their composition have critical functions in maintaining membrane integrity, regulation, signaling and energy for metabolism of cancer cells. It has been shown that lipids such as phosphatidylcholine (PC),

phosphatidylethanolamine (PE) and fatty acids aberrantly express in cancer

progression/metastasis due to cellular transitions. Nanoparticle mediated delivery of PTX may alter the cellular membrane lipid composition, which might lead to the reversal of the drug resistance. Therefore, it is highly imperative to study the effects of PPNPs on membrane lipid profile and drug resistance in PanCa cells.

1. Lipid Profile: 1-50 nM PTX or PPNPs alone or in combination with 1, 2.5, 5,

10, 15, 20, 30, and 50 nM GEM in GEM-sensitive and GEM-resistant PanCa cell lines will be used. Cells will be treated for 1, 2, 3 and 5 days and the lipid will be extracted from cells.

Briefly, lipids will be extracted into a chloroform:methanol: lM hydrochloric acid (10:20: 1 v/v in PBS) solution from cell pellet and the organic layer that contains lipids will be selectively collected. Lyophilized lipid extracts will be re-dispersed in 5 mL milli-Q water for lipid structure and lipid profile evaluation using atomic force microscopy (AFM, Veeco Metrology,

Inc.) and Liquid chromatography-mass spectrometry (LCMS) systems. AFM structural evaluation will be performed by dropping 10 μΐ_^ of lipid extract solution on cleaved mica substrate (Ted Pella, Inc.) and allowed to dry overnight under vacuum desiccators. The dried films will be analyzed for structural variation between cellular lipid extracts using a multimode AFM in tapping mode employing a scan size of 20-100 μιη and height of 100-300 nm with the help of 125^m-long silicon probe with a resonance frequency of approximately 300 Hz and a tip radius of <10 nm (Ted Pella, Inc.). LCMS measurements will be performed to evaluate overall lipid profiles from cells using a 4000 Q-Trap liquid chromatogram and a linear ion trap mass spectrometer.

2. Ionic Channels and Ion Transporters: Drug resistance is also caused by decreased drug uptake, increased drug efflux, down-regulation of the K⁺ and/or CI^" channels as well as of Ca²⁺ channels. It has been shown that PTX plays a key role in the modulation of ionic channels and ion transporters and thus induces chemo- sensitization. Therefore, the effect of PPNPs (2 or 5 nM) mediated: a) time-dependent changes in cellular water content (mL/g, cell dry weight), b) Cl₂ content (μΜ/g, cell dry weight) by Ag⁺ titration, c) K⁺ and Na⁺ content by emission flame photometry, in GEM-sensitive and GEM-resistant PanCa cell lines with and without GEM (1-50 nM) will be evaluated. This will provide a rationale of chemo- sensitized drug-induced apoptosis through modulation of ion transporters, which is the main cause of multi-drug resistance (MDR).

3. Modulation of GEM resistance: The intracellular retention and accumulation of GEM after treating cells with 1-5 nM PTX or PPNPs alone or in combination with 1-5 nM GEM over a period of time (1-10 days) will be examined. After treatment, cells will be lysed in acetonitrile, sonicated for 1 min and cisplatin or paclitaxel internalization will be estimated by HPLC. Similarly, these cells will be collected in 2X SDS-PAGE sample buffer to determine the expression of P-gp activity and the MDR associated proteins (ABCCl/MRPl/ABCB l/P-gp proteins) by immunoblot assay. The important genes/proteins expressions that are associated with EMT will be examined: E-cadherin, Vimentin, zinc finger E-box-binding homeobox 1, 2 (ZEB 1, 2), p63, mitogen-activated protein kinase (MAPK), targets mediator 1 (MED1, also called TRAP220 and PPARBP), CD24, CD44, CD49b, and CD133.

EXAMPLE 21

To evaluate the effect of PPNPs on SHH signaling and chemo-sensitizing microRNAs

Cross-talk between tumor cells and stromal cells is important in cancer pathobiology. The chemokine CXCL12 (stromal cell-derived factor- l(SDF-l)) is abundantly produced by the stromal cells and promotes progression, metastasis and chemo-resistance of PanCa. CXCL12 interacts with CXCR4 to induce the expression of SHH in PanCa cells. SHH then acts predominantly on the stromal cells to induce desmoplasia which negatively impacts patient's therapeutic outcome. To assess the effect of PPNPs on SHH transcriptional activity, a reporter plasmid with cDNA that encodes lucif erase downstream of eight copies of GLI1- binding sites will be used. Cells will be transfected with this luciferase reporter along with control Renilla- luciferase expression vector. To determine inhibitory effects of PPNPs formulation on CXCR4 activation and SHH expression, PanCa cells (MiaPaca, Panc-1, HPAFII, Capan-1, BxPC3, SW1990) will be cultured in serum- free media for 18 hr and then treated with CXCL12 (100 ng/niL) along with free PTX (1-50 nM) or PPNPs for 24 hrs.

Luciferase activity will be measured 24-48 hr post-transfection using the Dual-luciferase assay kit. Following treatment, components of the SHH signaling pathway such as SHH, GLI1, GLI2, PATCHED 1, PATCHED2, and SUFU will be examined by Western blotting and quantitative real time (qPCR) analyses. The up-regulated expression of miR-21 is inversely correlated with PanCa patient's survival. Recent studies have shown the role of miR-21 and miR-200a in PanCa chemo-resistance. Therefore, the effects of PPNPs formulation on the modulation of miR-21 and miR-200a expression using GEM-resistant cell lines (Panel, BxPC- 3 and MiaPaca-E, M) will be determined.

EXAMPLE 22

Molecular effects of PPNPs on pancreatic stellate (PSC) and cancer stem-like cells (CSCs)

Human pancreatic stellate cells (PSCs) will be isolated from 250-300 mg of freshly collected pancreatic tumor samples. Tumor samples will be collected from the surgery unit and will be digested with 0.03% collagenase P in Hank's buffered salt solution. The suspension of cells will be centrifuged in a 13.2% iohexol gradient and PSCs will be separated from the fuzzy band just above the interface of the iohexol solution and the aqueous buffer and cultured in 10% FCS containing IMDM growth media. Cell population purity will be assessed by vitamin A auto-fluorescence and cell populations greater than 90% pure will be used for all proposed experiments. PSCs will be incubated with blank PPNPs or PPNPs and cell proliferation will be assessed at 24-96 hrs by MTT assays. The expression of relevant proteins such as PTCH, SMO, GLI, MMPs, Collagen (I, II, III), stellate cell activation-associated protein (STAP), VEGF and FGF in PSCs after 48 hrs of PPNPs treatment will be examined by Western blotting and quantitative real time (qPCR) analyses. In addition to the aforementioned PSC cells, the molecular effects of PPNPs on cancer stem-like cells (CSCs) will be determined. Briefly, CSCs (already procured from Celprogen, San Pedro, CA) will be characterized by high expression of stem cell markers including CD133, CD44, SOX2, and Oct4. These cells will be treated with free PTX or PPNPs for 24 hrs and then processed for MTS assays (for cell proliferation) and Western blotting, and Q-RT-PCR (for the expression analysis of core pluripotency factors, SOX2, Oct4, and NANOG). CSCs are also known to display

higher/increased microtentacles (McTN), thus the effect of PTX and PPNPs on the McTN levels, known to promote metastatic efficiency of CSCs, will be investigated using confocal microscopy analysis. Also, reporter constructs will be created by cloning wild-type or mutated enhancer regions of NANOG/SOX2/Oct4 genes into the pGL3-control vector, and luciferase assays will be used to determine the effect of PPNPs on promoter activity by measurement of firefly and Renilla luciferase activity using the Dual Luciferase Reporter assay (Promega). The effects of the disclosed NP-Drug formulation on cellular internalization and growth of CSCs have been observed (Fig. 24).

EXAMPLE 23

Investigations on PK/PD and Systemic/ Acute Toxicity of PPNPs

The objective of this example is to examine in vivo delivery and clinical translational potential of PPNPs in PDX PanCa mouse model by determining biodistribution, PK/PD, tumor uptake/retention and toxicity profiles. This experiment is highly desirable because NP delivery systems may use EPR effects and reach to target tumor site(s). This experiment will be evaluated using qualitative PPNPs (PTX) biodistribution and

pharmacokinetic analysis. In addition to the disclosed PPNPs, Abraxane® will also be used for comparison. For these studies, the PDX PanCa mouse model will be employed (nu/nu, 6-8 weeks old, The Jackson Laboratory). These mouse models are routinely used for therapy and molecular studies. Tumor bearing PDX PanCa mice will be randomly assigned into 8 treatment groups and will be administered with control or various therapeutic formulations by i.v.

injection as shown in Table 3.

Table 3. Experimental design to determine bioavailability, pharmaco-kinetics and molecular mechanism of PPNPs Treatment Group Dose (mg/kg) Mice per Group End Point

Saline 100 μΙ 6 To compare PK-PD, systemic/acute toxicity,

PTX 1 0 6 and therapeutics and molecular mechanism

Abraxane® 1 0 6 of PPNPs

PPNPs 1 0 6

GEM 1 0 6

PTX + GEM 10 + 10 6

PPNPs + GEM 10 + 10 6

Abraxane® + GEM 10 + 10 6

For early time PK profiles, blood samples (20 μί) will be collected in tubes at predetermined time intervals (5, 10, 15, 30 min, 1, 2, 4 and 8 hrs). The amount of PTX will be measured by utilizing liquid-liquid extraction followed by reversed-phase HPLC and tandem MS (LC/MS/MS) detection. For later time PK profiles, the animals will be sacrificed at 24, 48, 98 and 168 hrs after injection. 6 mice per group will be sacrificed at each time point and the blood, liver, kidney, spleen, heart, lung, brain, and tumor, will be collected, weighed, processed and the PTX or GEM and PTX/GEM content will be determined by HPLC. Single-dose PK parameters include maximum concentration (C_max), time of the maximum concentration (T_max), apparent terminal elimination rate constant (λζ), and terminal elimination half- life (ti_/2).

Individual estimates of λζ for PTX and PPNPs will be obtained by log-linear regression of the terminal portions of the plasma concentration-time curves; ti_/2 will then be calculated as 1η(2)/λζ. WinNonlin v5.2.1 NCA model 201, IV bolus software will be used to calculate the PK/PD parameters. The total number of mice required for this study is 192 (6 mice per group x 8 groups x 4 time points).

In the same in vivo experiment, the systemic/acute toxicity profile of treatment groups will be examined by evaluating the following parameters: (1) Body weight changes will be recorded bi-weekly and reported in the form of change of body weight as a function of time), (2) Blood cell counts (white blood cells, red blood cells and platelet counts) will be measured using a Countess® Automated Cell Counter, (3) Liver enzyme levels (aspartate transaminase, alanine aminotransferase, and alkaline phosphatase) will be quantified using spectrophotometric methods, and (4) Inflammatory markers from serum (Interleukin-6, 8, 18, tumor necrosis factor- alpha, C-reactive protein, and Interferon gamma) will be measured by ELISA method. For these studies (except body weight changes), mice will be anesthetized, euthanized and blood/plasma and organs/tumors will be collected for further histological analysis. A total of 40 mice per experiment are required for analyzing the in vivo therapeutic efficacy. Tumor volume differences will be analyzed using an ANOVA model at 15 weeks.

EXAMPLE 24

To investigate effects of PPNPs on SHH signaling in PDX mouse models

In vivo therapeutic effects of PPNP formulation and its effect on SHH signaling will be determined in the PDX PanCa mouse model. Alterations in SHH signaling and TME associated proteins upon treatment with different therapeutics (PTX, PPNPs, Abraxane®, PTX plus GEM, and PPNPs plus GEM, and Abraxane® plus GEM) as shown in Table 3 will be examined. As described above, Tumor bearing PDX mice will be randomly assigned into 8 treatment groups (Table 2). 10 mice per group will be used in this study to achieve statistically significant results. Mice will be administered with ip/iv route (three injections for three subsequent weeks) and will be monitored at bi-weekly intervals to record body weight, sudden change in physical appearance and excessive tumor growth. Mice will be sacrificed

immediately if an apparent excessive tumor growth is noticed or if mice lose more than 10% of the total body weight. All mice will be sacrificed at 15 weeks of age. At dissection, the size of the pancreatic tumor will be evaluated by wet weight and volume (volume =4/3x π x (x/2) x (y/2)2) will be measured bi-dimensionally using a digital Vernier caliper. Metastasis will be determined by the presence of visible metastatic lesions in peritoneal organs such as liver, lungs, diaphragm, lymph nodes, and caecum. Tumor tissues will be dissected and fixed for histological, immunohistochemical (IHC) and immunoblot analyses. Pancreatic tumors will be excised and fixed in 4% formalin- saline solution and then processed for paraffin embedding, sectioning (5 μιη) H&E staining. Sections will be evaluated to classify malignant lesions. Histological analysis will be performed for the evaluation of pancreatic intraepithelial neoplasia (PanIN) lesions and adenocarcinoma. IHC analysis will also be performed to determine the expression of SHH signaling (SHH, GLI1-2, PATCHEDl-2, and SUFU), PCNA and ki67.

EXAMPLE 25

To determine effects of PPNPs on TME

Stromal cells and ECM components provide the pivotal microenvironment for tumor development. Acquisition of an activated phenotype of fibroblasts is associated with expression of markers such as smooth muscle genes (aSMA and SM22a), enzymes involved in collagen biosynthesis (P4Hb), and oxidative-stress genes, such as stellate cell activation- associated protein (Cygb/STAP). The disclosed data suggest potent inhibitory effects of the PPNPs formulation on desmoplastic activity (collagen-I synthesis and GLI1 protein) in PanCa cells. Suppression of SHH signaling pathways and suppression of stromal cells/PSC activation by the PPNPs formulation may alter the TME, resulting in inhibition of desmoplasia, tumorigenesis and metastasis. Therefore, the expression of TME associated markers in response to PPNPs treatment will be investigated. Histo-architecture and IHC Analysis for TME: IHC analysis will also be performed to determine the expression of TME associated proteins such as MUC1, E- cadherin, cytokeratin-18, β-catenin, Collagen-I, Fibronectin, Vimentin, Snail- 1 (markers of EMT), matrix metalloproteinases (MMP2, MMP3 and MMP9, cell invasion markers) and hypoxia inducible factor-a (HIF-a). Tumor sections will be stained for CD34, vascular endothelial growth factor (VEGF) and vascular endothelial growth factor receptor (VEGFR) proteins using specific antibodies to determine blood vessel density in the PanCa tumors. Additionally, multiple antigen staining to determine stroma- tumor cell interaction using markers of stromal cells and tumor cells will be performed. The intensity (graded 0-4, none-very intense) and extent of staining (no staining, <25%, 25-50%, 51-75% or >75%) will be graded. Immunoblot analysis: Pancreatic tumor tissues removed from each treated and control group will be pooled and homogenized in RIPA buffer. Protein samples will be loaded onto gradient gels (4-20%), transferred to PVDF membranes and probed for the above mentioned TME associated proteins. The expression of PTCH, SMO, GLI, MMPs, Collagen (I-III), STAP, VEGF and FGF will also be examined by qPCR.

EXAMPLE 26

Generation of MUC13 targeted PPNPs formulation

1. Reactivity of anti-MUC13 MAbs with MUC13 Expressing Cancer Cells: A panel of anti-MUC13 MAbs against different regions of MUC13 (C13; Near SEA domain, C14 and CI 8; Tandem repeat domain) have been generated by using purified recombinant MUC13 and hybridoma technology. After several rounds of screening, three (C13, C14 and C18) monoclonal antibodies (MAbs) were identified. Of these three, C14 MAbs showed the highest immunoreactivity with MUC13 in different assays such as immunoblotting, IHC, ELISA, immunoprecipitation, flow cytometry and immunofluorescence. The C14 MAb showed reactivity with fixed, as well as live cancer cells, suggesting this antibody recognizes MUC13 in its native confirmation. Humanized anti-MUC13 antibody, which can be useful for clinical use in the future was also generated. These antibodies can be used for targeting PanCa cells.

Therefore, conjugating these MAbs to PPNPs and determining the therapeutic efficacy of this targeted formulation in PanCa is proposed. 2. Generation of PPNP-immunoconjugates Antibody Conjugation Procedure: Amine groups of PLL on the PPNPs provides an exposed surface moiety available for linking with NHS-PEG-NHS (conjugation linker) that can be conjugated to amines present on the antibody. This chemistry will be utilized for anti-MUC13 MAb (C14) conjugation (Fig. 27). Briefly, 10 mg/ml of PPNPs will be activated by incubation with 1 mg NHS-PEG-NHS. The activated PPNPs (2 ml at 5 mg/ml) will be added to 500 μg purified anti-MUC13 MAb in 1 ml of PBS buffer, pH 7.4 at 4 °C. To block the remaining reactive sites, 0.1 ml of 25 mM glycine in PBS will be added and incubated for 30 min. Physico-chemical characterization of anti- MUC13 MAb coupled PPNPs will be performed. The coupling of MAbs with PPNPs will be determined by immunoblotting, confocal microscopy and immunogold TEM.

3. Determination of Immunoreactivity and Internalization of PPNPs immunoconj u ates : Immunoreactivity of the PPNPs immunoconjugates will be determined by a cell binding assay using MUC13 positive (HPAFII or CaPan-1) and negative (MiaPaca or Panc- 1) cells as shown in Fig. 27. For this assay, cells will be fixed with methanol, blocked with serum and incubated with MAb coupled NPs followed by FITC conjugated anti-mouse secondary antibody. Binding of nano-immunoconjugates with cells will be observed by flow cytometry and confocal microscopy. Internalization of NPs will be examined by confocal microscopy and TEM.

EXAMPLE 27

Generation of MUC13 targeted PPNPs formulation

Therapeutic Efficacy of MUC13 Targeted PPNPs: In vivo therapeutic efficacy of MUC13 MAb (C14) and humanized MUC13 antibody (HuAb) targeted PPNPs will be determined as described. For in vitro experiments, MUC13 positive (HPAFII or CaPan-1) and negative (MiaPaca or Panc-1) cells will be used. In addition to the PanCa xenograft mouse model, PDA.MUC1 transgenic mice will also be used. For that, breeding pairs of PDA and

MUCl.Tg mice will be procured and allowed to cross breed, and genomic DNA will be used to genotype the triple transgenic mice using PCR. Although it is known that these mice develop pancreatic tumors within 16-26 weeks, tumor volume and tumor blood flow will be measured with a high frequency ultrasound machine (Visual Sonics, Vevo 2100). Tumor bearing mice will be randomly assigned into treatment groups (Table 4).

Table 4: Experimental design to determine therapy applications of anti-MUC13 MAb conjugated PPNPs in combination with GEM. Treatment Group Dose (mg/kg) Mice /Group

PBS 100 μΙ 10

Gemcitabine (GEM) 1 0 10

PPNPs 1 0 10

PPNPS + GEM 10+ 10 10

C14 (MUC13 MAb)-PPNPs 1 0 10

C14-PPNPS+GEM 10 + 10 10

MOPC21 (Control lg)- PPNPs 10 10

MOPC21 -PPNPS + GEM 10 + 10 10

Ten (10) mice per group will be needed to achieve statistically significant results. Mice will be divided into treatment groups as shown in Table 4. MOPC-21 MAb will be used as control Ig. For this, PPNPs or GEM (10 mg/kg; in 100 μΐ volume/mice/dose, 3 doses for 3 subsequent weeks) will be administered to the mice (Table 4). Tumor growth, animal survival, IHC, and immunoblot analysis will be performed.

EXAMPLE 28

Antibody Conjugation to the NPs

PLGA NPs were conjugated to antibody (CC49; anti-TAG-72 MAb and J591; anti-PSMA MAb) through reaction with surface ligand NHS-PEG-NHS. UV-Vis

spectrophotometer measurement based calculations demonstrate (92%) antibody conjugation efficiency which was further confirmed by TEM analysis (average of 2-3 antibody molecules per NP). This method also allows anti-MUC13 (Fig. 22A) conjugation to PPNPs at

physiological pH, ensuring the antibody retains its immunoreactivity. SDS-PAGE analysis of antibody targeted PPNPs generated through this process indicates successful conjugation of the antibody (Fig. 22B). Antibody targeted NPs are capable of intracellular delivery of drugs even in PanCa.

EXAMPLE 29

To investigate effects of MUC13 targeted PPNPs on tumor microenvironment (TME)

The expression of TME associated markers and on the expression of miR-21 and miR-200a in tumor tissues collected from these mice will be investigated. EXAMPLE 30

Effects of dietary chemopreventive agents on MUC13 and factors regulating MUC13 expression.

The effect of apigenin, curcumin, genistein on MUC13 and miR-145/132 will be tested. CRC cells (SW480 and SW620; paired cell line model, T84, LoVo and HT29) will be treated with apigenin (10-20 μΜ), genistein (20-40 μΜ) and curcumin (10- 20 μΜ) individually and in combination for 96 h. Subsequently, total miRNA will be extracted and the level of MUC13 and miR-145/132 will be analyzed by q-RT-PCR. Additionally, the effects of these chemopreventive compounds on the responsiveness (chemoresistance) of 5'FU (5-30 μΜ) and oxaplatin (5-40 μΜ), cellular motility and invasion will be examined. This study will determine the role of chemopreventive compounds in restoration of miR-145/132 and thus inhibition of MUC13 expression.

Claims

WHAT IS CLAIMED IS:

1. An antibody, or a binding fragment thereof, which binds specifically to a MUC13 protein expressed on the surface of a cancer cell.

2. The antibody of claim 1, wherein the antibody is a monoclonal antibody.

3. The antibody of claim 1, wherein the antibody is a chimeric antibody.

4. The antibody of claim 1, wherein the antibody is a humanized antibody.

5. The antibody of any one of claims 1 to 4, wherein the antibody binds to a domain of the MUC13 protein.

6. The antibody of claim 5, wherein the domain of the MUC 13 protein is the a domain.

7. The antibody of claim 5, wherein the domain of the MUC 13 protein is the β domain.

8. The antibody of claim 5, wherein the domain of the MUC 13 protein is the SEA domain.

9. The antibody of claim 5, wherein the domain of the MUC 13 protein is the tandem repeat domain.

10. The antibody of claim 5, wherein the domain of the MUC13 protein is the EGF-like 1 domain.

11. The antibody of claim 5, wherein the domain of the MUC 13 protein is the EGF-like 2 domain.

12. The antibody of claim 5, wherein the domain of the MUC13 protein is the EGF-like 3 domain.

13. The antibody of claim 5, wherein the domain of the MUC 13 protein is the transmembrane domain.

14. The antibody of claim 1, wherein the antibody comprises one or more sequences selected from the group consisting of SEQ ID NO: l, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12.

15. The antibody of claim 1, wherein the antibody consists of one or more sequences selected from the group consisting of SEQ ID NO:l, SEQ ID NO:2, SEQ ID NO:3, SEQ ID NO:4, SEQ ID NO:5, SEQ ID NO:6, SEQ ID NO:7, SEQ ID NO:8, SEQ ID NO:9, SEQ ID NO: 10, SEQ ID NO: 11, and SEQ ID NO: 12.

16. The antibody of claim 1, wherein the antibody is labeled with a detectable moiety.

17. The antibody of claim 16, wherein the detectable moiety is selected from the group consisting of a fluorophore, a chromophore, a radionuclide, a chemiluminescent agent, a bioluminescent agent and an enzyme.

18. The antibody of claim 1, wherein the antibody is bound to a solid matrix.

19. The antibody of claim 1, wherein the antibody is bound to a paclitaxel loaded nanoparticle (PPNP) composition.

20. The antibody of claim 19, wherein the PPNP composition comprises pluronic F127.

21. The antibody of claim 19, wherein the PPNP composition comprises poly(l-lysine).

22. The antibody of claim 19, wherein the PPNP composition comprises a

PLGA core.

23. The antibody of claim 19, wherein the PPNP composition comprises a

PEG linker.

24. A pharmaceutical composition comprising the antibody, or binding fragment thereof, according to claim 1, and a pharmaceutically acceptable carrier, excipient, or diluent.

25. A pharmaceutical composition comprising the antibody, or binding fragment thereof, of claim 1, and a therapeutic agent.

26. The antibody of claim 1, wherein the antibody is bound to a magnetic nanoparticle (MNP).

27. The antibody of claim 26, wherein the MNP comprises:

(a) a core MNP;

(b) first layer of cyclodextrin over the core MNP; and (c) a second layer of a pluronic polymer over the cyclodextrin layer.