Biomarkers with therapeutic implications for peritoneal cancer spread

Abstract

The present invention relates to a method for detecting or determining the susceptibility of a subject with peritoneal carcinomatosis to treatment with an inhibitor of plasminogen activator inhibitor 1 (PAI-1), wherein the method comprises determining the concentration of PAI-1 in ascites and determining the level of phosphorylated tumor signal transducer and activator of transcription 3 (STAT3). The level of phosphorylated STAT3 can also be determined by measuring the concentration of one or more surrogate markers (such as IL-6, IL-10, CCL2, MMP9 and ANGPT1) in ascites.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to Singapore Provisional Application No. 10201902763U filed on March 27, 2019, the contents of which are hereby incorporated by reference in their entirety for all purposes. Field of the Invention

[0003] The present invention relates generally to the field of molecular biology. In particular, the present invention relates to the use of biomarkers for the detection, diagnosis and subsequent treatment of cancer. Background of the Invention

[0005] Colorectal cancer is the third most common cancer and the fourth most common cause of cancer death worldwide, accounting for 1.4 million new cases and 600,000 deaths each year. Deaths from colorectal cancer are mostly due to metastasis with peritoneal carcinomatosis (PC) occurring in 15% of all patients, accounting for up to 30% of all metastases. Despite palliative systemic chemotherapy, PC consistently demonstrates significantly shorter overall survival compared to other forms of metastatic colorectal cancer without peritoneal involvement.

[0006] Cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) have revolutionized the treatment of peritoneal carcinomatous spread. Cytoreductive surgery refers to a series of visceral and peritoneal resection procedures that remove all macroscopic disease. Remaining microscopic viable disease is then eradicated using instillations of HIPEC chemotherapeutic agents. The combination of cytoreductive surgery and HIPEC has significantly improved survival in patients with peritoneal carcinomatous spread of colorectal origin. The median survival of patients who received cytoreductive surgery and HIPEC was 33 months, compared to a median survival of 6 to 12 months for patients who received systemic chemotherapy alone. However, despite this significant improvement, more work is needed to further improve outcomes for patients with colorectal peritoneal carcinomatous spread by improving HIPEC regimens, as surgery is unlikely to improve patient outcomes further.

[0007] Therefore, improved patient stratification is needed to improve treatment.

[0008] Overview

[0009] In one aspect, the present disclosure relates to a method for treating a subject having spread of peritoneal cancer with an inhibitor of "plasminogen activator inhibitor 1" (PAI-1), the method comprising determining the concentration of PAI-1 and determining the phosphorylation level of "signal transducer and activator of transcription 3" (STAT3) in a sample obtained from the subject; administering the PAI-1 inhibitor to a subject showing (a) an increase in PAI-1 concentration and an increase in STAT3 phosphorylation, or (b) a decrease in PAI-1 concentration and an increase in STAT3 phosphorylation; wherein the increase and / or decrease in PAI-1 concentration and STAT3 phosphorylation is compared to a reference value.

[0010] In another aspect, the present disclosure relates to a method for detecting or determining the susceptibility of a subject having peritoneal carcinomatosis to treatment with an inhibitor of "plasminogen activator inhibitor 1" (PAI-1), the method comprising determining the concentration of PAI-1 and determining the phosphorylation level of "signal transducer and activator of transcription 3" (STAT3) in a sample obtained from the subject; wherein if the subject exhibits (a) an increase in PAI-1 concentration and an increase in STAT3 phosphorylation, or (b) a decrease in PAI-1 concentration and an increase in STAT3 phosphorylation, the subject is susceptible to the treatment; wherein if the subject exhibits (c) a decrease in PAI-1 concentration and a decrease in STAT3 phosphorylation, the subject is considered not susceptible to the treatment; wherein the increase and / or decrease in PAI-1 concentration and STAT3 phosphorylation level is compared with a reference value.

[0011] In one aspect, the present disclosure relates to a panel of markers for treating patients with peritoneal cancer spread with inhibitors of "plasminogen activator inhibitor 1" (PAI-1), or for detecting or determining the susceptibility of patients with peritoneal cancer spread to treatment with inhibitors of "plasminogen activator inhibitor 1" (PAI-1), wherein the panel of markers includes PAI-1 and one or more surrogate markers of STAT3 phosphorylation or p-STAT3.

[0012] In another aspect, the disclosure relates to the use of a panel of markers in the methods disclosed herein, wherein the panel includes PAI-1 and one or more surrogate markers of STAT3 phosphorylation, or PAI-1 and p-STAT3.

[0013] BRIEF DESCRIPTION OF THE DRAWINGS

[0014] The invention will be better understood with reference to the detailed description when considered in conjunction with the non-limiting examples and accompanying drawings, in which:

[0015] Figure 1The data shown indicate that the presence of ascites leads to a worse prognosis for patients, regardless of the histological subtype. (A) Kaplan-Meier survival curves for all patients with peritoneal cancer spread (P = 0.002). (B) Kaplan-Meier survival curves for patients with colorectal cancer with peritoneal cancer spread (P = 0.001). (C) Kaplan-Meier survival curves for patients with ovarian cancer with peritoneal cancer spread (P = 0.077).

[0016] Figure 2 (A) The addition of acellular ascites increased cancer cell proliferation in a dose-dependent manner. 0.1% acellular ascites was sufficient to maintain cell viability without proliferation. (B) Treatment with acellular ascites significantly increased cancer cell migration. (C) Treatment with acellular ascites significantly increased cell sedimentation of cancer cells in vitro, regardless of the serum-supplemented medium (As: ascites, SFM: serum-free medium, FBS: fetal bovine serum).

[0017] Figure 3 Pathways that were significantly upregulated following treatment with cell-free ascites are shown. (A) Pathways upregulated in peritoneal carcinoma (PC) cell lines treated with 5% and 0.1% cell-free ascites. (B) Specific pathways upregulated in cells treated with cell-free ascites are not common to pathways activated by survival signals. These figures show that several signaling pathways were found to be upregulated when cancer cell lines were treated with cell-free ascites, including the IL6-JAK-STAT3 signaling pathway. This indicates that activation of STAT3 plays an important role in this disease. The term "treatment" referred to in this figure and context is different from the definition of "treatment" provided in the Definitions section below. In Figure 3 In the context of , treatment refers to exposing a cell line model to acellular ascites collected from a patient in vitro. For example, a cancer cell line is exposed to 5% acellular ascites in vitro and changes in the physical phenotype (e.g., proliferation or migration) or molecular phenotype (e.g., changes in gene expression) of the cells are observed.

[0018] Figure 4 (A) Treatment with 5% acellular ascites activates STAT3 via phosphorylation at Tyr 705. (B) Treatment with 5% acellular ascites of different histological peritoneal carcinomatous (PC) subtypes results in STAT3 activation, with acellular ascites of colorectal origin showing the highest activation.

[0019] Figure 5(A) Representative immunohistochemical staining of p-STAT3 in colorectal primary tumors and their matched metastases. (B) STAT3 activation is more prevalent in metastases than in primary tumors (P: primary tumor, M: metastasis). In the context of the present invention, overall, this data emphasizes that the STAT3 signaling pathway is more upregulated in metastases than in primary tumors, and it is inferred that metastases are more dependent on STAT3 signaling. This in turn suggests that metastases are more susceptible to STAT3 inhibition than primary tumors. In other words, targeting STAT3 signaling in metastases may be more effective than targeting primary tumors.

[0020] Figure 6 (A) Bar graph showing the most differentially expressed epithelial-mesenchymal transition (EMT) genes in established cell line models of colorectal peritoneal carcinomatosis treated with acellular ascites. (B) Proteins involved in the coagulation pathway are most prevalent in acellular ascites of colorectal carcinomatosis origin. (C) Cytokine arrays performed on acellular ascites from peritoneal carcinomatosis from different histological subtypes identified abundant PAI-1 levels in acellular ascites from colorectal peritoneal carcinomatosis.

[0021] Figure 7 Query and survival analysis of PAI-1, STAT3 and EMT expression in the Cancer Genome Atlas Colorectal Adenocarcinoma (TCGA COADREAD) cohort (n=345) are shown. (A) Correlation between PAI-1 and STAT3 expression. (B) Correlation between PAI-1 expression and EMT signature. The correlation of (AB) was determined by Pearson correlation coefficient test. Linear regression line is shown. (C) Kaplan-Meier survival analysis shows that colorectal cancer with high levels of PAI-1, activated STAT3 signaling and abundant epithelial-mesenchymal transition (EMT) signatures has the worst survival. (P: PAI-1, S: STAT3 signaling, E: EMT signature)

[0022] Figure 8 (A) Receptor tyrosine kinase (RTK) phosphorylation array performed on colorectal peritoneal carcinoma (PC) cell lines treated with cell-free ascites showed no JAK activation, suggesting a non-canonical STAT3 activation mechanism. (B) Western blot validation showed no JAK activity in cells treated with cell-free ascites.

[0023] Fig. 9Results of screening using ELISA are shown for (A) acellular ascites from colorectal peritoneal carcinomatosis (PC) (n=55) and (B) acellular ascites from different histological PC subtypes (n=156). PAI-1 levels in ascites and p-STAT3 (Y705) levels of cancer cells after acellular ascites treatment were measured and plotted to determine their correlation. PAI-1 concentrations were plotted on a log2 scale. p-STAT3 (Y705) levels are shown as optical density readings at 450nm (OD450). Correlation analysis was determined by Pearson's correlation coefficient test.

[0024] Fig.10 Untransformed values ​​of PAI-1 and p-STAT3 (Y705) levels were used in a gating strategy to identify patient subpopulations that may benefit from PAI-1 inhibition. Three distinct patient groups can be observed—patients with high PAI-1 levels and high STAT3 activation, termed PAI-1 paracrine addicted or PPA patients (upper right quadrant); patients with low PAI-1 levels but high STAT3 activation, termed co-activators predominant or CAP patients (upper left quadrant); and patients with low PAI-1 levels and low STAT3 activation, termed alternative pathways activation or APA patients (lower left quadrant). (A) PAI-1 and p-STAT3 gating of acellular ascites of colorectal peritoneal carcinomatosis (PC). (B) PAI-1 and p-STAT3 gating of acellular ascites of different histological PC subtypes. (C) PAI-1 and p-STAT3 cut-off values ​​used to stratify patients into three different groups. (D) Cohort of acellular ascites used in this analysis.

[0025] Fig.11The effects of TM5441 (PAI-1 inhibitor) on three different groups of cell-free ascites treated Colo-205 cells are shown. (A) Representative inhibitor dose-response curves for the PAI-1 paracrine addiction (PPA) group (black solid line), coactivator dominant (CAP) group (black dashed line), alternative pathway activation (APA) group (grey solid line), and fetal bovine serum (FBS; control group, grey dashed line) show a left shift in the dose-response curve, indicating responsiveness to PAI-1 inhibition. (B) Differential sensitivity of cell-free ascites corresponding to three different groups to TM5441, with the PAI-1 paracrine addiction (PPA) group (n=18) being the most sensitive to PAI-1 inhibition, followed by the coactivator dominant (CAP) group (n=59) and the alternative pathway activation (APA) group (n=17). (C) Cell-free ascites cohorts used in this analysis.

[0026] Fig.12 The effects of various pharmacological inhibition on three different groups of cell-free ascites treated Colo-205 cells are shown. Representative inhibitor dose-response curves for the PAI-1 paracrine addiction (PPA) group (black solid line), coactivator dominant (CAP) group (black dashed line), alternative pathway activation (APA) group (grey solid line), and fetal bovine serum (FBS; control, grey dashed line). The corresponding IC 50 Values ​​are shown as insets, mean ± SD. (A) Tiplaxtinin (PAI-1 inhibitor) dose-response curve, (B) Napabucasin (STAT3 inhibitor) dose-response curve, (C) BEZ235 (PI3K / mTOR dual inhibitor) dose-response curve, and (D) mitomycin C (a conventional chemotherapeutic agent–DNA crosslinker used in hyperthermic intraperitoneal chemotherapy (HIPEC)) dose-response curve. Targeting PAI-1, a major paracrine factor in acellular ascites, was shown to be more effective than targeting downstream signaling pathways, proliferation pathways, or DNA synthesis activated by acellular ascites.

[0027] Fig.13(A) Signaling pathways affected by PAI-1 inhibition were identified by RNA microarray analysis of cancer cells treated with cell-free ascites representing PAI-1 paracrine addiction (PPA) (PC085), coactivator dominant (CAP) (PC249), or fetal bovine serum (FBS; control) in the presence of TM5441 or DMSO vehicle. The IL6-JAK-STAT3 signaling pathway was significantly downregulated in PAI-1 paracrine addiction (PPA)-treated cells after PAI-1 inhibition. Normalized enrichment scores less than 0 indicate pathway inhibition, and scores greater than 0 indicate pathway activation. (B) Cancer cells treated with PAI-1 paracrine-addicted (PPA) acellular ascites (PC085 and PC383), coactivator-dominant (CAP) acellular ascites (PC249), and alternative pathway activated (APA) acellular ascites (PC010) in the presence of varying concentrations of TM5441 or DMSO vehicle (as measured by ELISA) demonstrated that cells exposed to PAI-1 paracrine-addicted (PPA) acellular ascites were dependent on PAI-1 to activate STAT3, as they required lower concentrations of TM5441 to inhibit STAT3 activation.

[0028] Fig.14(A) Schematic diagram of the modified peritoneal cancer index (PCI) for assessing tumor burden in a mouse model of peritoneal cancer proliferation (PC) cell line. This scoring system is a modification of the peritoneal cancer proliferation index (PCI) score of Klaver et al. (Klaver Y.LB, Hendriks T., Lomme R.MLM, Rutten HJT, Bleichrodt RP, de Hingh IHJT (2010) Intraoperative hyperthermic intraperitoneal chemotherapy after cytoreductive surgery for peritoneal carcinomatosis in an experimental model. British Journal of Surgery. 97: 1874-80) and Sugarbaker (Sugarbaker PH (1998) Intraperitoneal chemotherapy and cytoreductive surgery for the prevention and treatment of peritoneal carcinomatosis and sarcomatosis. Seminars in Surgical Oncology. 14: 254-61).

[0029] (B) In vivo validation of differential sensitivity to PAI-1 inhibition in a peritoneal carcinomatosis (PC) cell line mouse model treated with PAI-1 paracrine addiction (PPA) acellular ascites (PC085), coactivator-dominated (CAP) acellular ascites (PC249), and fetal bovine serum (FBS; control). The images shown represent peritoneal metastases formed in response to PAI-1 inhibition or vehicle. Arrows indicate visible tumors. (C) Tumor burden was assessed by a modified peritoneal carcinomatosis index (PCI) score. Mice treated with PAI-1 paracrine addiction (PPA) acellular ascites significantly reduced tumor burden in response to TM5441 compared to mice treated with coactivator-dominated (CAP) acellular ascites (PC249) and fetal bovine serum (n=5 mice / group).

[0030] Fig.15 We showed that TM5441 effectively inhibited peritoneal tumor formation in a mouse model of peritoneal carcinomatosis (PC) cell line exposed to PAI-1 paracrine-addicted (PPA) acellular ascites (PC085) by intraperitoneal (ip) instillation, but not when administered orally (n=4 mice / group).

[0031] Fig.16 Matched patient acellular ascites and its cellular components were used to generate patient-derived ascites-dependent xenografts (PDADX). (A) Representative images of intraperitoneal tumors formed in the PC383 patient-derived ascites-dependent xenograft (PDADX) and PC249 patient-derived ascites-dependent xenograft (PDADX) models. Arrows indicate visible tumors. (B) Representative hematoxylin and eosin (H&E) staining and immunohistochemical analysis showed that patient-derived ascites-dependent xenograft (PDADX) tumors had similar histological features to the corresponding patient tumor tissues, and these patient-derived ascites-dependent xenograft (PDADX) tumors were colonic (CK20+CK7-CDX2+). Scale bar, 50 μM.

[0032] Fig.17 PAI-1 inhibition was shown to be highly effective in an in vivo mouse model of acellular ascites addicted to PAI-1 paracrine addiction (PPA). (A) PAI-1 paracrine addiction (PPA) patient-derived ascites-dependent xenografts (PDADX) (PC383) and coactivator-dominant (CAP) patient-derived ascites-dependent xenografts (PDADX) (PC249) were treated with their matched acellular ascites or fetal bovine serum (FBS) in the presence of DMSO vehicle or 2 mM TM5441 (n = 4 mice / group). After killing the mice, tumor burden was quantified by weighing all visible tumors. Only PAI-1 paracrine addiction (PPA) patient-derived ascites-dependent xenografts (PDADX) treated with matched PAI-1 paracrine addiction (PPA) acellular ascites were sensitive to PAI-1 inhibition and showed a significant reduction in tumor burden. (B) Coactivator dominant (CAP) patient-derived ascites-dependent xenografts (PDADX) (PC249) were treated with their matched acellular ascites or PAI-1 paracrine-addicted (PPA) acellular ascites (PC383) in the presence of DMSO vehicle or 2 mM TM5441 (n=4 mice / group, except for the group treated with PC249 acellular ascites and DMSO (n=3)). Coactivator dominant (CAP) patient-derived ascites-dependent xenografts (PDADX) exposed to PAI-1 paracrine-addicted (PPA) acellular ascites became sensitive to PAI-1 inhibition, although not in the presence of their matched ascites.

[0033] Fig.18 A proposed model showing paracrine perturbations that could be used for new therapeutic strategies for peritoneal carcinomatosis (PC).

[0034] Fig.19 (A) Workflow for selecting candidates for p-STAT3 surrogate biomarkers. (B) Target prioritization based on systematic paired correlation analysis. Genes selected for validation by ELISA are shown in bold. Others represent genes that are not in the top 25% of positive correlation with STAT3 in the TCGA COADREAD database, and genes that are not in the top 25% of down-regulated / up-regulated in the TM5441 microarray database.

[0035] Fig. 20 A panel of validated surrogate biomarkers for p-STAT3 is shown (n=70). (A) Correlation between p-STAT3 and selected p-STAT3 surrogate biomarker candidates IL6, IL10, CCL2, MMP9, and ANGPT1. The concentration of surrogate biomarkers in acellular ascites of each patient was measured by ELISA and plotted against the degree of STAT3 phosphorylation (n=70 samples / surrogate marker). Correlation analysis was determined by Spearman correlation coefficient test. (B) Receiver operating characteristic (ROC) curve representing the ability of a single p-STAT3 surrogate biomarker to correctly classify the PAI-1 paracrine addiction (PPA) / coactivator dominant (CAP) group or alternative pathway activation (APA) group. (C) Critical values ​​of p-STAT3 surrogate biomarkers for classifying samples into the PAI-1 paracrine addiction (PPA) / coactivator dominant (CAP) group or alternative pathway activation (APA) group. (D) Summary of classification accuracy of combinations of single biomarkers and composite biomarkers. If the concentration of the sample is above the cut-off value, the biomarker is considered positive (+). (E) Summary of cut-off values ​​that can be used to identify patients who may be sensitive to PAI-1 inhibition.

[0036] Fig.21Shown is a panel of alternative biomarkers for p-STAT3 (n=40), (A) correlation between p-STAT3 and selected p-STAT3 alternative biomarker candidates TGFB1, POSTN, VSIG4, CD44 and CXCL10. The concentration of alternative biomarkers in each patient's cell-free ascites was measured by ELISA and plotted against the degree of STAT3 phosphorylation (n=40 samples / alternative marker). Correlation analysis was determined by Spearman's correlation coefficient test. (B) Receiver operating characteristic (ROC) curves representing the ability of a single p-STAT3 alternative biomarker to correctly classify the PAI-1 paracrine addiction (PPA) / coactivator-dominated (CAP) group or the alternative pathway activation (APA) group. (C) Receiver operating characteristic (ROC) curves for a composite biomarker panel consisting of TGFB1, POSTN, VSIG4, CD44 and CXCL10. (D) Receiver operating characteristic (ROC) curves of IL6 (left) and a composite biomarker panel including IL6, TGFB1, POSTN, VSIG4, CD44, and CXCL10 (right) using matched samples used in the analysis of TGFB1, POSTN, VSIG4, CD44, and CXCL10. (E) Summary of the area under the curve (AUC) for individual biomarkers and the composite biomarker panel.

[0037] definition

[0038] As used herein, the terms "level" and "concentration" are used synonymously.

[0039] As used herein, the term "biomarker" or "marker" refers to a molecular indicator of a specific biological property, biochemical characteristic, or aspect that can be used to determine the presence or absence and / or severity of a specific disease or condition. In other words, a "biomarker" is defined as a laboratory measurement that reflects the activity of a disease process. Examples of biomarkers are, but are not limited to, proteins, metabolites, genes, DNA, and RNA. Biomarkers as disclosed herein refer to isolated biomarkers. Evaluation of these biomarkers and their correlation with pathological conditions or diseases can be performed by, for example, determining the presence or absence of a marker, differences in the expression levels of the same marker in different clinical settings, and / or comparative analysis between diseased and disease-free samples.

[0040] As used herein, the term "surrogate marker" refers to the measurement of the level of a biomarker in a body fluid, which indicates an active biological process or signaling pathway, or the clinical pathological level of a disease. For example, a surrogate marker as described herein refers to one or more biomarkers that can be used as a surrogate or representative of an intended target. Therefore, as used herein, a surrogate marker can also refer to a panel of biomarkers that are used as a surrogate parameter for the level of STAT3 activation in cells obtained, for example, by analyzing ascites of a patient. For example, as shown herein, the biomarkers listed herein can be used as surrogate markers for STAT3 phosphorylation.

[0041] As used herein, the term "PAI-1" refers to plasminogen activator inhibitor-1 (PAI-1), also known as endothelial plasminogen activator inhibitor or serine protease inhibitor E1 (serpin E1). PAI-1 is a protein encoded by the human serine protease inhibitor E1 gene. The main function of PAI-1 is to inhibit urokinase-type plasminogen activator (uPA) and tissue-type plasminogen activator (tPA), inhibiting the enzyme responsible for cleaving plasminogen to form plasmin. Plasmin, independently or in combination with matrix metalloproteinases, mediates the degradation of the extracellular matrix. In this case, PAI-1 inhibits urokinase-type plasminogen activator by binding to the active site, preventing the formation of plasmin. Additional inhibition is mediated by PAI-1 in conjunction with urokinase-type plasminogen activator (uPA) / urokinase-type plasminogen activator receptor (uPAR) complexes, resulting in the degradation of the latter. It can therefore be said that PAI-1 inhibits the serine proteases tissue plasminogen activator (tPA) and urokinase plasminogen activator (uPA) / urokinase and is therefore an inhibitor of fibrinolysis (the physiological process that degrades blood clots). In addition, PAI-1 inhibits the activity of matrix metalloproteinases, which play a key role in the invasion of malignant cells through the basement membrane. In humans, PAI-1 is mainly produced by the endothelium (the cells lining the blood vessels), but is also secreted by other tissue types (such as adipose tissue and stromal tissue).

[0042] As used herein, the term "PAI-1 inhibitor" refers to a compound that is capable of inhibiting or blocking the activity of plasminogen activator inhibitor-1 (PAI-1). Various compounds and drugs are not limited to a single action and therefore can be considered PAI-1 inhibitors, even though they are structurally different. In other words, the inhibition of PAI-1 is a comprehensive feature of these compounds.

[0043] As used herein, the term "ascites" refers to the abnormal accumulation of fluid in the abdomen. There are many causes of ascites, including but not limited to cirrhosis of the liver, intra-abdominal cancer, congestive heart failure and tuberculosis. The term "ascites" may also refer to the free fluid in the peritoneal cavity. As used herein, when referring to the use of ascites in a treatment context, for example, when cells in cell culture are exposed to acellular ascites, this refers to contacting cells in vitro with acellular ascites fluid obtained from a subject in order to elucidate changes in biomarker levels and observe overall changes in the molecular or physical phenotype of the cells.

[0044] As used herein, the term "acellular ascites" refers to the supernatant component of ascites derived from, for example, a patient. The acellular ascites referred to herein is collected from the peritoneal cavity at the beginning of cytoreductive surgery (CRS) or during conventional ascites extraction (puncture), and is centrifuged for 10 minutes at 2000 g to separate the cellular components from the fluid components. The fluid components are filtered and sterilized using a 0.22 μm filter to make them suitable for downstream experiments. It will be appreciated by those skilled in the art that other sterilization methods known in the art can be used to obtain acellular ascites suitable for downstream applications.

[0045] As used herein, the term "phosphorylation" refers to the process by which a protein kinase transfers a phosphate group from adenosine triphosphate (ATP) or guanosine triphosphate (GTP) to one or more free hydroxyl groups of an amino acid. In general, phosphorylation is one of the switches used in signal cascades and pathways. Depending on the context of the pathway in question, phosphorylation can be used as an "on" or "off" switch. As an example of STAT3 phosphorylation (also referred to as "p-STAT3" in this disclosure), in STAT3 signaling, phosphorylation of key amino acid residues (such as tyrosine 705) on STAT3 induces the formation of STAT3 dimers, which are then translocated to the nucleus to regulate specific gene expression and trigger downstream signal cascades in cells.

[0046] As used herein, the term "STAT3" refers to signal transduction and transcription activator 3, a transcription factor encoded by the STAT3 gene. In response to growth factors, hormones and cytokines, STAT3 is phosphorylated by upstream receptor kinases, and therefore undergoes dimerization before translocation to the nucleus, where STAT3 dimers act as transcription activators. However, STAT3 pathways can also be activated independently of upstream receptor kinases by non-canonical pathways (see, for example, Interferon Independent Non-Canonical STAT Activation and Virus Induced Inflammation (Viruses. 2018 April; 10 (4): 196)).

[0047] As used herein, the term "p-STAT3 activation level" is used interchangeably with the terms "STAT3 phosphorylation," "STAT3 activation," or "STAT3 phosphorylation level."

[0048] As used herein, the term "sample" refers to a biological sample, which includes, but is not limited to, any amount of material from a living thing or a previously living thing. Such organisms include, but are not limited to, humans, mice, monkeys, rats, rabbits, and other animals. Such substances include, but are not limited to, body fluids, such as blood, plasma, ascites, serum, urine, cells, organs, tumor samples, biopsy samples, tissues, bones, bone marrow, lymph, lymph nodes, and skin. Such samples can be obtained from subjects known to have the disease, subjects believed to have the disease, and subjects without the disease. It will be appreciated by those skilled in the art that each type of sample requires different (pre) treatment steps before it can be used in the claimed method. By way of various examples, for samples in liquid form, centrifugation is required to separate cells and soluble components. For samples in solid form, tissue dissociation needs to be performed using a combination of mechanical dissociation and enzyme treatment to produce a single cell suspension, which can be centrifuged to separate supernatant and cell components. The supernatant / soluble components and cell components can then be evaluated by our in vitro and in vivo experiments. Those skilled in the art should know the methods required to obtain samples suitable for use in the methods disclosed herein.

[0049] As used herein, the term "peritoneal cancer spread" refers to the intra-abdominal spread of cancer, where the origin of the cancer spread can be a malignancy from an intra-abdominal organ or from the peritoneum itself (the thin layer of tissue that lines most of the abdominal organs).

[0050] As used herein, the term "cytoreductive surgery (CRS)" refers to the complete removal of macroscopic tumors found in the abdominal cavity by serial peritonectomy and evisceration.

[0051] As used herein, the term "hyperthermic intraperitoneal chemotherapy" refers to a therapy used to eradicate microscopic lesions left behind after cytoreductive surgery, which involves the administration of a heated solution of chemotherapy drugs into the peritoneal cavity for 60 to 90 minutes.

[0052] As used herein, the term "paracrine factor" refers to a diffusible and soluble protein secreted by a cell to regulate cellular responses in adjacent cells or cells of origin through paracrine or autocrine interactions. Examples of such paracrine factors include, but are not limited to, interleukin 6 (IL6), transforming growth factor β (TGF-β), Wnt proteins, sonic hedgehog (SHH), vascular endothelial growth factor (VEGF), and epidermal growth factor (EGF).

[0053] As used herein, the term "oncogenic addiction" refers to the phenomenon that a cell signaling cascade is activated when it is exposed to a paracrine factor. For example, STAT3 activation leads to the production and secretion of more of the same paracrine factor, resulting in a positive feedback loop (see, e.g., Fig.18 ). These cells use a positive feedback biological loop to grow and activate pathway activation, and therefore become addicted to the process. By the same logic, the term "oncogenic addiction to PAI-1" refers to a situation where PAI-1 activation leads to the production of more PAI-1, resulting in a positive feedback loop based on PAI-1. If the creation of this positive feedback loop is blocked, the cells that lack the key stimulus they have become accustomed to (i.e., addicted to) will die.

[0054] Detailed Description

[0055] The presence of ascites in colorectal peritoneal cancer spread predicts a poor prognosis. It is hypothesized that ascites is biologically relevant and can be used to explore new therapies. Exploiting tumor biology to identify new therapeutic strategies for this disease shows great clinical impact. As shown here, small molecule inhibitors targeting major signaling pathways for colorectal peritoneal cancer spread can be used in the clinical setting.

[0056] Thus, methods are disclosed herein that enable targeted therapy for patients with peritoneal cancer spread. It is also shown herein that, for example, small molecule inhibitors targeting major signaling pathways can be used to treat colorectal peritoneal cancer spread, or these inhibitors can be used in the following clinical settings: in the neoadjuvant setting, reducing the tumor burden in patients who are not candidates for cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC, also known as IPHC-hyperthermic intraperitoneal chemotherapy) to convert these patients into candidates for cytoreductive surgery and hyperthermic intraperitoneal chemotherapy; in the adjuvant setting, by adding small molecule inhibitors to the hyperthermic intraperitoneal chemotherapy regimen to improve the efficacy of eradicating residual microscopic lesions after cytoreductive surgery; in the palliative setting, reducing the debilitating symptoms caused by peritoneal disease; and in the preventive treatment setting, colorectal cancer patients at high risk of developing peritoneal cancer spread.

[0057] Currently, the only form of cure or standard of cure for patients who have or have peritoneal cancer metastasis is cytoreductive surgery with the instillation of hyperthermic intraperitoneal chemotherapy at the end of surgery. However, current hyperthermic intraperitoneal chemotherapy regimens do not take advantage of knowledge of tumor biology and only use conventional chemotherapy in the form of cytotoxic drugs. Furthermore, patients who are eligible for cytoreductive surgery and hyperthermic intraperitoneal chemotherapy only account for 10% of all patients with peritoneal cancer metastasis.

[0058] Within the scope of the present disclosure, biomarkers that can predict the response to the treatment of intraperitoneal (IP) instillation of PAI-1 inhibitors (e.g., but not limited to TM5441) have been identified. Using the methods disclosed herein, different patient groups that are considered to be responsive to this therapy have been determined. One of the groups includes patients with high concentrations of PAI-1 (≥20ng / mL) and high STAT3 activation (≥0.2OD450) at the same time, and without being bound by theory, it is believed that they are highly susceptible to PAI-1 inhibition. Another group includes patients with lower PAI-1 concentrations (<20ng / mL) compared to the first group, but high STAT3 activation (≥0.2OD450). This group of patients is also considered to be susceptible to PAI-1 inhibition. For example, this can be seen in ascites with high PAI-1 levels and simultaneous activation of STAT3 signaling in, for example, cancer cells. In the clinical setting, intraperitoneal instillation of PAI-1 inhibitors could be used in the neoadjuvant setting, during hyperthermic intraperitoneal chemotherapy, or even in the palliative care setting, thus providing a treatment option for many more patients than those who qualify for cytoreductive surgery and hyperthermic intraperitoneal chemotherapy. It is also believed that PAI-1 inhibitors could be nebulized for use in the palliative care setting, such as for pressurized intraperitoneal aerosol chemotherapy (PIPAC).

[0059] Furthermore, the data generated suggest that this strategy is applicable to patients with colorectal peritoneal carcinomatous spread and also to patients with peritoneal carcinomatous spread of other histological subtypes.

[0060] Thus, in one example, the subtype of peritoneal cancer spread can be, but is not limited to, colorectal peritoneal cancer spread, small intestinal peritoneal cancer spread, mesothelioma, endometrial peritoneal cancer spread, gastric peritoneal cancer spread, ovarian peritoneal cancer spread, appendiceal peritoneal cancer spread, pancreatic peritoneal cancer spread, urinary tract peritoneal cancer spread, and pseudomyxoma peritonei (PMP). In another example, the peritoneal cancer spread is of unknown origin. In one example, the subtype of peritoneal cancer spread is colorectal peritoneal cancer spread.

[0061] As used herein, the term "unknown primary" when used in conjunction with a tumor, tumor sample or subtype refers to the presence of peritoneal carcinomatous spread, where the primary tumor cannot be determined by clinical, radiological and pathological evaluation. This uncertainty may be due to reasons such as, but not limited to, the (small) size of the primary tumor is insufficient for pathological evaluation, or the primary tumor is encapsulated by external peritoneal carcinomatous spread, making it impossible to perform clinical detection, or the lack of tumor markers with high specificity.

[0062] In the context of the experiments disclosed in the present disclosure, the term "other peritoneal carcinomatosis (PC) histology" refers to histological subtypes of peritoneal carcinomatosis originating from the following sites, namely, lung, breast, peritoneum, gastro-ovarian synchronous, small intestine, urothelium, and palate. Due to the small number of samples collected in each subgroup, these samples were classified as "other PC histology".

[0063] In one example, peritoneal cancer spread is malignant. In another example, peritoneal cancer spread is a primary tumor. In yet another example, peritoneal cancer spread is a metastasis or a secondary tumor.

[0064] In another example, a method is disclosed for predicting, determining or detecting the susceptibility of a subject with peritoneal cancer metastasis to treatment with an anticancer drug or an anticancer therapeutic agent instilled in the peritoneal cavity based on the level of PAI-1 in the ascites in the peritoneal cavity. Without being bound by theory, it is believed that STAT3 activation in cancer cells exposed to ascites allows identification of a subgroup of patients who would benefit from PAI-1 inhibition.

[0065] As used herein, the term "susceptibility" refers to the tendency of something (e.g., a disease) to be affected by something else (e.g., a treatment for the disease). This effect may be favorable or unfavorable, depending on the subject in question. For example, if a disease is susceptible to a particular treatment, then the susceptibility of the disease to a particular treatment is a favorable effect. The disease is then said to be susceptible (or sensitive) to the treatment. On the other hand, if a disease is not susceptible to a given treatment, then the disease is considered unresponsive or resistant to the treatment.

[0066] As defined above, the term "predicting susceptibility" refers to the tendency that something (e.g., a disease) may be affected by something else (e.g., a treatment for the disease). In other words, predicting the susceptibility of cancer to a particular treatment is to determine whether the cancer will respond to treatment or anticancer treatment with a certain drug or anticancer drug. It is worth noting that the term "determining susceptibility" is not equivalent to, for example, "performing a prognosis." The former term focuses only on the possible response of the disease to a specific drug or therapy, while the latter describes the patient's clinical outcome, which is defined by parameters such as, but not limited to, the length of time that the disease is stable (after such a state is obtained), the length of time of overall survival and / or disease-free survival. Although in some cases, the influence of one term on another may be associated, that is, a disease that responds well to a given treatment (i.e., the disease is susceptible to the treatment) may increase the likelihood that the patient will obtain a positive prognosis for overall disease progression, but this cannot be used as a rule. As will be appreciated by those skilled in the art, a positive prognosis depends on many patient-specific factors, in addition to the susceptibility of the disease to treatment, e.g., the patient's overall health status before treatment, metabolism, diet, aggressiveness of the (primary) disease, secondary diseases and / or infections, etc.

[0067] Also disclosed herein are methods of predicting, determining or detecting the susceptibility of a subject having peritoneal cancer spread to anti-cancer drug treatment or anti-cancer therapy.

[0068] First, it was recognized from clinical data on patients with peritoneal carcinomatous spread who underwent surgery that patients with clinically evident ascites in the peritoneal cavity had a worse prognosis than those without clinically evident ascites. This prognostic significance was associated with peritoneal carcinomatous spread of colorectal origin, although it was not limited to this histologic subtype ( Figure 1 ). It is noteworthy that the comparison basis of the term "poorer prognosis" is as follows: a group of patients with a poorer prognosis are those patients who develop clinically evident ascites during surgery compared to those patients who do not have clinically evident ascites during surgery. As used herein, the term "clinically evident ascites" refers to ascites present during surgery in a volume of, for example, 50 ml or more.

[0069] In vitro treatment of established cell line models of peritoneal carcinomatous dissemination (Colo-205, HM3-TERT, and LP9-TERT) with cell-free ascites collected from patients showed increased proliferation, migration, and formation of colonies on stromal cells in a co-culture model ( Figure 2 ), a cell line model of peritoneal cancer spread that mimics tumors that are close to their in vivo environment.

[0070] Gene expression analysis of peritoneal carcinomatous cell lines treated with cell-free ascites showed activation of the STAT3 pathway ( Figure 3 ), indicating that STAT3 activation plays an important role in this disease.

[0071] Western blot analysis of STAT3 phosphorylation in cells treated with cell-free ascites showed that STAT3 signaling was activated via phosphorylation at Tyr705 ( Figure 4 a). Screening of cell-free ascites collected from different histological subtypes revealed that STAT3 activation was most prevalent when cells were treated with cell-free ascites collected from colorectal peritoneal carcinomatous disseminated compared with peritoneal carcinomatous disseminated from other anatomical sources ( Figure 4 b). Thus, the data show that acellular ascites from colorectal peritoneal cancer metastases induces a higher rate of STAT3 activation than acellular ascites from peritoneal cancer metastases from other anatomical sources. In addition, it is noteworthy that acellular ascites collected from peritoneal cancer metastases from other anatomical sources can also activate STAT3 signaling.

[0072] Immunohistochemistry of primary colorectal cancers matched to peritoneal metastases obtained from the same patients showed that STAT3 activation was more prevalent in metastases than in primary tumors ( Figure 5). Therefore, the data show that the treatment effect of depriving metastatic cells of STAT3 signaling is good compared to the strategy of depriving primary tumors of STAT3 signaling. This is because STAT3 activation is more common in metastatic tumors than in primary tumors. As shown in the data provided herein, compared with tumors in which STAT3 signaling is not activated by PAI-1, a subgroup of patients whose tumors have high STAT3 signaling due to high PAI-1 levels are more susceptible to PAI-1 inhibition. In tumors that do not show any STAT3 signaling activation, this situation is even less.

[0073] Treatment of an established cell line model of colorectal peritoneal carcinomatosis with cell-free ascites also resulted in enrichment of epithelial-mesenchymal transition (EMT) markers ( Figure 6 a). Unbiased cell-free ascites mass spectrometry screening performed on cell-free ascites of different histological origins together with a cytokine array identified the importance of coagulation / thrombolytic factors in cell-free ascites of colorectal peritoneal carcinomatosis ( Figure 6 b). PAI-1 (involved in preventing blood clotting) was also shown to be highly enriched in acellular ascites from colorectal peritoneal carcinomatosis ( Figure 6 c). This means that, by proteomic analysis of acellular ascites, for example, by mass spectrometry or cytokine arrays, the coagulation pathway was found to be enriched in colorectal peritoneal cancer proliferation. From the perspective of marker candidates, PAI-1, which is involved in the coagulation cascade, was also shown to be extremely abundant. Thus, a phenomenon is being described in which cancer cells hijack the presence of an active coagulation pathway for oncogenic activation. In other words, and without being bound by theory, it is believed that the presence of an activated coagulation pathway in the peritoneal cavity leads to the activation of oncogenic signaling pathways in cancer cells triggered by coagulation factors or factors involved in preventing coagulation. This is not intended to describe coagulation in the physical sense of having a blood clot in the abdomen.

[0074] The inventors' query of The Cancer Genome Atlas (TCGA) database showed that colorectal cancer with high levels of PAI-1 activated STAT3 signaling ( Figure 7 a) and showed enrichment of epithelial-mesenchymal transition signatures ( Figure 7 b) and have the worst prognosis ( Figure 7 c). In summary, it has been shown that when cancer cells are exposed to ascites, PAI-1 in the ascites can lead to STAT3 activation in these cancer cells, ultimately resulting in an epithelial-mesenchymal transition (EMT) phenotype, which is responsible for the clinical presentation of biologically aggressive tumors, leading to a poor prognosis in these patients. Notably, no JAK activation was found in cell lines treated with cell-free ascites, suggesting that ascites activates STAT3 signaling in a non-classical manner ( Figure 8). This means that in this case, STAT3 is activated in a non-classical manner, rather than a classical manner. Therefore, without being bound by theory, it is believed that other activators (e.g., PAI-1), rather than the classical activators of STAT3, such as IL6, can activate STAT3.

[0075] Thus, in one example, the sample is, but is not limited to, ascites, blood, serum, urine, drainage fluid, surgical drainage fluid, liquid body fluid, supernatant obtained from cells, supernatant obtained from organs, supernatant obtained from tissues, lymph, supernatant obtained from lymph nodes, liquid biopsy samples, and supernatant obtained from biopsy samples.

[0076] The supernatant obtained from an organ, tissue, etc. may refer to a liquid obtained from, for example, an organ sample that has been macerated, minced, ground, or pulverized after extraction. Alternatively, for samples containing little or no liquid, the sample may be placed in a clinically compatible buffer before or after mincing. The resulting liquid is called the supernatant, which may then be used downstream for further analysis.

[0077] In another example, the sample is a liquid sample. In yet another example, the method disclosed herein can be carried out on one or more samples. For example, the method disclosed herein can be carried out on two samples. In another example, the determination or measurement of PAI-1 concentration can be carried out on a sample, and the determination or measurement of STAT3 activation (for example, by phosphorylation) level can be carried out on another sample. These samples may be from the same or different sources. In one example, the first sample can be a cell-free sample, and the second sample can be a sample containing cells. In another example, the first sample can be ascites, and the second sample can be a biopsy sample. In one example, PAI-1 concentration and STAT3 activation (for example, by phosphorylation or by surrogate markers) can be measured in a single sample. In other words, the determination of PAI-1 concentration and STAT3 activation can be carried out on a single sample.

[0078] Knowing that PAI-1 is upstream of STAT3 activation by cancer cells via paracrine signaling, PAI-1 levels were systematically elucidated in acellular ascites fluid collected from patients with PC. An established PC cell line model, Colo-205, was also treated with these acellular ascites fluids and p-STAT3 levels were elucidated using an enzyme-linked immunosorbent assay (ELISA) to determine the extent of STAT3 activation. PAI-1 levels in the ascites fluid (log2; x-axis) were plotted against the extent of STAT3 phosphorylation (resulting in STAT3 activation) (y-axis), and it was identified that PAI-1 levels in the ascites fluid were positively correlated with STAT3 activation levels in the acellular ascites-treated cells, both in the context of acellular ascites fluid from patients with PC and in the context of acellular ascites fluid collected from patients with other histological subtypes of PC ( Fig. 9 a, b).

[0079] Then with the corresponding STAT3 phosphorylation degree analysis in the peritoneal carcinomatosis (PC) cell that is exposed to these ascites, the unconverted PAI-1 level in the acellular ascites.The phosphorylation level of STAT3 (Tyr705) is set as greater than 0.2 (OD 450) as the definition of activated STAT3 signal transmission, and it is noted that all PAI-1 levels show activated STAT3 signal transmission higher than the sample of 20ng / mL.This observed result facilitates the definition to three (sub) groups, as shown in the following section.

[0080] First, ascites with high PAI-1 levels (i.e., PAI-1 levels are greater than 20ng / ml) show a heavy reliance on PAI-1 to activate STAT3 signaling. These samples are referred to as PAI-1 paracrine addiction (PPA). Cell lines treated with acellular ascites collected from these patients result in high levels of STAT3 phosphorylation (high STAT3 activity). Without being bound by theory, it is believed that the activation of STAT3 in cancer cells may be completely dependent on the PAI-1 levels in the acellular ascites collected from this group of patients, emphasizing the carcinogenic addiction phenomenon of the upstream activator of this pathway. Secondly, acellular ascites with low PAI-1 levels (i.e., PAI-1 levels are less than 20ng / ml) and with activation of STAT3 signaling in cells exposed to these acellular ascites are referred to as coactivator-dominated (CAP). Despite low PAI-1 levels, cell lines treated with acellular ascites collected from these patients still result in high levels of STAT3 phosphorylation (high STAT3 activity). Without being bound by theory, it is believed that in this group, the combination of PAI-1 and other ligands may activate STAT3 signal transmission. Finally, the acellular ascites with low PAI-1 levels (i.e., PAI-1 levels are lower than 20ng / ml) and the acellular ascites that fail to activate STAT3 signal transmission may have ligands that activate other signaling pathways. These samples are referred to as alternative pathway activation (APA). The acellular ascites treated cell lines collected from these patients did not cause significant levels of STAT3 phosphorylation (low STAT3 activity). Fig.10 a and 10b emphasize that the classification of different forms of acellular ascites applies to acellular ascites of disseminated origin from colorectal peritoneal carcinoma as well as acellular ascites of other histologic subtypes.

[0081] To confirm this theory, Colo-205 cell lines were treated with TM5441 (PAI-1 inhibitor) in the presence of acellular ascites from 3 different subgroups, with the expectation that cells exposed to PAI-1 paracrine-addicted (PPA) acellular ascites would be highly sensitive to PAI-1 inhibition. As predicted, differential sensitivity to PAI-1 inhibition was observed based on PAI-1 and p-STAT3 gating ( Fig.11 Treatment with another PAI-1 inhibitor (Tiplaxtinin) also showed the same trend of differential response, emphasizing that PAI-1 inhibition is specific and the observed effects are not due to the cytotoxic effects of the inhibitor ( Fig.12a). Subsequently, a STAT3 inhibitor (Napabucasin), a dual PI3K / mTOR inhibitor (BEZ235), and a conventional chemotherapeutic agent (mitomycin C) used in hyperthermic intraperitoneal chemotherapy (HIPEC) for the treatment of colorectal peritoneal cancer metastasis (PC) were tested to compare their efficacy in inhibiting PAI-1 oncogenic addiction with inhibition of downstream signaling pathways activated by acellular ascites and cell proliferation. It was found that directly targeting cancer cells in the presence of acellular ascites was ineffective because the acellular ascites promoted chemoresistance in these tumor cells ( Fig.12 bd).

[0082] To further investigate the downstream signaling pathways involved in determining sensitivity to PAI-1 inhibition, RNA microarray was performed on Colo-205 cells treated with cell-free ascites representing PAI-1 paracrine addiction (PPA) (PC085), coactivator dominant (CAP) (PC249), or fetal bovine serum (FBS; control) in the presence of TM5441 or DMSO vehicle. Gene set enrichment analysis (GSEA) identified that the IL6-JAK-STAT3 signaling pathway was significantly downregulated in the PAI-1 paracrine addiction (PPA) group after PAI-1 inhibition ( Fig.13 This finding is consistent with the initial hypothesis that the hypersensitivity of the PAI-1 paracrine addiction (PPA) group to PAI-1 inhibition is attributed to the PAI-1-STAT3 signaling pathway. Similarly, measurements of p-STAT3 in cells treated with these cell-free ascites and TM5441 indicated that different concentrations of STAT3 were required to abrogate STAT3 activation ( Fig.13 b).

[0083] As proof-of-concept that this was not simply an in vitro biological observation, Colo-205 cells were injected intraperitoneally into BALB / c nude mice along with acellular ascites or fetal bovine serum (FBS) to create a peritoneal carcinomatosis (PC) model. These mice were treated with intraperitoneal (ip) injections of TM5441. Consistent with the in vitro results, a significant reduction in tumor burden was observed in mice treated with PAI-1 paracrine addicted (PPA) acellular ascites ( Fig.14 In one example, the optimal route of administration was then evaluated by comparing intraperitoneal injection and oral administration of TM5441. In a mouse model of peritoneal carcinomatosis (PC), intraperitoneal instillation of TM5441 was significantly superior to oral administration in reducing tumor burden ( Fig.15 This finding is consistent with observations in patients with peritoneal carcinomatosis (PC), in which systemic administration of drugs is generally considered ineffective because of the peritoneal-plasma barrier that results in reduced penetration of cytotoxic drugs from plasma into peritoneal tumors and ascites.

[0084] Subsequently, two patient-derived ascites-dependent xenografts (PDADXs), one from the PAI-1 paracrine-addicted (PPA) group (PC383 patient-derived ascites-dependent xenografts (PDADXs)) and one from the coactivator-dominant (CAP) group (PC249 patient-derived ascites-dependent xenografts (PDADXs)), were developed to better recapitulate the PAI-1 addiction theory as an avatar in patients with peritoneal carcinomatosis (PC). Morphological evaluation of the PADX tumors showed signet ring cell morphology, similar to the histology of the patient's initial tumor. Immunohistochemical staining also confirmed that the PADX tumors were colon-derived ( Fig.16 ).

[0085] When treated with TM5441, PC383 PDADX mice exposed to matched acellular ascites from the same patient elicited significantly better tumor growth inhibition compared to the vehicle control group and the fetal bovine serum (FBS) group. In contrast, PC249 PDADX mice exposed to acellular ascites from their matched patients and treated with TM5441 showed no reduction in tumor burden compared to the vehicle control group, similar to the tumor burden of the FBS group ( Fig.17 a). When PC249 patient-derived ascites-dependent xenograft (PDADX) mice were exposed to acellular ascites (PC383 ascites) from a PAI-1 paracrine-addicted (PPA) group, these tumor cells became susceptible to PAI-1 inhibition despite being resistant to PAI-1 inhibition in the presence of their own matched acellular ascites ( Fig.17 b). Taken together, this information describes a previously unknown oncogenic addiction phenomenon in the context of a closed biological system, in which the tumor and its microenvironment are isolated from the systemic circulation. In this context, paracrine factors provide key stimuli for pathway activation; paracrine inhibition provides the stopping point ( Fig.18 ).

[0086] The patient-derived ascites dependent xenograft (PDADX) model has two components. The first component is a solid tumor that is formed by allowing the cellular components in the ascites to nodulate in the host, usually in a mouse. The second component is acellular ascites collected from the same patient who acquired the solid tumor. The acellular ascites is co-injected into mice with the proliferating cellular components. This is a model that takes into account the intrinsic phenotype of the cells, as well as the paracrine environment of the tumor in the peritoneal cavity.

[0087] As a proof of concept, i.e., the method disclosed herein is capable of subclassifying patient ascites into PAI-1 paracrine addiction (PPA) group, coactivator dominant (CAP) group, and alternative pathway activation (APA) group, it is sought to identify surrogate markers of STAT3 activation in cells by analyzing the patient's acellular ascites. In short, STAT3-related genes were identified from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database by collecting all genes involved in the known STAT3 pathway. Secreted STAT3-related proteins were selected based on the extracellular genes listed in the NCBI Biosystems database and the proteins identified by mass spectrometry analysis of acellular ascites. Transcriptomic comparisons were performed using the two databases to prioritize putative STAT3 surrogate markers and to identify genes that were downregulated and upregulated in cells treated with PAI-1 paracrine addiction (PPA) acellular ascites in response to TM5441 (PAI-1 inhibition). Genes were ranked from the most downregulated to the most upregulated, followed by a systematic paired correlation analysis of candidate genes. As Fig.19 As shown in b, paired analysis of each group was prioritized and representative genes were selected from each group based on the literature review to reduce the selection to 35 genes. Based on the prioritization, the potential good correlation with p-STAT3 from the Luminex assay data, and the importance of the candidate genes in cancer pathogenesis in the literature review, targets were selected for further evaluation by enzyme-linked immunosorbent assay (ELISA) ( Fig.19 This was validated in a cohort of 40 to 70 patients, identifying a 4-biomarker panel that determined the level of STAT3 activation in cells analyzed from the patient's cell-free ascites fluid ( Fig. 20 and Fig.21 ). This discovery could also serve as the basis for, for example, a point-of-care stratification kit for patients who would benefit from PAI-1 therapy.

[0088] As described above, the present disclosure highlights exemplary critical levels of PAI-1 in acellular ascites fluid of patients with peritoneal carcinomatous metastasis and, when combined with the levels of STAT3 activation in cancer cells exposed to these acellular ascites fluids, identifies a subgroup of patients who would benefit from PAI-1 inhibition.

[0089] In one example, the concentration of PAI-1 is between 0ng / ml and 450ng / ml, between 10ng / ml and 20ng / ml, between 15ng / ml and 25ng / ml, or between 19ng / ml and 29ng / ml. In one example, the concentration of PAI-1 is between 0ng / ml and 17ng / ml. In another example, the concentration of PAI-1 is between 0ng / ml and 20ng / ml. In another example, the concentration of PAI-1 in the context of the present invention is either less than 20ng / ml, or greater than or equal to 20ng / ml.

[0090] In another example, the level of STAT activation as measured by phosphorylation is between 0 and 1.7 (measured as optical density at 450 nm (OD450)). In one example, the level of STAT activation as measured by phosphorylation is between 0.01 and 1, between 0.1 and 0.5, between 0.05 and 0.19, between 0.18 and 0.26, between 0.24 and 0.48, between 0.35 and 0.5, about 0.08, between 0.4 and 0.6, between 0.5 and 0.75, between 0.65 and 0.8, between 0.79 and 0.90, between 0.88 and 0.95, between 0.9 and 1, about 0.1, about 0.15, about 0.17, about 0.18, about 0.19, about 0.2, about 0.21, about 0.22, about 0.23, about 0.24, about 0.25, or about 0.3 (measured at optical density at 450 nm (OD450)). In another example, the level of STAT activation as measured by phosphorylation in the context of the present invention is either less than 0.2 ng / ml (OD450) or greater than 20 ng / ml (OD450).

[0091] Reference to the term "0" (zero) includes as a value based on the understanding that when the presence of a marker is, for example, below the detection limit of a kit or detection method and is therefore not measurable, "0" is also used. In this case, the observed value is usually indicated as "not applicable (na)" or "nil".

[0092] In order to include most PAI-1 paracrine addiction (PPA) / coactivator dominant (CAP) samples, the lower 5% percentile of alternative biomarker values ​​of 60 PAI-1 paracrine addiction (PPA) / coactivator dominant (CAP) samples were selected as initial cutoff values ​​(Extended Data, not shown). For MMP9, the biomarker value with the highest value in the alternative pathway activation (APA) samples, 13 ng / ml, was selected to exclude all alternative pathway activation (APA) samples. Based on the group of 3 or 4 initial cutoff values, 52 PAI-1 paracrine addiction (PPA) / coactivator dominant (CAP) samples and 2 alternative pathway activation (APA) samples were filtered out as PAI-1 paracrine addiction (PPA) / coactivator dominant (CAP) samples (Extended Data, not shown), corresponding to 86.67% and 80.0% accuracy, respectively.

[0093] To improve accuracy, more stringent cutoffs for IL6 and IL10 were chosen to exclude false positive alternative pathway activation (APA) samples, and less stringent cutoffs for CCL2 and MMP9 were chosen to include false negative PAI-1 paracrine addiction (PPA) / coactivator dominance (CAP) samples. The final cutoffs were Fig. 20 c. Based on the groups of 3 or 4 final cut-off values, 56 PAI-1 paracrine addiction (PPA) / coactivator dominance (CAP) samples and 1 alternative pathway activation (APA) sample were filtered out as PAI-1 paracrine addiction (PPA) / coactivator dominance (CAP) samples (Extended Data, not shown), corresponding to accuracies of 93.33% and 90.0%, respectively. The overall accuracy of this composite biomarker panel (passing ≥ 3 biomarker cut-off values) was 92.86% ( Fig. 20 b).

[0094] Based on the information provided herein, it has been shown that IL6 alone is the most statistically robust predictor of STAT3 phosphorylation (p-STAT3) based on a stepwise approach and the best subsets approach using the Akaike information criterion or the Bayesian information criterion. In general, regression analysis is a statistical method for evaluating whether a set of independent variables significantly affects a dependent variable. Stepwise regression is a method for fitting a regression model by automatically adding or removing individual predictors and selecting a single model based on statistical significance. The best subsets regression method is a method for comparing all possible models using a specified set of predictors, and displays the best fitting model containing one predictor, two predictors, etc. The Akaike information criterion is an estimate of the out-of-sample prediction error and relative quality of each model, thereby providing a means of model selection. The Bayesian information criterion is a criterion for model selection in a limited set of models, which is based on the likelihood function and solves possible overfitting problems by adding more parameters.

[0095] For example, a cutoff value of IL6 at 997pg / ml can define PAI-1 paracrine addiction (PPA) / coactivator-dominated (CAP) samples with 95% accuracy, and exclude alternative pathway activation (APA) samples with 80% accuracy, equivalent to 92.86%. It is further shown that the overall prediction accuracy can be improved with the increase in the number of biomarkers used in the composite biomarker group. For example, a group of IL6, IL10, CCL2 and MMP9 with 3 or 4 positive biomarkers as the standard can identify PAI-1 paracrine addiction (PPA) / coactivator-dominated (CAP) subjects with 93.33% accuracy, and exclude alternative pathway activation (APA) subjects with 90% accuracy, equivalent to 92.86% overall accuracy. Other exemplary groups can be found throughout this specification. The above means that the minimum number of markers required to obtain statistically robust results is a biomarker (e.g., IL6). These biomarkers can be, but are not limited to, the biomarkers listed herein. In one example, the biomarker panel (panel or group) includes IL6. In one example, a single biomarker is used in the methods disclosed herein, wherein the biomarker is but is not limited to IL6 (interleukin 6), IL10 (interleukin 10), CCL2 (chemokine (CC motif) ligand 2; also known as monocyte chemoattractant protein 1 (MCP1) or small inducible cytokine A2), MMP9 (matrix metallopeptidase 9, also known as 92kDa type Iv collagenase, 92kDa gelatinase or gelatinase B (GELB)), TGFB1 (transforming growth factor beta 1), POSTN (periostin PN or osteoblast-specific factor OSF-2), VSIG4 (containing V-set and immunoglobulin domains 4), CD44 and CXCL10 (CXC motif chemokine 10, also known as gamma interferon-induced protein 10 (IP-10) or small inducible cytokine B10). In another example, two biomarkers are used in the methods disclosed herein, wherein the two biomarkers are, but are not limited to, the following combinations: IL6 and IL10; IL6 and CCL2; IL10 and CCL2; IL6 and MMP9; IL10 and MMP9; and CCL2 and MMP9. In yet another example, three biomarkers are used in the methods disclosed herein, wherein the three biomarkers are, but are not limited to, the following combinations: IL6, IL10 and CCL2; IL6, IL10 and MMP9; IL6, CCL2 and MMP9; IL10, CCL2 and MMP9. In another example, four biomarkers are used in the methods disclosed herein, wherein the four biomarkers are IL6, IL10, CCL2 and MMP9.In yet another example, five biomarkers are used in the methods disclosed herein, wherein the five biomarkers are TGFB1, POSTN, VSIG4, CD44, and CXCL10. In another example, six biomarkers are used in the methods disclosed herein, wherein the six biomarkers are IL6, TGFB1, POSTN, VSIG4, CD44, and CXCL10. In another example, the group disclosed herein includes, but is not limited to, the following biomarkers: IL6; IL10; CCL2; MMP9; IL6 and IL10; IL6 and CCL2; IL10 and CCL2; IL6 and MMP9; IL10 and MMP9; CCL2 and MMP9; IL6, IL10 and CCL2; IL6, IL10 and MMP9; IL6, CCL2 and MMP9; IL10, CCL2 and IL6; and IL10, CCL2 and MMP9.

[0096] For example, the cutoff values ​​of four surrogate biomarkers were determined by screening acellular ascites of 70 patients. Taking into account the flexibility of patient samples, a ±5% cutoff range was included for each biomarker. Therefore, in one example, the present invention, when referring to a cutoff value, refers to a specific cutoff value with a ±5% buffer or a ±2% buffer.

[0097] In one example, a patient subgroup or subset is defined as having a PAI-1 level between 0ng / ml and 20ng / ml and a p-STAT3 activation level below 0.2 (OD450). In another example, a patient subgroup or subset is defined as having a PAI-1 level between 0ng / ml and 20ng / ml and a p-STAT3 activation level equal to or greater than 0.2 (≥0.2; OD450). In another example, a patient subgroup or subset is defined as having a PAI-1 level equal to or greater than 20ng / ml (≥20ng / ml) and a p-STAT3 activation level equal to or greater than 0.2 (≥0.2; OD450).

[0098] In yet another example, a patient subgroup or subset is defined as having a PAI-1 level between 0 ng / ml and 17 ng / ml and a p-STAT3 activation level below 0.2 (OD450). In another example, a patient subgroup or subset is defined as having a PAI-1 level between 0 ng / ml and 17 ng / ml and a p-STAT3 activation level equal to or greater than 0.2 (≥0.2; OD450). In another example, a patient subgroup or subset is defined as having a PAI-1 level equal to or greater than 17 ng / ml (≥17) and a p-STAT3 activation level equal to or greater than 0.2 (≥0.2; OD450).

[0099] The concentrations of five exemplary surrogate markers identified using the methods disclosed herein (in this case IL6, IL10, CCL2, MMP9, and ANGPT1) were plotted against the degree of STAT3 phosphorylation. Fig. 20 As shown. Based on Spearman correlation analysis ( Fig. 20 R in , IL6, IL10, and CCL2 were selected as surrogate biomarkers for STAT3 phosphorylation. Although MMP9 showed a weak correlation with phosphorylated STAT3, the concentration of MMP9 in PAI-1 paracrine addiction (PPA) / coactivator dominance (CAP) samples was significantly higher than that in alternative pathway activation (APA) samples (unpaired t-test, P < 0.05). Inclusion of MMP9 as a surrogate biomarker helped to exclude alternative pathway activation (APA) samples from PAI-1 paracrine addiction (PPA) / coactivator dominance (CAP) samples.

[0100] Therefore, in one example, a patient subgroup or subset is defined based on the concentration of PAI-1 and p-STAT3. If p-STAT3 is used to determine which patient subgroup or subset the subject to be tested belongs to (e.g., used in combination with PAI-1), other surrogate markers other than p-STAT3 can be selectively measured. In another example, if p-STAT3 is measured directly, surrogate markers are no longer measured. In another example, if p-STAT3 is not used to determine which patient subgroup or subset the subject to be tested belongs to, surrogate markers listed herein are used instead of STAT3 phosphorylation for direct measurement.

[0101] In one example, a PAI-1 concentration below 20 ng / ml indicates that the patient belongs to the coactivator dominant (CAP) or alternative pathway activated (APA) subgroup. In another example, a PAI-1 concentration greater than or equal to 20 ng / ml indicates that the patient belongs to the PAI-1 paracrine addicted (PPA) subgroup.

[0102] In one example, a p-STAT3 concentration of less than 0.2 OD450 indicates that the patient belongs to the alternative pathway activation (APA) subgroup. In another example, a p-STAT3 concentration of at least 0.2 OD450 or higher indicates that the patient belongs to the PAI-1 paracrine addiction (PPA) or coactivator dominant (CAP) subgroup.

[0103] In one example, if the patient is shown to have a PAI-1 concentration of at least 20 ng / ml or higher and a p-STAT3 concentration of at least 0.2 OD450 or higher, the patient subgroup or subset is defined as a PAI-1 paracrine addiction (PPA) group.

[0104] In one example, if the patients are shown to have a PAI-1 concentration of less than 20 ng / ml and a p-STAT3 concentration of at least 0.2 OD450 or higher, the patient subgroup or subset is defined as a coactivator dominant (CAP) group.

[0105] In one example, if the patients are shown to have a PAI-1 concentration of less than 20 ng / ml and a p-STAT3 concentration of less than 0.2 OD450, the patient subgroup or subset is defined as the alternative pathway activation (APA) group.

[0106] In one example, if the patient is shown to have a PAI-1 concentration of at least 20 ng / ml or more and an elevated p-STAT3 concentration, the patient subgroup or subset is defined as the PAI-1 paracrine addiction (PPA) group.

[0107] In one example, if the patients are shown to have a PAI-1 concentration of less than 20 ng / ml and an elevated p-STAT3 concentration, the patient subgroup or subset is defined as the coactivator dominant (CAP) group.

[0108] In one example, if the patients are shown to have a PAI-1 concentration below 20 ng / ml and a reduced p-STAT3 concentration, the patient subgroup or subset is defined as the alternative pathway activation (APA) group.

[0109] In one example, if the patients are shown to have increased PAI-1 concentration and p-STAT3 concentration of at least 0.2 OD450 or higher, the patient subgroup or subset is defined as the PAI-1 paracrine addiction (PPA) group.

[0110] In one example, if the patients are shown to have a reduced PAI-1 concentration and a p-STAT3 concentration of at least 0.2 OD450 or higher, the patient subgroup or subset is defined as a coactivator dominant (CAP) group.

[0111] In one example, if the patients are shown to have a reduced PAI-1 concentration and a p-STAT3 concentration of less than 0.2 OD450, the patient subgroup or subset is defined as the alternative pathway activation (APA) group.

[0112] In one example, the concentration of p-STAT3 is measured using one or more surrogate markers, wherein the surrogate markers are, but are not limited to, IL6, CCL2, IL10, MMP9, TGFB1, POSTN, VISG4, CD44, CXCL10, and combinations thereof.

[0113] In one example, a patient subgroup or subset is defined using a panel of markers including IL6, CCL2, IL10, MMP9, TGFB1, POSTN, VISG4, CD44, and CXCL10. In another example, a patient subgroup or subset is defined using a panel of markers including IL6, CCL2, IL10, and MMP9. In yet another example, a patient subgroup or subset is defined using a panel of markers including PAI-1 and pSTAT3.

[0114] In one example, the critical value of IL6 is a concentration of 997pg / ml. In another example, the critical value of IL10 is a concentration of 15pg / ml. In another example, the critical value of CCL2 is a concentration of 450pg / ml. In yet another example, the critical value of MMP9 is a concentration of 3ng / ml. In the above examples, a concentration equal to or greater than the specific critical value of each marker indicates that the patient belongs to the PAI-1 paracrine addiction (PPA) and coactivator-dominated (CAP) subgroups. In other words, for the corresponding markers, the values ​​shown herein may also be referred to as critical values ​​or "(+)". On the contrary, if the determined concentration is lower than the reference critical value of the same marker mentioned above, the corresponding marker may be indicated as "(-)".

[0115] In one example, a panel of markers including IL6, CCL2, IL10 and MMP9 is used to define a patient subgroup or subset, wherein a combination of any two markers showing a concentration below a cutoff value indicates that the patient belongs to the alternative pathway activation (APA) subgroup.

[0116] In one example, a panel of markers including IL6, CCL2, IL10 and MMP9 is used to define a patient subgroup or subset, wherein a combination of any three markers showing a concentration above a cutoff value indicates that the patient belongs to the PAI-1 paracrine addicted (PPA) and coactivator dominant (CAP) subgroups.

[0117] In another example, a panel of markers including IL6, CCL2, IL10 and MMP9 is used to define a patient subgroup or subset, wherein all four markers showing concentrations above a cutoff value indicate that the patient is PAI-1 paracrine addicted (PPA) and coactivator dominant (CAP).

[0118] In another example, a panel of markers including TGFB1, POSTN, VSIG4, CCD44 and CXCL10 is used to define a patient subgroup or subset, wherein all five markers showing concentrations above a cutoff value indicates that the patient belongs to the PAI-1 paracrine addiction (PPA) and coactivator dominant (CAP) subgroups.

[0119] In yet another example, a panel of markers including IL6, TGFB1, POSTN, VSIG4, CCD44 and CXCL10 is used to define a patient subgroup or subset, wherein all six markers showing concentrations above a cut-off value indicate that the patient belongs to the PAI-1 paracrine addiction (PPA) and coactivator dominant (CAP) subgroups.

[0120] In another example, the concentration of p-STAT3 is determined first, and then the concentration of PAI-1 is determined.

[0121] In one example, if the p-STAT3-based concentration measurement results show that the patient belongs to the PAI-1 paracrine addiction (PPA) and coactivator-dominated (CAP) subgroup, a PAI-1 concentration of less than 20 ng / ml indicates that the subject belongs to the coactivator-dominated (CAP) subgroup. If the p-STAT3-based concentration measurement results show that the patient belongs to the PAI-1 paracrine addiction (PPA) and coactivator-dominated (CAP) subgroup, a PAI-1 concentration of at least 20 ng / ml or higher indicates that the subject belongs to the PAI-1 paracrine addiction (PPA) subgroup. If the p-STAT3-based concentration measurement results show that the patient belongs to the alternative pathway activation (APA) subgroup, a PAI-1 concentration of less than 20 ng / ml indicates that the subject belongs to the alternative pathway activation (APA) subgroup. If the p-STAT3-based concentration measurement results show that the patient belongs to the alternative pathway activation (APA) subgroup, a PAI-1 concentration of at least 20 ng / ml or higher indicates that the subject belongs to an undetermined subgroup.

[0122] In another example, a subgroup or subset of patients is defined as having an IL6 concentration of less than 997 pg / ml, a CCL2 concentration of less than 450 pg / ml, an IL10 concentration of less than 15 pg / ml, and an MMP9 concentration of less than 3 ng / ml. This group is referred to as the alternative pathway activation (APA) group as defined herein.

[0123] In another example, a subgroup or subset of patients is defined as having an IL6 concentration equal to or greater than 997 pg / ml (≥997 pg / ml), a CCL2 concentration equal to or greater than 450 pg / ml (≥450 pg / ml), an IL10 concentration equal to or greater than 15 pg / ml (≥15 pg / ml), and an MMP9 concentration equal to or greater than 3 ng / ml (≥3 ng / ml). This group is collectively referred to as the PAI-1 paracrine addiction (PPA) and coactivator dominant (CAP) group as defined herein.

[0124] In one example, the methods disclosed herein can be performed in a treatment setting, which is but not limited to a neoadjuvant treatment setting, an adjuvant treatment setting, a palliative treatment setting, and a preventive treatment setting. In another example, the methods disclosed herein can be performed on the same subject in one or more settings.

[0125] As used herein, the term "environment" refers to the time of assessing biomarkers and the timing of treatment. For example, the term "neoadjuvant therapy environment" means that ascites has been extracted before the patient receives surgery, and ascites is extracted by percutaneous drainage surgery. After determining the patient's susceptibility, appropriate treatment will be provided (depending on which group the patient falls into, i.e. PAI-1 paracrine addiction (PPA), coactivator-dominant (CAP), alternative pathway activation (APA) group). In the adjuvant therapy environment, a drainage tube is inserted before surgery to extract ascites from the abdominal cavity. After determining the patient's susceptibility, appropriate treatment will be provided during hyperthermic peritoneal chemotherapy (HIPEC) (depending on which group the patient belongs to, i.e. PAI-1 paracrine addiction (PPA), coactivator-dominant (CAP), alternative pathway activation (APA) group). In the palliative care environment, the patient does not receive any surgery and extracts ascites for analysis. Patients received appropriate palliative care (depending on which group the patient belonged to, i.e., PAI-1 paracrine addiction (PPA), coactivator-dominant (CAP), alternative pathway activation (APA) groups).

[0126] In another example, a surrogate marker is used to determine or measure the level of STAT3 activation (or phosphorylation). In another example, the STAT3 phosphorylation level is determined by measuring the concentration of one or more surrogate markers. Alternatively, the STAT3 phosphorylation level can also be determined by directly measuring the concentration of phosphorylated STAT3. It will be appreciated by those skilled in the art that STAT3 phosphorylation cannot be directly determined, for example, in a liquid sample, because phosphorylation occurs in the cell. Therefore, when measuring the STAT3 phosphorylation level in a liquid form, cells exposed to acellular ascites must be subjected to cell lysis in vitro, in vivo, and in a clinical setting. The STAT3 phosphorylation level in the obtained sample is determined using, for example, an enzyme-linked immunosorbent assay (ELISA) or any other method capable of determining the level. Cell lysis can be performed using methods known to those skilled in the art, and they can determine which method is most suitable for the sample in hand.

[0127] In another example, the STAT3 phosphorylation level is determined by measuring the concentration of one or more alternative markers. In yet another example, the STAT3 phosphorylation level (p-STAT3) can also be determined by measuring the p-STAT3 level of the cell components present in ascites or tumor biopsy. In another example, the level of STAT3 phosphorylation can be determined by directly measuring the concentration of phosphorylated STAT3 and by measuring the concentration of one or more alternative markers.

[0128] As used herein, the term "surrogate marker" refers to one or more (bio) markers that can be used to replace the expected target or as a representative of the expected target. The term "biomarker" can and can be used interchangeably with the term "surrogate marker" in the present disclosure. For example, as disclosed herein, STAT3 activation levels can be measured by determining the level of IL6. In an example, the relationship between the surrogate marker and the expected target can be proportional, meaning that the increase or decrease in the level or concentration of the surrogate marker is understood to have the same increase or decrease in the level or concentration of the expected target. This relationship can also be linear. However, there may also be surrogate markers that are inversely proportional to the expected target.

[0129] In one example, the surrogate markers used to determine the level of STAT3 activation (or phosphorylation) may be, but are not limited to, one or more markers listed in Table 1.

[0130] In one example, the STAT3 phosphorylation level is determined by measuring the concentration of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10 or more surrogate markers. In one example, the STAT3 phosphorylation level is determined by measuring the concentration of at least 3 surrogate markers. In one example, these 3 markers can be but are not limited to IL6, IL10 and CCL2. In one example, the STAT3 phosphorylation level is determined by measuring the concentration of at least 4 surrogate markers. In one example, these 4 markers can be but are not limited to IL6, IL10, CCL2 and MMP9. In one example, the STAT3 phosphorylation level is determined by measuring the concentration of at least 5 surrogate markers. In one example, these 5 markers can be but are not limited to TGFB1, POSTN, VSIG4, CD44 and CXCL10. In one example, the STAT3 phosphorylation level is determined by measuring the concentration of at least 6 surrogate markers. In one example, these 6 markers can be but are not limited to IL6, TGFB1, POSTN, VSIG4, CD44 and CXCL10. In one example, a surrogate marker is used to perform the method disclosed herein. In another example, 2 surrogate markers are used to perform the method disclosed herein. In another example, 3 surrogate markers are used to perform the method disclosed herein. In another example, 4 surrogate markers are used to perform the method disclosed herein. In another example, 5 surrogate markers are used to perform the method disclosed herein. In another example, 6 surrogate markers are used to perform the method disclosed herein. For example, for example, a biomarker panel will measure the concentration of a limited number of biomarkers. In one example, the panel includes or consists of IL6, IL10, CCL2, and MMP9. In the method disclosed herein, in order to define a patient sample as PAI-1 paracrine addicted (PPA) / coactivator-dominated (CAP), the value of the surrogate marker detected in the sample must pass the corresponding critical value defined for each surrogate marker. For example, in a group of 4 markers, at least 3 of the 4 surrogate markers must pass their corresponding critical values. For example, in a 2-marker group, at least one biomarker or both biomarkers must pass their corresponding cutoff value, depending on the markers selected. For example, in a 3-marker group, at least two biomarkers or all biomarkers must pass their corresponding cutoff value, depending on the markers selected. For example, in a 4-marker group, at least 3 biomarkers or all biomarkers must pass their corresponding cutoff value, depending on the markers selected. See Exemplary Groups Fig. 20 D.

[0131] Table 1: Non-exhaustive list of putative surrogate markers for determining STAT3 activation levels

[0132]

[0133]

[0134]

[0135]

[0136]

[0137]

[0138]

[0139]

[0140] Fig.19 a provides an overview of the selection workflow of p-STAT3 surrogate markers. In short, and as described above, STAT3-related genes were determined from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database by searching for all genes involved in the known STAT3 pathway. Secreted STAT3-related proteins were selected based on the extracellular genes listed in the NCBI Biosystems database and the proteins determined by mass spectrometry analysis of cell-free ascites. Two databases were used for transcriptomic comparison to prioritize the putative STAT3 surrogate markers. Database 1 was used to determine genes that were positively correlated with STAT3 in the Cancer Genome Database (TCGA) colorectal cancer (COADREAD) data set. Genes were arranged from the most positively correlated to the least correlated with STAT3. Database 2 was derived from microarray analysis of cells treated with cell-free ascites of PAI-1 paracrine addiction (PPA) exposed to TM5441 to determine genes that were downregulated and upregulated in cells treated with PAI-1 paracrine addiction (PPA) cell-free ascites in response to TM5441 (PAI-1 inhibitor). Upregulated genes were also of interest, as these are thought to represent genes involved in the rescue mechanism in response to PAI-1 inhibition. Again, genes were ranked from most downregulated to most upregulated. A systematic pairwise correlation analysis was then performed on the candidate genes by focusing on the top 1% and 25% of genes that were positively correlated with STAT3 in database 1, and the top 1% and 25% of genes that were most downregulated and most upregulated in database 2. Fig.19As shown in b, paired analysis of each group was prioritized and representative genes were selected from each group based on the literature review to reduce the list of potential targets to 35 genes. Based on the prioritization, the potential good correlation with p-STAT3 from the Luminex assay data, and the importance of candidate genes in cancer pathogenesis from the literature review, 10 targets were selected for further evaluation using enzyme-linked immunosorbent assay (ELISA). Using Spearman correlation analysis, the concentration of each surrogate marker in cell-free ascites fluid was correlated with the level of p-STAT3 in cells treated with cell-free ascites fluid.

[0141] Therefore, the surrogate marker disclosed herein can be selected based on its correlation with STAT3.Compared with the same marker in acellular ascites treated sample or negative control, the surrogate marker disclosed herein can also be selected based on its upregulation or downregulation.Once sorted (for example, by prevalence, priority or any other criteria), these markers can be but are not limited to the top 1%, 2%, 3%, 4%, 5%, 6%, 7%, 8%, 9%, 10%, 11%, 12%, 13%, 14%, 15%, 16%, 17%, 18%, 19%, 20%, 21%, 22%, 23%, 24% or 25% of all markers listed based on the above criteria.For example, a marker in the top 1% of a marker that is positively correlated with STAT3 can be selected.In another example, a marker in the top 1% of a marker that is negatively correlated with STAT3 phosphorylation can be selected.As used herein, positive correlation refers to the proportional relationship between a surrogate marker and its target. Thus, a negative correlation refers to an inversely proportional (or opposite) relationship between a surrogate marker and its target. For example, a positive correlation means that an increase in the target concentration results in an increase in the surrogate marker concentration. A positive correlation may also mean that a decrease in the target concentration results in a decrease in the surrogate marker concentration. Conversely, a negative correlation means that an increase in the target concentration results in a decrease in the surrogate marker concentration. Markers may also be selected in the top 1% or 25% of markers that are upregulated or downregulated compared to a control or any other benchmark.

[0142] In another example, a surrogate marker is selected based on its up-regulation and / or down-regulation. Such up-regulation or down-regulation can be determined based on the level of such marker in a sample that has been treated with a PAI-1 inhibitor, for example.

[0143] Those skilled in the art will readily appreciate that markers may be selected for reasons and criteria other than those listed herein, e.g., markers that do not show any significant correlation with STAT3 but show a significant effect on, e.g., multivariate analysis. It will also be appreciated that, for example, multiple criteria may be applied to the initial marker pool to narrow the scope and obtain a final list of alternative markers.

[0144] Of the 10 selected targets, 5 exemplary candidate surrogate markers (IL6, IL10, CCL2, MMP9, and ANGPT1) were validated on 70 patient samples and successfully identified an exemplary composite biomarker panel. For example, such a composite biomarker panel may consist of four targets (IL6, CCL2, IL10, and MMP9) that are surrogate biomarkers for STAT3. The overall accuracy of this exemplary panel was 92.86%.

[0145] In addition, five candidate surrogate markers (TGFB1, POSTN, VSIG4, CD44, and CXCL10) were validated in 40 patient samples, yielding Fig.21 Results are shown. This exemplary composite biomarker panel yielded an area under the curve (AUC) value of 0.83 (P=0.001). Combining IL6 with the composite biomarker panel resulted in an area under the curve (AUC) value of 0.98 (P<0.0001).

[0146] Thus, in one example, the surrogate markers may be, but are not limited to, one or more of the following: LUM, ANGPT1, IL1B, POSTN, TNC, MMP9, MMP2, TIMP3, DCN, VSIG4, CXCL5, CD36, ANGPT2, SERPINB5, IL6, CCL2, LEP, VCAM1, CCL8, ITGAM, THBS1, FN1, COL5A1, MXRA5, C3, CXCL10, TGFB1, CD44, TIM3, TNFSF13B, CEACAM1, LAMB1, IL10, IL5, IL22. In yet another example, the surrogate markers may be, but are not limited to, one or more of the following: IL6, IL10, CCL2, MMP9, ANGPT1, TGFB1, POSTN, VSIG4, CD44, and CXCL10. In another example, the surrogate markers may be, but are not limited to, one or more or all of the following: IL6, IL10, CCL2, MMP9, and ANGPT1. In another example, the surrogate markers may be, but are not limited to, one or more or all of the following: IL6, IL10, CCL2, and MMP9. In another example, one of the surrogate markers is IL6. In yet another example, the combination or group of surrogate markers used includes IL6.

[0147] Thus, in one example, the surrogate markers are, but are not limited to, IL6, IL10, CCL2, MMP9, ANGPT1, TGFB1, POSTN, VSIG4, CD44, and CXCL10. In another example, the surrogate markers are, but are not limited to, IL6, IL10, CCL2, MMP9, and ANGPT1. In yet another example, the surrogate markers are, but are not limited to, IL6, IL10, CCL2, and MMP9. In another example, the surrogate markers include IL6, IL10, CCL2, MMP9, and ANGPT1. In another example, the surrogate markers include at least IL6, IL10, CCL2, and MMP9. In another example, the surrogate markers are, but are not limited to, IL6, TGFB1, POSTN, VSIG4, CD44, and CXCL10. In yet another example, the surrogate markers are, but are not limited to, TGFB1, POSTN, VSIG4, CD44, and CXCL10.

[0148] The conclusion drawn from this group of patients is that acellular ascites (collected from a patient subgroup) activates other signaling pathways, thereby maintaining cancer cells. It is also noted that when the cell line model established is exposed to these acellular ascites, it seems that there is no acellular ascites with high PAI-1 levels associated with low-level STAT3 phosphorylation. This further indicates that PAI-1 activates STAT3. In case this statement is incorrect, people will observe ascites samples with high PAI-1 levels, and when cells are exposed to these acellular ascites, these samples will not activate STAT3 signal transmission. However, when cells are exposed to acellular ascites with high PAI-1 levels, these ascites samples do activate STAT3 signal transmission, and this fact supports and lays the foundation for the method disclosed herein. In summary, a subset or subgroup of patients with acellular ascites with high PAI-1 levels is identified, and it has been shown that high PAI-1 levels drive the STAT3 activation of cancer cells. Without being bound by theory, it is believed that if the paracrine STAT3 activation of cancer cells depends on the PAI-1 level in these ascites, this will lead to the oncogenic addiction phenomenon of a single upstream ligand. That is, when cells are considered to be highly susceptible to ligand inhibition of PAI-1 in ascites, the patient's acellular ascites has high PAI-1 and activated STAT3 signaling. Such ligand inhibition of PAI-1 can be performed by, for example, intraperitoneal instillation of a PAI-1 inhibitor.

[0149] Next, Colo-205, an established cell line model for the spread of colorectal peritoneal cancer, was systemically exposed to cell-free ascites fluid collected from patients, and the cells were then treated with TM5441, a PAI-1 inhibitor. Fig.11As shown, paracrine activation of Colo-205 results in different sensitivities to TM5441. Ascites collected from patients (it is believed that STAT3 activation in cancer cells of these patients depends on PAI-1 levels in cell-free ascites) are most susceptible to inhibition by TM5441, confirming the finding that cancer cells exposed to these cell-free ascites are addicted to PAI-1 oncogenicity. In other words, the data shown here indicate that, for example, when cells are exposed to cell-free ascites of the PAI-1 paracrine addiction (PPA) group, these cells rely on ascites to activate STAT3 signaling within them. When PAI-1 in cell-free ascites is blocked (ligand inhibition), STAT3 signaling within the cells is inhibited and the cells die. For example, STAT3 activation of cells exposed to cell-free ascites of the coactivator dominant (CAP) group is less dependent on PAI-1, but a response may still occur. At the same time, cells exposed to cell-free ascites of the alternative pathway activation (APA) group are not dependent on PAI-1 and do not activate STAT3, and are therefore not susceptible to PAI-1 inhibition.

[0150] Thus, in one example, a method for detecting or determining the susceptibility of a subject having peritoneal carcinomatosis to treatment with a PAI-1 inhibitor is disclosed, the method comprising determining the concentration of plasminogen activator inhibitor 1 (PAI-1) and determining the phosphorylation level of "signal transducer and activator of transcription-3" (STAT3) in a sample obtained from the subject; wherein the subject is susceptible to treatment if the subject exhibits (a) an increased PAI-1 concentration and an increased STAT3 phosphorylation, or (b) a decreased PAI-1 concentration and an increased STAT3 phosphorylation; wherein the increase and / or decrease is compared to the PAI-1 concentration and STAT3 phosphorylation level measured in a sample obtained from a reference group.

[0151] Validation in an in vivo mouse model using cell-free ascites that activates paracrine STAT3 signaling via PAI-1 confirmed sensitivity to intraperitoneal instillation of TM5441 ( Fig.14 , Fig.15 and Fig.17). Some examples of PAI-1 inhibitors have been shown to bind to s4A in PAI-1. Based on the 3D conformation of the s4A position, precursors of PAI-1 inhibitors were identified by computer simulation virtual screening (Izuhara et al., Arterioscler Thromb Vasc Biol. 2008; 28: 672-677). The docking model of these precursors to the s4A position of PAI-1 has been reported before (Izuhara et al., Journal of Cerebral Blood Flow & Metabolism (2010) 30, 904–912). In one example, the PAI-1 inhibitor binds to the s4A position in PAI-1. In another example, the PAI-1 inhibitor is an anticancer therapeutic agent or anticancer drug. In another example, as disclosed herein, administration of a PAI-1 inhibitor results in inhibition of PAI-1 activity compared to patients with the same disease.

[0152] In yet another example, the anticancer treatment or anticancer drug is, but is not limited to, a small molecule, a chemotherapeutic agent, a peptide, an antibody, a combination thereof, and a combination therapy. In another example, the anticancer drug is, but is not limited to, TM5441 (5-chloro-2-[[2-[2-[[3-(3-furanyl)phenyl]amino]-2-oxoethoxy]acetyl]amino]benzoic acid sodium salt; CAS 1190221-43-2), TM5007 (N,N-bis[3,3'-carboxy-4,4'-(2,2'-thienyl)-2,2'-thienyl]adipamide; CAS No. 342595-05-5), TM5275 (5-chloro-2-[[2-[2-[4-(diphenylmethyl)-1-piperazinyl]-2-oxoethoxy]acetyl]amino]-benzoic acid sodium salt; CAS 1103926-82-4), Tiplaxtinin (2-(1-benzyl-5-(4-(trifluoromethoxy)phenyl)-1H-indol-3-yl)oxoacetic acid; CAS 393105-53-8), ZK4044 and its derivatives. The example structures of various anticancer drugs are shown below:

[0153]

[0154]

[0155] In another example, the PAI-1 inhibitor is administered intraperitoneally.

[0156] In another example, a panel of markers for treating patients with peritoneal cancer spread with inhibitors of "plasminogen activator inhibitor 1" (PAI-1), or for detecting or determining the susceptibility of patients with peritoneal cancer spread to treatment with inhibitors of "plasminogen activator inhibitor 1" (PAI-1), wherein the panel of markers includes PAI-1, and one or more STAT3 phosphorylation or p-STAT3 surrogate markers. In one example, the use of a panel of markers in the methods referred to herein is disclosed, wherein the panel includes PAI-1 and one or more STAT3 phosphorylation surrogate markers, or PAI-1 and p-STAT3. In one example, the panel includes PAI-1 and one or more or all of IL6, IL10, CCL2, and MMP9. In another example, the panel includes PAI-1 and one or more or all of IL6, IL10, CCL2, MMP9, and ANGPT1. In yet another example, the group includes PAI-1 and one or more or all of TGFB1, POSTN, VSIG4, CD44, and CXCL10. In another example, the group includes PAI-1 and one or more or all of IL6, TGFB1, POSTN, VSIG4, CD44, and CXCL10.

[0157] In another example, a use of a PAI-1 inhibitor in the manufacture of a medicament for treating peritoneal cancer spread is disclosed, wherein the medicament is to be administered to a subject determined to belong to a patient group that is determined to be susceptible to treatment with PAI-1 inhibition. In another example, as disclosed herein, the susceptibility of the subject is determined by measuring PAI-1 concentration and STAT3 phosphorylation (p-STAT3) and comparing the measured values ​​with the cutoff values ​​disclosed herein.

[0158] In the context of the present invention, the term "administering" and variations of the term include "administer" and "administration", including contacting the compound or composition of the present invention with an organism or any relevant surface by any suitable means, applying, delivering or providing the compound or composition of the present invention to an organism or any relevant surface.

[0159] As used herein, the term "treat" refers to any and all uses of treating a disease state or symptoms, preventing disease development, or otherwise preventing, hindering, slowing or reversing the progression of disease or other adverse symptoms.

[0160] In the context of this specification, the terms "therapeutically effective amount" and "diagnostally effective amount" include within their meaning a sufficient but non-toxic amount of a compound or composition of the invention to provide the desired therapeutic or diagnostic effect. The exact amount required will vary from subject to subject, depending on factors such as the species being treated, the age and general condition of the subject, the severity of the condition being treated, the specific drug being administered, the mode of administration, and the like. Thus, an exact "effective amount" cannot be specifically specified. However, for any given situation, an appropriate "effective amount" can be determined by one of ordinary skill in the art using only routine experimentation.

[0161] In vitro validation with Tiplaxtinin (PAI-1 inhibitor) highlighted that inhibition of the PAI-1 Michaelis complex is a potential mechanism for how cells become addicted to PAI-1 oncogenesis. Treatment with Napabucasin (STAT3 inhibitor) highlighted that STAT3 inhibition alone is useless, as the Michaelis complex may activate other signaling cascades in addition to STAT3 signaling. Treatment with dual PI3K / mTOR inhibitors or mitomycin C (DNA damage inducer) highlighted the lack of efficacy of these drugs when cancer cells are exposed to ascites-driven paracrine activation ( Fig.12 ). Therefore, in one example, the concentration of PAI-1 is determined by measuring the concentration of PAI-1 to urokinase plasminogen activator (uPA) / tissue plasminogen activator (tPA) complex. In another example, the concentration of PAI-1 is determined by measuring the concentration of PAI-1 in acellular ascites. In another example, the concentration of PAI-1 is determined by measuring active and / or dormant (latent) forms of PAI-1 and / or with complexes including but not limited to urokinase plasminogen activator (uPA), tissue plasminogen activator (tPA), vitronectin and combinations thereof. In another example, the concentration of PAI-1 is determined by directly measuring or measuring the concentration of PAI-1 with one or more complexes. That is, PAI-1 does not necessarily form complexes with, such as urokinase plasminogen activator (uPA) / tissue plasminogen activator (tPA) or other proteins to produce downstream effects. In yet another example, the level of STAT3 phosphorylation is determined by measuring the level of p-STAT3 in an established cell line model of colorectal peritoneal carcinomatosis. In one example, the cell line model of colorectal peritoneal carcinomatosis is treated with cell-free ascites. In another example, the level of STAT3 phosphorylation is determined by measuring the level of p-STAT3 in a cell line model of colorectal peritoneal carcinomatosis treated with cell-free ascites.

[0162] In another example, a method for treating a subject having peritoneal carcinomatosis with a PAI-1 inhibitor is disclosed, the method comprising determining the concentration of plasminogen activator inhibitor 1 (PAI-1) and determining the phosphorylation level of "signal transducer and activator of transcription-3" (STAT3) in a sample obtained from the subject; administering the PAI 1 inhibitor to a subject who exhibits (a) an increase in PAI-1 concentration and an increase in STAT3 phosphorylation, or (b) a decrease in PAI-1 concentration and an increase in STAT3 phosphorylation; wherein the increase and / or decrease is compared to the PAI-1 and STAT3 phosphorylation levels measured in a sample obtained from a reference group.

[0163] In one example, the PAI-1 inhibitor is an anticancer drug.

[0164] In the methods disclosed herein, the control group refers to a group of subjects with peritoneal cancer spread. In another example, the control group is a group of patients who do not have peritoneal cancer spread but have benign tumors.

[0165] Comparison of the values ​​obtained from the experiments disclosed herein leads to the definition of reference values ​​disclosed herein (also referred to as critical values), which have been determined for each marker to be measured. The comparison between the measured value and the critical value is performed in a relative, qualitative manner (e.g., the concentration of one marker is greater than or less than the concentration of other markers) or in a quantitative manner (e.g., comparing X values ​​to Y values). Due to the nature of the measurement, the reference value or critical value may also include a buffer near a specific value. For example, a critical value with a 2% buffer means that if the critical value is 10, the buffer will result in a range of 9.8 to 10.2 that is allowed for the measurement. Depending on the background of the critical value, buffering may also be applied in only one direction. For example, if the critical value is at least 10, a 2% buffer will result in a value of 9.8 that is also acceptable. If the critical value is not greater than 10, a 2% buffer will result in a value of 10.2 that is also acceptable. In another example, the buffer may be 3%, 4%, or 5% of the critical value in question. In another example, the buffer may be 5% of the critical value in question. In another example, the buffer may be 2% of the critical value in question.

[0166] It is also contemplated within the scope of the present application that systems for detecting markers, substitutes or other disclosed herein are included. For example, such a detection system is capable of diagnosing or detecting or predicting the likelihood of a patient or subject suffering from peritoneal cancer spread. Therefore, the biomarkers as described herein may be incorporated into a diagnostic tool, a detection system, a diagnostic method, a prediction method, or a method for determining the likelihood of a patient suffering from peritoneal cancer spread. An exemplary detection system may include, for example, a receiving portion for receiving a sample from a patient suspected of suffering from peritoneal cancer spread, wherein the sample is suspected of containing one or more biomarkers disclosed herein, and a detection portion, which includes one or more substances capable of detecting one or more biomarkers disclosed herein. The sample used in the system may be, but is not limited to, a sample type disclosed herein.

[0167] To aid in the detection of the biomarkers disclosed herein, the detection system may include a substance that can bind or specifically bind to any biomarker disclosed herein. For example, such a substance may be a biospecific capture reagent, such as an antibody (or its antigen binding fragment) that recognizes a biomarker and / or its variant, an interactive fusion protein, an aptamer, or an affibody (which is an affinity protein of a non-immunoglobulin source based on a three-helix bundle protein domain). When used, the substance may, for example, be bound to a solid phase, wherein the biomarker may be detected by methods known in the art, such as mass spectrometry, or by eluting the biomarker from a biospecific capture reagent and detecting the eluted biomarker using methods known in the art, such as conventional matrix-assisted laser desorption / ionization (MALDI) or by surface-enhanced laser desorption / ionization (SELDI). For example, the detection system is included on a biochip, a test strip, or a microtiter plate.

[0168] Companion biomarkers indicative of treatment have been identified based on the concept of carcinogenic addiction in patients with peritoneal cancer dissemination. The identified biomarkers for activation of STAT3 and other signaling pathways are part of the coagulation cascade. In other words, activation of the coagulation cascade after surgery can stimulate the growth of cancer cells. It is also believed that excessive activation of the coagulation or fibrinolytic cascades is carcinogenic, and inhibition of both processes has shown potential therapeutic relevance. In addition, gene expression analysis of 2 colorectal peritoneal cancer dissemination cell lines after treatment with cell-free ascites showed that STAT3 signaling was activated. In addition, validation experiments on cell-free ascites (n=13) showed that STAT3 was most associated with colorectal peritoneal cancer dissemination. Clinically, colorectal cancer patients with activated STAT3 and epithelial-mesenchymal transition (EMT) in the TCGA database (n=345) have a poor prognosis. Interestingly, receptor tyrosine kinase arrays did not show JAK kinase phosphorylation, indicating atypical activation of STAT3 signaling. Cytokine arrays and mass spectrometry identified potential STAT3-activating ligands that are independent of JAK kinases, including POSTN, CD24, and CD44. Exposing cell lines to cell-free treatments showed sensitivity to inhibitors of upstream non-canonical STAT3 activators in both in vitro and in vivo settings.

[0169] The invention illustratively described herein may be suitably implemented in the absence of any one element or elements, one limitation or multiple limitations not specifically disclosed herein. Thus, for example, the terms "comprising", "including", "containing", etc. should be interpreted broadly and without limitation. In addition, the terms and expressions used herein have been used as descriptive and not restrictive terms, and the use of these terms and expressions is not intended to exclude any equivalent features or portions thereof of the features shown and described, but it should be recognized that various modifications are possible within the scope of the invention claimed. Therefore, it should be understood that although the present invention has been specifically disclosed through preferred embodiments and optional features, those skilled in the art may make modifications and changes to the invention embodied in the disclosed article, and these modifications and changes are considered to be within the scope of the present invention.

[0170] As used in this application, the singular forms "a", "an", and "the" include plural referents unless the context clearly dictates otherwise. For example, the term "genetic marker" includes a plurality of genetic markers, including mixtures and combinations thereof.

[0171] As used herein, the term "about," in the context of ingredient concentrations of a formulation, typically means ±5% of the stated value, more typically ±4% of the stated value, more typically ±3% of the stated value, more typically ±2% of the stated value, even more typically ±1% of the stated value, and even more typically ±0.5% of the stated value.

[0172] Throughout the disclosure, certain embodiments may be disclosed in a range format. It should be understood that the description of the range format is only for convenience and brevity, and should not be construed as a rigid limitation to the disclosed range. Therefore, it should be considered that the description of the range has specifically disclosed all possible subranges and each numerical value in the range. For example, it should be considered that the description of the range, for example, from 1 to 6, has a specifically disclosed subrange, for example, from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6, from 3 to 6, etc., and a single number in the range, for example, 1, 2, 3, 4, 5 and 6. No matter how wide the scope is, this applies.

[0173] Certain embodiments may also be described broadly and generally herein. Each narrower species and subgeneric grouping belonging to this general disclosure also forms a part of this disclosure. This includes general descriptions of the present embodiments with conditions or negative limitations that remove any subject matter from the genus, regardless of whether the removed material is specifically recited herein.

[0174] The invention has been described broadly and generically herein. Each narrower species and subgeneric grouping falling within that generic disclosure also forms a part of the invention. This includes the generic description of the invention with a proviso or negative limitation that removes any subject matter from that genus, regardless of whether the removed material is specifically recited herein.

[0175] Other embodiments are within the scope of the following claims and non-limiting examples. In addition, where features or aspects of the invention are described in terms of Markush groups, those skilled in the art will recognize that the invention is also thereby described in terms of any individual member or subgroup of members of the Markush group.

[0176] Experimental Section

[0177] Materials and methods

[0178] Patient recruitment, biospecimen collection, and processing

[0179] Patients treated for peritoneal carcinomatosis at the National Cancer Centre, Singapore were identified and recruited. Informed consent was obtained from all patients according to the study protocol approved by the SingHealth Central Institutional Review Board (CIRB Reference No.: 2015 / 2479 / F). All experiments were performed in accordance with relevant guidelines and regulations. Tumor specimens collected postoperatively were systematically divided into multiple blocks. One portion was immediately snap-frozen in liquid nitrogen and stored in a −80°C freezer, while another portion was fixed in formalin to construct formalin-fixed paraffin-embedded (FFPE) blocks. The remaining tissue was processed in the laboratory to establish primary cell lines and patient-derived xenografts. Ascitic fluid collected from the peritoneal cavity at the beginning of cytoreductive surgery (CRS) or during routine ascitic fluid extraction (puncture) was centrifuged at 2000 g for 10 minutes to separate cellular components from fluid components. The fluid components were filter-sterilized using a 0.22 μm filter to make them suitable for downstream experiments. The cellular components of ascites are used for downstream assays and to generate patient-derived ascites-dependent xenograft (PDADX) models.

[0180] Cell lines

[0181] Human metastatic colon cancer cell lines Colo-205 and SNU-C1 were purchased from the American Type Culture Collection and cultured in RPMI medium containing 10% fetal bovine serum (FBS), 1% penicillin-streptomycin, and 1% antifungal agents. Human normal peritoneal mesothelial cell lines LP9 / TERT and HM3 / TERT were purchased from the Brigham and Women's Hospital Cell Culture Center and cultured in M199 / M106 containing 15% iron-supplemented newborn calf serum, 0.4 μg / mL hydrocortisone, 10 ng / mL epidermal growth factor, 1% penicillin-streptomycin, and 1% antifungal agents. All cells were grown overnight in serum-free medium before the experiment.

[0182] Primary clinical endpoint

[0183] The primary clinical endpoint was overall survival (OS). OS was defined as the time from surgery to death, regardless of etiology. Kaplan-Meier curves were drawn to compare 5-year overall survival (OS) with or without ascites. The presence of ascites was defined as more than 50 mL of fluid in the peritoneal cavity. The log-rank test was used to determine the statistical significance of the curve comparison.

[0184] Proliferation assay

[0185] A total of 5000 cells / well were seeded in 96-well plates and grown in serum-free RPMI medium supplemented with different concentrations of acellular ascites. Cell proliferation was assessed using CellTitreGlo assay (Promega, Madison, US) on days 0 and 5. These experiments were performed in triplicate and repeated 3 times.

[0186] Cell migration assay

[0187] Colo-205 or SNU-C1 cells were serum starved for 24 hours and then treated with 3 different cell culture media (serum-free RPMI, RPMI supplemented with 10% fetal bovine serum (FBS), or serum-free medium supplemented with 5% cell-free ascites) for 24 hours. The pretreated cells were then seeded into a 6-well transwell migration assay at a density of 600,000 cells / well. The inner cavity of the transwell plate was filled with serum-free medium and the outer cavity was filled with 10% fetal bovine serum (FBS) medium. The cells were allowed to migrate for 24 hours. These experiments were performed in triplicate and repeated 3 times.

[0188] Cell sedimentation assay

[0189] A total of 70,000 cells / well of LP9 / TERT or HM3 / TERT were seeded in 12-well plates and grown to fusion in complete medium to form a feeder layer. Subsequently, the mesothelial feeder layer was serum-starved and then co-cultured with cancer cells. 35,000 cells / well of Colo-205 or SNU-C1 were inoculated into each well of 3 different culture media (serum-free RPMI, RPMI supplemented with 10% fetal bovine serum (FBS), or serum-free RPMI supplemented with 5% cell-free ascites) and incubated for 24 hours. Gently wash 5 times with complete medium to remove unattached cancer cells. Calculate the average number of cells precipitated in three areas of each well. The final number of cells settled was determined by the average of three determinations.

[0190] Gene expression analysis

[0191] To evaluate the signaling pathways that were upregulated after treatment with acellular ascites, Colo-205 and SNU-C1 cells were treated with 5% and 0.1% acellular ascites for 24 hours. To evaluate the signaling pathways affected by PAI-1 inhibition, Colo-205 cells were treated with acellular ascites or fetal bovine serum (FBS; control group) representing the PAI-1 paracrine addiction (PPA) group, the coactivator-dominated (CAP) group in the presence of DMSO vehicle or 27.25 μM TM5441 for 24 hours. Total RNA was isolated using the Qiagen miniprep kit (Qiagen, CA, USA) according to the manufacturer's instructions. Gene expression analysis was performed using the Affymetrix GeneChip Genome U133 Plus 2.0 microarray platform (Affymetrix, Santa Clara, CA) according to the manufacturer's protocol. The microarray data were uploaded to the free programming software R (R Foundation for Statistical Computing, Vienna, Austria) for processing and normalization. Gene set enrichment analysis (GSEA) was used to assess the enrichment of genes showing up- and down-regulation using the GSEA graphical user interface (GUI) software ( http: / / www.broadinstitute.org / gsea / ).

[0192] Western blotting

[0193] Colo-205 or SNU-C1 cells were starved overnight in serum-free medium and then treated with 5% of patient cell-free ascites for 24 hours. The next day, cells were harvested and lysed on ice for 1 hour in M-PER (Mammalian Protein Extraction Reagent, Thermo Scientific Inc.) supplemented with Pierce protease and phosphatase inhibitors (Thermo Scientific Inc.). Lysates were centrifuged at 14,000 g for 20 minutes at 4°C to obtain clear supernatants. Protein concentration was determined using Bradford protein assay reagent (Bio-Rad). The specific amount of protein was calculated (5 μg for STAT3 and actin; 25 μg for phospho-STAT3 (Tyr705) and phospho-STAT3 (Ser727); 10 μg for JAK1, JAK2, phospho-JAK1 (Tyr1022 / Tyr1023) and phospho-JAK2 (Tyr1007 / Tyr1008)) and aliquoted into 0.2 mL thin-walled PCR tubes. The lysate was denatured at 97°C for 5 minutes and separated on a 10% polyacrylamide gel in Tris / glycine / SDS running buffer (24.76 mM Tris, 191.83 mM glycine and 0.1% SDS) and then transferred to a 0.45 μm nitrocellulose membrane (Bio-Rad) in Tris / glycine / methanol transfer buffer (24.76 mM Tris, 191.83 mM glycine and 20% methanol). The membrane was blocked in 5% skim milk in 1x PBS containing 0.1% Tween 20 (PBST) for 1 hour at room temperature and then blotted with primary antibody for 1.5 hours.The dilutions of the primary antibodies were: 1:2,000STAT3 (Cell Signaling Technology; #4904); 1:1,000phospho-STAT3 (Tyr705) (Cell Signaling Technology; #9145); 1:1,000phospho-STAT3 (Ser727) (Cell Signaling Technology; #94994); 1:1,000JAK1 (Santa Cruz Biotechnology; sc-277); 1:1,000phospho-JAK1 (Tyr1022 / Tyr1023) (Santa Cruz Biotechnology; sc-16773); 1:1,000JAK2 (Santa Cruz Biotechnology; sc-294); 1:1,000phospho-JAK2 (Tyr1007 / Tyr1008) (Santa Cruz Biotechnology; sc-16566) and 1:100,000 β-actin (Sigma Aldrich; A1978). After washing 4 times in PBST (5 minutes each wash), the blot was incubated with anti-rabbit or anti-mouse horseradish peroxidase (HRP)-linked secondary antibodies (GE Healthcare Life Sciences; NA934 or NA931) at room temperature for 30 minutes. After washing 4 more times in PBST, Pierce SuperSignal West Dura Persistent Substrate (Thermo Scientific Inc.) was added to the blot and incubated at room temperature for 5 minutes. Excess liquid was allowed to drip off and the blot was wrapped in polyethylene for exposure to. Autoradiographic film (Santa Cruz Biotechnology, CA) was used to scan images using a GS-800TM calibrated densitometer (Bio-Rad).

[0194] Immunohistochemistry (IHC)

[0195] Formalin-fixed paraffin-embedded (FFPE) samples from cases of peritoneal carcinomatosis (PC) with matching primary tumors and metastases were identified and interrogated using chromogen-based immunohistochemistry (IHC) staining. All immunohistochemistry (IHC) staining was performed using Bond Max Autostainer (Leica Microsystems, Ltd, Milton Kynes, UK) as recommended by the manufacturer. The blocks of formalin-fixed paraffin-embedded (FFPE) were cut into 4 μm thick slices and mounted on slides. Rabbit anti-phosphorylated STAT3 (Tyr705) monoclonal antibody (#9145L, Cell Signalling Technology, Massachusetts, US, 1:50, pH9, 30 minutes) was optimized and used. The slides were evaluated by two independent scorers who were not aware of the clinical data in advance, and the staining results were determined based on the percentage of positive staining in the tumor epithelial component in each slide. Formalin-fixed paraffin-embedded (FFPE) samples were also collected from patient-derived ascites-dependent xenograft (PDADX) tumors and probed with antibodies against CK7, CK20, and CDX2 to confirm the histology and origin of the formed patient-derived ascites-dependent xenograft (PDADX) tumors. Rabbit anti-CK7 monoclonal antibody (#31-1167-00, RevMabBiosciences, California, USA, 1:200, pH9, 20 minutes), rabbit anti-CK20 polyclonal antibody (HPA024309, Sigma Aldrich, Missouri, USA, 1:200, pH9, 20 minutes) and rabbit anti-CDX2 monoclonal antibody (#12306, CellSignaling Technology, Massachusetts, USA, 1:100, pH9, 20 minutes) were optimized and used for immunohistochemistry (IHC) staining.

[0196] Mass spectrometry

[0197] Mass spectrometry analysis was performed on proteins isolated from the soluble and exosomal fractions of acellular ascites from a patient with benign serous cystadenofibroma (n=1) and malignant acellular ascites from a patient with colorectal peritoneal carcinomatosis (n=3). Briefly, liquid chromatography-tandem mass spectrometry (LC-MS / MS) analysis of digested peptides was performed using an Orbitrap Elite from Thermo Scientific Inc. and a QExactive mass spectrometer coupled to a Dionex UltiMate 3000 UHPLC system from Thermo Scientific Inc. (Bremen, Germany).

[0198] Cytokine analysis

[0199] Proteome Profiler Human Cytokine arrays (ARY022B, R&D Systems, Minneapolis, USA) consisting of 105 cytokines were used to analyze plasma (n=1), benign acellular ascites from a patient with benign serous cystadenofibroma (n=1), and malignant acellular ascites from patients with colorectal peritoneal carcinomatosis (n=4), gastric peritoneal carcinomatosis (n=1), and ovarian peritoneal carcinomatosis (n=1). The concentration of all proteins in the fluid was quantified using the Bradford protein assay (Biorad, Hercules, US), and equal amounts of protein were incubated with the membrane array according to the manufacturer's instructions.

[0200] Epithelial-mesenchymal transition (EMT) gene analysis

[0201] Epithelial-mesenchymal transition (EMT) gene analysis was performed using the RT2 Profiler PCR array (Qiagen, CA, USA) containing 84 EMT-related genes. RNA was extracted from Colo-205 and SNU-C1 cells grown for 24 hours in complete medium and 5% cell-free ascites using the RNeasy extraction kit (Qiagen). cDNA was synthesized using the RT2 first-chain kit (Qiagen), and reverse transcription polymerase chain reaction was performed using RT2 SYBR Green Mastermixes (Qiagen). The results were analyzed using Qiagen's Gene Globe data analysis center tool.

[0202] Phospho-receptor tyrosine kinase (RTK) analysis

[0203] Phosphorylation of receptor tyrosine kinases (RTKs) was analyzed using a human RTK phosphorylation antibody array (RayBiotech, GA, US), allowing the relative phosphorylation levels of 71 different human RTKs to be detected simultaneously in cell lysates. Proteins were extracted from cell lysates of Colo-205 and SNU-C1 treated with 5% cell-free ascites or 10% fetal bovine serum (FBS) for 24 hours. Total protein concentration was determined using the Bradford protein assay (Biorad, Hercules, US), and 40 μg of protein was used for phospho-RTK analysis according to the manufacturer's instructions.

[0204] The Cancer Genome Database (TCGA) Survival Analysis

[0205] The prognostic significance of regulating PAI-1, STAT3 and epithelial-mesenchymal transition (EMT) in the Cancer Genome Database (TCGA) colorectal adenocarcinoma (COADREAD) data set (n=345) was determined using Kaplan-Meier total survival (OS) curve analysis. Based on the critical value determined by recursive classification, patients were stratified into high (P+, ≥3.071) or low (P-, <3.071) PAI-1 expression, high (S+, ≥0.074) or low (S-, <0.074) STAT3 expression, and high (E+, ≥0.096) or low (E-, <0.096) epithelial-mesenchymal transition (EMT) expression. Due to the small sample size (n<20), four subtypes (PS-E+, P+SE-, P+S-E+, P+S+E-) were excluded from the analysis. Statistical significance was tested using the log-rank test.

[0206] Enzyme-linked immunosorbent assay (ELISA)

[0207] The concentrations of PAI-1 (DSE100), IL6 (D6050), IL10 (D1000B), CCL2 (DCP00), MMP9 (DMP900), ANGPT1 (DANG10), TGFB1 (DB100B), and CXCL10 (DIP100) in acellular ascites were quantified using the human Quantikine ELISA kit from R&D Systems. The concentrations of POSTN (DY3548B) and CD44 (DY7045-05) in acellular ascites were quantified using the human DuoSet ELISA kit from R&D Systems. The concentration of VSIG4 (ELH-VSIG4-1) in acellular ascites was quantified using the ELISA from RayBiotech. All samples were subjected to 2 technical replicates according to the manufacturer's instructions. Total STAT3 and phospho-STAT3 (Tyr705) were detected using ELISA (7305C and 7300C, Cell Signalling Technology, Massachusetts, USA). Protein was isolated from cell lysates of Colo-205 and SNU-C1 treated with 5% cell-free ascites for 24 hours. In all experiments, ELISA for total STAT3 and p-STAT3 (Y705) was performed using 25 μg of protein according to the manufacturer's instructions.

[0208] In vitro drug treatment

[0209] A total of 5,000 cells / well were seeded in 96-well plates and grown in serum-free RPMI medium supplemented with 5% acellular ascites or in complete medium for 24 hours, then treated with different concentrations of TM5441 (PAI-1 inhibitor), Tiplaxtinin (PAI-1 inhibitor), Napabucasin (STAT3 inhibitor), BEZ235 (PI3K / mTOR dual inhibitor) and mitomycin C (chemotherapeutic agent for hyperthermic intraperitoneal chemotherapy (HIPEC)) for 72 hours. Cell proliferation was assessed using CellTitreGlo assay (Promega, Madison, US). These experiments were performed three times and repeated at least 3 times.

[0210] Generation of Patient-Derived Ascites-Dependent Xenografts (PDADX)

[0211] All mouse experiments were performed in accordance with protocols approved by the SingHealth Institutional Animal Care and Use Committee (IACUC reference number: 2017 / SHS / 1295). Ascites collected from patients with peritoneal carcinomatosis were centrifuged at 2000g for 10 minutes to concentrate the cellular components and separate the liquid components. 1 mL of cell pellet was resuspended with 1 mL of ascites, and 400 μL of the mixture was implanted intraperitoneally into 6-week-old BALB / c nude mice (n=5 mice) to generate patient-derived ascites-dependent xenografts (PDADX) passage 0 (P0). For subsequent passages, patient-derived ascites-dependent xenografts (PDADX) tumors were cut into small pieces using a surgical blade and passed through an 18-G syringe needle. The cut tumors were resuspended with matched patient ascites at a 1:1 ratio and implanted intraperitoneally into 6-week-old BALB / c nude mice (n=10 mice).

[0212] Drug treatment of in vivo PC cell line mouse models

[0213] In order to determine the efficacy of PAI-1 inhibition in different susceptibility groups in vivo, 5×10 6Colo-205 cells were co-injected with acellular ascites or fetal bovine serum (FBS) representing the PAI-1 paracrine addiction (PPA) group and the coactivator dominant (CAP) group into the peritoneal cavity of 6-8 week-old BALB / c nude mice (female, n=5 mice / group), and 1.75mM TM5441 was administered intraperitoneally for treatment. Ascites and drug treatment were performed by intraperitoneal injection of 400μL 5% acellular ascites or 10% fetal bovine serum containing TM5441 every 3 days for 21 days. After 3 weeks, mice were sacrificed and tumor burden was quantified based on the modified peritoneal cancer diffusion index (PCI) score and expressed as the total peritoneal cancer diffusion index (PCI) score. The total peritoneal cancer diffusion index (PCI) score was calculated based on the sum of the scores for each area, ranging from 0 to 39.

[0214] To determine the optimal drug concentration and drug delivery method, a total of 16 6-8 week-old female BALB / c nude mice were selected for the experiment. Each mouse was injected intraperitoneally with 5×10 6 Colo-205 cells. The mice were divided into 4 groups and given the following treatments: (i) 5% acellular ascites containing 1% DMSO, (ii) 5% acellular ascites containing 1mM TM5441, (iii and iv) 5% acellular ascites containing 2mM TM5441. Treatment was performed by intraperitoneal injection (i-iii) and oral administration (iv) of 400μL of 5% acellular ascites containing DMSO vehicle / drug every 3 days for up to 21 days. After 3 weeks, the mice were sacrificed and the tumor burden was quantified based on the modified peritoneal cancer diffusion index (PCI) score and expressed as the total peritoneal cancer diffusion index (PCI) score. The total peritoneal cancer diffusion index (PCI) score was calculated based on the sum of the scores for each area, ranging from 0 to 39.

[0215] Drug therapy of patient-derived ascites-dependent xenografts (PDADX)

[0216] Acellular ascites and its cellular components from matched patients were used to generate patient-derived ascites-dependent xenografts (PDADX) to better recapitulate important features of patients with peritoneal carcinomatous spread. PAI-1 paracrine-addicted (PPA) patient-derived ascites-dependent xenografts (PDADX) tumors (100 mg) were implanted intraperitoneally into 16 female BALB / c nude mice, and coactivator-dominant (CAP) patient-derived ascites-dependent xenografts (PDADX) tumors (100 mg) were implanted intraperitoneally into 16 female BALB / c nude mice. Then PAI-1 paracrine addiction (PPA) patient-derived ascites-dependent xenografts (PDADX) and coactivator-dominant (CAP) patient-derived ascites-dependent xenografts (PDADX) were divided into 4 groups and given the following treatments: (i) 5% PAI-1 paracrine addiction (PPA) or coactivator-dominant (CAP) acellular ascites containing 1% DMSO, (ii) 5% PAI-1 paracrine addiction (PPA) or coactivator-dominant (CAP) acellular ascites containing 2mM TM5441, (iii) 10% fetal bovine serum (FBS) containing 1% DMSO, and (iv) 10% fetal bovine serum (FBS) containing 2mM TM5441. Treatment was performed by intraperitoneal administration every 3 days for 21 days. After the mice were sacrificed, tumor burden was quantified by weighing all visible tumors.

[0217] To determine whether susceptibility to PAI-1 inhibition is dependent on acellular ascites rather than tumor, acellular ascites from patients that are unresponsive to PAI-1 inhibition were treated with acellular ascites from patients that are paracrine-addicted (PPA). Briefly, coactivator-dominant (CAP) patient-derived ascites-dependent xenografts (PDADX) tumors (100 mg) were implanted intraperitoneally into 16 female BALB / c nude mice. Mice were divided into 4 groups and treated as follows: (i) 5% coactivator-dominated (CAP) acellular ascites containing 1% DMSO, (ii) 5% coactivator-dominated (CAP) acellular ascites containing 2mM TM5441, (iii) 5% PAI-1 paracrine-addicted (PPA) acellular ascites containing 1% DMSO, and (iv) 5% PAI-1 paracrine-addicted (PPA) acellular ascites containing 2mM Tm5441. Treatment was performed by intraperitoneal administration every 3 days for 21 days. After the mice were sacrificed, tumor burden was quantified by weighing all visible tumors.

[0218] p-STAT3 surrogate marker selection

[0219] STAT3-related genes were determined from the Kyoto Encyclopedia of Genes and Genomes (KEGG) database by searching for all genes involved in the known STAT3 pathway. Based on the extracellular genes listed in the NCBI Biosystems database and the proteins identified in the mass spectrometry analysis of acellular ascites, secretory STAT3-related proteins were selected. Two databases were used for transcriptomic comparison to prioritize putative STAT3 alternative markers. The first database was used to determine the genes that were positively correlated with STAT3 in the TCGACOADREAD data set. Genes were arranged from the most positively correlated to the least correlated with STAT3. The second database was derived from microarray analysis of cells treated with PAI-1 paracrine addiction (PPA) acellular ascites exposed to TM5441 to determine the genes that were downregulated and upregulated in PPA acellular ascites treated cells in response to PAI-1 inhibition. Upregulated genes are also worthy of attention because these genes may represent genes that participate in the rescue mechanism in response to PAI-1 inhibition. Similarly, genes are arranged from the most downregulated to the most upregulated. A systematic pairwise correlation analysis was then performed on the candidate genes by focusing on the top 1% and top 25% of genes that were positively correlated with STAT3 in database 1 and the top 1% and top 25% of genes that were most downregulated and most upregulated in database 2. Each group was prioritized for pairwise analysis and representative genes were selected from each group based on the literature review to be reduced to 35 genes. Based on the prioritization, the potential good correlation with p-STAT3 from the Luminex assay data, and the importance of the candidate genes in cancer pathogenesis from the literature review, 10 targets were selected for further evaluation using ELISA. The concentration of each surrogate marker in cell-free ascites was correlated with the p-STAT3 level of ascites-treated cells using Spearman correlation analysis.

Claims

1. Use of an inhibitor of "plasminogen activator inhibitor 1" (PAI-1) in the preparation of a medicament for use in a method for treating a subject suffering from metastatic peritoneal cancer, wherein the method comprises determining the concentration of PAI-1 and determining the phosphorylation level of "signal transducer and activator of transcription 3" (STAT3) in a sample obtained from the subject, wherein the sample is an ascites sample or a drainage fluid sample; administering a PAI-1 inhibitor to a subject who exhibits (a) increased PAI-1 concentration and increased STAT3 phosphorylation, or (b) decreased PAI-1 concentration and increased STAT3 phosphorylation; wherein the increase and / or decrease in PAI-1 concentration and STAT3 phosphorylation is compared to a reference value, wherein the reference value for PAI-1 concentration is about 20 ng / ml; and wherein the reference value for STAT3 phosphorylation is about 0.2 as measured by optical density reading at 450 nm.

2. Use according to claim 1, wherein the concentration of PAI-1 is determined by measuring the concentration of PAI-1 directly and / or in one or more complexes.

3. The use according to claim 1, wherein the level of STAT3 phosphorylation is determined by measuring the concentration of one or more surrogate markers, and / or by directly measuring the concentration of STAT3 phosphorylation. The use according to claim 1 , wherein the PAI-1 inhibitor is administered intraperitoneally.

5. The use according to claim 1, wherein the peritoneal cancer spread is selected from the group consisting of: colorectal peritoneal cancer spread, small intestinal peritoneal cancer spread, mesothelioma, endometrial peritoneal cancer spread, gastric peritoneal cancer spread, ovarian peritoneal cancer spread, appendiceal peritoneal cancer spread, pancreatic peritoneal cancer spread, urothelial carcinoma spread and pseudomyxoma peritonei (PMP).

6. The use according to claim 1, wherein the method is performed in a treatment setting selected from the group consisting of: a neoadjuvant treatment setting, an adjuvant treatment setting, a palliative treatment setting, and a preventive treatment setting.

7. The use according to claim 1, wherein the reference value is obtained from a reference group including subjects suffering from peritoneal carcinomatous spread.

8. The use according to claim 1, wherein administration of the PAI-1 inhibitor results in inhibition of PAI-1 activity compared to patients suffering from the same disease.

9. Use of a first agent for detecting "plasminogen activator inhibitor 1" (PAI-1) and a second agent for detecting the phosphorylation level of "signal transducer and activator of transcription 3" (STAT3) in the preparation of a kit for use in a method for detecting or determining the susceptibility of a subject with peritoneal carcinomatosis to treatment with an inhibitor of "plasminogen activator inhibitor 1" (PAI-1), wherein the method comprises determining the concentration of PAI-1 using the first agent and determining the phosphorylation level of STAT3 using the second agent in a sample obtained from the subject, wherein the sample is an ascites sample or a drainage fluid sample; wherein the subject is susceptible to the treatment if the subject exhibits (a) an increased concentration of PAI-1 and an increased phosphorylation of STAT3, or (b) a decreased concentration of PAI-1 and an increased phosphorylation of STAT3; wherein if the subject shows (c) a decrease in PAI-1 concentration and a decrease in STAT3 phosphorylation, the subject is considered not susceptible to treatment; wherein the increase and / or decrease in PAI-1 concentration and STAT3 phosphorylation levels are compared to a reference value, wherein the reference value for PAI-1 concentration is about 20 ng / ml; and wherein the reference value for STAT3 phosphorylation is about 0.2 as measured by an optical density reading at 450 nm.

10. The use according to claim 9, wherein the PAI-1 inhibitor is administered intraperitoneally.

11. The use according to claim 9, wherein the peritoneal cancer spread is selected from the group consisting of: colorectal peritoneal cancer spread, small intestinal peritoneal cancer spread, mesothelioma, endometrial peritoneal cancer spread, gastric peritoneal cancer spread, ovarian peritoneal cancer spread, appendiceal peritoneal cancer spread, pancreatic peritoneal cancer spread, urothelial carcinoma spread and pseudomyxoma peritonei (PMP).

12. The use of claim 9, wherein the method is performed in a treatment setting selected from the group consisting of: a neoadjuvant treatment setting, an adjuvant treatment setting, a palliative treatment setting, and a preventive treatment setting.

13. The use according to claim 9, wherein the reference value is obtained from a reference group including subjects suffering from peritoneal carcinomatous spread.

14. The use according to claim 9, wherein administration of the PAI-1 inhibitor results in inhibition of PAI-1 activity compared to patients suffering from the same disease.

15. The use according to claim 9, wherein the second agent is an agent for detecting one or more surrogate markers.

16. The use according to claim 3 or 15, wherein the surrogate marker is selected from the group consisting of IL6, IL10, CCL2, MMP9, ANGPT1, TGFB1, POSTN, VSIG4, CD44 and CXCL10.

17. The use according to claim 16, wherein the surrogate marker is selected from the group consisting of IL6, IL10, CCL2, MMP9 and ANGPT1.

18. The use according to claim 16, wherein the surrogate marker is selected from the group consisting of IL6, IL10, CCL2 and MMP9.

19. The use according to claim 16, wherein the surrogate markers include IL6, IL10, CCL2, MMP9 and ANGPT1; or wherein the surrogate markers include at least IL6, IL10, CCL2 and MMP9.

20. The use according to claim 16, wherein the surrogate marker is selected from the group consisting of IL6, TGFB1, POSTN, VSIG4, CD44 and CXCL10.

21. The use according to claim 16, wherein the surrogate marker is selected from the group consisting of: TGFB1, POSTN, VSIG4, CD44 and CXCL10.

22. The use according to claim 1 or 9, wherein the PAI-1 inhibitor is an anticancer drug or anticancer therapy.

23. The use according to claim 22, wherein the anticancer drug is selected from the group consisting of: (a) TM 5441, which is 5-chloro-2-[[2-[2-[[3-(3-furyl)phenyl]amino]-2-oxoethoxy]acetyl]amino]benzoic acid sodium salt, having CAS 1190221-43-2; (b) TM5007, which is N,N-bis[3,3'-carboxy-4,4'-(2,2'-thienyl)-2,2'-thienyl]adipamide, having CAS 342595-05-5; (c) TM5275, which is 5-chloro-2-[[2-[2-[4-(diphenylmethyl)-1-piperazinyl]-2-oxoethoxy]acetyl]amino]-benzoic acid sodium salt, having CAS 1103926-82-4; (d) tiplaxtinin, which is 2-(1-benzyl-5-(4-(trifluoromethoxy)phenyl)-1H-indol-3-yl)oxoacetic acid, having CAS 393105-53-8; (e) ZK4044; and (f) their derivatives.

24. Use of an agent for detecting a panel of markers in the preparation of a kit for use in the method defined in claim 1 or 9, wherein the panel comprises (a) PAI-1 and one or more surrogate markers of STAT3 phosphorylation or (b) PAI-1 and p-STAT3.

25. The use according to claim 24, wherein the panel comprises PAI-1 and one or more of IL6, IL10, CCL2 and MMP9.

26. The use according to claim 24, wherein the panel comprises PAI-1 and one or more of IL6, IL10, CCL2, MMP9 and ANGPT1.

27. The use according to claim 24, wherein the panel comprises PAI-1 and one or more of TGFB1, POSTN, VSIG4, CD44 and CXCL10.

28. The use according to claim 24, wherein the panel comprises PAI-1 and one or more of IL6, TGFB1, POSTN, VSIG4, CD44 and CXCL10.

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