CN110613850A

CN110613850A - Cyclin-dependent kinase 1 inhibitors and uses thereof

Info

Publication number: CN110613850A
Application number: CN201910441888.5A
Authority: CN
Inventors: 吴文铭; 彭俊雅; 陈澔; 刘路路; 黄丹; 李冬晶; 赵玉沛
Original assignee: Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Current assignee: Peking Union Medical College Hospital Chinese Academy of Medical Sciences
Priority date: 2019-05-24
Filing date: 2019-05-24
Publication date: 2019-12-27

Abstract

The present invention relates to a cyclin dependent kinase 1(CDK1) inhibitor and uses thereof, in particular to uses thereof in the prevention or treatment of pancreatic cancer or in the inhibition of pancreatic cancer cell proliferation. The present invention also relates to a method for screening an active ingredient for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation using cyclin-dependent kinase 1 as a target and the use of cyclin-dependent kinase 1 for screening the above active ingredient.

Description

Cyclin-dependent kinase 1 inhibitors and uses thereof

Technical Field

The invention belongs to the field of cancer treatment, and particularly relates to a cyclin dependent kinase 1(CDK1) inhibitor and application thereof in preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation. The present invention also relates to a method for screening an active ingredient for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation using cyclin-dependent kinase 1 as a target and the use of cyclin-dependent kinase 1 for screening the above active ingredient.

Background

Pancreatic cancer is called 'king of cancer', has difficult early diagnosis, poor treatment effect and high fatality rate, and has 9 th morbidity and 6 th mortality in Chinese malignant tumor. The treatment means for pancreatic cancer mainly include surgical treatment, radiotherapy and chemical drug therapy. However, only 15-20% of patients with pancreatic cancer can be treated by surgery, and the overall remission rate of radiotherapy and chemotherapy on pancreatic cancer is low. In addition, compared to other tumors such as breast cancer and lung cancer, a targeted drug effective against pancreatic cancer is lacking. In recent years, molecular targeted drugs have become hot spots in tumor therapy research, and targeted drugs against estrogen receptor and human epidermal growth factor receptor 2(HER2) have a significant cancer suppression effect in breast cancer and have been applied to the comprehensive treatment of clinical breast cancer patients. In conclusion, the low operation rate, the resistance to the traditional chemotherapy drugs and radiotherapy and the lack of effective targeted drugs are important reasons for the poor prognosis of pancreatic cancer. Therefore, researchers are required to have a more thorough understanding of the mechanisms of pancreatic cancer development and progression in order to find key targets for early diagnosis and treatment.

The batch sequencing technology is a key technology required in the process of searching key targets for early diagnosis and treatment of pancreatic cancer. The bulk sequencing technique generally involves grinding the entire tumor tissue and/or tissue adjacent to the tumor, extracting DNA or RNA, constructing a library using molecular biology techniques, and performing high-throughput sequencing. By comparing the sequencing results of the tumor tissue and the tissue beside the cancer, the difference information of the genome, the transcriptome, the epigenetic group and other layers is obtained and possible drug targets are prompted. It has been found that most pancreatic cancer patients have KRAS mutation (more than 90%) and inactivation of cancer suppressor genes such as TP53, SMAD4, CDKN2A (more than 50%) according to batch genomic studies (performed using Bulk DNA sequencing) techniques; batch transcriptome (performed by using batch DNA sequencing) technology) studies identified that signal pathways such as KRAS, TGF- β, Wnt, Notch, ROBO/SLIT, chromatin remodeling, and DNA repair are abnormally regulated in pancreatic cancer patients; in addition, epigenetic level studies have also found that some pancreatic cancer patients have inactivation of histone modifying enzymes, SWI/SNF regulated chromatin recombination complexes. Although traditional genome, transcriptome and epigenetic level researches identify key mutant genes and abnormal regulation signal pathways in the pancreatic cancer development process, these findings cannot be successfully transformed into clinical application mainly due to the limitation of batch technology, namely only hybrid information of multiple cell types in cancer tissues can be obtained, and the heterogeneity of tumors cannot be captured to define real treatment targets.

Pancreatic tissue is composed of a complex cellular component including pancreatic acinar cells, ductal cells, endocrine cells (alpha cells, beta cells, delta cells, etc.) and stromal components (fibroblasts, vascular endothelial cells, smooth muscle cells, astrocytes, and various immune cells, etc.). Research shows that after the pancreatic tissue becomes the pancreatic cancer tissue, the cell type is more complex, and the matrix component accounts for 70% of the pancreatic cancer tissue, and the tumor cells account for less than 30%. The differences between tumor cells and the diversity of stromal components contribute to the intratumoral heterogeneity of pancreatic cancer tissues. To target pancreatic cancer therapy, it is first necessary to resolve the malignant cell population that maintains its tumor characteristics. However, limited by batch sequencing technology, the malignant cell population of pancreatic cancer tissue is only known a little, and it is still controversial whether it originates from acinar cells or duct cells, and the state, function, interaction, evolution relationship, etc. of pancreatic cancer tissue are not known a little. In particular, the traditional batch sequencing technology measures the promiscuous information of various types of cells in cancer tissues, the heterogeneity of tumors cannot be captured, and abnormal regulatory pathway signals in malignant tumor cells can be covered by a large amount of promiscuous information, so that the real specific drug target is difficult to define.

In recent years, the revolution in sequencing technology, the rapid development of single cell sequencing technology, has allowed researchers to understand the vital information at various levels from the single cell level. STRT-Seq (reverse transcription sequencing of Single-Cell labeled), Smart-Seq and Smart-Seq2, Cell-Seq (Cell expression determined by linear amplification and sequencing, Cell expression by linear amplification and sequencing) and PMA-Seq (Phi29-mRNA amplification and sequencing ), Drop-Seq (10 Xgenomics based on The Single-Cell Gene expression detection scheme of The chromosome system, 10Xgenomics The chromosome Single Gene expression solution) Single-Cell transcriptome deep sequencing methods, as well as various bioinformatic analytic methods matched thereto, have been developed and show technical advantages in tumor heterogeneity, rare subpopulation identification, etc. Therefore, by virtue of the single cell sequencing technology, pancreatic cancer tumor cells can be known from higher precision, potential targets are provided for targeted therapy of pancreatic cancer, and small molecule inhibitors for inhibiting proliferation of pancreatic cancer cells are developed on the basis, so that a novel clinical strategy is provided for prevention and treatment of pancreatic cancer.

Disclosure of Invention

Technical problem

The technical problem to be solved by the invention is to search a potential target for targeted therapy of pancreatic cancer and develop a small molecule inhibitor for inhibiting pancreatic cancer cell proliferation on the basis of the potential target.

The strategy for solving the technical problems is to screen out key molecules of the abnormal signal path as potential drug targets according to the abnormal regulation signal path of malignant tumor cells in pancreatic cancer tissues, search targeted small molecule inhibitors aiming at the screened potential drug targets and verify the inhibition effect of the targeted small molecule inhibitors on the growth of pancreatic cancer cells.

Specifically, the technical problem is solved by the following solutions:

1. identification of malignant tumor cells in human pancreatic cancer tissue: analyzing the gene expression profile and the chromosome copy number variation of a single cell in the pancreatic cancer tissue by using a single-cell transcriptome sequencing technology to identify malignant tumor cells in the pancreatic cancer tissue;

2. identifying a malignant tumor cell proliferation subpopulation in human pancreatic cancer tissue that is involved in maintaining tumor characteristics;

3. identifying aberrant regulatory signaling pathways of malignant tumor cell proliferation subpopulations in human pancreatic cancer tissues: deep bioinformatics analysis is carried out aiming at malignant tumor cells, the differences of gene expression and function among the malignant tumor cells are explored, and a key signal path with specificity up-regulated is searched;

4. screening key molecules of malignant tumor cell abnormal signal pathways in human pancreatic cancer tissues as potential drug targets: screening out key variable molecules of the abnormal regulation signal path as potential drug targets according to the abnormal regulation signal path of the tumor cells;

5. aiming at the screened potential drug target, a targeted small molecule inhibitor is searched, and the inhibition effect of the targeted small molecule inhibitor on the proliferation of human pancreatic cancer cells is verified in vitro.

Solution to the problem

The inventor conducts single-cell transcriptome sequencing on 41986 cells of 24 preoperative and non-chemotherapeutic human pancreatic cancer tissues and 15544 cells of 11 control pancreatic tissues by an optimized human pancreatic tissue separation method, draws a cell map of a first large sample human pancreatic ductal adenocarcinoma (pancreatic cancer for short) (see figure 1) and identifies the types and proportions of all cells in the human pancreatic cancer tissues, thereby determining that the type II ductal cells are malignant tumor cell groups. Further research on the state and function of the malignant tumor cell population discovers that a cell subset with high proliferation property exists in the malignant tumor cell population, and the cell subset is named as a proliferation subset. A key signal pathway molecule specifically up-regulated in this proliferative subpopulation, Cyclin-dependent kinase 1 (abbreviated CDK1), is obtained by differential gene analysis methods, which participates in cell cycle regulation, transcriptional regulation and mRNA processing by binding to Cyclin B. It was further verified by immunohistochemistry that CDK1 is highly expressed in a malignant cell proliferation subpopulation in human pancreatic cancer tissue. Meanwhile, the inventors found that the proliferation of pancreatic cancer cell lines can be completely inhibited by using a CDK1 small-molecule inhibitor in vitro, which effectively indicates that CDK1 can be used as a potential target for treating pancreatic cancer, and the CDK1 small-molecule inhibitor can be used as a potential drug for treating pancreatic cancer.

The inventors have completed the present invention based on the above unexpected findings. Specifically, the present invention includes the following aspects:

1. a cyclin-dependent kinase 1 inhibitor for use in the prevention or treatment of pancreatic cancer or for inhibiting pancreatic cancer cell proliferation.

2. The cyclin-dependent kinase 1 inhibitor of aspect 1, wherein the cyclin-dependent kinase 1 inhibitor is selected from the group consisting of: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

3. The cyclin-dependent kinase 1 inhibitor according to aspect 1 or 2, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma, other types of ductal origin, acinar cell carcinoma, small gland carcinoma, or small cell carcinoma.

4. The cyclin-dependent kinase 1 inhibitor according to aspect 3, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, an adenosquamous carcinoma, a mucinous carcinoma, a mucoepidermoid carcinoma, a signet ring cell carcinoma, or a ciliated cell carcinoma.

5. A pharmaceutical composition for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation comprising a cyclin-dependent kinase 1 inhibitor and a pharmaceutically acceptable carrier.

6. The pharmaceutical composition of aspect 5, wherein the cyclin-dependent kinase 1 inhibitor is: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

7. The pharmaceutical composition according to aspect 5 or 6, wherein the cyclin-dependent kinase 1 inhibitor is the only active ingredient in the pharmaceutical composition.

8. The pharmaceutical composition according to aspect 5 or 6, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma, other types of ductal-derived carcinomas, acinar cell carcinomas, small gland carcinomas, or small cell carcinomas.

9. The pharmaceutical composition according to aspect 8, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, or ciliated cell carcinoma.

10. Use of a cyclin-dependent kinase 1 inhibitor for the prevention or treatment of pancreatic cancer or for inhibiting pancreatic cancer cell proliferation or for the preparation of a medicament for the prevention or treatment of pancreatic cancer or for inhibiting pancreatic cancer cell proliferation.

11. The use of aspect 10, wherein the cyclin-dependent kinase 1 inhibitor is: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

12. The use of aspect 10 or 11, wherein the cyclin-dependent kinase 1 inhibitor is the only active ingredient in the medicament.

13. The use of aspect 10 or 11, wherein the medicament further comprises a pharmaceutically acceptable carrier.

14. The use according to aspect 10 or 11, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma of the pancreas, other types of cancers of ductal origin, acinar cell carcinoma, small gland carcinoma or small cell carcinoma.

15. The use according to aspect 14, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, or ciliated cell carcinoma.

16. A method for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation, the method comprising administering to a subject in need thereof a cyclin-dependent kinase 1 inhibitor.

17. The method of aspect 16, wherein the cyclin-dependent kinase 1 inhibitor is: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

18. The method according to aspect 16 or 17, wherein the cyclin-dependent kinase 1 inhibitor is formulated in the form of a pharmaceutical composition together with a pharmaceutically acceptable carrier.

19. The method of aspect 16 or 17, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma of the pancreas, other types of cancers of ductal origin, acinar cell carcinoma, small gland carcinoma, or small cell carcinoma.

20. The method of aspect 19, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, or ciliated cell carcinoma.

21. A method of screening for an active ingredient for preventing or treating pancreatic cancer or inhibiting proliferation of pancreatic cancer cells, the method comprising the steps of:

1) contacting a subject with cyclin-dependent kinase 1;

2) measuring the inhibitory effect of the subject on cyclin-dependent kinase 1, wherein a subject showing an inhibitory effect on cyclin-dependent kinase 1 is indicative of an active ingredient for the prevention or treatment of pancreatic cancer or the inhibition of pancreatic cancer cell proliferation.

22. A method of screening for an active ingredient for preventing or treating pancreatic cancer or inhibiting proliferation of pancreatic cancer cells, the method comprising the steps of:

1) testing the expression level of cyclin-dependent kinase 1 in the presence or absence of the test agent;

2) comparing the expression level of cyclin-dependent kinase 1 in the presence or absence of the test agent to determine whether the test agent causes a change in the expression level of cyclin-dependent kinase 1;

3) screening for a test substance that decreases the expression level of cyclin-dependent kinase 1, which is indicative of an active ingredient for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation.

23. The method of aspect 21 or 22, wherein the cyclin-dependent kinase 1 is cyclin-dependent kinase 1 in an in vitro, ex vivo, or in vivo environment.

24. Use of cyclin-dependent kinase 1 for screening active ingredients for preventing or treating pancreatic cancer or inhibiting proliferation of pancreatic cancer cells or for preparing a kit for screening active ingredients for preventing or treating pancreatic cancer or inhibiting proliferation of pancreatic cancer cells.

25. A kit for screening an active ingredient for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation, the kit comprising cyclin-dependent kinase 1 and instructions describing the screening step.

The above aspects represent preferred embodiments of the present invention, but the present invention is not limited to the above preferred embodiments. In addition, the various features of the above embodiments of the invention may be combined with each other to form one or more new solutions, which also fall within the scope of the invention, as long as such new solutions are technically feasible.

Advantageous effects of the invention

The invention has the following beneficial effects:

1. by utilizing a single cell sequencing technology, a gene expression profile of a single cell in a pancreatic cancer tissue is obtained, a malignant cell group, namely II-type ductal cells, in the human pancreatic cancer tissue is identified, and a subgroup of cells related to cell proliferation is found in the malignant cell group;

2. cyclic-dependent kinase 1 (abbreviated CDK1) was unexpectedly found as a target for drug therapy of pancreatic cancer by analyzing its specific up-regulated expression of signaling pathways against a subpopulation of malignant cells associated with proliferation, and small molecule inhibitors against CDK1 were unexpectedly found as potential drugs for preventing or treating pancreatic cancer or inhibiting pancreatic cancer cell proliferation.

To date, no report has been made of CDK1 as a target for pancreatic cancer therapy and CDK1 inhibitors for preventing or treating pancreatic cancer, particularly inhibiting pancreatic cancer progression by acting on CDK 1. Therefore, the discovery of the invention is still the first time in the field, which provides a novel treatment strategy for overcoming the worldwide technical problem of pancreatic cancer and brings new hopes for the remission and rehabilitation of pancreatic cancer patients.

Detailed Description

"cyclin-dependent kinases (CDKs)" are a class of serine/threonine protein kinases, members of the protein kinase family. CDKs play a role in various stages of the cell cycle, enabling cells to proliferate in an orderly fashion. CDKs rely on binding to cyclins (cyclins) to perform key functions in the orderly progression of the cell cycle, and are important factors in cell cycle regulation. CDKs can bind to cyclins to form heterodimers, where CDKs are catalytic subunits and cyclins are regulatory subunits. The ordered progress of each phase of the cell cycle is promoted through the periodic expression and degradation of the cyclin, so that the change of cell growth and proliferation is brought. The presence of at least 13 CDKs, CDK1-13, has been identified in humans. Among them, Cyclin-dependent kinase 1(CDK1) is essential for the survival of cells. CDK1 plays a critical role in many biological processes in organisms, such as regulation of the cell cycle, activation of cell cycle checkpoints, DNA damage repair, and the like.

"cyclin-dependent kinase 1 inhibitor" generally refers to a substance having inhibitory activity against "cyclin-dependent kinase 1(CDK 1)". The person skilled in the art can test whether a substance has an inhibitory activity on cyclin-dependent kinase 1 by routine experimentation. Exemplary CDK1 inhibitors useful in the present invention include Dinaciclib (SCH727965), miciciclib (PHA-848125), AZD5438, and frataxidol (Flavopiridol, also known as Alvocidib). It should be understood that these exemplary CDK1 inhibitors are presented herein merely to illustrate the features and advantages of the present invention and do not constitute any limitations of the claims of the present invention. Those skilled in the art will recognize that other compounds having CDK1 inhibitory activity not specifically recited herein, such as PHA-793887, SNS-032(BMS-387032), ZK-304709, AT-7519, and the like, may also be used to achieve the objects of the present invention.

Dinaciclib (SCH727965, (2S) -1- [ 3-ethyl-7- [ [ (1-oxo-3-pyridinyl) methyl ] amino ] pyrazolo [1,5-a ] pyrimidin-5-yl ] -2-piperidineethanol) is a novel potent CDK1 inhibitor. Clinical trials for the treatment of acute myeloid leukemia (NCT03484520, phase I clinical), advanced/triple negative breast cancer (NCT 016753, phase I clinical) using Dinaciclib have been currently conducted.

Milciclib (PHA-848125, 4, 5-dihydro-N, 1,4, 4-tetramethyl-8- [ [4- (4-methyl-1-piperazinyl) phenyl ] amino ] -1H-pyrazolo [4,3-H ] quinazoline-3-carboxamide) is a potent, ATP-competitive CDK1 inhibitor. Clinical trials for treating liver cancer (NCT03109886, phase II) using micciclib are currently in progress.

AZD5438(4- (2-methyl-3-propan-2-ylimidazol-4-yl) -N- (4-methylsulfonylphenyl) pyrimidin-2-amine) is a potent CDK1 inhibitor. The clinical phase I trial that had been previously conducted to treat tumors with AZD5438 (Neoplasms) had been terminated. However, in vitro tests found that AZD5438 exhibits a broad spectrum of antiproliferative activity against lung, colorectal, breast, prostate and hematological tumors, and in vivo oral treatment with AZD5438 produced a statistically significant inhibition of growth of human tumor xenografts derived from breast, colon, lung, prostate and ovarian cancers.

Fraveline (i.e., alvocidib, 2- (2-chlorophenyl) -5, 7-dihydroxy-8- [ (3S,4R) -3-hydroxy-1-methylpiperidin-4-yl ] chromen-4-one) competitively inhibits CDK1 with ATP. Clinical trials are currently being conducted for the treatment of acute myeloid leukemia (NCT03441555, NCT 0356560, phase I of clinics) and myelodysplastic syndrome (NCT03593915, phase II of clinics) using frataxis.

The chemical formula and structural formula of the above 4 small molecule CDK1 inhibitors are listed in table 1.

Table 1 exemplary CDK1 inhibitors

"pancreatic cancer" refers to a malignancy that is primary or secondary to the pancreas, with the vast majority of pancreatic cancers being ductal adenocarcinomas that originate in the epithelium of the gland. In recent years, the incidence and mortality of pancreatic cancer has increased dramatically. Pancreatic cancer is highly malignant and difficult to diagnose and treat, and is one of the worst prognosis malignancies. The types of pancreatic cancer are mainly, depending on the pathological type of pancreatic cancer: 1. ductal adenocarcinoma, which accounts for 80% -90% of pancreatic cancer, is mainly composed of glands of duct-like structures differentiated to different degrees; 2. other types of cancers of ductal origin include: pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, ciliated cell carcinoma; 3. acinar cell carcinoma, accounting for only about 1%, with tumor cells in the shape of polygons, circles or short columns; 4. small gland cancer, a rare type of pancreatic cancer; 5. small cell carcinoma, small cell carcinoma of the pancreas, is morphologically similar to small cell carcinoma of the lung, accounting for approximately 1% -3% of pancreatic cancers.

By "pharmaceutically acceptable salt" of a compound is meant a salt of the compound that is suitable for administration to a subject for prophylactic or therapeutic purposes without causing unacceptable toxicity to the subject. Pharmaceutically acceptable salts include salts with inorganic acids (for example, salts with hydrochloric acid, hydrobromic acid, hydroiodic acid, nitric acid, sulfuric acid and phosphoric acid), salts with organic acids (for example, salts with formic acid, acetic acid, propionic acid, trifluoroacetic acid, fumaric acid, maleic acid, tartaric acid, citric acid, succinic acid, lactic acid, malic acid, methanesulfonic acid, benzenesulfonic acid and p-toluenesulfonic acid), salts with inorganic bases (for example, alkali metal salts such as sodium salt and potassium salt, alkaline earth metal salts such as calcium salt and magnesium salt, and aluminum salt and ammonium salt), salts with organic bases (for example, salts with trimethylamine, triethylamine, pyridine, picoline, ethanolamine, diethanolamine, triethanolamine, dicyclohexylamine and N, N' -dibenzylethylenediamine), and salts with basic or acidic amino acids (for example, salts with basic amino acids such as arginine, lysine and ornithine, or salts with acidic amino acids such as glutamic acid and aspartic acid). The pharmaceutically acceptable salts formed by the present invention of the cyclin-dependent kinase 1 inhibitor in free compound form are not limited in kind, as long as they retain inhibitory activity against cyclin-dependent kinase 1.

"stereoisomers" means compounds having the same composition and molecular weight but different physical and/or chemical properties due to different arrangement of atoms of the compounds in space. Stereoisomers include enantiomers (stereoisomers that are non-superimposable mirror images of each other), diastereomers (stereoisomers that are not mirror images of each other), racemates (mixtures containing equal amounts of the individual enantiomeric forms with opposite chirality). The present invention is not limited to the kind of stereoisomer of the cyclin-dependent kinase 1 inhibitor, as long as it retains inhibitory activity against cyclin-dependent kinase 1.

"solvate" means a solvent addition form of a compound containing a stoichiometric or non-stoichiometric amount of solvent. Certain compounds or salts thereof have a tendency to trap a fixed molar ratio of solvent molecules in the crystalline solid state, thereby forming solvates. If the solvent is water, the solvate formed is a hydrate; if the solvent is an alcohol, the solvate formed is an alcoholate. The present invention is not limited in the kind of solvate of the cyclin-dependent kinase 1 inhibitor as long as it retains inhibitory activity against cyclin-dependent kinase 1.

By "pharmaceutically acceptable carrier" is meant a carrier suitable for formulation with an active ingredient for prophylactic or therapeutic purposes into a pharmaceutical composition for administration to a subject without causing unacceptable toxicity to the subject. For the preparation of the pharmaceutical composition, any pharmaceutically acceptable carrier commonly used in the art may be employed. For example, to prepare solid dosage forms for oral administration, solid carriers known in the art may be used. Examples of the solid carrier are fillers such as glucose, microcrystalline cellulose, lactose, starch, powdered sugar, dextrin, mannitol and the like; binders such as methylcellulose, hypromellose, carboxymethylcellulose, microcrystalline cellulose, povidone, starch slurry, mucilage, and the like; disintegrants such as croscarmellose sodium, sodium carboxymethyl starch, crospovidone, hydroxypropyl starch, etc.; lubricants such as magnesium stearate, calcium stearate, talc, and the like. In addition, coloring agents, flavoring agents, sweetening agents, preservatives and the like may also be used as long as they are compatible with the ingredients used. The pharmaceutical composition of the present invention can be prepared in the form of, for example, tablets, capsules, powders, granules, pills, etc., using the above-mentioned solid carriers.

For preparing liquid dosage forms for oral administration, liquid carriers known in the art may be used. Examples of liquid carriers are water, ethanol, propylene glycol, glycerol, dimethyl sulfoxide, polyethylene glycol, and fatty oils, liquid paraffin, ethyl oleate, isopropyl myristate, and the like. The pharmaceutical composition of the present invention can be prepared in the form of, for example, a solution, a suspension, an emulsion, a syrup, or an elixir using the above-mentioned liquid carrier.

For preparing a dosage form for parenteral administration, sterile carriers known in the art may be used. Such as water for injection, oil for injection such as vegetable oil, e.g., sesame oil, soybean oil, peanut oil, castor oil, tea oil, other solvents for injection such as ethanol, propylene glycol, glycerin, polyethylene glycol, benzyl benzoate, ethyl oleate, dimethylacetamide, and the like. In addition, additives such as solubilizers, wetting agents, emulsifiers, suspending agents, buffers, antioxidants, chelating agents, and the like may be used in order to facilitate the preparation of injectable dosage forms. For sterile powders for injection, fillers and preservatives such as lactose, sucrose, maltose, mannitol, glycine, human serum albumin and the like can also be used.

The pharmaceutical compositions of the present invention may be administered by any suitable route of administration, for example, oral, parenteral (including intravenous, intradermal, subcutaneous, intramuscular, intraperitoneal and the like), topical (including sublingual), rectal, vaginal routes and the like. Preferably, the pharmaceutical composition according to the invention is administered by the oral route. It will be appreciated that the preferred route of administration will depend upon the age, sex, weight, general medical condition of the subject to be treated, the nature and severity of the condition to be treated, the potency of the active ingredient employed and the like.

"prevention" means preventing the appearance of pancreatic cancer or the recurrence of pancreatic cancer that has disappeared in a subject at risk of developing the disease. By "treatment" is meant controlling, reducing or alleviating the pathological progression of pancreatic cancer and prolonging the survival of the diseased subject. By "inhibiting pancreatic cancer cell proliferation" is meant preventing or slowing proliferation of pancreatic cancer cells.

The present invention does not have any limitation on the species of the subject having pancreatic cancer or the subject at risk of having pancreatic cancer, and preferably human and non-human mammals such as mice, rats, guinea pigs, cats, dogs, cows, horses, sheep, pigs, monkeys, etc., more preferably human.

In the process of completing the invention, the inventor utilizes a single-cell RNA sequencing technology to draw a pancreatic cancer tissue cell gene expression map, further screens pancreatic cancer drug treatment target genes, and verifies the effectiveness of the target gene treatment through in vitro inhibition experiments. This includes the following work:

1. pancreatic cancer tissue unicell RNA sequencing

The obtained pancreatic cancer tissues are dissociated and prepared into Single Cell suspensions by an enzyme digestion mode, and a cDNA library of each Single Cell in The pancreatic cancer tissues is constructed and sequenced by a Single Cell Gene Expression detection scheme (10X genomic Single Cell Expression Solution) method based on The chromosome system of 10X genomic.

2. Pancreatic cancer tissue cell population identification

For principal Component Analysis (Principle Component Analysis) of genes differentially expressed in each pancreatic cancer tissue cell of each patient, pancreatic cancer tissue cells were divided into 10-20 cell populations (see FIG. 1), and genes differentially expressed in each cell population compared to the other cell populations were obtained. Determining the cell types of each cell group by comparing the expression of genes which are known to be expressed by various marker cells in each cell group, such as identifying a cell group with high expression of AMBP gene as type I ductal cells by the AMBP gene which is known to be expressed in ductal cells; identifying a group of cells with high KRT19 gene expression as type II ductal cells by the KRT19 gene expressed in another ductal cell; identifying the cell group with high expression of PRSS1 gene as acinar cells through the PRSS1 gene which should be expressed in the acinar cells; identifying the cell group with high expression of the CHGB gene as the endocrine cell through the CHGB gene which should be expressed in the endocrine cell; identifying the cell group with high expression of CDH5 gene as endothelial cells through CDH5 gene which should be expressed in the endothelial cells; identifying the cell group with high expression of the LUM gene as the fibroblast by the LUM gene which should be expressed in the fibroblast; identifying the cell group with high RGS5 gene expression as astrocytes through the RGS5 gene which should be expressed in the astrocytes; identifying the cell group with high expression of AIF1 gene as macrophage by AIF1 gene which should be expressed in macrophage; identifying the cell group with high expression of CD3D gene as T lymphocyte through CD3D gene which should be expressed in the T lymphocyte; and the cell group highly expressing the MS4a1 gene was identified as B lymphocytes by the MS4a1 gene that should be expressed in the B lymphocytes (see fig. 2).

3. Pancreatic cancer tissue malignant cell identification

Pancreatic cancer is a malignant tumor derived from parenchymal cells of pancreatic tissue, including ductal cells, acinar cells, and endocrine cells, and thus may be a previously identified group of ductal cells type I, ductal cells type II, acinar cells, or endocrine cells. And because pancreatic cancer is an epithelial malignant tumor in histology, referring to the reported method for defining malignant cell group by single cell sequencing research of epithelial malignant tumor, the malignant cells of pancreatic cancer tissue are judged according to the following criteria: has epithelial properties; chromosomal copy number variation; and expressing the tumor-associated signature gene.

First, EPCAM genes were used as the genes to be expressed specifically and highly in epithelial cells, and their expression in ductal cell, acinar cell and endocrine cell groups was examined (see FIG. 3), and it was found that EPCAM genes were expressed highly in ductal cell, type I, acinar cell and endocrine cell groups, and were expressed less in endocrine cell subsets, and thus, it was excluded that endocrine cells were malignant cells of pancreatic cancer tissue.

Next, according to the reported algorithm (Patel, A.P. et al Single-cell RNA-seq high programs internal biology in primary globosiform).Science344, 1396-1401 (2014)) the level of chromosomal Copy Number Variation (CNV) was calculated for the ductal and acinar cell populations (see figure 4), with CNV levels for the type II ductal and acinar cell populations being much higher than those for the type I ductal and acinar cell populations.

Finally, functional enrichment analysis was performed on the genes differentially expressed in the type I ductal cell class and the type II ductal cell class (see fig. 5), and it was found that the function of the gene specifically highly expressed in the type I ductal cell class was associated with normal pancreatic function, and the function of the gene specifically highly expressed in the type II ductal cell class was associated with tumor progression. In conclusion, it can be preliminarily judged from the bioinformatics perspective that the type II ductal cells are malignant cells of pancreatic cancer tissues.

MUC1 and FXYD3 genes which are specifically and highly expressed in the II ductal cell group are selected, corresponding commercial protein antibodies are purchased, and the pancreatic ductal cell nucleus marked by the MUC1 and FXYD3 protein antibodies in pancreatic cancer tissues has high heterotypic property through an immunohistochemical staining method (see figure 6).

4. Identification of malignant proliferative subsets maintaining tumor characteristics

The type II ductal cell group identified as malignant cells can be further divided into 7 subgroups by using nonlinear dimensionality reduction (tSNE) analysis (see figure 7), specific expression genes of each subgroup are obtained by differential gene expression analysis, functional enrichment analysis is carried out on the specific expression genes of each subgroup (see figure 8), and the main expression genes of subgroups 1, 2 and 3 are related to detoxification, epithelial cell differentiation and translation. Subgroup 5 was associated with neutrophil activation, suggesting a possible association with the immune response. Subgroups 4 and 6 expressed genes were primarily associated with cell migration. Subgroup 6 was shown to be associated with hypoxic stress, the IL17 signaling pathway, suggesting its possible role in tumor metastasis. In addition, subgroup 7 highly expressed genes were associated with proliferation, suggesting that it is involved in the maintenance of tumor properties.

5. Proliferating cell subset analysis and drug target screening

The interaction (activation or inhibition) between highly expressed proliferation-related genes in subgroup 7 was analyzed using an Innovative Pathway Analysis (IPA) (see fig. 9, 10), and CDK1 gene was found to be located at the center of the gene interaction network.

The inventors searched and purchased the small molecule inhibitors Dinaciclib, miciciclib, AZD5438 and frataxin against the CDK1 gene at seleck chinese official website (https:// www.selleck.cn) using "CDK 1" as a keyword. Cell proliferation experiments with an in vitro Cell Counting Kit 8(Cell Counting Kit 8, CCK8) showed that Dinaciclib (10nM), miciciclib (10 μ M), AZD5438(5 μ M) and fravision (500nM) all significantly inhibited the proliferation of the pancreatic cancer MIAPaCa-2 Cell line (see fig. 11). The results indicate that CDK1 can be used as a target for pancreatic cancer drug therapy, and inhibitors such as Dinaciclib, Milciclib, AZD5438 and Fralazurity have the potential to be applied to pancreatic cancer drug therapy.

Drawings

FIG. 1 shows the clustering chart of pancreatic cancer tissue cells obtained by principal component analysis of single-cell RNA sequencing data of 24 pancreatic cancer tissue specimens, showing the cell types, the number of each cell type and the percentage of each cell type.

FIG. 2 shows the high-expression genes of various cell populations obtained by principal component analysis of single-cell RNA sequencing data of 24 pancreatic cancer tissue specimens. The meanings of the English abbreviations in FIG. 2 are as follows: AMBP: alpha-1-microglobulin gene; KRT 19: a keratin 19 gene; PRSS 1: serine protease 1 gene; CHGB: chromogranin B gene; CDH 5: cadherin 5 gene; LUM: a luminal protein gene; RGS 5: protein signal regulatory factor 5 gene; AIF 1: allograft inflammatory factor 1 gene; CD 3D: leukocyte differentiation antigen 3D gene; and MS4a 1: human transmembrane 4-domain subfamily a member 1 gene.

FIG. 3 shows the expression of the anti-epithelial cell adhesion molecule (EPCAM) gene in various cell populations.

FIG. 4 shows the Copy Number Variation (CNV) levels of various cell populations in 7 pancreatic cancer tissue specimens and 1 normal pancreatic tissue specimen.

FIG. 5 shows a differential gene function enrichment analysis of type I ductal cells and type II ductal cells. Functional enrichment analysis is carried out on specific high-expression genes in the type I ductal cell group and the type II ductal cell group respectively, and the cell functions in which the genes are involved are summarized.

FIG. 6 shows immunohistochemical staining of proteins encoded by two type II ductal cell population-specific high expression genes in pancreatic cancer tissue sections and normal pancreatic tissue sections. The meanings of the English abbreviations in FIG. 6 are: MUC 1: a mucin 1 gene; and FXYD 3: the sodium potassium pump motor regulatory protein domain comprises an ion transporter 3 gene.

FIG. 7 shows clustering of pancreatic cancer malignant cell subpopulations. After principal component analysis of the type II ductal cell population identified as malignant cells, it can be divided into 7 cell subsets.

FIG. 8 shows a functional enrichment analysis of pancreatic cancer malignant cell subpopulations. And (3) respectively carrying out function enrichment analysis on specific high-expression genes in 7 malignant cell subsets to summarize the cell functions in which the genes participate.

FIG. 9 shows an analysis diagram of interaction network of highly expressed proliferation-related genes in cells of malignant cell subset 7. And (3) carrying out gene interaction network analysis on the cell high-expression proliferation related genes of the malignant cell subgroup 7, and displaying the mutual activation/inhibition relationship among the proliferation related genes. The meanings of the English abbreviations in FIG. 9 are: CDK 1: cyclin-dependent kinase 1 gene; PLK 1: polo-like kinase 1 gene; AURKA: aurora (Aurora) kinase a gene; CCNA 2: a cyclin a2 gene; CCNB 2: cyclin B2 gene; HMMR: a hyaluronic acid-mediated cell movement receptor gene; UBE 2C: ubiquitin conjugating enzyme E2C gene; CCNB 1: cyclin B1 gene; TPX 2: kinesin family member 15L target protein gene; MAD2L 1: mitotic block defect 2-like protein 1 gene; CDC 20: a cell-division cyclin 20 gene; CKAP 2: cytoskeleton-associated protein 2 gene; PRC 1: polycomb inhibitory complex 1 gene; BIRC 5: the baculovirus apoptosis inhibitor repeat domain comprises a protein 5 gene; CDKN 3: cyclin-dependent kinase inhibitor 3 gene; PTTG 1: pituitary tumor transformation gene 1; and DLGAP 5: discs big homolog related protein 5 gene.

FIG. 10 shows the expression levels of cyclin-dependent kinase 1(CDK1) gene in 7 malignant cell subsets.

Figure 11 shows the effect of CDK1 inhibitors on inhibiting proliferation of pancreatic cancer cell lines in vitro. The effect of the four CDK1 inhibitors and the blank on the proliferation of pancreatic cancer cell lines was tested in vitro using cell technology reagent 8(CCK 8).

Detailed Description

For a further understanding of the present invention, specific embodiments thereof are described in detail below with reference to the examples. It is to be understood that such description is merely for purposes of further illustrating the features and advantages of the invention, and is not to be construed as limiting the aspects of the invention in any way.

It is important to note that those skilled in the art, on a basis of the present state of the art, may practice the present invention in view of the present disclosure. Moreover, similar modifications and equivalents will occur to those skilled in the art without departing from the spirit and scope of the invention and, it is apparent that such similar modifications and equivalents will be readily apparent to those skilled in the art, and are intended to be included herein.

Example 1: pancreatic tissue single cell transcriptome data acquisition

1. Clinical specimen collection

24 cases of surgically resected pancreatic cancer tissue (15mmX15mm) of pancreatic cancer patients who did not receive neoadjuvant radiotherapy or chemotherapy and 11 cases of surgically resected normal pancreatic cancer tissue (15mmX15mm) of non-pancreatic cancer patients who received pancreatic surgery were collected at Beijing coordination Hospital, Chinese academy of medicine, from 3 months of 2018 to 6 months of 2018. The study was in compliance with the medical ethical standards of Helsinkiddeclaration (Helsinkiddeclaration) and was approved by the Beijing council medical ethical Committee.

Pancreatic cancer tissue and normal pancreatic tissue were immediately stored ex vivo in RPMI 1640 medium (Corning) containing protease inhibitors (Solarbio) and 10% by volume fetal bovine serum (Gibco), transported on ice and single cell isolation procedures started within 30 minutes.

2. Single cell suspension preparation

After removal of fascia, fat and necrotic tissue from pancreatic and normal pancreatic tissue, the tissue was placed in an appropriate volume of digestive fluid [ digestive fluid was prepared by dissolving 1mg/mL collagenase type VIII (Sigma), 2mg/mL dispase (Roche), 1mg/mL trypsin inhibitor (Sigma) and 1 unit/mL DNaseI (NEB) in Phosphate Buffered Saline (PBS) (Hyclone) containing 5% fetal bovine serum (Gibco) by volume]In (1), the tissue is cut to about 2X 1 mm on ice³Of (2) debris. The tissue fragments were soaked in the digestive juice and digested at 37 ℃ for a total of 40 minutes. Transferring the digestive juice containing the tissue debris into a 50ml centrifuge tube, standing, collecting the supernatant, filtering with a 40 μm filter screen, collecting the filtrate, centrifuging at 800g for 4 min, and using the solution containing 1 monomerErythrocyte lysate (eBioscience) at DNaseI (NEB) site/mL removed erythrocytes. After washing 2 times with PBS (Hyclone) containing 0.04 wt.% bovine serum albumin (Sigma), the cells were finally resuspended at a concentration of 1X 10⁶The cell viability is kept between 80 and 90 percent per mL.

3. 10X library construction and sequencing

The Single Cell suspension prepared is converted into 10X libraries with each Cell marked with a biological bar code (barcode) by using a Single Cell 3 'end Library (The chromosome Single Cell 3' Library), a Gel Bead & Multiplex kit and a Chip kit (10X Genomics) based on The chromosome system, each Library contains about 5000 cells, cDNA amplification and sequencing Library construction are carried out according to a commercial instruction method (https:// www.10xgenomics.com/solutions/Single-Cell /) strictly, and Illumina HiSeqXTen sequencing is adopted, The sequencing mode is double-ended 150bp, and The data volume of one Cell is 2500-.

Example 2: single cell transcriptome data analysis

1. Single cell transcriptome data processing and quality control

Sequencing data was processed using the Cell range 2.1.0 pipeline using default and recommended parameters. FASTQ files generated from Illumina sequencing output were aligned to the human reference genome (hg19) using the STAR algorithm. Next, the gene expression matrix for each sample was obtained by specific molecular labeling (UMI) and filtering of the non-cellular barcodes. Finally, a gene expression matrix with cell labels and gene expression numbers is obtained.

The expression matrices were then read using the Seurat (v2.3.0) R software package for quality control and downstream analysis of single cell data. All functions are run using default parameters unless otherwise noted. Low quality data (<200 genes/cell, < 3 cells/gene, >10% mitochondrial gene) were removed during quality control. Before merging the samples, the expression matrix for each sample is read into Seurat.

2. Cell clustering and cell type identification

And (3) carrying out cell clustering and grouping by using a nonlinear dimension reduction (t-SNE) method. The R software package, seruat, was used to identify cell types. Principal component analysis (PCA analysis) was performed on the hypervariable genes. The important principal components were determined using JackStraw analysis and heat maps focused on Principal Components (PC) 1 to 20. PC 1 to 10 were used for graph-based clustering (0.8 for PDAC samples and 1 for pooled cells from PDAC and controls) to identify different cell populations. t-SNE analysis was performed using the previously calculated principal components 1 to 10. The type of each type of cell is subsequently determined based on known markers for these cells: AMBP (ductal cells type I), KRT19 (ductal cells type II), PRSS1 (acinar cells), CHGB (endocrine cells), RGS5 (astrocytes), LUM (fibroblasts), CDH5 (endothelial cells), AIF1 (macrophages), CD3D (T lymphocytes), MS4a1(B lymphocytes).

Type II ductal cells were divided into 7 cell subsets based on the same cell clustering and clustering method.

3. Copy Number Variation (CNV) estimation

The initial Copy Number Variation (CNV) of each cell population was estimated using the R software package InferCNV (v 2.0). When calculating copy number variation of all cell types from single cell gene expression data, the threshold set for each cell and the noise filtering threshold was 0.2. For each sample, the gene expression of the cells was re-normalized and the values were limited to-1 to 1. The CNV score for each cell was calculated as the second sum of CNV regions.

To fully study CNV levels in ductal cells 1 and 2 of each sample, the individual somatic CNVs were eliminated using the other cells as background and the CNV levels were recalculated within the same threshold. Finally, type II ductal cells CNV were found at a higher level compared to type I ductal cells.

4. Cell population expression profiling

And (3) obtaining the cell population specific marker gene by using the FindAllMarkers function in the Seurat package for the standardized gene expression data. To find the differential genes between cell populations,' find. Gene enrichment analysis was performed using DAVID (https:// DAVID. ncifcrf. gov/home. jsp) and Metascape (http:// metascap. org) on each cell population in pancreatic cancer tissue and the first 100 differentially expressed genes in type II ductal cells identified as malignant cells, with the results shown in tables 2-6.

TABLE 2 Gene expression characteristics of type I ductal cells in pancreatic cancer tissue (first 100)

Name of Gene	Gene expression level avg _ logFC	Significance P value	Name of Gene	Gene expression level avg _ logFC	Significance P value
						FXYD2	3.272466996	0	EPCAM	0.815213716	0
leftY1	2.295110723	0	KCNJ16	0.81258485	0
						SLC4A4	2.16551632	0	DCDC2	0.812255745	0
CLU	2.149174955	0	RAMP1	0.81197533	0
						ANXA4	2.0166095	0	NGFRAP1	0.80988908	0
DEFB1	1.947985264	0	FBXO21	0.807519491	0
						AMBP	1.877426153	0	FAM3B	0.794945073	0
CFTR	1.872971266	0	CD59	0.794739821	0
						CLDN10	1.815086546	0	C8orf47	0.79209588	0
SPP1	1.800089109	0	C3	0.791876912	0
						MMP7	1.650113023	0	SERPINA6	0.788085539	0
SERPINA5	1.647941662	0	HES1	0.787202549	0
						ATP1A1	1.487092033	0	BICC1	0.784288314	0
SLC3A1	1.457316626	0	C6	0.779145439	0
						RBP1	1.455588483	0	CA2	0.77785039	0
BEX1	1.360605228	0	UBD	0.772519182	0
						SH3YL1	1.356358016	0	GTF2I	0.772058967	0
SFRP5	1.351383522	0	AQP1	0.767663912	0
						GATM	1.347119125	0	FAIM	0.76017872	0
SORBS2	1.336999751	0	RAB3IP	0.75962232	0
						MT1F	1.324824327	0	TUSC3	0.753876806	0
GMNN	1.268592002	0	TCEA3	0.751750599	0
						REG1A	1.254599674	0	SOD3	0.748099747	0
CITED4	1.237536068	0	VTN	0.745610722	0
						SCTR	1.211266778	0	ADRA2A	0.741315391	0
PPP1R1B	1.192307766	0	NTRK2	0.740339419	0
						SERPING1	1.152572544	0	SCD5	0.736290886	0
KCNJ15	1.079575925	0	HMGN3	0.732250284	0
						AKAP7	1.056973271	0	RP11-528G1.2	0.731577191	0
ATP1B1	1.031355177	0	TESC	0.721895523	0
						KIF12	1.011824391	0	SLC37A4	0.718535221	0
PEBP1	1.008568571	0	ERRFI1	0.717263446	0
						MUC6	0.998292496	0	CYB5A	0.716016331	0
CXCL6	0.997883068	0	TACSTD2	0.705873971	0
						SERPINA1	0.986585995	0	PROX1	0.691060168	0
CLDN3	0.985170735	0	ISYNA1	0.688525907	0
						PMEPA1	0.952960686	0	HHEX	0.684572659	0
HSD17B2	0.949898423	0	ABCC3	0.683489779	0
						PPAP2C	0.949871554	0	S100A13	0.678128594	0
HOMER2	0.947887186	0	RHOBTB3	0.674366364	0
						FAM150B	0.920793818	0	COMTD1	0.67166931	0
C12orf75	0.915578769	0	CXADR	0.668158769	0
						UGT2A3	0.913609255	0	PHGDH	0.656743975	0
FGGY	0.885426955	0	GLIS3	0.655706915	0
						SOD2	0.866013036	0	TSTD1	0.655278858	0
KRT18	0.841764412	0	PKHD1	0.653584925	0
						SOX9	0.840537132	0	DMKN	0.653110279	0
RP11986E7.7	0.832521773	0	FLRT2	0.651020312	0
						PERP	0.82460172	0	TFPI2	0.650267822	0
KRT8	0.819286574	0	PBX1	0.646849327	0

TABLE 3 Gene expression characteristics of type II ductal cells in pancreatic cancer tissue (first 100)

Name of Gene	Gene expression level avg _ logFC	Significance P value	Name of Gene	Gene expression level avg _ logFC	Significance P value
						TFF1	2.772533544	0	OCIAD2	1.178199701	0
FXYD3	2.586168984	0	NQO1	1.170333634	0
						TFF2	2.349630212	0	TM4SF4	1.120076144	0
C19orf33	2.321975321	0	IFI27	1.112048693	0
						TFF3	2.297402467	0	DPCR1	1.110408285	0
KRT19	2.295478664	0	SFN	1.079363643	0
						AGR2	2.166293341	0	LINC01133	1.072622716	0
LCN2	2.06705409	0	PERP	1.058024271	0
						REG4	2.048061172	0	MSLN	1.049421995	0
LGALS4	1.961456132	0	SFTA2	1.042213643	0
						CEACAM6	1.911553862	0	CYP3A5	1.040217244	0
S100P	1.814908341	0	S100A10	1.037916609	0
						SPINK1	1.813340793	0	LIPH	1.030455242	0
TSPAN8	1.766240982	0	KLF5	1.023953444	0
						S100A6	1.758457708	0	CXCL5	1.019176252	0
SLPI	1.732456806	0	CLDN7	1.018151288	0
						PHGR1	1.70129086	0	RAB11FIP1	1.002638624	0
MUC1	1.685047935	0	CRABP2	0.98341776	0
						KRT8	1.684694444	0	C12orf75	0.974468489	0
SMIM22	1.640149272	0	HIST1H1C	0.970419914	0
						WFDC2	1.623572993	0	S100A11	0.961964847	0
SPINT2	1.607742709	0	PHLDA2	0.95799792	0
						KRT18	1.601152718	0	MGST1	0.956276805	0
CLDN4	1.598566735	0	LAMB3	0.952287622	0
						CTSE	1.593681231	0	LYZ	0.951898048	0
ELF3	1.55962735	0	CCL20	0.947074159	0
						PDZK1IP1	1.548944533	0	MUC13	0.944052136	0
CLDN18	1.538375692	0	LMO7	0.942347965	0
						KRT7	1.529126577	0	SDC4	0.935912719	0
EPCAM	1.483319399	0	PPDPF	0.92867284	0
						C15orf48	1.472865413	0	C19orf77	0.927994474	0
S100A14	1.44520083	0	CSTB	0.927907271	0
						GPX2	1.435164919	0	SERINC2	0.92518306	0
LSR	1.430554243	0	HN1	0.920593973	0
						CYSTM1	1.421962431	0	SAA1	0.917012109	0
TSPAN1	1.402447288	0	ANXA2	0.912839613	0
						TACSTD2	1.39724433	0	S100A2	0.903911858	0
TMC5	1.280210201	0	CAMK2N1	0.903134239	0
						PGC	1.274902832	0	TSPAN3	0.896442517	0
MAL2	1.273783482	0	PLA2G16	0.894345517	0
						SERPINA1	1.246644129	0	PSCA	0.893980457	0
CEACAM5	1.231840111	0	ANXA10	0.888302684	0
						PIGR	1.225368739	0	BIRC3	0.859768324	0
ATP1B1	1.220304656	0	ERBB3	0.859242855	0
						MMP7	1.216536821	0	SYT8	0.856476225	0
AGR3	1.213526181	0	SDCBP2	0.855777768	0
						LGALS3	1.212245021	0	JUP	0.853578519	0
GPRC5A	1.211431245	0	CDH1	0.851949236	0
						PI3	1.210350906	0	GCNT3	0.848016391	0
OLFM4	1.195178457	0	RP11-462G2.1	0.840568018	0

TABLE 4 characteristic expression genes of acinar cells in pancreatic cancer tissue (first 100)

Name of Gene	Gene expression level avg _ logFC	Significance P value	Name of Gene	Gene expression level avg _ logFC	Significance P value
						PRSS1	5.236605052	0	RP11-320N7.2	0.250044449	0
CTRB2	5.179753462	0	ANPEP	0.780142301	1.2E-306
						CELA3A	4.838744463	0	SLC39A5	0.292027399	2.2E-282
CTRB1	4.724315075	0	SLC43A1	0.305606072	1.9E-278
						REG1B	4.702706704	0	RP11-986E7.7	0.520641843	7.4E-274
CLPS	4.65145949	0	GAMT	0.670413262	3.1E-270
						CPB1	4.513887613	0	RBP1	1.121586543	4.4E-265
CPA1	4.351968886	0	SERPINA4	0.395926247	4.0E-223
						PLA2G1B	4.311988687	0	IMPA2	0.517676734	9.5E-221
REG3A	4.272185339	0	FAM3B	0.551741858	5.2E-214
						REG1A	4.253882194	0	CTC-479C5.12	0.576434405	4.3E-193
CTRC	4.208933992	0	MT1F	0.909068755	1.5E-190
						PNLIP	4.06135454	0	NR5A2	0.322338819	8.9E-183
CELA3B	4.00238189	0	HOMER2	0.338742532	1.8E-176
						PRSS3	3.846159863	0	STXBP6	0.384391781	1.5E-175
SYCN	3.779047838	0	C2CD4B	0.331035247	3.0E-172
						CELA2A	3.540312596	0	TCEA3	0.457396612	2.2E-156
CPA2	3.500611205	0	BNIP3	0.306867407	2.7E-153
						AMY2A	3.44786795	0	XBP1	0.641992282	1.6E-146
REG3G	3.195345533	0	CITED4	0.477171588	9.6E-145
						CEL	3.188155718	0	ERO1LB	0.295500017	1.4E-143
GP2	3.163436945	0	PDCD4	0.688726035	2.4E-142
						SPINK1	2.676256023	0	SCTR	0.371977531	2.0E-140
PNLIPRP1	2.521229193	0	CXCL17	0.271652803	9.2E-140
						KLK1	2.393377839	0	SHC2	0.312286381	1.9E-134
CELA2B	2.178530503	0	TPST2	0.32511141	2.3E-128
						MT1G	2.032090542	0	BCAT1	0.282068598	2.5E-127
GATM	2.010975328	0	SFRP5	0.279222723	1.1E-126
						CTRL	1.851992458	0	COMTD1	0.507151197	1.6E-124
AMY2B	1.633008632	0	AZGP1	0.293662407	1.0E-122
						CUZD1	1.630544859	0	DNAJC12	0.299908523	1.9E-122
LGALS2	1.169203136	0	OLFM4	1.495365703	2.7E-119
						GSTA1	1.088434738	0	PABPC4	0.560516603	3.9E-118
PDIA2	1.013342677	0	RARRES2	0.465440218	3.9E-114
						ERP27	0.987826475	0	IGFBP2	0.48294206	1.6E-113
SERPINI2	0.905250021	0	RNASE1	0.702768855	1.8E-113
						GSTA2	0.886794909	0	MT1X	0.935334158	1.5E-111
TMEM97	0.831745861	0	UBD	0.62226754	1.8E-111
						AQP8	0.81411901	0	SLC39A14	0.374960606	2.1E-106
ALB	0.804637248	0	CLDN10	0.334070011	3.3E-105
						MT1H	0.755453305	0	FXYD2	0.369492216	6.3E-100
FGL1	0.532791166	0	CYB5A	0.576170379	1.23E-98
						EPB41L4B	0.396768756	0	GRB10	0.255664073	1.09E-95
SLC30A2	0.371914878	0	C6orf222	0.258015249	2.99E-91
						KIAA1324	0.345214203	0	P4HB	0.48785023	3.68E-90
CBS	0.341016631	0	MT1E	0.606397194	3.55E-88
						GNMT	0.3173318	0	PGM1	0.449130613	5.29E-88
FSCN2	0.290973002	0	EIF4EBP1	0.43589467	7.78E-88
						TMEM52	0.256893286	0	CCDC64B	0.278301065	2.07E-87
AC078941.1	0.250852721	0	C3	0.499001765	3.80E-86

TABLE 5 Gene expression characteristic of endocrine cells in pancreatic cancer tissue (first 100)

Name of Gene	Gene expression level avg _ logFC	Significance P value	Name of Gene	Gene expression level avg _ logFC	Significance P value
						TTR	3.407751539	0	SYP	0.362743919	0
PCSK1N	3.200755845	0	NRXN1	0.361248995	0
						IAPP	2.527544419	0	CELF4	0.359193089	0
SCG5	2.052738492	0	KCNJ6	0.348617715	0
						CHGA	1.824336349	0	DUSP26	0.34842939	0
CHGB	1.539801452	0	SLC29A4	0.337011773	0
						SLC30A8	1.493639662	0	TCEAL2	0.331693357	0
SCGN	1.405850915	0	CPLX2	0.322333718	0
						ERO1LB	1.393556548	0	KCNMB2	0.318343163	0
NEUROD1	1.344942482	0	RAB26	0.313239945	0
						BEX1	1.20475688	0	TAGLN3	0.310235276	0
MIR7-3HG	1.18334554	0	ISL1	0.303618471	0
						SCG3	1.089599653	0	RAB3C	0.294513771	0
DLK1	1.058644067	0	KIF1A	0.29403703	0
						NKX2-2	1.030168142	0	CAMK2B	0.292547041	0
GAD2	1.029692598	0	GNG4	0.289732929	0
						FAM159B	1.001094884	0	C1orf127	0.28145357	0
ABCC8	0.999038397	0	NOL4	0.280094119	0
						STMN2	0.911239186	0	RP11-423H2.3	0.266524301	0
PCSK2	0.904710149	0	C1QL1	0.26592794	0
						PTPRN	0.889306434	0	TDRD9	0.256634915	0
SCG2	0.798776835	0	C21orf58	0.296069289	2.2E-301
						G6PC2	0.737799378	0	TMOD1	0.309713905	2.2E-281
UCHL1	0.715981062	0	NUPR1L	0.272385947	5.4E-280
						PCSK1	0.680092376	0	PCLO	0.417049553	9.1E-270
ASB9	0.668107405	0	PAK3	0.357103486	7.3E-261
						CRYBA2	0.660694947	0	FAM46C	0.48007022	3.9E-252
PAX6	0.655172694	0	BEX2	0.680921735	1.2E-239
						SYT7	0.625160457	0	SCGB2A1	0.714192294	1.7E-219
PCP4	0.619170152	0	RBP4	2.281287113	3.6E-219
						DHRS2	0.607523206	0	FXYD2	0.891859316	6.2E-205
GJD2	0.593437374	0	CADPS	0.346174625	1.0E-197
						SNAP25	0.571835139	0	FAM105A	0.573039168	1.5E-187
KIAA1324	0.571226287	0	RAP1GAP2	0.324449865	9.5E-186
						LINC00948	0.537740329	0	OLFM2	0.264680037	9.8E-180
HEPACAM2	0.53003118	0	ASCL2	0.294465637	4.3E-175
						APLP1	0.49212115	0	RIC3	0.443059555	2.1E-163
MLXIPL	0.486212402	0	SLC22A17	0.360863466	6.4E-163
						INSM1	0.48287768	0	PEG10	0.508011624	8.7E-162
PPP1R1A	0.479872032	0	INS	4.337019686	2.6E-159
						ELAVL4	0.479704142	0	RAB3B	0.319436162	3.5E-159
EEF1A2	0.475620738	0	QPCT	0.624636868	3.5E-157
						EDN3	0.474390749	0	DNAJC12	0.422090084	1.3E-151
ADCYAP1	0.472562554	0	SLC7A8	0.344670853	3.9E-151
						LINC00643	0.439926844	0	RASD1	0.551247366	2.8E-147
NPTX2	0.434110029	0	SST	4.46555179	2.7E-142
						KCNK16	0.418315874	0	SYT13	0.435885038	6.0E-137
NOVA1	0.415667147	0	STX1A	0.326878826	1.2E-136
						SYT4	0.371619801	0	PNMA2	0.259136846	1.8E-135
SAMD11	0.367359189	0	CPE	1.153390937	2.0E-133

TABLE 6 characterisation of the expression genes of subgroup 7 cells in type II ductal cells (first 100)

Name of Gene	Gene expression level avg _ logFC	Significance P value	Name of Gene	Gene expression level avg _ logFC	Significance P value
						PTTG1	1.723780457	0	CDCA3	0.395843826	0
CENPF	1.514906646	0	SGOL2	0.395800352	0
						HMGB2	1.497883253	0	CDCA8	0.392720545	0
UBE2C	1.291345411	0	KIF23	0.390017538	0
						H2AFZ	1.272164294	0	SGOL1	0.386859596	0
top2A	1.213339241	0	KNSTRN	0.386141018	0
						KIAA0101	1.117892621	0	RACGAP1	0.378033377	0
MKI67	1.112977071	0	AURKB	0.377689018	0
						CCNB1	1.108639186	0	RAD51AP1	0.368271926	0
HMGB1	1.102038826	0	FOXM1	0.366566836	0
						BIRC5	1.042799027	0	DEPDC1	0.360961751	0
SMC4	0.973873695	0	KIF4A	0.342971354	0
						CENPW	0.939093109	0	PRR11	0.321235041	0
CDKN3	0.905291907	0	SPC25	0.319656953	0
						CCNB2	0.878032386	0	CENPU	0.319284349	0
NUSAP1	0.875983973	0	BUB1	0.315829206	0
						CDC20	0.863693584	0	KIFC1	0.303510186	0
PRC1	0.763150493	0	KIF2C	0.299890151	0
						TPX2	0.751156236	0	CASC5	0.288097615	0
MAD2L1	0.746013239	0	IQGAP3	0.287931209	0
						TK1	0.706058107	0	PHF19	0.279744487	0
DTYMK	0.697782926	0	KIF20A	0.274408312	0
						ASPM	0.673419195	0	TRIP13	0.273083551	0
HMMR	0.634742684	0	KIF11	0.272832545	0
						KIF20B	0.632360885	0	OIP5	0.271690811	0
CENPE	0.620045136	0	ARHGAP11B	0.270945948	0
						TYMS	0.588412475	0	SAPCD2	0.266950039	0
RRM2	0.569000226	0	CKAP2L	0.263841927	0
						ANLN	0.564280823	0	CLSPN	0.261513933	0
AURKA	0.547930646	0	NDC80	0.256883159	0
						ZWINT	0.543485294	0	KIF14	0.256695998	0
UBE2T	0.539722947	0	FANCI	0.252300408	0
						CEP55	0.535585938	0	SMC2	0.404229633	9.62E-307
CKAP2	0.534292056	0	NCAPD2	0.332233272	1.33E-304
						GGH	0.526346371	0	HMGB3	0.655730409	1.49E-299
CDK1	0.518737414	0	ECT2	0.48415708	5.93E-292
						NUF2	0.499951888	0	STMN1	1.354847176	7.70E-291
CENPA	0.494319205	0	KPNA2	0.634759917	3.42E-282
						TROAP	0.490986696	0	UBE2S	0.968089349	6.64E-277
DLGAP5	0.472655986	0	TACC3	0.389194595	3.85E-274
						PBK	0.469919984	0	CKS2	1.256188815	6.94E-271
GTSE1	0.461076745	0	H2AFV	0.806286219	5.80E-268
						NEK2	0.453229854	0	TUBA1B	1.332920285	1.37E-263
CCNA2	0.447953037	0	LMNB2	0.365023319	1.51E-258
						CENPK	0.441139332	0	LSM5	0.817213808	5.01E-257
LMNB1	0.439024034	0	HNRNPA2B1	0.651086151	3.38E-227
						CENPN	0.427554966	0	HMGN2	1.057927856	2.90E-225
ARHGAP11A	0.417280925	0	SKA2	0.549331165	5.66E-224
						GPSM2	0.397694606	0	DHFR	0.444715185	6.41E-218
PLK1	0.396822198	0	CCDC34	0.557779041	1.81E-214

5. Immunohistochemical staining validation of malignant cell populations

FXYD3 and MUC1, highly expressed in type II ductal cells, were selected as marker genes and the corresponding commercial protein antibodies FXYD3(Novus Biologicals) and MUC1(Cell signaling technology) were purchased. Collecting pancreas cancer tissue (10mmX10mm) of pancreatic cancer patient who has not received neoadjuvant radiotherapy or chemotherapy and normal pancreas tissue (10mmX10mm) of pancreatic cancer patient who has received pancreas surgery and has been removed by surgery, fixing with methanol, sealing with paraffin, slicing with a microtome to obtain slices of 4 μm thickness, spreading on a glass slide, dewaxing and dehydrating with xylene, 100 vol% ethanol, 95 vol% ethanol, and 75 vol% ethanol, and performing microwave antigen retrieval in citrate solution with pH of 6.0. Endogenous peroxidase was blocked with 3 vol% hydrogen peroxide. After primary antibody and secondary antibody are incubated in sequence, Diaminobenzidine (DAB) is used for color development, and the ductal cell nucleus profile which can be marked by the II-type ductal cell marker is observed by an optical microscope to be high.

6. Gene interaction network analysis

The network Analysis function in the Ingenity Pathway Analysis software (IPA, Ingenity Systems) was used to analyze the interaction network between the proliferation-related genes highly expressed in the subgroup 7 cells of type II catheter cells and the proteins encoded by them. The results of network analysis showed that there was an activating or inhibiting effect between the proliferation related genes and their encoded proteins, and that the CDK1 gene and its encoded protein were centered in the interaction network, while, according to the subgroup 7 cell characteristic expression gene list, the CDK family members were only CDK1 genes among the top 100 genes that were highly expressed (see table 6). The above results suggest that CDK1 may be a target for drug therapy of pancreatic cancer.

Example 3: in vitro validation of drug therapy target genes

The purpose of this example was to further validate the feasibility of CDK1 as a target for pancreatic cancer drug therapy.

1. Selection of small molecule inhibitors

Using CDK1 as a keyword, the small molecule inhibitors Dinaciclib, Milciclib, AZD5438 and Frarazonema for CDK1 gene were retrieved and purchased at Selleck China official website (https:// www.selleck.cn).

2. Experiments with Small molecule inhibitors affecting cell proliferation

Cell proliferation experiments were performed on the MIA PaCa-2 pancreatic ductal adenocarcinoma Cell line using the in vitro Cell Counting Kit 8(Cell Counting Kit 8, CCK8) to observe the proliferation inhibitory effect of small molecule inhibitors on the MIA PaCa-2 pancreatic carcinoma Cell line.

1) Following the description, Dinaciclib, micciclib, AZD5438 and frataxin were dissolved to target concentrations according to the following table:

small molecule inhibitors	Dinaciclib	Milciclib	AZD5438	Degree of fraise
					Specification of	1mg	1mg	1mg	1mg
Solvent(s)	DMSO	DMSO	Ethanol	DMSO
					Solvent amount (mL)	2.5221	2.1712	2.6921	2.4886
Final concentration	1mM	1mM	1mM	1mM
					Concentration of experiment	10nM	10μM	5μM	500nM

；

2) MIA PaCa-2 cells were plated in 96-well plates at 5000 cells/well;

3) after 12 hours of cell attachment, solvent (DMSO), Dinaciclib, micciclib, AZD5438 and frataxime were added, respectively, to bring each inhibitor concentration to the experimental concentration above, at 37 ℃ and 5% CO₂Continuously culturing under the condition of (1);

4) add 10. mu.L of CCK8 reagent to each well at 0h, 24h, 48h and 72h after dosing, respectively, and incubate for 2.5h at 37 ℃;

5) the absorbance of each well at a wavelength of 450nm, i.e., the base 10 logarithm of the ratio of the intensity of the incident light at a wavelength of 450nm before it passes through the solution or a substance to the intensity of the transmitted light after it passes through the solution or substance, is measured. This value is proportional to the number of cells per well. And the absorbance at the wavelength of 630nm is taken as a reference and the absorbance of the blank hole is taken as a baseline value;

6) the above experiment was repeated Multiple times and statistical analysis was performed using GraphPad Prism (GraphPad Software, Inc.) to compare the level of difference in absorbance values between each drug-treated group and the blank control group at each time point using Multiple t-test: p <0.05, P <0.01, P <0.001, ns: there was no significant difference (no significant difference).

The results are shown in Table 7.

TABLE 7 Experimental results for drugs inhibiting proliferation of pancreatic cancer cell lines

See table 8 for statistical analysis results.

TABLE 8 statistical analysis of data from experiments with drug inhibition of proliferation of pancreatic cancer cell lines

As a result, Dinaciclib (10nM), Milnacciib (10. mu.M), AZD5438 (5. mu.M) and Fralazine (500nM) were found to significantly inhibit the proliferation of the pancreatic cancer MIA PaCa-2 cell line. The above results suggest that CDK1 can be used as a target for pancreatic cancer drug therapy, and inhibitors thereof such as Dinaciclib, micciclib, AZD5438 and fraveline have the potential to be applied to pancreatic cancer drug therapy.

Various aspects of the present invention have been illustrated by the above-described embodiments. It should be understood that the above-described embodiments are given for illustrative purposes only, and are not intended to limit the scope of the present invention in any way. Other variations and modifications will be apparent to persons skilled in the art based on the foregoing examples. And are neither required nor exhaustive of all embodiments. And obvious variations or modifications derived therefrom are within the scope of the invention.

Claims

2. The cyclin-dependent kinase 1 inhibitor of claim 1, wherein the cyclin-dependent kinase 1 inhibitor is selected from the group consisting of: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

3. The cyclin-dependent kinase 1 inhibitor according to claim 1 or 2, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma, other types of ductal origin, acinar cell carcinoma, small gland carcinoma, or small cell carcinoma.

4. The cyclin-dependent kinase 1 inhibitor according to claim 3, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, an adenosquamous carcinoma, a mucinous epidermoid carcinoma, a signet ring cell carcinoma, or a ciliated cell carcinoma.

6. The pharmaceutical composition of claim 5, wherein the cyclin-dependent kinase 1 inhibitor is: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

7. The pharmaceutical composition according to claim 5 or 6, wherein the cyclin-dependent kinase 1 inhibitor is the only active ingredient in the pharmaceutical composition.

8. The pharmaceutical composition of claim 5 or 6, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma, other types of ductal origin cancers, acinar cell carcinoma, small gland carcinoma, or small cell carcinoma.

9. The pharmaceutical composition according to claim 8, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, or ciliated cell carcinoma.

11. The use of claim 10, wherein the cyclin-dependent kinase 1 inhibitor is: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

12. The use of claim 10 or 11, wherein the cyclin-dependent kinase 1 inhibitor is the only active ingredient in the medicament.

13. The use of claim 10 or 11, wherein the medicament further comprises a pharmaceutically acceptable carrier.

14. The use of claim 10 or 11, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma of the pancreas, other types of ductal origin, acinar cell carcinoma, small gland carcinoma, or small cell carcinoma.

15. The use of claim 14, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, or ciliated cell carcinoma.

17. The method of claim 16, wherein the cyclin-dependent kinase 1 inhibitor is: 1) dinaciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 2) miciciclib or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 3) AZD5438 or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; 4) (ii) frataxime or a pharmaceutically acceptable salt, stereoisomer or solvate thereof; and 5) a combination of two or more of the above options 1) to 4).

18. The method of claim 16 or 17, wherein the cyclin-dependent kinase 1 inhibitor is formulated in a pharmaceutical composition with a pharmaceutically acceptable carrier.

19. The method of claim 16 or 17, wherein the pancreatic cancer is selected from one or two or more of ductal adenocarcinoma of the pancreas, other types of ductal origin, acinar cell carcinoma, small gland carcinoma, or small cell carcinoma.

20. The method of claim 19, wherein the other type of cancer of ductal origin is selected from one or two or more of a pleomorphic carcinoma, adenosquamous carcinoma, mucinous carcinoma, mucoepidermoid carcinoma, signet ring cell carcinoma, or ciliated cell carcinoma.

1) contacting a subject with cyclin-dependent kinase 1;

23. The method of claim 21 or 22, wherein the cyclin-dependent kinase 1 is cyclin-dependent kinase 1 in an in vitro, ex vivo, or in vivo environment.