KR20200093838A - Lipid biomarker composition for diagnosing of cancer and uses thereof - Google Patents

Abstract

The present invention relates to a lipid biomarker for diagnosis of cancer and uses thereof. Particularly, the present invention relates to a biomarker for diagnosis of cancer using a lipid expression level, a diagnostic kit including the same, and a use for diagnosing cancer. Furthermore, the present invention provides a method for monitoring and screening cancer therapeutic agents using analysis of the lipid expression level. A lipid biomarker composition for diagnosis of liver cancer includes: at least one lipid selected from a group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); and at least one lipid selected from a group b) consisting of lysophosphatidylcholine (LPC) and hexosylceramide (HexCer).

Description

Lipid biomarker composition for diagnosing of cancer and uses thereof}

The present invention relates to a lipid biomarker for cancer diagnosis and its use. Specifically, it relates to a biomarker for diagnosis of cancer using a lipid expression level, a diagnostic kit including the same, and a use for diagnosing cancer. Furthermore, the present invention provides a method for monitoring and screening for cancer therapeutics using the lipid expression level analysis.

Cells, the smallest units that make up the body, divide and grow by self-regulating functions, and when they reach their end of life or are damaged, they kill themselves to maintain an overall number balance. However, cancer, which is a disease caused by abnormal proliferation without dying cells due to self-regulation, is a major cause of death worldwide, and the incidence and mortality rates are increasing every year. Until now, the causes of cancer are known to have various and complex effects such as genetic factors, environmental factors, lifestyle and eating habits, and the necessity of a sophisticated molecular-level approach is needed to more clearly understand the causes of cancer. Is emerging.

As a method of diagnosing cancer, a method of diagnosis and diagnosis of a suspected area is usually used after imaging of CT, MRI, etc., but this is not an early diagnosis of cancer, and diagnosis is possible only after cancer cells have grown and developed to some extent. This is how limitations exist. Accordingly, recently, a method of diagnosing cancer early through genetic tests and protein tests is used, and in the case of lung cancer, an early diagnosis method using the method is widely used.

Lipidics is an academic field focused on identifying the biological and biochemical importance by qualitatively quantifying and quantifying the overall phenomena and changes occurring in the metabolic process of various lipid groups occurring in vivo. It is also aimed at research to find related biomarkers. In particular, with the recent rapid development of electrospray ionization-tandem mass spectrometry (ESI-MS-MS), structural analysis of lipid molecules has become possible, and the field of shotgun lipidomics can also be used for the analysis of biological tissues.

In addition, among various types of lipids, phospholipids (PLs) are known to play an important role in various functions in vivo, such as cell signaling, cell proliferation, and apoptosis. . Cancer cells are abnormally proliferative diseases in which the balance of the normal cell cycle is broken, and research for early diagnosis and prognosis of cancer using lipid physics is required.

Korean Registered Patent No. 10-1570143 Korean Patent Publication No. 10-2018-0041556

An object of the present invention is to provide a lipid biomarker composition for diagnosis of liver cancer.

Another object of the present invention is to provide a kit for diagnosing liver cancer comprising the lipid biomarker composition.

Another object of the present invention is to provide a method for providing information necessary for diagnosis of liver cancer using the lipid biomarker composition.

Another object of the present invention is to provide a method for monitoring liver cancer inhibitors or liver cancer therapeutic agents using the lipid biomarker composition.

Another object of the present invention is to provide a screening method for treating liver cancer using the lipid biomarker composition.

One aspect of the present invention for achieving the above object relates to a lipid biomarker composition that diagnoses liver cancer or analyzes the prognosis of liver cancer by predicting an increase or decrease in the expression level of a specific lipid species.

The lipid biomarker composition may include one or more lipids selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And

It relates to a lipid biomarker composition for diagnosing liver cancer, comprising at least one lipid selected from the group b) consisting of lysophosphatidylcholine (LPC) and hexylsylamide (HexCer).

The group a) is a group of lipids that is characterized by an increase or decrease in expression in a specific type of cancer, and the group b) is a group of lipids that is characterized by an increase or decrease in expression in common in several types of cancer diseases.

In the present invention, diagnosis and prognosis for cancer can be predicted by measuring and/or analyzing a) an increase or decrease in the expression of a lipid species included in the group, and b) an increase or decrease in the expression of a lipid species included in the group. .

Lipid notation in the present invention is indicated according to the system name and common name (IUPAC-IUBMB) according to world applied chemistry, biochemistry, and molecular biology standards in Lipidics.

Specifically, the phosphatidylinositol (PI) is 16:0/18:2, 16:0/20:4, 18:0/20:3 or 18:1/18:0, and the diacylglycerol ( Diacylglycerol, DG) is 16:1_18:0, the lysophosphatidylcholine (LPC) is 16:0 or 18:2, and the hexosylceramide (HexCer) can be d18:1/20:0 have.

In one embodiment of the present invention, samples from normal and cancer patients (liver cancer, stomach cancer, lung cancer, colon cancer, and thyroid cancer) were analyzed for lipid species, and phosphatidylinositol (PI) 16:0/18:2, 16 :0/20:4, 18:0/20:3, 18:1/18:0; Diacylglycerol (DG) 16:1_18:0; Lysophosphatidylcholine (LPC) 16:0, 18:2; Hexyl ceramide (Hexosylceramide, HexCer) d18: 1/20:0 has an AUC value of 0.8 or more, confirming that it can be effectively used as a biomarker in liver cancer diagnosis or prognosis prediction.

Another aspect of the present invention provides a liver cancer diagnostic kit comprising the lipid biomarker composition. The kit may include an agent capable of detecting the lipid biomarker of the present invention, and the agent may be included without limitation as long as it can detect the lipid biomarker of the present invention.

Another aspect of the invention,

1) measuring the level of lipid expression in the patient's sample,

The lipid may include at least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And lysophosphatidylcholine (LPC) and hexosylceramide (HxCer), comprising at least one lipid selected from the group; And

2) when the expression level of lipids of group a) and group b) in the sample of the patient is increased or decreased compared to the level of expression in the normal sample, the patient is judged as a liver cancer patient, which is necessary for diagnosis of liver cancer. It is about how to provide information.

Specifically, the method for providing information necessary for the diagnosis of liver cancer is 1) measuring the expression level of lipids in a sample of a patient, wherein the phosphatidylinositol is 16:0/18:2, 16:0/20:4, 18:0/20:3 or 18:1/18:0, the diacylglycerol is 16:1_18:0, the lysophosphatidylcholine is 16:0 or 18:2, and the hexylceramide is d18:1 /20:0; And

2) Liver cancer when the level of lipid expression in the sample of the patient is increased compared to the level of expression in the normal sample a) phosphatidyl inositol or diacylglycerol is decreased in the group, and b) lysophosphatidylcholine or hexyl ceramide is increased in the group It can be characterized as judging that the patient.

“Sample” in the present invention refers to any substance with or suspected of having or suspecting liver cancer disease. The sample may be natural or synthetic, and may be obtained through any means known to those skilled in the art. Samples include tissue, cells, whole blood, plasma, serum, blood, saliva, sputum, lymphatic fluid, cerebrospinal fluid, intercellular fluid or urine, as well as samples of cell culture components in vitro, e.g., cell components, cell culture media, recombinant cells And the like.

"Sample of patient" in the present invention refers to a biological sample obtained from a target object to determine whether or not to develop liver cancer disease, tissue, cell, whole blood, plasma, serum, blood, saliva, sputum, lymphatic fluid, cerebrospinal fluid, intercellular fluid or urine day Can.

In the present invention, "normal sample" refers to a biological sample obtained from an individual who has not developed a liver cancer disease.

In one embodiment of the present invention, an increase in phosphatidylinositol 16:0/18:2, 16:0/20:4, 18:0/20:3, 18:1/18:0 of the group a) is observed in liver cancer, A decrease in diacylglycerol 16:1_18:0 was observed, and b) a group of lysophosphatidylcholine 16:0 or 18:2, hexylceramide was found to have an increase in d18:1/20:0, in particular, each lipid All the species showed that the AUC value was 0.8 or more, and it was confirmed that they can be used as lipid biomarkers for liver cancer.

Another aspect of the present invention comprises the steps of treating a liver cancer inhibitor or a treatment for liver cancer in a sample of liver cancer patients; And measuring the expression level of lipids before and after treating the liver cancer inhibitor or the liver cancer treatment agent in the sample.

Specifically, the lipid may include at least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And lysophosphatidylcholine (LPC) and hexosylceramide (HexCer).

In the present invention, the liver cancer inhibitor or liver cancer treatment agent may be in the form of small molecules, compounds, antibodies, immunoanticancer drugs, viruses, etc., or treat or improve liver cancer disease through effects such as inhibiting the proliferation or metastasis of cancer or killing cancer cells. Any formulation that can be applied can be applied without limitation.

In the present invention, by measuring a change in the expression level of the lipid biomarker of the present invention for a sample treated with a liver cancer inhibitor or a liver cancer therapeutic agent, the cancer inhibitory ability and cancer treatment effect of the liver cancer inhibitor or liver cancer therapeutic agent can be monitored. For example, when the expression level of the lipid biomarker in the sample is significantly within the range of the normal sample according to the treatment of the liver cancer inhibitor or the liver cancer treatment agent, the cancer inhibitory ability and cancer treatment effect of the liver cancer inhibitor or liver cancer treatment agent is excellent. I can judge.

Another aspect of the present invention comprises the steps of treating a candidate for treatment of liver cancer in a sample of liver cancer patients; And measuring the expression level of lipids before and after processing the candidate substance in the sample.

Specifically, the lipid may include at least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And lysophosphatidylcholine (LPC) and hexosylceramide (HexCer).

In the present invention, by measuring a change in the expression level of the lipid biomarker of the present invention for a sample treated with a candidate drug for treating liver cancer, it is possible to determine the ability to inhibit liver cancer and the effect of treating liver cancer. For example, when the expression level of the lipid biomarker in the sample is significantly within the range of the normal sample according to the treatment of the candidate substance, the candidate substance may be selected as a therapeutic agent for liver cancer disease.

The lipid biomarker of the present invention can be used for diagnosis and prognosis of cancer disease. Depending on the specific expression pattern of the lipid species, detailed cancer types can be diagnosed. Accordingly, by combining the lipid biomarker set of the present invention, it can be widely used for early diagnosis and prognosis prediction for each cancer, and an appropriate treatment direction can be determined according to the diagnosis and predicted prognosis, resulting in cancer recurrence and mortality. Can be reduced.

1 is a schematic diagram of a liquid chromatography-electrospray ionization-mass spectrometer system.
FIG. 2 shows a chromatogram of detecting a lipid standard, a) is analyzed in positive ion mode, and b) shows results analyzed in negative ion mode.
FIG. 3 shows a volcano plot showing fold change and p-value values for comparison between the normal group and the cancer patient group according to the type of 219 lipid species analyzed.
Figure 4 shows a Principal component analysis (PCA) plot showing lipid species with a p-value of less than 0.01 in the cancer patient group when compared to the normal group.
5 shows that the heatmap is expressed by lipid species having a difference of 3 times or more in the cancer patient group and a p-value of 0.01 or less when compared with the normal group.
6 is a stacked bar graph showing compositional changes of highly expressed species for each geological group.
FIG. 7 is a bar graph of lipid species with a high abundance lipid that is more than twice as high as normal and has a p-value of less than 0.05, a) in 5 cancers, b) in 4 cancers, and c) 3 In eggplant cancer, d) is a lipid species characterized by two cancers and e) by one cancer.
8 shows a receiver operating characteristic (ROC) curve of a lipid species selected as a lipid biomarker for each cancer species.
FIG. 9 shows a list of lipid biomarkers having an AUC value of 0.8 or more for each cancer type, a) group is a lipid species showing characteristics only in one cancer, and b) group is a lipid species showing characteristics simultaneously in several types of cancer. ↑ means more than 2 times increase, ↓ means more than 2 times decrease.

Hereinafter, the present invention will be described in detail by examples. However, the following examples are only to illustrate the present invention, the present invention is not limited by the following examples.

Example 1. Preparation of plasma samples

Plasma samples were approved by the Institutional Review Board (IRB) and received from a university affiliated general hospital. Plasma samples were taken for men of average age 50 years old, respectively, normal (n=20), liver cancer (n=21), stomach cancer (n=20), lung cancer (n=17), colorectal cancer (n=16), and thyroid cancer. Obtained from patients (n=10), demographic information for each patient is shown in Table 1 below.

Control Liver cancer Stomach cancer Lung cancer Colorectal cancer Thyroid cancer Number of patients 20 21 20 17 16 10 Average age 50.2 ± 10.9 56.1 ± 10.6 58.5 ± 13.1 61.1 ± 9.6 58.9 ± 10.9 46.9 ± 19.9 Progress
step
(Cancer
stage) Ⅰ 0 0 3 2 4 No information Ⅱ 0 4 One One 3 No information Ⅲ 0 One 13 3 7 No information Ⅳ 0 7 One 10 0 No information p -value
(vs.control) 0.504 0.151 0.021 0.115 0.977

Example 2. Quantitative and qualitative analysis of lipids in plasma

All of the lipids obtained from the plasma samples of Example 1 were analyzed using a nanoflow ultrahigh performance liquid chromatography-electrospray ionization-tandem mass spectrometry (nUHPLC-ESI-MS/MS). Qualitative and quantitative analysis was performed in two steps. For qualitative analysis, a liquid chromatography (LC) model used a Dionex Ultimate 3000 RSLC nano system, and the mass spectrometer was a LTQ Velos ion trap mass spectrometer from Thermo Scientific (San Jose, CA, USA).

Lipid extracts in plasma of pooled samples for each group are identified according to the CID fragment pattern characteristic for each lipid species. Qualitative analysis was performed using LiPilot, a computer software program developed by the present inventors ( Patent Registration 10-1502694).

Subsequently, quantitative analysis was carried out in a selected reaction monitoring (SRM) mode that quantitatively quantifies only the lipid species that were qualitatively analyzed, and LC was used for nanoACQUITY UPLC of Waters (Milford, MA), and mass spectrometry was TSQ Vantage triple of Thermo Scientific It was analyzed using a stage quadrupole mass spectrometer.

A homemade capillary column with a total length of 7 cm was used as an analytical column, and a capillary tube with an inner diameter of 100 μm (outer diameter: 360 μm) purchased from Polymicro Technologies, LLC (Pheonix, AZ) was pulled out using a torch, and the end was cut to remove the cone. It was made into a shape to enable electrospray ionization. Also, to prevent the filler from the column from escaping even at high pressure, pressurize the 3 μm Watchers® ODS-P C18 particles (2.1 mm x 100 mm) filler purchased from Isu Industry Corp. (Seoul, Korea) with nitrogen gas. It was filled with a length of about 0.5 cm. The process is briefly shown in FIG. 1.

Lipid separation method

Lipid separation was performed in the order of high polarity by gradient elution. The composition of the mobile phases A and B used are H ₂ O:ACN (9:1, v/v), CH ₃ OH:ACN:IPA (2:2:6, v/v/v), respectively, and ionization mediators ( ionization modifier), a mixture of 5 mM Ammonium formate and 0.05% Ammonium hydroxide was added to the two mobile phases, respectively.

Qualitative analysis

For qualitative analysis, connect a micro column of stainless steel material purchased from IDEX Health & Science (Oak Harbor, WA, USA) with an analytical column and a capillary tube that allows flow from the pump, and an ESI voltage is formed on the other side. Pt wire to apply voltage and on-off valve to control split flow was connected to the other end. Thereafter, for loading of the sample, after closing the on-off valve, flow 100% of mobile phase A to the analysis column at a flow rate of 550 nL/min for 14 minutes, then open the on-off valve to open the flow rate from the pump at 7 μL/min The flow rate was increased to about 300 nL/min in the analysis column. In addition, the mobile phase B was changed from 75% to 80% for 4 minutes, and then maintained at 80% for 8 minutes. After that, it was raised to 90% for 18 minutes, then raised to 100% for 5 minutes, and maintained at 100% for 5 minutes again. The chromatogram obtained by separating the lipid standard by the gradient elution method under such conditions is shown in FIG. 2.

Quantitative analysis

Lipids are observed in the anion mode or cation mode of the mass spectrometer depending on the type, so quantitative analysis of LPC, PC, LPE, PE, PEp, DG, TG, Cer, SM, HexCer, SulfoHexCer in the cationic mode, LPG, PG, LPI , PI, LPA, PA were analyzed in anion mode.

The collision energy was set as shown in Table 2 below by finding the optimized value using standard materials for each lipid species.

Collision energy Geological species 20V LPE, PE, DG 25V LPC, TG, LPA 30V Cer, PA, 35V LPG, PG 40V PC, SM, HexCer 50V ST, LPI, PI

In addition, in order to correct the quantity and error, a lipid substance having an odd chain, which does not exist in vivo, was added to the sample for each type and used as an internal standard (IS). It was calibrated by dividing the peak area of the internal standard and calculating the amount of lipid.

A total of 335 individual lipid species were qualitatively analyzed according to the method described above, and the results of quantitative analysis of the total of 219 individual lipid species are shown in Table 3 below.

PC PE PG PI PA Sphingolipid Glycerolipid Total Qualitative analysis 58 37 17 36 20 27 140 335 Quantitative analysis 55 56 10 23 11 17 47 219

Quantitatively analyzed lipid species were PCA and one-way analysis of variance (ANOVA), regression analysis, receiver operating characteristic() using Minitap and SPSS (version 24.0, IBM Corp., Armonk, NY, USA) software. ROC) We performed statistical analysis such as a curve.

Example 3. Comparative analysis results of lipid species

volcano plot analysis

The fold change, which is the ratio indicating how much the lipid species increased or decreased in the individual cancer patient groups, comparing the normal group and the patient group according to the cancer type for the 219 lipid species analyzed in Example 2, and p-, indicating that these results are reliable data Volcano plots showing the value values on the x and y axes are shown in FIG.

The x-axis of FIG. 3 is a value for fold change, which means that there is no significant difference compared to the normal group as it is closer to the 0 value, and as the absolute value increases by 1, the value decreases by 2 times or more compared to the normal group. Indicates increasing. The y-axis is a value for p-value, which means that the larger the value, the more significant there is between the normal and patient groups.

Comparative analysis using the volcano plot showed both a trend of increasing and decreasing lipid changes in plasma in liver cancer and thyroid cancer, and in the case of gastric cancer, lung cancer, and colon cancer, more lipid species decreased compared to increasing lipid species. I could confirm.

Principal component analysis (PCA)

Principal component analysis (PCA) plot showing lipid species having a p-value value of less than 0.01 in the cancer patient group when compared to the normal group among 219 lipid species analyzed in Example 2 compared to the normal group is shown in FIG. 4 It is shown in.

The PCA plot makes it possible to interpret the patterns of the data by multiplying the data matrix of each individual patient by eigenvectors and expressing them as a single point in two dimensions. Based on the normal group, it shows that each cancer type shows a different pattern from the normal group, and it can be seen that different cancer types show different patterns.

Heatmap analysis

When compared with the normal group under the same conditions as the PCA plot, a difference of 3 times or more occurs in the cancer patient group, and a heatmap constructed by selecting only lipid species having a p-value of 0.01 or less is shown in FIG. 5.

Heatmap is expressed by changing the data matrix to z-score. It is expressed in blue when it has a negative value and in red when it has a positive value.

LPC showed a tendency to increase in liver and thyroid cancer compared to normal group, and gastric cancer showed a tendency to increase although there was a difference between patients. In addition, it was confirmed that LPI shows an increasing pattern only in thyroid cancer, and PI shows a tendency to increase only in liver cancer. On the contrary, PC, LPE, and PE showed a tendency to decrease in most cancer patients except thyroid cancer.

Analysis of high abundance lipid species

The present inventors compared the composition changes of high abundance species in order to confirm the trends seen in the PCA plot and the heatmap in more detail, and the results are shown in FIG. 6.

High abundance was calculated based on the normal group, and the relative abundance was calculated by dividing the peak area of each lipid species detected in one type of lipid group by the sum of the peak areas of all species detected in the lipid group. As a result, as shown in the Heatmap, LPC was found to increase in liver and stomach cancer, and LPI was also found to increase significantly more than 4 times in thyroid cancer. PE tends to decrease in all types of cancer. In addition, as in the results of Heatmap, PI showed a characteristic that increased more than 2 times only in liver cancer, and also confirmed that it increased more than 2 times in TG. Contrary to liver cancer, it was also confirmed that gastric cancer showed a characteristic that decreased more than twice in TG.

Analysis result synthesis

The present inventors synthesized the results of the analysis and selected lipid species having a high abundance lipid that is more than twice as high as the normal group and a p-value of less than 0.05, to select a total of 50 lipid species.

The selected lipid species are shown in bar graph in FIG. 7. a) is a lipid species showing significant changes in all 5 cancers, b) is 4, c) is 3, d) is 2, and e) is a lipid species characterized by only one cancer.

PI 18:1/18:0 is the only change in all cancers, and is more than doubled in liver cancer, while decreasing in the other 4 cancers. The remaining PI species, which change significantly only in liver cancer, also tend to increase as in 18:1/18:0, which is consistent with the heatmap results.

PEs with significant changes in b), c), and d) were found to have decreased characteristics in most cancer types, and LPC 16:0 and 18:2 increased in gastric cancer and thyroid cancer. Again, it was confirmed that the LPI increased in line with the results of the heatmap. Therefore, the lipid species selected in FIG. 7 were selected as lipid biomarkers for predicting cancer prognosis.

In addition, the diagnostic efficiency of selected lipid species was evaluated through the Receiver operating characteristic (ROC) curve shown in FIG. 8. Efficiency was evaluated according to the area under curve (AUC) value of the ROC curve, and it was determined that the higher the value, the higher the efficiency. The selected lipid species were targeted to 50 lipid species selected for each cancer type, and species having an AUC value of 0.8 or more are shown in FIG. 9.

As a result, among the 50 selected lipids, 8 types of liver cancer, 9 types of gastric cancer, 7 types of lung cancer, 8 types of colon cancer, and 6 types of lipid in thyroid cancer were found to have good AUC values of 0.8 or higher. Specifically, lipid species having an AUC value of 0.8 or higher include phosphatidylinositol (PI) 16:0/18:2, 16:0/20:4, 18:0/20:3, 18:1/18:0; Diacylglycerol (DG) 16:1_18:0; Phosphatidylcholine (PC) 34:2, 36:2, 36:3, 36:4; Lysophosphatidic acid (LPA) 18:2; Sphingomyelin (SM) d18:1/22:0; Lysophosphatidylinositol (LPI) 16:0, 18:0, 18:1; Triacylglycerol (TG) 50:1, 54:4; Lysophosphatidylcholine (LPC) 16:0, 18:2; Lysophosphatidylethanolamine (LPE) 16:0, 18:0, 18:1, 18:2; Phosphatidylethanolamine (PE) 36:1, 38:3, 38:4, 38:6, 16:0p/20:4, 16:1p/22:6, 18:0p/20:4, 18: 1p/18:1, 18:1p/20:4, 18:1p/22:4; As hexosylceramide (HexCer) d18:1/20:0, it was confirmed that the lipids could be used as biomarkers in cancer diagnosis or prognosis prediction.

The above description of the present invention is for illustration only, and those skilled in the art to which the present invention pertains can understand that the present invention can be easily modified into other specific forms without changing the technical spirit or essential features of the present invention. will be. Therefore, it should be understood that the embodiments described above are illustrative in all respects and not restrictive. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as distributed may be implemented in a combined form.

The scope of the present invention is indicated by the following claims, and all modifications or variations derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention.

Claims (10)

At least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And
A lipid biomarker composition for diagnosing liver cancer, comprising at least one lipid selected from the group b) consisting of lysophosphatidylcholine (LPC) and hexosylceramide (HexCer). According to claim 1,
The phosphatidylinositol (PI) is 16:0/18:2, 16:0/20:4, 18:0/20:3 or 18:1/18:0,
The diacylglycerol (Diacylglycerol, DG) is 16:1_18:0,
The lysophosphatidylcholine (LPC) is 16:0 or 18:2,
The hexosyl ceramide (Hexosylceramide, HexCer) is d18: 1 / 20: 0, lipid biomarker composition for diagnosing liver cancer. A kit for diagnosing liver cancer, comprising the composition of claim 1. 1) measuring the level of lipid expression in the patient's sample,
The lipid may include at least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And
Comprising at least one lipid selected from the group b) consisting of lysophosphatidylcholine (LPC) and hexosylceramide (HexCer); And
2) when the expression level of lipids of group a) and group b) in the sample of the patient is increased or decreased compared to the level of expression in the normal sample, the patient is judged as a liver cancer patient, which is necessary for diagnosis of liver cancer. How to provide information. According to claim 4,
1) measuring the level of lipid expression in the patient's sample,
The phosphatidylinositol is 16:0/18:2, 16:0/20:4, 18:0/20:3 or 18:1/18:0,
The diacylglycerol is 16:1_18:0,
The lysophosphatidylcholine is 16:0 or 18:2,
The hexylceramide is d18:1/20:0; And
2) Liver cancer when the level of lipid expression in the sample of the patient is increased compared to the level of expression in the normal sample a) phosphatidylinositol or diacylglycerol is decreased in the group, and b) lysophosphatidylcholine or hexylceramide is increased in the group A method for providing information necessary for diagnosing liver cancer, characterized in that it is determined to be a patient. The method of claim 4 or 5, wherein the patient's sample is a tissue, cell, whole blood, plasma, serum, blood, saliva, sputum, lymphatic fluid, cerebrospinal fluid, intercellular fluid, or urine sample. Treating the liver cancer patient sample with a liver cancer inhibitor or a liver cancer treatment agent; And
Comprising the step of measuring the expression level of the lipid before and after treatment with the liver cancer inhibitor or liver cancer treatment in the sample,
A method for monitoring liver cancer inhibitors or treatments for liver cancer. The method of claim 7,
The lipid may include at least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And
A method for monitoring liver cancer inhibitors or treatments for liver cancer, which is at least one lipid selected from the group b) consisting of lysophosphatidylcholine (LPC) and hexosylceramide (HexCer). Treating a candidate for treatment of liver cancer with a sample of liver cancer patient; And
A method of screening for a therapeutic agent for liver cancer, comprising the step of measuring the expression level of lipids before and after treating the candidate substance in the sample. The method of claim 9,
The lipid may include at least one lipid selected from the group a) consisting of phosphatidylinositol (PI) and diacylglycerol (DG); And
A lysophosphatidylcholine (LPC) and a hexyl ceramide (Hexosylceramide, HexCer) consisting of one or more lipids selected from the group, wherein the screening method for the treatment of liver cancer.

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