CN105760713A

CN105760713A - Tumor cell classifying method based on cell membrane phospholipid composition differences

Info

Publication number: CN105760713A
Application number: CN201410800403.4A
Authority: CN
Inventors: 刘云珠
Original assignee: Teach Airasia (tianjin) Education Technology Development Co Ltd
Current assignee: Teach Airasia (tianjin) Education Technology Development Co Ltd
Priority date: 2014-12-19
Filing date: 2014-12-19
Publication date: 2016-07-13

Abstract

The invention provides a tumor cell classifying method based on cell membrane phospholipid composition differences.The tumor cell classifying method comprises the steps that a gas chromatography-mass spectrometry combining technology is utilized to analyze the composition differences of cancer cell phospholipid fatty acids, but the pure gas chromatography-mass spectrometry combining technology has a certain limitations in most cases, for example, similar spectrograms produced by overlapped gas chromatography peaks and different types of cancer cells are difficult to distinguish directly.Therefore, the tumor cell classifying method applies a chemometrics method to solve the classification problem.According to the tumor cell classifying method, a partial least squares regression model is adopted to classify different types of cancer cells and can simultaneously achieve regression modeling, correlation analysis of two groups of variables and data structure simplification through one algorithm, and the variation information of response variables can be well interpreted.

Description

The tumor cell sorting technique of difference is constituted based on cell membrane phospholipid

Technical field

The invention relates to the sorting technique of tumor cell, particularly relates to partial least square model and constitutes, with cell membrane phospholipid, the sorting technique realizing tumor cell

Background technology

Malignant tumor has become as one of healthy principal disease of serious threat human life, there is high incidence and the feature of high fatality rate, latest report according to World Health Organization's IARC (IARC/WHO), to the year two thousand twenty, the sickness rate of tumor will rise 50%.The generation of tumor affects the health of economic development and people day by day, has put into the research for anti-curing oncoma of the substantial amounts of manpower and financial resources for these countries in the world.Therefore, the method taking effectively preventing tumor, the growth momentum of containment malignant tumor is extremely urgent.

A lot of diseases include tumor all with the change of phospholipid metabolism, and the change of cell membrane phospholipid can affect the physicochemical property of cell membrane, and then affects the biological function of various memebrane protein.The change of research cell membrane phospholipid not only facilitates the pathogeny illustrating these diseases and tumor, and contributes to diagnosing and treating of disease.Find that the content of phospholipid of tumor cell membrane is higher than normal cell studying in tumorigenic process, phospholipid mainly comprise the change of composition for biomacromolecule content in research tumor generating process and structure change, find new diagnosis index and therapy target is significant.The mixture containing fatty acid and phosphoric acid is produced after phospholipid hydrolysis.Lipoid fatty acid is the important component of nearly all active somatic cell membrane phospholipid, and increasing evidence shows, lipoid fatty acid is except as the skeleton of cell membrane phospholipid and energy storage form, and other that also take part in cell are much movable.Medical evidence, mankind's numerous disease all has much relations with lipoid fatty acid metabolism disorder, such as Alzheimer disease, diabetes, tumor and some infectious disease etc..Therefore, the focus of scientist's research is become about the research of cell membrane phospholipid fatty acid composition.Owing to cell membrane phospholipid turn-around speed is exceedingly fast, degrade rapidly with cell death and the structure of fatty acid of different tumor cell is not quite similar with kind.Due to the restriction of detection technique, film fat analysis is limited to the Analysis and Identification to overall lipid total amount more, due to the overlap of different fatty acid chromatographic peaks, the research of different tumor cell phospholipid composition differences is more difficult.

Summary of the invention

The problem that the invention to solve is, existing film fat analysis is limited to the Analysis and Identification to overall lipid total amount more, due to the overlap of different fatty acid chromatographic peaks, the research of different tumor cell phospholipid composition differences is more difficult, is unfavorable for the discriminating of tumor cell classification.

For solving above-mentioned technical problem, the invention the technical scheme is that and utilizes GC-MS technical Analysis tumor cell lipoid fatty acid composition difference, but simple GC-MS analytical technology often exists certain limitation, such as direct differentiation is difficult to for similar spectral produced by overlapping gas chromatogram peak and different types of cancerous cell.Therefore, the present invention adopts Partial Least-Squares Regression Model that different types of tumor cell is classified, Partial Least-Squares Regression Model can realize the simplification of the correlation analysis between regression modeling, two groups of variablees and data structure under an algorithm simultaneously, can explain the variation information of response variable well.Specifically comprise the following steps that

1) extraction of the cultivation of tumor cell and cell membrane phospholipid；

2) cell membrane phospholipid esterification and GC-MS technical Analysis: the cell membrane of tumor cell is carried out esterification process, by the fatty acid finger printing of GC-MS technology herborization oil；

3) set up Partial Least-Squares Regression Model tumor cell is classified.

Further, step 1) extracting method of described cell membrane phospholipid is: by the cell suspension collected in PBS, be settled to 1.5mL, by cell suspending liquid in ultrasonic cell disruptor under condition of ice bath rupture of membranes 50min.Taking the rupture of membranes liquid of certain volume in the mixed liquor of methanol and chloroform, concussion shakes up, and room temperature stands, phase under centrifuging and taking.

Further, step 2) method of described cell membrane phospholipid esterification is: in cell membrane phospholipid extracting solution, add the potassium hydroxide-methanol solution of 2mL1mol/L, 60 DEG C of water-bath 10min carry out esterification, obtain the fatty acid of esterification, add 2mL2mol/L hydrochloric acid, jolting, stand, add appropriate anhydrous sodium sulfate to dry, take subnatant to be measured.

Further, step 2) described GC-MS analysis condition is: gas chromatographic column is capillary column, model is DB-5MS, injector temperature is 250 DEG C, and the heating schedule of furnace temperature is initial temperature 100 DEG C, rises to 220 DEG C with 15 DEG C/min, retain 2min, rise to 250 DEG C with 10 DEG C/min, rise to 260 DEG C with 2 DEG C/min, retain 1.5min, sample size is 1 μ L, injection port takes not shunt mode, and carrier gas is helium, and its flow is 1mL/min, data acquisition modes is total ions chromatogram, ion source is EI, and its temperature is 250 DEG C, and transmission line temperature is 250 DEG C.

Further, step 3) when setting up model, the GC-MS fatty acid information of the cell sample of collection is randomized into two data sets, i.e. training set and forecast set, training set and all wrap the sample of all kinds of tumor cell in forecast set.Training set is used for building Partial Least-Squares Regression Model, it was predicted that collection is for proving the classification performance of Partial Least-Squares Regression Model

The invention has the advantage that and has the benefit effect that

1) Partial Least-Squares Regression Model can the tumor cell sample of all training sets of Accurate Prediction and forecast set, the predictive ability of training set discrimination and forecast set is all very strong, illustrates that PLS disaggregated model is for having good performance in the classification of variety classes tumor cell.

2) present invention for the change of biomacromolecule content and structure in research tumor generating process, find new diagnosis index and therapy target is significant.

Detailed description of the invention

1) cultivation of tumor cell and collection:

Tetra-kinds of cells of Hela, MCF-7, SMMC-7721, CEM are inoculated in RPMI1640 culture fluid respectively, are positioned over 5%CO₂In incubator, 37 DEG C of cultivations, after at the bottom of cell is paved with bottle, wash three times with PBS, then with containing 0.5% (w/v) tryptic buffer peptic cell, adding appropriate culture medium, collect cell.Cell in culture bottle is discarded a part, in remaining cell suspending liquid, adds RPMI1640 culture fluid, treat use next time.

2) extraction of cell membrane phospholipid

By collect cell suspension in PBS, be settled to 1.5mL, by cell suspending liquid in ultrasonic cell disruptor under condition of ice bath rupture of membranes 50min.Taking the rupture of membranes liquid of certain volume in the mixed liquor of 1mL methanol and 2mL chloroform, concussion shakes up, and room temperature stands 10min, centrifuge 4000r/min and is centrifuged 20min, takes off phase.

3) cell membrane phospholipid esterification

The KOH/CH of 2mL1mol/L is added in aforesaid liquid₃OH solution, 60 DEG C of water-bath 10min carry out esterification, obtain the fatty acid of esterification, add 2mL2mol/L hydrochloric acid, jolting, stand, add appropriate anhydrous sodium sulfate and dry, take subnatant to be measured.

4) the GC-TOFMS analysis condition of cancerous cell phospholipid esterification

nullGC conditions: gas chromatographic column is capillary column，Model is DB-5MS30m*0.25mm*0.25 μm，Injector temperature is 250 DEG C，Sample size is 1 μ L，The heating schedule of furnace temperature is initial temperature 100 DEG C，220 DEG C are risen to 15 DEG C/min，Retain 2min，250 DEG C are risen to 10 DEG C/min，260 DEG C are risen to 2 DEG C/min，Retain 1.5min，Sample size is 1 μ L，Injection port takes not shunt mode，Carrier gas is helium，Its flow is 1mL/min，Data acquisition modes is total ions chromatogram，Ion source is EI，Its temperature is 250 DEG C，Transmission line temperature is 250 DEG C，Ion source is EI，Ion source temperature is 250 DEG C，Transmission line temperature is 250 DEG C，Voltage is 1500V，Electron energy is-70eV.

5) based on content of fatty acid in the GC-MS different tumor cells analyzed

Four kinds of tumor cells contain some identical fatty acid, but the content of fatty acid but differs, and detailed data is in Table 1

The fatty acid composition of the different tumor cell of table 1

Note: "-" represents in this cell without this type of fatty acid

6) Partial Least-Squares Regression Model classification results to tumor cell

With table 1 data construct sample matrix, when setting up model, 48 tumor cell samples of collection are randomized into two data sets, and wherein training set has 35 samples, it was predicted that collection has 13 samples, training set and all comprise the sample of four class tumor cells in forecast set.Training set is used for building Partial Least-Squares Regression Model, it was predicted that collection is for proving the classification performance of Partial Least-Squares Regression Model.So-called discrimination refers to that training set sample is carried out the ratio of correct classification by mode identification method；Predictive ability refers to that forecast set sample is carried out the ratio of correct classification by the discrimination model of foundation.Table 2 lists Partial Least-Squares Regression Model prediction different pieces of information and concentrates the result of tumor cell classification.

Table 2 Partial Least-Squares Regression Model identification and classification result to training set and test set sample respectively

Be we can see that by upper table: Partial Least-Squares Regression Model can 48 samples of four class tumor cells of all training sets of Accurate Prediction and forecast set, the predictive ability of training set discrimination and forecast set is 100%, illustrates that PLS disaggregated model is for having good performance in the classification of variety classes tumor cell.

Claims

1. constitute the tumor cell sorting technique of difference based on cell membrane phospholipid, it is characterised in that comprise the steps:

3) set up Partial Least-Squares Regression Model tumor cell is classified.

2. the tumor cell sorting technique of difference is constituted according to claim 1 based on cell membrane phospholipid, it is characterized in that step 1) in the extracting method of cell membrane phospholipid be: by the cell suspension collected in PBS, it is settled to 1.5mL, by cell suspending liquid in ultrasonic cell disruptor under condition of ice bath rupture of membranes 50min, take the rupture of membranes liquid of certain volume in the mixed liquor of methanol and chloroform, concussion shakes up, and room temperature stands, phase under centrifuging and taking.

3. the tumor cell sorting technique of difference is constituted according to claim 1 based on cell membrane phospholipid, it is characterized in that step 2) in the method for cell membrane phospholipid esterification be: in cell membrane phospholipid extracting solution, add the potassium hydroxide-methanol solution of 2mL1mol/L, 60 DEG C of water-bath 10min carry out esterification, obtain the fatty acid of esterification, add 2mL2mol/L hydrochloric acid, jolting, stand, add appropriate anhydrous sodium sulfate to dry, take subnatant to be measured.

4. the tumor cell sorting technique of difference is constituted according to claim 1 based on cell membrane phospholipid, it is characterized in that step 2) in GC-MS analysis condition be: gas chromatographic column is capillary column, model is DB-5MS, injector temperature is 250 DEG C, the heating schedule of furnace temperature is initial temperature 100 DEG C, 220 DEG C are risen to 15 DEG C/min, retain 2 minutes, 250 DEG C are risen to 10 DEG C/min, 260 DEG C are risen to 2 DEG C/min, retain 1.5 minutes, sample size is 1 μ L, injection port takes not shunt mode, carrier gas is helium, its flow is 1mL/min, data acquisition modes is total ions chromatogram, ion source is EI, its temperature is 250 DEG C, transmission line temperature is 250 DEG C.

5. the tumor cell sorting technique of difference is constituted according to claim 1 based on cell membrane phospholipid, it is characterized in that step 3) in when setting up model, the GC-MS fatty acid information of the cell sample collected is randomized into two data sets, i.e. training set and forecast set, training set and forecast set are all wrapped the sample of all kinds of tumor cell, training set is used for building Partial Least-Squares Regression Model, it was predicted that collection is used for proving Partial Least-Squares Regression Model.