CN109735619A - Molecular markers associated with prognosis of non-small cell lung cancer and their applications - Google Patents
Molecular markers associated with prognosis of non-small cell lung cancer and their applications Download PDFInfo
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Abstract
本发明提供了与非小细胞肺癌预后相关的分子标志物及其应用。本发明结合非小细胞肺癌(NSCLC)基因芯片表达数据集，利用随机森林法和Cox单因素回归分析，在候选基因中找到表达水平与病人生存期显著相关的基因，对这些基因利用Cox多因素回归分析进行生存分析的建模，并用Kaplan Meier方法和时间依赖的ROC分析方法评价模型的表现，得到17个基因的肺癌预后标签集，这17个基因中的特定基因组合分别对术后病人进行生存期长短和复发风险高低分级，以进行个体化的治疗。该分子标志物不受NSCLC组织类型、疾病分期、年龄、性别等因素影响，可以作为NSCLC预后评价工具，并且对NSCLC患者具有普遍的适用性。The present invention provides molecular markers related to the prognosis of non-small cell lung cancer and applications thereof. The present invention combines the non-small cell lung cancer (NSCLC) gene chip expression data set, uses random forest method and Cox single factor regression analysis, finds genes whose expression level is significantly correlated with the patient's survival period in candidate genes, and uses Cox multi-factors for these genes. Regression analysis was performed to model the survival analysis, and the Kaplan Meier method and time-dependent ROC analysis method were used to evaluate the performance of the model, and a lung cancer prognosis signature set of 17 genes was obtained. Survival length and recurrence risk are graded for individualized treatment. The molecular marker is not affected by NSCLC tissue type, disease stage, age, gender and other factors, can be used as a prognostic evaluation tool for NSCLC, and has general applicability to NSCLC patients.
Description
Technical field
The present invention relates to field of medical molecular biology, the especially evaluation of lung cancer patient postoperative recurrence and direction of medication usage technology
Field, and in particular to molecular marker relevant to non-small cell lung cancer prognosis and its application.
Background technique
Lung cancer is one of most common malignant tumour.Lung cancer includes Small Cell Lung Cancer and non-small cell lung cancer, wherein non-small
Cell lung cancer accounts for the 85% of lung cancer entirety disease incidence.Non-small cell lung cancer on tissue morphology mainly include squamous carcinoma and gland cancer,
Its main feature is that Development process is slow, transfer diffusion is not noticeable.
Patients with Non-small-cell Lung is easy to recur and shift, therefore cure rate is extremely low, and the postoperative five year survival rate of patient is insufficient
15%.Although the diagnosing and treating of non-small cell lung cancer has apparent progress in recent years, there is no effectively about non-small
The prognostic markers object of cell lung cancer.In real work, cancer types of most of clinician according to patient, pathological staging
And the clinical indices such as related drugs reaction are treated, and judge the postoperative next step therapeutic scheme of patient.But lung cancer conduct
A kind of different substantiality disease, individual's difference is obvious, even if the identical individual of pathologic classifications, can still generate different drugs
Reaction, different therapeutic effects, different recurrence times etc., prognosis situation is complicated and is difficult to judge.Therefore, developing has height
The molecule prognostic markers object of sensitivity and pinpoint accuracy is significant to the clinical treatment for instructing non-small cell lung cancer.
Clinicopathologic Observation different from the past, the molecular marked compound based on gene expression dose can more accurately
Predict survival probability, risk of recurrence, providing for postoperative patient has targetedly individuation supplemental treatment regimens.Therefore, this hair
The bright prognostic markers object for being intended to provide non-small cell lung cancer clinically provides for the postoperative adjuvant therapy scheme of patients with lung cancer a
The guidance of body.
Summary of the invention
The first purpose of this invention is to provide the molecular labeling of effective judging prognosis for Patients with Non-small-cell Lung
Object, i.e., molecular marker relevant to non-small cell lung cancer prognosis.
A second object of the present invention is to provide the prognostic evaluation kits of non-small cell lung cancer patient.
Third object of the present invention is to provide the postoperative progress life cycle length of a kind of couple of non-small cell lung cancer patient and again
Send out the appraisement system of the high harmonic analysis of risk, auxiliary direction clinical treatment.
The purpose of the present invention is what is be achieved through the following technical solutions: the present invention determines candidate gene collection first.Has report
Road claims the exocytosis albumen in tumor microenvironment, plays an important role to the occurrence and development of tumour.In lung cancer early period of origination, swell
Oncocyte actively can convert surrounding fibroblast to exocytosis excretion body, and promoting fibroblast activation is that tumour is related
Fibroblast, and change the level to exocytosis albumen, lead to the remodeling of tumour cell microenvironment, be conducive to tumour
Further development.Therefore, these are influenced by tumour excretion body, development of the albumen to change to exocytosis level to tumour
It is most important.Theoretically, the corresponding gene of these albumen no less important in the development of tumour.In tumor tissues, these bases
Occurrence and development important role of the change of the expression of cause to tumour.Therefore, the present invention is by the volume of differential secretion albumen
Code gene is as the candidate gene for judging non-small cell lung cancer patient's prognosis performance.To further reduce candidate gene range, this
Invention, which combines, has disclosed the non-small cell lung cancer gene chip expression data set that multiple research institutions for delivering obtain, using with
The method and Cox single-factor regressioning analysis of machine forest, find expression in above-mentioned candidate gene and patient's life cycle is significant
Relevant one group of gene.Then, the modeling for being carried out survival analysis using Cox multinomial logistic regression to this group of gene, is used in combination
The performance of Kaplan Meier method and time dependent ROC (receiver operating curves) analysis method evaluation model.Finally,
To the lung cancer for prognosis tally set of one group of 17 gene, specific gene combination in this 17 genes is respectively to judging non-small cell lung
The Postoperative determination of carninomatosis people has remarkable effect.
Specifically, the present invention provides molecular marker relevant to non-small cell lung cancer prognosis, be COL6A1,
PLOD2、CTSZ、STMN2、EIF3B、SEPT2、GSR、DYNC1H1、SEC23A、MARCKS、TUBB、NRP1、LRP1、EIF5A、
One or more of ARSA, CD81, ANPEP.
Preferably, the present invention provides molecular markers relevant with non-small cell lung cancer prognosis below to combine, are as follows:
(1)PLOD2,EIF3B,SEC23A,MARCKS；Or
(2)PLOD2,EIF3B,MARCKS,LRP1；Or
(3)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS；Or
(4)COL6A1,PLOD2,EIF3B,LRP1,ANPEP；Or
(5)PLOD2,EIF3B,SEPT2,SEC23A,MARCKS；Or
(6)PLOD2,EIF3B,MARCKS,NRP1,LRP1；Or
(7)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,MARCKS；Or
(8)PLOD2,EIF3B,SEPT2,SEPT2,SEC23A,MARCKS；Or
(9)PLOD2,EIF3B,DYNC1H1,MARCKS,NRP1,LRP1；Or
(10)COL6A1,PLOD2,CTSZ,EIF3B,DYNC1H1,MARCKS；Or
(11)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,MARCKS；Or
(12)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,NRP1；Or
(13)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,ANPEP；Or
(14)PLOD2,EIF3B,SEPT2,MARCKS,TUBB,LRP1,ANPEP；Or
(15)PLOD2,EIF3B,DYNC1H1,SEC23A,MARCKS,LRP1,ANPEP；Or
(16)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEPT2,MARCKS；Or
(17)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,DYNC1H1,SEC23A；Or
(18)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEC23A,MARCKS；Or
(19)COL6A1,PLOD2,CTSZ,EIF3B,DYNC1H1,MARCKS,MARCKS；Or
(20)COL6A1,PLOD2,CTSZ,EIF3B,SEC23A,MARCKS,MARCKS；Or
(21)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,MARCKS,NRP1；Or
(22)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEPT2,DYNC1H1,SEC23A；Or
(23)COL6A1,PLOD2,CTSZ,SEPT2,SEPT2,DYNC1H1,SEC23A,LRP1；Or
(24)EIF3B,SEPT2,DYNC1H1,SEC23A,MARCKS,MARCKS,NRP1,LRP1；Or
(25)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEPT2,DYNC1H1,MARCKS,ANPEP；Or
(26)PLOD2、EIF3B、SEPT2、DYNC1H1、SEC23A、MARCKS、MARCKS、NRP1、LRP1。
Preferably, in an embodiment of the present invention, combination a for (1), corresponding probe are respectively as follows: 202619_
s_at,211501_s_at,204344_s_at,201668_x_at；
Combination a for (2), corresponding probe are respectively as follows: 202619_s_at, 211501_s_at, 201668_x_
at、1555353_at
Combination a for (3), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at, 201668_x_at, or,
216904_at,202619_s_at,212562_s_at,211501_s_at,213002_at；
Combination a for (4), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 211501_s_at,
1555353_at,234576_at,；
Combination a for (5), corresponding probe are respectively as follows: 202619_s_at, 211501_s_at, 1554747_a_
at,204344_s_at,201668_x_at；Or
202619_s_at,211501_s_at,200778_s_at,204344_s_at,201668_x_at；
Combination a for (6), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 213002_at,
210615_at,1555353_at；
Combination a for (7), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,213002_at；
Combination a for (8), corresponding probe are respectively as follows: 202619_s_at, 211501_s_at, 200778_s_
at,1554747_a_at,204344_s_at,201668_x_at；
Combination a for (9), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 229115_at,
213002_at,210615_at,1555353_at；
Combination a for (10), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,229115_at,213002_at；
Combination a for (11), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,201668_x_at,213002_at；
Combination a for (12), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,213002_at,210615_at；
Combination a for (13), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,213002_at,234576_at；
Combination a for (14), corresponding probe are respectively as follows: 202619_s_at, 211501_s_at, 200778_s_
at,201668_x_at,209026_x_at,1555353_at,234576_at；
Combination a for (15), corresponding probe are respectively as follows: 202619_s_at, 211501_s_at, 229115_
at,204344_s_at,213002_at,1555353_at,234576_at；
Combination a for (16), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,1554747_a_at,200778_s_at,213002_at；
Combination a for (17), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,1554747_a_at,229115_at,204344_s_at；
Combination a for (18), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,1554747_a_at,204344_s_at,213002_at；
Combination a for (19), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,229115_at,201668_x_at,213002_at；
Combination a for (20), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,204344_s_at,201668_x_at,213002_at；
Combination a for (21), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,201668_x_at,213002_at,210615_at；
Combination a for (22), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,1554747_a_at,200778_s_at,229115_at,204344_s_at；
Combination a for (23), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,1554747_a_at,200778_s_at,229115_at,204344_s_at,1555353_at；
Combination a for (24), corresponding probe are respectively as follows: 211501_s_at, 200778_s_at, 229115_
at,204344_s_at,201668_x_at,213002_at,210615_at,1555353_at；
Combination a for (25), corresponding probe are respectively as follows: 216904_at, 202619_s_at, 212562_s_
at,211501_s_at,1554747_a_at,200778_s_at,229115_at,213002_at,234576_at；
Combination a for (26), corresponding probe are respectively as follows: 202619_s_at, 211501_s_at, 200778_s_
at、229115_at、204344_s_at、201668_x_at、213002_at、210615_at、1555353_at。
Above-mentioned probe identity is the chip from Affymetrix U133 series.In one embodiment of the invention, institute
Probe is stated from 2.0 chip of Affymetrix U133.
The present invention provides above-mentioned molecular markers to prepare non-small cell lung cancer patient's prognostic evaluation kit, reagent
Or the application in chip.
The present invention provides above-mentioned molecular markers to prepare non-small cell lung cancer patient's shorter survival length or answer
Send out the application in risk height appraisement system.
The present invention provides above-mentioned molecular markers in preparing the postoperative direction of medication usage system of non-small cell lung cancer patient
Application.
Preferably, the system is kit or medicine box or instrument for the purpose of Treatment for Non-small Cell Lung.
It is stored non-small according to the existing life containing patient for the molecular marker of each above-mentioned combination of the present invention
As training set, (training set that the embodiment of the present invention uses is from random integration to cell lung cancer tumors tissue gene expression database
Three data concentrate at random pick 50% sample), can establish the multifactor regression model of corresponding Cox, obtain simultaneously
This kind combines the coefficient and risk score critical value of the corresponding probe variable of each gene.For each after predicting surgical
The Survival of patient, corresponds to the expression value of probe by detecting patient's tumor tissues, and by the corresponding band of these expression values
Enter into established regression model, the value acquired is the risk score of the patient.The risk score of the patient with before
To risk score critical value compare, higher than the risk score of the critical value, indicate that patient's shorter survival is short, recurrence may
Property is big；Lower than the risk score of the critical value, it is long to identify patient's shorter survival, and recurrence possibility is small.
The present invention provides a kind of kit, contains the detection reagent and/or inspection for detecting molecular marker of the present invention
Survey instrument；The kit is non-small cell lung cancer patient prognostic evaluation kit, non-small cell lung cancer patient's shorter survival
Length or risk of recurrence height kits for evaluation or the postoperative direction of medication usage kit of non-small cell lung cancer patient.
Present invention combination non-small cell lung cancer (NSCLC) gene chip expression data set, it is mono- using random forest method and Cox
Cox regression analysis finds expression and patient's life cycle significant relevant gene in candidate gene, to these genes benefit
The modeling of survival analysis is carried out with Cox multinomial logistic regression, and is analyzed with Kaplan Meier method and time dependent ROC
The performance of method evaluation model obtains the lung cancer for prognosis tally set of 17 genes, the above-mentioned specific gene group in this 17 genes
It closes and life cycle length and risk of recurrence height classification is carried out to postoperative patient NSCLC respectively, and then prompt clinic to different crowd
Carry out the adjuvant treatment of corresponding individuation.In addition, organization type, disease of the molecular marked compound independently of non-small cell lung cancer
By stages, age, gender and the factors such as whether smoke.Therefore, it is reliable to can be used as NCSCL for molecular marker provided by the invention
Prognostic evaluation tool, and to Patients with Non-small-cell Lung have universal applicability.
Detailed description of the invention
Fig. 1 is to identify that lung cancer excretion body influences one group of molecule of fibroblast differential secretion in embodiment 1: A is transmission
The lung cancer excretion volume morphing and size (Bar=200nm) of Electronic Speculum observation；B is that dynamic light scattering detects lung cancer excretion body partial size point
Cloth；C is the expression that western Blot detects lung cancer excretion body surface marker CD63, shows that isolated precipitating is non-small
The excretion body of cell lung cancer secretion；D be analysis of biological information compare by lung cancer excretion body handle fibroblast and normally at
Fibrocyte secretion the albumen that there were significant differences, the albumen of the lung fibroblast secretion of lung cancer excretion body processing with normally at
Fibrocyte secretion albumen, obtained by mass spectrum sequencing analysis, with the presence of 302 albumen expression significant difference (i.e.
Fold differences are greater than 1.5, and conspicuousness P value is less than 0.05).
Fig. 2 is the foundation of non-small cell lung cancer prognostic model in embodiment 2: one group of assortment of genes label is in training set
The statistical analysis of Kaplan-Meier, log-rank examine, the results showed that this group of prognostic gene can distinguish life cycle it is short and existence
The non-small cell lung cancer patient of phase length.
Fig. 3 A- Fig. 3 D is verifying of the non-small cell lung cancer prognostic model to prediction overall survival: one group of assortment of genes mark
The statistical analysis of the Kaplan-Meier concentrated in a verifying collection and three independent tests is signed, log-rank is examined, as a result table
Bright this group of prognostic gene can distinguish the non-small cell lung cancer patient that life cycle is short and life cycle is long.
Fig. 4 A- Fig. 4 D is that non-small cell lung cancer prognostic model predicts overall survival ROC curve analysis in 5 years: one group of gene
The time dependent ROC curve analysis that combination tag is concentrated in a verifying collection and three independent tests, the results showed that the prognosis
The assortment of genes can significantly distinguish the non-small cell lung cancer patient of high mortality and low actual in 5 years.
Fig. 5 A- Fig. 5 D is verifying of the non-small cell lung cancer model to prediction cancer relapse risk: one group of assortment of genes label
In the statistical analysis for the Kaplan-Meier that four individual authentications are concentrated, log-rank inspection result shows this group of prognostic gene energy
Enough distinguish the non-small cell lung cancer patient of high relapse rate and low recurrence rate.
Fig. 6 A- Fig. 6 D is that non-small cell lung cancer prognostic model predicts recurrence-free survival rate ROC curve analysis in 5 years, one group of base
The time dependent ROC curve analysis concentrated by combination tag in four individual authentications, the results showed that the prognostic gene combines energy
The significant non-small cell lung cancer patient for distinguishing high relapse rate and low recurrence rate in 5 years.
Specific embodiment
Following embodiment further illustrates the contents of the present invention, but should not be construed as limiting the invention.Without departing substantially from
In the case where spirit of that invention and essence, to modifications or substitutions made by the method for the present invention, step or condition, the present invention is belonged to
Range.
Unless otherwise specified, the materials, reagents and the like used in the following examples is commercially available；In embodiment
The conventional means that technological means used is well known to those skilled in the art.If not specified, lung described in following embodiment
Cancer cell is non-small cell lung cancer cell.
1 lung cancer excretion body of embodiment converts fibroblast and influences the protein level to exocytosis
It extracts the excretion body of non-small cell lung cancer secretion: collecting the serum free medium supernatant of culture lung cancer cell line.4
DEG C, 3000g is centrifuged 15 minutes, and supernatant is taken to be placed in new centrifuge tube.4 DEG C, 16000g is centrifuged 1 hour, takes supernatant to be placed in new
In centrifuge tube.4 DEG C, 120000g is centrifuged 2 hours, abandons supernatant.Sediment, i.e. excretion body exosomes is resuspended in PBS.Electronic Speculum identification
The excretion body structure being collected into: taking 10ul re-suspension liquid, drips on carbon containing copper mesh, and 2% uranium acetate is added after drying, and stands
5min, rinses 2min with PBS, draws surplus liquid with filter paper, cleans and dry afterwards three times repeatedly.It is seen under 80kV voltage transmission electron microscope
Examining excretion body structure is the film balloon-shaped structure with membrane bound, as a result as the A of Fig. 1 is shown.
Whole particle diameter distribution research is carried out to the excretion body being collected into: using Britain Malven company Nanosight3000
Re-suspension liquid is diluted to appropriate optical signalling detection level with PBS again, detected after mixing, the results showed that be collected by instrument
Excretion body vesicle diameter is in 30-200nm range, and as a result the B of such as Fig. 1 is shown, shows that the vesicle diameter being collected into meets excretion body
The range of diameter.
With the surface protein marker for the excretion body that the method validation of western blotting is collected into: utilizing BCA egg
White measuring method measures re-suspension liquid protein concentration, takes the resuspension fluids containing 1 μ g albumen, detects surface egg with western blotting
White marker object CD63, TSG101.Detect excretion body surface region feature PROTEIN C D63 and TSG101, using mouse monoclonal antibody (1:
1000 dilutions)；Cell characteristic albumen Tubulin is detected, using mouse monoclonal antibody (1:4000 dilution)；Detect internal reference albumen
GAPDH uses rabbit polyclonal antibody (1:10000 dilution).As a result as the C figure of Fig. 1 shows that the film bubble being collected into has excretion body mark
Remember object CD63 and TSG101 expression, but without the expression of cell characteristic albumen Tubulin, illustrates that the film bubble being collected into is excretion
Body.
Tumour excretion body is incubated for lung fibroblast: the tumour excretion liquid solution of resuspension is added to culture fibroblast
Culture medium in, tumour excretion liquid solution (the MEM culture medium+tumour excretion for containing 6 μ g is added in the every hole in three holes in 6 orifice plates
Body), the control medium (MEM culture medium) for being free of tumour excretion body is added in the other three hole, after being incubated for 72 hours, by culture medium
It is uniformly replaced with fresh serum free medium (MEM culture medium), then is incubated for 48 hours, supernatant is collected.4 DEG C, 3000g centrifugation
It 15 minutes, collects supernatant and mass spectrum sequencing is carried out to protein solution, microarray dataset is equipped with QExactive software
3000 machine of Thermo Ultimate.By the initial sequence information measured and database human Uniprot (version
2018.1) compare after, respectively obtain with tumour excretion body be incubated for fibroblast and unused tumour excretion body be incubated at fibre
Tie up the extracellular protein spectrum of cell secretion.Then, 302 are shared with the secretory protein of bioinformatics method comparing difference.As a result
If the D figure of Fig. 1 is shown, the standard for choosing differential secretion albumen is that fold differences are greater than 1.5, and significance of difference P value is less than 0.05.
Using this corresponding gene of 302 differential proteins as the gene sets for finding the tumor prognosis factor.
Embodiment 2 establishes non-small cell lung cancer prognostic model
In order to establish reliable non-small cell lung cancer prognostic model, the present invention collects, band relevant to non-small cell lung cancer
There is raw stored data set.The specific sample information of data set is shown in Table 1, table 2.
The non-small cell lung cancer patient information relevant to overall survival of table 1
The non-small cell lung cancer patient information relevant to recurrence-free survival rate of table 2
The experiment porch of data set is Affymetrix U133Plus2.0 chip.To the gene table of each data set
The standardization of Z value, i.e. (average value of the gene expression values-gene expression values in data set)/(gene expression values are carried out up to value
Standard deviation in data set) ("-" represents minus sign, and "/" represents the division sign), three data set GSE50081 are then randomly selected,
GSE37745 and GSE101929 totally 409 samples, and these three data sets are combined, therefrom randomly select 205 samples
This is as training set, and remaining 204 samples are as verifying collection (validation set).The relevant gene set packet of overall survival
Include GSE3141, GSE31210, GSE30219.The relevant gene set of recurrence-free survival rate includes GSE31210, GSE30219,
GSE8894,GSE50081.This seven data sets are as individual authentication data set (testing set).Then, analysis is obtained
The titles of 302 differential secretion albumen correspond to corresponding gene, and be applied in training set, pass through the method for random forest
Find the gene having a major impact to life cycle.
Cox single-factor regressioning analysis is carried out, picks out 17 and the significant relevant gene (p < 0.05) of patient's existence, this 17
The gene information of a prognosis label is shown in Table 3.
3 prognosis label gene of table
Then, totally 19 probes corresponding to this 17 genes carry out random combination without repetition, combine for each,
Analyzed by Cox Model is carried out in training set, establishes prognostic model, utilizes the corresponding probe variable of each gene in model
Coefficient and expression value, calculate the corresponding risk score critical value for being directed to the model.Further verify having for the model
Effect property, with obtained prognostic model and risk score critical value respectively in the relevant 1 verifying collection of overall survival and 3 independences
In test set and the relevant independent test of 4 recurrence-free survival rates concentrates and carries out Kaplan-Meier survival analysis, is used in combination
Log-rank test tests.Finally, it is concentrated in training set and 1 verifying collection and 7 independent tests, log-rank
The multifactor regression model of Cox that the P value of test inspection result is respectively less than 0.05 is left the prognostic model of non-small cell lung cancer, altogether
28.Any model, patient that can be significantly long by shorter survival and short life cycle distinguish, can also significantly will be postoperative
High risk of recurrence patient and low risk of recurrence patient distinguish.The molecular combinations of model are shown in Table 4.Prediction model is shown in Table 5.Prediction model
Obtained risk score critical value is shown in Table 6.
The assortment of genes of 4 non-small cell lung cancer prognostic model of table
5 prognostic model of table
Note: the probe title in table 5 is expressed as the expression value of the probe, and the corresponding formula of Gene Name can be counted in table 5
Calculate risk score (" * " indicates multiplication sign)
6 prognostic model risk score critical value of table
| The assortment of genes | Risk score critical value | The assortment of genes | Risk score critical value |
| 1 | -0.004284 | 15 | -0.014003 |
| 2 | 0.003898 | 16 | -0.036386 |
| 3 | -0.040707 | 17 | 0.003143 |
| 4 | -0.003746 | 18 | -0.010045 |
| 5 | -0.055524 | 19 | -0.033844 |
| 6 | -0.000928 | 20 | 0.005911 |
| 7 | -0.003877 | 21 | -0.009103 |
| 8 | 0.013358 | 22 | 0.005290 |
| 9 | -0.025576 | 23 | 0.005758 |
| 10 | -0.000036 | 24 | 0.003738 |
| 11 | -0.004525 | 25 | -0.033186 |
| 12 | -0.020949 | 26 | -0.024634 |
| 13 | -0.003874 | 27 | 0.005087 |
| 14 | 0.007349 | 28 | -0.028955 |
Prognosis prediction is carried out to lung cancer patient using above-mentioned prognostic model, any model is chosen, according to each patient's
The model gene combines corresponding probe collection expression value, calculates the risk score of each patient.The risk score be greater than pair
The patient of the risk score critical value of model is answered to be classified as high risk of recurrence patient or life cycle short patient, less than corresponding model
The patient of risk score critical value is classified as the patient of low risk of recurrence patient or life cycle length.
From above-mentioned prognostic model, for choosing the prognostic model that one is made of 5 probe collection, gene therein are as follows:
SEC23A, PLOD2, MARCKS, SEPT2, EIF3B.Fig. 2 is shown in performance of the prognostic model of 5 gene in training set.Fig. 2 is
For " SEC23A, PLOD2, MARCKS, SEPT2, EIF3B " combine the model established by training set, use Kaplan-Meier
Analysis, the P value that log-rank test is obtained have conspicuousness (P < 0.05).Table 7 is non-small cell lung cancer prognostic model in training
It concentrates and carries out Kaplan-Meier survival analysis, and the result tested with log-rank test.
The Kaplan-Meier existence point in overall survival training set of 7 non-small cell lung cancer prognostic gene combination tag of table
Analysis, log-rank test inspection result
The application of 3 non-small cell lung cancer prognostic model of embodiment
Non-small cell lung cancer prognostic model obtained in the training set that embodiment 2 is obtained is separately to a verifying
Collection, three independent test collection relevant to overall survival and four independent tests relevant with recurrence-free survival are concentrated, to postoperative
Patient carries out the prediction of the risk of recurrence of survival risk and disease.
The relevant data set of overall survival is given birth to the non-small cell lung cancer prognostic model that above-mentioned 5 probes form
For depositing rate prediction, the risk score that related data concentrates each patient, the risk point of patient are obtained according to the prognostic model
Number is classified as high risk patient greater than the corresponding risk score critical value of the prognostic model, and the risk score of patient is less than the base
Low-risk patient is classified as because of the corresponding risk score critical value of built-up pattern.It is postoperative according to obtained prediction result and patient
The conspicuousness P value that survival condition carries out Kaplan-Meier survival analysis calculates.P value shows that the prognostic model can less than 0.05
To predict the long patient of shorter survival and the short patient of shorter survival.
Fig. 3 is prediction of the model to postoperative overall survival.Fig. 3 A is the Kaplan- concentrated to the model in verifying
The significance analysis of Meier survival analysis.Fig. 3 B is the Kaplan-Meier to the model in independent test collection GSE30219
The significance analysis of survival analysis.Fig. 3 C is the Kaplan-Meier existence point to the model in independent test collection GSE31210
The significance analysis of analysis.Fig. 3 D is the significant of Kaplan-Meier survival analysis of the model in independent test collection GSE3141
Property analysis.Fig. 4 is the ROC curve analysis of non-small cell lung cancer prognostic model prediction overall survival.Fig. 4 A is that the model is being tested
5 years overall survival ROC curves analysis that card is concentrated.Fig. 4 B is 5 year totality of the model in independent test collection GSE30219
The analysis of survival rate ROC curve.Fig. 4 C is 5 year overall survival ROC curves of the model in independent test collection GSE31210 point
Analysis.Fig. 4 D is 5 year overall survival ROC curves analysis of the model in independent test collection GSE3141.
Similar, the non-small cell lung cancer prognostic model formed with above-mentioned 5 probes is to the relevant number of recurrence-free survival rate
For carrying out the prediction of recurrence-free survival rate according to collection, the risk point that related data concentrates each patient is obtained according to the prognostic model
Number, the height that is classified as that the risk score of patient is greater than the corresponding risk score critical value of the prognostic model recur patient, patient's
Risk score is classified as low recurrence patient less than the corresponding risk score critical value of the assortment of genes model.It is pre- according to what is obtained
It surveys result and patient's postoperative survival situation carries out the conspicuousness P value calculating of Kaplan-Meier survival analysis.P value less than 0.05,
Show that the prognostic model can predict the high patient of Postoperative recurrent rate and the low patient of Postoperative recurrent rate.Fig. 5 is the model pair
The prediction of postoperative recurrence-free survival rate.Fig. 5 A is model Kaplan-Meier survival analysis in independent test collection GSE8894
Significance analysis.Fig. 5 B is the conspicuousness point of model Kaplan-Meier survival analysis in independent test collection GSE30219
Analysis.Fig. 5 C is the significance analysis of model Kaplan-Meier survival analysis in independent test collection GSE31210.Fig. 5 D is
The significance analysis of model Kaplan-Meier survival analysis in independent test collection GSE50081.Fig. 6 is non-small cell lung
Cancer prognostic model predicts the ROC curve analysis of recurrence-free survival rate.Fig. 6 A is the model 5 years in independent test collection GSE8894
The analysis of recurrence-free survival rate ROC curve.Fig. 6 B is the model 5 years recurrence-free survival rate ROC in independent test collection GSE30219
Tracing analysis.Fig. 6 C is model recurrence-free survival rate ROC curve analysis in 5 years in independent test collection GSE31210.Fig. 6 D is
The model is analyzed in independent test collection in GSE500815 recurrence-free survival rate ROC curve.
Table 8 is non-small cell lung cancer prognostic gene combination tag in verifying collection and independent test concentration progress Kaplan-
Meier survival analysis, and the result tested with log-rank test.
The assortment of genes label of 8 non-small cell lung cancer prognosis of table is in overall survival and recurrence-free survival rate associated data set
The product test of middle prediction
The non-small cell lung cancer assortment of genes is concentrated progress Kaplan-Meier raw by the present invention in verifying collection and independent test
Analysis is deposited, and is tested with log-rank test, P value thinks that the assortment of genes can give birth to postoperative totality less than 0.05
The short patient of the patient and postoperative overall survival phase for depositing phase length separates；By postoperative high risk of recurrence patient and low risk of recurrence patient
It separates.The assortment of genes label of non-small cell lung cancer prognosis is tested what overall survival and recurrence-free survival rate related data were concentrated
Card is as a result, show that the specific gene combination in 17 genes of the invention screened can be respectively to postoperative non-small cell lung carninomatosis
People carries out life cycle length and risk of recurrence height is classified, to carry out the treatment of individuation.The molecular marker is not by NSCLC group
The influence of the factors such as type, staging, age, gender is knitted, can be used as NSCLC prognostic evaluation tool, and to NSCLC patient
With universal applicability.
Although having used general explanation, specific embodiment and test above, the present invention is described in detail,
But on the basis of the present invention, it can be made it is some modify or improve, this is apparent to those skilled in the art
's.Therefore, these modifications or improvements without departing from theon the basis of the spirit of the present invention, belong to claimed
Range.
Claims (8)
1. molecular marker relevant to non-small cell lung cancer prognosis, be COL6A1, PLOD2, CTSZ, STMN2, EIF3B,
One in SEPT2, GSR, DYNC1H1, SEC23A, MARCKS, TUBB, NRP1, LRP1, EIF5A, ARSA, CD81, ANPEP
Or it is multiple.
2. molecular marker as described in claim 1, characteristic are, are as follows:
(1)PLOD2,EIF3B,SEC23A,MARCKS；Or
(2)PLOD2,EIF3B,MARCKS,LRP1；Or
(3)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS；Or
(4)COL6A1,PLOD2,EIF3B,LRP1,ANPEP；Or
(5)PLOD2,EIF3B,SEPT2,SEC23A,MARCKS；Or
(6)PLOD2,EIF3B,MARCKS,NRP1,LRP1；Or
(7)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,MARCKS；Or
(8)PLOD2,EIF3B,SEPT2,SEPT2,SEC23A,MARCKS；Or
(9)PLOD2,EIF3B,DYNC1H1,MARCKS,NRP1,LRP1；Or
(10)COL6A1,PLOD2,CTSZ,EIF3B,DYNC1H1,MARCKS；Or
(11)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,MARCKS；Or
(12)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,NRP1；Or
(13)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,ANPEP；Or
(14)PLOD2,EIF3B,SEPT2,MARCKS,TUBB,LRP1,ANPEP；Or
(15)PLOD2,EIF3B,DYNC1H1,SEC23A,MARCKS,LRP1,ANPEP；Or
(16)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEPT2,MARCKS；Or
(17)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,DYNC1H1,SEC23A；Or
(18)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEC23A,MARCKS；Or
(19)COL6A1,PLOD2,CTSZ,EIF3B,DYNC1H1,MARCKS,MARCKS；Or
(20)COL6A1,PLOD2,CTSZ,EIF3B,SEC23A,MARCKS,MARCKS；Or
(21)COL6A1,PLOD2,CTSZ,EIF3B,MARCKS,MARCKS,NRP1；Or
(22)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEPT2,DYNC1H1,SEC23A；Or
(23)COL6A1,PLOD2,CTSZ,SEPT2,SEPT2,DYNC1H1,SEC23A,LRP1；Or
(24)EIF3B,SEPT2,DYNC1H1,SEC23A,MARCKS,MARCKS,NRP1,LRP1；Or
(25)COL6A1,PLOD2,CTSZ,EIF3B,SEPT2,SEPT2,DYNC1H1,MARCKS,ANPEP；Or
(26)PLOD2、EIF3B、SEPT2、DYNC1H1、SEC23A、MARCKS、MARCKS、NRP1、LRP1。
3. molecular marker as claimed in claim 2, which is characterized in that
Combination a for (1), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 204344_s_at,
201668_x_at；
Combination a for (2), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 201668_x_at,
1555353_at；
Combination a for (3), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at, 201668_x_at, or,
216904_at,202619_s_at,212562_s_at,211501_s_at,213002_at；
Combination a for (4), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 211501_s_at,
1555353_at,234576_at；
Combination a for (5), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 1554747_a_at,
204344_s_at,201668_x_at；Or
202619_s_at,211501_s_at,200778_s_at,204344_s_at,201668_x_at；
Combination a for (6), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 213002_at,
210615_at,1555353_at；
Combination a for (7), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,213002_at；
Combination a for (8), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 200778_s_at,
1554747_a_at,204344_s_at,201668_x_at；
Combination a for (9), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 229115_at,
213002_at,210615_at,1555353_at；
Combination a for (10), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,229115_at,213002_at；
Combination a for (11), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,201668_x_at,213002_at；
Combination a for (12), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,213002_at,210615_at；
Combination a for (13), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,213002_at,234576_at；
Combination a for (14), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 200778_s_at,
201668_x_at,209026_x_at,1555353_at,234576_at；
Combination a for (15), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 229115_at,
204344_s_at,213002_at,1555353_at,234576_at；
Combination a for (16), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,200778_s_at,213002_at；
Combination a for (17), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,229115_at,204344_s_at；
Combination a for (18), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,204344_s_at,213002_at；
Combination a for (19), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,229115_at,201668_x_at,213002_at；
Combination a for (20), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,204344_s_at,201668_x_at,213002_at；
Combination a for (21), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,201668_x_at,213002_at,210615_at；
Combination a for (22), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,200778_s_at,229115_at,204344_s_at；
Combination a for (23), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
1554747_a_at,200778_s_at,229115_at,204344_s_at,1555353_at；
Combination a for (24), corresponding probe be respectively as follows: 211501_s_at, 200778_s_at, 229115_at,
204344_s_at,201668_x_at,213002_at,210615_at,1555353_at；
Combination a for (25), corresponding probe be respectively as follows: 216904_at, 202619_s_at, 212562_s_at,
211501_s_at,1554747_a_at,200778_s_at,229115_at,213002_at,234576_at；
Combination a for (26), corresponding probe be respectively as follows: 202619_s_at, 211501_s_at, 200778_s_at,
229115_at、204344_s_at、201668_x_at、213002_at、210615_at、1555353_at。
4. any molecular marker of claim 1-3 is preparing non-small cell lung cancer patient's prognostic evaluation kit, examination
Application in agent or chip.
5. any molecular marker of claim 1-3 is preparing non-small cell lung cancer patient's shorter survival length or is answering
Send out the application in risk height appraisement system.
6. any molecular marker of claim 1-3 is in preparing the postoperative direction of medication usage system of non-small cell lung cancer patient
Application.
7. such as application described in claim 5 or 6, which is characterized in that the system is for kit or with non-small cell lung cancer
Medicine box or instrument for the purpose for the treatment of.
8. a kind of kit, which is characterized in that the detection reagent containing any molecular marker of detection claim 1-3
And/or detecting instrument；The kit is non-small cell lung cancer patient prognostic evaluation kit, non-small cell lung cancer patient is postoperative
Life cycle length or risk of recurrence height kits for evaluation or the postoperative direction of medication usage kit of non-small cell lung cancer patient.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111564177A (en) * | 2020-05-22 | 2020-08-21 | 四川大学华西医院 | Construction method of early non-small cell lung cancer recurrence model based on DNA methylation |
| WO2023231280A1 (en) * | 2022-05-31 | 2023-12-07 | 深圳市陆为生物技术有限公司 | Product for evaluating recurrence risk of lung cancer patient |
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| CN101638656A (en) * | 2009-08-28 | 2010-02-03 | 南京医科大学 | Blood serum/blood plasma miRNA marker related to non-small cell lung cancer (SCLC) prognosis and application thereof |
| CN103492590A (en) * | 2011-02-22 | 2014-01-01 | 卡里斯生命科学卢森堡控股有限责任公司 | Circulating biomarkers |
| CN108315413A (en) * | 2017-12-31 | 2018-07-24 | 郑州大学第附属医院 | A kind of human liver cancer marker and application thereof |
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| WO2023231280A1 (en) * | 2022-05-31 | 2023-12-07 | 深圳市陆为生物技术有限公司 | Product for evaluating recurrence risk of lung cancer patient |
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| CN109735619B (en) | 2022-04-15 |
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