CN107202886B - A kind of biomarker pair and its selection method of sketch-based user interface - Google Patents
A kind of biomarker pair and its selection method of sketch-based user interface Download PDFInfo
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
- G01N33/57407—Specifically defined cancers
- G01N33/57423—Specifically defined cancers of lung
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/574—Immunoassay; Biospecific binding assay; Materials therefor for cancer
- G01N33/57484—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites
- G01N33/57488—Immunoassay; Biospecific binding assay; Materials therefor for cancer involving compounds serving as markers for tumor, cancer, neoplasia, e.g. cellular determinants, receptors, heat shock/stress proteins, A-protein, oligosaccharides, metabolites involving compounds identifable in body fluids
Abstract
The present invention relates to a kind of methods for selecting biomarker pair, type including ncRNA in measurement biological sample, measure the content of ncRNA in biological sample, calculate the ratio of any two kinds of ncRNA in each biological sample, according to ratio between the group of any two kinds of ncRNA of the average ncRNA level calculation of biological sample group, best ncRNAs pairs of (SVM-RFE) algorithms selection is selected using support vector machines cycle characteristics, using ncRNAs pairs of ratio as the index for being grouped sample.The method of the invention is able to solve the problem of data normalization difficulty of the ncRNA as biomarker when.The present invention is based on the NcRNAs that ratio obtains to compare to as biomarker better than endogenous and exogenous miRNA.
Description
Technical field
The invention belongs to biological detecting method fields, and in particular to a kind of biomarker pair of sketch-based user interface and its
Selection method, more particularly relate to it is a kind of selection blood plasma in ncRNAs pairs method more particularly to one kind can distinguish health it is right
According to ncRNAs pairs and its specific choice method with adenocarcinoma of lung.
Background technique
MiRNAs is interior life, small non-coding RNAs, usual 18-25 length of nucleotides.They are found in mRNA and turn
It adjusts and plays a crucial role after record.MiRNAs plays key effect in cell differentiation, proliferation, apoptosis, and participates in
The disease of many types includes cancer, diabetes, cardiovascular and cerebrovascular and neurological disease.In addition to miRNAs, there are also some other small non-
Coding RNA s plays a significant role in many levels for adjusting gene expression, such as chromatin Structure, transcription, mRNA it is stable and
Translation, ncRNAs include small snoRNAs, and Piwi- interacts RNAs (piRNAs), short interfering rna s (siRNAs) and tRNAs,
These ncRNAs multilated in cancer and other diseases.For example, snoRNAs includes a height small ncRNAs group abundant,
There are in gene montage and silencing a limited number of snoRNAs groups of ncRNA- identity function with one.In the recent period it is reported that 3
A snoRNAs shows differential expression in non-small cell lung cancer patient, it has recently been demonstrated that three in tumour is formed
SnoRNAs display changes expression formula and may make in lung neoplasm generation in non-small cell lung cancer (NSCLC) patient, and SNORA42
For oncogene.
In recent years, a series of research shows that miRNAs is in such as serum, blood plasma, saliva, lotion, sputum and urine these body fluid
In can be detected, circulation miRNAs is detected by foreign substance or microvesicle package, or is tied up with differential protein such as Ago-2
It is fixed.Once miRNAs can be occupied by other cells (cell-cell communication) in extracellular space, degenerated by RNases, or excretion.To the greatest extent
The secretion of pipe miRNAs and integrated mechanism are not fully understood, and circulation miRNAs may participate in physiology and pathological activity.
These are found to be circulation ncRNAs and beat as the non-invasive diagnostic of variety classes disease and prediction biomarker
Yishanmen is opened.Due to high sensitivity, high specificity and template required amount are few, and most of researchs at present use measurement circulation
MiRNAsis reverse transcription quantitative PCR (RT-qPCR) method.Because it is very low to recycle RNAs concentration in body fluid, accurately measures and follow
The expression of ring miRNA is a huge challenge.In addition, the variation of system factor such as original material quantity similar to gene expression,
Sample collection, RNA are extracted, and reverse transcription, PCR, these can all influence final result and cause deviation and quantitative error.So working as
Before, normative references control molecule be used to standardize circulation miRNA PCR data, it is therefore an objective to just assessments miRNA
Expression.It include at present endogenous and external source control with reference to control molecule.Many researchers select using the synthesis RNA sequence that increases sharply
(as C. nematode miR-39 and miR-54 or Mirnas of plant s) as extreme value reference pair shine, for standardize circulation miRNA
QPCR analysis.A series of internal contrast is used.For example, one of little nucleolar RNAs (snoRNAs) member, if RNU6B is most
It early be used to recycle miRNA data normalization, but be cancelled later, due to special disease and tumor prognosis.Many researchs are examined
Consider miRNA reference, as miR-16, it shows difference in cancer patient plasma sample.In default of concentration method for normalizing, this
It will affect the data consistency and reproducibility of different researchs.Therefore, the task of top priority is to find the optimality criterion of circulation miRNA data
Change method.
The standardization of plasma/serum ncRNA RT-qPCR experimental data is a challenge.It illustrates by miRNA, because from corpusculum
The yield of the total serum IgE obtained in hematocele slurry or serum sample (μ l of i.e., 100 or 200) is lower than spectrophotometry accurate quantitative analysis
Limiting value, sample collection, storage and processing in error also influences circulation miRNA quantitative analysis accuracy and reliability.Mirror
In endogenous or external source with reference to the impurity in control molecule, the adjustment technology difference in RNA recovery routine is recommended in current experiment.It is right
In the standardization of circulation miRNA qPCR analysis, synthesis RNA sequence (such as C. nematode is added in many researcher's selections in the sample
MiR-39 and miR-54 or Mirnas of plant s).We select C. nematode Cel-miR-54 outer as one in early-stage study
Portion's control, it is found that it is not a good reference in sequencing and RT-qPCR data.Reason is these synthesis
MiRNAs is applied directly to be degraded quickly in blood plasma, and the endogenous miRNAs stability of ratio is poor afterwards in its addition blood plasma, because it
Not by the active protection of S-RNase.Moreover, circulation miRNAs is relatively stable, because they are by the active guarantor of S-RNase
Shield, also because they otherwise be incorporated into albumen or be included in endosome among.
Some researchers are to seek source reference miRNAs (ECM) in suitable to be made that effort；In any case, for blood
MiRNA quantitative analysis not yet identifies ECMs. ideal enough for example, miR-16 is often used as reference at present, but serum
The high level of middle miR-16 is related to the Bone tumour of breast cancer patients, and reports and show that endogenous miR-16 is very poor standard
Change the factor.Report that let-7d/g/i is an interior source reference well for the standardization for recycling miRNA data from Chen X etc.,
We are measured using let-7d/g/i in an experiment.We have found that they cannot stablize expression in our sample.
The sample of Chen comes from Chinese, although lung cancer sample is included in, this may be one that we do not obtain analog result
A reason.Widely used interior source reference has-MiR-19130 is also not a good reference in our experiment.We
More endogenous controls such as U637, RNU4438, RNU4839, miR-16 40, miR-10330 and miR- can constantly be tested
23a41, they are commonly used instantly.However, the research of Chen has been found that these referring to the result ratio let- obtained
7d/g/i is also poor.It is well known that ideal endogenous reference pair is according to the condition at least met: they are in all samples and experiment item
Expression can be stablized in part.This is difficult to prove which candidate endogenous molecule meets this condition.
Usage rate has been used in some diseases as molecular labeling.However, special technique study mentions not yet
Method to sketch-based user interface is applied to circulation ncRNA sequencing and RT-qPCR data normalization.Currently, about circulation ncRNAs
(miRNAs) paper about 99% is still using external source or the endogenous standard for carrying out cycle P CR data with reference to control molecule
Change.Some researchs are still shone in the more preferable reference pair for extremely seeking to recycle miRNA data normalization.
Summary of the invention
There is research to have shown that circulation ncRNA, such as miRNAs in the recent period, is stable and people can be used for as molecular labeling
Class medical diagnosis on disease and prognosis.It is using new-generation sequencing and quantitatively real-time however since the circulation ncRNAs concentration in blood is very low
RT-PCR is carried out in plasma/serum ncRNA experiment, and data normalization is a challenge.It is outer that standardized method at present is based on synthesis
Source property standard control or to find endogenous miRNA control be inappropriate, because of their unstable expression, from without finding
The significant ncRNAs of reliable differential expression.
In view of the above-mentioned defects in the prior art, the present invention provides a kind of standardized methods of sketch-based user interface, for replacing
Using single ncRNAs biomarker, to identical sample, we calculate the ratio of any two ncRNAs, and use production
Raw ratio is as biological marker.
On the one hand, the present invention provides a kind of method for selecting biomarker pair, includes the following steps
(1) type of ncRNAs in biological sample is determined；
(2) content of ncRNAs in biological sample is determined；
(3) ratio in each biological sample between any two kinds of ncRNA is calculated；
(4) according to the cell mean of every kind of ncRNA in multiple biological sample groups, any two kinds of ncRNA cell means are calculated
Between ratio；
(5) best ncRNAs pairs of (SVM-RFE) algorithms selection is selected using support vector machines cycle characteristics；
(6) using ncRNAs pairs of ratio as the index for being grouped sample.
The method of selection biomarker pair of the present invention, wherein the biological sample is blood plasma；The biology sample
Product group includes at least normal specimens group, disease sample group, and the preferably described disease sample group includes cancer specimen group, benign tumour sample
Product group；The ncRNA includes miRNA, snoRNA, piRNA, siRNA and tRNA.
The method of selection biomarker pair of the present invention, wherein the step (1) includes RNA extraction and small molecule
RNA sequencing.
The method of selection biomarker pair of the present invention, wherein RNA extraction is to try blood plasma with TRIzol
Agent is extracted, and absorption in silicon dioxide film closing column is added, the RNA of absorption is collected after cleaning.
The method of selection biomarker pair of the present invention, wherein being surveyed by SMARTer smRNA-seq method
Sequence specifically includes RNA sample carrying out the connection of 3 ' connectors, 5 ' RT primer annealings, 5 ' connector connections, reverse transcription, PCR amplification.
The method of selection biomarker pair of the present invention, wherein fixed by reverse transcription and PCR in the step (2)
Amount (RT-qPCR) determines the content of blood plasma ncRNAs, it is preferable to use Taqman miRNA kit carries out qRT-PCR detection.
The method of selection biomarker pair of the present invention, wherein data of the step (3) according to RT-qPCR,
Ratio (ncRNA1/ncRNA2) use of 2 small molecule ncRNA contents is compared CT method (2- Δ CT) and is counted in same sample
It calculates, Δ CT=CTncRNA1-CTncRNA2.
The method of selection biomarker pair of the present invention, wherein the step (4) includes by blood plasma ncRNA concentration
It is converted by log2, non-matching T inspection, average ncRNA between more different biological sample groups is carried out using SPSS20.0 software
Ratio, significant p- value are set as 0.05.
The method of selection biomarker pair of the present invention, wherein support vector machines circulation is special in the step (5)
Property selection (SVM-RFE) algorithm include:
A, the feature that initialization data set includes；
B, the SVM of training dataset；
C, according to 2 ranking feature of ci=(wi)；
D, the 50% of inferior grade feature is rejected；
E, return step b.
The method of selection biomarker pair of the present invention, it is characterised in that: the ncRNA can also use other
Biomarker replacement, the other biomarkers object includes mRNA, DNA, protein, metabolite.
Second aspect, the present invention provide a kind of biology mark that the method choice by the selection biomarker pair obtains
Remember object pair.
Biomarker of the present invention is to its selected from the following group of miR378a-3p/miR126-5p, sno-DR119/
tRNA-Thr-ACG、sno-ACA33/miR378a-3p、tRNA-Thr-ACG/sno-U57、tRNA-Thr-ACG/miR378a-
3p。
The third aspect, the present invention provide the biomarker to the purposes in preparation adenocarcinoma of lung diagnostic reagent.
It is worth noting that, the method for the present invention for selecting biomarker pair is in vitro biological sample for implementation
Object, but its direct purpose be in order to select biomarker to (in order to subsequent research or application), and not to biology
The individual of sample source is diagnosed or is treated, because selecting biological sample used in the method for biomarker pair, it comes
The health status (such as adenocarcinoma of lung disease condition) of source individual has been determined by other methods diagnosis.Therefore institute of the present invention
The method for stating the inherently non-clinical diagnostic purpose of method of selection biomarker pair.
Although principle according to the present invention, the biomarker that the present invention selects to can be used in by biological sample material by
The health status of source individual classify and has huge clinical value；But this only shows that the method for the invention obtains
The clinical application of biomarker pair may relate to methods for clinical diagnosis, and select the method for biomarker pair itself,
Then it is not belonging to any methods for clinical diagnosis.
Compared with prior art, the present invention achieves following beneficial technical effect:
(1) method of the standardization circulation ncRNA data of sketch-based user interface proposed by the present invention, is made using the ratio of ncRNAs
For classification foundation, compared to single ncRNA is used, the ratio of ncRNAs is more, difference is more significant, can more accurately react
True value.Such as to identical sample, we calculate the ratio of any two ncRNAs first, then between more different groups
Ratio expression rather than single ncRNA level are compared.Because 2 ncRNAs use identical sample, in same item
It is expressed simultaneously under part, the true value that the relative expression levels of 2 ncRNAs ratio compare reflection.
(2) present invention demonstrated on mathematical logic the method for the invention be correctly, it independently of any outside or
Internal reference controls molecule, and existing based on outside or inside control standardized method better than any.This ratio strategy will be
Clinical application provides an actual method in terms of recycling biomarker of the ncRNA as human diseases.The present invention is mathematically
Prove method of the method better than any normalization factor compareed based on endogenous or external source of sketch-based user interface.Based on endogenous or external source
There are two assume for the standardized method of control.First, it is assumed that the miRNA to be measured and internal control in identical sample are by identical
System factor influence；Second, it is assumed that control value is the same in true in different samples.And the method for sketch-based user interface be just assumed that it is identical
Different miRNAs in sample have identical system factor, therefore, mathematically clearly demonstrate the standardization of sketch-based user interface
Method is better than the standardized method shone based on reference pair, because whether being difficult to understand second hypothesis really.
(3) the biomarker primer pair of sketch-based user interface increases the probability found and have clinical meaning biomarker.Based on than
The standardized method of rate can find prior difference ncRNA candidates in various disease group.This is logically also easy
In understanding, for example, the ratio of miRNA1/miRNA2 is given in the normal group of health and cancer group, if compared just in cancer group
Chang Zuzhong has the multiple of a up-regulation to change, and miRNA2 compares the multiple change for having a downward in normal group in cancer group.
MiRNA1/miRNA2 multiple between such words cancer group and normal group changes bigger than independent miRNA1 or miRNA2.Cause
This when we cannot find have great change it is single labelled when, the method for sketch-based user interface will increase we find have clinical meaning
The probability of biomarker.
(4) present invention has found 5 circulation ncRNA ratios with the method, this 5 ncRNA combinations have 100% prediction
Accuracy distinguishes adenocarcinoma of lung and normal person, and the present invention not only tests miRNAs, also test other types of ncRNAs, such as
SnoRNAs and tRNAs.
Detailed description of the invention
Fig. 1: the reading number of exogenous control Cel-miR-54.
7 plasma sample set (15 samples/set) are used for the sequencing of microRNA, before RNA is extracted and is sequenced,
The exogenous Cel-miR-54 equivalent of synthesis is added in 7 plasma sample set.LC represents normal health control (2 samples
Collection), BE is represented benign (2 sample sets), and AD represents adenocarcinoma of lung (2 sample sets) and SC represents prognosis of squamous cell lung cancer (1 sample
This collection).
Fig. 2: the RT-qPCR CT value that external source and endogenous reference pair are shone in cancer and non-cancer sample.The classification of CT value is
The plasma sample amount for being 129 based on sum, these samples include lung cancer, the control of benign and normal health.(a) in 129 samples
External source C. nematode Cel-miR-54CT value.(b) endogenous reference pair shines has-miR-191CT value in 129 samples.(c) 129 samples
Endogenous reference pair is according to average has-Let-miR-let 7d, g, i CT value in this.
Fig. 3: the quantity of single the ncRNA quantity and ncRNA ratio that have differences.
X-axis represents all measurable characteristics (miRNA ratio or miRNA), and normal health compares the area vs adenocarcinoma of lung Zhong Ke
Dosis refracta, normal health compare that vs is benign and benign vs adenocarcinoma of lung.Non-matching t-test be used for identify can distinguish miRNA or
MiRNA ratio.Value≤0.05 P and multiple, which change, is cut to 2.0.
Fig. 4: the expression value of representativeness ncRNA ratio in normal sample and adenocarcinoma of lung sample.
Adenocarcinoma: adenocarcinoma of lung；Normal: normal.Each individual ncRNA uses real-time quantitative in blood plasma
RT-PCR is measured, and the ratio of 2 ncRNAs is calculated as (2 in identical sample-ΔCT), wherein Δ CT=CT ncRNA1-CT
NcRNA2, so-Δ CT=log2 (ncRNA1/ncRNA2).(A)miR378a-3p/miR126-5p.(B)sno-DR119/
tRNA-Thr-ACG.(C)tRNA-Thr-ACG/sno-U57.(D)tRNA-Thr-ACG/miR378a-3p.(***p<0.001)。
Fig. 5: adenocarcinoma of lung and Normal group plasma sample pass through the differentiation that 5 pairing ncRNA ratios mark.
Two-way hierarchical clustering based on 5 pairing labels is executed to show group clustering.50 adenocarcinoma of lung samples
(Adeno) and 29 normal health controls (Normal) are used for real-time RT-qPCR.Colour bar indicates the expression value of label.
Specific embodiment
Below in conjunction with specific embodiment, the present invention is further explained.These embodiments are merely to illustrate the present invention and do not have to
In limiting the scope of the invention.In the following examples, the experimental methods for specific conditions are not specified, usually according to normal condition or presses
According to condition proposed by manufacturer.Unless otherwise defined, all professional and scientific terms as used herein and this field are ripe
It is identical to practice meaning known to personnel.In addition, any method similar to or equal to what is recorded and material all can be applied to
In the method for the present invention.The preferred methods and materials described herein are for illustrative purposes only.
In the examples where no specific technique or condition is specified, described technology or conditions according to the literature in the art,
Or it is carried out according to product description.Reagents or instruments used without specified manufacturer, be can be by regular channel commercially available from
The conventional products of acquisition.
Embodiment 1
Sample group and plasma sample are collected
In The People's Hospital of Peking University, we collect about 1250 patients with lung cancer samples in lung cancer biology library, from this
We have selected the group including 130 patients for this research in a little samples, this 130 sample examples include 50 morning
Stage phase (stage I, II) adenocarcinoma of lung and 15 prognosis of squamous cell lung cancer (SCC), 35 benign, and 30 normal.Early stage gland cancer and squama
Shape cell lung cancer SCC sample inclusion criteria includes: only to suffer from the chest disease for not having far-end transfer；We start not have in blood sampling first 1 year
Staging tomography or radiotherapy；At least 2 years clinical trail data.Optimum sample patient candidate is selected need to be through low dosage computer scanning
Show that (LDCT) suffers from a series of lung minor illness (such as polyp, hamartoma, and inflammatory lesion) of non-tumours.It is all be selected in benign patient and
Normal person is next annual all to carry out LDCT, and does not suffer from cancer at least 2 years.These patients and the demographic information of control are such as
Supplementary table 1.Cancer, benign and normal sample match as far as possible at age, race, gender and smoking state aspect.Normal group
Also referred to as high risk group, this group of people has 30 years or more smoking histories before grab sample and history of giving up smoking was lower than 15 years.Institute is ill
Personal data all obtains written formal agreement, and meets the related request of The People's Hospital of Peking University's Institutional Review Board.
All plasma samples are collected with EDTA anticoagulant tube, and 4000RPM is centrifuged 10min, then 12,000RPM high speed centrifugation
15min completely removes cell fragment.Upper plasma is stored in -80 DEG C before analysis.All samples are collected when diagnosing for the first time.
Embodiment 2
RNA is extracted and sequencing
RNA extracts as previously described.Blood plasma total serum IgE, the extraction including blood plasma microRNA s use aliquot miRNeasy
kit(Qiagen,Valenciz,CA).In short, 0.5ml blood plasma dilutes (1ml in total) with the water 1:1 of no Rnase, divide completely
3mL is added in every 1mL sample volume after layerLS reagent, sample vortex mix 10s, and incubation at room temperature 15min is (in total
4ml) nucleoprotein complex is allowed to decompose completely.4 DEG C, 12000g is centrifuged 10min, draws supernatant (including RNA) into new pipe, adds
0.8mL chloroform acutely mixes 15s, 12,000g centrifugation 15min.2.5 times of volumes are added into new pipe in careful upper strata aqueous phase of drawing
Ethyl alcohol.Sample liquid is directly added into silicon dioxide film closing column, RNA is adsorbed, and is gone with the cleaning buffer solution that supplier provides
Except impurity.Water (80 DEG C of preheatings in advance) with 16 μ l without Rnase collects the RNA being adsorbed.
In this research, we using California wish a kind of next-generation sequencing in city to study plasma sample, this
Kind technology is as previously described.In short, being save the cost and sample, we analyze microRNA sequencing (smRNA-seq) first,
To identify microRNAs and some other circulation small molecule non-coding RNAs (sncRNAs).We select 7 sample sets, this
In 7 sample sets include 30 high risk normal healthy controls (normal), 30 benign protuberance lesions (benign), 30 adenocarcinomas of lung, and
15 prognosis of squamous cell lung cancer.Normally, benign and cancer sample is at the age, and gender, race and smoking state aspect are all matched.
Training set sample (coming from The People's Hospital of Peking University, but very unfortunate, I is lost an example normal sample when carrying out PCR) is by pre-
Phase collects.Verifying collection sample is collected as expected.Except squamous cell carcinoma group, every group of two sample set (each sample set 15) into
Row smRNA is sequenced, and mixes 500 μ l blood plasma on an equal basis in each sample set.Each sample 20,000,000 read with about 90% reading with
Human genome compares.
Library construction preliminary experiment, 6 μ l serum RNA extract eluent, and draft has carried out on a small quantity preliminary experiment as indicated
It is carried out after modification.One miRNA library construction is to be connected by each RNA sample by 3 ' connectors, 5 ' RT primer annealings, 5 ' connectors
Connection, reverse transcription, and PCR amplification.12 parts of sample library mixed in equal amounts read each channel with cBot (Illumina) after polymerization
Single reading flow cell concentration be 10.5pmol.HiSeq 2500 (Illumina) sequencing is set as 50 circulations.It is more
It decomposes raw sequencing data and v.1.8.2 generates FASTQ file using CASAVA in road.
From FASTQ file, by the way that by connector and sequencing reading frame Local Alignment, 3' sequence measuring joints will be removed.We adopt
3' connector is removed with excision connector software.After connector removes, all sequences have the missing less than 15bps length.Each text
The reading in library will be summarized as the label of quantization FASTA format.Because bowtie, FASTA reading will be mapped to that genome.To disappear
It is only least to compare unmatched unique mapping site and be described except FUZZY MAPPING records, at most allow two not
Match.The express spectra in different libraries will depend on mankind ncRNAs mapping cleaning and read back.Each mapping trajectories annotation is come
From multiple ncRNA databases.
Embodiment 3
Reverse transcription and real-time PCR
Using TaqmanmiRNA experiment reagent box (Applied Biosystems, the U.S.), the grass provided according to manufacturer
Case, NcRNAs will be measured.In short, the RNA of about 30ng abundance uses TaqManncRNA reverse transcription reagent box (Applied
Biosystems, the U.S.) by reverse transcription, reaction volume is 15 μ L.The expression of ncRNAs is carried out qRT-PCR in triplicate
Quantitative analysis, using TaqMan MicroRNA experiment reagent box (Applied Biosystems, the U.S.),
4 system of Eppendorfiplex (Eppendorf North America, Hauppauge, NY).For around standardization issue,
We using same ratio strategy come alternate standard, to reduce experimental error.
Embodiment 4
Statistical analysis
For identical sample, we calculate the sequencing and RT-qPCR data rate of any two ncRNAs.For RT-
QPCR data, the calculating of the expression of 2 small molecule ncRNA (ncRNA1/ncRNA2) ratios, which uses, compares CT method (2-ΔCT),
To identical sample, Δ CT=CT ncRNA1-CT ncRNA2.After blood plasma ncRNA concentration is converted by log2, we are used
SPSS20.0 software carries out non-matching T- inspection, compares adenocarcinoma groups, average ncRNA ratio between benign patient and Normal group
Rate, significant p- value are set as 0.05.Chi-square Test is carried out with 20.0 software of SPSS, relatively more trained and Qualify Phase sample gender,
The distribution of race and cancer staging, age are examined with t-, and significant p- value is set as 0.05.It is selected using support vector machines cycle characteristics
(SVM-RFE) algorithm is selected to select best ncRNAs.SVM-RFE48 is a kind of calculation that character subset is selected for specific learning objective
Method.Its rudimentary algorithm is: (1) feature that initialization data set includes, and the SVM of (2) training dataset, (3) are according to ci=(wi
)2The 50% of inferior grade feature, (5) return step 2 are rejected in ranking feature, (4).In each RFE step 4, some features are because of SVM
The active variable of disaggregated model is rejected.Feature is eliminated according to relevant criterion, this standard supports discriminant function phase with them
It closes, in each step SVM by retraining.It is used for according to the ncRNA ratio that feature selecting algorithm selects using support vector machines
(SVMs) classification.5 times of right-angled intersection verification process include inside and outside verifying.We used estimated performance index, packets
Sensibility is included, specificity, positive predictive value (PPV), area (AUC) judges to predict under negative predictive value (NPV) and ROC curve
Precision.
Embodiment 5
Sketch-based user interface to circulation the standardized method of ncRNA cross-sectional data independently of any internal or external standard control
Because external source and endogenous control standardize all insincere (Fig. 2) to circulation ncRNA cross-sectional data, we test one
A sketch-based user interface, for recycling the standardized method of ncRNA cross-sectional data.Firstly, we calculate any two in identical sample
The ratio of a ncRNAs, then expression ratio rather than the expression of relatively simple ncRNA in more different groups.It takes
MiRNA and internal control (IC) are as an example (table 1).
Rate of the table 1 based on method for normalizing
* positive value is represented and is raised in cancer, and negative value representative is lowered in cancer.
The expression value of miRNA1 is 4 and 8 respectively in normal sample and cancer sample, and multiple variation is 2 (rows between two groups
1)；The expression value of internal contrast 1 (IC1) is 2 and 4 (rows 2) respectively in normal sample and cancer sample.If miRNA1 passes through
IC1 standardization, the multiple change between normal sample and cancer sample is 1 (row 5)；If miRNA1 is marked by internal control 2 (IC2)
Standardization, the multiple change between normal sample and cancer sample are -4 (averagely lowering 4 times).It can be seen that without standard (row 1)
Or different internal controls (IC1 or IC2) is used, the multiple between normal sample and cancer sample changes different.With miRNA2 phase
Seemingly, we obtain different multiple change result (such as row 2,6 and 8).If we standardized first by IC1 miRNA1 and
Then miRNA2 calculates the ratio of the value of IC1 standardization miRNA1 and miRNA2, the value of normal sample is 0.5, and cancer sample
Value be 2, multiple changes into 4 (rows 9).It is interesting that if we are standardized miRNA2 (row 10) by IC2 or do not have to appoint
What control (row 11), then calculates ratio of the identical sample with two miRNAs, and the rate value of normal sample remains as 0.5 (row
10 and 11), and the value of cancer sample is also 2 (rows 10 and 11), it is still 4 (rows 10 and 11) that multiple, which changes,.The results show that regardless of me
With which kind of internal control method, the constant rate of any two miRNAs in identical sample.So for miRNA cross-sectional data
Standardization, we can only calculate the ratio (row 11) of any two miRNAs in identical sample, this is totally independent of in any
What source or external source compareed.
Embodiment 6
The data normalization method of sketch-based user interface is correct on mathematical logic
From table 1, we are it has shown that the standardized method of sketch-based user interface is meaningful.Here, I it is expected from mathematics
Prove that the method is correct in logic.In addition, we use miRNA as an example, our final goal is attempt to send out
Now biologically true miRNA value (turemiRNA), however, usually our miRNA from obtained in experiment
(OBSmiRNA) value is not true value.In fact, OBSmiRNA value is the knot that truemiRNA is embedded into that different system factors obtains
Fruit.In RT-qPCR experiment, system factor may include RNA and extract (I), reverse transcription (R), PCR (P), different time (T) etc..
Therefore, it is provided that in a concrete case such as S1
(1) OBSmiRNA1=TruemiRNA1*Is1*Rs1*Ps1*Ts1
Similarly, it will be assumed that the system factor in identical sample for miRNA2 is the same, in same S1
OBSmiRNA2 is equally provided that
(2) OBSmiRNA2=TruemiRNA2*Is1*Rs1*Ps1*Ts1
Therefore, (3) OBSmiRNA1/OBSmiRNA2=TruemiRNA1/TruemiRNA2
From (3) row, we are it is clear that the ratio of 2 observation miRNAs values is equal to 2 very in identical sample
The ratio of real miRNAs value.Therefore, we mathematically prove, in identical sample, 2 observation miRNAs ratios can be true
Reflect that 2 miRNAs biological values, this biological value are it is desirable that measurement.
Therefore, PCR value is CT value, and CT value is actually logarithm.From formula (4), it is understood that 2 miRNAs
Log ratio is actually the difference of 2 CT values of 2 miRNAs, this to calculate simpler and clinically to use this
The data based on RT-qPCR are more convenient a bit.(4)Log2(OBSmiRNA1/OBSmiRNA2)=Log2(2-CTmiRNA1/2-CTmiRNA2)
=Log2(2-CTmiRNA1/2-CTmiRNA2)=Log2(2-CTmiRNA1+CTmiRNA2)=CTmiRNA2-CTmiRNA1
Embodiment 7
Mathematically, the standardized method of sketch-based user interface is better than endogenous or external source reference standard method
Although we prove that the standardized method of sketch-based user interface is that card is true on mathematical logic from mathematical angle, people
It may have a question, because it is assumed that being the same to different miRNAs system factors in identical sample.Theoretically it
It is pair, because that two miRNAs are in identical sample, it should be embedded in identical system factor.In fact, the standard of being based on
The reference pair of change method, which is shone, has also been made same setting.
The standardized method for comparing sketch-based user interface and endogenous or external source reference standard side are further analyzed from mathematical angle
Method:
(1) OBSmiRNA1S1=TruemiRNA1S1*Is1*Rs1*Ps1*Ts1
It can be arranged as follows
(2) Is1*Rs1*Ps1*Ts=Factor1
Then, the miRNA1 true value in sample 1 (S1) is
(3) TruemiRNA1S1=OBSmiRNA1S1/Factor1
Similarly, the miRNA1 true value in sample 2 (S2) is
(4) TruemiRNA1S2=OBSmiRNA1S2/Factor2
Similarly, internal control (IC) true value in sample 1 (S1) and sample 2 is
(5) TrueICS1=OBSICS1/Factor1
(6) TrueICS2=OBSICS2/Factor2
Therefore (5) and (6) are based on, we obtain
(7) Factor1=OBSICS1/TrueICS1
(8) Factor2=OBSICS2/TrueICS2
Factor 1 in (3) is replaced with Factor 1 in (7), Factor2 replaces Factor2 in (4) in (8), we obtain
It arrives
(9) TruemiRNA1S1=(OBSmiRNA1S1/OBSICS1) * TrueICS1
(10) TruemiRNA1S2=(OBSmiRNA1S2/OBSICS2) * TrueICS2
Assuming that (11) TrueICS1=TrueICS2
Therefore
(12) TruemiRNA1S1=OBSmiRNA1S1/OBSICS1
(13) TruemiRNA1S2=OBSmiRNA1S2/OBSICS2
(12) and in (13) formula is the standardized method currently based on endogenous or exogenous control.It is considered in phase
With in sample, the normalized value by the internal observation miRNA obtained referring to (IC) is the true value of miRNA.To obtain
This value, there are two assume here: first, it is assumed that in identical sample, the shadow of miRNA to be measured and internal control by same system factor
It rings (such as (2) and (5) or (4) and (6)), second, it is assumed that in different samples, true interior control value is the same (such as (11)).So
And this be difficult to recognize second assume be pair or wrong.Method based on ratio is just assumed that in identical sample different
MiRNAs has identical system factor, and therefore, I is clear from mathematical angle and demonstrates, and the standardized method of sketch-based user interface is excellent
In the standardized method shone based on reference pair.
Embodiment 8
The standardized method of sketch-based user interface can find the more more important difference that can be used as candidates in various disease group
Different ncRNA
Initially we assume that, circulation RT-qPCR data are used with the standardized method of sketch-based user interface, because external source is added
Property control the standardization of sequencing data is had failed.As an example by miRNA, a miRNA at least 20 times readings, are being surveyed
We have found 631 maturation miRNAs in sequence sample.Then, we calculate the ratio of any two miRNAs in identical sample
Rate, we unexpectedly obtain 198765 ratios (Fig. 3), and candidate is found in various disease group fully increasing us
The quantity of miRNAs, these candidate miRNAs are differential expressions with reduced value molecule.To obtain a differential expression miRNA ratio
It is worth table, we carry out cancer and normal group, cancer and optimum group, benign and normal group of Differential expression analysis in sample set.Times
Number changes >=2 and p value≤0.05, it has been found that the mature miRNA ratio (miRNA/miRNA) largely significantly changed,
Wherein normally with have 30,989 in cancer versus's group, normally with have 12,701 in benign contrast groups, benign and cancer versus
There are 7,044 in group.The quantity of these ratios significantly changed is more than the quantity that miRNAs single in 3 groups changes, single
One miRNA data normalization is based on global intermediate value (Fig. 3).
Embodiment 9
The ncRNA biomarker of sketch-based user interface is for distinguishing normal healthy controls and adenocarcinoma of lung
For the candidate ncRNAs that can distinguish lung cancer Yu non-lung cancer sample for testing these sketch-based user interfaces, from sequencing data
In, we select about 20 pairs of apparent ncRNA ratios of pairing to come more normal group and cancer group first, 29 normal samples,
50 adenocarcinoma of lung early stage samples, the pairing in terms of race, gender and smoking state of these adenocarcinoma of lung samples.Use support vector machines
It returns feature and eliminates (SVM-RFE) feature selecting and svm classifier algorithm, it has been found that a combination by 5 ncRNA ratios,
All measurement parameters can be made to reach prediction accuracy 100%, measurement parameter includes sensibility, specificity, positive predictive value
(PPV), area (AUC) under negative predictive value (NPV) and ROC curve.Fig. 4 shows representativeness ncRNA ratios numerator label 50
Expression value in example adenocarcinoma of lung and 29 normal samples.Even if Fig. 5 is described using unsupervised hierarchical clustering, adenocarcinoma of lung with
Normal sample can distinguish and the mistake of none single sample point.
Comparative example 1
The standard that additional C. nematode Cel-miR-54 has not been to circulation microRNA sequencing controls
In order to determine that circulation small molecule ncRNA marks the detection to lung cancer, we execute horizontal small point of full gene group
(smRNA-seq) is sequenced in sub- ncRNA, saves cost and sample using based on the sample sets of Human plasma samples.We are first
SmRNA-seq is carried out to determine blood plasma small molecular ribonucleic acid microRNAs and some other circulation small molecule non-coding
RNAs (sncRNAs), 7 sample sets used include 30 high-risk healthy individuals (normal healthy controls), 30 benign protuberance lesions,
30 early stage adenocarcinomas of lung and 15 prognosis of squamous cell lung cancer (SCC).Each sample set includes 15 samples.Normal control, it is benign and
Cancer sample matches in terms of age, sex, race and smoking state.Sample is adopted as expected in Rush University medical center
Collection.Control group, optimum group and adenocarcinoma groups use two sample sets, one sample set of SCC.Each sample set includes 500 μ L etc.
Pooled plasma is measured, smRNA-seq is used for.This process is wishing the completion of city (CA) Illumina next generation's microarray dataset.Greatly
About 20,000,000 reading samples generate the 90% of data and compare with human genome.
Since C- nematode Cel-miR-5429 is that human body is no, in sequencing, it can be used as external is added and compares.
Before RNA is extracted, equivalent Cel-miR54 is added in each sample set.In all sample sets, it is intended that read equivalent cel-
miR-54.As shown in Figure 1, the cel-miR-54 data that each collection is read in 7 sample sets are different.One adenocarcinoma of lung group is read
Getting greatest measure is 200.It is 0 that SCC group, which reads numerical value,.Thus, it is believed that additional Cel-miR-54 control, to smRNA-
The standardization of sequencing data is not up to standard.
Comparative example 2
Obtained by control of the additional C. nematode Cel-miR-54 as small molecule ncRNA circulation quantitative RT-PCR (RT-qPCR)
The standardization of data is not also up to standard
Assuming that external source C. nematode Cel-miR-54 is small molecule ncRNA circulation RT-PCR (RT-qPCR) data normalization
One additional control.We select 129 samples (29 normal healthy controls, 50 adenocarcinomas of lung, 35 benign and 15 SCC), into
The RT-qPCR of row Cel-miR-54.Equivalent Cel-miR-54 is added in equivalent blood plasma (200 μ l), single blood in these blood plasma
Slurry sample is before RNA extraction.As shown in Figure 2 A, it has been found that the CT value of issued external control Cel-miR-54 is very not
Stable；CT value approximate range is 14-34.Highest and lowest CT value correlation has 40 times of difference with initial data in about 20 CT
It is different.Because being added to equivalent Cel-miR-54, it is desirable to have similar CT value to same sample.It is therefore believed that additional C.
Standardization of the nematode Cel-miR-54 as the control the data obtained of small molecule ncRNA circulation quantitative RT-PCR (RT-qPCR)
It is not up to standard.
Comparative example 3
Endogenous control is not up to standard to the standardization of small molecule ncRNA circulation quantitative RT-PCR (RT-qPCR) data
We are added control such as Cel-miR-54 with external source and have failed to the standardization of circulation ncRNART-qPCR data, I
Think whether can be standardized circulation ncRNART-qPCR data with endogenous control.Based on issued report, we are selected
The endogenous control of has-miR-19130 and has-miRNAs, Let-7d, Let-7g and Let-7i 31 as us.We make
With with do identical blood plasma when external source compares cel-miR-54 (Fig. 2), extract equivalent body from same volume (200 μ l) plasma sample
Product RNA (about 2 μ l), and to identical 129 parts of samples, RT-qPCR is carried out using endogenous control.As shown in Fig. 2, announced
Endogenous control includes has-miR-191 CT value (Fig. 2 B) and has-MiRNAs, Let-7d, Let-7g and Let-7i (Fig. 2 C)
Average value is equally distributed different and unstable.It is therefore believed that reference pair is selected to shine as circulation ncRNA RT-qPCR data
Standardization it is improper.
Above description is not limitation of the present invention, and the present invention is also not limited to the example above.The art it is common
Within the essential scope of the present invention, the variations, modifications, additions or substitutions made also should belong to protection of the invention to technical staff
Range, protection scope of the present invention are subject to claims.
Claims (11)
1. a kind of method for selecting biomarker pair, includes the following steps
(1) type of ncRNAs in biological sample is determined；
(2) content of ncRNAs in biological sample is determined；
(3) ratio in each biological sample between any two kinds of ncRNA is calculated, according to the data of RT-qPCR, in same sample
The ratio ncRNA1/ncRNA2 of 2 small molecule ncRNA contents, which is used, compares CT method 2-ΔCTIt is calculated, Δ CT=CTncRNA1-
CTncRNA2；
(4) it according to the cell mean of every kind of ncRNA in multiple biological sample groups, calculates between any two kinds of ncRNA cell means
Ratio；
(5) best ncRNAs pairs of SVM-RFE algorithms selection is selected using support vector machines cycle characteristics, support vector machines circulation is special
Property selection SVM-RFE algorithm include:
A, the feature that initialization data set includes；
B, the SVM of training dataset；
C, according to 2 ranking feature of ci=(wi)；
D, the 50% of inferior grade feature is rejected；
E, return step b；
(6) using ncRNAs pairs of ratio as the index for being grouped sample.
2. the method for selection biomarker pair as described in claim 1, it is characterised in that: the biological sample is blood plasma；
The biological sample group includes at least normal specimens group, disease sample group；The ncRNA include miRNA, snoRNA, piRNA,
SiRNA and tRNA.
3. the method for selection biomarker pair as claimed in claim 2, it is characterised in that: the disease sample group includes cancer
Disease sample sets, benign tumour sample sets.
4. the method for selection biomarker pair as described in claim 1, it is characterised in that: the step (1) includes that RNA is mentioned
It takes and is sequenced with microRNA.
5. the method for selection biomarker pair as claimed in claim 4, it is characterised in that: the RNA extraction is by blood plasma
It is extracted with TRIzol reagent, absorption in silicon dioxide film closing column is added, the RNA of absorption is collected after cleaning.
6. the method for selection biomarker pair as claimed in claim 4, it is characterised in that: pass through SMARTer smRNA-
Seq method is sequenced, specifically include by RNA sample carry out the connection of 3 ' connectors, 5 ' RT primer annealings, 5 ' connector connections, reverse transcription,
PCR amplification.
7. the method for selection biomarker pair as described in claim 1, it is characterised in that: by anti-in the step (2)
Transcription and PCR quantitative (RT-qPCR) determine the content of blood plasma ncRNAs.
8. the method for selection biomarker pair as claimed in claim 7, it is characterised in that: use Taqman miRNA reagent
Box carries out RT-qPCR detection.
9. the method for selection biomarker pair as described in claim 1, it is characterised in that: the step (4) includes by blood
Starch ncRNA concentration by log2 convert, using SPSS20.0 software progress non-matching T inspection, more different biological sample groups it
Between average ncRNA ratio, significant p- value is set as 0.05.
10. a kind of adenocarcinoma of lung diagnosis biomarker pair obtained by the selection of claim 1 the method, selected from the following group
miR378a-3p/miR126-5p、sno-DR119/tRNA-Thr-ACG、sno-ACA33/miR378a-3p、tRNA-Thr-
ACG/sno-U57、tRNA-Thr-ACG/miR378a-3p。
11. diagnosis biomarker is to the purposes in preparation adenocarcinoma of lung diagnostic kit as claimed in claim 10.
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| WO2015165779A2 (en) * | 2014-05-01 | 2015-11-05 | Stichting Vu-Vumc | Small ncrnas as biomarkers |
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| Plasma microRNA biomarkers for detection of mild cognitive impairment;Kira S. Sheinerman et al.;《AGING》;20120930;第4卷(第9期);590-605、17-18 |
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