CN117660640A - Methylation biomarker, kit and method for auxiliary detection of EGFR gene mutation of lung cancer somatic cells - Google Patents
Methylation biomarker, kit and method for auxiliary detection of EGFR gene mutation of lung cancer somatic cells Download PDFInfo
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Abstract
The invention discloses a methylation biomarker, a kit and a method for auxiliary detection of EGFR gene mutation of lung cancer somatic cells, wherein the methylation biomarker comprises any one of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986 and chr10: 94303998-94304199. The inventor of the invention finds that 224 DNA methylation areas including chr19:13198677-13198878 and the like can assist in detecting whether EGFR genes in lung cancer somatic cell samples have harmful mutation, and can overcome the problem of low single DNA methylation signals, and improve the sensitivity and specificity of detection, thereby providing more effective auxiliary detection service for clinical targeted medication treatment of lung cancer patients and the like.
Description
Technical Field
The invention belongs to the technical field of biology, and particularly relates to a methylation biomarker, a kit and a method for auxiliary detection of EGFR gene mutation of lung cancer somatic cells.
Background
From a pathological and therapeutic perspective, lung cancer can be broadly divided into two major categories, non-small cell lung cancer (non small cell lung cancer, NSCLC) and small cell lung cancer (small cell lung cancer, SCLC), wherein non-small cell lung cancer accounts for about 80% -85%, including histological subtypes such as adenocarcinoma and squamous carcinoma, and the balance small cell lung cancer [ national health committee of the people's republic of China, herd, wu Yilong, gao Shugeng, & Wang Jie (2022) & primary lung cancer diagnosis and treatment guide (2022 edition) & rational drug discovery in china, 19 (9), 28 ]. Mutations, fusions and gene expansion of various cancer-related genes have also been demonstrated in many reports to have a highly correlated relationship with the formation of lung cancer, particularly non-small cell lung cancer.
Epidermal Growth Factor Receptor (EGFR) is a membrane surface receptor with tyrosine kinase activity, and the 3 subregions involved are critical for mediating signal transduction. By forming various dimers, either homologous or heterologous, with other receptors, different extracellular stimuli can be introduced into the cell on the one hand, and on the other hand, various downstream signal pathways can be activated and various biological effects can be produced, transcription factors are regulated and transcription of the relevant genes activated, triggering anti-apoptotic, cell proliferation, angiogenesis and even invasion and metastasis processes of tumors. Targeted treatment of lung cancer is currently widely used for non-small cell cancers (non-small cell lung cancer, NSCLC) containing EGFR mutations, because the former (EGFR) is one of the common driving genes for the latter (NSCLC), and cancer cells containing EGFR mutations have a growth advantage over the same class of cells with wild-type on the one hand, and also have increased sensitivity to EGFR tyrosine kinase inhibitors on the other hand [ Eberhard DA, johnson BE, amler LC, et al, mutations in the epidermal growth factor receptor and in KRAS are predictive andprognostic indicators inpatients with non-small-cell lung cancer treated with chemotherapy alone and in combination with erlotinib.j Clin oncol.2005;23 (25) 5900-5909.Doi:10.1200/JCO.2005.02.857]. Furthermore, the presence of EGFR mutations can be a prognostic factor. EGFR mutations are most common in lung adenocarcinoma, and the mutation frequency varies among different ethnic groups, with Asians (20% -40%) being more common than caucasians (5% -20%). Changes in exon 18-21 other than EGFR mutations are most common, typically exon 19 deletions and exon point mutations [ John T, liu G, tsao MS. Overview of molecular testing in non-small-cell growth cancer: mutational analysis, gene copy number, protein expression and otherbiomarkers ofEGFR for the prediction ofresponse to tyrosine kinase inhibitors. Oncogene.2009;28Suppl 1:S14-S23.doi:10.1038/onc.2009.197].
The large amount of clinical data published indicates that tumors have spatial and temporal heterogeneity, in that the sensitive and resistant mutations corresponding to the targeted drug are diverse, e.g., mutations may occur in different genes, at different sites in the same gene, or in different mutation types (point mutations, small fragment indels, copy number variations, gene fusions) in the same gene. Histobiopsy pathology as a gold standard for clinically establishing tumor molecular typing, it is often necessary to align the genomic sequences of tumor tissue with normal tissue from the same individual to locate the location and type of mutation. However, in most cases specimens of normal tissue controls are often difficult to obtain, which presents a significant challenge for tissue biopsies and their detection techniques. In addition, tissue biopsy requires surgical sampling, puncturing, etc. of the patient, and is not physiologically acceptable because of some damage to the patient's body. Peripheral blood free DNA (cfDNA) detection is a non-invasive "liquid biopsy" technique that is simpler and easier to handle and more acceptable to patients than tissue biopsy.
In the human genome, DNA methylation is an important epigenetic modification, plays an important role in gene transcription, and is involved in transcriptional regulation along with histone modification, chromatin conformation remodeling. In contrast, the tumor is mainly characterized by hypermethylation of cancer suppressor gene and DNA repair gene, hypomethylation of repeated sequence DNA, imprinting loss of some genes, etc., so that the tumor has a very close relationship with the occurrence of the tumor. By analyzing high-throughput methylation sequencing data of tumor tissue samples with different mutations, after a reasonable biological statistical model is constructed, specific mutation conditions in unknown samples can be effectively predicted, so that on one hand, the experiment and analysis cost can be effectively reduced, the detection sensitivity and specificity can be improved, and on the other hand, the method has a good promotion effect on basic clinical research. Currently, conventional methods for detecting EGFR gene mutation mainly comprise WGS, WES, gene panel, RNA-seq and the like, and methods for detecting methylation by cfDNA (cfDNA) comprise a polymerase chain reaction-based technology, a method related to a next-generation sequencing technology and the like.
In view of the foregoing, it is desirable to find a detection method that is not only simple and feasible, but also overcomes the low methylation signal of a single DNA while improving the sensitivity and specificity of detecting mutations.
Disclosure of Invention
Based on the above, the invention aims to provide a methylation biomarker, a kit and a method for assisting in detecting EGFR gene mutation of lung cancer somatic cells.
The technical scheme for realizing the aim of the invention comprises the following steps.
In a first aspect of the invention, there is provided a methylation biomarker for assisting in detecting EGFR gene mutation in lung cancer somatic cells, wherein the methylation biomarker comprises any one of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986 and chr10: 94303998-94304199.
In a second aspect, the invention provides the use of a reagent for detecting the methylation biomarker in the preparation of a kit for predicting, detecting, classifying, monitoring treatment, prognosticating or otherwise evaluating EGFR gene mutation in lung cancer somatic cells.
In a third aspect of the invention, an auxiliary detection kit for lung cancer somatic EGFR gene mutation is provided, which comprises reagents for detecting the methylation difference degree of the methylation biomarker.
In a fourth aspect, the invention provides the use of the above-described kit for predicting, detecting, classifying, monitoring therapy, prognosticating or otherwise assessing EGFR gene mutation in lung cancer somatic cells.
In a fifth aspect of the invention, a method for assisted detection of lung cancer somatic EGFR gene mutation is provided. The method comprises the following steps of extracting peripheral blood DNA of a biological sample to be detected; performing bisulfite conversion on the DNA; detection of the degree of methylation difference of the above-mentioned methylation biomarkers.
The inventor of the invention finds 224 DNA methylation areas including chr19:13198677-13198878 and the like, establishes a prediction model by adopting random forest or logistic regression and other modes aiming at different combination detection of the areas, finds that the detection can assist in detecting whether EGFR genes in lung cancer somatic cell samples have harmful mutation or not, and can also overcome the problem of low single DNA methylation signals and improve the detection sensitivity and specificity, thereby providing more effective auxiliary detection service for clinical targeted medication treatment and other aspects of lung cancer patients. Moreover, based on detecting the methylation states of the DNA methylation biomarkers in the sample somatic cells, the methylation detection kit can also more comprehensively analyze methylation changes in occurrence and development of lung cancer, is applied to early screening, auxiliary diagnosis, curative effect evaluation, recurrence monitoring and other stages of lung cancer, and provides more accurate and sensitive detection service for clinic.
Drawings
FIG. 1 is a plot of the Heatmap of 224 markers in 14 EGFR_mut and 6 EGFR_wt samples of the example.
Fig. 2 is a ROC plot of 224 markers in 14 egfr_mut and 6 egfr_wt samples in the example.
Detailed Description
The present invention will be described more fully hereinafter in order to facilitate an understanding of the present invention. This invention may be embodied in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. The terminology used in the description of the invention herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the invention. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The experimental procedures, which do not address the specific conditions in the examples below, are generally followed by conventional conditions, such as those described in Green and Sambrook et al, molecular cloning, an experimental guideline (Molecular Cloning: A Laboratory Manual, 2013), or by the manufacturer's recommendations. The various chemicals commonly used in the examples are commercially available.
In some embodiments of the invention, a methylation biomarker for assisting in detecting EGFR gene mutation of lung cancer somatic cells is disclosed, wherein the methylation biomarker comprises any one of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986 and chr10: 94303998-94304199.
In some of these embodiments, the methylation biomarker comprises any of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986, and chr10: 94303998-94304199.
In some of these embodiments, the methylation biomarker comprises any of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986, chr10:94303998-94304199, chr1:50881885-50882086, chr9:130700842-130701043, chr9:96068585-96068786, chr6:28303851-28304336, and chr17: 59539353-59539707.
In some of these embodiments, the methylation biomarker comprises at least one of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986, chr10:94303998-94304199, chr1:50881885-50882086, chr9:130700842-130701043, chr9:96068585-96068786, chr6:28303851-28304313, chr17:5953953-593977, chr9:135037068-135037269, chr7:96644701-96644902, chr6:144608097-144608298, chr17:6277107-6277538, chr6:17281246-17281447, chr17:39594-5995, chr10:13149539-131498876, chr6:143999585-1439786, chr7: 5458981 and chr 780: 177054059-177054426.
In some of these embodiments, the methylation biomarker comprises chr19:13198677-13198878, chr6:25882281-25882482, chr6: the patent publication, "patent" is a "patent" is "is" used "to" is "is" used "to" is "to" is "used" to "to" is "to" is "to" to "is" to "to" is "to" is "to" to "is" to "is" to "to" is "to" to "is" to "to" is "to" to "is" to "to" is "to" to "is" to "to" is "to" to "is" to "is" to "to" either "readily". "or" to "to" "".........to "to" to novel to to novel to novel to "to to novel to to" to "to to novel to" to to "to" to novel to to novel to novel to to novel to novel to to novel to to.
In some of these embodiments, the methylation biomarker comprises chr19:13198677-13198878, chr6:25882281-25882482, chr6: the patent claims and patent claims are to be expressly described herein.A patent claims is also to be expressly described.A patent claims.A patent claims is also to be expressly described.A patent claims.3.A patent claims is also to be expressly described.A patent claims.8.3.seven-g.seven-g.seven-g., g, g.........to-g to-g to-to-g to-g to-to-to to g to to, chr15:65197802-65198043, chr2:191684930-1916868131, chr14:23775565-23775566, chr10:131330618-131330819, chr19:12939466-12939667, chr2:19557394-19557595, chr1:200443203-200443404, chr2:175193256-175193457, chr10:131309043-131309244, chr2:1769947984-17698185, chr1:180182537-180182738, chr2:17538193598, chr16:862986-86613187, chr1:226556812-226557013, chr22:173565-47766, chr7:928233-92238484, chr19:51231856, chr7:9282306-230736, 15459. 154073560, chr20:23968749-23968950, chr1:197887568-197887769, chr3:128210029-128210260, chr8:106104599-106104800, chr10:71892512-71892713, chr10:88517527-88517728, chr7:43690166-43690367, chr16:89034057-89034258, chr19:58095347-58095548, chr3:94646455-9464556, chr7:27554-27232755, chr12:67676762-6767262, chr7:41869754-41869955, chr1:16762-167868863, chr19:1466887-1467112, chr12:035035204-112405, chr1:5290-5388111, chr14-538811, and chr14-388525. 36990953-36991154, and at least one of the following.
In some of these embodiments, the methylation biomarker further comprises at least one of the other markers selected from table 1.
In other embodiments of the invention, the use of a reagent for detecting the above-described methylation biomarkers in the preparation of a kit for predicting, detecting, classifying, monitoring therapy, prognosticating or otherwise evaluating EGFR gene mutation in lung cancer somatic cells is disclosed.
In other embodiments of the invention, a lung cancer somatic EGFR gene mutation assisted detection kit is disclosed, comprising reagents for detecting the degree of methylation difference of the above methylation biomarkers.
In some embodiments, the kit is prepared using polymerase chain reaction techniques, in situ hybridization techniques, enzymatic mutation detection techniques, chemical cleavage mismatch techniques, mass spectrometry techniques, gene chip techniques, or gene sequencing techniques, or a combination thereof.
In some embodiments, the polymerase chain reaction technique of the detection technique employed in the above-described kit includes, but is not limited to, RT-PCR, immuno PCR, nested PCR, fluorescent PCR, in situ PCR, membrane bound PCR, anchor PCR, in situ PCR, asymmetric PCR, long distance PCR, parachute PCR, gradient PCR, and the like; high throughput detection techniques include, but are not limited to, simplified genome methylation sequencing, whole genome methylation sequencing, DNA enrichment sequencing, pyrophosphate sequencing, sulfite conversion sequencing; detection techniques based on mass spectrometry, such as GC-MS, LC-MS, MALDI-TOFMS, FT-MS, ICP-MS, SIMS; based on chip detection platforms such as 450K and 850K methylation detection techniques.
In some of these embodiments, the detection methods employed by the above-described kits include, but are not limited to, at least one of fluorescent quantitative PCR, methylation specific PCR, digital PCR, DNA methylation chip, targeted DNA methylation sequencing, whole genome methylation sequencing, DNA methylation mass spectrometry.
In other embodiments of the invention, the use of the above-described kits for predicting, detecting, classifying, monitoring therapy, prognosticating or otherwise assessing lung cancer somatic EGFR gene mutation is disclosed.
In other embodiments of the invention, a method for aiding in the detection of EGFR gene mutation in lung cancer somatic cells is disclosed. The method comprises the following steps of extracting peripheral blood DNA of a biological sample to be detected; performing bisulfite conversion on the DNA; detection of the degree of methylation difference of the above-mentioned methylation biomarkers.
In some of these embodiments, the above-described methods include, but are not limited to, the following techniques: methylation-specific PCR, sulfite PCR sequencing, real-time quantitative methylation-specific PCR, and the like; high throughput detection techniques include simplified genome methylation sequencing, whole genome methylation sequencing, DNA enrichment sequencing, pyrophosphate sequencing, sulfite conversion sequencing, and the like; detection technology based on detection platforms such as mass spectrum; based on chip detection platforms such as 450K and 850K methylation detection techniques.
The invention is described in detail below with reference to the drawings and the specific embodiments.
Details of the methylation biomarkers (methylation regions) according to the present invention are shown in Table 1 below.
TABLE 1
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Wherein intronic is an intron, intersystemic is an intergenic sequence, exonic is an exon, upstream is an upstream fragment, downstream is a downstream fragment.
Example 1
The embodiment discloses a detection method for assisting in detecting EGFR gene mutation of lung cancer somatic cells by 224 methylation areas, which specifically comprises the following steps:
1. sample information
The 20 lung cancer samples contained 7 females and 13 males; the ages are between 21 and 78 years, and the average age is 56.9 years; the main diagnosis information is 10 cases of adenocarcinoma, 1 case of squamous carcinoma and 9 cases of other cases; stage 1, 4, 14, 1, respectively stage III, stage IV, stage 1 record deletions according to pathology (cancer different stages are outlined as cancer stage I: tumor in situ, not yet spread to any lymph node, possibly completely resected by surgery; cancer stage II: less than 5CM but spread to nearby lymph nodes, or between 5CM-7CM and possibly spread to any nearby lymph nodes, or greater than 7CM and not yet spread to nearby lymph nodes but possibly invading nearby tissue structures in the lung; cancer stage III: all more severe tumor states than stage II, can spread to extra-pulmonary lymph nodes, or invade nearby tissue in the lung, but not yet have distant metastasis yet occurred, it is difficult to completely resect the tumor by surgery; cancer stage IV: distant metastasis to contralateral lung, pleura, pericardium, or distant by blood); all 20 exceptional blood samples were subjected to whole exon and RNA-seq sequencing, mutation analysis was performed, and SNVs, indels and other information were obtained, which were 14 EGFR_mut and 6 EGFR_wt samples respectively according to EGFR mutant sample and EGFR wild type sample groupings.
2. Library building process and method
1. Peripheral blood DNA extraction and methylation database construction
1.1, extraction of peripheral blood DNA.
The procedure for extracting DNA from the lung cancer peripheral Blood sample was performed according to the DNeasy Blood & Tissue Kit protocol of QIAGEN.
1.2 conversion
The extracted peripheral blood DNA (50 ng) was subjected to bisulfite conversion to convert unmethylated cytosines in the DNA to uracil, while methylated cytosines remained unchanged, resulting in bisulfite-converted DNA, and the conversion was performed according to the EZ DNAMethylation-Lightning Kit instruction of Zymo Research.
1.3, terminal repair
The 17ul sample after the conversion was added to the following reagents for reaction:
the reaction was performed in a PCR instrument according to the following procedure:
when the second step (95 ℃) of the PCR reaction reaches 5min, the sample is immediately taken out of the PCR instrument and directly inserted into ice, and the sample is placed for more than 2min and then subjected to the next step of operation.
1.4 connection I
The following reaction liquid is prepared:
| component (A) | Single dose (μl) |
| The reaction product of the last step | 20 |
| H 2 O | 4 |
| MLB1 buffer | 8 |
| MLR1 reagent | 2 |
| MLR5 reagent | 2 |
| MLE1 enzyme | 2 |
| MLE5 enzyme | 2 |
| Reaction mixing volume | 40 |
The reaction was performed in a PCR instrument according to the following procedure:
| 37℃ | 30min |
| 95℃ | 5min |
| 10℃ | hold |
| thermal cover | 105℃ |
1.5 amplification I
The following reaction liquid was prepared
The reaction was performed in a PCR instrument according to the following procedure:
1.6 purification I:
the amplified I reaction product was purified by adding 166ul of a 1:6 fold dilution of AgencourtAMPure Beads (half an hour prior to room temperature equilibration) eluting with 21 μl EB, and the purification steps were as follows:
the reaction product of the previous step was centrifuged, and 166. Mu.l of Agencourt AM Pure Beads diluted 1:6 times was added to each sample, and the mixture was blown and mixed with a pipette. Incubate at room temperature for 5min. Centrifuging, and standing on a magnetic rack for 5min. The supernatant was aspirated. 200 μl of 80% EtOH is added, the mixture is left stand for 30s, ethanol is sucked away, the mixture is centrifuged after repeated once, the PCR tube is placed on a magnetic rack, the residual ethanol is sucked away, and the magnetic beads are uncapped and dried for 2-3 min, and the mixture is not overdried. Adding 21 μl EB for eluting, stirring with a pipette, and standing at room temperature for 3min. Centrifuging, placing the PCR tube on a magnetic rack, and standing for 3min. Mu.l of the supernatant was pipetted into a new PCR tube.
1.7 connection II
The following reaction liquid is prepared:
| component (A) | Volume (mul) |
| Reaction volume of the last step | 20 |
| H 2 O | 4 |
| MSB1 buffer | 8 |
| MSR1 reagent | 2 |
| MSR5 reagent | 2 |
| MSE1 enzyme | 2 |
| MSE5 enzyme | 2 |
| Total volume of | 40 |
The reaction was carried out in a PCR instrument according to the following procedure
| Temperature (temperature) | Time | Cycle number |
| 37℃ | 30min | 1 |
| 95℃ | 5min | 1 |
| 10℃ | Hold | 1 |
1.8Indexing PCR (amplification product library construction)
The following reaction liquid is prepared:
| component (A) | Volume (mul) |
| Reaction volume of the last step | 40 |
| H 2 O | 6 |
| 2XKAPAHiFiHotStartReadyMix | 8 |
| I5 linker primers | 2 |
| I7 linker primers | 2 |
| Total volume of | 100 |
The reaction was carried out in a PCR instrument according to the following procedure
1.9 purification II
The product after the Indexing PCR reaction was purified by adding Agencourt AM Pure Beads (half an hour prior to equilibration at room temperature), eluting with 41. Mu.l EB, and the purification steps were as follows:
the reaction product of the previous step was centrifuged, and 71. Mu.l of undiluted Agencourt AM Pure Beads was added to each sample, and the mixture was blown and mixed with a pipette. Incubate at room temperature for 5min. Centrifuging, and standing on a magnetic rack for 5min. The supernatant was aspirated. 200 μl of 80% EtOH was added, left to stand for 30s, the ethanol was removed, and after repeating the steps once, the PCR tube was centrifuged and placed on a magnetic rack to remove the remaining ethanol. The cover is opened to dry the magnetic beads for 2 to 3 minutes, and the magnetic beads are not excessively dried. Adding 41 μl EB for eluting, stirring with a pipette, and standing at room temperature for 3min. Centrifuging, placing the PCR tube on a magnetic rack, and standing for 3min. Mu.l of the supernatant was pipetted into a new PCR tube. Quantitative Qubit: 1 μl was taken and the library was quantified with Qubit dsDNA HS Assay Kit.
2. And (3) carrying out oligonucleotide probe capturing enrichment on the samples after library establishment to obtain the on-machine final library in the specific area. The hybridization capture kit was xGen Lockdown Reagents from IDT company, and was specifically prepared according to the instructions.
3. And sequencing the sample after hybridization capture by using a sequencer of Illumina company to obtain a sequencing result.
4. And (5) analyzing the machine-starting data:
performing conventional bioinformatics analysis on the original data of the sequencer, filtering low-quality reads (reads) through fastp, removing adapters, consensus sequences and PolyA/T at the two ends of the reads to obtain ideal insert sequences (target intervals), comparing the reads with positions corresponding to hg19 by using bismark, performing de-duplication on the reads according to UMI to obtain real reads data (bam file) obtained by capturing each sample by a probe, and performing statistics and analysis on the bam file to obtain methylation data for subsequent data re-analysis.
5. Relevant clean-up and processing analyses were performed on the raw sequencing data [ Liang, W.et al, non-invasive diagnosis of early-stage lung cancer using high-throughput targeted DNA methylation sequencing of circulating tumor DNA (ctDNA). 2019.9 (7): p.2056 ], and the percent methylated cytosine (beta value) for each region was determined based on reads.
6. For these 6 egfr_wt and 14 egfr_mut samples (14 samples contain 2 nonframeshift deletion (non-frameshift deletion), 2 nonframeshift deletion-inserts (non-frameshift indels), 13 nonsynonymous SNV (non-synonymous mutations), part of the samples have multiple mutation forms) methylation detection information, 224 markers in table 1 are used for analysis, the hetmap is shown in fig. 1, these 20 samples are randomly sliced 50 times (the number of balanced wt and mut samples in each slice) according to a ratio of 1:1, each slice is modeled inside the train set by using Random Forest (Random Forest), the risk score of each sample is calculated inside the test set by using the model, and the risk score is compared with the standard diagnosis to obtain the discrimination sensitivity, the specificity, the AUC, the NPV, the PPV and the like of the methylation region combination, and the 50 modeling AUC is shown in fig. 2. The average probability of each marker was calculated 50 times, the top 5marker was taken, and the predicted performance AUC of each marker is shown in table 2 below, from the AUC, it can be seen that these markers have good predicted performance (the ranking derived from the model feature importance, there is a slight difference from the ranking of the predicted performance AUC of each marker, but the overall trend of the ranking is consistent, and the AUC levels of the following top5 markers all belong to the first rank).
TABLE 2 predictive Performance AUC of top5 marker over 20 samples
| marker ID | AUC |
| chr19:13198677-13198878 | 0.9191 |
| chr6:25882281-25882482 | 0.9200 |
| chr6:25882382-25882583 | 0.9038 |
| chr2:232545785-232545986 | 0.9163 |
| chr10:94303998-94304199 | 0.9210 |
Example 2
For the 14 EGFR_mut samples of example 1 (14 samples contained 2 nonframeshift deletion (non-frameshift deletion), 2 nonframeshift deletion-inserts (non-frameshift indels), 13 nonsynonymous SNV (non-synonymous mutations), part of the samples had multiple mutant forms at the same time), they were used as positive groups, 6 EGFR_wt samples as negative groups were matched, the same 50 cuts as in example 1 were used, the combinations of 5marker,10marker,20marker,50marker,100marker were used, respectively, and modeling was performed using Random Forest (Random Forest), wherein 5marker was
chr19:13198677-13198878，chr6:25882281-25882482，chr6:25882382-25882583，
chr2:232545785-232545986, chr10:94303998-94304199; the combination of 10, 20, 50, 100 markers is a randomly increased marker on a 5-marker basis, for example 10 markers (chr 19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986, chr10:94303998-94304399, chr1:50881885-50882086, chr9:130700042-130701043, chr9:96068585-96068786, chr6:28303851-28304362, chr17:5955953-59539707), 20marker (chr19: 13198677-13198878, chr6:25882281-25882482, chr6:25882382-258823, chr2:232545785-232545986, chr10:94303998-94304399, chr1:50881885-50882086, chr9:130842-130701043, chr9:968585-96068786, chr6:28303851-28304362, chr17:595595553-595507, chr9:135037068-135037269, chr7:966401-9649602, chr6:144608097-144608298, chr17:62107-62308, chr6:17281246-17281447, chr17:3994-5959595949350-131498, chr5-96498, chr6:999585-999586, chr9:549986, chr7-1357269, chr7:54955055-5506, christ1-549539, christmas 5-54955, christmas 6:5-545506, christmas 6:5-5455022950marker(chr19:13198677-13198878，chr6:25882281-25882482，chr6:25882382-25882583，chr2:232545785-232545986，chr10:94303998-94304199，chr1:50881885-50882086，chr9:130700842-130701043，chr9:96068585-96068786，chr6:28303851-28304336，chr17:59539353-59539707，chr9:135037068-135037269，chr7:96644701-96644902，chr6:144608097-144608298，chr17:62775107-62775308，chr6:17281246-17281447，chr17:59539594-59539795，chr10:131498350-131498576，chr6:143999585-143999786，chr7:5458780-5458981，chr2:177054059-177054426，chr2:176994061-176994568，chr10:90966580-90966887，chr1:43832835-43833036，chr12:51318406-51318607，chr20:31148589-31148790，chr6:126949342-126949543，chr10:126429186-126429387，chr1:48233421-48233622，chr2:237476488-237476689，chr2:19557080-19557476，chr19:42927934-42928135，chr10:128594020-128594221，chr1:18969596-18969797，chr1:225662379-225662580，chr20:44838900-44839101，chr19:12899476-12899677，chr4:74862011-74862212，
chr1:91184332-91184533，chr7:19812427-19812628，chr2:177054492-177054693，
chr9:126769909-126770110，chr15:74725581-74725782，chr15:40340149-40340350，
chr1:233749552-233749753，chr7:6866700-6866924，chr14:36983461-36983662，
chr10:102905600-102905801，chr1:160712658-160712859，chr2:7017706-7017907，
chr16:30817087-30817288)、100marker(chr19:13198677-13198878，chr6:25882281-25882482，
chr6:25882382-25882583，chr2:232545785-232545986，chr10:94303998-94304199，
chr1:50881885-50882086，chr9:130700842-130701043，chr9:96068585-96068786，
chr6:28303851-28304336，chr17:59539353-59539707，chr9:135037068-135037269，
chr7:96644701-96644902，chr6:144608097-144608298，chr17:62775107-62775308，
chr6:17281246-17281447，chr17:59539594-59539795，chr10:131498350-131498576，
chr6:143999585-143999786，chr7:5458780-5458981，chr2:177054059-177054426，
chr2:176994061-176994568，chr10:90966580-90966887，chr1:43832835-43833036，
chr12:51318406-51318607，chr20:31148589-31148790，chr6:126949342-126949543，
chr10:126429186-126429387，chr1:48233421-48233622，chr2:237476488-237476689，
chr2:19557080-19557476，chr19:42927934-42928135，chr10:128594020-128594221，
chr1:18969596-18969797，chr1:225662379-225662580，chr20:44838900-44839101，
chr19:12899476-12899677，chr4:74862011-74862212，chr1:91184332-91184533，
chr7:19812427-19812628，chr2:177054492-177054693，chr9:126769909-126770110，
chr15:74725581-74725782，chr15:40340149-40340350，chr1:233749552-233749753，
chr7:6866700-6866924，chr14:36983461-36983662，chr10:102905600-102905801，
chr1:160712658-160712859，chr2:7017706-7017907，chr16:30817087-30817288，
chr6:10385045-10385246，chr2:63276397-63276598，chr6:28304370-28304571，
chr17:8532678-8532879，chr1:18971975-18972176，chr3:15450877-15451078，
chr1:51983638-51983839，chr12:54418011-54418212，chr14:61111437-61111638，
chr11:62308432-62308633，chr10:131498289-131498490，chr6:28303954-28304241，
chr15:65197802-65198043，chr2:191684930-191685131，chr14:23775665-23775866，
chr10:131330618-131330819，chr19:12939466-12939667，chr2:19557394-19557595，
chr1:200443203-200443404，chr2:175193256-175193457，chr10:131309043-131309244，
chr2:176947984-176948185，chr1:180182537-180182738，chr2:175193389-175193598，
chr16:86612986-86613187，chr1:226556812-226557013，chr22:47173565-47173766，
chr7:92238283-92238484, chr19:51231655-51231856, chr7:92237965-92238236, chr4:154073359-154073560, chr20:23968749-23968950, chr1:197887568-197887769, chr3:128210029-128210260, chr8:106104599-106104800, chr10:71892512-71892713, chr10:88517527-88517728, chr7:43690166-43690367, chr16:89034057. -89034258, chr19:58095347-58095548, chr3:946455-9464556, chr7:27232554-27232755, chr12:676767676922-67676714123, chr7:41869754-41869955, chr1:167868662-167868863, chr19:1466887-1467112, chr12:112035204-112035405, chr1:53528890-53529111, chr2:23857855-238578456, chr14:36990953-36991154), under these marker numbers, the modeled average auc and sensitivity, specificity is shown in table 3 below, with 14 egfr_muts under 5, 10, 20, 50, 100 markers, respectively, judged as 12, 13, and 12 samples of egfr_mut. Indicating that a combination of different numbers of these methylated regions can be used as markers to aid in the detection of the presence or absence of EGFR gene mutations in a somatic sample.
TABLE 3 Table 3
Auc is the area under the ROC curve, se is sensitivity, sp is specificity, acc is accuracy, ppv is a positive predictive value, npv is a negative predictive value, adjppv is a corrected positive predictive value, adjnpv is a corrected negative predictive value, and the same applies below.
Example 3
For the 14 egfr_mut samples as positive group and the 6 egfr_wt samples as negative group in example 1 (20 samples total), these samples were positive according to 14: the 6 negative principle was randomly given to sample labels, 50 Random cuts were made as in example 1, and then a combination of 5, 10, 20, 50, 100 markers was used as in example 2, respectively, and modeling was performed using Random Forest (Random Forest). This procedure was independently repeated 25 times, and the average auc and sensitivity, specificity of the modeling were counted for the number of markers described above, as shown in table 4 below.
TABLE 4 Table 4
The results show that example 3, which is a random reference, the model has no discriminatory power at all for sample groupings of randomly assigned tags (Mean auc < 0.5).
The above results show that the model performed well above the random reference (case shown in example 3) by grouping and modeling according to the sample facts case (case shown in example 1 and example 2), indicating that the findings in example 1 and example 2 are of practical biological significance.
The technical features of the above-described embodiments may be arbitrarily combined, and all possible combinations of the technical features in the above-described embodiments are not described for brevity of description, however, as long as there is no contradiction between the combinations of the technical features, they should be considered as the scope of the description.
The above examples illustrate only a few embodiments of the invention, which are described in detail and are not to be construed as limiting the scope of the invention. It should be noted that it will be apparent to those skilled in the art that several variations and modifications can be made without departing from the spirit of the invention, which are all within the scope of the invention. Accordingly, the scope of protection of the present invention is to be determined by the appended claims.
Claims (10)
1. A methylation biomarker for assisting in detecting EGFR gene mutation of lung cancer somatic cells, which is characterized by comprising any one of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986 and chr10: 94303998-94304199.
2. The methylation biomarker for assisting in detecting EGFR gene mutation of lung cancer somatic cells according to claim 1, wherein the methylation biomarker comprises any one of chr19:13198677-13198878, chr6:25882281-25882482, chr6:25882382-25882583, chr2:232545785-232545986 and chr10: 94303998-94304199.
3. The methylation biomarker for assisting in detecting lung cancer somatic EGFR gene mutation according to claim 2, wherein the methylation biomarker further comprises any of chr1:50881885-50882086, chr9:130700042-130701043, chr9:96068585-96068786, chr6:28303851-28304336 and chr17: 59539353-59539707.
4. The methylation biomarker for assisting in detecting EGFR gene mutation in lung cancer somatic cells according to claim 2, wherein the methylation biomarker further comprises chr1:50881885-50882086, chr9:130700042-130701043, chr9:96068585-96068786, chr6:28303851-28304313, chr17:5955953-59539707,
chr9:135037068-135037269，chr7:96644701-96644902，chr6:144608097-144608298，
any of chr17: 62775107-6275508, chr6:17281246-17281447, chr 17:59594-59397795, chr 10:1314984350-131498876, chr6:143999585-143999786, chr7:5458780-5458981 and chr2: 177054059-177054426.
5. The methylation biomarker for assisting in detecting EGFR gene mutation in lung cancer somatic cells according to claim 2, wherein the methylation biomarker further comprises chr1:50881885-50882086, chr9:130700042-130701043, chr9:96068585-96068786, chr6:28303851-28304313, chr17:5955953-59539707,
chr9:135037068-135037269，chr7:96644701-96644902，chr6:144608097-144608298，
chr17:62775107-62775308，chr6:17281246-17281447，chr17:59539594-59539795，
chr10:131498350-131498576，chr6:143999585-143999786，chr7:5458780-5458981，
chr2:177054059-177054426，chr2:176994061-176994568，chr10:90966580-90966887，
chr1:43832835-43833036，chr12:51318406-51318607，chr20:31148589-31148790，
chr6:126949342-126949543，chr10:126429186-126429387，chr1:48233421-48233622，
chr2:237476488-237476689，chr2:19557080-19557476，chr19:42927934-42928135，
chr10:128594020-128594221，chr1:18969596-18969797，chr1:225662379-225662580，
chr20:44838900-44839101，chr19:12899476-12899677，chr4:74862011-74862212，chr1:91184332-91184533，chr7:19812427-19812628，chr2:177054492-177054693，
chr9:126769909-126770110，chr15:74725581-74725782，chr15:40340149-40340350，
any of chr1: 233749552-23379753, chr7:6866700-6866924, chr14:36983461-36983662, chr10:102905600-102905801, chr1:160712658-160712859, chr2:7017706-7017907 and chr16: 30817087-30817288.
6. The methylation biomarker for assisting in detecting EGFR gene mutation in lung cancer somatic cells according to claim 2, wherein the methylation biomarker further comprises chr1:50881885-50882086, chr9:130700042-130701043, chr9:96068585-96068786, chr6:28303851-28304313, chr17:5955953-59539707,
chr9:135037068-135037269，chr7:96644701-96644902，chr6:144608097-144608298，
chr17:62775107-62775308，chr6:17281246-17281447，chr17:59539594-59539795，
chr10:131498350-131498576，chr6:143999585-143999786，chr7:5458780-5458981，
chr2:177054059-177054426，chr2:176994061-176994568，chr10:90966580-90966887，
chr1:43832835-43833036，chr12:51318406-51318607，chr20:31148589-31148790，
chr6:126949342-126949543，chr10:126429186-126429387，chr1:48233421-48233622，
chr2:237476488-237476689，chr2:19557080-19557476，chr19:42927934-42928135，
chr10:128594020-128594221，chr1:18969596-18969797，chr1:225662379-225662580，
chr20:44838900-44839101，chr19:12899476-12899677，chr4:74862011-74862212，
chr1:91184332-91184533，chr7:19812427-19812628，chr2:177054492-177054693，
chr9:126769909-126770110，chr15:74725581-74725782，chr15:40340149-40340350，
chr1:233749552-233749753，chr7:6866700-6866924，chr14:36983461-36983662，
chr10:102905600-102905801，chr1:160712658-160712859，chr2:7017706-7017907，
chr16:30817087-30817288，chr6:10385045-10385246，chr2:63276397-63276598，
chr6:28304370-28304571，chr17:8532678-8532879，chr1:18971975-18972176，
chr3:15450877-15451078，chr1:51983638-51983839，chr12:54418011-54418212，
chr14:61111437-61111638，chr11:62308432-62308633，chr10:131498289-131498490，
chr6:28303954-28304241，chr15:65197802-65198043，chr2:191684930-191685131，
chr14:23775665-23775866，chr10:131330618-131330819，chr19:12939466-12939667，
chr2:19557394-19557595，chr1:200443203-200443404，chr2:175193256-175193457，
chr10:131309043-131309244，chr2:176947984-176948185，chr1:180182537-180182738，
chr2:175193389-175193598，chr16:86612986-86613187，chr1:226556812-226557013，
chr22:47173565-47173766，chr7:92238283-92238484，chr19:51231655-51231856，chr7:92237965-92238236，chr4:154073359-154073560，chr20:23968749-23968950，
chr1:197887568-197887769，chr3:128210029-128210260，chr8:106104599-106104800，
chr10:71892512-71892713，chr10:88517527-88517728，chr7:43690166-43690367，
chr16:89034057-89034258，chr19:58095347-58095548，chr3:9464355-9464556，
chr7:27232554-27232755，chr12:67613922-67614123，chr7:41869754-41869955，
any one of chr1:167868662-167868863, chr19:1466887-1467112, chr12:112035204-112035405, chr1:53528890-53529111, chr2:23857855-238578456 and chr14: 36990953-36991154.
7. The methylation biomarker for assisting in detecting lung cancer somatic EGFR gene mutation according to claim 6, wherein the methylation biomarker further comprises at least one other marker selected from table 1.
8. Use of a reagent for detecting a methylation biomarker according to any of claims 1 to 7 in the preparation of a kit for predicting, detecting, classifying, monitoring therapy, prognosticating or otherwise assessing lung cancer somatic EGFR gene mutation.
9. An auxiliary detection kit for lung cancer somatic EGFR gene mutation, which is characterized by comprising a reagent for detecting the methylation difference degree of the methylation biomarker of any one of claims 1 to 7.
10. The method for auxiliary detection of EGFR gene mutation of lung cancer somatic cells is characterized by comprising the following steps of extracting peripheral blood DNA of a biological sample to be detected; performing bisulfite conversion on the DNA; detection of the degree of methylation difference of the methylation biomarker of any of claims 1 to 7.
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