CN113373234A - Small cell lung cancer molecular typing determination method based on mutation characteristics and application - Google Patents
Small cell lung cancer molecular typing determination method based on mutation characteristics and application Download PDFInfo
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Abstract
The invention belongs to the technical field of genes, and discloses a small cell lung cancer molecule typing determination method based on mutation characteristics and application thereof. The invention comprehensively analyzes the characteristics of gene mutation, copy number change and the like of 178 cases of small cell lung cancer by a Whole Exon Sequencing (WES) method, and analyzes the immune characteristics of TMB, TNB, PDL1, CD8+ T cells and the like. The invention integrates the gene characteristics and the immune characteristics of the small cell lung cancer, and provides three gene change molecular typing of the small cell lung cancer for the first time. The invention is essential for understanding the characteristics of heterogeneity of small cell lung cancer and developing individualized treatment, and can promote the development of individualized clinical experiments of small cell lung cancer.
Description
Technical Field
The invention belongs to the technical field of genes, and particularly relates to a small cell lung cancer molecular typing determination method based on mutation characteristics and application.
Background
At present, Small Cell Lung Cancer (SCLC) has high malignancy and poor prognosis, and chemotherapy or chemotherapy combined radiotherapy is always applied clinically as two important treatment means. Recently, although immunotherapy has made some research progress in small cell lung cancer, the progress is limited. Due to the unique biological characteristics of the small cell lung cancer, the genome characteristics are determined and analyzed, and the method has very important clinical significance. In fact, molecular biology studies have shown that small cell lung cancer can be divided into four subtypes, SCLC-A, SCLC-N, SCLC-P and SCLC-Y, which can provide necessary clues for personalized treatment. However, current molecular typing is derived by analyzing the transcriptome level of foreign data.
At present, relevant molecular typing is carried out aiming at genome mutation characteristics and immune related characteristics of the small cell lung cancer, and no relevant literature report exists at home and abroad. Therefore, the genome alteration characteristics and the immune characteristics of the small cell lung cancer are deeply and comprehensively analyzed, and related subtype classification is carried out, so that the individual treatment of the small cell lung cancer is further promoted.
Through the above analysis, the problems and defects of the prior art are as follows: the prior art has no technology for carrying out subtype typing analysis and determination on the genome characteristics and the immune characteristics of the small cell lung cancer.
The difficulty in solving the above problems and defects is: since TP53 and RB1 are the two most common mutations in small cell lung cancer, it is difficult to re-molecularly type based on gene alteration profiles.
The significance of solving the problems and the defects is as follows: the method is very important for individual treatment of small cell lung cancer and excavation of drug targets.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a small cell lung cancer molecular typing determination method based on mutation characteristics and application thereof.
The invention is realized in such a way that the application of the small cell lung cancer gene modification molecular typing in the preparation of the drugs for treating the small cell lung cancer is provided.
The small cell lung cancer gene alteration molecular typing is as follows: cluster 1 (mainly enriched in Signature 4: smoking-related gene characteristics (leading to the conversion of G.C to T.A, with a tendency to methylate CpG dinucleotides)), Cluster2 (mainly enriched in Signature 6: DNA mismatch repair-related gene characteristics (additional C.G to T.A at NpCpG base sites)), and Cluster 3 (mainly enriched in Signature 5: unidentified related gene characteristics (several characteristics of A.T to G.C)).
Another object of the present invention is to provide a kit, andthe above-mentionedThe kit comprises the small cell lung cancer gene alteration molecular typing in the application.
Another object of the present invention is to provide a method for determining molecular typing of small cell lung cancer based on mutation characteristics, comprising:
and (3) carrying out signature correlation analysis on the genome by analyzing the gene change characteristics of the small cell lung cancer, and carrying out unsupervised clustering to determine the typing of the small cell lung cancer molecules.
Further, the small cell lung cancer molecular typing determination method based on the mutation characteristics comprises the following steps:
step one, constructing a DNA library and sequencing a whole exome; carrying out sequence comparison and variation detection;
step two, performing immunohistochemical staining by adopting an enhanced marking polymer system; analyzing the gene change characteristics of the small cell lung cancer, carrying out signature correlation analysis on the genome, carrying out unsupervised clustering, and determining the typing result of the small cell lung cancer molecules.
Further, in step one, the performing DNA library construction and whole exome sequencing comprises:
cutting genome DNA into 200bp fragments by enzyme method; after end repair and A tailing, adding T-shaped joints at both ends; amplifying the purified DNA by ligation-mediated PCR, sequencing the paired-end multiplex samples using NovaSeq6000 system; sequencing libraries were generated using 96RXN xGen outer Research Panel v 1.0.
Further, the sequencing comprises: the sequencing depth was 200 x per tissue sample and 100 x per control.
Further, in the first step, the sequence alignment and variation detection comprises:
(1) performing FASTP pretreatment on the raw data to obtain an aptamer sequence, and comparing clean readings in Fast Q format with a reference human genome hg19/GRCh37 by using Burrow-Wheeler aligner; sequencing the mapped BAM file by using an SAM tool and Picard and processing a PCR copy;
(2) generating a final BAM file by using the GATK, detecting the mononucleotide mutation of the somatic cell by using the MuTect, and detecting the small insertion and deletion of the somatic cell by using a GATK somatic cell Indel detector; performing variant annotation based on multiple databases using ANNOVAR;
(3) further analyzing the cancer hotspots screened from the disease database by the retained non-synonymous SNVs with the variation allele frequency (namely cut off is more than or equal to 3% or VAF cut off is more than or equal to 1%);
(4) calculating tumor mutation load, and calculating the number of nonsynonymous SNV and the number of included variation of each coding region; identifying important driving genes by combining two methods of MutsigCV and dDNdScv;
(5) the genome of the cancer important target is used for recognizing 2.0 copy number variation.
Further, the plurality of databases includes a variant description, a population frequency database, a variant function prediction database, and a phenotype or disease database.
Further, the identification of 2.0 copy number variation by using cancer important target genome comprises: at the chromosome arm level, meaningful amplifications or deletions were screened for further analysis with FDR based on criteria with cutoff < 10%; at the lesion level, significant amplifications were screened with FDR based on criteria with a cutoff of < 5% and G-Score based on cutoff >0.3, and further analysis was performed with FDR (criteria with a cutoff of < 5% and G-Score based on cutoff of < -0.2).
Further, the performing immunohistochemical staining comprises:
with anti-PD-L1, anti-CD 8+After overnight staining at 4 ℃, washing with phosphate buffer for 3 times, each for 5 min;
staining with corresponding secondary antibody at 37 deg.C for 30min, washing with PBS 3 times for 5min each time;
further dyeing with 3, 3-diaminobenzoic acid, washing with distilled water;
performing hematoxylin staining, dehydrating, removing, and fixing with neutral gum;
and collecting stained tissue images by using a KF-PRO-120 and KF-BIO digital pathological slide scanner.
Further, the anti-PD-L1 is Cst, 13684, 1: 100, respectively; the anti-CD 8+Cst, 85336, 1: 100.
by combining all the technical schemes, the invention has the advantages and positive effects that: the invention comprehensively analyzes the characteristics of gene mutation, copy number change and the like of 178 cases of small cell lung cancer by a Whole Exon Sequencing (WES) method, and analyzes the immune characteristics of TMB, TNB, PDL1, CD8+ T cells and the like. The invention integrates the gene characteristics and the immune characteristics of the small cell lung cancer, and provides three gene change molecular typing of the small cell lung cancer for the first time. The invention is essential for solving the characteristics of small cell lung cancer heterogeneity and developing individualized treatment, and can promote the development of individualized clinical experiments of small cell lung cancer.
Drawings
FIG. 1 is a flow chart of a method for determining molecular typing of small cell lung cancer based on mutation characteristics according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of the genomic molecular typing of small cell lung cancer provided by the embodiments of the present invention.
FIG. 3 is a schematic diagram of the difference of the molecular typing gene mutation of the small cell lung cancer provided by the embodiment of the invention.
FIG. 4 is a schematic diagram of the difference between the copy numbers of the typing genes of the small cell lung cancer molecules according to the embodiment of the present invention.
FIG. 5 is a schematic diagram of the differences of the molecular typing immune-related characteristics of small cell lung cancer provided by the embodiments of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
Aiming at the problems in the prior art, the invention provides a small cell lung cancer molecular typing determination method based on mutation characteristics and application thereof, and the invention is described in detail below with reference to the accompanying drawings.
The small cell lung cancer molecular typing determination method based on the mutation characteristics provided by the embodiment of the invention comprises the following steps:
and (3) carrying out signature correlation analysis on the genome by analyzing the gene change characteristics of the small cell lung cancer, and carrying out unsupervised clustering to determine the typing of the small cell lung cancer molecules.
The invention provides an application of small cell lung cancer gene modification molecule typing in preparation of a small cell lung cancer treatment drug.
The small cell lung cancer gene alteration molecular typing is as follows:
cluster 1 (mainly enriched Signature 4: smoking-related gene characteristics (leading to the conversion of G.C to T.A, with a tendency to methylate CpG dinucleotides)), Cluster2 (mainly enriched Signature 6: DNA mismatch repair-related gene characteristics (extra C.G to T.A at NpCpG base sites)) and Cluster 3 (mainly enriched Signature 5: unidentified related gene characteristics (several characteristics of A.T to G.C)).
It is another object of the present invention to provide a kit comprising the small cell lung cancer gene-altering molecular typing for use as described.
As shown in fig. 1, the method for determining the molecular typing of small cell lung cancer based on the mutation characteristics provided by the embodiment of the present invention includes the following steps:
s101, constructing a DNA library and sequencing a whole exome; carrying out sequence comparison and variation detection;
s102, performing immunohistochemical staining by using an enhanced marker polymer system;
s103, analyzing the gene change characteristics of the small cell lung cancer, carrying out signature correlation analysis on the genome, carrying out unsupervised clustering, and determining the typing result of the small cell lung cancer molecules.
The DNA library construction and whole exome sequencing provided by the embodiment of the invention comprises the following steps:
cutting genome DNA into 200bp fragments by enzyme method; after end repair and A tailing, adding T-shaped joints at both ends; amplifying the purified DNA by ligation-mediated PCR, sequencing the paired-end multiplex samples using NovaSeq6000 system; sequencing libraries were generated using 96RXN xGen outer Research Panel v 1.0.
The sequencing provided by the embodiment of the invention comprises the following steps: the sequencing depth was 200 x per tissue sample and 100 x per control.
The sequence alignment and variation detection provided by the embodiment of the invention comprises the following steps:
(1) performing FASTP pretreatment on the raw data to obtain an aptamer sequence, and comparing clean readings in Fast Q format with a reference human genome hg19/GRCh37 by using Burrow-Wheeler aligner; sequencing the mapped BAM file by using an SAM tool and Picard and processing a PCR copy;
(2) generating a final BAM file by using the GATK, detecting the mononucleotide mutation of the somatic cell by using the MuTect, and detecting the small insertion and deletion of the somatic cell by using a GATK somatic cell Indel detector; performing variant annotation based on multiple databases using ANNOVAR;
(3) further analyzing the cancer hotspots screened from the disease database by the retained non-synonymous SNVs with the variation allele frequency (namely cut off is more than or equal to 3% or VAF cut off is more than or equal to 1%);
(4) calculating tumor mutation load, and calculating the number of nonsynonymous SNV and the number of included variation of each coding region; identifying important driving genes by combining two methods of MutsigCV and dDNdScv;
(5) the genome of the cancer important target is used for recognizing 2.0 copy number variation.
The plurality of databases provided by the embodiments of the present invention include a variant description, a population frequency database, a variant function prediction database, and a phenotype or disease database.
The method for identifying 2.0 copy number variation by using the cancer important target genome provided by the embodiment of the invention comprises the following steps: at the chromosome arm level, meaningful amplifications or deletions were screened for further analysis with FDR based on criteria with cutoff < 10%; at the lesion level, significant amplifications were screened with FDR based on criteria with a cutoff of < 5% and G-Score based on cutoff >0.3, and further analysis was performed with FDR (criteria with a cutoff of < 5% and G-Score based on cutoff of < -0.2).
The immunohistochemical staining method provided by the embodiment of the invention comprises the following steps:
with CST, 13684, 1: 100 anti-PD-L1, CST, 85336, 1: 100 anti-CD 8+After overnight staining at 4 ℃, washing with phosphate buffer for 3 times, each for 5 min;
staining with corresponding secondary antibody at 37 deg.C for 30min, washing with PBS 3 times for 5min each time;
further dyeing with 3, 3-diaminobenzoic acid, washing with distilled water;
performing hematoxylin staining, dehydrating, removing, and fixing with neutral gum;
and collecting stained tissue images by using a KF-PRO-120 and KF-BIO digital pathological slide scanner.
The anti-PD-L1 provided by the embodiment of the invention is CST, 13684, 1: 100, respectively; the anti-CD 8+CST, 85336, 1: 100.
the typing result of the small cell lung cancer molecule provided by the embodiment of the invention comprises the following steps:
obtaining 3 molecular typing subclasses which are respectively Cluster 1, Cluster2 and Cluster 3 by carrying out unsupervised clustering.
The technical solution of the present invention is further described with reference to the following specific embodiments.
Example 1:
DNA library construction and Whole Exome Sequencing (WES).
The genomic DNA was enzymatically cleaved into 200 bp-sized fragments. After end repair and a tailing, a T-joint was added at both ends. To construct the library, the purified DNA was amplified by ligation-mediated PCR, followed by generation of the final sequencing library using 96RXN xGen outer Research Panel v1.0(Integrated DNA Technologies, USA) according to the manufacturer's instructions. Paired-end multiplex samples were sequenced using the NovaSeq6000 system. The sequencing depth was 200 x per tissue sample and 100 x per control.
And (3) sequence alignment and variation detection.
The raw data were pre-processed by FASTP to trim the aptamer sequences, and clean reads in Fast Q format were subsequently aligned with the reference human genome (hg19/GRCh37) using a Burrow-Wheeler aligner (BWA, v0.7.15). The SAM tool and Picard (2.12.1) (http:// Picard. sourceform. net) are used to sort the mapped BAM files and process the PCR copies. To calculate sequencing coverage and depth, final BAM files were generated from GATK (genome analysis toolkit 3.8) for local alignment and base quality recalibration. Single Nucleotide Variants (SNV) were detected from somatic cells using MuTect, and small insertions and deletions (Indels) were detected from somatic cells using the GATK somatic cell Indel detector. ANNOVAR software was used for variant annotation based on multiple databases, including variant descriptions (HGV), population frequency databases (1000 genome project, dbSNP, ExAC), variant function prediction databases (Polyphen-2 and SIFT), and phenotypic or disease databases (OMIM, COSMIC, ClinVar). The non-synonymous SNVs retained were further analyzed for screening of cancer hotspots from disease databases using Variant Allele Frequency (VAF) (cut off 3% or more) or VAF (cut off 1% or more). Tumor Mutational Burden (TMB) was calculated, and the number of nonsynonymous SNVs and the number of inclusion variations per coding region were calculated. Important driver genes were identified by combining both MutsigCV and dNdScv methods, as described in previous studies, with false discovery rates (FDR, cut off < 10%). Copy Number Variation (CNV) was identified using the cancer important target genome identification (gist) 2.0 algorithm. At the chromosomal arm level, meaningful amplifications or deletions were screened with FDR (cutoff < 10%) for further analysis. At the lesion level, significant amplifications were screened with FDR (cut off < 5%) and G-Score (cut off >0.3) and significant deletions were screened with FDR (cut off < 5%) and G-Score (cut off < -0.2) for further analysis.
Immunohistochemical staining.
Immunohistochemical staining was performed using an Enhanced Labeling Polymer System (ELPS). After staining with anti-PD-L1 (Cst, 13684, 1: 100), anti-CD 8+ (Cst, 85336, 1: 100) overnight at 4 ℃ washing 3 times with phosphate buffer each for 5 min. The cells were stained with the corresponding secondary antibody at 37 ℃ for 30min and then washed 3 times with PBS for 5min each. Further dyeing with 3, 3-Diaminobenzoic Acid (DAB) and washing with distilled water. Hematoxylin staining was then performed, followed by dehydration, removal, and fixation with neutral gums. And collecting stained tissue images by using a KF-PRO-120 and KF-BIO digital pathological slide scanner.
Results
Genome molecular typing construction of small cell lung cancer
By analyzing the gene change characteristics of the small cell lung cancer, signature correlation analysis is carried out on the genome, unsupervised clustering is carried out, and finally 3 subclasses are obtained, namely Cluster 1, Cluster2 and Cluster 3.
The invention compares the difference of the driving gene mutation of the three molecular typing of Cluster 1, Cluster2 and Cluster 3. The results show that TP53 and RB1 are still the genes with the highest mutation frequency of the small cell lung cancer, and are 93.26 percent and 44.38 percent respectively. The OR51I2 gene mutation is different among three subtypes.
The invention compares the difference between the gene copy number changes of the chromosome level of the three molecular typing of Cluster 1, Cluster2 and Cluster 3. The results indicate that at the gene copy number amplification level, there are some differences in the three molecular typing on chromosomes 1, 2, 3, 5, 6, 15, 16, 20, and 22. In addition, there are some differences in the three molecular typing on chromosomes 5, 7, 9, 10, 11, 14, 15, and 16 in terms of gene copy number deletion. (. 0.05;. 0.01;. 0.001)
The invention compares the differences of the immune related characteristics of the three molecular classifications of Cluster 1, Cluster2 and Cluster 3. The results show that there are some differences among TNB, PDL1(TPS), PDL1(CPS) and CD8+ T cells in all three molecular typing. Importantly, the surprising finding of this study was that the Cluster 1 subtype has higher TNB, and has higher PDL1 expression and infiltration of CD8+ T cells.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An application of small cell lung cancer gene modification molecule typing in preparing medicine for treating small cell lung cancer is disclosed.
2. The use of claim 1, wherein said small cell lung cancer genetically altered molecular typing comprises:
cluster 1, enriching Signature 4, smoking related gene characteristics;
cluster2, enriching Signature 6, DNA mismatch repair related gene characteristics;
cluster 3, enriching Signature 5, and gathering unknown related gene characteristics.
3. A kit comprising the small cell lung cancer genetically altered molecular typing for use according to any one of claims 1 to 2.
4. A small cell lung cancer molecular typing determination method based on mutation characteristics is characterized by comprising the following steps:
and (3) carrying out signature correlation analysis on the genome by analyzing the gene change characteristics of the small cell lung cancer, and carrying out unsupervised clustering to determine the typing of the small cell lung cancer molecules.
5. The method for determining molecular typing of small cell lung cancer based on mutation characteristics according to claim 4, wherein the method for determining molecular typing of small cell lung cancer based on mutation characteristics comprises the following steps:
step one, constructing a DNA library and sequencing a whole exome; carrying out sequence comparison and variation detection;
step two, performing immunohistochemical staining by adopting an enhanced marking polymer system; analyzing the gene change characteristics of the small cell lung cancer, carrying out signature correlation analysis on the genome, carrying out unsupervised clustering, and determining the typing result of the small cell lung cancer molecules.
6. The method for molecular typing and determination of small cell lung cancer based on mutation characteristics as claimed in claim 5, wherein in step one, the DNA library construction and whole exome sequencing comprises:
cutting genome DNA into 200bp fragments by enzyme method; after end repair and A tailing, adding T-shaped joints at both ends; amplifying the purified DNA by ligation-mediated PCR, sequencing the paired-end multiplex samples using NovaSeq6000 system; generating a sequencing library using 96RXN xGen outer research & reservoir 1.0;
the sequencing comprises the following steps: the sequencing depth was 200 x per tissue sample and 100 x per control.
7. The method for molecular typing of small cell lung cancer according to claim 5, wherein the sequence alignment and variation detection in step one comprises:
(1) performing FASTP pretreatment on the raw data to obtain an aptamer sequence, and comparing clean readings in Fast Q format with a reference human genome hg19/GRCh37 by using Burrow-Wheeler aligner; sequencing the mapped BAM file by using an SAM tool and Picard and processing a PCR copy;
(2) generating a final BAM file by using the GATK, detecting the mononucleotide mutation of the somatic cell by using the MuTect, and detecting the small insertion and deletion of the somatic cell by using a GATK somatic cell Indel detector; performing variant annotation based on multiple databases using ANNOVAR;
(3) further analyzing the cancer hotspots screened from the disease database by the retained non-synonymous SNVs with the variation allele frequency (namely cut off is more than or equal to 3% or VAF cut off is more than or equal to 1%);
(4) calculating tumor mutation load, and calculating the number of nonsynonymous SNV and the number of included variation of each coding region; identifying important driving genes by combining two methods of MutsigCV and dDNdScv;
(5) the genome of the cancer important target is used for recognizing 2.0 copy number variation.
8. The method of claim 7 for molecular typing of small cell lung cancer based on mutational characteristics wherein the plurality of databases comprise a variant description, a population frequency database, a variant function prediction database, and a phenotype or disease database;
the identification of 2.0 identification copy number variation by using cancer important target genome comprises the following steps: at the chromosome arm level, meaningful amplifications or deletions were screened for further analysis with FDR based on criteria with cutoff < 10%; at the lesion level, significant amplifications were screened with FDR based on criteria with a cutoff of < 5% and G-Score based on cutoff >0.3, and further analysis was performed with FDR (criteria with a cutoff of < 5% and G-Score based on cutoff of < -0.2).
9. The method of determining molecular typing of small cell lung cancer based on mutational characteristics according to claim 4, wherein said performing immunohistochemical staining comprises:
with anti-PD-L1, anti-CD 8+After overnight staining at 4 ℃ the cells were washed with phosphate buffer3 times, each time for 5 min;
staining with corresponding secondary antibody at 37 deg.C for 30min, washing with PBS 3 times for 5min each time;
further dyeing with 3, 3-diaminobenzoic acid, washing with distilled water;
performing hematoxylin staining, dehydrating, removing, and fixing with neutral gum;
and collecting stained tissue images by using a KF-PRO-120 and KF-BIO digital pathological slide scanner.
10. The method for molecular typing of small cell lung cancer based on mutational characteristics as claimed in claim 9, wherein the anti-PD-L1 is Cst, 13684, 1: 100, respectively; the anti-CD 8+Cst, 85336, 1: 100.
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