CN115074439B - Group of NK/T cell lymphoma prognosis related genes, genome prognosis model and application thereof - Google Patents
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Abstract
The invention discloses a group of NK/T cell lymphoma prognosis related genes, which comprise: BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B, and NRG1. The invention also provides a genome prognosis model of the NK/T cell lymphoma, a method for constructing the genome prognosis model of the NK/T cell lymphoma, application of the NK/T cell lymphoma prognosis related gene to construction of the genome prognosis model and a detection kit of the NK/T cell lymphoma prognosis related gene. The invention can be used for accurately predicting the prognosis of NK/T cell lymphoma patients, and can combine and improve the existing NK/T cell lymphoma prognosis scoring system to ensure that the system has better evaluation effect.
Description
Technical Field
The invention relates to the field of gene mutation detection, in particular to a group of NK/T cell lymphoma prognosis related genes, a genome prognosis model constructed by the NK/T cell lymphoma prognosis related genes and application of the genome prognosis model.
Background
NK/T cell lymphoma is a non-Hodgkin lymphoma, and NK cells and cytotoxic T cells derived from lymphocytes often invade lymphoid organs around the nose, and is frequently found in young men. There are currently a number of prognostic scoring systems applied to NK/T cell lymphomas. Among them, the International Prognostic score (IPI), the Prognostic Index of NK/T Cell Lymphoma (PINK) and the improved PINK-E of Lymphoma were well-validated, and a series of corresponding treatments were proposed for the high-risk and low-risk groups of NK/T Cell Lymphoma patients. The risk factors included in these prognostic scoring systems are primarily clinical data for patients, including advanced age, advanced patients, extranodal involvement greater than 1, and non-nasal types.
However, currently a subset of patients lack sufficiently effective risk stratification to guide clinical treatment, and therefore risk stratification and prognostic assessment for NK/T cell lymphoma patients still needs further improvement.
With the increasing convenience of the second generation sequencing technology and the increasing of genetic analysis means, some researches in recent years reveal potential driving injuries related to the disease risk of NK/T cell lymphoma, including the genetic polymorphisms of single nucleotide sites of genes related to JAK-STAT/NF-kB/MAPK pathway, epigenetic modification molecules, RNA helicase and HLA-DPB1, IL18RAP and HLA-DRB 1. These studies lay a solid foundation for the establishment and perfection of genomic prognosis models.
Disclosure of Invention
The invention aims to solve the technical problems and provides a technical scheme capable of realizing more accurate and effective prognosis judgment on NK/T cell lymphoma patients.
To achieve the above objects, the present invention provides a set of NK/T cell lymphoma prognosis related genes comprising: BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B, and NRG1.
In another aspect, the present invention provides a genomic prognosis model of NK/T cell lymphoma, wherein the genomic prognosis model is constructed based on the following group of genes of interest: BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B, and NRG1.
In another aspect, the present invention also provides a method for constructing a genomic prognostic model of NK/T cell lymphoma, comprising the steps of:
step one, performing genome sequencing on an NK/T cell lymphoma tumor sample, and analyzing to obtain all genes with somatic mutation;
step two, combining patient clinical data corresponding to a sequencing sample, and screening a group of prognosis related genes which are obviously and frequently associated with the prognosis of the NK/T cell lymphoma from all genes with mutation by using LASSO Cox regression, wherein the group of prognosis related genes comprises BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B and NRG1;
step three, constructing the genome prognosis model by using the group of prognosis related genes, analyzing a survival curve, and evaluating the survival rate of NK/T cell lymphoma patients and the efficiency of the genome prognosis model;
step four, carrying out correlation analysis on the genome prognosis model and risk factors contained in the existing NK/T cell lymphoma prognosis scoring system, and checking the independence of the genome prognosis model;
and step five, comparing the advantages and disadvantages of the genome prognosis model and other risk factors on the NK/T cell lymphoma prognosis by using multivariate Cox regression analysis.
The method for constructing the genome prognosis model according to the present invention can be used for non-disease diagnosis purposes as well as for disease diagnosis purposes.
Preferably, according to the method of the present invention, in the second step, when the NK/T cell lymphoma patient has a mutation in any of 13 genes of the genomic prognosis model, the patient is assigned a risk score of 1, and as a mutant group, the patient without mutation is a wild type group.
Preferably, the method according to the present invention, wherein in step four, the existing NK/T cell lymphoma prognostic scoring system incorporated into the analysis includes, but is not limited to IPI, PINK or PINK-E.
Preferably, the method according to the present invention, wherein after the fifth step, the genomic prognosis model is further integrated into the existing NK/T cell lymphoma prognosis scoring system, so as to obtain an improved NK/T cell lymphoma prognosis scoring system.
On the other hand, the invention also provides application of the NK/T cell lymphoma prognosis related gene to construction of an NK/T cell lymphoma genome prognosis model.
In another aspect, the invention also provides the use of the NK/T cell lymphoma prognosis related gene according to the invention for combining and improving the existing NK/T cell lymphoma prognosis scoring system.
In another aspect, the present invention provides a kit for detecting a gene involved in prognosis of NK/T cell lymphoma, wherein the kit comprises a probe for capturing a target gene, and the target gene comprises: BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B, and NRG1.
The invention has the following beneficial effects:
1. the novel genome prognosis model constructed by the 13 genes with somatic mutation has obvious prediction value on prognosis of progression-free survival (PFS) and total survival (OS) of NK/T cell lymphoma patients, so that more accurate and effective prognosis judgment on NK/T cell lymphoma patients can be realized, poor treatment prognosis can be improved in a targeted manner, the medical level is improved, and the life quality is improved.
2. The genome prognosis model can be used for improving the existing NK/T cell lymphoma prognosis scoring system and has better prediction effect, so that the risk stratification and prognosis evaluation of NK/T cell lymphoma patients are further improved, and the genome prognosis model has good clinical popularization prospect.
Drawings
FIG. 1 shows the specific somatic mutation of 13 genes used for constructing a genomic prognosis model in 100 samples of NK/T cell lymphoma tumors in which mutations were identified (black indicates that the gene in the sample has a mutation, and white indicates no mutation), and the percentage indicated on the right side of the graph is the frequency of the mutation of the corresponding gene in 100 samples.
FIG. 2 is a genome prognosis model for dividing NK/T cell lymphoma patients in training set into wild type group and mutant type group, and survival curve analysis was performed to show the difference of progression-free survival PFS (upper panel, A) and total survival OS (lower panel, B) between two groups of patients.
FIG. 3 is a genomic prognostic model that divides confirmed concentrated NK/T cell lymphoma patients into wild type and mutant groups, and survival curve analysis shows the difference in progression-free survival PFS (upper panel, A) and total survival OS (lower panel, B) between the two groups of patients.
FIG. 4 is a heat map of the correlation between 8 risk factors, including the genomic prognosis model, and 9 factors, including the genomic prognosis model and the sample country source, for each, only the significant Cram er's V correlation coefficient (P < 0.05) is shown in the figure, with the coefficient size corresponding to the color in the right legend.
FIG. 5 is a graph showing survival curves of progression-free survival PFS of the present IPI (A), PINK (B) and PINK-E (C) prognosis scoring systems and the IPI-G (D), PINK-G (E) and PINK-E-G (F) prognosis scoring systems respectively added to a genomic prognosis model for improvement, wherein the larger the value of Harrell's C index (C-index), the higher the efficiency of the prediction model is.
Detailed Description
In order that the above objects, features and advantages of the present invention can be more clearly understood, the present invention will be described in further detail with reference to the accompanying drawings and specific embodiments. It should be understood by those skilled in the art that the examples are only for the understanding of the present invention and should not be construed as the specific limitations of the present invention; unless otherwise specified, the sequencing and analysis methods used in the following examples are conventional methods.
As used herein, "prediction" or "prognosis" refers to predicting the course or outcome of a patient's condition and does not mean that the course or outcome of the patient's condition can be predicted with 100% accuracy. "predicting" or "prognosis" refers to determining whether a certain process or outcome is more likely than not, and does not mean determining the likelihood of the certain process or outcome occurring by comparison to a situation in which the certain process or outcome does not occur. As used herein, a particular process or outcome is more likely to be observed in a patient identified as a mutant by the genomic prognostic model than in a person not displaying that characteristic.
A total of 260 NK/T cell lymphoma tumor samples from the tumor prevention and treatment center of Zhongshan university and Total Hospital, singapore were collected for genomic sequencing data consisting of 50 whole genome sequencing data and 210 targeted capture sequencing data. All genes were analyzed for the presence of somatic mutations in NK/T cell lymphomas.
Using LASSOCox regression in combination with 212 NK/T cell lymphoma patients with corresponding survival data as a training set, 13 mutated genes, BCOR (NCBI Gene ID: 54880), JAK3 (NCBI Gene ID: 3718), KRAS (NCBI Gene ID: 3845), MYH11 (NCBI Gene ID: 4629), DCC (NCBI Gene ID: 1630), ITK (NCBI Gene ID: 3702), NCBI CH1 (NCBI NOT: 4851), FAS (NCBI Gene ID: 355), RET (NCBI Gene ID: 5979), BIRC3 (NCBI Gene ID: 330), MLLT1 (NCBI Gene ID: 4298), LRP1B (NCBI Gene ID: 53353), and NRG1 (Gene ID: 3084), which are associated with NK/T cell lymphoma patients's prognosis high frequency, were screened using the LASSOCox regression. As shown in FIG. 1, the specific somatic mutation of the 13 genes in 100 samples of NK/T cell lymphoma tumors in which mutations were identified (black indicates that the gene in the sample has a mutation, and white indicates no mutation), and the percentage indicated on the right side of the figure is the frequency of the mutation of the corresponding gene in 100 samples.
A genome prognosis model for predicting the prognosis of NK/T cell lymphoma was constructed by using the 13 objective genes, and when a patient suffering from NK/T cell lymphoma had a mutation of any of the 13 objective genes, the patient was assigned a risk score of 1, and the patient was used as a mutant group, and the patient without the mutation was used as a wild-type group. In other words, when there is a mutation of any gene among the 13 target genes in NK/T cell lymphoma patients, the number of mutations of any gene is 1, and therefore, the number of patients with the mutation type is 1, and the number of patients with the wild type (non-mutation type) is 0, and these patients are grouped.
Statistically tested, the risk grouping of NK/T cell lymphoma patients using the genomic prognosis model can significantly predict the prognosis of PFS and OS of the patients (PFS and OS: P <0.0001, log rank test; FIG. 2), and can be repeated in an independent validation set (PFS: P =0.041, OS = P0.011; FIG. 3), indicating that the genomic prognosis model of the present invention has high prognosis efficacy.
The existing NK/T cell lymphoma prognosis scoring system mainly comprises IPI, PINK and PINK-E, and the included risk factors comprise advanced age, patients with advanced stage, ECOG physical performance score larger than 1, increased lactate dehydrogenase, extranodal involvement part number larger than 1, non-nasal type and high copy number of serum EB Virus (Epstein-Barr Virus, EBV). And carrying out correlation analysis on the genome prognosis model and the risk factors to calculate Cram er's V correlation coefficients of the genome prognosis model and the risk factors so as to test whether the genome prognosis model has independence.
Correlation analysis shows that the genome prognosis model is weakly correlated with other risk factors (
FIG. 4), which shows the independence of the genomic prognostic model of the present invention, can be used for risk stratification and prognostic evaluation of NK/T cell lymphoma patients together with other risk factors.
In addition, the multivariate Cox regression analysis compared the efficacy of the genomic prognosis model with other risk factors in predicting the prognosis of NK/T cell lymphoma patients, the genomic prognosis model having the greatest risk ratio compared to the other risk factors (table 1), indicating that the genomic prognosis model of the present invention is the most significantly correlated risk factor with the prognosis of PFS and OS in NK/T cell lymphoma patients.
TABLE 1 Cox regression model test for various risk factors
Risk ratio, 95% confidence interval and significance as univariate/multivariate for NK/T cell lymphoma prognosis
In addition, the genomic prognosis model can be combined with the existing NK/T cell lymphoma prognosis scoring system.
And calculating the sum of the risk score of the genome prognosis model and the score results of the existing NK/T cell lymphoma prognosis scoring systems (IPI, PINK and PINK-E) as the improved scoring systems (IPI-G, PINK-G and PINK-E-G) for predicting the prognosis of the NK/T cell lymphoma patient.
Through the statistical test of the Harrell's C index, compared with the prognosis effects of the original IPI, PINK and PINK-E (respectively corresponding to A, B and C in the figure 5), the prognosis effects of the IPI-G, PINK-G and PINK-E-G (respectively corresponding to A, B and C in the figure 5) after the genome prognosis model is combined by each scoring system are obviously improved (P)<0.001,χ 2 Test), which indicates that the genomic prognostic model of the present invention can be used to improve the current NK/T cell lymphoma prognostic scoring system to achieve more accurate prognostic assessment.
The present invention can also provide a kit for detecting a gene involved in prognosis of NK/T cell lymphoma, using the 13 target genes, wherein the kit contains a probe for capturing the target genes, and the target genes include: BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B, and NRG1. Thereby, the prognostic evaluation of NK/T cell lymphoma is realized.
It should be noted that the above description is not intended to limit the present invention, and the present invention is not limited to the above examples, and those skilled in the art should also make changes, modifications, additions or substitutions within the spirit and scope of the present invention.
Claims (4)
1. A genomic prognosis model for NK/T cell lymphoma, wherein the genomic prognosis model is constructed based on a group of genes of interest consisting of: BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B, and NRG1.
2. A method for constructing a genomic prognostic model of NK/T cell lymphoma, for non-disease diagnostic purposes, characterized by the steps of:
step one, performing genome sequencing on an NK/T cell lymphoma tumor sample, and analyzing to obtain all genes with somatic mutation;
step two, combining clinical data of a patient corresponding to a sequencing sample, and screening a group of prognosis related genes which are obviously and frequently associated with the prognosis of NK/T cell lymphoma tumor from all genes with mutation by using LASSOCox regression, wherein the group of prognosis related genes comprises BCOR, JAK3, KRAS, MYH11, DCC, ITK, NOTCH1, FAS, RET, BIRC3, MLLT1, LRP1B and NRG1; when a patient with NK/T cell lymphoma has a mutation of any gene in 13 genes of the genome prognosis model, the patient is endowed with a risk score of 1 and is taken as a mutant group, and the patient without the mutation is taken as a wild type group;
thirdly, constructing the genome prognosis model by using the group of prognosis related genes, analyzing a survival curve, and evaluating the survival rate of NK/T cell lymphoma patients and the efficiency of the genome prognosis model;
step four, carrying out correlation analysis on the genome prognosis model and risk factors contained in the existing NK/T cell lymphoma prognosis scoring system, and checking the independence of the genome prognosis model;
and step five, comparing the advantages and disadvantages of the genome prognosis model and other risk factors on the NK/T cell lymphoma prognosis by using multivariate Cox regression analysis.
3. The method according to claim 2, wherein in step four, the existing NK/T cell lymphoma prognostic scoring system as analyzed is included, but not limited to IPI, PINK or PINK-E.
4. The method of claim 2, wherein after step five, the method further comprises the step of combining the genomic prognosis model into an existing NK/T cell lymphoma prognosis scoring system to obtain an improved NK/T cell lymphoma prognosis scoring system.
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| WO2015186774A1 (en) * | 2014-06-05 | 2015-12-10 | 公益財団法人がん研究会 | Nk/t cell lymphoma examining method |
| CN110499364A (en) * | 2019-07-30 | 2019-11-26 | 北京凯昂医学诊断技术有限公司 | A kind of probe groups and its kit and application for detecting the full exon of extended pattern hereditary disease |
| CN111850116A (en) * | 2019-06-06 | 2020-10-30 | 上海交通大学医学院附属瑞金医院 | Gene mutation site group of NK/T cell lymphoma, targeted sequencing kit and application |
| CN112410424A (en) * | 2020-11-04 | 2021-02-26 | 上海交通大学医学院附属瑞金医院 | Detection kit and database building method for NK/T cell lymphoma related genes |
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| WO2015186774A1 (en) * | 2014-06-05 | 2015-12-10 | 公益財団法人がん研究会 | Nk/t cell lymphoma examining method |
| CN111850116A (en) * | 2019-06-06 | 2020-10-30 | 上海交通大学医学院附属瑞金医院 | Gene mutation site group of NK/T cell lymphoma, targeted sequencing kit and application |
| CN110499364A (en) * | 2019-07-30 | 2019-11-26 | 北京凯昂医学诊断技术有限公司 | A kind of probe groups and its kit and application for detecting the full exon of extended pattern hereditary disease |
| CN112410424A (en) * | 2020-11-04 | 2021-02-26 | 上海交通大学医学院附属瑞金医院 | Detection kit and database building method for NK/T cell lymphoma related genes |
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| Plasma circulating tumor DNA assessment reveals KMT2D as a potential poor prognostic factor in extranodal NK/T-cell lymphoma;Qiong Li;《Biomarker Research》;20200717;第8卷(第27期);第1-12页 * |
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