CN115992241A - Application of histone acetylation and iron death related genes in predicting diffuse large B cell lymphoma prognosis - Google Patents
Application of histone acetylation and iron death related genes in predicting diffuse large B cell lymphoma prognosis Download PDFInfo
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Abstract
The invention belongs to the technical field of disease prognosis and molecular biology, and particularly relates to application of histone acetylation and iron death related genes in predicting diffuse large B cell lymphoma prognosis. According to the invention, a diffuse large B cell lymphoma prognosis model is constructed based on histone acetylation and iron death related genes, so that prognosis of diffuse large B cell lymphoma is predicted and evaluated, experiments prove that the prognosis model is obviously related to the OS of a DLBCL patient, the OS of the DLBCL patient with a high risk value is obviously shorter than that of a patient with a low risk value, and the possibility of death is higher, so that the diffuse large B cell lymphoma has a good prediction effect, can be used for predicting the prognosis of diffuse large B cell lymphoma and assisting clinical decision, and meanwhile, the related genes can also be used as targets for screening medicines for preventing or treating diffuse large B cell lymphoma, so that the diffuse large B cell lymphoma has good practical application value.
Description
Technical Field
The invention belongs to the technical field of disease prognosis and molecular biology, and particularly relates to application of histone acetylation and iron death related genes in predicting diffuse large B cell lymphoma prognosis.
Background
The disclosure of this background section is only intended to increase the understanding of the general background of the invention and is not necessarily to be construed as an admission or any form of suggestion that this information forms the prior art already known to those of ordinary skill in the art.
Diffuse large B-cell lymphoma (DLBCL) is the most common non-hodgkin's lymphoma type, a heterogeneous subtype of invasive B-cell tumors with different clinical, immunophenotype and biological characteristics. Although R-CHOP (rituximab, cyclophosphamide, doxorubicin, vincristine, and prednisone) is effective and safe for this treatment, up to 45% -50% of patients are at risk of relapse. Thus, new strategies are needed to improve the clinical outcome of DLBCL patients.
Epigenetic changes are directly related to the pathogenesis of lymphomas. Histone acetylation is one of these changes. Histone acetylation is the most widely studied post-translational modification. Post-translational modifications of histones not only regulate transcription and DNA repair, but also are associated with stable maintenance of depressed chromatin. Acetylation modulators tightly regulate lysine residues at the N-terminal tail of histones. Histone Acetyltransferases (HATs) catalyze acetylation, and Histone Deacetylases (HDACs) catalyze deacetylation. In addition, there are other modulators that recognize modified histones and thus play a role in acetylation.
Iron death is a novel cell death with unique properties and recognition function, involving physical conditions or various diseases including cancer. Unlike autophagy and apoptosis, iron death is a form of iron-dependent, lipid peroxidation-mediated cell death. High expression of ferritin enzyme repressor genes is associated with low survival rates for various cancers. Studies have shown that DLBCL is one of the most sensitive to ferritin inducers among the eight cell lines harvested from various tissues. Thus, iron death may be one of the fundamental mechanisms of concern in DLBCL.
Disclosure of Invention
The inventor provides application of histone acetylation and iron death related genes in predicting diffuse large B cell lymphoma prognosis through long-term technology and practical exploration. The invention constructs a relevant prognosis model by screening Histone Acetylation Genes (HAG) and iron death related genes (FRG), and results prove that the gene has good prediction effect on survival of patients suffering from diffuse large B cell lymphoma. Based on the above results, the present invention has been completed.
In order to achieve the technical purpose, the invention adopts the following technical scheme:
in a first aspect of the invention, there is provided a marker for predicting prognosis of diffuse large B-cell lymphoma, said marker being selected from any one or more of the following histone acetylation genes and iron death-related genes: KAT2A, GCLC, ENPP2 and HIF1A.
Further, the marker is a group consisting of KAT2A, GCLC, ENPP2 and HIF1A.
The invention discovers that the histone acetylation gene and the iron death related gene are obviously related to the prognosis situation of patients with diffuse large B cell lymphoma, so that a diffuse large B cell lymphoma prognosis evaluation model is constructed based on the markers, and the calculation formula = e (0.536887497 * GCLC expression level + -1.044825854 x enpp2 expression level + -3.873131171 x hif1a expression level +0.014318015 x kat2a expression level) 。
In a second aspect of the invention, there is provided the use of a substance for detecting a marker as described above for the preparation of a product for predicting diffuse large B-cell lymphoma prognosis.
Wherein the prognosis comprises a prognostic assessment of total survival (OS) of diffuse large B-cell lymphoma patients.
In a third aspect of the invention there is provided a product for predicting diffuse large B-cell lymphoma prognosis comprising a substance for detecting a marker as defined above.
In a fourth aspect of the invention, there is provided a system for predicting diffuse large B-cell lymphoma prognosis, said system comprising at least:
an acquisition module configured to: obtaining the expression level of the marker in the subject;
an evaluation module configured to: predicting a risk score of the diffuse large B-cell lymphoma prognosis according to the expression level of the marker obtained by the obtaining unit, and outputting the risk score;
an output module configured to: and obtaining a prediction result according to the risk score.
Wherein the evaluation unit comprises at least one diffuse large B cell lymphoma prognosis evaluation model, the prognosis evaluation model has a calculation formula of =e (0.536887497 * GCLC expression level + -1.044825854 x enpp2 expression level + -3.873131171 x hif1a expression level +0.014318015 x kat2a expression level) 。
In a fifth aspect of the invention, there is provided a computer readable storage medium having stored thereon a program which when executed by a processor performs the functions of the system according to the fourth aspect of the invention.
In a sixth aspect the invention provides an electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, the processor implementing the functions of the system according to the fourth aspect of the invention when the program is executed.
In a seventh aspect of the invention there is provided the use of a marker as described in the first aspect above as a target for screening for a medicament for the prophylaxis or treatment of diffuse large B-cell lymphoma.
Compared with the prior art, the one or more technical schemes have the following beneficial effects:
according to the technical scheme, the diffuse large B cell lymphoma prognosis model is constructed based on histone acetylation and iron death related genes, so that prognosis of diffuse large B cell lymphoma is predicted and evaluated, experiments prove that the prognosis model is obviously related to the OS of a DLBCL patient, the OS of the DLBCL patient with a high risk value is obviously shorter than that of a patient with a low risk value, and the possibility of death is higher, so that the method has a good prediction effect, can be used for predicting the prognosis of diffuse large B cell lymphoma and assisting clinical decision, and can be used as a target spot for screening related medicines for preventing and treating diffuse large B cell lymphoma, so that the method has good practical application value.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the invention.
FIG. 1 shows the molecular characteristics and correlation of histone acetylation modulator in DLBCL according to the present invention. Mutation frequency of 43 histone acetylation modulators in 37 DLBCL patients in tcga database. CNV frequency of histone acetylation regulator in dlbcl. C. Expression of histone acetylation regulator in mutant and wild-type groups. D. Histone acetylation-related interactions between the histone modulators studied. E. Iron death-related interactions between the iron death-related genes studied. F. Protein-protein interactions between iron death-related genes and histone acetylation regulator.
FIG. 2 is a graph showing the construction of a LASSO Cox regression model based on 4 related genes in the examples of the present invention. The optimal logarithmic lambda value is indicated by the vertical black line in the graph.
FIG. 3 is a prognostic assay of a 4-gene prognostic model in a GSE87371 cohort according to an embodiment of the invention. A. Distribution and median of risk scores in GSE87371 cohorts, distribution of OS status, OS and risk scores. B. AUC of time-dependent ROC curves validated the prognostic predictive power of risk scores in GSE87371 cohorts. C. Survival curves of OS for high and low risk group patients in GSE87371 cohorts. Principal component analysis map of gse87371 queue.
FIG. 4 is a model of validating a 4-gene prognosis in GSE10846 cohort according to an embodiment of the invention. Distribution and median of risk scores in gse10846 cohorts, distribution of OS status, OS and risk scores. Survival curves of OS for high and low risk group patients in gse10846 cohorts. Principal component analysis map of gse10846 queue. D. AUC of time-dependent ROC curve verifies prognostic performance of risk scores in GSE10846 cohorts.
FIG. 5 is a graph showing an independent prognostic predictor in a patient with a risk score of DLBCL according to an embodiment of the present invention; GSE87371 derives the results of a.single and b.multiple factor Cox regression analysis for OS in the cohort. * P <0.05; * P <0.01; * P <0.001; * P <0.0001.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the present application. 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 application belongs.
It is noted that the terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments in accordance with the present application. As used herein, the singular is also intended to include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that the terms "comprises" and/or "comprising" when used in this specification are taken to specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof. In addition, the molecular biological methods not described in detail in the examples are all conventional in the art, and specific operations can be referred to the molecular biological guidelines or the product specifications.
The prognosis of DLBCL patients is greatly improved due to targeted treatment with ferritin and histone acetylation modulating factors. Histone Acetylation Genes (HAGs) and iron death-related genes (FRGs) may provide some implications for prognosis, immunosuppressive characteristics, and other characteristics of DLBCL.
In view of the above, in an exemplary embodiment of the present invention, there is provided a marker for predicting prognosis of diffuse large B-cell lymphoma, the marker being selected from any one or more of the following histone acetylation genes and iron death-related genes: KAT2A, GCLC, ENPP2 and HIF1A.
In yet another embodiment of the present invention, the marker is a group consisting of KAT2A, GCLC, ENPP2 and HIF1A.
According to the invention, the research shows that the histone acetylation gene and the iron death related gene are obviously related to the prognosis of patients with diffuse large B cell lymphoma, so that a diffuse large B cell lymphoma prognosis evaluation model is constructed based on the markers, the diffuse large B cell lymphoma prognosis evaluation model has a calculation formula of =e (0.536887497 * GCLC expression level + -1.044825854 x enpp2 expression level + -3.873131171 x hif1a expression level +0.014318015 x kat2a expression level) 。
In yet another embodiment of the present invention, there is provided the use of a substance for detecting a marker as described above for the preparation of a product for predicting diffuse large B-cell lymphoma prognosis.
Wherein the prognosis comprises an assessment of total survival (OS) of a diffuse large B-cell lymphoma patient.
In yet another embodiment of the present invention, there is provided a product for predicting prognosis of diffuse large B-cell lymphoma, comprising a substance for detecting the above-mentioned marker.
In yet another embodiment of the present invention, the means for detecting the above-described markers include, but are not limited to, means for detecting the expression level of the markers for RT-PCR, real-time quantitative PCR, in situ hybridization, northern hybridization, liquid phase hybridization, ribozyme protection assay, RAKE method, gene chip and gene sequencing.
In yet another embodiment of the invention, the products include, but are not limited to, primers, probes, gene chips, nucleic acid formulations, kits and related devices, apparatuses, etc. for detecting the expression level of the markers.
In yet another embodiment of the present invention, there is provided a system for predicting diffuse large B-cell lymphoma prognosis comprising at least:
an acquisition module configured to: obtaining the expression level of the marker in the subject;
an evaluation module configured to: predicting a risk score of the diffuse large B-cell lymphoma prognosis according to the expression level of the marker obtained by the obtaining unit, and outputting the risk score;
an output module configured to: and obtaining a prediction result according to the risk score.
Wherein the evaluation unit comprises at least one diffuse large B-cell lymphoma prognosis evaluation model, the evaluation model has a calculation formula=e (0.536887497 * GCLC expression level + -1.044825854 x enpp2 expression level + -3.873131171 x hif1a tableReaching level +0.014318015 x kat2a expression level 。
In yet another embodiment of the present invention,
a high expression of the subject's risk score above a threshold value indicates that the subject is poorly predicted (has a short overall survival);
the risk score for the subject is low when the subject is below the threshold, indicating that the subject is better prognosis (longer overall survival).
In yet another embodiment of the present invention, the threshold may be a median threshold of scoring of the prognostic model.
In yet another embodiment of the present invention, a computer-readable storage medium is provided, on which a program is stored which, when executed by a processor, performs the functions of the system as described above.
In yet another embodiment of the present invention, an electronic device is provided that includes a memory, a processor, and a program stored on the memory and executable on the processor, the processor implementing the functions of the system as described above when the program is executed.
In yet another embodiment of the present invention, there is provided the use of the above-described marker as a target for screening a medicament for preventing or treating diffuse large B-cell lymphoma.
In yet another embodiment of the invention, the effect of the drug candidate on these biomarkers before and after use can be utilized to determine whether the drug candidate can be used to prevent or treat diffuse large B-cell lymphoma.
The invention is further illustrated by the following examples, which are given for the purpose of illustration only and are not intended to be limiting. If experimental details are not specified in the examples, it is usually the case that the conditions are conventional or recommended by the sales company; the present invention is not particularly limited and can be commercially available.
Examples
Materials and methods
Study population and data acquisition
The data disclosed for DLBCL may be downloaded from the GEO database (http:// www.NCBI. NLM.NIH.gov/GEO), (GSE 87371/GPL570 and GSE10846/GPL 570). Patient inclusion criteria included (a) histologically diagnosed DLBCL (b) complete gene expression data; (c) complete survival information. Table 1 summarizes the baseline characteristics of patients in these three cohorts. 221 patients from the GSE87371 dataset were used as training cohorts and 388 patients from GSE10846 and dataset, respectively, were used as validation cohorts.
Table 1 clinical features of DLBCL patients in this study
Mutations and interactions of histone acetylation modulators
Mutation pattern analysis was performed on 43 histone acetylation-related genes in the DLBCL queue using cBIoPortal (https:// www.cbioportal.org /). Protein-protein interactions (PPI) between HFGs were visualized using sting and retreatment by Cytoscape.
Construction and validation of a model for prognosis-related histone acetylation and iron death-related genes
The relationship between the expression level of iron-death-related genes and the total survival (OS) of DLBCL patients was elucidated by single factor Cox analysis. In GSE87371, iron-death-related genes with both differential expression and prognostic value were screened for use in constructing prognostic models. The generated key genes were evaluated using the LASSO method based "glmnet" R language package. Regression coefficients of these key genes were calculated using a multifactor Cox regression model. A prognostic model was established based on multifactor Cox regression of these genes. The risk score for the patient is calculated based on the normalized expression level of each gene and its corresponding regression coefficients. The formula is established as follows: score = e Sum (expression level of each gene. Times. Corresponding coefficient) . According to risk valuesThe median threshold divides the patients into high risk and low risk groups. Based on this model, GSE10846 as a validation queue performs the calculations in the same manner.
Statistical analysis
Based on the expression of genes in the model, principal component analysis was performed using the "prcomp" function of the "statistical" R package. Time-dependent ROC analysis and subsequent Area Under Curve (AUC) calculation were performed using the "timeROC" package in R. Single and multiple factor Cox regression analysis was performed to verify independent predictors. The risk ratio and 95% confidence interval for each variable were calculated. The "ggplot2", "ggforest" and "venn diagram" packages in R (4.0.2 version) are used for visualization. p values less than 0.05 are considered statistically significant. P <0.05, P <0.01, P <0.001, P < 0.0001).
Results
221 patients from the GSE87371 dataset and 388 patients from the GSE10846 dataset were included in the study. The detailed clinical characteristics of these patients are summarized in table 1.
Genetic variation of DLBCL histone acetylation modulator
Of the 37 samples in the TCGA database, 12 samples were mutated at a frequency of 32.43% (fig. 1A). According to the study results, CREBBP had the highest mutation frequency, followed by KAT6A, EP, HDAC8, HDAC9, BRD4, BRD2, PBRM1, SMARCA2, BAZ2B, and SMARCA4. Depending on the mutation status of CREBBP, DLBCL samples were divided into mutant and wild groups, and it was noted that some genes (KAT 2B, KAT6A, KAT6B, KAT7, EP300, CREBBP, HDAC1, BPTF, ATAD2B, BAZ2B, TAF1, SMARCA4, PBRA 1) were overexpressed in the mutant group (fig. 1B). Regarding copy number variation, the amplification rates of HDAC9, YEATS4, HDAC7, HDAC11 and KAT2B were high, but KAT6A was copy number lost (fig. 1C). Interactions between histone acetylation modifications and iron death
Of the 270 iron death-related genes, 32 were important predictive variables. Correlation analysis of 43 histone acetylation modulators and 32 iron death-related genes showed significant auto-positive correlation (fig. 1d, e). The results show that not only does there be a significant correlation between the same biological groups, but there is also a positive correlation between the different groups. The correlation heat map was used to illustrate the correlation between histone acetylation regulator and the expression pattern of iron death-related genes (fig. 1F). In fig. 3D, there is a clear negative correlation between KAT2A and most iron death-related genes.
Establishing a prognosis model in DLBCL
By using LASSO Cox regression analysis, a prognostic model for predicting the OS of a DLBCL patient is constructed by using the expression profile of a gene with prognostic significance. The model determines 4 genes based on the optimal value λ (fig. 2). Wherein KAT2A is histone acetylation regulator, GCLC and HIF1A, ENPP2 are iron death related genes. The risk score is calculated as e (0.536887497 * GCLC expression level + -1.044825854 x enpp2 expression level + -3.873131171 x hif1a expression level +0.014318015 x kat2a expression level) . Patients were divided into high risk groups (n=111) and low risk groups (n=110) according to median thresholds (fig. 3A). As shown in fig. 3A, the probability of death is significantly higher in the high risk group than in the low risk group. Survival curves showed that the overall survival of the high risk subgroup patients was significantly shorter than that of the low risk subgroup patients (fig. 3C, P<0.001). The OS risk score predictive performance at different time points was calculated by a time dependent ROC curve drawn by R software. As shown in fig. 3B, AUC of 1 year reached 0.715, AUC of 2 years reached 0.728,3 years reached 0.732. Principal component analysis showed that different groups of patients had significant aggregation (fig. 3D).
Verification of 4 Gene prognosis model in GSE10846 cohort
To verify the predictive ability of the 4-gene model in a large DLBCL patient cohort, values in the GSE10846 dataset were calculated by using the median of the same risk formula calculations from the GSE87371 cohort (fig. 4A). Patients in the high risk group died more easily and survived for a shorter period of time than in the low risk subgroup (fig. 4b, p < 0.001). Similar to the results in the GSE87371 cohort, principal component analysis showed significant aggregation in different groups of patients (fig. 4C). In the GSE10846 cohort, the 1 year AUC was 0.662,2 year AUC and the 0.666,3 year AUC was 0.672 (fig. 4D).
Independent prognostic value of 4 Gene prognostic model
The above analysis shows that DLBCL patients in different subgroups are closely related to the 4-gene prognosis model. To verify whether the correlation between risk scores and clinical pathology features of these patients was authentic, single-and multi-factor Cox regression analysis was performed. In the one-factor regression analysis, the risk scores correlated significantly with OS in GSE87371 cohorts (hr= 10.640, 95% ci=5.055-22.399, p < 0.001) (fig. 5A). As shown in fig. 5B, after correction for other factors, the risk score remains an independent predictor of OS in multivariate Cox regression (hr= 6.180, 95% ci= 2.903-13.157, p < 0.001). In addition, this result is variable in the GSE10846 queue.
Histone acetylation is an epigenetic modification necessary for cancer biology (proliferation, apoptosis, immune response, drug resistance). Iron death, a form of cell death distinct from autophagy and apoptosis, provides a new therapeutic approach for tumor treatment. There has been extensive discussion about genes related to ferritin enzymes in cancer, such as GPX4, FSP1, etc. The present invention demonstrates the potential malignant mechanisms of histone acetylation regulator and iron death-related genes in DLBCL development and their predictive value for DLBCL prognosis.
The prognosis model provided by the invention consists of four genes (KAT 2A, GCLC, ENPP2 and HIF 1A), and the genes can be divided into histone acetylation regulator and iron death related genes. KAT2A, also known as Gcn5, is a histone acetyltransferase that transfers acetyl groups to lysine residues, facilitating transformation modifications at different positions of histone H3. KAT2A has proven a viable target in previous studies to reduce the growth of acute myelogenous leukemia by significantly promoting bone marrow differentiation and apoptosis. Glutamate-cysteine ligase catalytic subunit (GCLC) is an antioxidant enzyme and iron metabolin, regulated by transcription of nuclear factor erythrocyte 2-associated factor 2, and can protect iron poisoning by maintaining glutamate balance in the event of cystine starvation. There are two genes that are significantly down-regulated in DLBCL tumor cells. The enzyme encoded by the outer nucleotide pyrophosphatase-phosphodiesterase 2 (ENPP 2) is an autologous lipase (ATX), an extracellular lysophospholipase D, and has been shown to protect cardiomyocytes from erastin-induced iron poisoning. However, in the current study, the low expression of ENPP2 is closely related to poor prognosis, and its mechanism is yet to be further studied. Studies have shown that HIF1A, as a driver of iron poisoning, may promote tumor cell death by inhibiting GPX 4. Furthermore, in pancreatic cancer cells, the deletion of HIF1A degrades the p53 protein by binding to five response elements in the p53 promoter, thereby acting as a tumor promoter, increasing its invasive and metastatic activity.
In summary, the present invention developed and validated a gene signature from histone acetylation and iron death related genes, providing personalized survival assessment for newly diagnosed DLBCL patients. This predictive system works well to provide recommendations for treatment decisions, follow-up and prognosis to the patient and its family members by the clinician.
The foregoing description is only of the preferred embodiments of the present application and is not intended to limit the same, but rather, various modifications and variations may be made by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principles of the present application should be included in the protection scope of the present application.
Claims (10)
1. A marker for predicting prognosis of diffuse large B-cell lymphoma, wherein said marker is selected from any one or more of the following histone acetylation genes and iron death-related genes: KAT2A, GCLC, ENPP2 and HIF1A.
2. The marker of claim 1, wherein the marker is a group consisting of KAT2A, GCLC, ENPP2 and HIF1A.
3. Use of a substance for detecting a marker according to claim 1 or 2 for the preparation of a product for predicting diffuse large B-cell lymphoma prognosis.
4. A product for predicting prognosis of diffuse large B-cell lymphoma, said product comprising a substance for detecting a marker according to claim 1 or 2.
5. The predictive diffuse large B-cell lymphoma prognosis product of claim 4, wherein said substances comprise substances for detecting the expression level of said markers for RT-PCR, real-time quantitative PCR, in situ hybridization, northern hybridization, liquid phase hybridization, ribozyme protection analysis, RAKE method, gene chip and gene sequencing;
the product comprises a primer, a probe, a gene chip, a nucleic acid preparation, a kit, related devices and equipment for detecting the expression level of the marker.
6. A system for predicting diffuse large B-cell lymphoma prognosis, said system comprising at least:
an acquisition module configured to: obtaining the expression level of the marker of claim 1 or 2 in a subject;
an evaluation module configured to: predicting a risk score of the diffuse large B-cell lymphoma prognosis according to the expression level of the marker obtained by the obtaining unit, and outputting the risk score;
an output module configured to: and obtaining a prediction result according to the risk score.
7. The system of claim 6, wherein the evaluation unit comprises at least one diffuse large B-cell lymphoma prognosis evaluation model; further, the prognostic evaluation model has a calculation formula=e (0.536887497 * GCLC expression level + -1.044825854 x enpp2 expression level + -3.873131171 x hif1a expression level +0 . 014318015 kat2a expression level ；
The risk score of the subject is high when the risk score is higher than a threshold value, and the prognosis of the subject is poor;
the risk score of the subject is low when it is below a threshold, indicating a better prognosis for the subject.
8. A computer readable storage medium, on which a program is stored, which program, when being executed by a processor, realizes the functions of the system according to claim 6 or 7.
9. An electronic device comprising a memory, a processor and a program stored on the memory and executable on the processor, characterized in that the processor implements the functions of the system according to claim 6 or 7 when executing the program.
10. Use of the marker of claim 1 or 2 as a target for screening a medicament for preventing or treating diffuse large B-cell lymphoma.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115572768A (en) * | 2022-11-04 | 2023-01-06 | 山东第一医科大学附属省立医院(山东省立医院) | Prognosis evaluation and combined treatment aiming at diffuse large B cell lymphoma |
| CN117153252A (en) * | 2023-08-31 | 2023-12-01 | 山东第一医科大学附属省立医院(山东省立医院) | Prognosis biomarker for patients with diffuse large B cell lymphoma, and system and application thereof |
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN115572768A (en) * | 2022-11-04 | 2023-01-06 | 山东第一医科大学附属省立医院(山东省立医院) | Prognosis evaluation and combined treatment aiming at diffuse large B cell lymphoma |
| CN115572768B (en) * | 2022-11-04 | 2023-12-19 | 山东第一医科大学附属省立医院(山东省立医院) | Prognosis evaluation and combined treatment for diffuse large B cell lymphoma |
| CN117153252A (en) * | 2023-08-31 | 2023-12-01 | 山东第一医科大学附属省立医院(山东省立医院) | Prognosis biomarker for patients with diffuse large B cell lymphoma, and system and application thereof |
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