CN117965731A - Application of SRSF12 gene as acute myeloid leukemia specific molecular marker - Google Patents

Application of SRSF12 gene as acute myeloid leukemia specific molecular marker Download PDF

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CN117965731A
CN117965731A CN202410141961.8A CN202410141961A CN117965731A CN 117965731 A CN117965731 A CN 117965731A CN 202410141961 A CN202410141961 A CN 202410141961A CN 117965731 A CN117965731 A CN 117965731A
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srsf12
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myeloid leukemia
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李佳佳
张孟孟
谢志滨
王蒙
张平平
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First Affiliated Hospital of Bengbu Medical College
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Abstract

The invention relates to the fields of molecular biology and clinical application, in particular to application of SRSF12 gene as a specific molecular marker of Acute Myeloid Leukemia (AML), especially application in preparing products for AML diagnosis, treatment and prognosis evaluation. According to the invention, through analyzing the expression condition of SRSF12 in tumor and normal tissues, the difference between the SRSF12 expression and clinical characters, the independent prognosis analysis and diagnosis value of SRSF12 in AML patients, the correlation between the SRSF12 expression and tumor immune infiltration, the construction of SRSF12 related protein interaction network, the correlation between the SRSF12 expression and drug reaction and other related bioinformatics analysis and clinical analysis prove that the SRSF12 is used as a potential biomarker, can be used for diagnosis, treatment and prognosis evaluation of AML patients, and guides the accurate diagnosis and treatment of patients.

Description

Application of SRSF12 gene as acute myeloid leukemia specific molecular marker
Technical Field
The invention relates to the fields of molecular biology and clinical application, in particular to application of SRSF12 gene as a specific molecular marker of acute myeloid leukemia.
Background
Acute myeloid leukemia (acute myeloid leukemia, AML) is a clonal hematopoietic malignant disease characterized by hematopoietic stem cell differentiation disorders and abnormal proliferation, with a high degree of heterogeneity, the most common type of acute leukemia in adults. The prognosis difference of patients is large, and the death rate is high, so that the occurrence and development mechanism of acute myeloid leukemia is clear, and the search of the molecular marker for early diagnosis and prognosis evaluation has important significance.
In view of this, the present invention has been made.
Disclosure of Invention
In order to make up for the defects of the prior art, the invention aims to provide application of SRSF12 genes as specific molecular markers of acute myeloid leukemia.
More than 95% of genes in the human genome undergo alternative splicing, an important regulatory mechanism for gene expression at the post-transcriptional level. The serine/arginine-rich splicing factor SR protein family (SRSF) plays an important regulatory role in the RNA alternative splicing process by recognizing and binding splice elements on precursor RNAs, recruiting assembled spliceosomes to promote or inhibit the occurrence of alternative splicing events. SRSF12 is one of the members of the SR protein family, having a classical SR protein domain. The invention facilitates better guidance of treatment strategies and prognosis evaluation of AML patients through research on specific regulation mechanisms of SRSF12 in AML.
In a first aspect of the invention, there is provided the use of the SRSF12 gene as a specific molecular marker for acute myeloid leukemia.
In a second aspect, the invention provides the use of the SRSF12 gene as a specific molecular marker in diagnosis, treatment, prognosis evaluation of acute myeloid leukemia.
Specifically, the SRSF12 gene can be used as a target point for diagnosis, treatment and prognosis evaluation of acute myeloid leukemia.
The expression level of the SRSF12 gene is correlated with the survival rate of patients with acute myeloid leukemia. Preferably, acute myeloid leukemia is diagnosed, treated, and prognosticated by detecting the expression level of the SRSF12 gene; more preferably, acute myeloid leukemia is diagnosed, treated, and prognosis assessed by detecting mRNA expression levels of the SRSF12 gene.
In a third aspect, the invention provides application of SRSF12 gene as a specific molecular marker in preparing products for diagnosis, treatment and prognosis evaluation of acute myeloid leukemia.
Preferably, the product comprises: reagents, kits and medicaments.
Preferably, the reagent and the kit comprise specific primers for detecting SRSF12 Gene (Gene ID: 135295), wherein the specific primers are an upstream primer shown as SEQ ID NO.1 and a downstream primer shown as SEQ ID NO. 2.
Preferably, housekeeping gene ACTIN is used as an internal reference, and the internal reference primers are an upstream primer shown in SEQ ID NO. 3 and a downstream primer shown in SEQ ID NO. 4.
Preferably, the medicament is an acute myeloid leukemia therapeutic medicament.
In a fourth aspect of the invention, there is provided the use of the SRSF12 gene as a specific molecular marker in the screening of drugs for the treatment of acute myeloid leukemia.
Preferably, the drug selected includes, but is not limited to, ML312, isoliquiritigenin, BRD-K34099515, BRD-K86535717, and the like.
The PI3K-AKT signal pathway, the AMPK signal pathway and the Jak-STAT signal pathway regulated by the SRSF12 gene can regulate the occurrence and development of acute myeloid leukemia.
In a fifth aspect, the invention provides the use of the SRSF12 gene-regulated PI3K-AKT signaling pathway, AMPK signaling pathway, jak-STAT signaling pathway in diagnosis, treatment, and prognosis evaluation of acute myeloid leukemia.
In a sixth aspect, the invention provides the use of the SRSF12 gene-regulated PI3K-AKT signaling pathway, AMPK signaling pathway, jak-STAT signaling pathway in the preparation of a product for diagnosis, treatment and prognosis evaluation of acute myeloid leukemia.
Preferably, the product comprises: reagents, kits and medicaments.
Preferably, the reagent and the kit comprise specific primers for detecting SRSF12 genes, wherein the specific primers are an upstream primer shown in SEQ ID NO. 1 and a downstream primer shown in SEQ ID NO. 2.
Preferably, housekeeping gene ACTIN is used as an internal reference, and the internal reference primers are an upstream primer shown in SEQ ID NO. 3 and a downstream primer shown in SEQ ID NO. 4.
In a seventh aspect of the invention, a kit for diagnosing acute myeloid leukemia is provided, which comprises a specific primer for detecting SRSF12 gene, wherein the specific primer is an upstream primer shown as SEQ ID NO.1 and a downstream primer shown as SEQ ID NO. 2.
Preferably, housekeeping gene ACTIN is used as an internal reference, and the internal reference primers are an upstream primer shown in SEQ ID NO. 3 and a downstream primer shown in SEQ ID NO. 4.
In an eighth aspect of the invention, there is provided an acute myeloid leukemia prognosis evaluation kit comprising specific primers for detecting the SRSF12 gene, wherein the specific primers are an upstream primer shown as SEQ ID NO. 1 and a downstream primer shown as SEQ ID NO. 2.
Preferably, housekeeping gene ACTIN is used as an internal reference, and the internal reference primers are an upstream primer shown in SEQ ID NO. 3 and a downstream primer shown in SEQ ID NO. 4.
The beneficial effects are that:
The invention utilizes a GEPIA database to verify by analyzing an AML data set from a cancer genome map (TCGA), a normal sample GTEx data set and a TIMER2.0 to explore the expression condition of SRSF12 in a TCGA tumor and a normal tissue sample, analyzes the difference between the SRSF12 expression and clinical characters based on the TCGA data set, independently prognosis analysis and diagnosis values of the SRSF12 in an AML patient, and discusses the related biological functions and pathways through GO and KEGG enrichment analysis. In addition, the correlation between SRSF12 expression and tumor immune infiltration is also discussed through TIMER2.0, an SRSF12 related protein interaction network is constructed based on a STRING database, and the correlation between SRSF12 expression and drug response is determined by using a CTRP database. Therefore, the differential expression of the SRSF12 between 13 tumor and normal tissue samples is statistically significant (P < 0.05), the SRSF12 is mainly expressed in the AML, and the SRSF12 has reference value for diagnosis and prognosis judgment of AML patients, wherein the high expression, age and cytogenetic risks of the SRSF12 are all independent predictors (P < 0.05) with good prognosis of the AML patients. The result of the GO enrichment analysis shows that the SRSF12 is enriched in biological processes such as embryonic organ development and the like, and the KEGG enrichment analysis shows that the SRSF12 is mainly involved in regulating neuroactive ligand-receptor interaction, PI3K-AKT signal pathway, jak-STA signal pathway and the like, and the SRSF12 expression is positively correlated with helper T cell infiltration and pDC, tcm, T cell infiltration, and is negatively correlated with neutrophil infiltration and macrophage infiltration. PPI analysis showed that SRSF12 interacts with proteins such as SRSF11, FUS, SRSF1, SRSF9, and that SRSF12 expression is also significantly associated with multiple agents of hematopoietic and lymphoid tissues.
In conclusion, the SRSF12 is proved to be a new potential biomarker by bioinformatics analysis and clinical analysis, can be used for diagnosis, treatment and prognosis evaluation of AML patients, and guides accurate diagnosis and treatment of the patients; in addition, the target can be used for developing medicines for treating AML.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
FIG. 1A shows the expression of SRSF12 in TIMER2.0 database between TCGA tumor and normal tissues;
FIG. 1B is a graph showing the difference in SRSF12 expression in healthy versus AML samples in UCSC Xena databases;
FIG. 1C is a diagram showing the expression of SRSF12 in AML and healthy samples at GEPIA;
FIG. 1D is a graph showing the correlation of SRSF12 expression with leukocyte index;
FIG. 1E is a graph showing the correlation results between SRSF12 expression and FAB stage;
FIG. 1F is a graph showing the results of correlation of SRSF12 expression with cytogenetic risk;
FIG. 1G is a graph showing the results of the correlation of SRSF12 expression with cytogenetics;
FIG. 2 is a graph of survival analysis of SRSF12 high expression groups and SRSF12 low expression groups of AML patients in the TCGA database; wherein A is the survival rate analysis of the SRSF12 high expression group and the SRSF12 low expression group of FAB stage (M1 & M2); b is the survival rate analysis of SRSF12 high expression group and SRSF12 low expression group of FAB stage (M2 & M3); survival analysis of SRSF12 high expression group and SRSF12 low expression group of FAB stage (M1 & M2& M3); survival analysis of SRSF12 high expression group and SRSF12 low expression group of FAB stage (M2 & M3& M4); e is the survival analysis of SRSF12 high expression group and SRSF12 low expression group of FAB stage (M3 & M4); f is the survival rate analysis of SRSF12 high expression group and SRSF12 low expression group of FAB stage (M3 & M4& M5); g is the survival rate analysis of the SRSF12 high expression group and the SRSF12 low expression group of male patients; h is a survival analysis of a high SRSF12 expression group and a low SRSF12 expression group of patients under 60 years of age; i is the overall survival rate analysis of the SRSF12 high expression group and the SRSF12 low expression group;
FIG. 3A is a forest chart of a SRSF12 one-factor COX regression analysis in the TCGA-LAML dataset AML;
FIG. 3B is a forest graph of SRSF12 multifactorial COX regression analysis in the TCGA-LAML dataset AML;
FIG. 4A is an analysis of ROC curves of the SRSF12 gene in the TCGA database;
FIG. 4B is a nomographic analysis of the SRSF12 gene in the TCGA database;
FIG. 5A is a volcanic plot based on SRSF12 differential gene screening;
FIG. 5B is a graph of the results of GO enrichment analysis of SRSF 12;
FIG. 5C is a graph of the results of a KEGG pathway enrichment analysis performed on SRSF 12;
FIG. 6A shows the difference in expression of 24 immune cells in the TIMER 2.0 database AML in the high SRSF12 expression group and the low SRSF12 expression group;
FIG. 6B is a correlation heat map of 24 immune cells;
FIG. 6C is a lollipop plot of the correlation of SRSF12 expression with 24 immune cells;
FIG. 7 is a scatter plot of the correlation of SRSF12 expression with immune cells of the TCGA-LAML database;
FIG. 8 is a protein-protein interaction (PPI) network obtained from SRSF12 introduction into a sting;
FIG. 9 is a correlation between SRSF12 expression and drug response;
FIG. 10 is a graph showing the results of detection of the expression level of SRSF12 in AML patients and healthy samples;
FIG. 11 shows the correlation between the expression level of SRSF12 and the survival time of AML patients.
Detailed Description
It should be noted that the following detailed description is illustrative and is intended to provide further explanation of the 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 exemplary embodiments according to the present application. As used herein, the singular forms also include the plural unless the context clearly indicates otherwise, and furthermore, it is to be understood that when the terms "comprises" and/or "comprising" are used in this specification, they specify the presence of stated features, steps, operations, devices, components, and/or combinations thereof.
The technical solutions of the present invention will be clearly and completely described in connection with the embodiments, and it is apparent that the described embodiments are some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Example 1: differential analysis of SRSF12 expression in AML
Expression of SRSF12 across all TCGA tumors and normal tissues was explored using the TIMER2.0 database. The results showed that SRSF12 has statistical significance (P < 0.05) in differential expression between 13 tumors and normal tissues, such as Cholangiocarcinoma (CHOL), colon adenocarcinoma (COAD), head and neck squamous cell carcinoma (HNSC), renal chromocytoma (KICH), hepatocellular carcinoma (LIHC), lung adenocarcinoma (LUAD), etc. (fig. 1A). Downloading TCGA GTEx-LAML data set from UCSC Xena database, comprising 70 normal samples GTEx and 173 TCGA tumor samples, carrying out log2 (value+1) normalization treatment on the RNA expression data, and combining RNA expression spectrums of 70 normal samples GTEx and 173 TCGA tumor samples by using 'limma' R to obtain corresponding RNA expression matrix. And the corresponding SRSF12 expression matrix is obtained by extracting the SRSF12 expression level from the sample, the data are visualized by using an R package 'ggplot & lt 2 & gt', the difference of the SRSF12 expression in an AML sample is found to be obvious (figure 1B), and the verification is carried out by using GEPIA, so that the SRSF12 is highly expressed in the AML (figure 1C). Based on the TCGA-LAML database, the data were visualized using R package "ggplot", and SRSF12 high expression was found to be significantly correlated with clinical symptoms such as leukocyte index and FAB staging (fig. 1D-G).
Example 2: correlation of SRSF12 expression with clinical Properties
150 AML samples (TCGA-LAML) were downloaded from TCGA database, and differences in clinical traits of high and low SRSF12 expression groups were analyzed based on TCGA-AML dataset, showing significant statistical differences in white blood cell index (p=0.002), FAB typing (P < 0.001), cytogenetic risk (p=0.026) and cytogenetics (p=0.001) between the two groups (table 1), indicating that SRSF12 expression was associated with the above clinical traits.
TABLE 1 relationship between SRSF12 expression and clinical Properties in 150 AML patients in TCGA-LAML
Example 3: survival analysis of SRSF12 in AML patients
Excluding samples without complete survival information, 150 AML samples in TCGA-LAML dataset were included in survival analysis, AML patients in TCGA database were divided into SRSF12 high-expression group and SRSF12 low-expression group, K-M survival curve was drawn using "survivinal" R package to explore the relationship between SRSF12 expression and AML patient survival, and the results showed that SRSF12 high-expression group had better survival rate (TCGA-LAML: p < 0.001) (fig. 2I), and subgroup analysis showed that SRSF12 high expression was significantly correlated with prognosis of AML in ：M1&M2(HR＝0.45,P＝0.016),M2&M3(HR＝0.32,P＝0.008),M1&M2&M3(HR＝0.49,P＝0.023),M2&M3&M4(HR＝0.28,P＜0.001),M3&M4(HR＝0.26,P＝0.002),M3&M4&M5(HR＝0.30,P＝0.001), men (hr=0.33, p < 0.001), age < = 60 (hr=0.29, p < 0.001) (fig. 2A-H).
Example 4: prognostic assay of SRSF12 in AML
Based on the expression of SRSF12 in AML patient samples of the TCGA-LAML dataset, a one-factor, multifactorial COX regression analysis was performed, which showed that age (< = 60, P < 0.001; HR:0.301;95% CI: 0.195-0.464), cytogenetic risk (Favorable, P < 0.001; HR:0.242;95% CI: 0.113-0.159) and SRSF12 expression level (High, P < 0.001; HR:0.366;95% CI: 0.234-0.572) correlated with patient prognosis. Multifactorial COX regression analysis showed that age (<=60, P < 0.001; HR:0.307;95% CI: 20.195-0.485), cytogenetic risk (Favorable, P=0.004; HR:0.318;95% CI: 0.145-60.697) and SRSF12 expression levels (High, P < 0.001; HR:0.299;95% CI: 0.184-0.485) correlated with patient prognosis (Table 2).
TABLE 2 single and multiple factor COX regression analysis of SRSF12 in AML
Example 5: prognostic assay of SRSF12 in AML
Based on the expression of SRSF12 in AML patient samples of TCGA-LAML dataset, one-factor multifactorial COX regression analysis was performed, and forest map visualization was performed using R package "ggplot2", showing that age, cytogenetic risk, and SRSF12 expression were all independent prognostic factors (p < 0.05) for AML patients (fig. 3A-B).
Example 6: diagnostic value of expression of SRSF12 gene in AML
Diagnostic time-dependent curves and nomograms were constructed based on the TCGA-LAML database to assess overall survival for AML patients for 1,3, 5 years. Variables with P less than 0.05 each are considered independent risk factors for prognosis of AML patients. Visualization was performed using R package "ggplot 2". A time-dependent survival ROC curve was established for SRSF12 to predict survival rates of 1 year, 3 years, and 5 years, all AUC values being less than 0.5, SRSF12 was considered suitable for predicting prognosis of AML patients. The expression levels of SRSF12 are combined with clinical variables, and nomograms are constructed to predict patient survival probabilities at 1,3 and 5 years. The alignment shows that the SRSF12 expression levels are better predicted for prognosis than traditional clinical features such as age, WBC index, etc. (FIGS. 4A-B).
Example 7: gene Ontology (GO) enrichment analysis and Kyoto Gene and genome encyclopedia (KEGG) enrichment analysis of SRSF12 and its differential genes
METASCAPE is a tool for analyzing gene function annotation covering genome data and bioinformatics data of various species, and can rapidly perform large-scale bioinformatics analysis. The TCGA-LAML data set is divided into two groups based on SRSF12 expression level, 368 differential genes (log 2FoldChange I is more than 2 and P is less than 0.05) are screened by using R language, the volcanic diagram shows that 225 red dispersion points are expression up-regulating genes, 143 blue dispersion points are expression down-regulating genes, and Top5 represents genes: THSD7A, CACNA D2, NPXN3, IBSP, LAMC3, the remaining genes are shown in grey dots (fig. 5A). The Gene Ontology (GO) enrichment analysis was performed on the target gene SRSF12 using METASCAPE database, annotating the biological processes (biological process, BP), cellular components (cellular component, CC) and molecular functions (molecular function, MF) of the target gene, determining the major metabolic pathways in which it was involved and performing the kyoto gene and genome encyclopedia (Kyoto encyclopedia of genes and genome, KEGG) pathway enrichment analysis. GO function annotation and KEGG enrichment analysis are carried out on the SRSF12 related differential splicing genes, and the analysis finds that the SRSF12 related differential splicing genes are enriched in embryonic organ development (embryonic organ development), embryonic organ morphogenesis (embryonic organ morphogenesis), embryonic skeletal system development (embryonic SKELETAL SYSTEM development) and the like in biological processes; and is enriched in cell composition in collagen-containing extracellular matrix (collagen-containing extracellular matrix) and postsynaptic membrane component (integral component of postsynaptic density membrane) etc.; the molecular functions mainly regulate the functions of genes such as signal receptor activation (SIGNALING RECEPTOR ACTIVATOR), receptor ligand activity (receptor LIGAND ACTIVITY), hormone activity (hormonactivity) and the like (FIG. 5B). KEGG enrichment analysis showed major involvement in modulating neuroactive ligand-receptor interactions (Neuroactive ligand-receptor interaction), PI3K-AKT signaling pathway (PI 3K-AKT SIGNALING PATHWAY), AMPK signaling pathway (AMPKSIGNALING PATHWAY), jak-STAT signaling pathway (Jak-STAT SIGNALING PATHWAY), and the like (fig. 5C).
Example 8: correlation analysis of SRSF12 expression and immunoinfiltration in AML patients
The relationship between SRSF12 expression and tumor immune cell infiltration and its effect on patient prognosis was analyzed using the "Immune Association" module in the TIMER 2.0 database. Visualization was performed using R package "ggplot 2". The box-type plot was drawn based on the relative composition of 24 immune cells, and the expression differences of 24 immune cells in the high SRSF12 expression group and the low SRSF12 expression group were observed (red for the high expression group and blue for the low expression group), and the differential expression of 12 immune cells in the SRSF12 high expression group and the low expression group was statistically significant (P < 0.05) (fig. 6A). The correlation heat map of 24 immune cells was plotted and it was found that there was a different degree of correlation between 24 immune cells (fig. 6B). Plotting the correlation lollipop of SRSF12 expression with 24 immune cells, SRSF12 was found to correlate positively with helper T-cell (T helper, r=0.253; p=0.002), tcm (r=0.204; p=0.012), pDC (r=0.189; p=0.020), T-cell (r=0.164; p=0.044) infiltrates, whereas with neutrophil (Neutrophils, r= -0.403; p < 0.001), macrophage (Macrophages, r= -0.380; p < 0.001), eosinophil (Eosinophils, r= -0.381, p < 0.001), iDC (r= -0.301; p < 0.001) infiltrates (fig. 6C).
Example 9: correlation analysis of SRSF12 expression and immunoinfiltration in AML patients
Based on the TCGA-LAML database, a correlation scatter plot of SRSF12 expression with immune cells was drawn and visualized using the R package "ggplot 2". The results show that SRSF12 expression is significantly positively correlated with infiltration levels of helper T cells (T helper, r=0.253; p=0.002), tcm (r=0.204; p=0.012), pDC (r=0.189; p=0.020), T cells (r=0.164; p=0.044) (fig. 7A-D); whereas the infiltration levels with neutrophils (Neutrophils, R= -0.403; P < 0.001), macrophages (Macrophages, R= -0.380; P < 0.001), eosinophils (Eosinophils, R= -0.381; P < 0.001), iDC (R= -0.301; P < 0.001) were significantly inversely correlated (FIG. 7E-H).
Example 10: protein-protein interaction (PPI) network of SRSF12
The interacting genes or proteins were retrieved using the on-line tool (STRING) website (http:// STRING-db. Org /), and SRSF12 was introduced into the on-line tool STRING to obtain a protein-protein interaction (PPI) network. The results show that SRSF12 interacts with SRSF11, FUS, SRSF1, SRSF9, TRA2A, CLK2, CLK3, EIF4A3, MAGOH, SRPK2 proteins (fig. 8).
Example 11: correlation analysis between SRSF12 expression and drug response
The CTRP database is a comprehensive database containing valuable drug response data and response profiles for 860 compounds in 481 cell lines, supplemented with RNA-seq. This example uses these databases to identify the expression of SRSF12 between different cell lines and calculates Pearson correlation coefficients from the area under the drug response curve (AUC), P <0.05 being considered statistically significant. The results show that there is a significant relationship between SRSF12 expression and drug response in hematopoietic and lymphoid tissues (fig. 9). Wherein ML312 (p=0.006), isoliquiritigenin (isoliquiritigenin) (p=0.032) are significantly inversely correlated with SRSF12 expression, BRD-K34099515 (p=0.016), BRD-K86535717 (p=0.047) are significantly positively correlated with SRSF12 expression.
Example 12: PCR detection of SRSF12 Gene Change
S1: peripheral venous blood samples of 60 AML patients and 30 healthy controls were collected for RNA and mononuclear cell extraction: a. 1ml Trizol was added to each well for RNA extraction; b. transferring the homogenate to a centrifuge tube without RNase in sequence; c. standing at room temperature for 5min, adding pre-cooled chloroform (200 μl chloroform/1 ml Trizol) into the centrifuge tube, shaking vigorously for 15s, standing at room temperature for 10min, centrifuging (12000 rpm) for 15min; d. carefully aspirate about 500. Mu.l of the upper aqueous phase, transfer to a centrifuge tube without RNase, add equal volume (500. Mu.l) of isopropanol, mix upside down 6-8 times, and place in a-20deg.C refrigerator for 30min; centrifuging at e.4 ℃ and 10000rpm for 15min to obtain RNA precipitate; f. discarding the supernatant, washing the precipitate with 650 μl of 75% ethanol (75% ethanol configuration: 1 times DEPC treated water plus 3 times absolute ethanol), centrifuging at 4deg.C at 8000rpm for 5min, discarding the supernatant; g. repeating step (f) for one time, discarding supernatant, sucking residual ethanol, and naturally drying for 5-10min (note that the ethanol is not completely dried); h. adding a proper amount of Rnase-free H2O to dissolve RNA, and storing in a refrigerator at-20 ℃ for later use.
S2: reverse transcription of cDNA: a. the first strand cDNA synthesis kit is adopted to synthesize cDNA, and the specific steps are as follows: the following reagents were added to a 0.2ml PCR tube: total RNA 5.0l, random Primer p (dN) 6 (0.2 g/l) 1.0l, rnase-free ddH2O 70 ℃ for 5min, and quick ice bath 10sec 5.0l、5×Reaction Buffer 4.0l、dNTP Mix(10mmol/L)2.0l、Rnase inhibitor(20U/l)1.0l、AMV Reverse Transcriptase(10U/l)2.0l, total volume 20.0l; b. mixing, and heating at 37deg.C for 5min; c, carrying out warm bath at 42 ℃ for 60min; the reaction was terminated by a 10min incubation at 70 ℃.
S3: polymerase chain reaction PCR:
a. primer synthesis: primer sequences used for reverse transcription PCR are:
SRSF12-human-F：5′-AGGTGATCGCAAAACACCAGG-3′(SEQ ID NO:1)；
SRSF12-human-R：5′-ATCGCCTGTGTCGAGACTCTT-3′(SEQ ID NO:2)；
taking housekeeping gene ACTIN as an internal reference, and the sequence of the internal reference primer is as follows:
actin-human-F：5′-AGAGCCTCGCCTTTGCCGATCC-3′(SEQ ID NO:3)；
actin-human-R：5′-CTGGGCCTCGTCGCCCACATA-3′(SEQ ID NO:4)；
and b, preparing a reaction solution according to the Real time-PCR reaction system. ddH2O 7.0l, sybrGreen QPCR MASTER Mix 10.0l, forward primer 1.0l, REVERSE PRIMER 1.0.0 l and cDNA template 1.0l are added into a PCR reaction tube respectively, and are fully and uniformly mixed.
S4: PCR amplification conditions: 94℃for 10min, (94℃for 20s,60℃for 20s,72℃for 20 s) 40 cycles.
S5: real-Time PCR data processing: after PCR amplification, the automatic analysis result of the real-time fluorescent quantitative PCR instrument is used for determining the Ct value of each specimen according to the negative control adjustment threshold and the base line, and determining whether the Ct value is effective according to the melting curve. The results are exported, and the expression difference of the target gene between the control group and each concentration group is analyzed by adopting a 2 -△△CT method, and the calculation formula is as follows: delta ct=ct Target gene －Ct Internal reference , then obtaining the average value of the delta cts of the control group, which is denoted as delta Ct Control mean , subtracting delta Ct Control from the delta cts of each group, obtaining the delta Ct value, namely delta ct= delta Ct Sample of －△Ct Control mean , and then calculating the 2 -△△CT value of each group, namely the relative expression of genes in each group. The expression level of SRSF12 was increased in AML patients compared to normal control. P < 0.05 was statistically significant (FIG. 10).
Example 13: correlation of SRSF12 expression level with survival time of AML patient
Based on the median of the SRSF12 PCR data, 60 patients were divided into two groups: a high expression set, a low expression set; the overall survival time of 60 AML patients was analyzed by Kaplan-Meier survival curve, the overall survival time of SRSF12 low-expression patients was significantly shortened compared with the higher expression group, and the difference was statistically significant (P <0.01, FIG. 11).
Taken together, the above examples found that SRSF12 was expressed higher in a variety of tumors than in neighboring normal tissues by analysis of the TIMER2.0 database. Analysis of TCGA-LAML samples using R language found that SRSF12 was highly expressed in AML tissue and that its high expression correlated well with patient prognosis. Based on the TCGA data set, the correlation, independent prognosis and diagnosis value of the SRSF12 expression and the clinical characters of the patient are analyzed, and the SRSF12 expression is related to the white blood cell count, FAB stage and cytogenetics of the patient, and the high-expression, low-age and cytogenetics risk of the SRSF12 are independent prediction factors with good prognosis of the patient. The diagnostic value of SRSF12 in AML prognosis is explored, and the prediction of SRSF12 expression level on prognosis is superior to the traditional clinical characteristics such as age, WBC index and the like. It was shown that SRSF12 may be correlated well with patient prognosis as an oncogene. GO function annotation and KEGG enrichment analysis are carried out on the differential splicing genes related to SRSF12, and the biological process is found to mainly relate to embryo organ development, embryo skeletal system development and the like; cell composition is mainly distributed in extracellular matrix, postsynaptic membrane and the like; molecular functions mainly regulate signal receptor activation, receptor ligand activity, hormonal activity, and the like. KEGG pathway analysis showed that SRSF12 target gene is mainly enriched in PI3K-AKT signaling pathway, AMPK signaling pathway, jak-STAT signaling pathway, etc. The expression of SRSF12 was positively correlated with T helper, tcm, pDC, T cells in an immunocyte infiltration assay. PPI analysis shows that SRSF12 interacts with various proteins such as SRSF11, FUS and the like, and SRSF12 expression is in negative correlation with ML312 and isoliquiritigenin and in positive correlation with BRD-K34099515 and BRD-K86535717.
The invention discovers that the expression of the splicing factor SRSF12 in AML tissues is obviously up-regulated through bioinformatics analysis and is well correlated with the prognosis of patients; SRSF12 expression can affect infiltration of immune cells in the tumor microenvironment. SRSF12 may be involved in the occurrence and development of AML as a potential oncogene.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.

Claims (10)

  1. The use of the SRSF12 gene, characterized in that the use is of the SRSF12 gene as a specific molecular marker for acute myeloid leukemia.
  2. 2. The use according to claim 1, characterized in that it is the use of the SRSF12 gene as a specific molecular marker in the diagnosis, treatment, prognosis evaluation of acute myeloid leukemia.
  3. 3. The use according to claim 1, characterized in that it is diagnostic, therapeutic, prognostic evaluation of acute myeloid leukemia by detecting the expression level of the SRSF12 gene.
  4. 4. The use according to claim 1, characterized in that it is the use of the SRSF12 gene as a specific molecular marker for the preparation of a product for diagnosis, treatment, prognosis evaluation of acute myeloid leukemia.
  5. 5. The use according to claim 4, wherein the product comprises: reagents, kits and medicaments.
  6. 6. The use according to claim 5, wherein the reagent and kit comprise specific primers for detecting SRSF12 gene, the specific primers are an upstream primer shown as SEQ ID NO. 1 and a downstream primer shown as SEQ ID NO. 2.
  7. 7. The use according to claim 5, wherein the medicament is a medicament for the treatment of acute myeloid leukemia.
  8. 8. The use according to claim 1, characterized in that it is the use of the SRSF12 gene as a specific molecular marker for screening of drugs for the treatment of acute myeloid leukemia.
  9. 9. The use according to claim 1, wherein the use is of the SRSF12 gene-regulated PI3K-AKT signaling pathway, AMPK signaling pathway, jak-STAT signaling pathway in the diagnosis, treatment, prognosis evaluation of acute myeloid leukemia.
  10. 10. The diagnosis kit for acute myelogenous leukemia is characterized by comprising a specific primer for detecting SRSF12 genes, wherein the specific primer is an upstream primer shown as SEQ ID NO. 1 and a downstream primer shown as SEQ ID NO. 2.
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