Use of RNA pseudouridine modification in the preparation of an acute myeloid leukemia in vitro test product

Abstract

The application relates to the field of biological medicine, and particularly discloses application of RNA pseudouridine modification in preparation of an acute myeloid leukemia in vitro detection product. The application takes the pseudouridine modification level of a specific gene-derived RNA molecule as an inspection index, reflects the molecular changes related to acute myeloid leukemia from the aspect of epitranscription, helps to improve the accuracy of risk assessment of acute myeloid leukemia, and has sensitivity and specificity in distinguishing acute myeloid leukemia and normal controls in terms of the pseudouridine modification level of the RNA molecule corresponding to any one of the PDE3A gene, the DPP9 gene, the SNORD59A gene, the FP236383.1 gene, the SNORD14C gene and the RNU2-6P gene. The application can be applied to the detection of blood or bone marrow and other samples outside the body, the sampling mode is simple, has good accessibility and popularization value, and is favorable for realizing early screening and risk stratification of acute myeloid leukemia.

Description

Technical Field

[0001] This invention relates to the field of biomedical technology, and in particular to the application of RNA pseudouridine modification in the preparation of in vitro diagnostic products for acute myeloid leukemia. Background Technology

[0002] Acute myeloid leukemia (AML) is a highly aggressive and heterogeneous hematologic malignancy. Despite advances in clinical management and molecular profiling, many patients still suffer from poor prognoses. The integration of multi-omics sequencing technologies has accelerated the characterization of AML and improved the accuracy of risk stratification, thus supporting the development of more targeted treatment strategies. However, due to its inherent biological complexity, AML treatment remains challenging, highlighting the need for other molecular markers that can be reliably measured in clinical samples, in addition to sequence variations.

[0003] Besides genetic alterations, dysregulated procedures such as epigenetic and epitranscriptional mechanisms are increasingly recognized as markers of cancer, making them highly attractive intervention targets. Pseudoruridylation and its modifications are associated with malignant phenotypes under certain conditions. For example, SHQ1 has been reported to promote T-cell acute lymphoblastic leukemia (T-ALL) by regulating U2 spliceosome RNA pseudouridineation, thereby affecting precursor mRNA splicing. Furthermore, the pseudouridine synthase DKC1 has been proposed as a therapeutic target for colorectal cancer, sparking interest in the pharmacological regulation of pseudouridine-related factors. In contrast, the pseudouridine profile of the whole transcriptome in acute myeloid leukemia (AML) and the contribution of pseudouridine-modified genes to AML-related remodeling remain poorly understood.

[0004] Pseudoruridine is one of the most abundant post-transcriptional RNA modifications in human cells, present in various RNAs, including messenger RNA, ribosomal RNA, transfer RNA, and non-coding RNA. The human genome encodes 13 pseudouridine synthases (PUS), which play crucial roles in regulating physiological processes and disease pathogenesis. However, systematic analysis of transcriptome-wide pseudouridineization in an acute myeloid leukemia (AML) cohort has been limited by practical analytical methods, such as the need for sensitive and quantitatively comparable measurements of heterogeneous clinical samples.

[0005] Therefore, there is an urgent need to develop an in vitro detection technology based on the level of pseudouridine modification in RNA from specific gene sources, so as to achieve effective assessment of the risk of acute myeloid leukemia, thereby providing a new technical means for early screening and risk stratification of acute myeloid leukemia. Summary of the Invention

[0006] The purpose of this invention is to address the above-mentioned shortcomings of the prior art by providing the application of RNA pseudouridine modification in the preparation of in vitro detection products for acute myeloid leukemia (AML). Using bisulfite-induced deletion sequencing technology, whole transcriptome Ψ analysis was performed on peripheral blood and bone marrow samples from 43 AML patients and non-leukemia control groups, identifying a group of differentially expressed RNA pseudouridine modification genes for AML, including coding genes (such as DPP9, PDE3A) and non-coding RNAs (such as SNORD59A, FP236383.1, RNU2-6P, SNORD14C).

[0007] To achieve the above objectives, the present invention adopts the following technical solution: The first aspect of the present invention is to provide the application of RNA pseudouridine modification in the preparation of an in vitro diagnostic product for acute myeloid leukemia, wherein the in vitro diagnostic product is used to detect the pseudouridine modification level of RNA molecules corresponding to at least one of the genes PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C and RNU2-6P derived from an in vitro sample of a subject, and to assess whether the subject has acute myeloid leukemia or the risk of having acute myeloid leukemia based on the pseudouridine modification level.

[0008] Furthermore, the RNA is a combination of at least two of the RNA molecules corresponding to the PDE3A gene, DPP9 gene, SNORD59A gene, FP236383.1 gene, SNORD14C gene, and RNU2-6P gene.

[0009] Furthermore, the pseudouridine modification sites of the PDE3A gene, DPP9 gene, SNORD59A gene, FP236383.1 gene, SNORD14C gene, and RNU2-6P gene are as follows: Located within the PDE3A gene, it corresponds to position 20551493 on chromosome 12 of the human reference genome GRCh38 version, and is located at nucleotide 182249 downstream of the start of the PDE3A gene sequence. This specific site corresponds to nucleotide 101 in the sequence shown in SEQ ID NO:1. Located within the DPP9 gene, it corresponds to position 4724081 on chromosome 19 of the human reference genome GRCh38 version, and is located at nucleotide 593 downstream of the start of the DPP9 gene sequence. This specific site corresponds to nucleotide 101 in the sequence shown in SEQ ID NO:2. Located within the SNORD59A gene, it corresponds to position 56645072 on chromosome 12 of the human reference genome GRCh38 version, and is located at the 30th nucleotide downstream of the start of the SNORD59A gene sequence. This specific site corresponds to the 30th nucleotide in the sequence shown in SEQ ID NO:3. Located within the FP236383.1 gene, it corresponds to position 8401487 on chromosome 21 of the human reference genome GRCh38 version, and is located at nucleotide 20845 downstream of the start of the FP236383.1 gene sequence. This specific site corresponds to nucleotide 101 in the sequence shown in SEQ ID NO:4. Located within the SNORD14C gene, it corresponds to position 123059374 on chromosome 11 of the human reference genome GRCh38 version, and is located at the 49th nucleotide downstream of the start of the SNORD14C gene sequence. This specific site corresponds to the 49th nucleotide in the sequence shown in SEQ ID NO:5. Located within the RNU2-6P gene, it corresponds to position 46374500 on chromosome 13 of the human reference genome GRCh38 version, and is located at the 91st nucleotide downstream of the start of the SNORD14C gene sequence. This specific site corresponds to the 91st nucleotide in the sequence shown in SEQ ID NO:6.

[0010] Furthermore, the level of RNA pseudouridine modification is the proportion of pseudouridine nucleotides at specific sites on the mRNA, tRNA, or non-coding RNA of the gene.

[0011] Furthermore, the ex vivo sample is selected from blood samples or bone marrow samples, and the blood sample includes serum, plasma or peripheral blood.

[0012] Furthermore, the assessment is based on a preset threshold. When the pseudouridine modification level of the RNA molecule corresponding to at least one of the genes selected from PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P is higher than the preset threshold, the subject is determined to be a high-risk group for acute myeloid leukemia.

[0013] Furthermore, the preset threshold is determined through subject operating curve analysis. The preset threshold is the value corresponding to the point that maximizes the sum of sensitivity and specificity, and the area under the curve (AUC) of the evaluation model established based on the preset threshold is not less than 0.8.

[0014] Furthermore, the in vitro diagnostic product is used for early screening, subtype classification, efficacy monitoring, or relapse risk assessment of acute myeloid leukemia.

[0015] A second aspect of the present invention is to provide an in vitro detection method for acute myeloid leukemia, comprising the following steps: Provide ex vivo samples derived from the subjects; RNA was extracted from the in vitro sample; The pseudouridine modification level of RNA molecules corresponding to at least one of the genes PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P in the in vitro sample was detected. The risk of acute myeloid leukemia in the subjects was assessed based on the level of pseudouridine modification. When the pseudouridine modification level of the RNA molecule corresponding to the PDE3A gene is higher than 0.3, the subject is identified as a high-risk group for acute myeloid leukemia. And / or when the pseudouridine modification level of the RNA molecule corresponding to the DPP9 gene is higher than 0.2, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the SNORD59A gene is higher than 0.4, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the FP236383.1 gene is higher than 0.5, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the SNORD14C gene is higher than 0.3, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the RNU2-6P gene is higher than 0.3, the subject is determined to be a high-risk group for acute myeloid leukemia.

[0016] A third aspect of the present invention is to provide an in vitro diagnostic kit for the detection of acute myeloid leukemia, the kit containing a reagent for detecting the level of RNA pseudouridine modification of the gene.

[0017] Compared with the prior art, the beneficial effects of the present invention are: (1) The present invention uses the pseudouridine modification level of RNA molecules from specific genes as an indicator. Compared with traditional markers such as DNA methylation, protein expression or miRNA level, it reflects the molecular changes related to acute myeloid leukemia at the epitranscriptional level, which can provide a new detection dimension and help improve the accuracy of acute myeloid leukemia risk assessment.

[0018] (2) This invention detects the pseudouridine modification level of RNA molecules corresponding to PDE3A gene, DPP9 gene, SNORD59A gene, FP236383.1 gene, SNORD14C gene and RNU2-6P gene. Compared with the overall RNA modification level analysis, it has stronger targeting and specificity, which helps to reduce non-specific interference and improve the reliability of detection results.

[0019] (3) By setting a preset threshold, the present invention establishes a correspondence between the RNA pseudouridine modification level and the risk of acute myeloid leukemia, so that the test results can be directly used for risk stratification of subjects, with clear judgment criteria, which is convenient for implementation and promotion in in vitro test products.

[0020] (4) This invention can be applied to the detection of isolated samples such as blood or bone marrow. The sampling method is relatively simple, with good accessibility and promotion value, which is conducive to the early screening and risk stratification of acute myeloid leukemia. Attached Figure Description

[0021] Figure 1 To illustrate gene expression profiles and global RNA Ψ modification levels, Figure A shows PCA analysis based on whole transcriptome gene expression from 43 samples. The samples are labeled as PB control (green), BM control (gray), PB AML (orange), and BM AML (dark red). PC1 and PC2 explain 25.34% and 21.39% of the total variance, respectively. Figure B compares the deletion rates of Ψ sites in different sample groups (myeloid acute myeloid leukemia, myeloid control, peripheral blood acute myeloid leukemia, and peripheral blood control) between bisulfite-treated and untreated libraries. The error bars represent the standard deviation. Figure C shows the density distribution of Ψ modification levels in each group, with most sites ranging from 25% to 75%.

[0022] Figure 2 This is a heatmap of sample correlations based on gene expression profiles. The heatmap shows the pairwise Pearson correlation coefficients calculated based on transcriptomic gene expression profiles among all samples (n = 43). Rows and columns represent individual samples, and annotations indicate sample groups, including acute myeloid leukemia (AML) samples and control samples. Color intensity reflects the strength of correlation, with red indicating a high correlation and blue indicating a low correlation. Overall, the samples show a trend of clustering by disease state. Many AML samples show high intra-group similarity and relatively low correlation with the control group. Although some sample mixing was also observed, these results support the consistency of gene expression data and are consistent with the heterogeneity of transcriptomic features in AML.

[0023] Figure 3To illustrate transcriptomic differential expression and functional enrichment in AML, Figure A shows a hierarchical clustering heatmap of differentially expressed genes (DEGs) in AML and control samples, with color intensity representing normalized expression levels (red: upregulated; blue: downregulated). Figure B shows a volcano plot of DEGs, with the x-axis representing log2 fold change (AML vs. control) and the y-axis representing the -log10 p-correction value. Red / blue dots represent upregulated (n=1285) / downregulated (n=1063) DEGs (|log2FC|>1, p-correction value<0.05). Figure C shows a GO enrichment bubble plot of DEGs. The x-axis represents the gene ratio, and the y-axis lists the biological processes involved in the enrichment. Bubble size represents the number of differentially expressed genes in each item, and color indicates p-value adjustment. Figure 4 This is a graph showing the enrichment analysis of pathways associated with Ψ site dysregulation in acute myeloid leukemia (AML).

[0024] Figure 5 To illustrate the sequencing depth distribution of Ψ modification sites in each sample group, a bar chart shows the average sequencing depth of high-confidence Ψ sites in each sample, grouped by tissue origin and disease state, including BM_control (bone marrow of non-leukemia control group, n = 10), PB_control (peripheral blood of control group, n = 13), BM_AML (bone marrow of acute myeloid leukemia patient, n = 10), and PB_AML (peripheral blood of acute myeloid leukemia patient, n = 10). The height of the bar chart represents the average sequencing depth of each Ψ site in each sample. The overall similar sequencing depth among the groups indicates consistent sequencing depth and supports subsequent analysis of Ψ modification levels.

[0025] Figure 6 Figure 1 shows the expression, overall Ψ level, and differentially expressed Ψ sites of the PUS gene in acute myeloid leukemia (AML). Figure A represents the transcriptional level (log2 CPM) of 13 PUS genes in the control group (grey box plot) and the AML group (red box plot). Statistical significance is expressed as *p<0.05, **p<0.01, ***p<0.001; ns indicates no statistical significance. Figure B shows the correlation between PUS10 expression and the overall Ψ modification level between samples (r = 0.6, p = 2 × 10⁻⁶). -5The shaded areas represent 95% confidence intervals; C represents the expression (log2TPM) of PUS10 in LAML (n = 173) and normal (n = 70) samples from the GEPIA2 database; D represents the Kaplan-Meier survival curves of AML patients stratified according to PUS10 expression levels (high expression group vs. low expression group); E is a volcano plot of differentially expressed Ψ sites in AML, with orange and blue dots representing significantly upregulated and downregulated Ψ sites, respectively (p < 0.05); F is a heatmap of 44 significantly altered Ψ sites in control and AML samples, with color intensity representing the level of Ψ modification after z-score normalization.

[0026] Figure 7 To illustrate the distribution of high-confidence Ψ sites across different RNA organisms, a pie chart shows the proportion of high-confidence Ψ sites assigned to different RNA categories. Protein-coding transcripts accounted for the largest proportion (44%), followed by long non-coding RNAs (lncRNAs, 41.5%), small nuclear RNAs (snRNAs, 4.0%), small nucleolar RNAs (snoRNAs, 3.6%), ribosomal RNAs (rRNAs, 3.3%), mitochondrial tRNAs (Mt_tRNAs, 1.8%), rRNA pseudogenes (1.1%), and other RNAs (0.7%). All percentages are calculated based on the total number of Ψ sites detected.

[0027] Figure 8 The overall proportion of pseudouridine modification in RNA is shown in the box plot, which shows the distribution of the proportion of Ψ modification (deletion rate) in different RNA categories. Each box represents the interquartile range (IQR), and the center line represents the median modification level.

[0028] Figure 9 To illustrate the relationship between changes in Ψ modification and alterations in gene expression in AML, a scatter plot is used to show the relationship between the log2 fold change (FC) of differentially expressed and modified genes in AML (x-axis) and the log2FC of Ψ modification level (y-axis). The dashed lines divide the four quadrants: Q1, expression increases when Ψ level increases; Q2, expression decreases when Ψ level increases; Q3, expression decreases when Ψ level decreases; Q4, expression increases when Ψ level decreases.

[0029] Figure 10 The figure shows the Ψ modification level of candidate genes and their performance evaluation in AML. Figure A represents the Ψ modification level of selected pseudouridine-modified genes in AML (red box plot) and control samples (gray box plot), quantified as deletion rate (%). p<0.05, p<0.01, p<0.001; B is the ROC curve showing the diagnostic sensitivity and specificity of the Ψ modification levels of DPP9 (AUC = 84.2%, optimal cutoff value = 0.2) and PDE3A (AUC = 84.8%, optimal cutoff value = 0.3) in AML.

[0030] Figure 11 This study presents a protein-protein interaction (PPI) network of differentially modified Ψ genes in AML. This PPI network summarizes known or predicted protein interactions between genes containing altered Ψ sites in AML. Nodes represent proteins, and node sizes correspond to degree centrality (range: 2.5–10). Edges represent known or predicted functional interactions based on the STRING database. This analysis provides a network view of potential functional relationships between Ψ-related genes in AML.

[0031] Figure 12 To assess the performance of Ψ modification levels in candidate genes in AML detection, this figure summarizes the area under the curve (AUC) values ​​of Ψ modification levels in distinguishing AML from control samples across multiple candidate genes, obtained through receiver operating characteristic (ROC) analysis.

[0032] Figure 13 To illustrate the differences in Ψ modification levels of specific non-coding RNAs in acute myeloid leukemia (AML), Figure A is a box plot showing the Ψ modification levels (quantified as deletion rate) of SNORD59A, FP236383.1, RNU2-6P, and SNORD14C in control and AML samples; Figure B is an ROC curve, assessing the ability of Ψ levels at each site to distinguish between AML and control groups, showing the AUC values ​​of SNORD59A (87.1%), FP236383.1 (86.6%), RNU2-6P (85.9%), and SNORD14C (82.6%).

[0033] Figure 14 This invention summarizes the sensitivity and specificity of the pseudouridine modification levels of RNA molecules corresponding to the PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P genes in distinguishing AML from normal controls. Detailed Implementation

[0034] To make the objectives, technical solutions, and advantages of the present invention clearer, embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0035] This invention is based on the abnormal changes in pseudouridine (Ψ) in RNA epigenetic modifications during tumorigenesis and development. Pseudouridine modification can affect the expression regulation of related genes by altering the spatial structure, stability, and translation efficiency of RNA molecules. In the development of acute myeloid leukemia, the pseudouridine modification level of RNA molecules from specific genes undergoes significant changes, thus it can serve as a potential molecular marker for disease risk assessment.

[0036] This invention enables in vitro assessment of the risk of acute myeloid leukemia in subjects by detecting the pseudouridine modification level of RNA molecules derived from specific genes (PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P) and establishing risk assessment criteria using statistical methods.

[0037] In this invention, the object of examination is RNA molecules in an in vitro sample derived from a subject. The in vitro sample includes serum, plasma, peripheral blood, or bone marrow. Preferably, the sample is a peripheral blood or bone marrow sample. The method for extracting total RNA can be a conventional method in the art, such as phenol / chloroform extraction, silica gel column purification, magnetic bead extraction, etc.

[0038] The PDE3A gene, DPP9 gene, SNORD59A gene, FP236383.1 gene, SNORD14C gene and RNU2-6P gene involved in this invention are all known genes, and their nucleotide sequences can be obtained from public databases (such as GenBank).

[0039] In this invention, the pseudouridine modification is a pseudouridine modification at a specific site on the corresponding RNA molecule, wherein the specific site is one of the following: Located on human chromosome 12, its precise coordinates are position 20551493 on chromosome 12. This site lies within the coverage area of ​​the PDE3A gene (whose Ensembl identifier is ENSG00000172572). Calculations show that this site corresponds to the 182249th nucleotide downstream of the start of the PDE3A gene sequence (based on the genomic start position defined in GRCh38). This invention provides a nucleotide fragment containing this site and its flanking sequences, as shown in SEQ ID NO:1 in the sequence listing. SEQ ID NO:1 is 199 bp in length and is a sequence composed of the target site (chr12:20551493), its upstream 100 bp fragment, and its downstream 98 bp fragment. Specifically, the specific site described in this invention (i.e., the aforementioned 182249th nucleotide) corresponds to the 101st nucleotide of SEQ ID NO:1 counting from the 5' end. Located on human chromosome 19, its precise coordinates are position 4724081 on chromosome 19. This site lies within the coverage area of ​​the DPP9 gene (whose Ensembl identifier is ENSG00000142002). Calculations show that this site corresponds to the 593rd nucleotide downstream of the start of the DPP9 gene sequence (based on the genomic start position defined in GRCh38). This invention provides a nucleotide fragment containing this site and its flanking sequences, as shown in SEQ ID NO:2 in the sequence listing. SEQ ID NO:2 is 199 bp in length and is a sequence composed of the target site (chr19: 4724081), its upstream 100 bp fragment, and its downstream 98 bp fragment. Specifically, the specific site described in this invention (i.e., the aforementioned 593rd nucleotide) corresponds to the 101st nucleotide of SEQ ID NO:2, counting from the 5' end. Located on human chromosome 12, its precise coordinates are chromosome 12, position 56645072. This site lies within the coverage area of ​​the SNORD59A gene (its Ensembl identifier is ENSG00000207031). Calculations show that this site corresponds to the 30th nucleotide downstream of the start of the SNORD59A gene sequence (based on the genomic start position defined in GRCh38). This invention provides a nucleotide fragment containing this site and its flanking sequences, as shown in SEQ ID NO:3 in the sequence listing. SEQ ID NO:3 is 75 bp in length and is a sequence composed of the target site (chr12: 56645072), its upstream 29 bp fragment, and its downstream 45 bp fragment. Specifically, the specific site described in this invention (i.e., the aforementioned 30th nucleotide) corresponds to the 30th nucleotide of SEQ ID NO:3 counting from the 5' end. Located on human chromosome 21, its precise coordinates are position 8401487. This site lies within the coverage area of ​​the FP236383.1 gene (whose Ensembl identifier is ENSG00000280441). Calculations show that this site corresponds to the 20845th nucleotide downstream of the start of the FP236383.1 gene sequence (based on the genomic start position defined in GRCh38). This invention provides a nucleotide fragment containing this site and its flanking sequences, as shown in SEQ ID NO:4 in the sequence listing. SEQ ID NO:4 is 199 bp in length and is a sequence composed of the target site (chr12:8401487), its upstream 100 bp fragment, and its downstream 98 bp fragment. Specifically, the specific site described in this invention (i.e., the aforementioned 20845th nucleotide) corresponds to the 101st nucleotide of SEQ ID NO:4, counting from the 5' end. Located on human chromosome 11, its precise coordinates are chromosome 11, position 123059374. This site lies within the coverage region of the SNORD14C gene (its Ensembl identifier is ENSG00000202252). Calculations show that this site corresponds to the 49th nucleotide downstream of the start of the SNORD14C gene sequence (based on the genomic start position defined by GRCh38). This invention provides a nucleotide fragment containing this site and its flanking sequences, as shown in SEQ ID NO:5 in the sequence listing. SEQ ID NO:5 is 88 bp in length and is a sequence composed of the target site (chr12: 123059374), its upstream 48 bp fragment, and its downstream 39 bp fragment. Specifically, the specific site described in this invention (i.e., the aforementioned 49th nucleotide) corresponds to the 49th nucleotide of SEQ ID NO:5, counting from the 5' end.

[0040] Located on human chromosome 13, its precise coordinates are position 46374500. This site lies within the coverage area of ​​the RNU2-6P gene (whose Ensembl identifier is ENSG00000223336). Calculations show that this site corresponds to the 49th nucleotide downstream of the start of the RNU2-6P gene sequence (based on the genomic start position defined in GRCh38). This invention provides a nucleotide fragment containing this site and its flanking sequences, as shown in SEQ ID NO:6 in the sequence listing. SEQ ID NO:6 is 190 bp in length and is a sequence composed of the target site (chr12: 46374500), its upstream 90 bp fragment, and its downstream 99 bp fragment. Specifically, the specific site described in this invention (i.e., the aforementioned 91st nucleotide) corresponds to the 91st nucleotide of SEQ ID NO:6, counting from the 5' end.

[0041] It should be noted that, unless otherwise stated, the genomic coordinates and locations involved in this invention are based on the human reference genome GRCh38 (hg38) version.

[0042] In this invention, the RNA pseudouridine modification level is the pseudouridine ratio at a specific site on the mRNA, tRNA, or non-coding RNA of the gene.

[0043] In some embodiments, the level of pseudouridine modification at one or more of the above-mentioned sites can be detected. The detection can be performed on RNA samples extracted from ex vivo samples such as blood or bone marrow samples, and can employ conventional detection methods in the art, including but not limited to locating and / or quantifying Ψ modification using chemical modification combined with reverse transcription, enzymatic treatment, mass spectrometry, or high-throughput sequencing.

[0044] The following specific embodiments illustrate the application of RNA pseudouridine modification provided by the present invention in the preparation of in vitro detection products for acute myeloid leukemia.

[0045] This invention complies with relevant regulations and has been approved by the Medical Ethics Committee of Zhongnan Hospital of Wuhan University (Approval No.: 2024051K).

[0046] <Research Cohort> This invention collected 43 clinical specimens from Zhongnan Hospital of Wuhan University, including peripheral blood (10 patients with acute myeloid leukemia [AML] and 13 non-leukemia control cases) and bone marrow aspiration fluid (10 AML patients and 10 non-leukemia control cases). Diagnosis was based on standard clinical diagnostic criteria.

[0047] Forty-three collected samples were included in the Ψ sequencing analysis, including 23 peripheral blood samples and 20 bone marrow aspiration samples. There were no significant differences between the two groups in terms of age and sex. The detailed demographics and clinical characteristics of the participants are summarized in Table 1. Compared with the control group, the hemoglobin level, red blood cell count, and platelet count of AML patients were significantly decreased, while the white blood cell count was significantly increased. These results were consistent with the hematological abnormalities associated with AML.

[0048] Table 1. Clinical and demographic characteristics of participants in the study cohort.

[0049]

[0050] <RNA Extraction> First, density gradient centrifugation was performed on peripheral blood samples to isolate peripheral blood mononuclear cells (PBMCs), and then total RNA was extracted using TRIzol reagent (Invitrogen, 15596018CN). Total RNA in bone marrow samples was extracted using the RNAprep Pure kit (TIANGEN, DP439). Residual genomic DNA was removed by treatment with DNase I. The purified RNA was chemically fragmented using a fragmentation reagent (NEB, E6150S).

[0051] <Bisulfite Conversion and Library Construction> The fragmented RNA (about 100 ng) was treated with sodium bisulfite to generate the bisulfite-converted fraction ("EX"). At the same time, the matching fragmented RNA without bisulfite treatment was treated as an input control ("IN"). A strand-specific library was prepared using the SMARTer Stranded Total RNA-Seq Kit V3 (Takara Bio, 634487) according to the manufacturer's instructions, but Maxima H Minus Reverse Transcriptase (Thermo Fisher Scientific, EP0751) was used instead of SMARTScribe II for first-strand cDNA synthesis. The library was sequenced on the Illumina NovaSeq 6000 platform (paired-end sequencing, 150 bp; Genewiz).

[0052] <Identification of Ψ Sites from Sequencing Data Using Bisulfite-Induced Deletion Mapping> A Ψ sequencing library was constructed from 43 clinical samples, including patient-derived samples and healthy control samples, collected as peripheral blood and bone marrow aspirates. Matched RNA-seq datasets from the same samples provided important controls for filtering background noise. The library construction protocol preserved the strand orientation and designated the R2 sequence of the reads as representative of the sense strand. Thus, all downstream analyses were performed based solely on read2 data. Adapter sequences were first removed from the Illumina raw reads using cutadapt and quality trimming was performed. Subsequently, PCR duplicates were removed using seqkit. During library construction, an 8-bp UMI sequence and a 6-bp constant region were integrated to correct amplification bias and improve alignment accuracy. These technical sequences were removed from the deduplicated reads using UMI_tools prior to alignment. After quality control, the cleaned sequencing reads were aligned to the human reference genome (hg38) using HISAT2 (v2.2.1). Reads that failed to align were systematically excluded from subsequent analyses. To improve alignment accuracy and specifically detect deletion features indicative of Ψ modification, the realignment.py script from the PRAISE pipeline was applied. This step effectively filtered out low-confidence alignment results. The entire data processing and alignment strategy followed the standard workflow outlined in the PRAISE protocol.

[0053] Candidate Ψ sites were screened to establish high-confidence datasets for the AML group and the control group separately. Group-specific thresholds included: alignment quality ≥ 5; site coverage ≥ 10; ≥ 2 reads carrying deletions with deletion coverage ≥ 10%; not present in background ("IN") samples; and detected in ≥ 50% of the samples in each group. Missing data were imputed using the average coverage per site.

[0054] <Quantifying Ψ levels in AML clinical samples> To quantify Ψ modification in individual AML clinical samples, a ratio calculation method was employed. Specifically, the Ψ level at each genomic site was defined as the ratio of the number of reads with the characteristic deletion signature to the total number of reads aligned to that site. This yielded a site-specific score ranging from 0 (indicating no modification) to 1 (indicating complete modification). To measure the Ψ value at the global sample level, the total number of reads containing deletions at all high-confidence sites was divided by the cumulative coverage of these sites. Subsequently, these calculated Ψ values were used to investigate their association with the expression levels of PUS genes.

[0055] "1]]<Ψ differential analysis in AML> To identify Ψ-sites with differentially modified patterns between AML patients and healthy control donors, statistical difference analysis was performed on the modification levels of each candidate site. A linear model was established using the subjects' disease status as the grouping variable, and a t-test modified using an empirical Bayesian method was employed to assess the significance of each candidate site. The obtained p-values ​​were adjusted using a multiple hypothesis testing method to control the false discovery rate (FDR), thereby selecting differentially modified sites that met the pre-defined significance criteria. The RNA pseudouridine modification level refers to the modification proportion of the corresponding RNA site.

[0056] Specifically, this embodiment uses the limma R package for linear modeling and statistical analysis. Within this framework, the lmFit function is used to perform a modified t-test to evaluate the significance of each candidate Ψ site. Subsequently, the Benjamini-Hochberg method is applied to correct for multiple hypothesis testing to control for the false discovery rate (FDR).

[0057] <Statistical Analysis> Further statistical analysis was performed on the selected large-amount data. For comparisons between two independent samples, a two-tailed t-test was used if the data conformed to a normal distribution and had homogeneity of variance; otherwise, a non-parametric test was used. Continuous variables were expressed as median and interquartile range. Preferably, a p-value less than 0.05 was used as the criterion for statistical significance.

[0058] It should be noted that the above statistical analysis can be performed using the R language environment or commercial statistical software.

[0059] Specifically, all statistical analyses in this embodiment were performed using commonly used statistical software such as SPSS version 21.0, employing standard methods known in the art, including descriptive statistics, analysis of variance, and correlation analysis. For comparisons between independent groups, the nonparametric Mann-Whitney U test or the two-tailed Student's t test was selected based on the data distribution characteristics. Continuous variables were expressed as median and interquartile range (IQR). Statistical significance was defined as a two-tailed p-value less than 0.05.

[0060] Example 1 A study of overall Ψ modification levels that are comparable between AML patients and controls.

[0061] To verify the quality of the sequencing data, this embodiment first evaluated the gene expression profiles of all 43 samples and performed principal component analysis (PCA). PCA analysis based on whole-genome expression profiles was able to effectively distinguish between leukemia samples and non-leukemia samples (e.g., ...). Figure 1(As shown in A in the figure). To quantify the overall RNA Ψ modification level in AML patients, this invention analyzed the overall Ψ modification level in 20 AML patients and 23 controls. Compared with the untreated library, the bisulfite-treated library showed a significant reverse transcription deletion signal at the Ψ sites. The mean deletion level at all Ψ sites was approximately 50%, with deletion levels at most sites ranging from 25% to 75% (e.g., ...). Figure 1 (As shown in B and C). No significant differences in overall Ψ modification levels were observed among the study groups.

[0062] To assess transcriptional consistency and intergroup stratification, this embodiment used genome-wide gene expression profiling for correlation analysis. Pearson correlation heatmaps showed that the samples generally tended to cluster by disease state (e.g., Figure 2 (As shown). Many AML samples (red labels) showed high intragroup correlations, while control samples (gray labels) also showed strong intragroup similarities. Although some mixing was observed between AML and control samples, this likely reflects biological heterogeneity in sample composition. The overall pattern was consistent with disease-associated transcriptomic differences and supports subsequent differential expression and Ψ modification analyses.

[0063] Example 2 Transcriptomic and functional analysis of differentially expressed genes in acute myeloid leukemia.

[0064] To characterize transcriptional alterations associated with AML, gene expression profiles were compared between AML and control samples. Unsupervised hierarchical clustering analysis based on genome-wide expression patterns showed that AML and control samples were largely separated (e.g., Figure 3 As shown in A), this supports disease-related expression differences. Differential expression analysis identified 2358 significantly differentially expressed genes (DEGs) between the two groups (|log2FC|>1, p-corrected <1×10⁻⁶). -5 In AML, 1295 genes were upregulated and 1063 genes were downregulated (e.g., Figure 3 (As shown in B in the diagram).

[0065] To elucidate the functional relevance of DEGs, this invention performed gene ontology (GO) enrichment analysis. DEGs were significantly enriched in GO biological processes associated with immune cell differentiation and activation, cell adhesion and interaction, and inflammatory signaling (p < 4 × 10⁻⁶ after correction). -4 Representative GO entries include monocyte differentiation, T cell receptor signaling pathway, interleukin adhesion, and classical NF-κB signaling (such as...). Figure 3as shown in C in []. In addition, enrichment of other entries related to leukocyte apoptosis and regulation of cellular homeostasis was also observed, indicating that AML-related transcriptional changes involve immune regulation and cell survival programs.

[0066] In addition, KEGG pathway enrichment analysis was performed using genes containing differential Ψ sites in AML and control samples. KEGG network analysis prominently showed enrichment of pathways related to leukemogenesis and immune signaling, including the acute myeloid leukemia pathway, NF-κB, FoxO, and MAPK signaling pathways, and cytokine-cytokine receptor interaction (such as Figure 4 as shown). These results are consistent with the possible association between Ψ remodeling and signaling pathways related to AML biology.

[0067] Example 3 Analysis of the expression profile of Ψ synthases and identification of genome-wide Ψ sites in acute myeloid leukemia (AML).

[0068] To evaluate the data quality, the present invention detected the average sequencing coverage of high-confidence Ψ sites in all samples. All groups showed sufficient and comparable coverage, with an average sequencing depth exceeding 30× per site, and similar distributions among groups (such as Figure 5 as shown), and showed a consistent distribution. This coverage can be used for subsequent quantitative analysis of Ψ modification levels and differential expression analysis.

[0069] Based on the observed transcriptomic differences between AML and control samples, the expression of Ψ synthase-related genes in AML was next detected to determine if it had changed. In this example, the transcriptional levels of 13 Ψ synthase-related genes were evaluated, and it was found that 8 of these genes were significantly upregulated in AML compared to the control group (such as Figure 6 shown in A in []. Among these candidate genes, only the expression of PUS10 was significantly positively correlated with the overall Ψ modification level (such as Figure 6 shown in B in []. Integrating the PUS10 expression data with the AML transcriptome profiles from the GEPIA2 database confirmed its high expression in AML subtypes and suggested its association with patient prognosis (such as Figure 6 shown in C and D in []. These results suggest that the Ψ modification map may be related to the expression of Ψ synthase-related genes and suggest that PUS10 is a candidate factor worthy of further study.

[0070] To analyze the Ψ modification sites in AML and control samples, the <Ψ differential analysis method for AML> was used to screen for high-confidence Ψ sites. After quality control, 275 high-confidence Ψ sites were identified in all samples (as shown in Table 2). Analysis of the high-confidence Ψ sites revealed significant differences in the distribution of Ψ sites among different RNA classes (such as Figure 7(As shown). The Ψ site was the most prevalent in protein-coding transcripts (44%), followed by long non-coding RNAs (lncRNAs, 41%). A significant proportion of pseudouridine modification was also detected in small nuclear RNAs (snRNAs, 4%) and small nucleolar RNAs (snoRNAs, 3.6%), consistent with the potential role of pseudouridine in RNA processing and related RNP functions. This distribution reflects the broad involvement of pseudouridine modification in various RNA-mediated functions and provides clues for further investigation into its role in post-transcriptional regulation.

[0071] Table 2. Results of gene differential expression analysis.

[0072]

[0073] Note: + represents a positive chain; - represents a negative chain.

[0074] Further analysis was conducted on the distribution of pseudouridine acidification modification ratios in each RNA class (e.g., Figure 8 (As shown). Among the annotated categories, only snRNAs showed significantly higher levels of pseudouridine acidification in AML than in the control group, while no generalized changes were observed in other RNA categories. Interestingly, this snRNA-specific increase contrasts with the lack of generalized changes in pseudouridine acidification modifications in other RNA organisms, despite the upregulation of key PUS proteins, including PUS1, PUS7, and DKC1, in AML. This striking difference may stem from posttranscriptional or subcellular regulatory mechanisms that decouple the expression of synthases from their catalytic output.

[0075] Differential modification analysis identified 44 Ψ sites that were significantly altered in acute myeloid leukemia (AML) (P<0.05), including 17 highly modified sites and 27 lowly modified sites (e.g., ...). Figure 6(As shown in E and F in the diagram). Notably, although upregulation of multiple pseudouridine esterases was observed, the number of highly modified sites was lower than that of lowly modified sites. This pattern may reflect the site specificity of pseudouridine esterification and the fact that the global Ψ signal integrates contributions from multiple sites, including those with insignificant or small changes. Furthermore, increases at a few sites may still be biologically significant, especially when the changes are large or the affected transcripts have important functions. Next, this invention compares the log2 fold changes in the expression of included genes and Ψ levels (e.g., ...) Figure 9 As shown in the figure, the relationship between changes in gene expression and alterations in Ψ modification in AML was investigated. Based on the coordination of gene expression-modification patterns, genes were divided into four quadrants: Q1, with increased expression and elevated Ψ levels; Q2, with decreased expression and elevated Ψ levels; Q3, with decreased expression and decreased Ψ levels; and Q4, with increased expression and decreased Ψ levels. Heterogeneity in the expression-modification relationships of different genes was observed. For example, MT-ND4 and ACADM were located in Q1, with both their expression and Ψ modification showing consistent increases, while RNU2-6P was located in Q3, with both its expression and Ψ modification showing decreases. Given that RNU2-6P is associated with U2 snRNA and pre-mRNA splicing, this observation suggests the need for further investigation into whether dynamic changes in Ψ are related to alterations in RNA processing in AML.

[0076] Example 4 Identification and network connectivity of differentially pseudouridine-modified genes in acute myeloid leukemia.

[0077] To investigate the alterations in gene-specific pseudouridine monophosphate (PUR) modification in AML and their clinical significance, this invention compared the PURPH levels of candidate genes in AML and control samples. Some genes showed significantly different deletion rates between the two groups, including DPP9 and PDE3A (e.g., Figure 10 As shown in Figure A), this indicates elevated pseudouridine acidification levels in these transcripts in AML. Previous studies have reported that the DPP8 / 9 specific inhibitor Val-boroPro can effectively inhibit the proliferation of various AML cell models, and its efficacy has been validated in vitro and in vivo systems. Furthermore, PDE3A has become one of the therapeutic targets for AML, and the PDE3A inhibitor anagrelide (ANA) has shown significant anti-leukemic activity. However, anagrelide is a protein-level inhibitor that primarily interferes with the cAMP signaling pathway by inhibiting the activity of the PDE3A enzyme, and does not necessarily mean that the cause of PDE3A abnormalities is pseudouridine acidification at the RNA level.

[0078] Surprisingly, consistent with these reports, whole-transcriptome pseudouridine acidification analysis showed a significant increase in the pseudouridine acidification level of the PDE3A gene in AML samples. This suggests that dysregulation of pseudouridine acidification at these sites may be functionally associated with the biological characteristics of acute myeloid leukemia (AML).

[0079] To explore the potential functional relationships among genes with altered pseudouridine sites in AML, a protein-protein interaction (PPI) network was constructed using a set of differentially pseudouridine-treated genes (e.g., Figure 11 (As shown). Nodes represent proteins, with node size proportional to their degree, and edges represent known or predicted associations in the STRING database. The network contains multiple highly connected nodes and shows significant connectivity between ribosome-related proteins (e.g., RPS3 and RPL17) and gene clusters related to mitochondrial function and metabolism (e.g., MT-ND4 and ACADM). Furthermore, multiple RNA-related factors are present in the network, suggesting that genes affected by pseudouridine remodeling in AML may be involved in pathways such as translation, mitochondrial processes, and RNA regulation. The PPI network collectively provides a network view of the potential interaction structures of Ψ-related genes in AML and offers a framework for prioritizing candidate genes for subsequent functional studies.

[0080] The potential of Ψ modification levels of DPP9 and PDE3A in differentiating between AML and non-AML patients was further evaluated. Receiver operating characteristic (ROC) curve analysis determined the optimal Ψ modification thresholds for DPP9 and PDE3A to be 0.2 and 0.3, respectively, with corresponding areas under the curve (AUC) values ​​of 84.8% and 84.2% (e.g., 0.2% and 0.3% respectively). Figure 10 (As shown in B in the figure). These results support the potential application value of gene-specific Ψ levels as a diagnostic feature of AML. Furthermore, significant Ψ alterations were also detected in other leukemia-related genes, including TAF1D and RPS3, which play important roles in leukemia development. The performance of these Ψ-modified genes (quantified by AUC values) ranged from 69.1% to 75.9% (e.g., as shown in B in the figure). Figure 12 (As shown).

[0081] Example 5 Risk assessment of Ψ-modified noncoding RNA in acute myeloid leukemia.

[0082] To evaluate the potential of Ψ-modified non-coding RNAs (ncRNAs) as diagnostic biomarkers for AML, this example compared the Ψ levels (quantified as deletion rate) of annotated ncRNA sites in AML and control samples. Significant differences were observed in the Ψ levels of four ncRNAs, including SNORD59A, FP236383.1, RNU2-6P, and SNORD14C (e.g., SNORD59A, FP236383.1, RNU2-6P, and SNORD14C). Figure 13 (As shown in A in the figure). Analysis of these candidate sites revealed site-specific bidirectional changes in Ψ levels. The mean Ψ modification level of SNORD59A increased from 41% in the control sample to 53% in AML, and the mean Ψ modification level of FP236383.1 increased from 44% to 58%. In contrast, the expression level of RNU2-6P decreased from 42% to 26%, while the expression level of SNORD14C decreased from 30% to 19%. These bidirectional changes highlight the site-specific remodeling of pseudouridine modification in AML.

[0083] To assess the diagnostic potential of these pseudouridine modification sites, receiver operating characteristic (ROC) curve analysis was employed. All four sites demonstrated strong discriminatory ability in distinguishing AML from normal samples, with AUC values ​​of 87.1%, 86.6%, 85.9%, and 82.6% for SNORD59A, FP236383.1, RNU2-6P, and SNORD14C, respectively (e.g., 87.1%, 86.6%, 85.9%, and 82.6%). Figure 13 (As shown in B in the figure). These results indicate that the level of pseudouridine modification at these non-coding RNA sites has the sensitivity and specificity to distinguish AML from normal controls.

[0084] This invention ultimately screened at least one of six genes: PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P. The pseudouridine modification level of the RNA molecules corresponding to these genes demonstrated sensitivity and specificity in distinguishing AML from normal controls. Figure 14As shown, when the pseudouridine modification level of the RNA molecule corresponding to the PDE3A gene is higher than 0.3, the subject is identified as a high-risk individual for acute myeloid leukemia (AML); when the pseudouridine modification level of the RNA molecule corresponding to the DPP9 gene is higher than 0.2, the subject is identified as a high-risk individual for AML; when the pseudouridine modification level of the RNA molecule corresponding to the SNORD59A gene is higher than 0.4, the subject is identified as a high-risk individual for AML; when the pseudouridine modification level of the RNA molecule corresponding to the FP236383.1 gene is higher than 0.5, the subject is identified as a high-risk individual for AML; when the pseudouridine modification level of the RNA molecule corresponding to the SNORD14C gene is higher than 0.3, the subject is identified as a high-risk individual for AML; and when the pseudouridine modification level of the RNA molecule corresponding to the RNU2-6P gene is higher than 0.3, the subject is identified as a high-risk individual for AML.

[0085] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. The application of RNA pseudouridine modification in the preparation of in vitro detection products for acute myeloid leukemia, characterized in that, The in vitro diagnostic product is used to detect the pseudouridine modification level of RNA molecules corresponding to at least one of the genes PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P in vitro samples derived from the subject, and to assess whether the subject has acute myeloid leukemia or the risk of having acute myeloid leukemia based on the pseudouridine modification level.

2. The application according to claim 1, characterized in that, The RNA is a combination of at least two of the RNA molecules selected from the PDE3A gene, DPP9 gene, SNORD59A gene, FP236383.1 gene, SNORD14C gene and RNU2-6P gene.

3. The application according to claim 1 or 2, characterized in that, The pseudouridine modification sites of the PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P genes are as follows: Located within the PDE3A gene, it corresponds to position 20551493 on chromosome 12 of the human reference genome GRCh38 version, and is located at nucleotide 182249 downstream of the start of the PDE3A gene sequence. This specific site corresponds to nucleotide 101 in the sequence shown in SEQ ID NO:

1. Located within the DPP9 gene, it corresponds to position 4724081 on chromosome 19 of the human reference genome GRCh38 version, and is located at nucleotide 593 downstream of the start of the DPP9 gene sequence. This specific site corresponds to nucleotide 101 in the sequence shown in SEQ ID NO:

2. Located within the SNORD59A gene, it corresponds to position 56645072 on chromosome 12 of the human reference genome GRCh38 version, and is located at the 30th nucleotide downstream of the start of the SNORD59A gene sequence. This specific site corresponds to the 30th nucleotide in the sequence shown in SEQ ID NO:

3. Located within the FP236383.1 gene, it corresponds to position 8401487 on chromosome 21 of the human reference genome GRCh38 version, and is located at nucleotide 20845 downstream of the start of the FP236383.1 gene sequence. This specific site corresponds to nucleotide 101 in the sequence shown in SEQ ID NO:

4. Located within the SNORD14C gene, it corresponds to position 123059374 on chromosome 11 of the human reference genome GRCh38 version, and is located at the 49th nucleotide downstream of the start of the SNORD14C gene sequence. This specific site corresponds to the 49th nucleotide in the sequence shown in SEQ ID NO:

5. Located within the RNU2-6P gene, it corresponds to position 46374500 on chromosome 13 of the human reference genome GRCh38 version, and is located at the 91st nucleotide downstream of the start of the SNORD14C gene sequence. This specific site corresponds to the 91st nucleotide in the sequence shown in SEQ ID NO:

6.

4. The application according to claim 1 or 2, characterized in that, The pseudouridine modification level of the RNA is the proportion of pseudouridine at a specific site on the mRNA, tRNA, or non-coding RNA of the gene.

5. The application according to claim 1 or 2, characterized in that, The ex vivo sample is selected from blood samples or bone marrow samples, and the blood sample includes serum, plasma or peripheral blood.

6. The application according to claim 1 or 2, characterized in that, The assessment is based on a preset threshold. When the pseudouridine modification level of the RNA molecule corresponding to at least one of the genes selected from PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P is higher than the preset threshold, the subject is determined to be a high-risk group for acute myeloid leukemia.

7. The application according to claim 6, characterized in that, The preset threshold is determined through subject operating curve analysis. The preset threshold is the value corresponding to the point that maximizes the sum of sensitivity and specificity, and the area under the curve (AUC) of the evaluation model established based on the preset threshold is not less than 0.

8.

8. The application according to claim 1 or 2, characterized in that, The in vitro diagnostic products are used for early screening, subtype classification, efficacy monitoring, or relapse risk assessment of acute myeloid leukemia.

9. An in vitro detection method for acute myeloid leukemia, characterized in that, Includes the following steps: Provide ex vivo samples derived from the subjects; RNA was extracted from the in vitro sample; The pseudouridine modification level of RNA molecules corresponding to at least one of the genes PDE3A, DPP9, SNORD59A, FP236383.1, SNORD14C, and RNU2-6P in the in vitro sample was detected. The risk of acute myeloid leukemia in the subjects was assessed based on the level of pseudouridine modification. When the pseudouridine modification level of the RNA molecule corresponding to the PDE3A gene is higher than 0.3, the subject is identified as a high-risk group for acute myeloid leukemia. And / or when the pseudouridine modification level of the RNA molecule corresponding to the DPP9 gene is higher than 0.2, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the SNORD59A gene is higher than 0.4, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the FP236383.1 gene is higher than 0.5, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the SNORD14C gene is higher than 0.3, the subject is determined to be a high-risk group for acute myeloid leukemia; And / or when the pseudouridine modification level of the RNA molecule corresponding to the RNU2-6P gene is higher than 0.3, the subject is determined to be a high-risk group for acute myeloid leukemia.

10. An in vitro diagnostic kit for acute myeloid leukemia, characterized in that, The kit contains a reagent for detecting the level of RNA pseudouridine modification in the gene described in any one of claims 1-3.

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