A marker for the classification of olfactory neuroblastoma subtypes and its application

Abstract

This application relates to the field of disease diagnosis, and specifically discloses a marker for the subtype classification of olfactory neuroblastoma. The marker includes a basal type marker, a neural type marker, and a mesenchymal type marker. The gene expression profiles used in this application are derived from high-precision single-cell sequencing, with high accuracy and discrimination, and can be projected onto ordinary transcriptome sequencing with relatively simple sequencing steps and lower costs to obtain the classification conclusion. Therefore, it is conducive to verification and promotion within a certain range, helps to classify ONB patients in clinical work, and assists in the selection of corresponding drug treatments according to the molecular characteristics of each subtype.

Description

Technical Field

[0001] This specification relates to the field of disease diagnosis, and particularly to a marker for the subtype classification of olfactory neuroblastoma and its application. Background Art

[0002] (I) Brief Introduction to the Clinical Features of Olfactory Neuroblastoma

[0003] Olfactory neuroblastoma (ONB) is a malignant tumor that occurs in the olfactory region of the anterior cranial base, accounting for about 3% - 6% of all nasal and sinus malignant tumors and 0.3% of all upper respiratory tract malignant tumors. The incidence of ONB is approximately 0.04 / 100,000 people per year, and the incidence of ONB has shown an upward trend in recent years. Although its exact location and mechanism of occurrence are not yet fully clear, ONB is generally considered to originate from the sensory neurons of the olfactory epithelium.

[0004] In past studies, some scholars have explored the staging methods of olfactory neuroblastoma. However, since ONB is a rare naso - cranial base tumor, limited by the sample size, the relevant research has progressed slowly, and there is no internationally unified standard for its clinicopathological grading system. Currently, the modified Kadish staging (Foote staging), proposed by Kadish et al. in 1976 and modified by Foote et al. in 1993, is the most commonly used ONB staging system in clinical practice. In addition, the Hyams pathological grading system, based on the differentiation level of ONB and first reported by Hyams et al. in 1989, is based on the histological characteristics of ONB.

[0005] Existing literature reports have shown that the prognosis of ONB is related to its clinical stage and pathological grade. The 5 - year survival rate of Kadish stage A tumors can be 75% - 90%, while that of Kadish stage C tumors is only 45%; the 5 - year survival rate of tumors with high Hyams grade is only 25%, while that of low - stage tumors can be as high as 80%. There are significant differences in the prognosis of ONB cases under different pathological morphological classifications, indicating that olfactory neuroblastoma is a highly heterogeneous tumor type. Different tumor individuals under the same pathological diagnosis show differences in morphological characteristics, molecular pathological expression, invasion range, etc., resulting in significant differences in the treatment mode, treatment efficiency, clinical outcome, etc. of different types of ONB patients. This clinical situation reflects the lack of an effective classification theory and a recognized staging system for ONB, resulting in objective difficulties in formulating treatment plans and disease guidelines.

[0006] (II) Current Research Status of the Tumor Origin and Classification of Olfactory Neuroblastoma

[0007] In the olfactory epithelium (OE), neurogenesis is a dynamic process that persists throughout adulthood. The OE contains multiple cell types, including horizontal basal cells (HBCs), globose basal cells (GBCs), immediate neuronal precursors (INPs), immature and mature olfactory receptor neurons (iORNs & mORNs), non-neuronal microvillar (MVs) cells, sustentacular cells (SUSs), and ducts of submucosal Bowman's glands (BGs). As a rare sinonasal malignancy, olfactory neuroblastoma (ONB) has been generally considered to originate from the olfactory cell components of the OE in recent years and has been initially confirmed to express some marker genes of immature olfactory neurons.

[0008] After Trojanowski et al. observed neurofilament structures in ONB tumor cells using the then-advanced electron microscopy technique in 1982 and published this result in the New England Journal that year, researchers generally began to accept the hypothesis that ONB originated from olfactory epithelial neurons. However, although the hypothesis that ONB originates from the olfactory mucosa has been proposed for nearly half a century, relatively few studies have been published on which specific level of the olfactory neuron development process ONB may specifically originate from.

[0009] In 2018, Classe et al. reported a multi-omics study that included whole exome sequencing (WES), bulk RNA seq sequencing, and DNA methylation sequencing data of tumor tissues from a cohort of 18 ONB cases. At the level of bulk mRNA seq data, the authors used analysis techniques such as unsupervised clustering to classify ONB into a Neural type with better differentiation and expression of neurodevelopmental marker molecules, and a Basal type with poorer differentiation and upregulation of cell cycle-related gene expression. By comparing the bulk RNA seq data of olfactory neuroblastoma with the olfactory neuron subsets in the olfactory mucosa defined by single-cell sequencing, the researchers found that the Basal subtype was similar to the globular basal cells (GBCs) of the normal olfactory mucosa in terms of the expression of RNA transcription genes, and the Neural type was more similar to the more mature direct neuronal progenitor cells (INPs), immature olfactory mucosal sensory neurons (iORNs), and mature olfactory mucosal sensory neurons (mORNs) during the development of the olfactory mucosa. Thus, for the first time, this study pointed out the high tumor heterogeneity of ONB through high-throughput sequencing technology and related analyses, and first proposed the binary classification hypothesis of ONB.

[0010] In May 2024, Finlay et al. published the results of a single-cell sequencing study on the tumor heterogeneity of ONB and the similarity between ONB and small cell lung cancer (SCLC) in the Cancer Cell, a sub-journal of the Cell magazine. The study demonstrated that ONB originated from the GBC layer of the olfactory epithelium, and ONB exhibited heterogeneity in cell fate and could mimic the normal GBC developmental trajectory. Through lineage tracing and scRNA transcriptomics studies, the authors determined that ONB was similar to SCLC, and mouse and human ONB showed mutually exclusive NEUROD1 (neural differentiation) and pou2f3 (mesenchymal differentiation)-like states. This study further explored the cell origin and tumor molecular typing of ONB and proposed possible hypotheses. Summary of the Invention

[0011] The present application provides a marker for the classification of olfactory neuroblastoma subtypes, and the marker includes a basal subtype marker, a neural subtype marker, and a mesenchymal subtype marker; the basal subtype marker includes at least one of the following genes or their fragments: UBE2C, HMGB2, CENPF, NNAT, HIST1H4C, HIST1H1A, TUBA1B, PTTG1, TOP2A, NUSAP1, HIST1H1B, CCNB1, UBE2S, BIRC5, CKS1B, CKS2, TPX2, H2AFZ, PCP4, CDK1, MFAP4, MKI67, PBK, MAD2L1, HMGB1, CKAP2, CCNB2, SMC4, CENPW, HIST1H1D, UBE2T, CDKN3, ASPM, TUBA1C, TYMS, DLGAP5, PCLAF, PRC1, NUF2, ARL6IP1, TMPO, CDC20, KPNA2, HMGN2, DTYMK, HIST1H1E, HIST1H1C, MDK, HIST1H3B, H2AFX; the neural subtype marker includes at least one of the following genes or their fragments: CRABP1, SCG5, PEG10, MAP1B, GNG8, CIB2, STMN2, PCSK1N, CHGB, RTN1, MIR7-3HG, SNRPN, EEF1A2, MEG3, GRP, SEC11C, NHLH1, KIF19, KCNK9, APMAP, TLCD3B, UNCX, CALB2, BEX1, IRX2, PEBP1, RGS10, CIRBP, VAMP2, FXYD3, KLHL35, MAP1LC3A, BEX2, NCAM1, GADD45B, NEUROD1, FXYD6, ATP6V0E2, C11orf96, CAMK2N1, C5orf38, CPE, RPS3, TMPRSS6, DUSP26, PDLIM1, STX1A, FABP6, KCTD17, SPOCK2;The mesenchymal markers include at least one of the following genes or their fragments: SLPI, S100A6, WFDC2, MT1X, MGP, CRYAB, S100A11, SAT1, CCN2, IGFBP7, VMO1, APOE, IER3, IGFBP5, S100A4, ANXA2, S100A10, VIM, MT2A, CD9, IFI27, LGALS1, LYPD2, TIMP1, IFITM3, ITGB1, LGALS3, CALD1, KRT18, SPARC, COL11A1, COL18A1, CEBPD, CSTB, CD59, APLP2, ID3, PTN, COL3A1, CCN1, KRT8, DST, TPM4, CYBA, ALDH1A1, CLU, IFITM2, CD63, TPM2, ZFP36L1.;

[0012] The present application also provides the use of the above-mentioned marker or its analyte in the preparation of a product for classifying olfactory neuroblastoma subtypes.

[0013] The present application also provides a product for classifying olfactory neuroblastoma subtypes, and the product includes the genes of the above-mentioned markers and / or their analytes.

[0014] The present application also provides an olfactory neuroblastoma subtype detection device, and the olfactory neuroblastoma subtype detection device includes the following modules: an information acquisition module for providing sequencing information of target markers of a sample to be tested, where the target markers are the markers for classifying olfactory neuroblastoma subtypes as described above; a scoring module for scoring the subtype based on the sequencing information of the target markers of the sample to be tested; and a judgment module for judging whether the olfactory neuroblastoma subtype is a basal type, a neural type or a mesenchymal type based on the score of the subtype.

[0015] The present application also provides a computer-readable storage medium, and the storage medium stores computer instructions, which when executed by a processor, implement a method for detecting olfactory neuroblastoma subtypes, and the method includes: acquiring sequencing information of target markers of a sample to be tested, where the target markers are the markers for classifying olfactory neuroblastoma subtypes as described above; scoring the subtype based on the sequencing information of the target markers of the sample to be tested; and judging whether the olfactory neuroblastoma subtype is a basal type, a neural type or a mesenchymal type based on the score of the subtype.

[0016] The present application also provides an electronic terminal, which includes: a processor, a memory, an input / output interface, and a communication port; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes the method for detecting the subtypes of olfactory neuroblastoma in the above-mentioned computer-readable storage medium.

[0017] The beneficial effects brought by the present application include but are not limited to: The present application first proposed a three-subtype concept for a rare tumor, olfactory neuroblastoma (ONB). From the perspectives of gene expression and molecular typing, ONB cases are divided into basal type, neural type, and mesenchymal type, and the gene expression profiles and molecular functional pathways of each subtype are described, which promotes the understanding of ONB subtypes in related fields. In this process, the present application newly discovered a Mesenchymal type ONB that expresses mesenchymal cell-related characteristics. Through single-cell sequencing technology, the molecular characteristics of mesenchymal type ONB were successfully identified and characterized. And based on the NBM ONB molecular characteristics obtained by single-cell sequencing, using existing open-source R code and program packages, an algorithm was developed, enabling the differentiation of the ONB three-subtype system discovered by single-cell sequencing in ordinary transcriptome sequencing samples with relatively low cost and less difficulty in popularization. The typing gene expression profile used in this technology is derived from high-precision single-cell sequencing, with high accuracy and discrimination, and can be projected onto ordinary transcriptome sequencing with relatively simple sequencing steps and low cost to obtain typing conclusions. Therefore, it is conducive to verification and popularization within a certain range, helps to classify ONB patients in clinical work, and assist in the selection of corresponding drug treatments according to the molecular characteristics of each subtype. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] The present application will be further described by way of exemplary embodiments, which will be described in detail through the drawings. These embodiments are not restrictive, where:

[0019] Figure 1For the tumor heterogeneity of ONB as shown in some embodiments of the present application, a) The UMAP plot shows 7 subpopulations after reclustering of ONB malignant epithelial cells, and the cell cycle score of each cell is calculated using a gene list related to the cell cycle; b) The UMAP describes the characteristic scores of the classical Basal-type and Neural-type ONB in tumor cells; c) The correlation between 40 NMF modules generated from 10 ONB tumor datasets; hierarchical clustering identifies 5 gene modules representing tumor commonalities; d) The bar chart shows the representative GO pathways enriched in each NMF module; e) The violin plot shows the expression scores of 5 NMF modules in 7 tumor subpopulations (from top to bottom: Basal, Neural, Mes-1, Mes-2, Ciliation); f) The UMAP plot shows the annotated phenotypes of 7 ONB tumor subpopulations; g) The stacked bar chart shows the proportion of cells in each tumor subpopulation found in each ONB sample; h) The heat map shows the representative GSVA pathways enriched in ONB tumor subpopulations except the ciliated subpopulation.

[0020] Figure 2 To characterize three subtypes of ONB based on scRNA-seq analysis as shown in some embodiments of the present application, a) The ternary plot depicts the NBM Scores (Neural / Basal / Mesenchymal scores) of each ONB tumor cell and the NBM scores of tumor cells in 10 ONB tumor datasets involved in the study; b) Project the scRNA-seq NBM subtype features onto the bulk RNA seq ONB patient study set cohort containing 20 samples. Upper heat map: Clinical characteristics of all ONB patients, including modified Kadish stage, Dulguerov stage, Hyams grade, and orbital invasion degree, are represented by different colors. Lower heat map: A heat map showing the expression of each gene in the NBM ONBgene list signature gene set (Appendix 1) for each ONB patient; c) Project the scRNA-seq NBM subtype features onto the bulk RNA seq ONB patient validation set cohort containing 18 samples (GSE118995).

[0021] Figure 3Characterization of three subtypes of ONB based on scRNA-seq analysis as shown in some embodiments of the present application. a) Project the scRNA-seq NBM subtype features onto a cohort of a bulk RNA seq ONB patient study set containing 20 samples. Lower heatmap: shows the scores of Neural / Basal / Mesenchymal subtype features calculated by the AddModuleScore() function for the TPM matrix of 20 ONB patients; b) Flowchart of the ONB NBM three-subtype method based on the gene expression profile obtained from single-cell sequencing.

[0022] Figure 4 The efficacy of predicting three subtypes of ONB by the scoring system as shown in some embodiments of the present application. From left to right, the AUC values of the Basal Score, Neural Score, and Mesenchymal Score for each subtype of ONB predicted by the scoring system are 1, 0.96, and 0.95, respectively.

[0023] Figure 5 To explore the similarity and origin speculation between the olfactory epithelial (OE) cell subsets and ONB tumor cells as shown in some embodiments of the present application. a) UMAP plot shows the distribution of OE cell subsets in normal adults, including horizontal basal cells (HBCs), globose basal cells (GBCs), immediate neuronal progenitors (INPs), immature olfactory neurons (iORNs), mature olfactory neurons (mORNs), immature sustentacular cells (iSus), and mature sustentacular cells (mSus) subsets; b) Violin plot centrally shows the expression levels of classical marker genes in olfactory neuron and sustentacular cell subsets; c) Two-dimensional representation of the single-cell gene expression profile based on principal component analysis. Slingshot predicts an early bifurcation of the differentiation trajectories of neurons and sustentacular cells; d) Heatmap shows the Pearson correlation between the scRNA expression profiles of ONB malignant subsets (columns) and olfactory epithelial cells (rows), and the olfactory epithelial cells (rows) are arranged in the order of differentiation of neuronal and sustentacular cell lineages; e) Heatmap characterizes the subset positions enriched with NBM ONB features in normal OE subsets; f) Featureplot characterizes the subset positions enriched with NBM ONB features in normal OE subsets.

[0024] Figure 6 Module diagram of an olfactory neuroblastoma subtype detection device as shown in some embodiments of the present application.

[0025] Figure 7 Flowchart of a method for detecting olfactory neuroblastoma subtypes as shown in some embodiments of the present application.

[0026] Figure 8Schematic diagram of the architecture of the electronic terminal 700 shown in some embodiments of the present application.

[0027] Figure 9 Differentially expressed genes among neuroblast / basal / mesenchymal ONB tumor cells shown in some embodiments of the present application. Detailed implementation manners

[0028] To more clearly illustrate the technical solutions of the embodiments of this specification, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are only some examples or embodiments of this specification. For those of ordinary skill in the art, without creative efforts, this specification can also be applied to other similar scenarios based on these drawings. Unless obvious from the language context or otherwise stated, the same reference numerals in the figures represent the same structure or operation.

[0029] As shown in this specification and the claims, unless the context clearly indicates an exceptional situation, words such as "a", "an", "one", and / or "the" are not specifically singular and may also include plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of the clearly identified steps and elements, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0030] Flowcharts are used in this specification to illustrate the operations performed by the systems according to the embodiments of this specification. It should be understood that the previous or subsequent operations are not necessarily executed precisely in sequence. On the contrary, they can be executed in reverse order or simultaneously. At the same time, other operations can also be added to these processes, or one or several steps can be removed from these processes.

[0031] The present application provides a marker for the subtype classification of olfactory neuroblastoma, and the marker includes a basal subtype marker, a neural subtype marker, and a mesenchymal subtype marker; the basal subtype marker includes at least one of the following genes or their fragments: UBE2C, HMGB2, CENPF, NNAT, HIST1H4C, HIST1H1A, TUBA1B, PTTG1, TOP2A, NUSAP1, HIST1H1B, CCNB1, UBE2S, BIRC5, CKS1B, CKS2, TPX2, H2AFZ, PCP4, CDK1, MFAP4, MKI67, PBK, MAD2L1, HMGB1, CKAP2, CCNB2, SMC4, CENPW, HIST1H1D, UBE2T, CDKN3, ASPM, TUBA1C, TYMS, DLGAP5, PCLAF, PRC1, NUF2, ARL6IP1, TMPO, CDC20, KPNA2, HMGN2, DTYMK, HIST1H1E, HIST1H1C, MDK, HIST1H3B, H2AFX; the neural subtype marker includes at least one of the following genes or their fragments: CRABP1, SCG5, PEG10, MAP1B, GNG8, CIB2, STMN2, PCSK1N, CHGB, RTN1, MIR7-3HG, SNRPN, EEF1A2, MEG3, GRP, SEC11C, NHLH1, KIF19, KCNK9, APMAP, TLCD3B, UNCX, CALB2, BEX1, IRX2, PEBP1, RGS10, CIRBP, VAMP2, FXYD3, KLHL35, MAP1LC3A, BEX2, NCAM1, GADD45B, NEUROD1, FXYD6, ATP6V0E2, C11orf96, CAMK2N1, C5orf38, CPE, RPS3, TMPRSS6, DUSP26, PDLIM1, STX1A, FABP6, KCTD17, SPOCK2;The mesenchymal markers include at least one of the following genes or their fragments: SLPI, S100A6, WFDC2, MT1X, MGP, CRYAB, S100A11, SAT1, CCN2, IGFBP7, VMO1, APOE, IER3, IGFBP5, S100A4, ANXA2, S100A10, VIM, MT2A, CD9, IFI27, LGALS1, LYPD2, TIMP1, IFITM3, ITGB1, LGALS3, CALD1, KRT18, SPARC, COL11A1, COL18A1, CEBPD, CSTB, CD59, APLP2, ID3, PTN, COL3A1, CCN1, KRT8, DST, TPM4, CYBA, ALDH1A1, CLU, IFITM2, CD63, TPM2, ZFP36L1.;

[0032] In some embodiments, the olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neural olfactory neuroblastoma, and mesenchymal olfactory neuroblastoma. In some embodiments, the basal olfactory neuroblastoma subgroup highly expresses cell proliferation and cell cycle pathways relative to the neural olfactory neuroblastoma subgroup and the mesenchymal olfactory neuroblastoma subgroup. In some embodiments, the neural olfactory neuroblastoma subgroup has the functions of neurogenesis and olfactory transduction, and the mesenchymal olfactory neuroblastoma subgroup has cell functions including angiogenesis, epithelial-mesenchymal transition, extracellular matrix remodeling, inflammatory response, and chemokine secretion.

[0033] The present application also provides the use of the above-mentioned markers or their detection substances in the preparation of products for classifying olfactory neuroblastoma subtypes.

[0034] In some embodiments, the detection substance can be selected from any one or more of antibodies, membrane strips, chips, probes, or primer pairs.

[0035] As used herein, the term "primer" refers to a naturally occurring oligonucleotide (such as a restriction fragment) or a synthetically produced oligonucleotide that can serve as a starting point for the synthesis of a primer extension product. When under appropriate conditions (such as buffer, salt, temperature, and pH) and in the presence of nucleotides and reagents for nucleic acid polymerization (such as DNA-dependent or RNA-dependent polymerase), the primer extension product is complementary to a nucleic acid strand (template or target sequence). Generally, a set of primers will consist of at least two primers, an "upstream primer" and a "downstream primer", which together define the amplicon (the sequence to be amplified using the primers).

[0036] The term "probe" refers to any molecule that can selectively bind to a target biomolecule (e.g., a nucleic acid sequence that hybridizes to the probe). In some embodiments, the probe can be labeled, e.g., with a fluorophore and a quencher. In some embodiments, the probe can be a Taqman probe with a fluorescent reporter group added to the 5' end and a fluorescent quencher group added to the 3' end.

[0037] An antibody is a protective protein produced by the body in response to the stimulation of an antigen. In some embodiments, the antibody can be used as a detection reagent to detect the expression of a gene.

[0038] The present application also provides a product for classifying subtypes of olfactory neuroblastoma, which product comprises the gene and / or its detection substance among the above-mentioned markers.

[0039] In some embodiments, the detection substance can be selected from any one or more of an antibody, a membrane strip, a chip, a probe or a primer pair.

[0040] The present application also provides a device for detecting subtypes of olfactory neuroblastoma, as Figure 6 shown, the device for detecting subtypes of olfactory neuroblastoma comprises the following modules: an information acquisition module 610, a scoring module 620, and a judgment module 630.

[0041] The information acquisition module 610 can be used to provide sequencing information of the target marker of the sample to be tested, and the target marker is the marker for classifying subtypes of olfactory neuroblastoma as described above. In some embodiments, the sequencing information can include single-cell RNA sequencing information and / or ordinary transcriptome RNA sequencing information.

[0042] In some embodiments, the sample to be tested can be a tumor tissue of a patient with olfactory neuroblastoma.

[0043] The term "sample" refers to any composition containing nucleic acids isolated from a subject. In some embodiments, the sample can be selected from at least one of blood, tissue, blood cells, bone marrow, ascites, fine needle biopsy sample, cell-containing body fluid, cell-free floating nucleic acid, sputum, saliva, urine, semen, cerebrospinal fluid peritoneal fluid, pleural fluid, feces, lymph, skin swab, oral swab, nasal swab or lavage. In some embodiments, preferably, the sample can be a tumor tissue excised from a patient with olfactory neuroblastoma.

[0044] The scoring module 620 can be used to score the subtype based on the sequencing information of the target marker of the sample to be tested.

[0045] In some embodiments, the scoring module obtains the basal, neural, and mesenchymal tumor characteristic scores of olfactory neuroblastoma patients based on the sequencing information of the target markers of the sample to be tested.

[0046] In some embodiments, the scoring module calculates the gene expression level of the target marker based on the sequencing information of the target marker of the sample to be tested, and obtains the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads of the gene expression level; further, each individual olfactory neuroblastoma case in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads is uniformly scored to obtain the basal, neural, and mesenchymal tumor characteristic scores of a single olfactory neuroblastoma case.

[0047] Fragments Per Kilobase of exon model per Million mapped fragments refers to the number of fragments of transcripts per thousand bases per million mapped reads.

[0048] Reads Per Kilobase per Million mapped reads (abbreviated as RPKM) represents the number of reads from a gene per thousand base lengths per million reads. RPKM is obtained by dividing the number of reads mapped to the gene by the total number of reads mapped to the genome (in millions) and the length of the RNA (in KB).

[0049] In some embodiments, the "CreateSeuratObject()" function of the R language package "Seurat" can be used to convert the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads into a data object for Seurat package operations. In some embodiments, the "AddModuleScore()" function of the Seurat package can be used to uniformly assign scores to each individual olfactory neuroblastoma case in the normalized expression matrix of ordinary transcriptome RNA sequencing information of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads. In some embodiments, the formula "Normalized Score = (x - min(x)) / (max(x) - min(x))" can be used to standardize the basal, neural, and mesenchymal tumor feature scores respectively, so that the assigned scores with discrete distributions are concentrated in the range of 0 to 1.

[0050] In some embodiments, after the sequencing information of the target marker has gone through necessary quality control, data cleaning, alignment and other conventional processes, the gene expression level can be calculated through the alignment results to obtain the TPM normalized expression matrix of the gene expression level. The specific steps are as follows: ① Quality control: First, the original sequencing data (Fastq format) needs to be quality-controlled. Usually, the R language package FastQC is used for preliminary quality inspection, and then the R language package Trimmomatic or other toolkits are used for quality trimming. ② Read alignment: The R language alignment toolkit (such as HISAT2, STAR, etc.) is used to align the quality-trimmed reads to the reference genome. ③ Data cleaning: The R language package Picard or samtools, etc. are used to mark and remove duplicate PCR reads, and tools such as StringTie or Cufflinks are used to perform transcriptome assembly on the SAM / BAM file to generate transcripts and estimate the expression level. The sequencing method of ordinary transcriptome bulk RNA-Seq is fragmentary, so it is necessary to read the fragment information and align and assemble it with the overall gene information of the genome to obtain the overall expression information of a single gene. The conventional bulk RNA sequencing process is usually composed of extraction steps, reverse transcription steps, PCR steps, etc. Sequencing bias will be generated in the above steps. The purpose of quality control and data cleaning is to eliminate the bias through statistical processing after the data is downloaded to improve the data quality and ensure the accuracy and scientificity of the subsequent analysis results.

[0051] A determination module 630 can be used to determine the subtype of olfactory neuroblastoma as basal, neural or mesenchymal based on the score of the subtype.

[0052] In some embodiments, the determination module 630 can determine the subtype of olfactory neuroblastoma according to the following steps: when the normalized basal tumor characteristic score ≥ 0.3 points, it is determined that the olfactory neuroblastoma is of the basal type; when the normalized basal tumor characteristic score < 0.3 points and the normalized neural tumor characteristic score ≥ 0.15 points, it is determined that the olfactory neuroblastoma is of the neural type; when the normalized basal tumor characteristic score < 0.3 points, the neural tumor characteristic score < 0.15 points, and the mesenchymal tumor characteristic score > 0 points, it is determined that the olfactory neuroblastoma is of the mesenchymal type.

[0053] The present application also provides a computer-readable storage medium, and the storage medium stores computer instructions. When the computer instructions are executed by a processor, a method for detecting the subtype of olfactory neuroblastoma is implemented. The flowchart of the method is as Figure 7As shown. In step S710, the sequencing information of the target biomarker of the sample to be tested can be obtained, and the target biomarker is the biomarker for olfactory neuroblastoma subtype classification as described above; in step S720, the subtype can be scored based on the sequencing information of the target biomarker of the sample to be tested; in step S730, it can be determined whether the olfactory neuroblastoma subtype is basal type, neural type or mesenchymal type based on the score of the subtype.

[0054] In some embodiments, the sequencing information may include single-cell RNA sequencing information and / or ordinary transcriptome RNA sequencing information.

[0055] In some embodiments, the sample to be tested may be the tumor tissue of an olfactory neuroblastoma patient.

[0056] In some embodiments, based on the sequencing information of the target biomarker of the sample to be tested, the basal type, neural type, and mesenchymal type tumor feature scores of an olfactory neuroblastoma patient can be obtained.

[0057] In some embodiments, based on the sequencing information of the target biomarker of the sample to be tested, the gene expression level of the target biomarker can be calculated to obtain a normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads of the gene expression level. In some embodiments, further, each individual olfactory neuroblastoma case in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads can be uniformly scored to obtain the basal type, neural type, and mesenchymal type tumor feature scores of a single olfactory neuroblastoma case.

[0058] In some embodiments, the "CreateSeuratObject()" function of the R language package "Seurat" can be used to convert the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads into a data object for Seurat package operations.

[0059] In some embodiments, the "AddModuleScore()" function of the Seurat package can be used to uniformly assign scores to each individual case of olfactory neuroblastoma in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads in the ordinary transcriptome RNA sequencing information.

[0060] In some embodiments, the formula "Normalized Score = (x - min(x)) / (max(x) - min(x))" can be used to standardize the basal, neural, and mesenchymal tumor feature scores respectively, so that the assigned scores with discrete distributions are concentrated in the range of 0 to 1.

[0061] The present application also provides an electronic terminal 800, which includes: a processor 810, a memory 820, an input / output interface 830, and a communication port 840; the memory 820 is used to store a computer program, and the processor 810 is used to execute the computer program stored in the memory, so that the terminal executes the method for detecting the subtype of olfactory neuroblastoma as described in the above computer-readable storage medium.

[0062] The processor 810 may execute computing instructions (program code) and perform the functions of the detection device 600 described in this application. The computing instructions may include programs, objects, components, data structures, procedures, modules, and functions (the functions refer to the specific functions described in this application). For example, the processor 810 may process the instructions for detecting the subtype of olfactory neuroblastoma in the olfactory neuroblastoma subtype detection device 600. In some embodiments, the processor 810 may include a microcontroller, a microprocessor, a reduced instruction set computer (RISC), an application specific integrated circuit (ASIC), an application specific instruction set processor (ASIP), a central processing unit (CPU), a graphics processing unit (GPU), a physics processing unit (PPU), a microcontroller unit, a digital signal processor (DSP), a field programmable gate array (FPGA), an advanced RISC machine (ARM), a programmable logic device, and any circuit and processor capable of performing one or more functions, etc., or any combination thereof. For illustration only, Figure 8 only one processor 810 is described herein, but it should be noted that this application may include multiple processors.

[0063] The memory 820 may store data / information obtained from any component in the olfactory neuroblastoma subtype detection device 600. In some embodiments, the memory 820 may include a mass storage, a removable storage, a volatile read and write memory, and a read only memory (ROM), etc., or any combination thereof. Exemplary mass storage may include a magnetic disk, an optical disk, and a solid state drive, etc. The removable storage may include a flash drive, a floppy disk, an optical disk, a memory card, a USB flash drive, a compact disk, and a portable hard disk, etc. The volatile read and write memory may include a random access memory (RAM). The RAM may include a dynamic RAM (DRAM), a double data rate synchronous dynamic RAM (DDR SDRAM), a static RAM (SRAM), a thyristor RAM (T-RAM), and a zero capacitor (Z-RAM), etc. The ROM may include a mask ROM (MROM), a programmable ROM (PROM), an erasable programmable ROM (PEROM), an electrically erasable programmable ROM (EEPROM), a CD-ROM, and a digital versatile disc ROM, etc.

[0064] The input / output interface 830 can be used to input or output signals, data, or information. In some embodiments, the input / output interface 830 can be used to implement the interaction behavior between a user (e.g., the person corresponding to the sample to be tested, the user of the olfactory neuroblastoma subtype detection device 600, etc.) and the processor 710. In some embodiments, the user can input the characteristic information of the person corresponding to the sample to be tested through the input / output interface 830. In some embodiments, the input / output interface 830 can include an input device and an output device. Exemplary input devices can include a keyboard, a mouse, a touch screen, a microphone, etc., or any combination thereof. Exemplary output devices can include a display device, a speaker, a printer, a projector, etc., or any combination thereof. Exemplary display devices can include a liquid crystal display (LCD), a light-emitting diode (LED)-based display, a flat panel display, a curved display, a television device, a cathode ray tube (CRT), etc., or any combination thereof.

[0065] The communication port 840 can be connected to a network for data communication. The connection can be a wired connection, a wireless connection, or a combination of both. Wired connections can include cables, optical fibers, telephone lines, etc., or any combination thereof. Wireless connections can include Bluetooth, WiFi, WiMax, WLAN, ZigBee, mobile networks (e.g., 3G, 4G, or 5G, etc.), etc., or any combination thereof. In some embodiments, the communication port 840 can be a standardized port, such as RS232, RS485, etc. In some embodiments, the communication port 840 can be a specially designed port.

[0066] In the experimental methods in the following embodiments, unless otherwise specified, they are all conventional methods. The test materials used in the following embodiments, unless otherwise specified, are all purchased from conventional biochemical reagent companies. In the following embodiments, for quantitative tests, three repeated experiments are set, and the results are averaged.

[0067] Example 1 - Study on the Characteristics of ONB Tumor Cell Subgroups

[0068] Single-cell RNA transcriptome sequencing (scRNA seq) technology can analyze relevant genetic information at the RNA expression level of single cells and construct a cell molecular expression map. In recent years, it has been widely used in the exploration of various tumor heterogeneities and the research on tissue development origins. In the research of this application, an attempt was made to explore the tumor heterogeneity and tumor typing of olfactory neuroblastoma (ONB) using scRNA sequencing technology.

[0069] To depict the diversity of ONB tumor cells, 24,686 malignant cells from 10 ONB tumor tissues were screened and re-clustered into 7 tumor subpopulations ( Figure 1a). According to the ONB multi-omics study published by Classe et al., the two known subtypes of ONB, namely the basal type and the neural type, can be verified in ONB single-cell data through the gene expression characteristics of the basal / neural markers provided in the study ( Figure 1 b); In addition, it was found that certain ONB tumor subsets (C4-C7) have a unique expression pattern that cannot be characterized by the gene markers of the known Neural / Basal subtypes ( Figure 1 b, Extended Data Figure 2 a).

[0070] Therefore, this application performed non-negative matrix factorization (NMF) analysis to investigate the expression characteristics of tumor heterogeneity within ONB, and obtained that ONB expresses 5 major gene modules ( Figure 1 c). Through GO enrichment pathway analysis, it can be concluded that the 5 gene modules represent different functions ( Figure 1 d). Therefore, ONB tumor subsets can be divided into 4 major functional categories ( Figure 1 e- Figure 1 f), namely the categories related to olfactory nerve development (Module 1; CHGB / HES6 / NEUROD1) and cell cycle (Module 2; MKI67 / TOP2A / UBE2C), which respectively reflect the expression characteristics of the known neural and basal ONB subtypes. Module 4 (CAPS / TPPP3 / PIFO) is associated with ciliary structure and motility. In addition, GO pathway enrichment analysis also revealed that 2 additional NMF modules (Module 3, NRG1 / WNT10A, Module 5, BMP7 / LAMA1) have mesenchymal cell characteristics.

[0071] The discovery of the "mesenchymal-like" ONB tumor subset has triggered further exploration of the internal heterogeneity of ONB tumors ( Figure 1 g). Through gene set variation analysis (GSVA, Figure 1 h), it was found that the basal-type ONB subset (Basal ONB) highly expresses cell proliferation and cell cycle pathways, the neural-type ONB subset (Neural ONB) has the functions of neurogenesis and olfactory transduction, while the newly defined mesenchymal-type subset (Mesenchymal ONB) has various cell functions including angiogenesis, epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, inflammatory response, and chemokine secretion, ( Figure 1 h).

[0072] Subsequently, the present application calculated the differentially expressed genes (DEGs) among neural / basal / mesenchymal (NBM) ONB tumor cells, and the results are as Figure 9 shown, and the top 50 upregulated DEGs in terms of expression level were used to evaluate the tumor feature score in each ONB malignant cell (see Appendix 1).

[0073] Example 2 - Discovery of Neural / Basal / Mesenchymal Subtypes of ONB Tumors

[0074] Neural, Basal, and Mesenchymal type ONB tumor cells may exist in a mixed state in the overall ONB tumor sample. To further clarify the distribution of this mixed cell state, first, a gene set consisting of the top 50 genes in terms of the expression level of the differentially expressed genes among neural / basal / mesenchymal (NBM) ONB tumor cells, a total of 150 genes, was used as the gene set (NBM ONB genelist) that can represent the molecular characteristics of NBM type ONB. Using the "AddModuleScore()" function in the Seurat package of R language, the Neural, Basal, and Mesenchymal type feature scores (Neural / Basal / Mesenchymal Scores) of each ONB tumor cell were calculated using this gene set. Subsequently, a ternary plot was drawn, and each ONB tumor cell was placed in the plot according to the relative value of its respective NBM Score, and different categories (neural / basal / mesenchymal cells) were marked with different colors ( Figure 2 a). Generally speaking, the ternary plot confirmed the three-part structure of the ONB tumor cell phenotype and at the same time indicated that these 150 differentially expressed genes can be used for typing. Furthermore, when the ternary plot pictures of individual patients were shown separately to observe the specific composition of NBM cells in each patient in detail, it was found that Neural, Basal, and Mesenchymal type cells tended to be enriched in different tumor individuals respectively, thus showing 3 macroscopically distinguishable tumor typing patterns ( Figure 2a), it can be found that Basal-type tumor cells are only present in 5 cases numbered ONB-946, ONB-311, ONB-548, ONB-599, ONB-983, etc., and in the distribution patterns of tumor cells in these patients, Neural, Basal, and Mesenchymal-type tumor cells always exist; while in 4 cases numbered ONB-764, ONB-288, ONB-199, ONB-860, etc., the distribution patterns of tumor cells in patients show a state where only Neural and Mesenchymal-type tumor cells exist; particularly, in the case numbered ONB-733, only Mesenchymal-type tumor cells exist. The above distribution patterns of tumor cells suggest that there are three classification states in ONB tumor patients mainly characterized by Basal-type, Neural-type, and Mesenchymal-type tumor cells respectively, and there is a determination priority of Basal-type > Neural-type > Mesenchymal-type for tumor type determination, which can be characterized by the expression Score of ONB NBM three-classification respectively.

[0075] To verify this finding, a bulk RNA-seq case cohort (HRA007322) consisting of 20 ONB patients who underwent surgical resection was used as the discovery cohort to further explore the clinical classification of ONB. The gene sets (NBM ONB gene list) of the Neural / Basal / Mesenchymal (NBM) ONB molecular characteristics of the 20 patients in the discovery cohort were pulled to form a matrix, and semi-supervised clustering was performed. The results showed that the 20 ONB patients could be divided into 3 main subgroups through different patterns of the expression levels of the NBM ONB gene list ( Figure 2 b). The characteristics of two groups of patients can be respectively characterized by classical Neural-type and Basal-type gene markers. However, after sorting the samples according to the expression of the NBM ONB gene list, it was found that another group of tumors (N = 4) separately expressed Mesenchymal-type tumor characteristics. This result indicates that there is a third subtype of ONB that expresses Mesenchymal-type stromal characteristics.

[0076] Subsequently, the bulk RNA-seq cohort (GSE118995) containing 18 ONB patients disclosed by Classe et al. (Classe M, Yao H, Mouawad R, et al. Integrated Multi-omic Analysis of Esthesioneuroblastomas Identifies Two Subgroups Linked to Cell Ontogeny[J]. Cell Rep, 2018;25(3):811-21.e5.) was used as the external validation cohort, and the NBM ONB gene list gene set was used as the marker gene for clustering. After semi-supervised clustering, consistent results with those observed in the study cohort were obtained, that is, there are three types of ONB tumor individuals, mainly expressing the gene marker characteristics of neural / basal / mesenchymal (NBM) ONB. This step used external data to verify the generalizability of the ONB three-classification theory ( Figure 2 c). Finally, since the newly discovered ONB subtype was enriched with the marker genes of mesenchymal-like cells, we named this previously unclarified new ONB subtype as the mesenchymal type.

[0077] Example 3 - Establishment of the method for defining the Neural / Basal / Mesenchymal subtypes of ONB tumors: Based on bulk RNA seq sequencing data

[0078] Single cell RNA sequencing (scRNA-seq) is a high-throughput experimental technique for quantifying the gene expression profiles of specific cell populations at the single cell level using RNA sequencing. It can effectively analyze heterogeneous systems in early developmental tissues or complex tissues (such as tumor tissues, etc.), but has disadvantages such as cumbersome sample submission and sequencing processes and high costs. Ordinary transcriptome RNA sequencing (bulk RNA seq) sequences samples composed of cell mixtures. Although it can only estimate the average expression level of genes in the cell population, the sequencing steps are relatively simple and the cost is low, which is conducive to verifying and promoting the conclusions of scRNA sequencing within a certain range.

[0079] Therefore, in further research of this application, a method was developed to project the olfactory neuroblastoma NBM subtype scoring system established by the above-mentioned single cell scRNA sequencing analysis onto bulk RNAseq sequencing samples ( Figure 3a). In this part of the work, after the sequencing data of 23 ONB bulk RNA seq cases in the research cohort were integrated routinely after sequencing, subsequent analysis was performed in the form of a TPM matrix. Using the "CreateSeuratObject()" function of the R language package "Seurat", the TPM matrix can be converted into a data object that the Seurat package can operate on. Using the total of 3 groups and 150 genes (50 genes in each group) in the NBM ONB gene list described above as the gene set used for scoring, the "AddModuleScore()" function of the Seurat package was used to uniformly score each ONB case individual in the bulk RNA seq TPM matrix, obtaining the Neural type (neural type), Basal type (basal type), and Mesenchymal type (mesenchymal type) tumor feature scores (Neural / Basal / Mesenchymal Scores, NBM Scores) of a single ONB case. In the research cohort, the expression pattern of the NBM Scores of the ONB bulk RNA seq cohort calculated using the above method was similar to the three-phase diagram of the NBM Score of the scRNA ONB single-cell cohort Figure 2 observed in a). The present application notes that most basal ONB samples are also enriched with relatively high Neural Score and Mesenchymal Score; ONB patients with the neural type may also have a relatively high Mesenchymal Score, but a relatively low Basal Score; while in ONB patients with the mesenchymal type, the tumor shows a pure high expression of the mesenchymal type score, with relatively low Basal Score and Neural Score. This indicates that mesenchymal ONB - this unique new subtype of ONB is characterized by both a high mesenchymal type feature score and double-negative expression of neural type and basal type features. The present application notes that the findings of the present application also change the previous understanding of the classical neural type / basal type ONB binary classification, that is, the determination of basal ONB has priority compared to neural type ONB. The results obtained by detecting the same sample using two methods (bulkRNA seq sequencing and scRNA-seq sequencing) are consistent.

[0080] In the above steps, the scoring rules for uniformly scoring each ONB case individual in the bulk RNA seq TPM matrix are as follows:

[0081] Principle of the AddModuleScore() function in the R package "Seurat": The genes of interest to the researcher are extracted from the expression matrix, and the average expression of these genes is calculated for each data individual. The average value of the background genes is used to find the bin where each gene is located, and genes are randomly selected as the background within that bin. Finally, the average value of all target genes is calculated, and the average value of all background genes is calculated, and the difference between the two is the Score value corresponding to the gene list input into this function.

[0082] Based on the findings of single-cell scRNA sequencing and bulk RNA-seq sequencing of ordinary transcriptomes, this application established a classification flow chart to assist us in classifying bulk RNA seq ONB samples with calculated Neural / Basal / MesenchymalScore into three subtypes in a method applicable to clinical practice ( Figure 3 b). It should be noted that according to the flow chart of this pattern recognition, the basal (Basal), neural (Neural), and mesenchymal (Mesenchymal) type ONB tumors derived from the NBM Score are not parallel and juxtaposed relationships, but rather there is a priority in feature determination (i.e., Basal type > Neural type > Mesenchymal type).

[0083] The Basal Score, Neural Score, and Mesenchymal Score are respectively standardized using the formula "Normalized Score = (x - min(x)) / (max(x) - min(x))" to make the assigned scores with discrete distributions concentrated within the 0-1 interval for classification according to the score interval. ONB with a higher expression score of basal type features is determined to be of the basal (Basal) type (if the standardized Basal Score ≥ 0.3 points, regardless of the levels of Neural / Mesenchymal Score, it is determined to be of the basal type); if the expression of basal type features is low (standardized Basal Score < 0.3 points), but the expression of neural type features is high (standardized Neural Score ≥ 0.15 points), it is determined to be of the neural (Neural) type ONB (regardless of the level of Mesenchymal Score). Finally, ONB with only high expression of mesenchymal type features is determined to be of the mesenchymal (Mesenchymal) type (i.e., standardized Basal Score < 0.3 points and Neural Score < 0.15 points, and at the same time Mesenchymal Score > 0 points is the mesenchymal type).

[0084] So far, through the joint analysis of single-cell sequencing and ordinary transcriptome RNA sequencing data of ONB, a rare malignant tumor of the anterior cranial base, this application has successfully established the concept of the three subtypes of ONB and used an external dataset for verification. The tumor sequencing data used in this application was obtained from the tumor tissues of ONB patients who underwent endoscopic nasal tumor resection at the Eye, Ear, Nose and Throat Hospital of Fudan University from November 2019 to June 2021, and were subjected to 10×genomics single-cell sequencing and analysis. The normal control dataset for scRNA sequencing in this application was selected from the scRNA sequencing data (GSE139522) of 4 normal adult olfactory mucosa published by Durante et al. in the journal "Nature Neuroscience" (doi: 10.1038 / s41593-020-0587-9) in March 2020. The validation set data for bulk RNA seq sequencing used in this application was obtained from the 18 ONB bulk RNA seq data (GSE118995) published by Classe et al. in the journal "Cell Reports" (doi: 10.1016 / j.celrep.2018.09.047) in October 2018. This study conforms to the Declaration of Helsinki and has been reviewed and approved by the Ethics Committee of the Eye, Ear, Nose and Throat Hospital of Fudan University (Ethical Approval Number:

[2021] Lunshenzi No. 2021038). In this study, informed consent documents for all ONB patients who underwent endoscopic nasal surgery in the Department of Otorhinolaryngology of the Eye, Ear, Nose and Throat Hospital of Fudan University were signed and retained. For patients whose information and sequencing data were obtained from the GEO database, their informed consent was signed and retained by the researchers who released the data.

[0085] (1) Gene set used for scoring (NBM ONB gene list)

[0086] The present technical invention aims to obtain a new three-classification method for olfactory neuroblastoma (ONB) through differential expression analysis of gene expression profiles. In the research related to this technical invention, we named these three new subtypes of ONB as Neural type, Basal type, and Mesenchymal type respectively. The three subtypes of Neural / Basal / Mesenchymal can be referred to as the "NBM three-classification" according to the abbreviations of their English names.

[0087] The specific genes included in the gene expression set related to the NBM three-classification (NBM ONB gene list) are a total of 3 groups of 150, with 50 genes in each group representing the three ONB subtypes of Neural / Basal / Mesenchymal. The specific genes are shown in the following table:

[0088] Appendix 1:

[0089]

[0090]

[0091] (2) The objects to which scores are assigned and the nature of the data input into the scoring system

[0092] For patients pathologically diagnosed with olfactory neuroblastoma (ONB), tumor specimens are obtained through biopsy or surgery, and bulk RNA sequencing (bulk RNA seq) is performed. After the raw data is downloaded, through necessary quality control, data cleaning, alignment and other conventional processes, the gene expression level is calculated based on the alignment results to obtain the TPM (Transcripts Per Million) normalized expression matrix of gene expression levels.

[0093] TPM is a unit often used in the field of RNA sequencing data analysis, representing the proportion of a certain transcript in every million reads. TPM values can be used to compare the expression abundances between different genes or different samples, and can standardize the RNA-Seq sequencing depth of samples to eliminate the influence of the sequencing depth of samples on the analysis of gene expression levels. Specifically, the calculation formula for TPM values is: the number of reads of each gene (ReadCount) ÷ the number of species-specific transcripts (Effective Length) ÷ the total number of reads (TotalRead Count) × 1000000, where EffectiveLength represents the effective length of each transcript.

[0094] (3) The specific operation method for the scoring system to score the objects to which scores are assigned

[0095] Use the free, open-source statistical software "R" (version > 4.0.0) for subsequent data analysis, and load the R language package "Seurat" (version > 3.2.0) dedicated to quality control, analysis and exploration of single-cell RNA-seq data in the R environment.

[0096] ① After the TPM matrix obtained through data processing of the bulk RNA sequencing of ONB tumor samples is loaded into the R language environment, use the "CreateSeuratObject()" function of the Seurat package to convert the TPM matrix into a data object that can be further processed by the Seurat package.

[0097] ② In the description of the technical solution of this part, the ONB NBM gene list mentioned above, which consists of 3 groups and 150 genes (50 genes in each group), is used as the gene set for scoring. The "AddModuleScore()" function of the Seurat package is used to calculate the respective scores of the three ONB subtypes of neural / basal / mesenchymal corresponding to the data of each ONB patient in the TPM matrix. In the output result of this step, each ONB patient will obtain a Neural Score, a Basal Score, and a Mesenchymal Score.

[0098] ③ The formula "Normalized Score = (x - min(x)) / (max(x) - min(x))" is used to normalize the BasalScore, Neural Score, and Mesenchymal Score respectively, so that the discrete distributed score values are concentrated in the range of 0 to 1. The NBM Score calculated in the previous step is used to determine the ONB classification: (1) ONB with a higher expression score of basal type features is determined to be of the basal type (if the normalized Basal Score ≥ 0.3 points, regardless of the levels of Neural / Mesenchymal Score, it is determined to be of the basal type); (2) If the expression of basal type features is low (normalized BasalScore < 0.3 points) and the expression of neural type features is high (normalized Neural Score ≥ 0.15 points), it is determined to be of the neural (Neural) type ONB (regardless of the level of Mesenchymal Score); (3) ONB with only high expression of mesenchymal type features is determined to be of the mesenchymal (Mesenchymal) type (that is, when the normalized Basal Score < 0.3 points and the Neural Score < 0.15 points, and at the same time the Mesenchymal Score > 0 points, it is of the mesenchymal type). (See the <Drawings> part of this application for specific steps)

[0099] (4) Statistical methods and statistical power for constructing the scoring system

[0100] The discovery process of NBM three-classification uses the K-means clustering method to perform unsupervised clustering on the ONB bulk RNA seq TPM matrix. According to the distribution of the marker genes corresponding to the ONB NBM gene list in the clustering results, it is not difficult to conclude that the case cohort in the matrix can be divided into three categories when K = 3, which biologically correspond to the Neural / Basal / Mesenchymal subtypes of ONB respectively. The calculation principle of the AddModuleScore() function in the R language package "Seurat": The genes of interest to the researcher are extracted from the expression matrix, and the average value of the expression of these genes is calculated for each data individual. The average value of the background genes is used to find the bin where each gene is located, and genes are randomly selected as the background within this bin. Finally, the average value of all target genes is calculated uniformly, and the average value of all background genes is calculated. The subtraction of the two is the Score value corresponding to the gene list input into this function. Based on this principle, we calculated the statistical efficacy of this scoring method for the bulk RNA seq data matrix of ONB patients in the experimental dataset by performing Neural / Basal / Mesenchymal Score scoring respectively, and evaluated it with the ROC curve and the area under the curve (AUC) value. The AUC values of the BasalScore, Neural Score, and Mesenchymal Score of each subtype of ONB predicted by the scoring system involved in this patent are 1, 0.96, and 0.95 respectively, showing relatively good statistical prediction efficacy( Figure 4 ).

[0101] The present technical invention first proposed a three-typed concept for a rare tumor, olfactory neuroblastoma (ONB). From the perspectives of gene expression and molecular typing, ONB cases are divided into basal type, neural type, and mesenchymal type, and the gene expression profiles and molecular functional pathways of each subtype are described, promoting the understanding of ONB subtypes in related fields. In this process, we newly discovered a Mesenchymal type ONB that expresses mesenchymal cell-related characteristics. Through single-cell sequencing technology, we successfully identified and characterized the molecular characteristics of mesenchymal type ONB. And based on the molecular characteristics of NBM ONB obtained by single-cell sequencing, using existing open-source R code and packages, we developed an algorithm that enables us to distinguish the ONB three-typed system discovered by single-cell sequencing in ordinary transcriptome sequencing samples with lower cost and less promotion difficulty. The typing gene expression profile used in this technology is derived from high-precision single-cell sequencing, with high accuracy and discrimination, and can be projected onto ordinary transcriptome sequencing with relatively simple sequencing steps and lower cost to obtain typing conclusions. Therefore, it is conducive to verification and promotion within a certain range, helps to classify ONB patients in clinical work, and assist in the selection of corresponding drug treatments according to the molecular characteristics of each subtype.

[0102] In addition, our previous research results related to the technology of the present invention showed that ONB tumor cells of different subtypes may correspond to different olfactory epithelium (OE) nerve cell component sources. This means that there is a strong correlation between ONB subtypes and tumor differentiation status. In related research, we used the scRNA dataset of adult OE (GSE139522) (Durante MA, Kurtenbach S, Sargi ZB, et al. Single-cell analysis of olfactory neurogenesis and differentiation in adult humans [J]. Nat Neurosci. 2020;23(3):323 - 326.). We studied the subpopulations of normal olfactory epithelial cells to further explore the potential origin cells of each ONB subtype ( Figure 5 a). Referring to the marker genes of multiple cell subpopulations of known human and mouse OE ( Figure 5b), we identified six subpopulations corresponding to the olfactory stem cell developmental lineages, including HBCs (TP63, KRT5), GBCs (ASCL1, HES6), supporting cells (including immature mSus and mature iSus; CXCL17, CYP2J2), direct neural progenitor cells (INPs; LHX2, NEUROD1), and immature and mature olfactory neurons (iORNs and mORNs; GNG8, GNG13). Cell developmental trajectory analysis revealed a dichotomous dendritic structure, showing that supporting cells directly transformed from HBCs, while the olfactory neuron cell lineage (INPs, iORNs, and mORNs) proliferated and differentiated from olfactory epithelial stem cells such as GBCs ( Figure 5 c).

[0103] Next, to find the diverse origins of ONB subtypes, we compared the transcriptomic correlations between NBM tumor cell subpopulations and adult OE cells. We performed Pearson's correlation coefficient analysis between normal OE and ONB tumor subpopulations, and the results showed that the olfactory epithelial stem cell GBCs were highly similar to the characteristics of basal-type ONB tumors, while the olfactory neuron lineage (INPs, iORNs, and mORNs) was mainly highly associated with neural-type ONB in terms of marker expression. Related gene expressions of mesenchymal-type ONB were observed in the supporting cell lineage ( Figure 5 d). The above results can be mutually confirmed with the scoring results of NBM marker expression fractions in OE cell subpopulations ( Figure 5 e-5f).

[0104] The normal OE cell sources corresponding to basal-type, neural-type, and mesenchymal-type ONB showed a trend of gradually maturing in differentiation, suggesting that the corresponding differentiation degrees of basal-type, neural-type, and mesenchymal-type ONB gradually increased. After obtaining the trichotomy of NBM, exploring the normal OE cell origins corresponding to each subtype, the related findings have strongly promoted our understanding of the origin, tumorigenesis, and development of ONB; it also has positive significance for explaining the disease to patients in actual clinical work.

[0105] Example 4

[0106] Tumor tissues of 20 olfactory neuroblastoma (ONB) patients who underwent transnasal endoscopic tumor resection at the Eye, Ear, Nose and Throat Hospital of Fudan University from June 2018 to June 2021 were collected. The postoperative pathology of the patients was diagnosed as ONB by the Pathology Department of the Eye, Ear, Nose and Throat Hospital. The samples were stored at -80 °C with RNA later and subjected to bulk RNA sequencing. After necessary quality control, data cleaning, alignment and other routine processes on the raw fastq data files output after sequencing, gene expression levels were calculated through the alignment results, and a TPM (Transcripts Per Million) normalized expression matrix containing the gene expression levels of 20 ONB patients was obtained.

[0107] Using the "CreateSeuratObject()" function in the R language package "Seurat", the TPM matrix can be converted into a data object that can be operated by the Seurat package. Using the NBM ONB gene list described above, a total of 3 groups and 150 genes (50 genes in each group) as the gene set used for scoring, and using the "AddModuleScore()" function in the Seurat package, a unified score was assigned to each ONB case individual in the bulkRNA seq TPM matrix to obtain the Neural type (neural type), Basal type (basal type), and Mesenchymal type (mesenchymal type) tumor characteristic scores (Neural / Basal / Mesenchymal Scores, NBM Scores, as shown in Table 2 in the appendix below).

[0108] Table 2 in the appendix

[0109] No Name NBM-bulk Basal Score Neural Score Mesenchymal Score 1 ONB-063 Mesenchymal -97.36627823 -265.5406626 215.0700149 2 ONB-330 Mesenchymal -118.0457886 -294.4765003 354.004021 3 ONB-022 Mesenchymal -103.4366143 -291.2959331 157.7965598 4 ONB-402 Mesenchymal -110.52749 -294.8201694 108.2838608 5 ONB-261C Neural -80.40230591 -49.63135148 -252.8734017 6 ONB-764 Neural -92.05053688 23.7042222 -103.3546089 7 ONB-659 Neural -73.23184959 -178.842147 -287.8849566 8 ONB-288 Neural -63.5252671 -120.5806248 -108.0000482 9 ONB-412 Neural -113.1001711 -114.6875911 -223.1715457 10 ONB-643 Neural -83.62268485 -141.7809125 -368.0043795 11 ONB-698 Neural -112.1635174 -193.4778876 -333.3043504 12 ONB-142 Neural -113.5957678 -139.3795657 95.5089331 13 ONB-199 Neural -89.47341666 -179.8556563 94.08927546 14 ONB-365 Neural -88.36433841 -235.0279074 -18.6105357 15 ONB-993 Basal 21.21275459 -278.8758454 -156.9426674 16 ONB-983 Basal -29.26707562 -283.1032653 203.322637 17 ONB-559 Basal 102.8333504 -245.069349 100.7289626 18 ONB-520 Basal 15.92237351 -311.4835678 -264.6410963 19 ONB-126 Basal 27.52366581 -175.1659575 23.67911894 20 ONB-249 Basal -30.30686164 -236.9324703 112.3629879

[0110] The formula "Normalized Score = (x - min(x)) / (max(x) - min(x))" was used to standardize the Basal Score, Neural Score, and Mesenchymal Score respectively, so that the discrete distributed score values were concentrated in the range of 0 - 1 for typing according to the score interval (see Table 3 in the appendix).

[0111] Table 3 in the appendix

[0112]

[0113] According to the instructions for the typing steps in this technical method, ONB typing was determined: (1) ONB with a standardized BasalScore ≥ 0.3 was determined to be basal type, regardless of the Neural / Mesenchymal Score. According to this standard, 6 cases numbered ONB-993, ONB-983, ONB-559, ONB-520, ONB-126, and ONB-249 were determined to be basal type; (2) For the remaining 14 patients (all with standardized Basal Score < 0.3), those with standardized Neural Score ≥ 0.15 were determined to be neural type ONB, regardless of the Mesenchymal Score. According to this standard, 10 patients, ONB-261C, ONB-764, ONB-659, ONB-288, ONB-412, ONB-643, ONB-698, ONB-142, ONB-199, and ONB-365, can be identified as neurological type. (3) The remaining 4 patients all had Basal Score < 0.3 and Neural Score < 0.15 after standardization, and only expressed mesenchymal characteristics (Mesenchymal Score > 0), so they can be identified as mesenchymal ONB. So far, all ONB cases involved in this embodiment have completed the ONB NBM three-type subtype determination proposed by the present technical invention.

[0114] The basic concepts have been described above. Obviously, for those skilled in the art, the above detailed disclosure is only for example and does not constitute a limitation of this specification. Although not explicitly stated here, those skilled in the art may make various modifications, improvements and corrections to this specification. Such modifications, improvements and corrections are suggested in this specification, so such modifications, improvements and corrections still belong to the spirit and scope of the exemplary embodiments of this specification.

[0115] At the same time, this specification uses specific words to describe the embodiments of this specification. For example, "one embodiment", "an embodiment", and / or "some embodiments" refer to a certain feature, structure or characteristic related to at least one embodiment of this specification. Therefore, it should be emphasized and noted that "one embodiment" or "an embodiment" or "an alternative embodiment" mentioned twice or more in different positions in this specification does not necessarily refer to the same embodiment. In addition, certain features, structures or characteristics in one or more embodiments of this specification can be appropriately combined.

[0116] In some embodiments, numbers are used to describe components and the quantity of attributes. It should be understood that such numbers used in the description of embodiments are modified by the modifiers "about", "approximate" or "substantially" in some examples. Unless otherwise specified, "about", "approximate" or "substantially" indicate that the said numbers allow a variation of ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may vary according to the characteristics required by individual embodiments. In some embodiments, the numerical parameters should consider the specified significant digits and adopt the method of retaining the general number of digits. Although the numerical ranges and parameters used in some embodiments of this specification to confirm the breadth of their scope are approximate values, in specific embodiments, such numerical settings are made as precise as possible within the feasible range.

[0117] Finally, it should be understood that the embodiments described in this specification are only used to illustrate the principles of the embodiments of this specification. Other deformations may also fall within the scope of this specification. Therefore, by way of example and not limitation, alternative configurations of the embodiments of this specification may be regarded as consistent with the teachings of this specification. Accordingly, the embodiments of this specification are not limited to the embodiments explicitly introduced and described in this specification.

Claims

1. Use of a detection reagent for olfactory neuroblastoma subtype classification markers in the preparation of a product for olfactory neuroblastoma subtype classification, wherein the markers include basal markers, neural markers, and mesenchymal markers; The basal markers include the following genes: UBE2C, HMGB2, CENPF, NNAT, HIST1H4C, HIST1H1A, TUBA1B, PTTG1, TOP2A, NUSAP1, HIST1H1B, CCNB1, UBE2S, BIRC5, CKS1B, CKS2, TPX2, H2AFZ, PCP4, CDK1, MFAP4, MKI67, PBK, MAD2L1, HMGB1, CKAP2, CCNB2, SMC4, CENPW, HIST1H1D, UBE2T, CDKN3, ASPM, TUBA1C, TYMS, DLGAP5, PCLAF, PRC1, NUF2, ARL6IP1, TMPO, CDC20, KPNA2, HMGN2, DTYMK, HIST1H1E, HIST1H1C, MDK, HIST1H3B, H2AFX; The neurogenic markers include the following genes: CRABP1, SCG5, PEG10, MAP1B, GNG8, CIB2, STMN2, PCSK1N, CHGB, RTN1, MIR7-3HG, SNRPN, EEF1A2, MEG3, GRP, SEC11C, NHLH1, KIF19, KCNK9, APMAP, TLCD3B, UNCX, CALB2, BEX1, IRX2, PEBP1, RGS10, CIRBP, VAMP2, FXYD3, KLHL35, MAP1LC3A, BEX2, NCAM1, GADD45B, NEUROD1, FXYD6, ATP6V0E2, C11orf96, CAMK2N1, C5orf38, CPE, RPS3, TMPRSS6, DUSP26, PDLIM1, STX1A, FABP6, KCTD17, SPOCK2; The mesenchymal markers include the following genes: SLPI, S100A6, WFDC2, MT1X, MGP, CRYAB, S100A11, SAT1, CCN2, IGFBP7, VMO1, APOE, IER3, IGFBP5, S100A4, ANXA2, S100A10, VIM, MT2A, CD9, IFI27, LGALS1, LYPD2, TIMP1, IFITM3 , ITGB1, LGALS3, CALD1, KRT18, SPARC, COL11A1, COL18A1, CEBPD, CSTB, CD59, APLP2, ID3, PTN, COL3A1, CCN1, KRT8, DST, TPM4, CYBA, ALDH1A1, CLU, IFITM2, CD63, TPM2, ZFP36L1; The olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neuronal olfactory neuroblastoma and mesenchymal olfactory neuroblastoma. The basal olfactory neuroblastoma subgroup highly expresses cell proliferation and cell cycle pathways compared to the neuronal olfactory neuroblastoma subgroup and the mesenchymal olfactory neuroblastoma subgroup. The neuronal olfactory neuroblastoma subgroup has the functions of neurogenesis and olfactory conduction. The mesenchymal olfactory neuroblastoma subgroup has cell functions including angiogenesis, epithelial-mesenchymal transition, extracellular matrix remodeling, inflammatory response and chemokine secretion. The detection reagent for detecting olfactory neuroblastoma subtypes comprises the following steps: Providing sequencing information of a target marker of a sample to be tested, wherein the target marker is a subtype classification marker for olfactory neuroblastoma; based on the sequencing information of the target marker of the sample to be tested, obtaining basal, neural, and mesenchymal tumor characteristic scores of olfactory neuroblastoma patients; Based on the characteristic score, the subtype of olfactory neuroblastoma is determined according to the following steps: When the standardized basal tumor characteristic score was ≥0.3, olfactory neuroblastoma was judged to be basal type; When the standardized basal-type tumor characteristic score was <0.3 points and the standardized neural-type tumor characteristic score was ≥0.15 points, olfactory neuroblastoma was judged to be neural-type; When the normalized basal tumor characteristic score is <0.3 points, the neural tumor characteristic score is <0.15 points, and the mesenchymal tumor characteristic score is >0 points, the olfactory neuroblastoma is determined to be mesenchymal; the sequencing information includes single-cell RNA sequencing information and / or common transcriptome RNA sequencing information; The sample to be tested is a tumor tissue of a patient with olfactory neuroblastoma; Based on the sequencing information of the target marker of the sample to be tested, the gene expression amount of the target marker is calculated to obtain the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments or Reads Per Kilobase per Million mapped reads of the gene expression amount; further, the quality of each individual olfactory neuroblastoma case in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exonmodel per Million mapped fragments or Reads Per Kilobase per Million mapped reads is unified to obtain the basal type, neural type, and mesenchymal type tumor characteristic scores of a single olfactory neuroblastoma case; Use the "CreateSeuratObject()" function of the R package "Seurat" to convert the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads into a data object operated by the Seurat package; And / or, use the "AddModuleScore()" function of the Seurat package to uniformly assign a score to each individual olfactory neuroblastoma case in the normalized expression matrix of the common transcriptome RNA sequencing information TranscriptsPer Million, Fragments Per Kilobase of exon model per Millionmapped fragments, or ReadsPer Kilobase per Million mapped reads; And / or, the formula "Normalized Score = (x-min(x)) / (max(x)-min(x))" is used to standardize the characteristic scores of basal, neural, and mesenchymal tumors, respectively, so that the discrete distribution scores are concentrated in the range of 0 to 1.

2. The use according to claim 1, characterized in that The detection reagent is selected from any one or more of a chip, a probe or a primer pair.

3. A product for olfactory neuroblastoma subtype classification, the product comprising a detection reagent for genes in olfactory neuroblastoma subtype classification markers, the markers comprising basal markers, neural markers and mesenchymal markers; the basal markers comprising the following genes: UBE2C, HMGB2, CENPF, NNAT, HIST1H4C, HIST1H1A, TUBA1B, PTTG1, TOP2A, NUSAP1, HIST1H1B, CCNB1, UBE2S, BIRC5, CKS1B, CKS2, TPX2 , H2AFZ, PCP4, CDK1, MFAP4, MKI67, PBK, MAD2L1, HMGB1, CKAP2, CCNB2, SMC4, CENPW, HIST1H1D, UBE2T, CDKN3, ASPM, TUBA1C, TYMS, DLGAP5, PCLAF, PRC1, NUF2, ARL6IP1, TMPO, CDC20, KPNA2, HMGN2, DTYMK, HIST1H1E, HIST1H1C, MDK, HIST1H3B, H2AFX; The neurogenic markers include the following genes: CRABP1, SCG5, PEG10, MAP1B, GNG8, CIB2, STMN2, PCSK1N, CHGB, RTN1, MIR7-3HG, SNRPN, EEF1A2, MEG3, GRP, SEC11C, NHLH1, KIF19, KCNK9, APMAP, TLCD3B, UNCX, CALB2, BEX1, IRX2, PEBP1, RGS10, CIRBP, VAMP2, FXYD3, KLHL35, MAP1LC3A, BEX2, NCAM1, GADD45B, NEUROD1, FXYD6, ATP6V0E2, C11orf96, CAMK2N1, C5orf38, CPE, RPS3, TMPRSS6, DUSP26, PDLIM1, STX1A, FABP6, KCTD17, SPOCK2; The mesenchymal markers include the following genes: SLPI, S100A6, WFDC2, MT1X, MGP, CRYAB, S100A11, SAT1, CCN2, IGFBP7, VMO1, APOE, IER3, IGFBP5, S100A4, ANXA2, S100A10, VIM, MT2A, CD9, IFI27, LGALS1, LYPD2, TIMP1, IFITM3 , ITGB1, LGALS3, CALD1, KRT18, SPARC, COL11A1, COL18A1, CEBPD, CSTB, CD59, APLP2, ID3, PTN, COL3A1, CCN1, KRT8, DST, TPM4, CYBA, ALDH1A1, CLU, IFITM2, CD63, TPM2, ZFP36L1; The olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neuronal olfactory neuroblastoma and mesenchymal olfactory neuroblastoma. The basal olfactory neuroblastoma subgroup highly expresses cell proliferation and cell cycle pathways compared to the neuronal olfactory neuroblastoma subgroup and the mesenchymal olfactory neuroblastoma subgroup. The neuronal olfactory neuroblastoma subgroup has the functions of neurogenesis and olfactory conduction. The mesenchymal olfactory neuroblastoma subgroup has cell functions including angiogenesis, epithelial-mesenchymal transition, extracellular matrix remodeling, inflammatory response and chemokine secretion. The detection reagent for detecting olfactory neuroblastoma subtypes comprises the following steps: Providing sequencing information of a target marker of a sample to be tested, wherein the target marker is a subtype classification marker for olfactory neuroblastoma; based on the sequencing information of the target marker of the sample to be tested, obtaining basal, neural, and mesenchymal tumor characteristic scores of olfactory neuroblastoma patients; Based on the characteristic score, the subtype of olfactory neuroblastoma is determined according to the following steps: When the standardized basal tumor characteristic score was ≥0.3, olfactory neuroblastoma was judged to be basal type; When the standardized basal-type tumor characteristic score was <0.3 points and the standardized neural-type tumor characteristic score was ≥0.15 points, olfactory neuroblastoma was judged to be neural-type; When the normalized basal tumor characteristic score is <0.3 points, the neural tumor characteristic score is <0.15 points, and the mesenchymal tumor characteristic score is >0 points, the olfactory neuroblastoma is determined to be mesenchymal; the sequencing information includes single-cell RNA sequencing information and / or common transcriptome RNA sequencing information; The sample to be tested is a tumor tissue of a patient with olfactory neuroblastoma; Based on the sequencing information of the target marker of the sample to be tested, the gene expression amount of the target marker is calculated to obtain the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments or Reads Per Kilobase per Million mapped reads of the gene expression amount; further, the quality of each individual olfactory neuroblastoma case in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exonmodel per Million mapped fragments or Reads Per Kilobase per Million mapped reads is unified to obtain the basal type, neural type, and mesenchymal type tumor characteristic scores of a single olfactory neuroblastoma case; Use the "CreateSeuratObject()" function of the R package "Seurat" to convert the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads into a data object operated by the Seurat package; And / or, use the "AddModuleScore()" function of the Seurat package to uniformly assign a score to each individual olfactory neuroblastoma case in the normalized expression matrix of the common transcriptome RNA sequencing information TranscriptsPer Million, Fragments Per Kilobase of exon model per Millionmapped fragments, or ReadsPer Kilobase per Million mapped reads; And / or, the formula "Normalized Score = (x-min(x)) / (max(x)-min(x))" is used to standardize the characteristic scores of basal, neural, and mesenchymal tumors, respectively, so that the discrete distribution scores are concentrated in the range of 0 to 1.

4. The product according to claim 3, characterized in that The detection reagent is selected from any one or more of a chip, a probe or a primer pair.

5. A device for detecting olfactory neuroblastoma subtypes, characterized in that: The olfactory neuroblastoma subtype detection device comprises the following modules: An information acquisition module, used to provide sequencing information of a target marker of a sample to be tested, wherein the target marker is a marker for classification of olfactory neuroblastoma subtypes; A scoring module, used to score the subtype based on the sequencing information of the target marker of the sample to be tested; A judgment module, used for judging whether the subtype of olfactory neuroblastoma is basal, neural or mesenchymal based on the subtype score; the markers include basal markers, neural markers and mesenchymal markers; The basal markers include the following genes: UBE2C, HMGB2, CENPF, NNAT, HIST1H4C, HIST1H1A, TUBA1B, PTTG1, TOP2A, NUSAP1, HIST1H1B, CCNB1, UBE2S, BIRC5, CKS1B, CKS2, TPX2, H2AFZ, PCP4, CDK1, MFAP4, MKI67, PBK, MAD2L1, HMGB1, CKAP2, CCNB2, SMC4, CENPW, HIST1H1D, UBE2T, CDKN3, ASPM, TUBA1C, TYMS, DLGAP5, PCLAF, PRC1, NUF2, ARL6IP1, TMPO, CDC20, KPNA2, HMGN2, DTYMK, HIST1H1E, HIST1H1C, MDK, HIST1H3B, H2AFX; The neurogenic markers include the following genes: CRABP1, SCG5, PEG10, MAP1B, GNG8, CIB2, STMN2, PCSK1N, CHGB, RTN1, MIR7-3HG, SNRPN, EEF1A2, MEG3, GRP, SEC11C, NHLH1, KIF19, KCNK9, APMAP, TLCD3B, UNCX, CALB2, BEX1, IRX2, PEBP1, RGS10, CIRBP, VAMP2, FXYD3, KLHL35, MAP1LC3A, BEX2, NCAM1, GADD45B, NEUROD1, FXYD6, ATP6V0E2, C11orf96, CAMK2N1, C5orf38, CPE, RPS3, TMPRSS6, DUSP26, PDLIM1, STX1A, FABP6, KCTD17, SPOCK2; The mesenchymal markers include the following genes: SLPI, S100A6, WFDC2, MT1X, MGP, CRYAB, S100A11, SAT1, CCN2, IGFBP7, VMO1, APOE, IER3, IGFBP5, S100A4, ANXA2, S100A10, VIM, MT2A, CD9, IFI27, LGALS1, LYPD2, TIMP1, IFITM3 , ITGB1, LGALS3, CALD1, KRT18, SPARC, COL11A1, COL18A1, CEBPD, CSTB, CD59, APLP2, ID3, PTN, COL3A1, CCN1, KRT8, DST, TPM4, CYBA, ALDH1A1, CLU, IFITM2, CD63, TPM2, ZFP36L1; The sequencing information includes single-cell RNA sequencing information and / or common transcriptome RNA sequencing information; The sample to be tested is a tumor tissue of a patient with olfactory neuroblastoma; The scoring module obtains the basal, neural, and mesenchymal tumor characteristic scores of olfactory neuroblastoma patients based on the sequencing information of the target markers of the sample to be tested; The determination module determines the subtype of olfactory neuroblastoma according to the following steps: When the standardized basal tumor characteristic score was ≥0.3, olfactory neuroblastoma was judged to be basal type; When the standardized basal-type tumor characteristic score was <0.3 points and the standardized neural-type tumor characteristic score was ≥0.15 points, olfactory neuroblastoma was judged to be neural-type; When the standardized basal tumor characteristic score was <0.3 points, the neural tumor characteristic score was <0.15 points, and the mesenchymal tumor characteristic score was >0 points, the olfactory neuroblastoma was judged to be mesenchymal type; The scoring module calculates the gene expression of the target marker based on the sequencing information of the target marker of the sample to be tested, and obtains the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments or Reads Per Kilobase per Million mapped reads of the gene expression; further, the quality of each individual olfactory neuroblastoma case in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments or Reads Per Kilobase per Million mapped reads is unified to obtain the basal type, neural type, and mesenchymal type tumor feature scores of a single olfactory neuroblastoma case; using the "CreateSeuratObject()" function of the R language package "Seurat", the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments or Reads Per Kilobase per Million mapped reads is converted into a data object operated by the Seurat package; And / or, use the "AddModuleScore()" function of the Seurat package to uniformly assign a score to each individual olfactory neuroblastoma case in the normalized expression matrix of common transcriptome RNA sequencing information Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads; And / or, the formula "Normalized Score = (x-min(x)) / (max(x)-min(x))" is used to standardize the characteristic scores of basal, neural, and mesenchymal tumors, respectively, so that the discrete distribution scores are concentrated in the range of 0 to 1.

6. A computer-readable storage medium, characterized in that: The storage medium stores computer instructions. When the computer instructions are executed by a processor, a method for detecting a subtype of olfactory neuroblastoma is implemented. The method includes: Obtaining sequencing information of a target marker of a sample to be tested, wherein the target marker is a marker for subtype classification of olfactory neuroblastoma; Based on the sequencing information of the target markers of the sample to be tested, the subtype is scored; The olfactory neuroblastoma subtype is judged as basal, neural or mesenchymal based on the subtype score; The markers include basal markers, neural markers and mesenchymal markers; The basal markers include the following genes: UBE2C, HMGB2, CENPF, NNAT, HIST1H4C, HIST1H1A, TUBA1B, PTTG1, TOP2A, NUSAP1, HIST1H1B, CCNB1, UBE2S, BIRC5, CKS1B, CKS2, TPX2, H2AFZ, PCP4, CDK1, MFAP4, MKI67, PBK, MAD2L1, HMGB1, CKAP2, CCNB2, SMC4, CENPW, HIST1H1D, UBE2T, CDKN3, ASPM, TUBA1C, TYMS, DLGAP5, PCLAF, PRC1, NUF2, ARL6IP1, TMPO, CDC20, KPNA2, HMGN2, DTYMK, HIST1H1E, HIST1H1C, MDK, HIST1H3B, H2AFX; The neurogenic markers include the following genes: CRABP1, SCG5, PEG10, MAP1B, GNG8, CIB2, STMN2, PCSK1N, CHGB, RTN1, MIR7-3HG, SNRPN, EEF1A2, MEG3, GRP, SEC11C, NHLH1, KIF19, KCNK9, APMAP, TLCD3B, UNCX, CALB2, BEX1, IRX2, PEBP1, RGS10, CIRBP, VAMP2, FXYD3, KLHL35, MAP1LC3A, BEX2, NCAM1, GADD45B, NEUROD1, FXYD6, ATP6V0E2, C11orf96, CAMK2N1, C5orf38, CPE, RPS3, TMPRSS6, DUSP26, PDLIM1, STX1A, FABP6, KCTD17, SPOCK2; The mesenchymal markers include the following genes: SLPI, S100A6, WFDC2, MT1X, MGP, CRYAB, S100A11, SAT1, CCN2, IGFBP7, VMO1, APOE, IER3, IGFBP5, S100A4, ANXA2, S100A10, VIM, MT2A, CD9, IFI27, LGALS1, LYPD2, TIMP1, IFITM3, ITGB1, LGALS3, CALD1, KRT18, SPARC, COL11A1, COL18A1, CEBPD, CSTB, CD59, APLP2, ID3, PTN, COL3A1, CCN1, KRT8, DST, TPM4, CYBA, ALDH1A1, CLU, IFITM2, CD63, TPM2, ZFP36L1; The sequencing information includes single-cell RNA sequencing information and / or common transcriptome RNA sequencing information; The sample to be tested is a tumor tissue of a patient with olfactory neuroblastoma; Based on the sequencing information of the target markers of the samples to be tested, the characteristic scores of basal, neural, and mesenchymal tumors of patients with olfactory neuroblastoma were obtained; Based on the sequencing information of the target marker of the sample to be tested, the gene expression amount of the target marker is calculated to obtain the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments or Reads Per Kilobase per Million mapped reads of the gene expression amount; further, each individual olfactory neuroblastoma case in the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model perMillion mapped fragments or Reads Per Kilobase per Million mapped reads is uniformly scored to obtain the basal, neural, and mesenchymal tumor characteristic scores of a single olfactory neuroblastoma case; Use the "CreateSeuratObject()" function of the R package "Seurat" to convert the normalized expression matrix of Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads into a data object operated by the Seurat package; And / or, use the "AddModuleScore()" function of the Seurat package to uniformly assign a score to each individual olfactory neuroblastoma case in the normalized expression matrix of common transcriptome RNA sequencing information Transcripts Per Million, Fragments Per Kilobase of exon model per Million mapped fragments, or Reads Per Kilobase per Million mapped reads; And / or, the formula "Normalized Score = (x-min(x)) / (max(x)-min(x))" is used to standardize the characteristic scores of basal, neural, and mesenchymal tumors, respectively, so that the discrete distribution scores are concentrated in the range of 0 to 1.

7. An electronic terminal, characterized in that: The electronic terminal includes: a processor, a memory, an input / output interface and a communication port; the memory is used to store a computer program, and the processor is used to execute the computer program stored in the memory, so that the terminal executes the method for detecting olfactory neuroblastoma subtypes as described in the computer-readable storage medium as claimed in claim 6.

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