Application of Ki-67 protein, CHG protein and CTGF protein or detection substances thereof

Abstract

The invention relates to the field of disease diagnosis, and particularly discloses application of Ki-67 protein, CHG protein and CTGF protein or detection substances thereof in preparation of products for tumor subtype classification, and the tumor is olfactory neuroblastoma. Representative molecular markers which correspond to various NBM types, can be verified by IHC staining and are limited in number are screened out from an ONB NBM trityping gene set obtained by an scRNA sequencing technology, and a simple optimization scheme which aims at the ONB NBM trityping and is suitable for clinical examination and classification is established through FFPE clinical queue verification.

Description

Technical Field

[0001] The present specification relates to the field of disease diagnosis, and in particular to the application of Ki-67 protein, CHG protein and CTGF protein or their detection substances. Background Art

[0002] 1. Introduction to the clinical features of olfactory neuroblastoma

[0003] Olfactory neuroblastoma (ONB) is a rare neuroectodermal malignant tumor of unknown etiology that originates from the primitive basal cells of the olfactory neuroepithelium, accounting for 3% to 6% of nasal and paranasal sinus tumors. Common sites of onset are the upper nasal cavity, such as the upper nasal septum, superior turbinate, and cribriform plate. ONB has a wide age range and a bimodal presentation, ranging from 11 to 20 years old and 51 to 60 years old, respectively. There is no obvious gender difference in onset. The center of the ONB lesion is confined to the nasal cavity in the early stage, showing local invasive growth. In the later stage, it can gradually invade adjacent tissues and organs, with distant metastasis mainly to lymph nodes and blood. Common metastatic sites are cervical lymph nodes, lungs, and bones. ONB has a relatively insidious onset, and the patient's clinical manifestations are closely related to tumor growth. There is often a lack of specific clinical symptoms in the early stage, and the patient is usually in the middle and late stages when he or she seeks medical attention.

[0004] In past studies, some scholars have discussed the staging of olfactory neuroblastoma. However, since ONB is a rare nasal skull base tumor, the relevant research progress has been slow due to the limited sample size, and there is no international unified standard for its clinical pathological grading system. At present, the modified Kadish staging (Foote staging) is the most commonly used ONB staging system in clinical practice. In addition, Hyams et al. first reported the Hyams pathological grading based on the histological characteristics of ONB in ​​1989 based on the differentiation level of ONB, which is a common system for morphological pathological grouping.

[0005] Existing literature reports show that the prognosis of ONB is related to its clinical stage and pathological grade. The 5-year survival rate of Kadish A stage tumors can be 75% to 90%, while the 5-year survival rate of Kadish C stage tumors is only 45%; the 5-year survival rate of Hyams high-grade (poorly differentiated) tumors is only 25%, while that of low-grade (well-differentiated) 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., which leads to large differences in treatment patterns, treatment efficacy, clinical outcomes, etc. for different types of ONB patients. This clinical situation reflects the lack of effective classification theory and recognized staging system for ONB, which leads to objective difficulties in the formulation of treatment plans and disease guidelines.

[0006] (II) Current status of research on molecular markers and prognostic classification of olfactory neuroblastoma

[0007] (1) Research progress on molecular classification of ONB and its prognostic correlation

[0008] In 2018, 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.e5.1] conducted bulk RNA seq sequencing analysis of 18 ONB tumors and found that ONB has two tumor subtypes with different differentiation levels, namely the poorly differentiated basal type and the well-differentiated neural type. The authors found molecular markers such as S-100 (OE supporting cell marker protein), KRTs (OE basal cell marker protein), and GFAP (OE neuronal marker protein), and successfully projected the tumor neural / basal typing results from the bulk RNA seq level to the protein expression level of immunohistochemistry. Through unsupervised cluster analysis of Ki-67, S-100, GFAP, and KRTs expression in 52 patients, the researchers found that the poorly differentiated Basal group had higher levels of KRT and Ki-67, and lower levels of GFAP and S-100; the well-differentiated Neural group had lower levels of KRT and Ki-67, and higher levels of GFAP and S-100. The authors also found that there was a significant difference in survival prognosis between the two groups, with the poorly differentiated Basal group being significantly lower than the well-differentiated Neural group.

[0009] In recent years, the development of high-throughput sequencing technologies represented by single cell RNA sequencing (scRNA-seq) has opened up new prospects for in-depth exploration of the molecular intrinsic types of highly heterogeneous rare tumors such as ONB. In 2023, Zunitch et al. found through scRNA sequencing and data analysis of ONB tumors that ONB may originate from the globular basal cell (GBCs) population of the olfactory epithelium and express the GBCs stemness marker EZH2 (a histone lysine N-methyltransferase), and believed that EZH2 inhibitors (such as tazetostat, etc.) can be used as targeted drugs for the treatment of ONB. The authors also found that some ONB tumor cells may express molecular characteristics similar to supporting cells, but this study failed to establish a direct association between ONB and the origin of OE supporting cells.

[0010] Furthermore, Finlay et al. published single-cell sequencing results on ONB tumor heterogeneity and the similarities between ONB and small cell lung cancer (SCLC) in May 2024. The study once again confirmed that ONB may originate from the GBC level of OE, and that ONB exhibits heterogeneity in cell fate and can mimic the normal GBC developmental trajectory. Through lineage tracing and scRNA transcriptomics studies, the authors determined that ONB is similar to SCLC, and mouse and human ONB exhibit mutually exclusive NEUROD1 (neural differentiation) and pou2f3 (mesenchymal differentiation)-like states, that is, tumor cells with mesenchymal-like characteristics are known to exist in SCLC, and ONB has a similar expression profile. This study indirectly discovered that there may be mesenchymal-like cell components in ONB, and further proposed possible hypotheses for the cellular origin of ONB and tumor molecular typing.

[0011] (2) Research progress on molecular biological markers and drug sensitivity targets of ONB

[0012] ONB is generally considered to originate from sensory neurons in the olfactory epithelium (OE). ONB is characterized by dense membrane-bound neurosecretory granules, neurofilaments, and microtubules in the cytoplasm. Usually, these structures in ONB stain positively for molecules such as neuron-specific enolase (NSE), synaptophysin (SYN), chromogranin (CHG), CD56, and LEU-7. Schwann cells (supporting cells) usually stain positively for S-100 protein and glial fibrillary acid protein, and generally appear around the tumor lobules.

[0013] Perhaps due to the rarity of ONB, there are only some preliminary studies on the characteristic molecular biological markers of its tumor. In 1995, Carney et al. reported that ONB expressed hASH-1, a molecular marker of olfactory neuron globose basal cells (GBCs). In 2011, Matayoshi et al. found that ONB also expressed calcium ion channel protein CNGCA2, a molecular marker of immature neurons of the olfactory mucosa. As a malignant tumor originating from the neuroectoderm, ONB is generally considered to be keratin (KRTs) negative, but Mandarano and Holbrook et al. reported that KRT18 expression was observed in their case cohorts; and KRT18 is a molecular marker of OE horizontal basal cells (HBCs), which once again provides evidence that ONB originates from immature neurons of the olfactory mucosa.

[0014] ONB proliferates actively, and the Ki-67 proliferation index is usually between 10% and 80%. In 2017, Gay et al. reported that about half of the tumors in their ONB patient cohort had upregulated expression of the PI3K / mTOR signaling pathway and the CDK-dependent cell cycle regulation pathway, verifying the heterogeneity of cell proliferation levels in ONB. Turri-Zanoni et al. found in a case series of 67 ONB patients that a Ki-67 index ≥ 20% was significantly associated with a higher risk of recurrence and a poorer disease-free survival rate.

[0015] The above results show that previous studies have conducted preliminary explorations on the molecular markers of ONB from the perspectives of the origin of ONB and tumor proliferation properties. At the same time, some research teams have also analyzed the drug targets related to these ONB molecular markers, trying to find the association between the intrinsic type of ONB molecules and drug sensitivity. In 2018, Topcagic et al. used multi-omics methods such as whole exome sequencing, RNA sequencing, and immunohistochemistry to deeply explore the molecular biological characteristics of ONB. The authors found a variety of gene expression patterns that serve as targets for classic chemotherapy drugs or chemotherapy resistance, such as low ERCC1 (cisplatin-sensitive sites, 10 / 12 cases), high TOPO1 (irinotecan-sensitive sites, 12 / 19 cases), high TUBB3 (vincristine-resistant sites, 13 / 14 cases), and high MRP1 (multidrug-resistant sites, 6 / 6 cases). The expression levels of these molecular markers related to drug responsiveness can effectively predict patients' chemotherapy responses and help screen patients' chemotherapy regimens. Summary of the invention

[0016] The present application provides the use of Ki-67 protein, CHG protein and CTGF protein or their detection products in preparing a product for tumor subtype classification, wherein the tumor is olfactory neuroblastoma.

[0017] The present application also provides a product for tumor subtype classification, the product comprising Ki-67 protein, CHG protein and CTGF protein and / or their detection substances, and the tumor is olfactory neuroblastoma.

[0018] The present application also provides a marker for tumor subtype classification, wherein the marker includes Ki-67 protein, CHG protein and CTGF protein, the tumor is olfactory neuroblastoma, and the olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neurogenic olfactory neuroblastoma and mesenchymal olfactory neuroblastoma.

[0019] The present application also provides an olfactory neuroblastoma subtype detection device, which includes the following modules: an information acquisition module, used to provide expression information of a target marker of a sample to be tested, wherein the target marker is the above-mentioned marker for classifying olfactory neuroblastoma subtypes; a scoring module, used to score the subtype based on the expression information of the target marker of the sample to be tested; and a judgment module, used to judge whether the olfactory neuroblastoma subtype is basal, neural or mesenchymal based on the subtype score.

[0020] The present application also provides a computer-readable storage medium, which stores computer instructions. When the computer instructions are executed by a processor, a method for detecting olfactory neuroblastoma subtypes is implemented, the method comprising: obtaining expression information of a target marker of a sample to be tested, wherein the target marker is the above-mentioned marker for classifying olfactory neuroblastoma subtypes; scoring the subtype based on the expression information of the target marker of the sample to be tested; and judging whether the olfactory neuroblastoma subtype is basal, neural, or mesenchymal based on the subtype score.

[0021] 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 olfactory neuroblastoma subtypes as described in the above-mentioned computer-readable storage medium.

[0022] The present application also provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for detecting olfactory neuroblastoma subtypes described in the above-mentioned computer-readable storage medium is implemented.

[0023] The beneficial effects brought by the present application include but are not limited to: the present application screens out a limited number of representative molecular markers corresponding to each NBM type, which can be verified by IHC staining, from the ONB NBM three-type gene set obtained by scRNA sequencing technology, and verifies them through FFPE clinical cohorts, thereby establishing a simple optimization scheme for clinical test classification for ONB NBM three-type.

[0024] Single-cell sequencing has the advantages of high accuracy and comprehensive information. However, the actual clinical work is often fast-paced, and it is difficult to prepare specimens specifically for single-cell sequencing in accordance with the experimental conditions required for single-cell sequencing; the relatively high sequencing cost makes it difficult to popularize the operation of "typing by single-cell sequencing results" in some underdeveloped areas and some local hospitals with limited laboratory conditions; and the single-cell sequencing technology requires the characteristics of fresh specimens, which makes it difficult to verify whether ONB tumor samples collected before the development of the NBM typing system have similar typing through single-cell sequencing. Considering that single-cell sequencing and conventional transcriptome RNA sequencing are both emerging and gradually popularized technologies in recent years, most medical institutions have retained ONB patient cohorts with formalin-embedded fixed (FFPE) tumor samples. The immunohistochemical staining (IHC) technology adapted to the expression level of relevant molecules in tumor specimens verified by FFPE specimens has the advantages of good specificity, high sensitivity, simplicity and rapidity, low cost, and good repeatability. The disadvantage of IHC technology is that it does not fully describe the molecular characteristics of tissues, but the ONB NBM gene combination (i.e., NBM ONB gene list) selected by high-throughput, high-precision scRNA sequencing technology in the early stage of this study and verified by the validation set can make up for this shortcoming. This technology invented and developed a simple, clinically applicable classification system to evaluate the NBM classification of ONB, which has the advantages of being able to use relatively convenient experimental techniques, being suitable for conveniently available FFPE samples, being easily generalizable, and being able to retrospectively study old cases that have been retained in the past, which helps clinicians quickly obtain the histopathological typing information of patients. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] The present application will be further described in the form of exemplary embodiments, which will be described in detail with reference to the accompanying drawings. These embodiments are not restrictive, and include:

[0026] Figure 1In order to show the tumor heterogeneity of ONB and the discovery and definition process of the new mesenchymal ONB subtype according to some embodiments of the present application, a) UMAP diagram shows the 7 subgroups after the ONB malignant epithelial cells are re-clustered. The cell cycle score of each cell was calculated using a list of cell cycle-related genes; b) UMAP describes the characteristic scores of classic basal and neural ONB in ​​tumor cells; c) Correlation between 40 NMF modules generated from 10 ONB tumor datasets, and hierarchical clustering identified 5 gene modules representing tumor commonalities; d) Bar chart shows representative GO pathways enriched in each NMF module; e) Violin plot shows the expression scores of 5 NMF modules in 7 tumor subgroups (from top to bottom: Basal, Neural, Mes-1, Mes-2, Ciliation); f) UMAP chart shows the annotated phenotypes of 7 ONB tumor subgroups; g) Stacked bar chart shows the proportion of cells found in each tumor subgroup in each ONB sample; h) Heat map shows representative GSVA pathways enriched in ONB tumor subgroups except ciliation subgroup.

[0027] Figure 2 To characterize the three subtypes of ONB based on scRNA-seq analysis as shown in some embodiments of the present application, a) the three-phase diagram depicts the NBM Scores (neural type / basal type / mesenchymal type scores) of each ONB tumor cell and the NBM scores of tumor cells in the 10 ONB tumor data sets involved in the study; b) the scRNA-seq NBM subtype features are projected into the ONB patient study set cohort containing 20 samples of the common transcriptome (bulk RNA seq), the upper heat map: the clinical characteristics of all ONB patients, including the modified Kadish stage, Dulguerov stage, Hyams grade and orbital invasion degree, represented by different colors, the lower heat map: a heat map showing the expression of each gene in the NBM ONBgene list marker gene set (Appendix 1) for each ONB patient; c) the scRNA-seq NBM subtype features are projected into the ONB patient validation set cohort containing 18 samples of the common transcriptome (bulk RNA seq) (GSE118995).

[0028] Figure 3The Ki-67 / CHG / CTGF expression cut-off value set for the ONB discovery set FFPE cohort shown in some embodiments of the present application, a) Typical Ki-67 / CHG / CTGF immunohistochemical staining results, showing that different cases in the group have different expressions of Neural / Basal / Mesenchymal ONB markers; b) Selection of Ki67 (%) cut-off value: 6 cases were determined to be Basal type by bulk RNA seq sequencing results analysis, and the R language min() function selected the lowest Ki-67 (%) value of the immunohistochemical staining results of these 5 patients (the obtained value was 25%); c) Selection of CHG H-Score cut-off value: 10 cases were determined to be Neural type by bulk RNA seq sequencing results analysis, and the R language min() function selected the lowest CHG Score value of the immunohistochemical staining results of these 10 patients (the obtained value was 75 points); d) CCN2 H-Score Selection of cut-off value: If an ONB patient has double negative expression of neurogenic and basal features (Ki-67 < 25% and CHG H-Score < 75 points), the ONB patient is judged to be mesenchymal type. Therefore, the H-Score cut-off value for determining whether ONB is mesenchymal type is set to 0 points.

[0029] Figure 4 This is a simple clinical classification method for characterizing the three subtypes of ONB based on immunohistochemical staining as shown in some embodiments of the present application. a) The ONB NBM subtype characteristics are projected into the FFPE validation set case cohort containing 30 samples through immunohistochemical marker Ki-67 / CHG / CTGF staining. The lower heat map shows the Ki-67 / CHG / CTGF staining expression of 30 ONB patients, and the neural / basal / mesenchymal ONB subgroups are distinguished; b) A recommended flowchart for the three-type ONB NBM based on the immunohistochemical staining results of Ki-67 / CHG / CTGF staining of FFPE samples (the specific classification process is described in the text).

[0030] Figure 5 For the clinical characteristics and prognostic analysis related to ONB NBM classification according to some embodiments of the present application, a) the bar graph shows the distribution comparison of Hyams grade between ONB NBM subtype tumor groups, *P<0.05; **P<0.01; ***P<0.001; ns. , not significant; b) the overall survival curve of the ONB patient cohort, stratified by the NBM tumor group predicted by the score (p=0.024).

[0031] Figure 6 It is a module diagram of an olfactory neuroblastoma subtype detection device according to some embodiments of the present application.

[0032] Figure 7 The present invention is a flowchart of a method for detecting olfactory neuroblastoma subtypes according to some embodiments of the present application.

[0033] Figure 8 Schematic diagram of the architecture of an electronic terminal according to some embodiments of the present application.

[0034] Fig. 9 These are differentially expressed genes among neural / basal / mesenchymal ONB tumor cells as shown in some embodiments of the present application.

[0035] Fig.10 The performance of the Ki-67 (%), CHG H-Score, and CTGF H-Score scoring systems in differentiating the three subtypes of ONB according to some embodiments of the present application. From left to right, the AUC values ​​of the scoring system for predicting the Basal subtype, Neural subtype, and Mesenchymal subtype of ONB are 1, 0.965, and 1, respectively. DETAILED DESCRIPTION

[0036] In order to more clearly illustrate the technical solutions of the embodiments of this specification, the following is a brief introduction to the drawings required for the description of the embodiments. Obviously, the drawings described below are only some examples or embodiments of this specification. For ordinary technicians in this field, this specification can also be applied to other similar scenarios based on these drawings without creative work. Unless it is obvious from the language environment or otherwise explained, the same reference numerals in the figures represent the same structure or operation.

[0037] As shown in this specification and claims, unless the context clearly indicates an exception, the words "a", "an", "an" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "comprise" and "include" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0038] Flowcharts are used in this specification to illustrate the operations performed by the system according to the embodiments of this specification. It should be understood that the preceding or following operations are not necessarily performed precisely in order. Instead, the steps may be processed in reverse order or simultaneously. At the same time, other operations may also be added to these processes, or one or more operations may be removed from these processes.

[0039] The present application provides the use of Ki-67 protein, CHG protein and CTGF protein or their detection products in preparing a product for tumor subtype classification, wherein the tumor is olfactory neuroblastoma.

[0040] In some embodiments, the detection object can be the Ki-67 protein, CHG protein and CTGF protein expression detection object. In some embodiments, preferably, the detection object can be selected from any one or more of antibodies, membrane strips, chips, probes or primer pairs.

[0041] 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, for example, with a fluorescent group and a quenching group. In some embodiments, the probe can be a Taqman probe with a fluorescent reporter group added to the 5' end and a fluorescent quenching group added to the 3' end.

[0042] Antibodies are proteins with protective effects produced by the body due to antigen stimulation. In some embodiments, antibodies can be used as detection reagents to detect gene expression.

[0043] The term "primer" as used herein refers to a naturally occurring oligonucleotide (e.g., a restriction fragment) or a synthetically produced oligonucleotide that is capable of serving as a starting point for the synthesis of a primer extension product that is complementary to a nucleic acid strand (a template or target sequence) when placed under appropriate conditions (e.g., buffer, salt, temperature, and pH) and in the presence of nucleotides and reagents for nucleic acid polymerization (e.g., a DNA-dependent or RNA-dependent polymerase). Typically, a set of primers will consist of at least two primers, an "upstream primer" and a "downstream primer" that together define an amplicon (a sequence to be amplified using the primers).

[0044] In some embodiments, the olfactory neuroblastoma subtype may include basal olfactory neuroblastoma, neuronal 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 neuronal olfactory neuroblastoma subgroup and the mesenchymal olfactory neuroblastoma subgroup. In some embodiments, the neuronal olfactory neuroblastoma subgroup has the functions of neurogenesis and olfactory conduction. In some embodiments, the mesenchymal olfactory neuroblastoma subgroup has cell functions including angiogenesis, epithelial-mesenchymal transition, extracellular matrix remodeling, inflammatory response and chemokine secretion.

[0045] In some embodiments, the Ki-67 protein can be a marker protein for basal olfactory neuroblastoma.

[0046] In some embodiments, the CHG protein may be a marker protein for olfactory neuroblastoma.

[0047] In some embodiments, the CTGF protein may be a marker protein for mesenchymal olfactory neuroblastoma.

[0048] The present application also provides a product for tumor subtype classification, the product comprising Ki-67 protein, CHG protein and CTGF protein and / or their detection substances, and the tumor is olfactory neuroblastoma.

[0049] In some embodiments, the detection object can be the Ki-67 protein, CHG protein and CTGF protein expression detection object. In some embodiments, preferably, the detection object can be selected from any one or more of antibodies, membrane strips, chips, probes or primer pairs. In some embodiments, the olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neuronal olfactory neuroblastoma and mesenchymal olfactory neuroblastoma.

[0050] The present application also provides a marker for tumor subtype classification, wherein the marker includes the protein in the above application, the tumor is olfactory neuroblastoma, and the olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neural olfactory neuroblastoma and mesenchymal olfactory neuroblastoma.

[0051] The present application also provides a device for detecting subtypes of olfactory neuroblastoma. Figure 6 As shown, the olfactory neuroblastoma subtype detection device includes the following modules: an information acquisition module 610 , a scoring module 620 and a judgment module 630 .

[0052] The information acquisition module 610 can be used to provide expression information of a target marker of a sample to be tested, wherein the target marker is the above-mentioned marker for classification of olfactory neuroblastoma subtypes. In some embodiments, the sample to be tested can be a tumor tissue of a patient with olfactory neuroblastoma. In some embodiments, the expression information can include Ki-67, CHG, and CTGF staining information based on FFPE white films of tumor tissue of ONB patients. In some embodiments, the staining can be immunohistochemical staining.

[0053] Scoring module 620 can be used to score subtypes based on the expression information of the target marker of the sample to be tested. In some embodiments, the scoring module can obtain the basal, neural, and mesenchymal tumor characteristic scores of patients with olfactory neuroblastoma based on the expression information of the target marker of the sample to be tested. In some embodiments, preferably, the scoring module can calculate the proliferation index or H-score value of the target marker based on the Ki-67, CHG, and CTGF staining images of the FFPE white film of the tumor tissue of the ONB patient.

[0054] The judgment module 630 can be used to judge whether the subtype of olfactory neuroblastoma is basal, neural or mesenchymal based on the score of the subtype. In some embodiments, the judgment module can judge the subtype of olfactory neuroblastoma according to the following steps: when the basal characteristic Ki-67 proliferation index is ≥25%, the olfactory neuroblastoma is judged to be basal; when the basal characteristic Ki-67 proliferation index is <25%, and the standardized neural tumor characteristic CHG H-Score is ≥75 points, the olfactory neuroblastoma is judged to be neural; when the basal characteristic Ki-67 proliferation index is <25%, and the standardized neural tumor characteristic CHG H-Score is <75, and the mesenchymal tumor characteristic CTGF H-Score>0 points, the olfactory neuroblastoma is judged to be mesenchymal.

[0055] In some embodiments, the calculation formula of the H-score can be H-Score=∑(Pi×i), wherein Pi refers to the proportion of cells with a certain intensity in the positive cells, and i refers to the staining intensity.

[0056] In some embodiments, the value range of the H-score may be 0 to 300, that is, each value is multiplied by 100, so that the maximum value of the H-score is 300.

[0057] In some embodiments, the Ki-67 proliferation index can be the percentage of Ki67-positive tumor cell nuclei among 100 tumor cell nuclei.

[0058] In some embodiments, the Ki-67 proliferation index can be a percentage ranging from 0-100%.

[0059] It should be noted that it should be understood that the division of the various modules of the above device is only a division of logical functions. In actual implementation, they can be fully or partially integrated into one physical entity, or they can be physically separated. These modules can all be implemented in the form of software called by processing elements; they can also be all implemented in the form of hardware; some modules can also be implemented in the form of software called by processing elements, and some modules can be implemented in the form of hardware. For example, the database acquisition module can be a separately established processing element, or it can be integrated in a certain chip. In addition, it can also be stored in a memory in the form of program code, and a certain processing element can call and execute the functions of the above database acquisition module. The implementation of other modules is similar. In addition, these modules can be fully or partially integrated together, or they can be implemented independently. The processing element described here can be an integrated circuit with signal processing capabilities. In the implementation process, each step of the above method or each module above can be completed by an integrated logic circuit of hardware in the processor element or instructions in the form of software.

[0060] For example, the above modules may be one or more integrated circuits configured to implement the above methods, such as one or more application specific integrated circuits (ASIC), or one or more digital singnal processors (DSP), or one or more field programmable gate arrays (FPGA) or graphics processing units (GPU). For another example, when a module is implemented in the form of a processing element scheduling program code, the processing element may be a general-purpose processor, such as a central processing unit (CPU) or other processors that can call program code. For another example, these modules may be integrated together and implemented in the form of a system-on-a-chip (SOC).

[0061] The present application also provides a computer-readable storage medium, wherein 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 flowchart of the method is as follows: Figure 7 shown.

[0062] In step S710, the expression information of the target marker of the sample to be tested is obtained, and the target marker is the above-mentioned marker for classification of olfactory neuroblastoma subtypes. In some embodiments, the expression information may include Ki-67, CHG and CTGF staining information based on FFPE white film of tumor tissue of ONB patients. In some embodiments, preferably, the staining may be immunohistochemical staining. In some embodiments, the sample to be tested may be a tumor tissue of a patient with olfactory neuroblastoma.

[0063] In step S720, the subtype is scored based on the expression information of the target marker of the sample to be tested. In some embodiments, the basal, neural, and mesenchymal tumor characteristic scores of patients with olfactory neuroblastoma can be obtained based on the expression information of the target marker of the sample to be tested. In some embodiments, the proliferation index or H-score value of the target marker can be calculated based on the Ki-67, CHG, and CTGF staining images of the FFPE white film of the tumor tissue of the ONB patient.

[0064] In some embodiments, the calculation formula of the H-score can be H-Score=∑(Pi×i), wherein Pi refers to the proportion of cells with a certain intensity in the positive cells, and i refers to the staining intensity.

[0065] In some embodiments, the value range of the H-score may be 0 to 300, that is, each value is multiplied by 100, so that the maximum value of the H-score is 300.

[0066] In some embodiments, the Ki-67 proliferation index can be the percentage of Ki67-positive tumor cell nuclei among 100 tumor cell nuclei.

[0067] In some embodiments, the Ki-67 proliferation index can be a percentage ranging from 0-100%.

[0068] In step S730, the olfactory neuroblastoma subtype is determined to be basal, neural, or mesenchymal based on the subtype score. In some embodiments, the olfactory neuroblastoma subtype can be determined according to the following steps: when the basal characteristic Ki-67 proliferation index is ≥25%, the olfactory neuroblastoma is determined to be basal; when the basal characteristic Ki-67 proliferation index is <25%, and the standardized neural tumor characteristic CHG H-Score is ≥75 points, the olfactory neuroblastoma is determined to be neural; when the basal characteristic Ki-67 proliferation index is <25%, and the standardized neural tumor characteristic CHG H-Score is <75, and the mesenchymal tumor characteristic CTGF H-Score>0 points, the olfactory neuroblastoma is determined to be mesenchymal.

[0069] An embodiment of the present application also provides an electronic terminal, which includes: a processor 810, a memory 820, an input / output interface 830, a communication port 840 and a bus 850; the memory 820 is used to store computer programs, and the processor 810 is used to execute the computer programs stored in the memory, so that the terminal executes the method for detecting olfactory neuroblastoma subtypes as described in the above-mentioned computer-readable storage medium.

[0070] The processor 810 can execute computing instructions (program code) and perform the functions of the detection device described in this application. The computing instructions may include programs, objects, components, data structures, processes, modules and functions (functions refer to specific functions described in this application). For example, the processor 810 can process instructions for detecting olfactory neuroblastoma subtypes in an olfactory neuroblastoma subtype detection device. 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 physical 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 circuits and processors capable of performing one or more functions, etc., or any combination thereof. For illustration only, Figure 8 Only one processor 810 is described, but it should be noted that the present application may include multiple processors.

[0071] The memory 820 can store data / information obtained from any component in the olfactory neuroblastoma subtype detection device. In some embodiments, the memory 820 may include a large capacity memory, a removable memory, a volatile read and write memory, and a read-only memory (ROM), etc., or any combination thereof. Exemplary large capacity memories may include disks, optical disks, and solid-state drives, etc. Removable memories may include flash drives, floppy disks, optical disks, memory cards, USB flash drives, compressed disks, and mobile hard disks, etc. Volatile read and write memories may include random access memories (RAM). RAM may include dynamic RAM (DRAM), double rate synchronous dynamic RAM (DDRSDRAM), static RAM (SRAM), thyristor RAM (T-RAM), and zero capacitance (Z-RAM), etc. ROM may include mask ROM (MROM), programmable ROM (PROM), erasable programmable ROM (PEROM), electrically erasable programmable ROM (EEPROM), compact disk ROM (CD-ROM), and digital versatile disk ROM, etc.

[0072] 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 interactive behavior between the user (e.g., the person corresponding to the sample to be tested, the user of the olfactory neuroblastoma subtype detection device, etc.) and the processor 810. 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 may include an input device and an output device. Exemplary input devices may include a keyboard, a mouse, a touch screen, a microphone, etc., or any combination thereof. Exemplary output devices may include a display device, a speaker, a printer, a projector, etc., or any combination thereof. Exemplary display devices may include a liquid crystal display (LCD), a display based on a light emitting diode (LED), a flat panel display, a curved display, a television device, a cathode ray tube (CRT), etc., or any combination thereof.

[0073] 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 the two. The wired connection can include an electric cable, an optical cable, or a telephone line, etc., or any combination thereof. The wireless connection can include Bluetooth, WiFi, WiMax, WLAN, ZigBee, a mobile network (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.

[0074] The bus 850 may connect the processor, memory, and other components. The memory 820 communicates with the processor 810 via the bus 850. The processor 810 reads data in the memory 820 via the bus 850, executes the program, and may write the result back to the memory. The input / output interface 830 exchanges data with the processor 810 and the memory 820 via the bus 850. For example, when a user enters data on the keyboard, the keyboard sends the data to the input / output interface 830 of the computer, and then transmits it to the processor 810 or the memory 820 via the data bus 850. The communication port 840 exchanges data with the processor 810 and the memory 820 via the bus 850. For example, when the computer receives network data via the Ethernet port, the data is first transmitted to the network interface card (NIC), and then transmitted to the processor 810 or the memory 820 via the network bus 850.

[0075] An embodiment of the present application further provides a computer program product, including a computer program. When the computer program is executed by a processor, the method for detecting olfactory neuroblastoma subtypes described in the above-mentioned computer-readable storage medium is implemented.

[0076] The present invention can be implemented as a computer program product including a computer-readable storage medium and a computer program code encoded on the medium for performing the above-described techniques.

[0077] The present invention may be implemented on any electronic device, such as a handheld computer, a personal digital assistant (PDA), a personal computer, a kiosk, a cellular phone, and the like.

[0078] Certain aspects of the present application include process steps and instructions described herein in algorithmic form. It should be noted that the process steps and instructions of the present application can be embodied in software, firmware or hardware, and when embodied in software, it can be downloaded and resided on different platforms used by various operating systems and can be operated from the platforms.

[0079] The present application also relates to an apparatus for performing the operations described herein. This apparatus may be specially constructed for the desired purpose, or the apparatus may comprise a general purpose computer selectively activated or reconfigured by a computer program stored in the computer. This computer program may be stored in a computer-readable storage medium, such as, but not limited to: any type of disk, including a floppy disk, an optical disk, a CD-ROM, a magneto-optical disk; a read-only memory (ROM), a random access memory (RAM), an EPROM, an EEPROM, a magnetic or optical card, an application specific integrated circuit (ASIC), or any type of medium suitable for storing electronic instructions, and may be coupled to a computer system bus. In addition, the computer referred to herein may include a single processor, or may be an architecture that employs a multi-processor design to seek increased computing power.

[0080] The experimental methods in the following examples are conventional methods unless otherwise specified. The experimental materials used in the following examples are purchased from conventional biochemical reagent companies unless otherwise specified. The quantitative tests in the following examples are repeated three times, and the results are averaged.

[0081] Example 1

[0082] Single-cell RNA sequencing (scRNA seq) technology can analyze relevant genetic information at the RNA expression level of a single cell and construct a cellular molecular expression map. In recent years, it has been widely used in the exploration of various tumor heterogeneity and the study of tissue development sources. In the research related to this patent invention, attempts were made to use scRNA sequencing technology to explore the tumor heterogeneity and tumor typing of olfactory neuroblastoma (ONB), and attempts were made to select representative molecules that can be identified by immunohistochemistry (IHC) staining from the high-precision molecular typing features obtained by scRNA analysis, so as to project the conclusions of scRNA sequencing into a formalin-fixed paraffin-embedded (FFPE) sample cohort, thereby establishing a simple clinical classification method for the three types of ONB.

[0083] (1) Study on characteristics of ONB tumor cell subpopulations

[0084] To characterize the diversity of ONB tumor cells, 24,686 malignant cells from 10 ONB tumor tissues were screened and re-clustered into seven tumor subgroups ( Figure 1 a). According to the multi-omics study of ONB published by Classe et al. mentioned above, the two known subtypes of ONB, namely basal and neural, can be verified in ONB single-cell data through the gene expression signatures of basal / neural markers provided in the study ( Figure 1 b); In addition, it was found that some ONB tumor subgroups (C4-C7) had a unique expression pattern that could not be characterized by known Neural / Basal subtype gene markers ( Figure 1 b).

[0085] Therefore, non-negative matrix factorization (NMF) analysis was performed to investigate the expression signatures of intra-tumor heterogeneity in ONB, resulting in five major gene modules expressed by ONB ( Figure 1 c). Through GO enrichment pathway analysis, 5 gene modules were found to represent different functions ( Figure 1 d). Therefore, ONB tumor subgroups can be divided into 4 main functional categories ( Figure 1 e- Figure 1f), namely, categories related to olfactory nerve development (module 1; CHGB / HES6 / NEUROD1) and cell cycle (module 2; MKI67 / TOP2A / UBE2C), which reflect the expression characteristics of known neural and basal ONBs, respectively. Module 4 mainly enriched the expression of functional characteristics related to the structure and movement of ciliated cells; tumor ciliated cells are an intrinsic subpopulation widely present in various types of tumor cells revealed in previous studies. Because their biological significance cannot reflect the tumor heterogeneity unique to ONBs that researchers are concerned about, they were not included in the subsequent tumor feature analysis. In particular, GO pathway enrichment analysis also revealed that two additional NMF modules (i.e., module 3, NRG1 / WNT10A, module 5, BMP7 / LAMA1) have mesenchymal cell characteristics.

[0086] The discovery of a “mesenchymal-like” ONB tumor subpopulation has triggered further exploration of the heterogeneity within ONB tumors ( Figure 1 g). Gene set variation analysis (GSVA, Figure 1 h), found that the basal ONB subgroup highly expressed cell proliferation and cell cycle pathways, the neural ONB subgroup had neurogenesis and olfactory conduction functions, and the newly defined subgroup had multiple cellular functions including angiogenesis, epithelial-mesenchymal transition (EMT), extracellular matrix (ECM) remodeling, inflammatory response and chemokine secretion ( Figure 1 h), the functions of these cells are consistent with the functional pathway enrichment characteristics of mesenchymal cells in the classical sense, so this newly defined ONB tumor subgroup was named Mesenchymal ONB tumor cells.

[0087] (2) Discovery of Neural / Basal / Mesenchymal subtypes of ONB tumors

[0088] The present application calculated the differentially expressed genes (DEGs) between neural / basal / mesenchymal (NBM) ONB tumor cells, and the results are as follows: Fig. 9As shown, the top 50 upregulated DEGs gene set (see Appendix 1) was used as a gene set that can represent the molecular characteristics of NBM-type ONB (NBM ONB gene list). The Neural, Basal, and Mesenchymal characteristic scores (Neural / Basal / Mesenchymal Scores) of each ONB tumor cell were calculated using this gene set. This application draws a three-phase diagram, placing each ONB tumor cell in the diagram according to the relative value of its respective NBM Score, and different categories (neural / basal / mesenchymal cells) are marked with different colors ( Figure 2 a). Overall, the three-phase diagram confirmed the three-type structure of ONB tumor cell phenotype. Furthermore, when the three-phase diagram images of a single patient were displayed separately to observe the specific composition of NBM cells in each patient in detail, it was found that Neural, Basal, and Mesenchymal cells tended to be enriched in different tumor individuals, thus showing three tumor classification patterns that can be distinguished by naked eyes ( Figure 2 a). It can be found that Basal tumor cells only exist in 5 cases numbered ONB-946, ONB-311, ONB-548, ONB-599, and ONB-983, and the distribution pattern of tumor cells in these patients always shows that Neural, Basal, and Mesenchymal tumor cells exist; while in 4 cases numbered ONB-764, ONB-288, ONB-199, and ONB-860, the distribution pattern of patient tumor cells shows that only Neural and Mesenchymal tumor cells exist; in particular, in the case numbered ONB-733, only Mesenchymal tumor cells exist. The above tumor cell distribution patterns suggest that there are three types of classification states in ONB tumor patients, which are mainly Basal, Neural, and Mesenchymal tumor cells, and the judgment of tumor type has a judgment priority of Basal type>Neural type>Mesenchymal type, which can be represented by the expression score of the three ONB NBM types.

[0089] To verify this finding, a bulk RNA-seq case cohort (HRA007322) consisting of 20 ONB patients who underwent surgical resection was used as a discovery cohort to further explore the clinical classification of ONB. The gene set (NBM ONB gene list) of the neural / basal / mesenchymal (NBM) ONB molecular characteristics of the 20 patients in the discovery cohort was pulled to form a matrix, and semi-supervised clustering was performed. The results showed that the 20 ONB patients could be divided into three major subgroups ( Figure 2 b). There are two groups of patients whose characteristics can be characterized by classic neural and basal gene signatures, respectively. However, after sorting the samples according to NBM ONB gene list expression, another group of tumors (N=4) was found to express mesenchymal tumor characteristics alone. This result suggests that there is a third subtype of ONB that expresses mesenchymal-type stromal characteristics.

[0090] Subsequently, the bulk RNA-seq cohort (GSE118995) of 18 ONB patients published 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 an external validation cohort, and the NBM ONB gene list was used as the marker gene for clustering. After semi-supervised clustering, the results were consistent with those observed in the study cohort, that is, there are three types of ONB tumor individuals, which mainly express the gene marker characteristics of neural / basal / mesenchymal (NBM) ONB. This step uses external data to verify the extensibility of the ONB trichotomy theory ( Figure 2 c). Finally, since the newly discovered ONB subtype was enriched with marker genes of mesenchymal-like cells, this previously unidentified new ONB subtype was named Mesenchymal.

[0091] Schedule 1:

[0092]

[0093]

[0094]

[0095] (3) Establishment of a rapid and simple method for defining neural / basal / mesenchymal subtypes of ONB tumors suitable for clinical scenarios: immunohistochemistry (IHC) staining based on formalin-fixed (FFPE) specimens

[0096] The NBM ONB gene list obtained by single-cell sequencing was scored and classified as ONB data of common transcriptome sequencing, and the NBM subtype scoring system of olfactory neuroblastoma established by single-cell scRNA sequencing analysis was projected onto bulk RNA seq sequencing samples ( Figure 2 b). The expression pattern of the calculated NBMScores of the ONB bulk RNA seq cohort and the NBM Score ternary diagram of the scRNA ONB single cell cohort ( Figure 2 a). The present application notes that most basal ONB samples are also enriched with higher neural and mesenchymal scores; patients with neural ONB may also have higher mesenchymal scores but lower basal scores; and in patients with mesenchymal ONB, tumors show pure high mesenchymal score expression, and their basal and neural scores are both low. This indicates that mesenchymal ONB, a unique new subtype of ONB, is characterized by both high mesenchymal feature scores and double negative expression of neural and basal features. The present application also notes that the findings of the present application have changed the previous understanding of the classic binary classification of neural / basal ONB, that is, the determination of basal ONB has priority over neural ONB.

[0097] High-throughput single-cell sequencing has the advantages of high precision and comprehensive analysis of tumor characteristics, but it also has unavoidable disadvantages such as only targeting fresh tumor specimens, numerous preparatory work before sequencing, high requirements for experimental conditions and cell status, long sequencing time, and cumbersome analysis process. In actual clinical work, the work pace is often fast, so it is difficult to prepare specimens specifically for single-cell sequencing in accordance with the experimental conditions required; the relatively high sequencing cost makes it objectively difficult to popularize the operation of "typing by single-cell sequencing results" in some underdeveloped areas and some local hospitals with limited laboratory conditions; and the single-cell sequencing technology requires the characteristics of fresh specimens, making it difficult to verify whether ONB tumor samples collected before the development of the NBM typing system also have similar typing through single-cell sequencing. Considering that single-cell sequencing and conventional transcriptome RNA sequencing are both emerging and gradually popularized technologies in recent years, most medical institutions have retained formalin-embedded fixed (FFPE) tumor specimens for ONB patient cohorts. Therefore, developing a simple and clinically applicable classification system to evaluate the NBM classification of ONB has the advantages of being able to use relatively convenient experimental techniques, being suitable for easily available FFPE samples, being easily scalable, and being able to retrospectively study previously retained old cases, which has become a technical problem that needs to be solved urgently.

[0098] If you want to use FFPE specimens to verify the expression level of related molecules in tumor specimens, the most suitable experimental technology recognized in clinical practice is immunohistochemistry (IHC). Its main principle is to use labeled antibodies or antigens to qualitatively, positionally or quantitatively detect the corresponding antigens or antibodies of cells, and observe them under a microscope or electron microscope after chemical color reaction. This technology is the product of the combination of immunofluorescence technology and morphological technology, and has the advantages of good specificity, high sensitivity, simplicity and rapidity, low cost and good repeatability. The disadvantage of IHC technology is that it does not fully describe the molecular characteristics of tissues, but the ONB NBM gene combination (i.e., NBM ONB gene list) selected by high-throughput and high-precision scRNA sequencing technology in the early work of this study and verified by the validation set can make up for this deficiency well. It is worth noting that the gene set obtained by single-cell sequencing includes 50 genes each of the three types of Neural / Basal / Mesenchymal, a total of 150 genes, and it is unrealistic to perform staining detection on all these genes in both laboratory and clinical pathological examinations. Therefore, this application screened out a limited number of representative molecular markers corresponding to each NBM type, which can be verified by IHC staining, from the ONB NBM three-type gene set obtained by scRNA sequencing technology, and verified them through FFPE clinical cohorts, thereby establishing a simple optimization scheme for clinical test classification for ONB NBM three-type.

[0099] First, this application attempts to select protein molecules that can be stained by IHC from the three groups of ONB NBM gene lists that characterize the molecular expression characteristics of the neural / basal / mesenchymal tritype ONB as described above, as representative molecular markers of each NBM subtype. The screening criteria and process of immunohistochemical molecular markers are as follows: ① Not all gene transcription products are protein molecules. However, IHC staining identifies the expression of protein markers, so only genes that are transcribed into protein molecules can be used for subsequent screening; ② The 3 groups of 150 genes included in the NBM ONB gene list are essentially a set of differentially expressed genes DEGs between the three groups of ONB tumor cells (Neural / Basal / Mesenchymal), and the top 50 upregulated DEGs genes are selected; the higher the expression, the more significant the expression of the gene in the tumor subtype, so the genes in the gene list are arranged from high to low according to the expression, and those with high expression are given priority; ③ Combining the review of ONB molecular markers and common IHC histochemical molecular markers for tumors, the selection of protein molecules with IHC antibodies on sale and that have been the focus of previous studies will help improve the applicability of this simple clinical classification method.

[0100] Through the above-mentioned process, Ki-67 (encoding gene MKI67), which represents the tumor proliferation index, was selected as the marker protein of basal ONB; human chromogranin (CHG, encoding gene CHGB), which represents neural differentiation and neural cell characteristics, was selected as the marker protein of neural ONB; connective tissue growth factor (CTGF, encoding gene CCN2), which represents mesenchymal cell differentiation, was selected as the marker protein of mesenchymal ONB. The results of IHC staining of the above Ki-67 / CHG / CTGF molecules in FFPE samples of tumor tissues of ONB patients showed that tumor tissues can express the above marker molecules, with good staining effect and obvious inter-tumor heterogeneity in expression levels ( Figure 3 a).

[0101] In order to verify the ability of the Ki-67 / CHG / CTGF molecular combination to distinguish ONB NBM subtypes and select the cut-off value for different intensity groups of Ki-67 / CHG / CTGF molecular staining, the present application collected, embedded and sectioned the FFPE specimens of the 20 ONB patients in the discovery set of the bulk RNA seq cohort described above that discovered the existence of three types of ONB, that is, the discovery set used in this study. The paraffin sections of each patient in the discovery set were stained with Ki-67 / CHG / CTGF molecules and their expression levels were analyzed.

[0102] After the IHC staining results are scanned out, the quantitative analysis method for the expression of the three molecules Ki-67 / CHG / CTGF is defined as follows:

[0103] ① Definition of Ki-67 proliferation index (Ki-67%): Count the percentage of Ki67-positive tumor cell nuclei among 100 tumor cell nuclei, select 4 fields of view of the whole section to calculate Ki-67% and take the average value;

[0104] ② CHG and CTGF expression was quantified using H-Score: H-score is an indicator used to evaluate the results of immunohistochemical staining, which comprehensively considers the two factors of positive cell ratio and staining intensity. The calculation formula of H-score is: H-Score = ∑(Pi×i)

[0105] Among them, Pi refers to the proportion of cells with a certain intensity in the positive cells, and i refers to the staining intensity, which is usually 0, 1, 2, or 3. In practical applications, the value range of H-score is often set to 0 to 300, that is, each value is multiplied by 100, so that the maximum value of H-score is 300.

[0106] Therefore, after the above IHC staining and expression evaluation, it was found that each ONB patient in the FFPE cohort obtained their own Ki-67 / CHG / CTGF expression levels, where Ki-67 (%) was distributed between 0-100%, and CHG and CTGF expression H-Score was distributed between 0-300 points. Next, this application selected the cut-off value for the expression distribution of Ki-67 (%), CHG, and CTGF by analyzing the specific staining scores of Ki-67 (%) / CHG / CTGF in the FFPE case cohort of ONB patients in the discovery set (Appendix 2) and combining the Neural / Basal / Mesenchymal typing of ONB cases in the discovery set based on the scRNA sequencing gene combination and bulk RNA seq sequencing results: ① In the discovery set, 6 cases were determined to be Basal type by bulk RNA seq sequencing results analysis. The R language min() function selected the lowest Ki-67 (%) value of the immunohistochemical staining results of these 5 patients (the obtained value was 25%), which was the cut-off value for determining whether ONB belongs to the Basal type by the proliferation index Ki67% ( Figure 3 b); ② In the discovery group, 10 cases were identified as Neural type by bulk RNA seq sequencing results. The R language min() function selected the lowest CHG Score value of the immunohistochemical staining results of these 10 patients (the obtained value was 75 points), which was the cut-off value for determining whether ONB was Neural type based on CHG staining intensity ( Figure 3 c); ③ It is worth noting that based on the results of single-cell sequencing and bulk RNA sequencing, the basal, neural, and mesenchymal ONB tumors derived are not parallel to each other, but there is a priority for feature determination (i.e., basal>neural>mesenchymal). That is, if an ONB patient has double negative expression of neural and basal features (Ki-67 < 25% and CHG H-Score < 75 points), the ONB patient is determined to be mesenchymal. Therefore, the H-Score cut-off value for determining whether ONB is mesenchymal is set to 0 points ( Figure 3 d).

[0107] Appendix 2 Ki-67 / CHG / CTGF expression levels in the discovery set ONB FFPE case cohort

[0108]

[0109] Combined with the Ki-67 / CHG / CTGF expression cut-off value set based on the ONB discovery set FFPE cohort, this application once again performed batch Ki-67 / CHG / CTGF staining in another group of 30 retrospective FFPE validation cohorts (validation set) with pathological diagnosis of ONB, and reproduced the results of the three classifications of ONB ( Figure 4 a). In addition, the validation set results suggest that Basal ONB is poorly differentiated, followed by Neural ONB, and Mesenchymal ONB is the best differentiated, which can prove that the simple clinical classification method of the Ki-67 / CHG / CTGF three-molecule combination has good discrimination for the case cohort. The applicant of this patent further proposed a flowchart to divide FFPE ONB samples into three subtypes, to assist otolaryngologists and pathologists in clinical practice, to perform simple clinical classification of ONB based on the IHC staining results of the three molecules ( Figure 4 b). ONBs with high Ki-67% (representing basal characteristics) expression were judged as basal type (if Ki-67% ≥ 25%, regardless of CHG or CTGF H-Score, they were judged as basal type); if the basal type characteristics were expressed at a low level (Ki-67% < 25%), but the neural type characteristics were expressed at a high level (CHG H-Score ≥ 75 points), they were judged as neural type ONB (regardless of CTGF H-Score). Finally, ONBs with only high expression of mesenchymal characteristics were judged as mesenchymal type (i.e., Ki-67% < 25% and CHG H-Score < 75 points, and CTGF H-Score > 0 points were mesenchymal type).

[0110] So far, through the joint analysis of single-cell sequencing and common transcriptome RNA sequencing data of ONB, a rare anterior skull base malignant tumor, this application has successfully established the concept of ONB tritypes and used external data sets for verification. The tumor sequencing data used in this study came from the collection of tumor tissues from ONB patients who underwent endoscopic tumor resection at the Affiliated Eye, Ear, Nose and Throat Hospital of Fudan University from November 2019 to June 2021. 10×genomics single-cell sequencing and analysis were performed. The normal control data set for scRNA sequencing in this study was selected from 4 normal adult olfactory mucosa scRNA sequencing data (GSE139522) published by Durante et al. [2] in the journal "Nature Neuroscience" in March 2020 (doi: 10.1038 / s41593-020-0587-9). The validation set data of bulk RNAseq sequencing used in this study were derived from 18 ONB bulk RNA seq data (GSE118995) published by Classe et al. in the journal Cell Reports in October 2018 (doi: 10.1016 / j.celrep.2018.09.047). The ONB validation set FFPE patient case cohort used in this study was derived from 30 tumor tissues collected from ONB patients who underwent endoscopic tumor resection at the Affiliated Eye, Ear, Nose and Throat Hospital of Fudan University from June 2018 to June 2021. This study complies with the Provisions of the Declaration of Helsinki and has been approved by the Ethics Committee of the Affiliated Eye, Ear, Nose and Throat Hospital of Fudan University (Ethics Approval No.:

[2021] Lun Shen Zi No. 2021038). Informed consent documents of all ONB patients who underwent endoscopic surgery in the Department of Otolaryngology, Affiliated Eye, Ear, Nose and Throat Hospital of Fudan University in this study were signed and retained. For patients who obtain information and sequencing data from the GEO database, their informed consent is signed and retained by the researchers who publish the data.

[0111] Example 2

[0112] (I) NBM ONB IHC markers used for typing

[0113] The present invention aims to derive a simplified clinical classification method for olfactory neuroblastoma (ONB) into three types through immunohistochemical staining differential expression analysis of ONB marker molecules. In the research related to the present invention, the present application names this new ONB three-type system as neural type, basal type, and mesenchymal type. The neural / basal / mesenchymal three-type can be referred to as "NBM three-type" according to the abbreviation of its English name.

[0114] The immunohistochemical markers associated with the three types of NBM are Ki-67: a marker protein for basal ONB; human chromogranin (CHG): a marker protein for neural ONB; and connective tissue growth factor (CTGF): a marker protein for mesenchymal ONB.

[0115] (II) Scoring objects and data nature input into the scoring system

[0116] Patients with pathological diagnosis of olfactory neuroblastoma (ONB) were given fresh tumor specimens through biopsy or surgery. After formalin fixation, embedding, sectioning and other routine steps in the early stage of immunohistochemistry operation, unstained FFPE white slides of tumor tissue of ONB patients were obtained. Three FFPE white slides were extracted from each ONB patient and IHC staining of Ki-67, CHG and CTGF was performed respectively. The immunohistochemical staining results were scanned to generate high-definition digital slide images, and digital slide reading software such as K-VIEWER was used to complete the immunohistochemical reading.

[0117] After scanning the IHC staining results, the quantitative analysis method for the expression of the three molecules Ki-67 / CHG / CTGF is defined as follows:

[0118] ① Definition of Ki-67 proliferation index (Ki-67%): Count the percentage of Ki67-positive tumor cell nuclei among 100 tumor cell nuclei, select 4 fields of view of the whole section to calculate Ki-67% and take the average value;

[0119] ② CHG and CTGF expression was quantified using H-Score: H-score is an indicator used to evaluate immunohistochemical staining results, which takes into account two factors: the proportion of positive cells and the intensity of staining. The calculation formula of H-score is:

[0120] H-Score=∑(Pi×i)

[0121] Among them, Pi refers to the proportion of cells with a certain intensity in the positive cells, and i refers to the staining intensity, which is usually 0, 1, 2, or 3. The value range of H-score is set to 0 to 300, that is, each value is multiplied by 100, so that the maximum value of H-score is 300.

[0122] In this step, after the above-mentioned IHC staining, result scanning and reading, and expression evaluation, each ONB patient obtained their own Ki-67 / CHG / CTGF quantitative expression. The proliferation index Ki-67% is a percentage ranging from 0 to 100%, and the CHG and CTGF expression H-Score is a score ranging from 0 to 300.

[0123] (III) Specific operation methods of the scoring system for scoring objects

[0124] Using the Ki67% value, CHG H-Score, and CTGF H-Score values ​​obtained in the previous step, the NBM classification of each ONB patient in the FFPE cohort is determined. The process is as follows: ONB with a higher expression of Ki-67% (representing basal characteristics) is judged as basal (if Ki-67% ≥ 25%, regardless of the CHG or CTGF H-Score, it is judged as basal); if the basal characteristic expression is low (Ki-67% < 25%), but the neural characteristic expression is high (CHG H-Score ≥ 75 points), it is judged as neural ONB (regardless of the CTGF H-Score). Finally, ONB that only highly expresses interstitial characteristics is judged as mesenchymal (i.e., Ki-67% < 25% and CHG H-Score < 75 points, and CTGF H-Score > 0 points is mesenchymal). (For specific steps, see the <Attached Figures> section of this application)

[0125] In this application, a limited number of representative molecular markers corresponding to each NBM type, which can be verified by IHC staining, are screened out from the ONB NBM three-type gene set obtained by scRNA sequencing technology, and verified by FFPE clinical cohort, so as to establish a simple optimization scheme suitable for clinical test classification for ONB NBM three-type.

[0126] Single-cell sequencing has the advantages of high accuracy and comprehensive information. However, the actual clinical work is often fast-paced, and it is difficult to prepare specimens specifically for single-cell sequencing in accordance with the experimental conditions required for single-cell sequencing; the relatively high sequencing cost makes it difficult to popularize the operation of "typing by single-cell sequencing results" in some underdeveloped areas and some local hospitals with limited laboratory conditions; and the single-cell sequencing technology requires the characteristics of fresh specimens, which makes it difficult to verify whether ONB tumor samples collected before the development of the NBM typing system have similar typing through single-cell sequencing. Considering that single-cell sequencing and conventional transcriptome RNA sequencing are both emerging and gradually popularized technologies in recent years, most medical institutions have retained ONB patient cohorts with formalin-embedded fixed (FFPE) tumor samples. The immunohistochemical staining (IHC) technology adapted to the expression level of relevant molecules in tumor specimens verified by FFPE specimens has the advantages of good specificity, high sensitivity, simplicity and rapidity, low cost, and good repeatability. The disadvantage of IHC technology is that it does not fully describe the molecular characteristics of tissues, but the ONB NBM gene combination (i.e., NBM ONB gene list) selected by high-throughput, high-precision scRNA sequencing technology in the early stage of this study and verified by the validation set can make up for this shortcoming. This technology invented and developed a simple, clinically applicable classification system to evaluate the NBM classification of ONB, which has the advantages of being able to use relatively convenient experimental techniques, being suitable for conveniently available FFPE samples, being easily generalizable, and being able to retrospectively study old cases that have been retained in the past, which helps clinicians quickly obtain the histopathological typing information of patients.

[0127] As discussed in the relevant background of this application, the Hyams grading system is an internationally recognized indicator that reflects the degree of pathological differentiation of ONB, which can be interpreted by the results of hematoxylin-eosin staining (HE staining) of FFPE sections. According to previous literature reports, the higher the Hyams grade of olfactory neuroblastoma, the worse the tumor differentiation and the higher the degree of dedifferentiation; the lower the Hyams grade, the better the tumor differentiation and the lower the degree of dedifferentiation. Through the NBM three-type determination method proposed in the present technical invention, this application determined the NBM subtype of each tumor in the ONB research cohort, and statistically analyzed whether there were differences in the Hyams staging between each subtype. The results showed that the Basal type ONB was the worst differentiated, the Neural type was moderately differentiated, and the Mesenchymal type was the best differentiated (P=0.002, Figure 5a). The survival analysis of the disease-free survival (DFS) of the three subtypes of ONB cases obtained by the study cohort classification according to the NBM classification method also showed that there were statistical differences in the prognostic results between different ONB subtypes, among which the mesenchymal type had the best prognosis and the basal type had the worst prognosis (P = 0.024, Figure 5 b). The simplified clinical classification method for three types of olfactory neuroblastoma proposed in the present invention relies on the tumor tissue of the FFPE section of the tumor. Therefore, the ONB Hyams staging and NBM classification information of the same tumor case can be obtained in a short time and conveniently through one-time embedding and sectioning, and different staining methods such as HE staining and immunohistochemical staining. This facilitates clinical researchers to quickly determine the malignancy of the patient's tumor and the possible outcome, and can help quickly provide assistance for the patient's surgical plan, resection range, subsequent adjuvant treatment measures, chemotherapy drug intensity and other decisions, thereby improving the patient's clinical benefits.

[0128] Example 3

[0129] Tumor tissues of 30 patients with olfactory neuroblastoma (ONB) who underwent endoscopic tumor resection at the Affiliated Eye, Ear, Nose and Throat Hospital of Fudan University from June 2018 to January 2022 were collected. The postoperative pathology of the patients was confirmed by the Department of Pathology of the Affiliated Eye, Ear, Nose and Throat Hospital of Fudan University for ONB. Fresh tumor samples were fixed in formalin, embedded in paraffin, and sliced ​​by a freezing microtome to obtain FFPE white slides. Three FFPE white slides with relatively complete morphology were taken from each tumor. After the necessary operations related to immunohistochemical staining, including dewaxing and hydration, antigen repair, blocking, antibody hybridization, color development, dehydration and sealing, immunohistochemical staining sections of Ki-67, CHG, and CTGF were obtained. The section results can be directly observed and interpreted by an optical microscope, or the pathological sections can be scanned by a pathological section scanner, and the immunohistochemical staining results can be remotely interpreted using film reading software such as K-Viewer.

[0130] After scanning the IHC staining results, the quantitative analysis method for the expression of the three molecules Ki-67 / CHG / CTGF is defined as follows when reading the film: ① Definition of Ki-67 proliferation index (Ki-67%): Count the percentage of tumor cell nuclei with positive Ki67 expression in 100 tumor cell nuclei, select 4 fields of view of the whole slice to calculate Ki-67% and take the average value; ② CHG and CTGF expression are quantified using H-Score: H-score is an indicator used to evaluate the results of immunohistochemical staining, which comprehensively considers the two factors of positive cell proportion and staining intensity. The calculation formula of H-score: H-Score = ∑ (Pi × i) Where Pi refers to the proportion of cells with a certain intensity in positive cells, and i refers to the staining intensity, which is usually 0, 1, 2, and 3. The value range of H-score is set to 0 to 300, that is, each value is multiplied by 100, so that the maximum value of H-score is 300.

[0131] In this step, after the above-mentioned IHC staining, result scanning and reading, and expression evaluation, each ONB patient obtained their own Ki-67 (%) / CHG / CTGF quantitative expression. The proliferation index Ki-67% is a percentage ranging from 0 to 100%, and the CHG and CTGF expression H-Score is a score ranging from 0 to 300.

[0132] According to the instructions for the typing step in this technical method, the Ki67% value, CHG H-Score, and CTGF H-Score values ​​obtained in the previous step were used to determine the NBM typing of each ONB patient in the FFPE cohort (Appendix 3): (1) ONB with a high expression of Ki-67% (representing basal characteristics) was determined to be basal (i.e., Ki-67% ≥ 25%, regardless of the CHG or CTGF H-Score, it was determined to be basal). According to this standard, 10 cases numbered 1-10 in Appendix 3 can be determined as basal; (2) For the remaining 20 patients (Ki-67% < 25%), those with a high expression of neurogenic characteristics (i.e., CHG H-Score ≥ 75 points, regardless of CTGF H-Score high or low), it is determined to be a neural type ONB. According to this standard, 15 cases numbered 11-25 in Appendix 3 can be determined as neural type; (3) The remaining 5 patients are all basal type / neural type double negative cases with Ki-67% <25% and CHG H-Score <75 points, and only express interstitial characteristics (CTGF H-Score>0 points), so they can be determined as interstitial ONB. So far, all ONB cases involved in this embodiment have completed the ONB NBM three-type subtype determination proposed by the present invention through the simple classification method of ONB three-type.

[0133] Appendix 3 ONB typing results of validation set FFPE case cohort (N=30) using simple clinical classification method

[0134]

[0135] We calculated the Ki-67 index (ki67%), CHG and CTGF H-Score values ​​obtained by using the above method in the validation set data set, and performed the statistical efficacy of Neural / Basal / Mesenchymal subtype classification on the IHC staining result data of ONB patients, and evaluated them with ROC curve and area under the curve (AUC) value. The AUC values ​​of the scoring system involved in this patent for predicting the Basal subtype, Neural subtype and Mesenchymal subtype of ONB are 1, 0.96 and 1 respectively, showing a relatively good statistical predictive efficacy ( Fig.10 ), indicating good sensitivity and specificity.

[0136] 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.

[0137] 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.

[0138] In some embodiments, numbers describing the number of components and attributes are used. It should be understood that such numbers used in the description of the embodiments are modified by the modifiers "about", "approximately" or "substantially" in some examples. Unless otherwise specified, "about", "approximately" or "substantially" indicate that the numbers are allowed to vary by ±20%. Accordingly, in some embodiments, the numerical parameters used in the specification and claims are approximate values, which may change according to the required features of individual embodiments. In some embodiments, the numerical parameters should take into account the specified significant digits and adopt the general method of retaining digits. Although the numerical domains and parameters used to confirm the breadth of their range in some embodiments of this specification are approximate values, in specific embodiments, the setting of such numerical values ​​is as accurate as possible within the feasible range.

[0139] 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 variations may also fall within the scope of this specification. Therefore, as an example and not a limitation, alternative configurations of the embodiments of this specification may be considered 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 Ki-67 protein, CHG protein and CTGF protein or their detection products in the preparation of products for tumor subtype classification, wherein the tumor is olfactory neuroblastoma.

2. The use according to claim 1, characterized in that The detection object is the Ki-67 protein, CHG protein and CTGF protein expression detection object. Preferably, the detection object is selected from any one or more of antibodies, membrane strips, chips, probes or primer pairs.

3. The use according to claim 1, characterized in that The subtypes of olfactory neuroblastoma include basal olfactory neuroblastoma, neural olfactory neuroblastoma and mesenchymal olfactory neuroblastoma; And / or, the Ki-67 protein is a marker protein for basal olfactory neuroblastoma; And / or, the CHG protein is a marker protein of neuronal olfactory neuroblastoma; And / or, the CTGF protein is a marker protein of mesenchymal olfactory neuroblastoma.

4. A product for tumor subtype classification, the product comprising Ki-67 protein, CHG protein and CTGF protein and / or their detection substances, wherein the tumor is olfactory neuroblastoma.

5. The product according to claim 4, characterized in that The detection object is the Ki-67 protein, CHG protein and CTGF protein expression detection object. Preferably, the detection object is selected from any one or more of antibodies, membrane strips, chips, probes or primer pairs; and / or, the olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neurogenic olfactory neuroblastoma and mesenchymal olfactory neuroblastoma.

6. A marker for tumor subtype classification, the marker comprising Ki-67 protein, CHG protein and CTGF protein, the tumor is olfactory neuroblastoma, and the olfactory neuroblastoma subtypes include basal olfactory neuroblastoma, neural olfactory neuroblastoma and mesenchymal olfactory neuroblastoma.

7. 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 for providing expression information of a target marker of a sample to be tested, wherein the target marker is the marker for classification of olfactory neuroblastoma subtypes according to claim 6; A scoring module, used to score the subtype based on the expression information of the target marker of the sample to be tested; A judgment module is used to judge whether the subtype of olfactory neuroblastoma is basal, neural or mesenchymal based on the subtype score.

8. The olfactory neuroblastoma subtype detection device according to claim 7, characterized in that: Other features include: The expression information includes Ki-67, CHG and CTGF staining information based on FFPE white slides of tumor tissues of ONB patients, Preferably, the staining is immunohistochemical staining; And / or, the sample to be tested is a tumor tissue of a patient with olfactory neuroblastoma; And / or, the scoring module obtains the basal, neural, and mesenchymal tumor characteristic scores of patients with olfactory neuroblastoma based on the expression information of the target marker of the sample to be tested. Preferably, the scoring module calculates the proliferation index or H-score value of the target marker based on the Ki-67, CHG, and CTGF staining images of FFPE white slides of tumor tissues of ONB patients; And / or, the judgment module determines the subtype of olfactory neuroblastoma according to the following steps: When the Ki-67 proliferation index, which is characteristic of the basal type, is ≥25%, the olfactory neuroblastoma is judged to be basal type; When the Ki-67 proliferation index of basal type is <25% and the CHG H-Score of neural type tumor is ≥75 after standardization, It was determined that olfactory neuroblastoma was of the neuronal type; When the Ki-67 proliferation index of basal type is <25%, and the CHG H-Score of neural type tumor is <75 after standardization, and the CTGF H-Score of mesenchymal type tumor is >0, the olfactory neuroblastoma is judged to be mesenchymal type.

9. The olfactory neuroblastoma subtype detection device according to claim 8, characterized in that: The calculation formula of the H-score is H-Score=∑(Pi×i), where Pi refers to the proportion of cells with a certain intensity in positive cells, and i refers to the staining intensity; And / or, the value range of the H-score is 0 to 300; And / or, the Ki-67 proliferation index is the percentage of tumor cell nuclei positive for Ki67 expression among 100 tumor cell nuclei; And / or, the Ki-67 proliferation index is a percentage ranging from 0-100%.

10. 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: Acquiring expression information of a target marker of the sample to be tested, wherein the target marker is the marker for subtype classification of olfactory neuroblastoma according to claim 6; Based on the expression information of the target markers of the sample to be tested, the subtype is scored; The olfactory neuroblastoma subtype was determined to be basal, neural, or mesenchymal based on the subtype score.

11. The computer-readable storage medium of claim 10, wherein: Other features include: The expression information includes Ki-67, CHG and CTGF staining information based on FFPE white slides of tumor tissues of ONB patients, Preferably, the staining is immunohistochemical staining; And / or, the sample to be tested is a tumor tissue of a patient with olfactory neuroblastoma; And / or, based on the expression information of the target markers of the sample to be tested, obtaining the basal, neural, and mesenchymal tumor characteristic scores of the olfactory neuroblastoma patient; And / or, determine the subtype of olfactory neuroblastoma according to the following steps: When the Ki-67 proliferation index, which is characteristic of the basal type, is ≥25%, the olfactory neuroblastoma is judged to be basal type; When the Ki-67 proliferation index, which is characteristic of the basal type, is <25%, and the CHG H-Score, which is characteristic of the neural type tumor, is ≥75 points after standardization, the olfactory neuroblastoma is judged to be of the neural type; When the Ki-67 proliferation index of basal type is <25%, and the CHG H-Score of neural type tumor is <75 after standardization, and the CTGF H-Score of mesenchymal type tumor is >0, the olfactory neuroblastoma is judged to be mesenchymal type.

12. The computer-readable storage medium of claim 11, wherein: Other features include: Based on the Ki-67, CHG, and CTGF staining images of FFPE white slides of tumor tissue from ONB patients, the proliferation index or H-score value of the target marker was calculated; And / or, the calculation formula of the H-score is H-Score=∑(Pi×i), wherein Pi refers to the proportion of cells with a certain intensity in positive cells, and i refers to the staining intensity; And / or, the value range of the H-score is 0 to 300, that is, each value is multiplied by 100, so that the maximum value of the H-score is 300; And / or, the Ki-67 proliferation index is the percentage of tumor cell nuclei positive for Ki67 expression among 100 tumor cell nuclei; And / or, the Ki-67 proliferation index is a percentage ranging from 0-100%.

13. 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 described in any one of claims 10 to 12.

14. A computer program product comprising a computer program, characterized in that When the computer program is executed by a processor, the method for detecting olfactory neuroblastoma subtypes as described in the computer-readable storage medium according to any one of claims 10 to 12 is implemented.

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