Gene detection kit for neuroblastoma molecular typing and application

Abstract

The invention provides a gene detection kit for neuroblastoma molecular typing and application. Specifically, the invention provides a group of gene groups for determining molecular typing of neuroblastoma and / or evaluating survival risk of neuroblastoma patients, the molecular typing based on tissue transcriptome sequencing performs subgroup division on clinical NB child patients from the perspective of full bulk RNA-seq, and the system is more comprehensive compared with a grading system formed by previous research; the probability of occurrence of adverse events such as metastasis, relapse and death of different individual child patients can be predicted during definite diagnosis of tumors, a current clinical risk level grading system is assisted, and accurate recognition of atypical high-risk child patients such as MYCN non-amplification and decision making of an early upgrading treatment strategy are achieved; the method is helpful for individualized selection of a novel immunotherapy scheme for recurrent refractory high-risk patients and improvement of treatment results.

Description

Technical Field

[0001] This invention relates to the field of biomedicine, specifically to a gene detection kit for molecular subtyping of neuroblastoma and its uses. Background Technology

[0002] Neuroblastoma (NB) is an embryonic solid tumor originating from the peripheral sympathetic nervous system, accounting for 10% of childhood cancers. According to the Childhood Oncology Group (COG) risk classification system, patients are categorized into different risk groups based on clinical characteristics such as age, International Neuroblastoma Staging System (INRGSS), and MYCN gene status, and treatment plans are developed accordingly. Although the prognosis of low- and intermediate-risk NB patients has significantly improved with comprehensive treatment regimens including surgery and chemotherapy, the overall 5-year survival rate for high-risk NB patients with relapsed or refractory disease remains below 40%, making it one of the most difficult childhood solid tumors to treat.

[0003] NB (nephropathy of prematurity) is believed to result from impaired cell differentiation during sympathetic-adrenal gland development due to various internal and external factors, ultimately leading to abnormal development. Clinically, NB patients exhibit high heterogeneity, and a thorough understanding of the tumor development mechanisms corresponding to different clinical patient groups is crucial for precision medicine of NB. In recent years, researchers have strived to classify NB patients at the epigenetic level, hoping to reveal the differences in tumor origin and progression among different clinical patient groups by leveraging the characteristic developmental trajectory of NB. Ackermann et al. studied the telomere maintenance mechanism and RAS / p53 pathway mutations in NB and proposed a corresponding clinical classification system for NB based on these two epigenetic features, optimizing the diagnosis and treatment process. Gartlgruber et al. identified four major epigenetic subtypes of NB driven by super-enhancers. These two representative cancer biology studies, from different epigenetic perspectives, have successfully built a bridge between the occurrence, development, and clinical characteristics of NB, which is of great significance for early diagnosis and prognostic assessment. However, current treatment outcomes for NB remain unsatisfactory.

[0004] Therefore, a more accurate and comprehensive risk stratification system needs to be introduced to assist clinicians in understanding the decision-making significance of different NB patient groups in dealing with emerging new treatment options under the current COG risk classification system, so as to guide the individualized and precision treatment of tumors. Summary of the Invention

[0005] The purpose of this invention is to provide a gene combination and application for molecular subtyping of neuroblastoma based on transcriptome sequencing, which can be applied to molecular diagnosis and liquid biopsy of all neuroblastoma tumor tissue bulk RNA-seq.

[0006] A first aspect of the present invention provides a set of genes for determining the molecular subtyping of neuroblastoma and / or assessing the survival risk of neuroblastoma patients, including (but not limited to) genes selected from the following group: MMP9, ANKRD20A19P, FAR2P1, MUC15, C1QTNF9B, FAM153B, LINC01297, SLCO1A2, MAGEA4, CCDC144NL-AS1, PAGE5, DDX1, MYCN, GAS5, RPS3, SOX11, RPL39, RPL29, NPM1, RPS24, RPL32, LDHB, RPS17, EF1B2, RPS 2. PRSS12, RPL18A, RPL9, RPL31, RPS11, NCAN, RPL36, LRRC75A-AS1, RPS3A, RPL34, RPL36A, RPS4X, RPL13, RPS25, DUSP4, ODC1, RPL17, RPS15A , RPS23, RPSA, RPL7A, RPL12, HNRNPA1, GNB2L1, RPS14, RPL6, RPS7, RPL14, RPL35A, RPL23, RPL4, RPS13, HSPD1, SLIT1, RPL18, RPL37A, RPS21, R PS15, SLC25A6, RPL37, NME1-NME2, RPL7, RPL23A, RPL13A, RPS5, PHGDH, RPL26, EEF1G, RPS18, NFIB, RPS16, RPLP1, B4GALNT4, SNHG1, TOMM20, AMH, PAICS, NACA, CCNI, EIF4A1, RPL3, RPLP0, RPS9, RPS27, NME1, RPL41, TRAP1, CBS, EIF3L, RPL10, CCNB1IP1, MEX3A, RPL23AP42, RPL10A, ADG RA3, CAMKV, TMEM97, FBL, AHCY, IMPDH2, CPNE7, PTPRS, TAF1D, LAPTM4B, RPL15, NCL, ZFAS1, TKT, PPA1, AL589743.1, HOXD10, CACNA1E, EIF4B, RBMX, HOXD9, LRPPRC, MTHFD2, ILF3, EEF1B2, FAM153A, ADCY1, ALCAM, NTRK1, CADM1, CAMK4, CLU, AHNAK, CALCA, CD59, CRYAB, MPZ, S100B and PIRT.

[0007] In another preferred embodiment, the gene group also includes neuroblastoma immunotherapy target genes: B4GALNT1, ST8SIA1, B7H3, ALK, and L1CAM.

[0008] In another preferred embodiment, the gene group also includes neuroblastoma immune checkpoint inhibitor genes: PDCD1, CD274, CTLA4, and LAG3.

[0009] In another preferred embodiment, the neuroblastoma molecular subtyping includes distinguishing neuroblastoma subgroups.

[0010] In another preferred embodiment, the neuroblastoma subgroups include the MYCN-amplified high-risk neuroblastoma subgroup (HR1), the MYCN-non-amplified high-risk neuroblastoma subgroup (HR2), the intermediate-low-risk neuroblastoma subgroup (LR1), and the intermediate-low-risk ganglioneuroma subgroup (LR2).

[0011] In another preferred embodiment, the neuroblastoma molecular subtyping indicates the risk of tumor recurrence and metastasis in neuroblastoma patients.

[0012] In another preferred embodiment, the incidence of adverse events in the MYCN-amplified high-risk neuroblastoma subgroup and the MYCN-non-amplified high-risk neuroblastoma subgroup was significantly higher than that in the intermediate- and low-risk neuroblastoma subgroup and the intermediate- and low-risk ganglioneuroma subgroup.

[0013] In another preferred embodiment, the characteristic genes in the high-risk neuroblastoma subgroup amplified by MYCN include: MYCN, DDX1, LDHB, EEF1B2, and GAS5.

[0014] In another preferred embodiment, the MYCN does not amplify characteristic genes in the high-risk neuroblastoma subgroup, including: MUC15, FAM153A, FAM153B, and SLCO1A2.

[0015] In another preferred embodiment, the characteristic genes in the intermediate- and low-risk neuroblastoma subgroup include: ADCY1, ALCAM, NTRK1, CADM1, and CAMK4.

[0016] In another preferred embodiment, the characteristic genes in the intermediate- and low-risk ganglioneuroma subgroup include: CLU, AHNAK, CALCA, CD59, and CRYAB.

[0017] In another preferred embodiment, the gene group comprises or is composed of the following characteristic genes:

[0018] (1) MYCN amplification of characteristic genes of high-risk neuroblastoma subgroup: MYCN, DDX1, LDHB, EEF1B2, GAS5;

[0019] (2) MYCN does not amplify characteristic genes of the high-risk neuroblastoma subgroup: MUC15, FAM153A, FAM153B, SLCO1A2;

[0020] (3) Characteristic genes of the intermediate- and low-risk neuroblastoma subgroup: ADCY1, ALCAM, NTRK1, CADM1, CAMK4 and PIRT;

[0021] (4) Characteristic genes of the intermediate- and low-risk ganglioneuroma subgroup: CLU, AHNAK, CALCA, CD59, CRYAB, S100B, MPZ.

[0022] A second aspect of the invention provides the use of a combination of detection reagents for the gene population described in the first aspect of the invention for preparing a detection kit to determine the molecular subtyping of neuroblastoma (NB) and / or assess the prognosis of neuroblastoma patients.

[0023] In another preferred embodiment, the neuroblastoma molecular subtyping includes distinguishing neuroblastoma subgroups.

[0024] In another preferred embodiment, the neuroblastoma subgroup consists of a MYCN-amplified high-risk neuroblastoma subgroup, a MYCN-non-amplified high-risk neuroblastoma subgroup, an intermediate-low-risk neuroblastoma subgroup, and an intermediate-low-risk ganglioneuroma subgroup.

[0025] In another preferred embodiment, the neuroblastoma molecular subtyping indicates the risk of tumor recurrence and metastasis in neuroblastoma patients.

[0026] In another preferred embodiment, the kit includes instructions for use, which state:

[0027] If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the MYCN amplified high-risk neuroblastoma subgroup (HR1 group): MYCN, DDX1, LDHB, EEF1B2, GAS5;

[0028] If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the MYCN non-amplified high-risk neuroblastoma subgroup (HR2 group): MUC15, FAM153A, FAM153B, SLCO1A2;

[0029] If high expression of genes selected from the following groups is detected, it suggests that the patient belongs to the intermediate- or low-risk neuroblastoma subgroup (LR1 group): ADCY1, ALCAM, NTRK1, CADM1, CAMK4; and

[0030] If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the intermediate-low risk ganglioneuroma subgroup (LR2 group): CLU, AHNAK, CALCA, CD59, CRYAB.

[0031] In another preferred embodiment, the kit includes instructions for use, which further specify:

[0032] (1) If a patient is detected to belong to the HR2 group, it suggests that the patient is more suitable for immunotherapy targeting genes selected from the following groups compared to the HR1 group: GD2, PD1, PD-L1, CTLA4; and / or

[0033] (2) If the patient is detected to belong to the LR1 group, it suggests that the patient is more suitable for immunotherapy targeting genes selected from the following groups compared to the LR2 group: GD2, B7H3, ALK, LAG3;

[0034] (3) If the patient is detected to belong to the LR2 group, it suggests that the patient is more suitable for immunotherapy targeting genes selected from the following groups compared to the LR1 group: PD1, PD-L1.

[0035] In another preferred embodiment, the detection reagent is a detection reagent suitable for bulk RNA-seq.

[0036] In a third aspect, the present invention provides a reagent combination for detecting the expression level of genes in the gene population described in the first aspect of the present invention.

[0037] In another preferred embodiment, the reagent is a reagent for detecting the amount of RNA, mRNA, or cDNA complementary to the mRNA transcribed from the gene.

[0038] In another preferred embodiment, the reagent is a primer, a probe, or a combination thereof.

[0039] In a fourth aspect, the present invention provides a product for molecular subtyping and / or survival risk assessment of neuroblastoma, comprising the reagent combination described in the third aspect of the present invention.

[0040] In another preferred embodiment, the product is used to determine the molecular subtyping of neuroblastoma and / or assess the survival risk of neuroblastoma patients.

[0041] In another preferred embodiment, the product is in the form of an in vitro diagnostic product.

[0042] In another preferred embodiment, the product is in the form of a diagnostic kit.

[0043] In another preferred embodiment, the product is a next-generation sequencing kit, a real-time quantitative PCR detection kit, or a gene chip.

[0044] In a fifth aspect of the invention, a predictive apparatus is provided for determining the molecular subtype of neuroblastoma in a patient using the gene population described in the first aspect of the invention, the apparatus comprising:

[0045] S1) Input module, the input module being used to input the gene population expression level from the sample of the patient;

[0046] S2) Data analysis module, which is used to predict the molecular subtype of neuroblastoma based on the input gene population expression level;

[0047] S3) Output module, which is used to output the prediction results.

[0048] In another preferred embodiment, the data analysis module predicts the molecular subtype of neuroblastoma according to the following rules:

[0049] If high expression of genes selected from the following groups is detected, it suggests that the patient has MYCN amplified high-risk neuroblastoma: MYCN, DDX1, LDHB, EEF1B2, GAS5;

[0050] If high expression of genes selected from the following groups is detected, it suggests that the patient has MYCN non-amplified high-risk neuroblastoma: MUC15, FAM153A, FAM153B, SLCO1A2;

[0051] High expression of genes selected from the following groups suggests that the patient has intermediate- to low-risk neuroblastoma: ADCY1, ALCAM, NTRK1, CADM1, CAMK4; and

[0052] If high expression of genes selected from the following groups is detected, it suggests that the patient has intermediate- or low-risk ganglioneuroma: CLU, AHNAK, CALCA, CD59, CRYAB.

[0053] It should be understood that, within the scope of this invention, the above-described technical features of this invention and the technical features specifically described below (such as in the embodiments) can be combined with each other to form new or preferred technical solutions. Due to space limitations, they will not be described in detail here. Attached Figure Description

[0054] Figure 1The figures shown are the results of using the Treehouse neuroblastoma training dataset in one embodiment of the present invention. Figure A shows the cluster distribution scatter plot of the Treehouse neuroblastoma training dataset, where 0-4 represent the five clusters of neuroblastoma samples—Group0 / 1 / 2 / 3 / 4—selected by the MLP model after training. Figure B shows the heatmap of subgroup characteristic gene expression in the Treehouse neuroblastoma training dataset. Figure C shows the subgroup characteristic genes verified by qPCR. Figure D shows the expression of subgroup characteristic genes at the transcriptome level in the four subgroups.

[0055] Figure 2 This displays the 2021 COG neuroblastoma risk grading system.

[0056] Figure 3 The chart shown is a summary of pathological types, MYCN status, and COG risk grading characteristics from the NB cohort of Shanghai Children's Medical Center in this embodiment of the invention.

[0057] Figure 4 This diagram illustrates the clinical definition of neuroblastoma molecular subtypes in an embodiment of the present invention.

[0058] Figure 5 The image shown is a result of qPCR verification of some genes in an embodiment of the present invention. The horizontal axis 0+4 represents subgroup 0 and subgroup 4 in NB molecular typing; 1-3 represent subgroups 1-3 in NB molecular typing, respectively.

[0059] Figure 6 The image shown is a bar chart illustrating the recurrence and metastasis rates of neuroblastoma molecular subtypes in this embodiment of the invention.

[0060] Figure 7 The figure shown is the KM survival curve of the neuroblastoma molecular subtype subgroup in this embodiment of the invention.

[0061] Figure 8 The diagram shows the bulk RNA-seq expression box plots of immunotherapy-related genes in four subgroups in this embodiment of the invention, including key enzyme genes for GD2 synthesis (B4GALNT1, ST8SIA1) and key immune checkpoint genes (PD1, PD-L1, B7-H3, CTLA4, L1CAM, LAG3).

[0062] Figure 9 The figure shown is a box plot of immunofluorescence staining and subgroup positive cell number distribution, using GD2 as an example in this embodiment of the invention.

[0063] Figure 10The figure shown is a box plot of immunofluorescence staining and subgroup positive cell number distribution, using PD1 and CD8 as examples in this embodiment of the invention.

[0064] Figure 11 The figures shown are box plots and bar charts illustrating the distribution of positive cell counts in subgroups using CTLA4 as an example in this embodiment of the invention. Detailed Implementation

[0065] Through extensive and in-depth research, the inventors have developed a method for accurately classifying the risk of neuroblastoma (NB) patients in the early stages of clinical practice using only readily available and cost-effective tumor tissue transcriptome sequencing, without relying on expensive methods such as single-cell sequencing or whole-genome sequencing. This invention uses molecular typing based on tissue transcriptome sequencing to subgroup clinical NB patients from a bulk RNA-seq perspective, rather than relying on relatively limited single epigenetic characteristics, making it more comprehensive than previous classification systems. Based on this model, the probability of adverse events such as metastasis, recurrence, and death can be predicted for different individual patients at the time of tumor diagnosis, assisting the current clinical risk classification system in accurately identifying atypical high-risk patients such as those with non-amplified MYCN and in making decisions on early escalation treatment strategies. Compared to ordinary clinical risk classification features, this model can specifically identify the expression of potential immune checkpoints such as GD2, PD1, and CTLA4 in the patient's tumor tissue, helping to individualize the selection of novel immunotherapy regimens for relapsed / refractory high-risk patients and improve treatment outcomes.

[0066] the term

[0067] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains. As used herein, when referring to a specifically enumerated numerical value, the term “about” means that the value can vary from the enumerated value by no more than 1%. For example, as used herein, the expression “about 100” includes all values ​​between 99 and 101 (e.g., 99.1, 99.2, 99.3, 99.4, etc.).

[0068] Neuroblastoma (NB)

[0069] Neuroblastoma (NB) is an embryonic solid tumor originating from the peripheral sympathetic nervous system, accounting for 10% of childhood cancers. According to the Childhood Oncology Group (COG) risk classification system, patients are categorized into different risk groups based on clinical characteristics such as age, International Neuroblastoma Staging System (INRGSS), and MYCN gene status, and treatment plans are developed accordingly. Although the prognosis of low- and intermediate-risk NB patients has significantly improved with comprehensive treatment regimens including surgery and chemotherapy, the overall 5-year survival rate for high-risk NB patients with relapsed or refractory disease remains below 40%, making it one of the most difficult childhood solid tumors to treat.

[0070] MYCN gene

[0071] The MYCN gene, in its haploid state in normal humans, is located on the distal short arm of chromosome 2 (2p23-24), consisting of three exons separated by two introns. The expressed protein, N-myc, is approximately 62-64 kDa, located in the cell nucleus, and has a half-life of approximately 30-50 minutes. The MYCN protein is a helix-loop-helix / leucine zipper (HLH / LZ) structure, forming a complex heterodimer with MAX. It has a high affinity for the CACGTG (E-box MYC site) sequence but low affinity for many non-classical DNA sequences. Like other proteins in the MYC family, MYCN is a transcription factor that regulates the expression of multiple target genes, thereby regulating various cellular functions such as cell proliferation, cell growth, protein synthesis, cell metabolism, cell invasion and metastasis, apoptosis, and differentiation. Approximately 25%–30% of neuroblastoma patients have MYCN gene amplification, mostly in advanced stages, with poor treatment outcomes and generally poor prognosis. In most cases, the higher the fold increase in MYCN, the worse the prognosis. In high-risk neuroblastomas, about 40% highly express MYCN. Consistently high MYCN expression can be detected in neuroblastoma tissues taken from different sites or at different stages from diagnosis to recurrence, indicating that high MYCN expression is a stable and inherent characteristic of high-risk neuroblastomas.

[0072] MYCN gene amplification

[0073] In neuroblastoma, the MYCN gene mutation is typically gene amplification—meaning that in neuroblastoma tumor cells with this mutation, the number of MYCN genes is much higher than in normal cells. This amplification prevents tumor cells from dying naturally, making them more malignant and harder to eradicate.

[0074] In neuroblastoma, once MYCN gene amplification is detected, the patient is classified as high-risk and treated according to the high-risk neuroblastoma protocol.

[0075] Transcriptome sequencing (RNA-seq)

[0076] The transcriptome, broadly speaking, refers to the collection of all transcribed products within a cell under a given physiological condition, including messenger RNA, ribosomal RNA, transfer RNA, and non-coding RNA; narrowly speaking, it refers to the collection of all mRNAs. Proteins are the primary carriers of cellular function, and the proteome is the most direct description of cellular function and state. The transcriptome, as the main means of studying gene expression, is the essential link between genomic genetic information and the proteome of biological function. Regulation at the transcriptional level is currently the most studied and is also the most important regulatory mechanism in organisms.

[0077] Transcriptome sequencing (RNA-Seq) studies the sum of all mRNAs that a specific cell can transcribe under a given functional state. Next-generation high-throughput sequencing technologies can comprehensively and rapidly obtain almost all transcript sequence information of a specific tissue or organ of a species under a given state, thereby accurately analyzing important life science issues such as gene expression differences, gene structural variations, and screening for molecular markers (SNPs or SSRs).

[0078] The main advantages of this invention are:

[0079] (1) This invention does not rely on expensive methods such as single-cell sequencing and whole-genome sequencing. It can accurately classify the risk of neuroblastoma patients in the early stage by relying solely on the relatively economical and readily available tumor tissue transcriptome sequencing in clinical practice.

[0080] (2) Molecular typing based on tissue transcriptome sequencing divides clinical NB patients into subgroups from the perspective of whole bulk RNA-seq, rather than based on a relatively one-sided single epigenetic feature, which is more comprehensive than the grading system formed by previous studies.

[0081] (3) Based on the molecular subtyping model provided by the present invention, the probability of adverse events such as metastasis, recurrence and death of different individual children can be predicted when the tumor is diagnosed. It can assist the current risk grading system used in clinical practice and realize the accurate identification of atypical high-risk children such as those with non-MYCN amplification and the decision-making of early upgrade treatment strategies.

[0082] (4) Compared with ordinary clinical risk grading features, this model can specifically identify the expression of potential immune checkpoints such as GD2, PD1, and CTLA4 in the tumor tissue of children, which helps to select new immunotherapy regimens for individualized treatment of relapsed and refractory high-risk patients and improve treatment outcomes.

[0083] The present invention will be further illustrated below with reference to specific embodiments. It should be understood that these embodiments are for illustrative purposes only and are not intended to limit the scope of the invention. Experimental methods in the following embodiments, unless otherwise specified, are generally performed under conventional conditions, such as those described in Sambrook et al., Molecular Cloning: A Laboratory Manual (New York: Cold Spring Harbor Laboratory Press, 1989), or as recommended by the manufacturer. Unless otherwise stated, percentages and parts are weight percentages and parts by weight.

[0084] Unless otherwise specified, all experimental materials and reagents used in the following examples are available from commercially available sources.

[0085] Example 1: Molecular subtyping of neuroblastoma based on transcriptome sequencing

[0086] This embodiment uses a dataset consisting of bulk RNA-Seq data from 201 NB patients in the UCSC Treehouse database as the training set. The expression matrix is ​​normalized using the "ScaleData" function in the Seurat R package with default parameters, and the "FindVaribleFeatures" function with the "vst" method is used to identify the top N highly variable features. To allow for efficient unsupervised clustering using Leiden, the inventors extracted the top N principal components to construct an N-dimensional neighborhood graph. In unsupervised clustering, Leiden clustering is calculated using an ND neighborhood graph with a resolution of X. The cluster identifier of the Leiden cluster is used as a label for molecular subtyping.

[0087] The inventors subsequently used a multi-layer perceptron (MLP) model to construct molecular subtyping. This model is a sequential model built using Keras and has the following layers:

[0088] (1) A dense layer with N dimensions and L1 regularization is used to load the input representation data. The activation function of this layer is ReLU;

[0089] (2) A dropout layer with a dropout rate of 0.000001;

[0090] (3) A 90-dimensional dense layer with ReLU activation function;

[0091] (4) A 60-dimensional dense layer with ReLU activation function;

[0092] (5) A dense layer with 5 dimensions and the activation function is Softmax. This layer outputs the predicted probability of each cluster.

[0093] Next, this MLP model was compiled using the "categorical_corssentropy" loss function and the Adam optimizer. Accuracy was monitored throughout the training process. Training consisted of 40 epochs with a batch size of 80. The training history was plotted using matplotlib. Twenty model replicates were trained, and models with training and validation accuracy exceeding 0.85 were saved for later quality assessment. The neuroblastoma samples were then divided into 5 clusters using the selected MLP model after training—Group 0 / 1 / 2 / 3 / 4 (…). Figure 1 A).

[0094] Finally, differentially expressed genes were identified in each subgroup of the five clusters through differential gene expression analysis; these are the genes relevant to each subgroup in the molecular subtyping. The expression of some key genes in the subgroups of the five clusters is shown below. Figure 1 The heatmap for B is shown below; the characteristic genes of each subgroup of molecular subtyping are arranged according to weighting factors as follows:

[0095] The characteristic genes of subgroup 1 (Group 1) are: ADCY1, ALCAM, NTRK1, CADM1, and CAMK4;

[0096] The characteristic genes of subgroup 2 (Group 2) are: MYCN, DDX1, LDHB, EEF1B2, and GAS5;

[0097] The characteristic genes of subgroup 3 are: CLU, AHNAK, CALCA, CD59, and CRYAB;

[0098] The characteristic genes of subgroup 04 (Group 0 and Group 4) are: MUC15, FAM153A, FAM153B, and SLCO1A2.

[0099] Example 2: Comparison of the effects of the present invention's NB molecular typing and the traditional NB risk classification standard

[0100] 1. Traditional Notebook Risk Classification Standard

[0101] Currently, the commonly used clinical risk stratification criteria for neuroblastoma patients often follow the revised COG risk stratification criteria issued by the Children's Oncology Group (COG) in 2021. This standard integrates multiple clinical indicators for NB patients, including age, INSS stage, MYCN status, 1p and / or 11q status, International Neuroblastoma Pathology Classification (INPC) category, imaging risk factors, pathological type (differentiation grade - mitotic index MKI), and segmental chromosomal aberrations (1p and / or 11q status), systematically classifying NB patients into four subgroups: very low risk, low risk, intermediate risk, and high risk (e.g., very low risk, low risk, intermediate risk, high risk). Figure 2 (As shown).

[0102] 2. Examination of the clinical significance of NB molecular subtyping

[0103] The initial molecular typing was based solely on bulk RNA-seq data from tumor tissues of 201 neuroblastoma patients in an online database, lacking supporting clinical information. Therefore, to further clarify whether each molecular subgroup has corresponding clinical significance, this embodiment constructed a validation cohort using 112 neuroblastoma patients from Shanghai Children's Medical Center. Molecular typing also divided the NB patients in the cohort into five subgroups: Group 0, Group 1, Group 2, Group 3, and Group 4.

[0104] Based on multiple clinical indicators of patients in the comprehensive cohort, the inventors found significant differences in COG risk grading, MYCN gene status, and pathological type among subgroups. Figure 3 Based on the observation results of subgroup clinical characteristics, both Group 0 and Group 4 were classified as high-risk for COG and both were classified as neuroblastoma (without ganglion cell components) in pathology. Furthermore, the MYCN gene was not amplified in either group. Therefore, in order to correspond to a specific clinical patient population, this invention grouped Group 0 and Group 4 together and conducted subsequent subgroup difference analysis.

[0105] The distribution of the three clinical features among the subgroups was then analyzed using chi-square and Fisher's exact tests. First, Group 04 / 2 was grouped into one group, and Group 1 / 3 into another. Then, a class association analysis was performed between these two groups.

[0106] The results showed that the two groups differed in COG risk stratification (P=0.000, χ2=48.548), MYCN gene amplification (P=0.000, χ2=12.874), and pathological type (P=0.001, χ2=11.955).

[0107] Next, the above metrics were further compared between Group04 and Group2, as well as between Group1 and Group3.

[0108] The results showed that Group 0 and Group 2 had no significant differences in risk stratification (P = 1.000, χ² = 0.678) and pathological type (P = 0.000), but a significant difference in MYCN gene status (P = 0.001). Similarly, Group 1 and Group 3 had no differences in COG risk stratification (P = 0.205, χ² = 1.603) and MYCN gene status (P = 1.000, χ² = 0.000), but a significant difference in pathological type (P = 0.000, χ² = 53.182).

[0109] Based on the above test results, the inventors successfully categorized the five groups into four corresponding clinical subgroups: Group 2 consists of high-risk NBs with MYCN amplification (HR1); Groups 0 and 4 (subgroup 04) together consist of high-risk NBs without MYCN amplification (HR2); Group 1 consists of low-to-intermediate-risk NBs (LR1); and Group 3 consists of low-to-intermediate-risk NBs containing ganglion cell components (LR2). Figure 4 ).

[0110] Therefore, MYCN amplification was used to identify high-risk neuroblastoma (subgroup 2, characteristic genes: MYCN, DDX1, LDHB, EEF1B2, GAS5), MYCN non-amplification was used to identify high-risk neuroblastoma (subgroup 04, characteristic genes: MUC15, FAM153A, FAM153B, SLCO1A2), intermediate- to low-risk neuroblastoma (subgroup 1, characteristic genes: ADCY1, ALCAM, NTRK1, CADM1, CAMK4), and intermediate- to low-risk ganglioblastoma (subgroup 3, characteristic genes: CLU, AHNAK, CALCA, CD59, CRYAB). The results of some of these gene amplifications were verified by qPCR. Figure 1 C and Figure 5 As shown, the transcriptomic expression levels of characteristic genes in each subgroup are compared to, for example... Figure 1 The box plot is shown in Figure D.

[0111] 3. Comparison of the effectiveness of NB molecular typing and traditional COG hazard classification standards

[0112] The molecular subtyping of neuroblastoma (NB) in this invention was compared with the gold standard of traditional COG risk subtyping. The results are shown in Table 1:

[0113] Table 1

[0114]

[0115] Table 1 shows that for high-risk NB detection, the NB molecular typing of this invention has a sensitivity of 0.65 (30 / 46 = 0.65) and a specificity of 0.94 (62 / 66 = 0.94). The inventors found that because the LR2 group is the undifferentiated mesenchymal NB group, previous studies reported that some patients in this subgroup had poor prognoses. Therefore, the proportion of high-risk NBs (HR-NBs) in this subgroup was higher than that in the LR1 group. However, for ease of differentiation, molecular typing considered LR1 and LR2 as broad subgroups of intermediate and low risk, resulting in a decrease in sensitivity. However, in the HR1 / 2 group, molecular typing, based solely on bulk RNA-seq data, identified 30 high-risk patients out of 34 patients with high specificity, possessing significant clinical reference value and serving as a supplement to existing clinical standards.

[0116] Example 3 Clinical Validation

[0117] In addition to the chi-square test and Fisher's exact test in Example 2 above, the clinical validation of the NB molecular subtyping model also includes adverse event ratios and survival analysis for each subgroup.

[0118] Statistical analysis of the number of tumor recurrence and metastasis events in NB patients during initial diagnosis and subsequent follow-up revealed that the incidence of adverse events was significantly higher in the HR1 and HR2 groups than in the LR1 and LR2 groups. Figure 6 This further confirms the classification results of poor prognosis for NB patients in the HR1 and HR2 groups.

[0119] Survival analysis employed the log-rank test, and KM survival curves were plotted. Results showed that the survival outcomes of the HR1 and HR2 groups were significantly worse than those of the LR1 and LR2 groups, but no statistically significant differences were found between these two subgroups. Figure 7 This result suggests that after identifying the HR1 and HR2 subgroups through molecular typing, treatment regimens should be appropriately upgraded to improve patient outcomes.

[0120] Example 4 Histological Verification

[0121] In addition to the clinical-level validation described in Example 3 above, this example predicts the immunotherapy efficacy for different subgroups of patients in the cohort.

[0122] First, based on bulk RNA-seq of the NB patient cohort at Shanghai Children's Medical Center, we conducted intergroup expression comparison analysis of key GD2 synthesis genes (ST8SIA1, B4GALNT1) and immune checkpoint genes (PD1, PD-L1, LAG3, CTLA4, B7-H3, L1CAM), and used t-tests for difference analysis.

[0123] The results indicated that in the high-risk (HR2) group without MYCN amplification, the expression of ST8SIA1, PD-1, PD-L1, and CTLA4 was significantly higher than that in the high-risk (HR1) group with MYCN amplification. Figure 8 This suggests that the atypical high-risk group, where this treatment method is currently relatively scarce, may have a better response to GD2 monoclonal antibodies and immune checkpoint blockade therapy.

[0124] Therefore, the inventors chose immunofluorescence staining, randomly selecting 6 NB specimens from each subgroup of the sample bank for GD2, CD8, PD1, and CTLA4 staining verification. The results showed that GD2-positive cells ( Figure 9 ), CD8 positive cells ( Figure 10 ), CTLA4 positive cells ( Figure 11 The number and proportion of PD1 positive cells were higher in the PD1 group than in the HR1 group, but the number of PD1 positive cells was lower. Figure 10 No significant differences were observed among the four subgroups. This suggests that anti-GD2 monoclonal antibody therapy may also yield good efficacy for high-risk neuroblastomas without MYCN gene amplification. Although immunofluorescence staining did not reveal a difference in PD1 expression between HR1 and HR2, this may be related to the low immunogenicity of neuroblastomas. Combined with previous literature reports that CTLA4 antibody can upregulate low PD-L1 expression in MYCN-non-amplified neuroblastomas (NBs) and thereby activate CD8+, which has tumor-killing effects... + CD28 + PD1 + T cells, this part of the study confirmed that CD8 in the HR2 group + T cells and PD1 + CD8 + The infiltration of T cells was significantly higher in the HR2 group than in the HR1 group, suggesting that combined anti-CTLA4 and anti-PD1 / PD-L1 therapy in HR2 could activate a more durable anti-tumor immune effect.

[0125] This embodiment validated the results of bioinformatics analysis at the histological level, further confirming that anti-GD2 therapy and anti-CTLA4 immune checkpoint blockade therapy may yield better efficacy in the high-risk NB subgroup where MYCN is not amplified.

[0126] discuss

[0127] This invention discloses a gene combination and application for molecular subtyping of neuroblastoma based on transcriptome sequencing. It includes the combination of all relevant genes for neuroblastoma molecular subtyping obtained from current big data models based on transcriptome sequencing results, a stratified molecular subtyping scheme, the combination of characteristic genes for each group of the molecular subtyping, and the application scope of this molecular subtyping. The combination of all relevant genes for neuroblastoma molecular subtyping obtained from current big data models based on transcriptome sequencing results was constructed using bulk RNA-seq data from tumor tissues of 201 neuroblastoma patients in an online database and validated by a cohort of over 100 neuroblastoma patients from Shanghai Children's Medical Center. The subgroup scheme for molecular subtyping was constructed by a big data model after autonomous learning and optimization, and validated by internal and clinical data. It can be divided into four subgroups based on prognosis. The combination of characteristic genes for each subgroup of the molecular subtyping is obtained by arranging the characteristic genes of each subgroup according to weighting factors, with each subgroup containing five characteristic genes.

[0128] The aforementioned molecular subtyping immunotherapy characteristic gene combination includes, but is not limited to, NB immunotherapy target genes and immune checkpoint inhibitory genes. The application scope of this molecular subtyping, based on published literature, is applicable to molecular diagnosis and liquid biopsy using bulk RNA-seq of all neuroblastoma tumor tissues. It reveals the correlation between neuroblastoma molecular subtyping and risk grouping, disease prognosis, and immunotherapy efficacy. It can obtain precise prognostic information such as risk staging and potential treatment outcomes, assisting in optimizing the clinical risk grading system. This enables early identification of characteristic genes and adjustment of standard treatment decisions for atypical high-risk NB patients. Simultaneously, it allows for individualized assessment of the potential efficacy of anti-GD2 monoclonal antibody therapy and the potential efficacy of immune checkpoint blockade therapies such as anti-PD1 and anti-CTLA4, guiding the development of precision treatment regimens such as novel combination immunotherapies.

[0129] Clinically, children with neuroblastoma undergo surgery at various stages, including early-stage pre-chemotherapy biopsy, post-chemotherapy complete resection, and recurrence of metastatic lesions. The resulting neuroblastoma tumor tissue is sent for relatively inexpensive and readily available whole-transcriptome sequencing. The bulk RNA-seq data is then used for molecular typing using this patented invention, yielding subgroup typing tags. Molecular typing provides precise risk staging, potential treatment outcomes, and predictions of immunotherapy efficacy. Combined with the current clinical COG risk grading system, this model focuses on identifying atypical high-risk patients without MYCN gene amplification, enabling timely decisions to upgrade standard treatment regimens in the early stages of the disease. Simultaneously, this model predicts the immune response of children to novel anti-GD2 monoclonal antibody therapy, assisting in the individualized selection of this relatively expensive treatment option for children with relapsed or refractory neuroblastoma. Furthermore, this model has predictive efficacy for immune checkpoint inhibitors such as PD1 and CTLA4, and can be used as an evaluation tool for future combination therapy of immune checkpoint inhibitors. The characteristic genes of the high-risk subgroups identified by this model can be used in the future to construct a liquid biopsy gene platform for children with neuroblastoma, thereby improving the accuracy of early diagnosis.

[0130] All documents mentioned in this invention are incorporated herein by reference as if each document were individually incorporated by reference. Furthermore, it should be understood that after reading the foregoing teachings of this invention, those skilled in the art can make various alterations or modifications to this invention, and these equivalent forms also fall within the scope defined by the appended claims.

Claims

1. A set of genes for determining the molecular subtype of neuroblastoma and / or assessing the survival risk of a neuroblastoma patient, characterized in that, comprises a gene selected from the group consisting of MMP9, ANKRD20A19P, FAR2P1, MUC15, C1QTNF9B, FAM153B, LINC01297, SLCO1A2, MAGEA4, CCDC144NL-AS1, PAGE5, DDX1, MYCN, GAS5, RPS3, SOX11, RPL39, RPL29, NPM1, RPS24, RPL32, LDHB, RPS17, EF1B2, RPS2, PRSS12, RPL18A, RPL9, RPL31, RPS11, NCAN, RPL36, LRRC75A-AS1, RPS3A, RPL34, RPL36A, RPS4X, RPL13, RPS25, DUSP4, ODC1, RPL17, RPS15A, RPS23, RPSA, RPL7A, RPL12, HNRNPA1, GNB2L1, RPS14, RPL6, RPS7, RPL14, RPL35A, RPL23, RPL4, RPS13, HSPD1, SLIT1, RPL18, RPL37A, RPS21, RPS15, SLC25A6, RPL37, NME1-NME2, RPL7, RPL23A, RPL13A, RPS5, PHGDH, RPL26, EEF1G, RPS18, NFIB, RPS16, RPLP1, B4GALNT4, SNHG1, TOMM20, AMH, PAICS, NACA, CCNI, EIF4A1, RPL3, RPLP0, RPS9, RPS27, NME1, RPL41, TRAP1, CBS, EIF3L, RPL10, CCNB1IP1, MEX3A, RPL23AP42, RPL10A, ADGRA3, CAMKV, TMEM97, FBL, AHCY, IMPDH2, CPNE7, PTPRS, TAF1D, LAPTM4B, RPL15, NCL, ZFAS1, TKT, PPA1, AL589743.1, HOXD10, CACNA1E, EIF4B, RBMX, HOXD9, LRPPRC, MTHFD2, ILF3, EEF1B2, FAM153A, ALCAM, NTRK1, CADM1, CAMK4, CLU, AHNAK, CALCA, CD59, CRYAB, MPZ, S100B, and PIRT.

2. The gene panel of claim 1, wherein, The neuroblastoma molecular subtyping comprises distinguishing between neuroblastoma subgroups; the neuroblastoma subgroups comprise a MYCN-amplified high-risk neuroblastoma subgroup (HR1), a MYCN-non-amplified high-risk neuroblastoma subgroup (HR2), a low-intermediate-risk neuroblastoma subgroup (LR1), and a low-intermediate-risk nodular neuroblastoma subgroup (LR2).

3. The gene panel of claim 1, wherein, The gene group includes or is composed of the following characteristic genes: (1) MYCN amplification of characteristic genes of high-risk neuroblastoma subgroup: MYCN, DDX1, LDHB, EEF1B2, GAS5; (2) MYCN does not amplify characteristic genes of the high-risk neuroblastoma subgroup: MUC15, FAM153A, FAM153B, SLCO1A2; (3) Characteristic genes of the intermediate- and low-risk neuroblastoma subgroup: ADCY1, ALCAM, NTRK1, CADM1, CAMK4 and PIRT; (4) Characteristic genes of the intermediate- and low-risk ganglioneuroma subgroup: CLU, AHNAK, CALCA, CD59, CRYAB, S100B, MPZ.

4. Use of a combination of detection reagents for the genetic group of claim 1, characterized in that, This kit is used to prepare a test kit for determining the molecular subtype of neuroblastoma (NB) and / or assessing the prognosis of neuroblastoma patients.

5. Use according to claim 4, characterized in that, The kit includes an instruction manual, which states: If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the MYCN amplified high-risk neuroblastoma subgroup (HR1 group): MYCN, DDX1, LDHB, EEF1B2, GAS5; If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the MYCN non-amplified high-risk neuroblastoma subgroup (HR2 group): MUC15, FAM153A, FAM153B, SLCO1A2; If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the intermediate- or low-risk neuroblastoma subgroup (LR1 group): ADCY1, ALCAM, NTRK1, CADM1, CAMK4; and If high expression of genes selected from the following groups is detected, it indicates that the patient belongs to the intermediate-low risk ganglioneuroma subgroup (LR2 group): CLU, AHNAK, CALCA, CD59, CRYAB.

6. Use according to claim 5, characterized in that, The instruction manual also states: (1) If a patient is detected to belong to the HR2 group, it suggests that the patient is more suitable for immunotherapy targeting genes selected from the following groups compared to the HR1 group: GD2, PD1, PD-L1, CTLA4; and / or (2) If the patient is detected to belong to the LR1 group, it suggests that the patient is more suitable for immunotherapy targeting genes selected from the following groups compared to the LR2 group: GD2, B7H3, ALK, LAG3; (3) If the patient is detected to belong to the LR2 group, it suggests that the patient is more suitable for immunotherapy targeting genes selected from the following groups compared to the LR1 group: PD1, PD-L1.

7. A reagent combination for detecting the expression level of genes in the gene population of claim 1.

8. A product for molecular typing and / or survival risk assessment of neuroblastoma, characterized in that, It comprises the reagent combination as described in claim 7.

9. A predictive device for determining the molecular subtype of neuroblastoma in a patient using the gene cluster of claim 1, the device comprising: S1) Input module, the input module being used to input the gene population expression level from the sample of the patient; S2) Data analysis module, which is used to predict the molecular subtype of neuroblastoma based on the input gene population expression level; S3) Output module, which is used to output the prediction results.

10. The prediction device of claim 9, wherein, The data analysis module predicts the molecular subtype of neuroblastoma according to the following rules: If high expression of genes selected from the following groups is detected, it suggests that the patient has MYCN amplified high-risk neuroblastoma: MYCN, DDX1, LDHB, EEF1B2, GAS5; If high expression of genes selected from the following groups is detected, it suggests that the patient has MYCN non-amplified high-risk neuroblastoma: MUC15, FAM153A, FAM153B, SLCO1A2; If high expression of genes selected from the following groups is detected, it suggests that the patient has intermediate- or low-risk neuroblastoma: ADCY1, ALCAM, NTRK1, CADM1, CAMK4; and If high expression of genes selected from the following groups is detected, it suggests that the patient has intermediate- or low-risk ganglioneuroma: CLU, AHNAK, CALCA, CD59, CRYAB.

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