A method for screening neoantigen polypeptide sequences of malignant solid tumors

Abstract

The present invention relates to the technical field of neoantigen screening, and specifically discloses a method for screening neoantigen polypeptide sequences of malignant solid tumors. The method comprises the following steps: obtaining neoantigen prediction results based on HLA class I molecule binding; screening to obtain candidate neoantigen-related mutations; extracting corresponding polypeptide sequences from the neoantigen prediction results to obtain a set of MHC class I potential neoantigen polypeptides; generating all 15-mer sequences centered on the mutation sites and predicting their binding ability to MHC class II molecules to obtain a set of MHC class II potential neoantigen polypeptide sequences; using the maximum margin extension algorithm to obtain long peptide sequences; synthesizing the polypeptide sequences to obtain candidate polypeptide sequences; and evaluating the immunogenicity of the candidate polypeptide sequences to obtain neoantigen polypeptide sequences. The present invention simultaneously considers the binding characteristics of both MHC class I and class II molecules, and can effectively improve the efficiency and accuracy of neoantigen screening.

Description

Technical Field

[0001] The present invention relates to the technical field of neoantigen screening, and particularly to a method for screening neoantigen polypeptide sequences of malignant solid tumors. Background Art

[0002] In recent years, with the rapid development of gene sequencing technology, as well as artificial intelligence and bioinformatics, the field of personalized cancer treatment has witnessed a major breakthrough. Among them, the development of cancer vaccines based on tumor neoantigens has become a research hotspot. Neoantigens are polypeptide sequences specifically mutated by tumor cells and recognized by the immune system. As tumor-specific targets, they have great potential in the development of personalized tumor vaccines and adoptive T cell therapy.

[0003] However, the top-ranked neoantigens selected based on prediction results have not shown the expected immunogenicity in subsequent experimental verification. The reason is that most current methods still focus on short peptides (8 - 12 amino acids) that bind to MHC class I, and there are the following problems with directly using these short peptides: 1) Short peptides can bind to MHCs of non-professional APCs, which lack the secondary signal mechanism for complete T cell activation, resulting in poor T cell responses or immune tolerance. 2) Short peptides can cause HLA (human leukocyte antigen) type restrictions because HLA is highly diverse in the population and HLA is mutable in the population, and mutations (especially LOH) occurring in HLA may lead to the loss of its antigen presentation function. 3) Short peptides are more easily digested by enzymes and eliminated from the body faster.

[0004] In recent years, a number of studies have confirmed that long peptides with a length of 15 to 31 amino acids can effectively enhance the immune responses of CD4+ and CD8+ T cells and thus induce a more comprehensive and persistent immune response because they can cover a wider range of HLA types and contain multiple epitope peptides. However, the methods for generating such long peptides based on existing neoantigen prediction technologies lack systematicness and effectiveness. Summary of the Invention

[0005] The present invention aims to solve the above problems. To this end, the present invention provides a method for screening neoantigen polypeptide sequences of malignant solid tumors, which adopts a dual molecular docking screening mechanism and simultaneously considers the binding characteristics of MHC class I and class II molecules, and can effectively improve the efficiency and accuracy of neoantigen screening, providing reliable technical support for the development of personalized tumor vaccines.

[0006] The present invention provides a method for screening neoantigen polypeptide sequences of malignant solid tumors, and the technical solution adopted is as follows: including the following steps:

[0007] Step 1: Obtain the neoantigen prediction results based on the binding of HLA class I molecules;

[0008] Step 2: According to the neoantigen prediction results, screen to obtain candidate neoantigen-related mutations;

[0009] Step 3: According to the candidate neoantigen-related mutations, extract the corresponding polypeptide sequences from the neoantigen prediction results to obtain a set of potential MHC class I neoantigen polypeptides;

[0010] Step 4: According to the candidate neoantigen-related mutations, obtain the protein sequence where the mutation site is located, and the protein sequence is a polypeptide sequence of no less than 15 amino acids;

[0011] Step 5: According to the protein sequence, use the sliding window method to generate all 15-mer sequences centered on the mutation site; predict the binding ability of each 15-mer sequence to MHC class II molecules, and screen the 15-mer sequences with a percentile rank of the elution ligand prediction score less than or equal to 1 to obtain a set of potential MHC class II neoantigen polypeptide sequences;

[0012] Step 6: According to the set of potential MHC class I neoantigen polypeptides and the set of potential MHC class II neoantigen polypeptide sequences, use the maximum margin expansion algorithm to obtain long peptide sequences;

[0013] Step 7: According to the long peptide sequences, synthesize polypeptide sequences, screen the polypeptide sequences that meet the quality control requirements to obtain candidate polypeptide sequences;

[0014] Step 8: Evaluate the immunogenicity of the candidate polypeptide sequences, and according to the evaluation results, obtain neoantigen polypeptide sequences.

[0015] Furthermore, the neoantigen prediction results include mutations, polypeptide sequences and their corresponding prediction scores, as well as the HLA typing results of the patient.

[0016] Furthermore, the neoantigen prediction results are the prediction results obtained by a neoantigen prediction method for a malignant solid tumor.

[0017] Furthermore, in Step 2, the screening criteria for selecting neoantigen-related mutations are: meeting any of the following criteria:

[0018] Criterion 1: The core peptide segment ranks within the top N1 in the scoring order in the neoantigen prediction results. In the neoantigen prediction results, the polypeptide sequence with the highest score corresponding to the mutation is its core peptide segment; and the expression level TPM of the mutated gene is greater than or equal to 0.5; and in the RNA sequencing data, the sequencing depth of the mutation site is less than 100 layers, or when the sequencing depth of the mutation site is greater than or equal to 100 layers, the mutation frequency is greater than 0;

[0019] Criterion 2: The mutated gene has been confirmed as a known driver gene.

[0020] Furthermore, in Step 3,

[0021] For candidate neoantigen-related mutations that meet criterion 1, extract the polypeptide sequences corresponding to them in the neoantigen prediction results with a score higher than N2.

[0022] For candidate neoantigen-related mutations that meet criterion 2, extract all the polypeptide sequences corresponding to them in the neoantigen prediction results.

[0023] Furthermore, in step 4,

[0024] For mutations with single amino acid substitutions, centering on the mutation site, extract the polypeptide sequences containing the mutation site and no more than 14 amino acids upstream and downstream of it to obtain the said protein sequence.

[0025] For insertions / deletions mutations, the extracted polypeptide sequence is from no more than 14 amino acids upstream of the mutation site to the stop codon, and select the polypeptide sequence containing the core peptide segment to obtain the said protein sequence. In the neoantigen prediction results, the polypeptide sequence with the highest score corresponding to the mutation is its core peptide segment.

[0026] Furthermore, if there is no corresponding MHC class II molecule for the candidate neoantigen-related mutation, the set of MHC class II potential neoantigen polypeptide sequences corresponding to this candidate neoantigen-related mutation is empty.

[0027] Furthermore, in step 6, for each candidate neoantigen-related mutation, according to the set of MHC class I potential neoantigen polypeptides, use the maximum margin expansion algorithm to construct MHC class I long peptide sequences; dock the 15-mer sequences in the set of MHC class II potential neoantigen polypeptide sequences with the MHC class I long peptide sequences in turn to obtain long peptide sequences.

[0028] Furthermore, the quality control requirements include: white or off-white powder; theoretical molecular weight of ±1.0 Da; purity greater than or equal to 95.0%; acetic acid less than or equal to 20%, TFA less than or equal to 1.0%; acetonitrile less than or equal to 0.041%, N,N-dimethylformamide less than or equal to 0.088%, diethyl ether less than or equal to 0.5%, dichloromethane less than or equal to 0.06%, methanol less than or equal to 0.3%; heavy metals less than or equal to 10 ppm; moisture less than or equal to 10%; bacterial endotoxin less than or equal to 5 EU / mg; microbial TAMC less than or equal to 200 cfu / g, TYMC less than or equal to 50 cfu / g.

[0029] Furthermore, in step 8, use the Elispot technique to verify whether the candidate polypeptide sequence can activate T cells and induce them to secrete cytokines, and evaluate its immunogenicity.

[0030] One or more of the above technical solutions in the embodiments of the present invention have at least one of the following technical effects:

[0031] The present invention adopts a dual molecular docking screening mechanism, taking into account the binding characteristics of both MHC class I and class II molecules, and significantly improving the accuracy of neoantigen prediction. The present invention uses the maximum margin expansion algorithm to integrate the potential neoantigen polypeptide set according to MHC class I and the potential neoantigen polypeptide sequence set according to MHC class II to achieve the intelligent optimization of candidate sequences.

[0032] Additional aspects and advantages of the present invention will be given in part in the following description, will become apparent in part from the following description, or will be learned through the practice of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0033] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the implementation examples or the prior art description. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0034] Figure 1 is a flowchart of the method provided by the present invention.

[0035] Figure 2 is a control chart of the detection results of the immune response of the neoantigen polypeptide provided by the present invention.

[0036] Figure 3 is a statistical chart of the detection results of the immune response of the neoantigen polypeptide provided by the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0037] To make the objectives, technical solutions, and advantages of the present invention clearer, the following will clearly and completely describe the technical solutions in the present invention in conjunction with the drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present invention. The following embodiments are used to illustrate the present invention, but cannot be used to limit the scope of the present invention.

[0038] In the description of this specification, the descriptions referring to terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" etc. mean that the specific features, structures, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the embodiments of the present invention. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, or characteristics described can be combined in a suitable manner in any one or more embodiments or examples. In addition, without contradiction, those skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0039] The following is a further detailed description of the present invention in conjunction with Figures 1 to 3 to further illustrate the present invention, and describe a method for screening a neoantigen polypeptide sequence of a malignant solid tumor of the present invention:

[0040] In this embodiment, as Figure 1 shown, a method for screening a neoantigen polypeptide sequence of a malignant solid tumor is provided, including the following steps:

[0041] Step 1: Obtain the prediction results of neoantigens based on HLA class I molecule binding.

[0042] In this embodiment, the neoantigen prediction results are the prediction results obtained by a method for predicting neoantigens of a malignant solid tumor. The neoantigen prediction results include mutations, polypeptide sequences and their corresponding prediction scores, as well as the HLA typing results of patients.

[0043] Specifically, the neoantigen prediction results of this embodiment are the prediction results of a method and system for predicting neoantigens of a malignant solid tumor disclosed in the Chinese invention patent with the application publication number CN119446264A, and the subsequent screening process is also based on the experimental results of this invention.

[0044] Step 2: According to the neoantigen prediction results, screen out candidate neoantigen-related mutations.

[0045] The screening criteria for selecting neoantigen-related mutations are: meeting any of the following criteria:

[0046] Criterion 1: Simultaneously meet Condition 1 to Condition 3.

[0047] Condition 1: The core peptide segment ranks within the top N1 in the score ranking in the neoantigen prediction results. In this embodiment, N1 is 50. In the neoantigen prediction results, the polypeptide sequences are divided by mutations, and the polypeptide sequence with the highest score corresponding to each mutation is used as its core peptide segment.

[0048] Condition 2: The expression level TPM of the mutant gene is greater than or equal to 0.5.

[0049] Condition 3: In RNA sequencing data, when the sequencing depth of the mutation site is less than 100 layers, or when the sequencing depth of the mutation site is greater than or equal to 100 layers, the mutation frequency is greater than 0.

[0050] Criterion 2: The mutated gene has been confirmed as a known driver gene.

[0051] If the mutated gene has been confirmed as a known driver gene, it is directly identified as a candidate neoantigen-related mutation without the need to simultaneously meet the three conditions of Criterion 1.

[0052] According to the above screening criteria, a total of 32 candidate neoantigen mutations were identified. These mutations include: 29 mutations with core peptide scores ranked 1st, 2nd, 5th, 7th, 9th, 10th, 12th, 13th, 14th, 16th, 17th, 18th, 19th, 22nd, 27th, 28th, 30th, 31st, 32nd, 33rd, 38th, 39th, 41st, 43rd, 46th, 47th, 48th, 49th, 50th; and 3 mutations occurring in the known driver genes SOCS1, EGFR, and TP53. See Table 1 for details.

[0053] Table 1 Table of candidate neoantigen-related mutations

[0054]

[0055] Step 3: According to the candidate neoantigen-related mutations, extract the corresponding polypeptide sequences from the neoantigen prediction results to obtain a set of MHC class I potential neoantigen polypeptides.

[0056] The extracted polypeptide sequences need to meet the following conditions:

[0057] For candidate neoantigen-related mutations that meet Criterion 1, extract the polypeptide sequences whose corresponding scores (prediction scores in Table 2) in the neoantigen prediction results are higher than N2. N2 is a manually selected score threshold, and in this embodiment, N2 is 0.5.

[0058] For candidate neoantigen-related mutations that meet Criterion 2, for mutations in known driver genes, the corresponding polypeptide sequences are not restricted by the score of 0.5, and all corresponding polypeptide sequences in the neoantigen prediction results are extracted.

[0059] Step 4: According to the candidate neoantigen-related mutations, obtain the protein sequence where the mutation site is located, and the protein sequence is a polypeptide sequence of no less than 15 amino acids.

[0060] Specifically, in Step 4,

[0061] For a mutation of a single amino acid substitution, centered on the mutation site, a polypeptide sequence containing the mutation site and no more than 14 amino acids upstream and downstream thereof is extracted to obtain the protein sequence. Preferably, 14 amino acids are taken from each of the upstream and downstream. In this case, the length of the protein sequence is at most 29 amino acids.

[0062] For an insertion / deletion mutation, the extracted polypeptide sequence is from no more than 14 amino acids upstream of the mutation site to the stop codon, and a polypeptide sequence containing the core peptide segment is selected to obtain the protein sequence. Preferably, 14 amino acids are taken from the upstream.

[0063] Step 5: According to the protein sequence, using the sliding window method, centered on the mutation site, all possible 15-mer sequences are generated. The binding ability of each 15-mer sequence to MHC class II molecules is predicted using the NetMHCIIpan 4.3 software. The strength of the binding ability is evaluated by the percentile rank of the eluted ligand prediction score. 15-mer sequences with a percentile rank of the eluted ligand prediction score less than or equal to 1 are screened to obtain the set of MHC class II potential neoantigen polypeptide sequences. See Table 2 for details.

[0064] Table 2 Candidate neoantigen-related mutation results table

[0065]

[0066]

[0067]

[0068]

[0069]

[0070]

[0071]

[0072] If there is no corresponding MHC class II molecule for the candidate neoantigen-related mutation, the set of MHC class II potential neoantigen polypeptide sequences corresponding to the candidate neoantigen-related mutation is empty. In this example, there are no corresponding MHC class II molecules for multiple candidate neoantigen-related mutations such as MAMDC4, ITPKB, SLC25A22, IRF4, and SBF1.

[0073] Step 6: According to the set of MHC class I potential neoantigen polypeptides and the set of MHC class II potential neoantigen polypeptide sequences, using the maximum margin extension algorithm, a long peptide sequence is obtained;

[0074] The specific process is as follows: For each candidate neoantigen-related mutation, according to the set of MHC class I potential neoantigen polypeptides, the maximum margin expansion algorithm is used to construct MHC class I long peptide sequences; the 15-mer sequences in the set of MHC class II potential neoantigen polypeptide sequences are docked with the MHC class I long peptide sequences in turn to obtain long peptide sequences. See Table 2 for details.

[0075] Step 7: According to the long peptide sequences, synthesize polypeptide sequences, screen the polypeptide sequences that meet the quality control requirements, and obtain candidate polypeptide sequences.

[0076] In this embodiment, the quality control requirements that need to be satisfied simultaneously include: white or off-white powder; theoretical molecular weight of ±1.0 Da; purity greater than or equal to 95.0%; acetic acid less than or equal to 20%, TFA less than or equal to 1.0%; acetonitrile less than or equal to 0.041%, N,N-dimethylformamide less than or equal to 0.088%, diethyl ether less than or equal to 0.5%, dichloromethane less than or equal to 0.06%, methanol less than or equal to 0.3%; heavy metals less than or equal to 10 ppm, heavy metals including cadmium, lead, arsenic, mercury, cobalt, vanadium, nickel; water content less than or equal to 10%; bacterial endotoxin less than or equal to 5 EU / mg; microbial TAMC less than or equal to 200 cfu / g, TYMC less than or equal to 50 cfu / g.

[0077] As shown in Table 2, 12 long peptide sequences failed to be synthesized, and the number of candidate polypeptide sequences that finally met the above quality control requirements was 20, which were respectively labeled as P002 - P009, P011 - P017, P0019 - P022, and P024.

[0078] Step 8: Evaluate the immunogenicity of the candidate polypeptide sequences, and according to the evaluation results, obtain neoantigen polypeptide sequences. Use the Elispot technique to verify whether the candidate polypeptide sequences can activate T cells and induce them to secrete cytokines to evaluate their immunogenicity.

[0079] In this embodiment, the Elispot technique is used to verify whether the 20 candidate polypeptide sequences successfully synthesized in Step 7 can activate T cells and induce them to secrete cytokines (IFN-γ), so as to evaluate their immune response. The verification results are as Figure 2 、 Figure 3 shown in (a) and (b) of. The negative / positive controls and positive judgment criteria for the ELISPOT experiment are as follows:

[0080] 1. Negative control group: Only DMSO (dimethyl sulfoxide) and normal saline (NS) are used as stimulants, and PBMCs (peripheral blood mononuclear cells) not pretreated with mixed peptides are used as the negative control group.

[0081] 2. Positive control group: Only DMSO and normal saline were used as stimulants, and PBMCs pretreated with a mixture of patient-individualized neoantigen peptides were used as the positive control group.

[0082] 3. Positive judgment criteria: 1) Weak positive: The stimulation index (SI value) is greater than 1.5, and the average count of stimulator spots is higher than that of the positive control. 2) Positive: The stimulation index (SI value) is greater than 2, and the average count of stimulator spots is higher than that of the positive control.

[0083] SI value setting: The average spot count value of the experimental group (including the positive control group) is divided by the average spot count value of the negative control group.

[0084] Figure 2 In this context, the Chinese meaning of Mix-peptide is mixed polypeptide, and the Chinese meaning of PHA is phytohemagglutinin.

[0085] This method targets all HLA subtypes of patients, contains multiple epitope peptides, and ensures that the generated long peptide sequence covers the minimum epitope of CD8+ T cells. The polypeptide sequences that can be recognized by CD4+ T cells and bind to MHC class II molecules will be evaluated, and the sequences with high immunogenicity will be integrated into the long peptide sequence to generate the final neoantigen polypeptide sequence. Such sequences can simultaneously activate CD4+ and CD8+ T cell subsets. This dual activation mechanism not only enhances the intensity of the immune response but also prolongs the duration of the immune response through the supporting effect of CD4+ T cells. By combining bioinformatics prediction, polypeptide synthesis feasibility evaluation, experimental verification, and immunological principles, this method can systematically screen out polypeptide sequences containing multiple epitopes and having the best immunogenicity.

[0086] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for screening neoantigen polypeptide sequences of malignant solid tumors, characterized in that, It includes the following steps: Step 1: Obtain the prediction results of neoantigens based on HLA class I molecule binding; Step 2: According to the neoantigen prediction results, screen to obtain candidate neoantigen-related mutations; Step 3: According to the candidate neoantigen-related mutations, extract the corresponding polypeptide sequences from the neoantigen prediction results to obtain the set of MHC class I potential neoantigen polypeptides; Step 4: According to the candidate neoantigen-related mutations, obtain the protein sequence where the mutation site is located, and the protein sequence is a polypeptide sequence of no less than 15 amino acids; Step 5: According to the protein sequence, use the sliding window method, with the mutation site as the center, to generate all 15-mer sequences; predict the binding ability of each 15-mer sequence to MHC class II molecules, and screen the 15-mer sequences with the percentile rank of the elution ligand prediction score less than or equal to 1 to obtain the set of MHC class II potential neoantigen polypeptide sequences; Step 6: According to the set of MHC class I potential neoantigen polypeptides and the set of MHC class II potential neoantigen polypeptide sequences, use the maximum margin expansion algorithm to obtain the long peptide sequence; Step 7: According to the long peptide sequence, synthesize the polypeptide sequence, screen the polypeptide sequences that meet the quality control requirements to obtain the candidate polypeptide sequences; Step 8: Evaluate the immunogenicity of the candidate polypeptide sequences, and according to the evaluation results, obtain the neoantigen polypeptide sequences.

2. The screening method of a neoantigen polypeptide sequence for malignant solid tumors according to claim 1, characterized in that, The neoantigen prediction results include mutations, polypeptide sequences and their corresponding prediction scores, as well as the HLA typing results of the patient.

3. The screening method for a neoantigen polypeptide sequence of malignant solid tumors according to claim 1, characterized in that, The neoantigen prediction results are the prediction results obtained by a neoantigen prediction method for a malignant solid tumor.

4. The screening method of a neoantigen polypeptide sequence for malignant solid tumors according to claim 1, characterized in that, In step 2, the screening criteria for selecting neoantigen-related mutations are: meeting any of the following criteria: Criterion 1: The core peptide segment is ranked within the top N1 in the scoring order in the neoantigen prediction results. In the neoantigen prediction results, the polypeptide sequence with the highest score corresponding to the mutation is its core peptide segment; and the expression level TPM of the mutated gene is greater than or equal to 0.5; and in the RNA sequencing data, the sequencing depth of the mutation site is less than 100 layers, or when the sequencing depth of the mutation site is greater than or equal to 100 layers, the mutation frequency is greater than 0; Criterion 2: The mutated gene has been confirmed as a known driver gene.

5. The screening method of a neoantigen polypeptide sequence for malignant solid tumors according to claim 4, wherein In step 3, For the candidate neoantigen-related mutations that meet Criterion 1, extract the polypeptide sequences with scores higher than N2 corresponding to them in the neoantigen prediction results; For the candidate neoantigen-related mutations that meet Criterion 2, extract all the polypeptide sequences corresponding to them in the neoantigen prediction results.

6. The screening method for neoantigen polypeptide sequences of malignant solid tumors according to claim 1, wherein In step 4, For mutations with single amino acid substitutions, with the mutation site as the center, extract the polypeptide sequence containing the mutation site and no more than 14 amino acids upstream and downstream of it to obtain the protein sequence; For insertions / deletions mutations, the extracted polypeptide sequence is from no more than 14 amino acids upstream of the mutation site to the stop codon, and select the polypeptide sequence containing the core peptide segment to obtain the protein sequence. In the neoantigen prediction results, the polypeptide sequence with the highest score corresponding to the mutation is its core peptide segment.

7. The screening method of a neoantigen polypeptide sequence for malignant solid tumors according to claim 1, characterized in that If there is no corresponding MHC class II molecule for the candidate neoantigen-related mutation, the set of MHC class II potential neoantigen polypeptide sequences corresponding to the candidate neoantigen-related mutation is empty.

8. The screening method for a neoantigen polypeptide sequence of malignant solid tumors according to claim 1, wherein In step 6, for each candidate neoantigen-related mutation, according to the set of MHC class I potential neoantigen polypeptides, the maximum margin extension algorithm is used to construct MHC class I long peptide sequences; the 15-mer peptide sequences in the set of MHC class II potential neoantigen polypeptide sequences are docked with the MHC class I long peptide sequences in turn to obtain long peptide sequences.

9. The screening method of a neoantigen polypeptide sequence for malignant solid tumors according to claim 1, wherein The quality control requirements include: white or off-white powder; theoretical molecular weight of ±1.0 Da; purity greater than or equal to 95.0%; acetic acid less than or equal to 20%, TFA less than or equal to 1.0%; acetonitrile less than or equal to 0.041%, N,N-dimethylformamide less than or equal to 0.088%, diethyl ether less than or equal to 0.5%, dichloromethane less than or equal to 0.06%, methanol less than or equal to 0.3%; heavy metals less than or equal to 10 ppm; water less than or equal to 10%; bacterial endotoxin less than or equal to 5 EU / mg; microbial TAMC less than or equal to 200 cfu / g, TYMC less than or equal to 50 cfu / g.

10. A method for screening a neoantigen polypeptide sequence of malignant solid tumors according to claim 1, characterized in that, In step 8, the Elispot technique is used to verify whether the candidate polypeptide sequence can activate T cells and induce them to secrete cytokines, and to evaluate its immunogenicity.

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