Method for screening potential neoantigen of tumor from transposition element

Abstract

The invention provides a method for screening a potential neoantigen of a tumor from a transposon element. The method comprises the following steps: collecting tumor tissue transcriptome sequencing data and normal tissue transcriptome sequencing data; identifying a TE transcript new type TEtrans based on a TE splicing event; performing feature analysis on the TEtrans; the TEtrans with the potential coding capability is screened out; and identifying the new antigen epitope peptide from the TEtrans: hydrolyzing all open reading frames of the to-be-selected TEtrans into 9 peptides which are mutually overlapped, removing annotated peptide fragments contained in Uniprot, defining the new antigen epitope peptide from the TEtrans according to allele typing of a tumor sample, further comparing the new antigen from the TEtrans with three common new antigens from genomic variation sources, and identifying the new antigen from the TEtrans. And screening to obtain the tumor potential new antigen. According to the invention, a brand new intergene region TE source transcript is successfully identified, and the transcript can be uniquely positioned and accurately quantified, so that a tumor specific transcript is screened as a potential tumor new antigen, and the method has huge potential in the aspect of developing tumor new antigen vaccines, especially tumors with low mutation load.

Description

Technical Field

[0001] The present invention belongs to the technical field of antigen screening, and in particular relates to a method for screening potential new tumor antigens from transposable elements. Background Art

[0002] Tumor-specific antigens (TSA), also known as neoantigens, are antigens specifically produced by tumor cells, mainly derived from gene mutations of coding genes, abnormal RNA splicing, and post-translational modifications of proteins. Because tumor neoantigens are highly tumor-specific, they can cause stronger immune responses, less immune tolerance, and lower off-target potential compared with tumor-associated antigens. At present, the development of tumor neoantigen vaccines still focuses on the source of gene mutations. Some phase I and II clinical trials have been found in tumors such as melanoma, pancreatic cancer, and hepatocellular carcinoma. Tumor neoantigen vaccines derived from mutations can synergize with immune checkpoint inhibitors to significantly enhance patients' immune responses and achieve survival benefits, which shows the great potential of neoantigens in cancer treatment. However, most gene mutations in tumors are random events and show significant heterogeneity in individual patients. Not all mutations can cause effective immune responses, which suggests that other types of antigens may also play an important role in tumor immunity. Sometimes, even if there are a large number of mutations in the tumor, the patient's response to ICB treatment is limited. It is also worth noting that the overall mutation frequency is low in some tumors, such as ovarian cancer and hepatocellular carcinoma. Therefore, targeting mutation-derived neoantigens is limited in both number and selection.

[0003] The non-coding regions of the genome are an important source of tumor neoantigens. More than 90% of the human genome is composed of non-coding regions. With the advancement of high-throughput sequencing technology, it has been found that about 70% of the non-coding genome can be transcribed into RNA. Transposable elements (TEs) are mobile DNA sequences that account for more than half of the human genome. They are mainly located in non-coding regions and play an important role in gene regulation. In tumors, TEs undergo epigenetic remodeling such as DNA hypomethylation and histone modification changes and are activated in large quantities. Due to the strict control of TE transcription under normal physiological conditions, the transcriptional activation of TEs in tumors is specific, and its transcription products can potentially serve as a new source of tumor neoantigens. Some studies have successively found that chimeric transcripts of TE-genes and viral proteins re-encoded by TE opening can produce new antigenic epitopes, which are presented by MHC class I molecules to activate T cell immune responses. These studies suggest that TE-derived neoantigens are widely present in tumors and greatly enrich the number and diversity of neoantigens in tumor patients. Since the opening of TEs mainly comes from epigenetic remodeling, TE-derived neoantigens are expected to overcome the limitations of mutation-derived neoantigens. Especially for patients with low-frequency mutations, these new antigens derived from TE are more likely to enhance T cell immune responses than new antigens derived from mutations, thereby further improving the efficacy of tumor immunotherapy.

[0004] The transcriptional forms of TE are complex, including autonomous transcription of isolated TE and chimeric transcripts formed by TE homologous genes through variable initiation, exonization and other methods. Due to the repetitiveness of TE sequences and multiple copies of the genome, the currently widely used RNA short-read second-generation sequencing is difficult to completely and accurately identify and distinguish these transcriptional forms, and it is difficult to accurately quantify TE-derived transcripts at the single site level, which will undoubtedly affect the identification of TE-encoded antigens and the determination of their tumor specificity. In view of the above limitations, some current studies choose to perform TE expression analysis at the family or subfamily level, but may miss information on specific sites with therapeutic significance, and it is difficult to identify TE non-classical open reading frames in complete transcripts; others focus on new antigens generated by chimeric transcription between TE and protein-coding genes, while ignoring other TE transcriptional forms. For example, some TE transcripts are derived from intergenic regions and are not related to classical protein-coding genes, but have the potential to promote cancer immunotherapy. Compared with the reported TE chimeric transcripts, these intergenic TE transcripts are more abundant, and experimental techniques such as ribosome sequencing (Ribo-seq) or immune peptidomics have confirmed that these transcripts have the potential to produce TE neoantigens, and their number may be more abundant. Therefore, identifying new TE transcription forms, especially intergenic TE-derived transcripts, is crucial for selecting tumor neoantigens from TE transcription products. Summary of the invention

[0005] The present invention provides a method for screening potential neoantigens for tumors from transposable elements. This method innovatively and successfully identifies novel intergenic region TE-derived transcripts from the perspective of RNA splicing, and can uniquely locate and accurately quantify the transcripts, thereby screening tumor-specific transcripts as potential neoantigens for tumors. Neoantigens derived from TEs can provide more neoantigen epitopes than single amino acid substitutions produced by mutations, and are shared among patients. Therefore, this method has great potential in the development of neoantigen vaccines for tumors, especially for those tumors with low mutation loads.

[0006] The technical solution adopted by the present invention to achieve the above-mentioned purpose is: a method for screening potential new tumor antigens from transposable elements, comprising the following steps:

[0007] (1) Collect tumor tissue transcriptome sequencing data and normal tissue transcriptome sequencing data;

[0008] (2) Identification of new TE transcript types based on TE splicing events

[0009] First, the RNA splicing site recognition and quantification program ASJA is used to identify TE splicing events in the tumor tissue transcriptome sequencing data and the normal tissue transcriptome sequencing data collected in step (1). Then, based on the location and quantitative information of the TE splicing events, the TE transcription forms TEtrans that are autonomously transcribed by TE, completely spliced ​​within TE, and have a high TE sequence ratio are screened according to the screening criteria.

[0010] (3) Characteristic analysis of TEtrans

[0011] The number of TEtrans in cancer and adjacent normal tissues was counted, and the expression pattern of TEtrans was further analyzed at the level of single transcripts. The expression levels in tumor samples, adjacent normal tissues and normal tissues were compared according to the comparison criteria, and the characteristics of TEtrans were analyzed.

[0012] (4) Screening of TEtrans with potential coding ability

[0013] First, the TEtrans sequences were extracted using the gffread software, and then the coding capacity and open reading frames of TEtrans were predicted using the CPAT software. The open reading frames with the start codon ATG and a length greater than 30 bp in the TEtrans sequences were identified, and potential coding open reading frames were screened according to the software recommended standards. TEtrans with coding open reading frames greater than 75 amino acids in length were further screened, and were required to be detectable in tumor cell lines and contain at least one tumor-specific or related splicing event.

[0014] (5) Identification of new antigen epitope peptides derived from TEtrans

[0015] The open reading frames of all candidate TEtrans were hydrolyzed into 9 overlapping peptides. After removing the annotated peptides in Uniprot, the peptides predicted by netMHCpan as having high affinity were defined as neoantigen epitope peptides derived from TEtrans based on the HLA-A, B, and C allele typing of TCGA tumor samples. The neoantigens derived from TEtrans were further compared with the neoantigens derived from three common genomic variations to screen for potential tumor neoantigens.

[0016] Preferably, the screening criteria in step (2) include that the transcription start site is located within TE 100 bp upstream and downstream, all splicing sites occur between TEs, and more than 50% of the overall transcripts are composed of TEs.

[0017] Preferably, the comparison criteria in step (3) include:

[0018] (1) The expression frequency of tumor samples in a certain tumor type is greater than 1%, the expression mean is greater than 0.01CPT, and the TE splicing events that are not expressed in the corresponding adjacent cancer tissues and all normal tissues are defined as tumor-specific TE splicing events;

[0019] (2) The expression frequency of tumor samples in a certain tumor type is greater than 5 times that of adjacent adjacent tissues, and also greater than 5 times the expression frequency of all GTEx normal tissues. TE splicing events with a mean expression value > 0.1 CPT in tumor samples are defined as tumor-related TE splicing events.

[0020] Preferably, the software recommendation standard in step (4) is to use open reading frames with a coding ability score greater than 0.364 as potential coding open reading frames.

[0021] Preferably, the three common genomic variations in step (5) are single base mutation, insertion / deletion and fusion gene.

[0022] Compared with the prior art, the beneficial effects that can be achieved by at least one of the above technical solutions adopted in the embodiments of this specification include at least:

[0023] First, the present invention directly extracts and quantifies splicing sites from RNA high-throughput sequencing data, and maps the splicing sites to single transcripts. The obtained splicing position information can be used to distinguish transcripts from different genomic copies of TE, and the quantification of splicing sites is conducive to the comparison of the site level of TE-derived transcripts, thereby identifying tumor-specific transcription forms;

[0024] Second, previous studies have focused on the potential of gene-related TE-derived transcripts to encode tumor neoantigens, such as TE-gene chimeric transcripts, while the present invention has identified a new type of TE transcripts formed by TE autonomous transcription and splicing, including a large number of intergenic TE-derived transcripts, more than 90% of which are unannotated and have high tumor specificity. Some of them have encoding ability and have good potential to encode tumor neoantigens, indicating that this method provides a new way to screen candidate tumor neoantigen targets from TE;

[0025] Third, the potential coding and tumor-specific TEtrans screened by the present invention, especially the intergenic region transcripts, are more immunogenic than single amino acid substitutions produced by mutations because the entire transcript is a "non-self" sequence. MHC affinity prediction also found that TEtrans potentially provide more new antigenic epitopes than genomic variations.

[0026] Fourth, the potentially encoded TEtrans screened by the present invention are autonomously transcribed by TE and mainly originate from tumor epigenetic dysregulation. In tumors with fewer new antigens contributed by genomic variations, the expression of these TEtrans can introduce more potential new antigens, indicating that the method of the present invention can provide more new antigen options for tumors with significant epigenetic dysregulation but low mutation load, such as ovarian cancer, liver cancer and other tumors. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on the drawings without paying creative work.

[0028] Figure 1 The identification process and verification diagram of the new type of TE trans transcripts based on TE splicing events, where (A) is the TE trans identification process, and (B) is the IGV and qPCR verification of two typical TE trans transcripts. In the IGV diagram, the blue solid line represents splicing on the positive strand, and the blue dotted line represents splicing on the negative strand; M is an electrophoresis marker;

[0029] Figure 2Characteristic analysis diagram of TEtrans, where (A) is the distribution diagram of the number of TEtrans in each tumor type of TCGA, (B) is the splicing sites contained in TEtrans with a higher unannotated ratio, (C) is the genomic location distribution diagram of the splicing site donors and acceptors contained in TEtrans, BG is all splicing sites, All is all TEtrans, Tumor_spec is TEtrans specifically expressed in tumor samples but not detected in adjacent cancer and normal samples, (D) is TEtrans with high tumor specificity, the heat map color represents the Z-score standardized value (Z-score of Mean Exp.) of the mean expression of TEtrans in each tumor type in a single TEtrans, and (E) is the expression of TEtrans in different tumor types;

[0030] Figure 3 Analysis diagram for screening TEtrans with potential coding ability, where (A) is a typical IGV schematic diagram of 4 candidate TEtrans in tumor tissues or cell lines, in which TE annotation only includes elements related to the transcript, and the blue rectangle in the transcript pattern diagram represents the predicted open reading frame, (B) shows that the 4 TEtrans are tumor-specifically expressed in multiple tumor types in TCGA, and (C) shows that the 4 candidate TEtrans can encode corresponding proteins after transfection in 293T;

[0031] Figure 4 The analysis diagram for identifying TEtrans-derived neoantigen epitope peptides, where (A) is a flow chart for selecting 240 TEtrans that are enriched in at least one tumor and predicted to have coding ability and a longer open reading frame; (B) is the load of TEtrans-derived neoantigen epitopes in various tumor samples of TCGA; (C) high TEtrans-derived neoantigen epitope load has higher IFN-γ responsiveness, CD8+T cell number, activated DC cell number and immune checkpoint expression level at the pan-cancer level; (D) TEtrans-derived neoantigen epitopes in a single tumor sample are significantly higher than those derived from single base mutations, insertions / deletions and gene fusion events; (E) The distribution of TEtrans-derived neoantigen epitopes is mutually exclusive with SNV, Indel and Fusion-derived neoantigens at higher levels;

[0032] Figure 5The immunogenicity validation analysis diagrams of potential TEtrans encoding, where (A) is the IFN-γ ELISPOT result of TEtrans-specific T cell clone induced by peripheral blood PBMC of a gastric cancer patient P7, (B) is the IFN-γ ELISPOT spot statistics of TEtrans-specific T cell clone induced by peripheral blood PBMC of P7, (C) is the IFN-γ ELISPOT result of TEtrans-specific T cell clone induced by peripheral blood PBMC of a healthy person P0201 with HLA-A02:01 typing, (D) is the IFN-γ ELISPOT spot statistics of TEtrans-specific T cell clone induced by peripheral blood PBMC of P0201, (E) is the monocytes isolated from the peripheral blood of two gastric cancer patients P1 and P2 and induced into mature DCs and then transfected with T4180 and T4960 mRNA, induced the corresponding TEtrans antigen-specific CD8+T cells IFN-γ ELISPOT results, the secondary stimulation used B cells transfected with the corresponding TEtrans mRNA, (F) is the IFN-γ ELISPOT spot statistics of TEtrans-specific CD8+T cell clones of P1 and P2 patients, (G) is the CFSE peak display of different intensities and the ratio of live cells after co-incubation of T4180 CD8+T cell clones with K562-HLA0201, (H) K562 cells expressing T4180 can activate T4180 CD8+T cell clones to secrete IFN-γ, the figure shows the result of flow cytometry detection of intracellular IFN-γ, (I) is the CFSE peak display of different intensities and the ratio of live cells after co-incubation of T2432 CD8+T cell clones with K562-HLA0201, (J) is the flow cytometry detection that K562 cells expressing T2432 can activate T2432 CD8+T cell clones to secrete IFN-γ. DETAILED DESCRIPTION

[0033] The embodiments of the present application are described in detail below with reference to the accompanying drawings.

[0034] The following describes the implementation methods of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments. The present application can also be implemented or applied through other different specific implementation methods, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that, in the absence of conflict, the following embodiments and the features in the embodiments can be combined with each other. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without making creative work belong to the scope of protection of the present application.

[0035] Example 1

[0036] A method for screening potential new tumor antigens from transposable elements, the specific steps are as follows:

[0037] (1) Collecting tumor tissue transcriptome sequencing data and normal tissue transcriptome sequencing data

[0038] The original bam sequencing files of 33 tumors and corresponding adjacent tissue samples were downloaded from the TCGA database website (https: / / tcga-data.nci.nih.gov / tcga / ); the linear splicing raw count expression matrix of 30 normal tissues covering 17,382 samples was obtained from the GTEx portal website (https: / / www.gtexportal.org / ); the original fastq sequencing files of tumor cell lines of 1,046 samples and 24 tissue types were downloaded from the CCLE website (https: / / portals.broadinstitute.org / ccle).

[0039] (2) Identification of new TE transcript types based on TE splicing events

[0040] ASJA, an RNA splice site identification and quantification program, was used to identify TE splicing events in TCGA, GTEx, and CCLE samples. The specific method is as follows: for the original fastq sequencing file, the RNA sequencing data was first quality controlled by FastQC, and then the hg38 reference genome was aligned using the STAR two-round alignment program to generate a bam file; all bam files were spliced ​​by StringTie according to GENCODEv29, and the coverage of the linear splice site was calculated according to the minimum coverage of the exons at both ends of the splice site, and standardized according to the coverage of all annotated splice sites, that is, the CPT-standardized splice site expression was obtained. Then, the donor and acceptor sites of the splicing event were extracted, and the bed file was constructed. The genomic position was aligned with the human hg38 genome RepeatMasker TE annotation file using the bedtools intersect command. At least one of the donor and acceptor sites was provided by TE, which was defined as a TE splicing event.

[0041] Based on the location and quantitative information of the above TE splicing events, we further screened out TE transcription forms that are autonomously transcribed by TE, completely spliced ​​within TE, and have a high TE sequence ratio. According to three screening criteria: (1) 100bp upstream and downstream of the transcription start site are located within TE; (2) all splicing sites occur between TEs; (3) more than 50% of the overall transcripts are composed of TEs; from the transcripts corresponding to the TE splicing events, 5361 TE-derived transcripts that are autonomously transcribed and spliced ​​by TEs were identified. This transcription form has not been systematically identified and reported before. We named this new type of TE-derived transcript TEtrans ( Figure 1 ).

[0042] (3) Characteristic analysis of TEtrans

[0043] The number of TEtrans in cancer and adjacent normal samples selected from the TCGA database was counted, and it was found that TEtrans was widely expressed in various tumor types ( Figure 2 A) We further analyzed the expression pattern of TEtrans at the level of single transcripts and compared their expression levels in TCGA primary tumor samples, adjacent tumor samples, and GTEx normal tissues. The criteria were as follows: (1) The expression frequency of tumor samples in a certain tumor type was greater than 1%, and the mean expression value was greater than 0.01CPT. The TE splicing events that were not expressed in the corresponding adjacent tumor tissues and all normal tissues were defined as tumor-specific TE splicing events (TSJ); (2) The expression frequency of tumor samples in a certain tumor type was greater than 5 times that of adjacent tumor tissues and also greater than 5 times the expression frequency of all GTEx normal tissues. The TE splicing events in tumor samples with a mean expression value greater than 0.1CPT were defined as tumor-associated TE splicing events (TAJ). It was found that 4348 (81.1%) TEtrans contained TSJ or TAJ, which were specifically expressed or significantly enriched in tumors, indicating that TEtrans is a type of transcript with high tumor specificity. The expression mean heat map showed that tumor-enriched TEtrans showed obvious tumor-specific expression ( Figure 2 D). The high-frequency TEtrans in various tumor types, especially in reproductive system tumors TGCT and OV, are also widely detected in other tumor types ( Figure 2 E), Figure 2E shows the expression frequency heat map of the 30 most frequently expressed TEtrans in each tumor type. The high-frequency TEtrans in reproductive system tumors are particularly widely expressed. We compared TE splicing events with annotated splicing events and annotated the genomic regions of their donor and acceptor sites. We found that the splicing events contained in TEtrans have a higher proportion of unannotated events than the overall TE splicing events, about 91.7% of which are unannotated ( Figure 2 B), and the donor and acceptor sites are enriched in the intergenic region. About 60% of tumor-specific TE splicing events occur in the intergenic region ( Figure 2 C), indicating that the method has captured a large number of new transcripts derived from intergenic TE. The above results show that the method of the present invention has successfully identified a new type of TE-derived transcript, TEtrans, which is an important transcription form of intergenic TE, has high tumor specificity, and its expression is widely shared among patients, suggesting its good potential as a tumor neoantigen target.

[0044] (4) Screening of TEtrans with potential coding ability

[0045] First, the sequences of TEtrans were extracted by gffread software, and then the coding capacity and open reading frame (ORF) of TEtrans were predicted by CPAT software. ORFs with ATG start codon and length greater than 30bp in TEtrans sequences were identified, and ORFs with coding capacity scores greater than 0.364 were recommended by the software as potential coding ORFs. Given that longer ORFs potentially encode more antigenic epitopes, we further screened TEtrans with coding ORF lengths greater than 75 amino acids, and required them to be detectable in CCLE tumor cell lines and contain at least one tumor-specific or related splicing event. A total of 240 potential coding TEtrans enriched in tumors were selected, accounting for about 5% of TEtrans (see 4A for the analysis process). These TEtrans potentially encode larger proteins and are specifically expressed in tumor cells, indicating that they may serve as a new and important source of tumor neoantigens. We further screened four transcripts from the potential TEtrans that were enriched in tumors and associated with anti-tumor immune cell components: T2432, T4180, T4960, and T5739, all of which were shared among multiple tumor types ( Figure 3 AB). We constructed mRNA expression vectors for TEtrans and synthesized the corresponding mRNA by in vitro transcription. We then verified the coding capacity and protein product size of these TEtrans in 293T cells ( Figure 3 C) It is speculated that these proteins may act as tumor neoantigens to activate immunity.

[0046] (5) Identification of new antigen epitope peptides derived from TEtrans

[0047] All the ORF frames of the candidate TEtrans were hydrolyzed into overlapping 9 peptides. After removing the peptides annotated in Uniprot, the peptides predicted by netMHCpan (4.1) as high-affinity peptides were defined as TEtrans-derived neoepitope peptides based on the HLA-A, B, and C allele typing of TCGA tumor samples. Finally, 6813 TEtrans-derived neoepitope peptides were identified, contributed by 240 potential encoded TEtrans. On average, each TEtrans can produce 33 epitope peptides with high affinity to different MHC-I class molecules (median 33, interquartile range 23-52). The TEtrans neoepitope load is highest in gastric cancer, esophageal cancer, and ovarian cancer ( Figure 4 B).

[0048] Analysis of the correlation between antitumor immune pathways and immune components showed that tumors with high TEtrans neoantigen epitope load at the pan-cancer level had higher IFN-γ responsiveness, CD8+ T cell and activated DC cell infiltration, and immune checkpoint expression levels ( Figure 4 C), which indicates that tumors with high expression of TEtrans neoantigens have perfect antigen presentation ability and T cell response, and mainly escape killing through immune checkpoint expression, which suggests that TEtrans neoantigens have potential combined treatment prospects with immune checkpoint inhibitors as immune targets.

[0049] We further compared the TEtrans-derived neoantigens with three common genomic variations: single nucleotide variation (SNV), insertion and deletion (Indel), and fusion gene (Gene Fusion)-derived neoantigens. From the perspective of single sample load, the TEtrans-derived neoantigen epitopes were significantly higher than those generated by genomic changes ( Figure 4 D); from the perspective of population coverage, the new antigen epitopes derived from TEtrans and genomic variation are mutually exclusive in population distribution at higher levels, that is, in tumors with fewer new antigens contributed by genomic variation, the expression of TEtrans can introduce more potential new antigens ( Figure 4 E). The above analysis shows that TEtrans is not only a richer source of tumor neoantigens, but also can complement the population covered by genomic variation, and thus has important clinical translational value in the development of neoantigen vaccine targets for tumor treatment and prevention.

[0050] Example 2 Verification of immunogenicity of potential encoded TEtrans

[0051] In order to verify whether TEtrans can encode new antigens to induce T cell activation, we collected 8-9 mL of EDTA anticoagulated peripheral blood from healthy people or tumor patients and separated human peripheral blood mononuclear cells (PBMC). Monocytes were obtained by STEM CELL CD14 pos selection magnetic beads positive selection, and then monocytes were induced to differentiate into dendritic cells (DC) in AIM V immune cell culture medium supplemented with GM-CSF and IL-4. DC maturation was induced by IFN-γ and lipopolysaccharide (LPS), thereby upregulating HLA molecules and co-stimulatory molecules to exert antigen presentation function. Human CD8+T cells were isolated by STEMCELL CD8 magnetic bead positive selection, and cultured in AIM V medium supplemented with 5% inactivated human AB serum. Cytokines 5ng / mL IL-7 and 5ng / mL IL-15 were also added, and the medium was replaced by half every 2-3 days. Human B cells were isolated by STEM CELL CD19 magnetic bead positive selection, and cultured in AIM V medium supplemented with 8% inactivated human AB serum. Cytokines 40ng / mL IL-4, 50ng / mL IL-21, 1μg / mL CD40L and 50μM β-mercaptoethanol were additionally supplemented. The medium was replaced by half every 2-3 days. After 7-10 days of in vitro culture, they can be used for mRNA transfection and antigen presentation. Because primary immune cells are difficult to transfect with nucleic acids, electroporation was often used in previous literature. However, this may have a significant impact on the viability of APCs, thereby affecting the subsequent antigen presentation function. For this reason, we used CALNP TM (Cell Available Lipid Nanoparticles) RNA delivery technology increases endosomal escape while maintaining normal uptake, thereby achieving efficient and low-toxic mRNA transfection. Based on the above method, PBMCs were directly transfected with the mRNA of four TEtrans, and it was found that all four TEtrans could activate T cells in PBMCs to secrete IFN-γ in vitro. Among them, T4180 showed good T cell activation effect in both PBMCs, while T2432 had a better T cell activation effect in PBMCs with HLA-A*02:01 typing ( Figure 5AD). To further explore whether TEtrans can specifically activate CD8+T cells to induce antigen-specific cytotoxic T lymphocyte (CTL) clones, we isolated CD8+T cells and monocytes from PBMCs of two other tumor patients, induced monocytes to become dendritic cells (DCs), transfected the corresponding mRNA and co-incubated with CD8+T cells of the same individual to induce antigen-specific activation. The results showed that T4960 could successfully activate CD8+T cells in P1 patients, while T4180 significantly activated CD8+T cells and secreted IFN-γ in both patients, and the activation effect was better than that of T4960 ( Figure 5 E and F). The above results show that T4180 has a good T cell activation effect in PBMCs of multiple individuals, suggesting that it has good potential to encode tumor neoantigens to activate immunity.

[0052] T4180 and T2432, which had the best T cell activation effect among HLA-A*02:01-typed PBMCs, were selected for tumor killing experiments. The control group used K562-HLA-A*02:01 cells that were not transfected with mRNA and stained with high and low concentrations and then mixed in equal amounts. The results showed that both T4180 and T2432 specific CD8+T cell clones showed 14% and 12% antigen-specific killing relative to the control group ( Figure 5 G and I). After co-incubation with K562 cells transfected with the corresponding TEtrans mRNA, both TEtrans-specific CD8+ T cell clones showed up-regulation of IFN-γ secretion ( Figure 5 H and J). These all indicate that TEtrans mRNA-induced CD8+ T cell clones can specifically kill tumors expressing corresponding antigens, further suggesting that TEtrans-encoded tumor neoantigens have great potential as candidate targets for tumor mRNA vaccines.

[0053] The above embodiments are only for illustrating the technical concept and features of the present invention, and their purpose is to enable ordinary technicians in the field to understand the content of the present invention and implement it accordingly, and they cannot be used to limit the protection scope of the present invention. Any equivalent changes or modifications made based on the essence of the content of the present invention should be included in the protection scope of the present invention.

Claims

1. A method for screening potential new tumor antigens from transposable elements, characterized in that: The following steps are involved: (1) Collect tumor tissue transcriptome sequencing data and normal transcriptome sequencing data; (2) Identification of new TE transcript types based on TE splicing events First, the RNA splicing site recognition and quantification program ASJA is used to identify TE splicing events in the tumor tissue transcriptome sequencing data and the normal tissue transcriptome sequencing data collected in step (1). Then, based on the location and quantitative information of the TE splicing events, the TE transcription form TEtrans that is autonomously transcribed by TE, completely spliced ​​within TE, and has a high TE sequence ratio is screened according to the screening criteria. (3) Characteristic analysis of TEtrans The number of TEtrans selected from tumor tissues and normal tissues was counted, and the expression pattern of TEtrans was further analyzed at the level of individual transcripts. The expression levels in tumor samples and normal tissues were compared according to the comparison criteria, and the characteristics of TEtrans were analyzed; (4) Screening of TEtrans with potential coding ability First, the TEtrans sequences were extracted using the gffread software, and then the coding capacity and open reading frames of TEtrans were predicted using the CPAT software. The open reading frames with the start codon ATG and a length greater than 30 bp in the TEtrans sequences were identified, and potential coding open reading frames were screened according to the software recommended standards. TEtrans with coding open reading frames greater than 75 amino acids in length were further screened, and were required to be detectable in tumor cell lines and contain at least one tumor-specific or related splicing event. (5) Identification of new antigen epitope peptides derived from TEtrans The open reading frames of all candidate TEtrans were hydrolyzed into 9 overlapping peptides. After removing the annotated peptides in Uniprot, the peptides predicted by netMHCpan as having high affinity were defined as neoantigen epitope peptides derived from TEtrans according to the HLA-A, B, and C allele typing of the tumor samples. The neoantigens derived from TEtrans were further compared with the neoantigens derived from three common genomic variations to screen for potential tumor neoantigens.

2. The method according to claim 1, characterized in that The screening criteria in step (2) include that the transcription start site is located within TE 100 bp upstream and downstream, all splicing sites occur between TEs, and more than 50% of the overall transcripts are composed of TEs.

3. The method according to claim 1, characterized in that The comparison criteria in step (3) include: (1) The expression frequency of tumor samples in a certain tumor type is greater than 1%, the expression mean is greater than 0.01CPT, and the TE splicing events that are not expressed in the corresponding adjacent cancer tissues and all normal tissues are defined as tumor-specific TE splicing events; (2) The expression frequency of tumor samples in a certain tumor type is greater than 5 times that of adjacent adjacent tissues, and also greater than 5 times the expression frequency of all GTEx normal tissues. TE splicing events with a mean expression value > 0.1 CPT in tumor samples are defined as tumor-related TE splicing events.

4. The method according to claim 1, characterized in that The software recommendation standard in step (4) is to use the open reading frames with coding ability scores greater than 0.364 as potential coding open reading frames.

5. The method according to claim 1, characterized in that The three common genomic variations in step (5) are single base mutation, insertion and deletion, and fusion gene.

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