Patent Grant
12018252
The present application is being filed along with a sequence listing in electronic format. The sequence listing is provided as a file entitled SequenceListingCALV007C2, created Apr. 28, 2022 which is 147 KB in size. The information in the electronic format of the sequence listing is incorporated herein by reference in its entirety.
Checkpoint inhibitor immunotherapeutics are revolutionizing cancer therapy. However, even in the most responsive cancers a substantial portion (50%-80%) of the patients have poor to no positive response (1-5). The evidence to date is that whether a patient has an effective response to the treatment depends on the nature of the immune response they have established against the tumor. More specifically, the level and quality of the immune response to neoantigens in the cancer seems to be most important.
Provided herein, in certain aspects, are peptide arrays comprising a plurality of frameshift variant peptides. In some cases, the plurality of frameshift variant peptides comprise peptides encoded by genes having a variant in a microsatellite (MS) in a coding region of the gene. Alternatively or in combination, the plurality of frameshift variant peptides comprise peptides encoded by an mRNA having a splicing error. In some embodiments, the plurality of frameshift variant peptides comprise two or more pooled frameshift peptides. In some cases, the plurality of frameshift variant peptides comprise one or more peptides provided in any one of Tables 1 or 7. In some embodiments, the plurality of frameshift variant peptides are fixed on a substrate. In some embodiments, the substrate comprises glass, composite, resin, or combination thereof. In some embodiments, the peptide array is configured to detect binding by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance. In some embodiments, the peptide array comprises at least about 25000, about 50000, about 75000, about 100000, about 125000, about 150000, about 175000, about 200000, about 225000, about 250000, about 275000, about 300000, about 325000, about 350000, about 375000, or about 400000 frameshift variant peptides.
In additional aspects, there are provided methods of measuring an immune response to a neoantigen peptide in a subject. In some cases, the method comprises: (a) contacting a biological sample obtained from a subject to a peptide array comprising a plurality of frameshift variant peptides. In some cases, the plurality of frameshift variant peptides comprise peptides encoded by genes having a variant in a microsatellite (MS) in a coding region of the gene. Alternatively or in combination, the plurality of frameshift variant peptides comprise peptides encoded by an mRNA having a splicing error. In some cases, the method further comprises detecting binding of the biological sample to at least one peptide in the peptide array. In some embodiments, the plurality of frameshift variant peptides comprise two or more pooled frameshift peptides. In some embodiments, the plurality of frameshift variant peptides comprise one or more peptides provided in any one of Tables 1 or 7. In some embodiments, the plurality of frameshift variant peptides are fixed on a substrate. In some embodiments, the substrate comprises glass, composite, resin, or combination thereof. In some embodiments, the peptide array is configured to detect binding by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance. In some embodiments, the peptide array comprises at least about 25000, about 50000, about 75000, about 100000, about 125000, about 150000, about 175000, about 200000, about 225000, about 250000, about 275000, about 300000, about 325000, about 350000, about 375000, or about 400000 frameshift variant peptides. In some embodiments, the biological sample comprises blood, serum, plasma, cerebrospinal fluid, saliva, urine, or combinations thereof. In some embodiments, the biological sample comprises an antibody. In some embodiments, the subject is a mammal. In some embodiments, the subject is a human, a dog, a cat, a mouse, a rat, a rabbit, a horse, a cow, or a pig. In some embodiments, the subject is suspected of having a cancer. In some embodiments, the cancer is selected from the group consisting of Acute lymphoblastic leukemia, Acute monocytic leukemia, Acute myeloid leukemia, Acute promyelocytic leukemia, Adenocarcinoma, Adult T-cell leukemia, Astrocytoma, Bladder cancer, Bone Cancer, Brain Tumor, Breast Cancer, Burkitt's lymphoma, Carcinoma, Cervical Cancer, Chronic Lymphocytic Leukemia, Chronic myelogenous leukemia, Colon Cancer, Colorectal cancer, Endometrial cancer, Glioblastoma multiforme, Glioma, Hepatocellular carcinoma, Hodgkin's lymphoma, Inflammatory breast cancer, Kidney Cancer, Leukemia, Lung cancer, Lymphoma, Malignant Mesothelioma, Medulloblastoma, Melanoma, Multiple myeloma, Neuroblastoma, Non-Hodgkin Lymphoma, Non-Small Cell Lung Cancer, Ovarian Cancer, Pancreatic Cancer, Pituitary tumor, Prostate cancer, Retinoblastoma, Skin Cancer, Small Cell Lung Cancer, Squamous cell carcinoma, Stomach cancer, T-cell leukemia, T-cell lymphoma, Thyroid cancer, and Wilms' tumor.
In further aspects, there are provided methods of detecting a cancer in a subject. In some embodiments, the method comprises: (a) contacting a biological sample obtained from a subject to a peptide array comprising a plurality of frameshift variant peptides. In some embodiments, the plurality of frameshift variant peptides comprise peptides encoded by genes having a variant in a microsatellite (MS) in a coding region of the gene. Alternatively or in combination, the plurality of frameshift variant peptides comprise peptides encoded by an mRNA having a splicing error. In some embodiments, the method further comprises detecting binding of the biological sample to at least one peptide in the peptide array. In some embodiments, the plurality of frameshift variant peptides comprise one or more peptides provided in any one of Tables 1 or 7. In some embodiments, the plurality of frameshift variant peptides comprise two or more pooled frameshift peptides. In some embodiments, the plurality of frameshift variant peptides are fixed on a substrate. In some embodiments, the substrate comprises glass, composite, resin, or combination thereof. In some embodiments, the peptide array is configured to detect binding by at least one of fluorescence, luminescence, calorimetry, chromatography, radioactivity, Bio-Layer Interferometry, and surface plasmon resonance. In some embodiments, the peptide array comprises at least about 25000, about 50000, about 75000, about 100000, about 125000, about 150000, about 175000, about 200000, about 225000, about 250000, about 275000, about 300000, about 325000, about 350000, about 375000, or about 400000 frameshift variant peptides. In some embodiments, the biological sample comprises blood, serum, plasma, cerebrospinal fluid, saliva, urine, or combinations thereof. In some embodiments, the biological sample comprises an antibody. In some embodiments, the subject is a mammal. In some embodiments, the subject is a human, a dog, a cat, a mouse, a rat, a rabbit, a horse, a cow, or a pig. In some embodiments, the subject is suspected of having a cancer. In some embodiments, the cancer is selected from the group consisting of Acute lymphoblastic leukemia, Acute monocytic leukemia, Acute myeloid leukemia, Acute promyelocytic leukemia, Adenocarcinoma, Adult T-cell leukemia, Astrocytoma, Bladder cancer, Bone Cancer, Brain Tumor, Breast Cancer, Burkitt's lymphoma, Carcinoma, Cervical Cancer, Chronic Lymphocytic Leukemia, Chronic myelogenous leukemia, Colon Cancer, Colorectal cancer, Endometrial cancer, Glioblastoma multiforme, Glioma, Hepatocellular carcinoma, Hodgkin's lymphoma, Inflammatory breast cancer, Kidney Cancer, Leukemia, Lung cancer, Lymphoma, Malignant Mesothelioma, Medulloblastoma, Melanoma, Multiple myeloma, Neuroblastoma, Non-Hodgkin Lymphoma, Non-Small Cell Lung Cancer, Ovarian Cancer, Pancreatic Cancer, Pituitary tumor, Prostate cancer, Retinoblastoma, Skin Cancer, Small Cell Lung Cancer, Squamous cell carcinoma, Stomach cancer, T-cell leukemia, T-cell lymphoma, Thyroid cancer, and Wilms' tumor.
In further aspects, there are provided compositions comprising a plurality of frameshift variant peptides. In some cases, the plurality of frameshift variant peptides comprise peptides encoded by genes having a variant in a microsatellite (MS) in a coding region of the gene. Alternatively or in combination, wherein the plurality of frameshift variant peptides comprise peptides encoded by an mRNA having a splicing error. In some embodiments, the plurality of frameshift variant peptides comprise one or more peptides provided in any one of Tables 1 or 7. In some embodiments, the plurality of frameshift variant peptides comprise two or more pooled frameshift peptides. In some embodiments, the composition further comprises an adjuvant. In some embodiments, the adjuvant is selected from the group consisting of ABM2, AS01B, AS02, AS02A, Adjumer, Adjuvax, Algammulin, Alum, Aluminum phosphate, Aluminum potassium sulfate, Bordetella pertussis, Calcitriol, Chitosan, Cholera toxin, CpG, Dibutyl phthalate, Dimethyldioctadecylammonium bromide (DDA), Freund's adjuvant, Freund's complete, Freund's incomplete (IFA), GM-CSF, GMDP, Gamma Inulin, Glycerol, HBSS (Hank's Balanced Salt Solution), IL-12, IL-2, Imiquimod, Interferon-Gamma, ISCOM, Lipid Core Peptide (LCP), Lipofectin, Lipopolysaccharide (LPS), Liposomes, MF59, MLP+TDM, Monophosphoryl lipid A, Montanide IMS-1313, Montanide ISA 206, Montanide ISA 720, Montanide ISA-51, Montanide ISA-50, nor-MDP, Oil-in-water emulsion, P1005 (non-ionic copolymer), Pam3Cys (lipoprotein), Pertussis toxin, Poloxamer, QS21, RaLPS, Ribi, Saponin, Seppic ISA 720, Soybean Oil, Squalene, Syntex Adjuvant Formulation (SAF), Synthetic polynucleotides (poly IC/poly AU), TiterMax Tomatine, Vaxfectin, XtendIII, and Zymosan.
In additional aspects, there are provided methods of treating or preventing cancer in a subject comprising administering a composition comprising any one of the frameshift variant peptides provided herein. In some embodiments, the subject is a mammal. In some embodiments, the subject is a human, a dog, a cat, a mouse, a rat, a rabbit, a horse, a cow, or a pig. In some embodiments, the cancer is selected from the group consisting of Acute lymphoblastic leukemia, Acute monocytic leukemia, Acute myeloid leukemia, Acute promyelocytic leukemia, Adenocarcinoma, Adult T-cell leukemia, Astrocytoma, Bladder cancer, Bone Cancer, Brain Tumor, Breast Cancer, Burkitt's lymphoma, Carcinoma, Cervical Cancer, Chronic Lymphocytic Leukemia, Chronic myelogenous leukemia, Colon Cancer, Colorectal cancer, Endometrial cancer, Glioblastoma multiforme, Glioma, Hepatocellular carcinoma, Hodgkin's lymphoma, Inflammatory breast cancer, Kidney Cancer, Leukemia, Lung cancer, Lymphoma, Malignant Mesothelioma, Medulloblastoma, Melanoma, Multiple myeloma, Neuroblastoma, Non-Hodgkin Lymphoma, Non-Small Cell Lung Cancer, Ovarian Cancer, Pancreatic Cancer, Pituitary tumor, Prostate cancer, Retinoblastoma, Skin Cancer, Small Cell Lung Cancer, Squamous cell carcinoma, Stomach cancer, T-cell leukemia, T-cell lymphoma, Thyroid cancer, and Wilms' tumor.
All publications, patents, and patent applications mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference.
The novel features of the disclosure are set forth with particularity in the appended claims. A better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description that sets forth illustrative embodiments, in which the principles of the disclosure are utilized, and the accompanying drawings of which:
Provided herein are methods and compositions for preventing, treating, and diagnosing cancer comprising the use of neoantigens. Neoantigens herein comprise peptides encoded by nucleic acids having frameshift mutations, such as insertions or deletions, causing a frameshift in the mRNA and a long stretch of mutant amino acids that are, in some cases, recognized as a non-self peptide by the immune system.
The success of checkpoint inhibitors in cancer therapy is largely attributed to activating the patient's immune response to their tumor's neoantigens arising from DNA mutations. This realization has motivated the interest in personal cancer vaccines based on sequencing the patient's tumor DNA to discover neoantigens. Embodiments provided herein relate to an additional, unrecognized source of tumor neoantigens. In some embodiments, errors in transcription of microsatellites (MS) and mis-splicing of exons create highly immunogenic frameshift (FS) neoantigens in tumors. The sequence of these FS neoantigens are predictable, allowing creation of a peptide array representing all possible neoantigen FS peptides. This array can be used to detect the antibody response in a patient to the FS peptides. A survey of 5 types of cancers reveals peptides that are personally reactive for each patient. This source of neoantigens and the method to discover them may be useful in developing cancer vaccines.
Personal cancer vaccines are promising as a new therapeutic treatment. These vaccines are currently based on mutations in tumor DNA. In some embodiments, variants in RNA production create frameshift neoantigens that may be another source of neoantigens for personal vaccines. Because there are only ˜220K of these antigens a simple peptide array can be used for their detection. Checkpoint inhibitor immunotherapeutics are revolutionizing cancer therapy. However, even in the most responsive cancers a substantial portion (50%-80%) of the patients have poor to no positive response (1-5). A surprising finding in the analysis of these patients was that one of the best correlates of response has been the total number of neoantigens in the tumor (6-8). This is also the case for patients with high microsatellite instability (MSI) where the production of FS neoantigens drives the effective anti-tumor immune responses (9-11). The realization of the immunological importance of these DNA mutations has spawned the effort to develop personal vaccines (12). As promising as early studies are of these vaccines, a major problem is that the majority of tumors will not have enough neoantigen-generating mutations to sustain development of a personal vaccine (13-15). For example, melanoma tumors have a high mutational level with an average of 200 neoepitope mutations. This provides a large number to algorithmically screen for optimal antigenic presentation. In recent reports of two Phase I clinical trials of personal melanoma vaccines, starting with 90-2,000 personal neoantigens, 10 or 20 were identified for the vaccine (16, 17). However, in glioblastoma multiforme (GBM) only 3.5% patients had a high tumor mutation load, and further analysis showed that only a very small subset of GBM patients would potentially benefit from checkpoint blockade treatment (18). This is also consistent with a lack of response in GBM patients to checkpoint inhibitors (19). Massive genomic sequencing results indicated that GBM, ovarian cancer, breast adenocarcinoma and many other cancer types had very low number non-synonymous mutations, which will make these cancers difficult targets for personalized cancer vaccines (14, 20).
To solve this problem, methods and compositions are provided herein related to an alternative source of neoantigens which expand the scope of the application and efficacy of the neoantigen based cancer vaccines. In the process of becoming a tumor, not only does the DNA mutation rate increase with faster cell divisions, but also there is a disruption of basic cellular functions, including RNA transcription, splicing and the quality control system on peptides (21). The disrupted RNA processes increase the FS transcripts generated by RNA splicing errors and the insertions and deletions (INDELs) of MSs (22). Both of these processes, combined with the disrupted quality control system in tumor cells, can lead to the production of FS peptides and exposure of the FS epitopes to the immune system. Embodiments provided herein relate to FS variants produced by errors in RNA processing as a source of cancer neoantigens and a simple system to detect them.
Disclosed herein are models for how errors in transcription microsatellites and mis-splicing of exons could create frameshift neoantigens. Embodiments provided herein include examples in the RNA of tumors for both mis-splicing and of mis-transcription of an INDEL where the errors are present at the RNA but not DNA level. Also provided are methods for analysis of the NCBI EST library to reveal other examples of FS variants. Using an array comprising all predicted FS peptides with specific qualifications, human sera from patients with 5 different cancers have higher antibody reactivity than people without cancer. Three different patterns of high antibody reactive can be determined—pan-cancer, cancer-type focused and personal. Several examples are presented demonstrating that the FS variants offer at least partial protection in mouse models and that the protection is additive for each FS antigen.
The methods and compositions provided herein indicates that variants produced at the RNA level in tumor cells may be a good source of neoantigens for vaccines for several reasons. First, these FS variants produce neoantigens which are more likely to be immunogenic than neo-epitopes encoded by single nucleotide mutations (7). Second, FS from MS INDELs would be particularly attractive sources. There are a limited number of possible variants (˜8600 of homopolymers >=7 bp), which encode about 7,000 FS peptides longer than 10 aa, thus reducing the search space for neoantigens. Third, because of the predictable number of candidates it should be possible to use a peptide array to screen for immune reactive neoantigens. This approach would be much simpler than sequencing tumor DNA obtained from a biopsy. Fourth, because any expressed gene has the potential to produce neoantigens, it may not be necessary to limit the vaccine to oncological driver genes. Finally, it should be difficult for the tumor cells to evolve away from the vaccine since these FSs are variants, not heritable mutations. Particularly if the FS antigen was produced in RNA from an essential gene, the tumor cells would need to restrict MHC presentation (17, 52) or create an immune suppressive environment (53) to escape an immune response.
Elements of the model are supported by other published work. The immunological reactivity of FS neoantigens is the presumed basis of the effectiveness of PD-1 in most MSI-H cancers (54, 55). It also explains the responsiveness of renal cancer to CPI therapy—these cancers have low point mutation levels but high FS mutations (3, 7, 20). It has also been shown that cancer cells have much higher mis-splicing rates than normal cells (39, 41, 56). Recently, Andre et al. (56) showed informatically that cancer cells could make neofusion sites by mis-splicing. However, their analysis did not include fusions that created FS peptides. Also, Alicia et.al. (57) analyzed intron retention in tumor databases. This process can also create FS neoepitopes, though apparently much less frequently than mis-splicing of exons. The only aspects of the model not independently confirmed are 1) that the FS peptides potentially generated at the RNA level are made in tumors, 2) that the RNA-generated FSPs can generate immune responses, and 3) that these peptides can be protective against tumors. However, the methods provided herein support these 3 remaining aspects of the model.
An important aspect of this source of neoantigens is that it may allow extending the personal vaccines to more patients and tumor types. Many tumors have relatively low numbers of DNA mutations and probably could not support constructing a vaccine (58). Estimates from published mutational surveys of various tumors(59) indicate that only 40% of patients could be treated with personal vaccines. However, the methods and compositions provided herein predicts that the RNA FS variants would be produced in any cancer type, even if the DNA mutation level is low. This is substantiated, for example, in GBM (
The model also predicts that there may be recurrent FSs produced in different tumors. This is substantiated, for example, at the RNA level for SMC1 FS in breast cancers (
Sets of FS peptides were found that had enriched activity in individual tumor types. A collection of a set of these peptides could potentially be used to constitute a general, therapeutic vaccine or one focused on a particular tumor or set of tumors. Such vaccines would have an advantage over a personal vaccine of being pre-made but would have fewer antigens in common with the tumor. Conceivably, pan-cancer peptides could be used to create a prophylactic cancer vaccine, as has been proposed for cancer associated antigens (60). However, as shown in comparing late and early stage pancreatic cancer profiles, a prophylactic vaccine from FS neoantigens would be best constituted from peptides reactive at early stages of cancer. Clinical trials in dogs were recently initiated of a prophylactic vaccine that is designed to be broadly protective (data not shown).
In
The vaccines tested did not produce complete protection by themselves in the models tested. However, it should be noted that both these models are very stringent and probably do not completely replicate natural tumors. One reason for this may be due to low level production of each FS neoantigen, consistent with the additive effects of the FS peptides in vaccines (
The arrays detect antibody responses to FS peptides. B-cell responses are not commonly considered important for an anti-tumor effect. It was recently shown that antibodies generated by dogs with cancer could be detected on an 800 FS peptide array. Peptides reactive on the dog array, whose homolog was also present in a mouse tumor line, were protective in the mouse models, while non-reactive peptides on the array did not confer protection. This study establishes that antibody response is an indicator of vaccine effectiveness. The level of antibody response correlated with protection in the mouse models. One explanation for this observation is that the IgG antibody response depends on CD4+ T-cell help. FS with good CD4+ T cell epitopes may also elicit tumor cell killing. It has been noted that CD4+ T cell responses to vaccines correlate with protection (66, 67).
In summary, the methods and compositions provided herein relate to another class of neoantigens that are useful in developing different types of cancer vaccines. Also provided herein are array formats for directly detecting immune responses to these tumor antigens. Dog and human clinical trials for use of the tumor antigens identified by the methods disclosed herein are underway.
As used herein, the term “detect,” “detection,” “detectable,” or “detecting” is understood both on a quantitative and a qualitative level, as well as a combination thereof. It thus includes quantitative, semi-quantitative, and qualitative measurements of measuring a cancer in a subject, using the methods and compositions as disclosed herein.
As used herein, the expression “a subject in need thereof” means a human or non-human mammal that exhibits one or more symptoms or indications of cancer, and/or who has been diagnosed with cancer, including a solid tumor and who needs treatment for the same. In many embodiments, the term “subject” may be interchangeably used with the term “patient”. For example, a human subject may be diagnosed with a primary or a metastatic tumor and/or with one or more symptoms or indications including, but not limited to, unexplained weight loss, general weakness, persistent fatigue, loss of appetite, fever, night sweats, bone pain, shortness of breath, swollen abdomen, chest pain/pressure, enlargement of spleen, and elevation in the level of a cancer-related biomarker.
The term “malignancy” refers to a non-benign tumor or a cancer. As used herein, the term “cancer” includes a malignancy characterized by deregulated or uncontrolled cell growth. Exemplary cancers include: carcinomas, sarcomas, leukemias, and lymphomas. Cancer includes primary malignant tumors (e.g., those whose cells have not migrated to sites in the subject's body other than the site of the original tumor) and secondary malignant tumors (e.g., those arising from metastasis, the migration of tumor cells to secondary sites that are different from the site of the original tumor). A cancer may include, for example, gastric, myeloid, colon, nasopharyngeal, esophageal, and prostate tumors, glioma, neuroblastoma, breast cancer, lung cancer, ovarian cancer, colorectal cancer, thyroid cancer, leukemia (e.g., Adult T-cell leukemia, Acute monocytic leukemia, Acute myeloid leukemia, Acute promyelocytic leukemia, myelogenous leukemia, lymphocytic leukemia, acute myelogenous leukemia (AML), chronic myeloid leukemia (CML), acute lymphoblastic leukemia (ALL), T-lineage acute lymphoblastic leukemia or T-ALL chronic lymphocytic leukemia (CLL), myelodysplastic syndrome (MDS), hairy cell leukemia), lymphoma (Hodgkin's lymphoma (HL), non-Hodgkin's lymphoma (NHL)), multiple myeloma, bladder, renal, gastric (e.g., gastrointestinal stromal tumors (GIST)), liver, melanoma and pancreatic cancer, sarcoma, Adenocarcinoma, Astrocytoma, Bone Cancer, Brain Tumor, Burkitt's lymphoma, Carcinoma, Cervical Cancer, Chronic Lymphocytic Leukemia, Chronic myelogenous leukemia, Endometrial cancer, Glioblastoma multiforme, Glioma, Hepatocellular carcinoma, Hodgkin's lymphoma, Inflammatory breast cancer, Kidney Cancer, Leukemia, Lymphoma, Malignant Mesothelioma, Medulloblastoma, Melanoma, Multiple myeloma, Neuroblastoma, Non-Hodgkin Lymphoma, Non-Small Cell Lung Cancer, Pancreatic Cancer, Pituitary tumor, Retinoblastoma, Skin Cancer, Small Cell Lung Cancer, Squamous cell carcinoma, Stomach cancer, T-cell leukemia, T-cell lymphoma, and Wilms' tumor.
As used herein the term “frameshift mutation” is a mutation causing a change in the frame of the protein. Thus, a frameshift variant peptide is a peptide in which a frame has changed due to a frameshift mutation. In some embodiments provided herein, a frameshift includes two or more pooled frameshifts. As used herein, the term “pooled” refers to a plurality of frameshift samples that have been combined to create a new composition.
As used herein, the term “microsatellite instability,” also known as “MSI” refers to the changes in microsatellite repeats in tumor cells or genetic hypermutability caused due to deficient DNA mismatch repair. Microsatellites, also known as simple sequence repeats, are repeated sequences of DNA comprising repeating units 1-6 base pairs in length. Although the length of microsatellites is highly variable from person to person and contributes to the DNA fingerprint, each individual has microsatellites of a set length. MSI results from the inability of the mismatch repair (MMR) proteins to fix a DNA replication error. MSI comprises DNA polymorphisms, wherein the replication errors vary in length instead of sequence. MSI comprises frame-shift mutations, either through insertions or deletions, or hypermethylation, leading to gene silencing. It is known in the art that microsatellite instability may result in colon cancer, gastric cancer, endometrium cancer, ovarian cancer, hepatobiliary tract cancer, urinary tract cancer, brain cancer, and skin cancers.
Cell Lines and Tissues
HEK293, B16-F10 and 4T1 cell lines were purchased from ATCC in 2006. Upon receipt, cells were cultured for three passages in RPMI medium (ATCC) with 10% FBS, 100 U/mL penicillin, and 100 mg/mL streptomycin and stored in aliquots under liquid nitrogen. Cells were maintained at 37° C. under humidified 5% CO2, 95% air. Cells between 2 and 20 passages were used. Cell lines were not re-authenticated. Other cells lines are listed in Table 2 and were cultured in ATCC-recommended media.
Mice and Mouse Tumor Models
BALB/c and C57BL/6 mice were from Charles River Laboratories or Jackson Laboratories. For the tumor challenge, 5×103 4T1 cells were injected in the mammary pad at the right flank of the mice, or 1×105 B16F10 cells were injected subcutaneously in the right flank of the mice. Tumor volumes were measured and calculated by (Length2×Width/2) daily after the size was larger than 1 mm3. Breeding pairs of BALB-neuT and FVB-neuN (FVB/N-Tg (MMTVneu) 202Mul) mice were obtained from Joseph Lustgarten, Mayo Clinic Arizona. Mice were monitored weekly for the tumor incidence after tumor size reached 1 mm3. All experiments were performed in accordance with protocols approved by the Institutional Animal Care and Use Committee of Arizona State University.
Statistical significance of differences was analyzed by a Student t-test.
EST Analysis
To identify potential putative chimeric transcripts, that when translated would result in a frame-shifted neo-peptide, two publicly available datasets and applied an algorithm that was used to identify chimeric transcripts were used. Specifically, the sequences found within the Expressed Sequence Taq (EST) library and the Human RefSeq database (23) from the National Center for Biotechnology Information (NCBI) were used. Using the stand-alone BLAST program, all EST sequences were aligned to RefSeq. ESTs that aligned with 50-85 base pairs and had 95% homology to RefSeqs that have been previously annotated by National Center Institute (NCI) were selected. The alignment data was filtered by eliminating the EST sequences that did not align to multiple RefSeqs or were aligned in the 3′-5′ orientation. Lastly, the sequences that aligned with non-coding sequence regions were eliminated. The remaining EST sequences were then used to identify the chimeric transcripts. Only the ESTs that aligned to two or more distinct RefSeq in consecutive positions were considered to be potential candidates. To be defined as a coding chimeric transcript, the EST sequences had to be at least 100 bp long with sequence similarity greater than or equal to 95% to the RefSeq. Also, the junction points between the two genes had to occur within the coding sequence of the upstream gene and orientation of the upstream gene alignment had to be in the positive (5′-3′) orientation. To eliminate false calls, all potential chimeric EST sequences had to be either present in more than one cDNA library or supported by three or more independent EST sequences. In addition, chimeric transcripts were classified based on the relative position of two genes. Classification of types of chimeric transcript was based on relative position of two fusion genes on the chromosome. Specifically, genes found on different chromosomes resulted in inter-chromosomal fusion while genes found in same chromosome were intra-chromosomal or read-through chimeric transcripts. Read-through chimeric transcripts resulted from two neighboring genes on same strand, otherwise intra-chromosomal.
PCR Screen for EST FS Candidates
The 50 Human Breast cancer cell lines were obtained from the American Type Culture Collection (ATCC) and were grown according to recommendations. Human breast cancer tissue specimens were acquired from Mayo Clinic, and were informed consent and approval by the Mayo Clinic Institutional Review Board. All specimens were coded and anonymized. All experiments were performed in accordance with the approval protocol. Total RNA was extracted from breast cancer cell lines and primary breast tissues using the TRIzol LS reagent (Life Technologies, Carlsbad, CA) following the manufacturers protocol. RNA integrity was determined by gel electrophoresis and concentration was determined by measuring absorbance at 260/280 on the Nano-drop (NanoDrop Products, Wilmington, DE). cDNA was prepared by using the SuperScript™ III First-Strand Synthesis SuperMix (Life Technologies, Carlsbad, CA) that includes random hexamers and oligo dT's following the manufacturer's recommended protocol. cDNA integrity and quality were assessed by performing a β-actin control PCR. End Point PCR primers for each chimeric transcript were designed using Primer3 (24) so that the forward and reverse primers both bind 80 bp to 280 bp upstream/downstream from the junction point. End-point PCR reactions using approximately 25 ng of cDNA, reagents from (Life Technologies, Carlsbad, CA) and 35 cycles were performed using Mastercycler ep gradient S (Eppendorf, Hamburg, Germany). PCR products were analyzed on 1.5% agarose gels. PCR products were purified, and sequence confirmed by Applied Biosystems 3730 (Life Technologies, Carlsbad, CA) sequencing.
End-Point RT-PCR
cDNAs from human primary breast tumors and normal mammary glands were from BioChain (Newark, CA). Total RNA from other sources was extracted with TRIzol (Life Technologies, Carlsbad, CA). cDNA was synthesized from total RNA using the SuperScript III First-Stand Synthesis SuperMix (Life Technologies). The primer sequences used for end-point RT-PCR were synthesized by Life Technologies or Sigma. End-point RT-PCR reactions (25 sL) used the GoTaq PCR kit (Promega, Madison, WI) and the following conditions: 95° C. for 2 min; 35 cycles of 95° C. for 30 secs, 60° C. for 30 sec (annealing), and 72° C. for 10 to 30 sec (extension); and 72° C. for 5 min. Exceptions were that mouse SMC1A primers used an annealing temperature of 55° C., and β-actin primers were done with 25 cycles and 30 sec of extension time. Sequence verification was performed on RT-PCR products in initial reactions and later during intermittent reactions. The following primers (from 5′ to 3′) for the PCR were used: SEC62 DNA human forward: TGCCATACCTGTTITITCCC (SEQ ID NO: 1); SEC62 human DNA reverse: AGTTATCTCAGGTAGGTGTTGC (SEQ ID NO: 2); SEC62 DNA dog forward: AAGGGAGTCTGTGGTTGA (SEQ ID NO: 3); SEC62 DNA dog reverse: CAAAGAGGGAAGAGAGTGG (SEQ ID NO: 4); SEC62 cDNA human forward: AAAGGAAAAGCTGAAAGTGGAA (SEQ ID NO: 5); SEC62 human cDNA reverse: GCAACAGCAAGGAGAAGAATAC (SEQ ID NO: 6); SEC62 cDNA dog forward: AAGGGAGTCTGTGGTTGA (SEQ ID NO: 7); SEC62 cDNA dog reverse: CAAAGAGGGAAGAGAGTGG (SEQ ID NO: 8); SMC1A mouse forward: CTGTCATGGGTTTCCTG (SEQ ID NO: 9); SMC1A mouse reverse: GAGCTGTCCTCTCCTTG (SEQ ID NO: 10); SMC1A human forward: CCTGAAACTGATTGAGATTGAG (SEQ ID NO: 11); SMC1A human reverse: TCTTCAGCCTTCACCATTTC (SEQ ID NO: 12); β-actin mouse forward: CCAACCGTGAAAAGATGACC (SEQ ID NO: 13); β-actin mouse reverse: TGCCAATAGTGATGACCTGG (SEQ ID NO: 14); β-actin human forward: CCAACCGCGAGAAGATGACC (SEQ ID NO: 15); β-actin human reverse: TGCCAATGGTGATGACCTGG (SEQ ID NO: 16); Rat Her-2 forward: ATCGGTGATGTCGGCGATAT (SEQ ID NO: 17); Rat Her-2 reverse: GTAACACAGGCAGATGTAGGA (SEQ ID NO: 18).
Sec62 Transfection and Flow Analysis
HEK293 cell line were purchased from ATCC and cultured with standard protocols. Lipofectamine 2000 Transfection Reagent (Thermo Fisher Scientific, MA) was used to transfect plasmids into cell lines for overnight. Cells were then prepared in FACS buffer and quantified with flow cytometry. The three open reading frames (ORFs) were assembled by PCR and inserted into pCMVi vector at EcoR I MCS site. Detailed sequences of three ORFs were included in Table 6.
Gene Expression
Gene expression was measured with the TaqMan Gene Expression Assay (Life Technologies) according to the manufacturer's directions. The hSMC1A-specific labeled probe was 5′-CAATGGCTCTGGGTGCTGTGGAATC-3′ (SEQ ID NO: 19). The unlabeled forward and reverse primers were 5′-GGGTCGACAGATTATCGGACC-3′ (SEQ ID NO: 20) and 5′-GTCATACTCCTGCGCCAGCT-3 (SEQ ID NO: 21), respectively. Results were normalized by human GAPDH.
Microsatellite Frameshift antigens: human mRNA sequences were acquired from NCBI CCDS databases (25). Microsatellite regions (homopolymers of 7 runs or more) were mapped to human coding genes, 2nd and 3rd reading frame peptide sequences after MS regions were predicted and stored in Microsatellite FS database, MS FS peptides 10 aa or longer were included in the human FS peptide array.
Mis-splicing Frameshift antigens: human mRNA sequences and exon coordinates were acquired from NCBI Refseq database (23). 2nd and 3rd reading frame FS peptide sequences were predicted from the start of every exon. Then all the FS peptides were aligned against the human proteome, FS peptides with higher than 98% homology to wild type proteome were removed. FS peptides 10 aa or longer were then included in the human FS peptide array. Table 7 depicts exemplary variant FS peptides.
A total number of 64 non-cancer control samples and 13 pancreatic stage 1 cancer samples, 85 late stage cancer samples from 5 cancer types were tested on the FS array, detailed information was summarized in Table 5. All samples were acquired from collaborators and were informed consent upon collection through the institute's own IRB. All samples were anonymized before receipt at Arizona State University (ASU) via Institutional Review Board (IRB) protocol No. STUDY00003722, ‘Receipt of Deidentified Human Serum for Immunosignature Analysis’ and protocol No. 0912004625, ‘Profiling Biological Sera for Unique Antibody Signatures’. All experiments were performed in accordance with the approval protocol.
400K Frameshift Peptide Array Assay
Serum was diluted 1:100 in binding buffer (0.01M Tris-HCl, pH 7.4, 1% alkali-soluble casein, 0.05% Tween-20) and 150 μl diluted samples were loaded into each compartment of the 12-plex array and incubated overnight at room temperature or 4° C. After sample binding, the arrays were washed 3× in wash buffer (1×TBS, 0.05% Tween-20), 10 min per wash. Primary sample binding was detected via Alexa Fluor® 647-conjugated goat anti-human IgG secondary antibody (Jackson ImmunoResearch #109-605-098). The secondary antibody was diluted 1:10,000 (final concentration 0.15 ng/μl) in secondary binding buffer (Ix TBS, 1% alkali-soluble casein, 0.05% Tween-20). Arrays were incubated with secondary antibody for 3 h at room temperature, washed 3× in wash buffer (10 min per wash), 30 secs in reagent-grade water, and then dried by centrifuging at 690 RPM for 5 mins. All washes and centrifugations were done on a Little Dipper 650C Microarray Processor (SciGene) with preset programs. Fluorescent signal of the secondary antibody was detected by scanning at 635 nm at 2 μm resolution and 15% gain, using an MS200 microarray scanner (Roche NimbleGen).
Plasmids for Genetic Immunization
The DNA fragments encoding FS peptides were cloned as a C-terminal fusion into the genetic immunization vectors pCMVi-UB (26) and pCMVi-LSrCOMPTT (27, 28) with the Bgl II and Hind III and mixed with 1:1 ratio as the vaccine antigen. Three adjuvants were encoded by genetic immunization vectors. The pCMVi-mGM-CSF vector expresses the adjuvant mouse granulocyte/macrophage colony-stimulating factor (mGM-CSF) under control of the human cytomegalovirus (CMV) promoter (27). LTAB indicates immunization with 1:5 ratio by weight of two plasmids, pCMVi-LTA and pCMVi-LTB, expressing the heat-labile enterotoxins LTA and LTB from Escherichia coli. These plasmids express LTA and LTB as C terminal fusions to the secretion leader sequence from the human α1 antitrypsin gene (29). Vectors pCMVi-UB, pCMVi-LSrCOMPTT, pCMVi-LTA (also called pCMVi-LS-LTA-R192G) and pCMVi-LTB are available from the PSI:Biology-Materials Repository DNASU (dnasu.org) at Arizona State University. Additional adjuvants were the class A CpG 2216 single-stranded oligodeoxynucleotide obtained from Sigma and alum from Pierce.
Bullet Preparation for Genetic Immunization with Gene Gun
Bullets for biolistic genetic immunization used the gold micronanoplex approach and were prepared as described (30) with the following changes. Two grams of 1-micron gold was used. Prior to addition of N-hydroxysuccinimide and N-(3-dimethylaminopropyl)-N′-ethylcarbodiimide hydrochloride, the gold was resuspended in 20 mL of a 0.1 M solution of 2-(N-morpholino) ethanesulfonic acid (MES), pH 6.0. DNA-gold micronanoplexes were prepared by combining, per bullet, 57 μL of cysteamine-gold solution with precipitated DNA (≤10 μg) that had been resuspended in ≤15 μL of water, and then vortexing for 10 min. To the DNA-cysteamine-gold was added 6 L/bullet of a freshly made solution of PEI-micron gold (167 mg/mL in 0.1 M MES, pH 6, without NaCl). The pelleted micronanoplexes were washed with ethanol prior to resuspension in n-butanol (55 L/bullet), followed by bullet formation under nitrogen gas.
Immunization Dosage and Regime and Tumor Challenge
C57BUB16-F10 Mouse Melanoma Model
Six week old mice (n=10 per group) received one genetic immunization with the Gene Gun in the pinna of the ear (4 shots/mouse) with 20 ng of antigen (SMC1A-1{circumflex over ( )}4 and non-protective Cowpox viral antigen CPV 172 (31)) in pCMVi vectors plus the adjuvants pCMVi-mGM-CSF (0.5 μg) and CpG 2216 (5 μg) for each shot. All of the mice were challenged with 1×105 B16-F10 cells 4 weeks after the immunization.
BALB/C-4T1 Mouse Breast Tumor Model
For the three MS FS experiments, all mice (n=10 per group) were genetically immunized in the ear by Gene Gun at 8 weeks of age (2 shots/mouse, 60 ng pooled antigens plus 0.25 μg LTAB and 2.5 μg CpG2216 as the adjuvant for each shot) and boosted twice (two days apart) in three weeks with 1 μg pooled antigens plus the same adjuvants dosage. All mice were boosted again in two weeks with 50 μg KLH conjugated MS FS peptides with 50 μg CpG 2216 and 50 ul alum in total 100 ul PBS. The negative groups were immunized with the empty vectors and KLH protein with the same dosage. All mice were challenged with 5×103 4T1 cells two weeks after the last immunization.
For the mSMC1A-1{circumflex over ( )}4 experiment, all mice were (n=10 per group) genetically immunized in the ear by Gene Gun at 8 weeks of age (2 shots/mouse, 1 μg antigen plus 0.25 μg LTAB and 2.5 μg CpG2216 as the adjuvant for each shot), and boosted in two weeks with KLH conjugated SMC1A-1{circumflex over ( )}4 peptide plus 50 μg Poly:IC (Sigma) in 100 ul PBS. The same regime was repeated in two weeks. The negative groups were immunized with the empty vectors and KLH protein with the same dosage. All mice were challenged with 5×103 4T1 cells 4 weeks after the last immunization. The CD8 and CD4 T cell depletion started 2 weeks after the last immunization by i.p injection of 100 μg antibody (anti CD8, clone 2.43; anti CD4, clone GK 1.5; BioXCell, West Lebanon, NH) every 3 days until the end of the experiment.
BALB-neuT Mice
Mice were genetically immunized by Gene Gun at 4-6 weeks with 100 ng of antigen(s) in pCMVi vectors, boosted twice (3-4 days apart) at 9-10 weeks with 1 μg of the same antigen(s), and boosted once at 13-14 weeks with protein. Genetic immunizations included adjuvants LTAB (0.5 μg) and CpG 2216 (5 μg). Protein boosts were 50 μg of KLH conjugated FS peptides (SMC1A-1{circumflex over ( )}4, n=32; RBM FS, n=22; SLAIN2 FS, n=14 and pool of three FS neoantigens, n=37). The protein boost included 50 μg CpG 2216 and 50 μl alum in 100 μl PBS as the adjuvant. The negative groups (n=30) were immunized with the empty vectors and GST or KLH protein with the same adjuvants and dosage.
ELISPOT
Peptides used in the ELISPOT assays were synthesized in-house. The Mouse IFN-7 ELISPOT Set (BD Biosciences) was used according to the manufacturer's directions except that blocking was at 37° C. 106 fresh mouse splenocytes were added to each well, followed by co-culturing for 48 hr with 20 μg of peptide in a volume of 200 μl RPMI medium. The plate was scanned and spots were analyzed by the AID EliSpot Reader System (Autoimmun Diagnostika GmbH, Germany).
Statistical Analysis
The statistical calculation software used was GraphPad Prism 7 (GraphPad Software, San Diego, CA) and JMP Pro (SAS Institute, NC). The data presentation and the statistical tests for each experiment are indicated in the legend of the corresponding figures, as well as the samples size and p-values.
Mistakes in RNA mis-splicing and transcription, particularly of INDELs of MSs in coding regions, in cancer cells may also be a source of neoantigens.
As seen in
This model makes several specific predictions. First, frequent FS variants in different cancers will be produced by errors in RNA splicing and transcription, not as DNA mutations. As an example of errors in mis-splicing, substantial levels of a FS transcript, SMC1 A1{circumflex over ( )}4 (exon 1 to exon 4), from the gene SMC1A in different mouse and human tumors were found (
The analysis of RNA-generated FS variants was expanded by comparing NCBI tumor EST libraries to normal EST libraries. To simplify the analysis, FS variants caused by exon skipping or trans-splicing were focused on, i.e. splicing exons from different genes. A total of 12,456 exon skipping variants and 5,234 trans-splicing variants were found (
Another source of FS transcripts in tumors predicted by embodiments of the model provided herein is INDELs in MSs generated in transcription. As an example, the microsatellite region in the Sec62 gene contains 9 and 11 repeats of Adenine in human and dog, respectively. The sequence of Sec62 and the corresponding INDEL frameshift peptides are shown in
To further validate the INDELs in the transcription and the translation of the FS peptide, three plasmids based on the dog Sec62 gene were constructed. One has the eGFP fused in the 3rd reading frame to the MS region of 11 A in the dog Sec62 CDS. The eGFP protein will be correctly translated if there is one A insertion during the transcription. The 11 A with 11 nucleotides of non-MS sequence in another plasmid as the negative control was replaced, so there is no MS related INDEL in the transcription and no expression of eGFP. The 11 A with 12A as the positive control was also replaced, so the eGFP is in the 1st reading frame and would be translated with the upstream dog Sec62 gene. (
The model also predicts that the increased expression of FS variants, combined with other aberrant proteins, would overwhelm the quality control system and could potentially elicit immune responses to these FS peptides. To test this, an array of all possible predicted RNA-defined frameshift peptides was designed, meeting specific qualifications that the tumor cell could produce from INDELs in coding MS and mis-splicing of exons.
There are over 8000 MS in the coding region of the human genome that are runs of 7 or more repeats of homopolymers. The majority of MS regions meeting selection criteria are A runs and the number of MS candidates decreases exponentially as the repeat length or frameshift peptide length criteria increases. Each MS could generate 2 predictable FS peptides depending on whether there was an insertion or deletion. In addition, there are ˜200,000 possible FS peptides that could be generated by mis-splicing of exons in the human genome, such as the examples of mis-splicing FSs. Similar to MS FSs, the number of mis-splicing FSs decreases exponentially as the FS peptide length requirement increases. Most of mis-splicing FSs are generated from the first 10 exons of human genes. The restriction of the peptide being longer than 10 amino acids for both sources of FS was applied. By these criteria there are over 220,000 possible FS antigens. Each FS antigen that was longer than 15 aa was divided into 15 aa, non-overlapping peptides. This produced a total of ˜400,000 peptides. Peptides that share more than 10 aa identical sequences with any human reference proteins were excluded. Finally, each FS array was designed to contain a total of 392,318 FS peptides (
NimbleGen (Roche, Madison, WI) synthesized the FS peptide array, processed the array assay and summarized the IgG signals of each array with their standard protocol (51). The specific IgG reactivities was analyzed to these FSPs in 64 non-cancer control samples and a total of 85 cancers from 5 different late stage cancer types with 17 samples each (LC: lung cancer, BC: breast cancer, GBM: glioblastoma, GC: gastric cancer, PC: pancreatic cancer) and 12 stage I pancreatic cancer samples.
Each array was normalized to its median florescence for analysis. Three patterns of FS feature reactivity that were higher in cancer than non-cancer were found: common reactivity against FS peptides across all 5 cancer types; cancer type specific reactivity and personal reactivity. Reactivity against ˜7000 selected peptides are shown in
Total reactivity on the 400K arrays was evaluated in the 5 cancer types and non-cancer samples with two methods. The first method compares the number of significant peptides in the cancer and control samples using fold change and p-values. By this method, BC, GC, PC and LC cancer samples had significantly more FS peptides compared to control samples which met the fold change and p-value criteria described in
The analysis of individual cancer samples within the same cancer type using the scoring method showed that there were three patterns of reactivity. Most of the positive FS peptides (69%˜80%) were personal for that individual. However, 16%˜19% of the positive peptides were shared between two samples in that cancer type, with 1.5%˜6.9% shared between 3 or more. The distribution of these classes is shown in
Embodiments of the model provided herein predicts that a FS peptide with high antibody reactivity is highly immunogenic and/or highly expressed in the tumor cells. These FS peptides could be cancer vaccine candidates. Analysis of the distribution of positive peptides allows the formulation 3 types of potential vaccines. One type is a personal vaccine. As an example, the personal vaccines for the 17 GBM patients are shown. Each patient had ˜5800 positive FS peptides using the 6SD cut-off criterion and ˜4500 positive FS peptides being unique for that patient (
As noted in
Finally, it was determined if there were FS peptides that were common across all 5 cancer types that met the p-value and frequency requirements. In
All of the samples used for this analysis were from patients with late stage cancer. Cancer vaccines could also potentially be used for treatment of early stage cancers, and it is unclear whether early and late stage cancer vaccines would require different components. 20,000 most reactive and recurrent peptides were compared to non-cancer for both the late stage and stage 1 pancreatic cancer. As evident in
The data presented herein shows that FS variants are present at the RNA level in tumors and that antibody responses to these FS peptides are present in cancer patients. However, the clinically relevant question is whether these FS variants can afford therapeutic value as vaccines, which is explored using mouse tumor models.
It was determined if the SMC1A 1{circumflex over ( )}4 FS peptide confers protection in the B16F10 mouse melanoma cancer model and/or the 4T1 mouse breast cancer model. This FS variant was shown to be common in both human and these mouse tumors (
It was tested whether the detection of FS variants in the RNA correlated with protection. The SLAIN2 and ZDHHC17 FSs had been identified in sequencing B16F10 cDNA. The SLAIN2 FS was present in the 4T1 mammary cancer cell line, but ZDHHC17 FS was not (
The model (
Embodiments of the model provided herein also predicts that each tumor cell will present multiple FS neoantigens. These peptides could be presented at low levels as only a fraction of each RNA would be defective. Therefore, multiplexing neoantigens in a vaccine would be predicted to be more protective. To test this prediction, three FS neoantigens were tested individually and pooled together as vaccines in the BALB-NeuT transgenic mouse mammary cancer model. Each FS neoantigen-based vaccine individually showed similar protection by significantly delaying the tumor growth. As predicted, the pooled neoantigen vaccine produced a significant additive increase in delaying tumor initiation and growth (
Furthermore, as shown in
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While preferred embodiments of the present invention have been shown and described herein, it will be obvious to those skilled in the art that such embodiments are provided by way of example only. Numerous variations, changes, and substitutions will now occur to those skilled in the art without departing from the invention. It should be understood that various alternatives to the embodiments of the invention described herein may be employed in practicing the invention. It is intended that the following claims define the scope of the invention and that methods and structures within the scope of these claims and their equivalents be covered thereby.
Any and all applications for which a foreign or domestic priority claim is identified in the Application Data Sheet as filed with the present application are hereby incorporated by reference under 37 CFR 1.57. The present application is a continuation of PCT application PCT/US2020/053728, filed Oct. 1, 2020, which claims the benefit of U.S. Provisional patent application Ser. No. 62/909,748 entitled “Methods and Compositions for Identifying Neoantigens for Use in Treating and Preventing Cancer,” filed Oct. 2, 2019, which are incorporated herein by reference in its entirety.
This invention was made with government support under W81XWH-07-1-0549 awarded by the Army Research office. The government has certain rights in the invention.
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| Number | Date | Country | |
|---|---|---|---|
| 20220257701 A1 | Aug 2022 | US |
| Number | Date | Country | |
|---|---|---|---|
| 62909748 | Oct 2019 | US |
| Number | Date | Country | |
|---|---|---|---|
| Parent | PCT/US2020/053728 | Oct 2020 | WO |
| Child | 17711849 | US |
