Method, system, and computer-accessible medium for modifying and / or redesigning peptide-centric chimeric antigen receptors (PC-cars) against novel peptide antigens

Abstract

Disclosed herein are methods, systems, computer-implemented methods, and computer-accessible media for modifying and / or redesigning peptide-centric chimeric antigen receptors (PC-CARs) against novel peptide antigens.

Description

Attorney Docket No. 11820-034W01YAR01-11PROMETHOD, SYSTEM, AND COMPUTER-ACCESSIBLE MEDIUM FOR MODIFYING AND / OR REDESIGNING PEPTIDE-CENTRIC CHIMERICANTIGEN RECEPTORS (PC-CARS) AGAINST NOVEL PEPTIDE ANTIGENSCross-Reference to Related Applications

[0001] This application claims the benefit of U.S. Provisional Patent Application No. 63 / 702,967, filed on October 3, 2024, the content of which is incorporated by reference herein in its entirety.Field of the Disclosure

[0002] The present disclosure is related to methods, systems, computer- implemented methods, and computer- accessible media for modifying and / or redesigning peptide-centric chimeric antigen receptors (PC-CARs) against novel peptide antigens.Background

[0003] Chimeric antigen receptor (CAR) T cell therapy has revolutionized cancer treatment, demonstrating exceptional efficacy against specific leukemias. Recently, it has been proven that targeting peptides displayed on major histocompatibility complexes (MHCs) greatly expands the number of actionable CAR antigens, facilitating targeting of essential and oncogenic intracellular proteins. However, developing peptide-centric CARs (PC-CARs) is challenging due to the low abundance of specific peptides on a given MHC, the small surface area of the peptide (<1% of the pMHC surface) for precise recognition, and the hypervariability of MHCs in the human population.

[0004] Accordingly, there is a need to address and / or at least partially overcome at least some of the deficiencies described herein.Summary

[0005] Such issues and / or deficiencies can at least be partially addressed and / or overcome with the exemplary embodiments of the present disclosure. To that end, according to the exemplary embodiments of the present disclosure, it is possible to provide an exemplary method, system and computer-accessible medium to utilize a generative one or more artificial intelligence (Al) models to generate and / or redesign a lead PC-CAR, 10LH, for example, initially capable of recognizing PHOX2B peptides upregulated in neuroblastoma, against novel peptide antigens. This can be done, for example, to recognize a CHRNA3 peptide displayed on the same MHC. Such exemplary embodiments of the present has the potential to significantly accelerate a determination or a generation of new PC-CARsAttorney Docket No. 11820-034W01YAR01-11PRO(including, but not limited to CARs that recognize the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)) for treating neuroblastoma and other cancers.

[0006] Indeed, the exemplary embodiments of the present disclosure can decrease the amount of time required to identify PC-CARs against new pMHCs by redesigning old PC- CARs with structural data. Indeed, it can be preferrable to maintain MHC contacts while changing peptide-contacting contacts. Thus, according to the exemplary embodiments of the present disclosure, it is possible to provide PC-CARs against CHRNA3 peptides which can be identified as enriched in neuroblastoma and can facilitate new PC -CAR T cell therapies for, e.g., neuroblastoma.

[0007] In some implementations, a computer-implemented method for generating a peptide centric (PC) chimeric antigen receptor (CAR) (PC-CAR) binding molecule is provided. The method can include: a) retrieving, by at least one processor, a first PC-CAR binding molecular model for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule; b) determining, by the at least one processor, PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC-CAR molecules; c) iteratively modeling, by the at least one processor, on-target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule; d) generating, by the at least one processor, a relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules that bound to the second target peptide in step c) to increase molecular complex structural stability of the modified PC-CAR binding molecules; e) analyzing, by the at least one processor, binding of the generated relaxed structure models to identify the best on-target binders from step d); f) iteratively modeling, by the at least one processor, off-target binding of the best on-target binders from the plurality of modified PC-CAR binding molecules of step e) to the first target peptide in the context of the first MHC molecule; g) identifying, by the at least one processor and based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step f), wherein the candidate modified PC-CAR binding molecules bind the second target peptide in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule, and exhibits affinity and specificity for the second peptide target.Attorney Docket No. 11820-034W01YAR01-11PRO

[0008] In some implementations, the method further includes: subsequent to iteratively modeling off-target binding, generating a second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules to increase stability of the modified PC- CAR binding molecules that did not bind to the first target peptide in step f).

[0009] In some implementations, the method further includes: aligning, by the at least one processor, a known PC-CAR structure model of known specificity with a target to generate the first PC-CAR binding molecular model.

[0010] In some implementations, aligning the known PC-CAR structure model to generate the first PC-CAR binding molecular model includes: identifying, by the at least one processor, peptide-binding residues within 6 Angstroms (A) of the known PC-CAR structure model, modeling, by the at least one processor, a new target pMHC molecule separately without the known PC-CAR structure model, modeling, by the at least one processor, the first PC-CAR binding molecular model or crystal structure, and superimposing, by the at least one processor, the PC-CAR-pMHC structure of the known PC-CAR structure model onto the modeled pMHC molecule, removing, by the at least one processor, the known pMHC from the new target pMHC molecule (PC-CAR superimposed on CHRNA3-pMHC), wherein the new target pHMC is used as an input to generate the plurality of modified PC-CAR molecules.

[0011] In some implementations, analyzing binding of the generated relaxed structure models includes: determining a specificity score for each molecule and selecting the plurality of candidate modified PC-CAR binding molecules to the second target peptide based on the determined specificity scores.

[0012] In some implementations, the specificity score for each molecule is determined based on possible bonds (e.g., interactions between a respective PC-CAR and pMHC molecule) within the respective model that are between 0-4 Angstroms (A).

[0013] In some implementations, generating the plurality of modified PC-CAR binding molecules includes using a deep learning model to predict a three-dimensional protein structures from a sequence corresponding with each molecule.

[0014] In some implementations, the first PC-CAR binding molecular model includes a computer structure model or crystal structure model.

[0015] In some implementations, the PC-CAR residues that facilitate binding to a second target peptide are determined based on binding residues within a predefined distance threshold.

[0016] In some implementations, the predefined distance threshold is between 0-6 A.Attorney Docket No. 11820-034W01YAR01-11PRO

[0017] In some implementations, the predefined distance threshold after step c is 5-7 A.

[0018] In some implementations, the predefined distance threshold after step f is 3-5 A.

[0019] In some implementations, generating the first or second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules includes performing a relaxation operation or modeling each PC-CAR binding molecule in a lower-energy state.

[0020] In some implementations, the first PC-CAR binding molecular model is selected from a plurality of sequences that includes most frequent sequences and best scoring (e.g., lowest or highest) sequences.

[0021] In some implementations, the plurality of candidate modified PC-CAR binding molecules are used for in vitro testing.

[0022] In some implementations, the first target peptide includes a PHOX2B epitope.

[0023] In some implementations, the PHOX2B epitope includes SEQ ID NO: 38.

[0024] In some implementations, the first PC-CAR includes a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, and SEQ ID NO: 3, respectively.

[0025] In some implementations, the first PC-CAR includes a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, and SEQ ID NO: 22, respectively.

[0026] In some implementations, the first peptide includes a CHRNA3 epitope.

[0027] In some implementations, the CHRNA3 epitope includes SEQ ID NO: 39.

[0028] In some implementations, the first MHC is HLA-matched to the HLA of the subject.

[0029] In some implementations, the techniques described herein relate to a PC-CAR (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)) specific for a CHRNA3 epitope including a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ IDAttorney Docket No. 11820-034W01YAR01-11PRONO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.

[0030] In some implementations, the techniques described herein relate to a PC-CAR, wherein the PC-CAR includes a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21 , SEQ ID NO: 23, respectively.

[0031] In some implementations, the techniques described herein relate to a PC-CAR, wherein the PC-CAR include the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.

[0032] In some implementations, the techniques described herein relate to a method 24- 26.

[0033] In some implementations, the techniques described herein relate to a method of treating a cancer in a subject including administering to the subject a peptide centric (PC) chimeric antigen receptor (CAR) (PC-CAR) immune cell including a CAR specific for a CHRNA3 peptide epitope to the subject.

[0034] In some implementations, the techniques described herein relate to a method, wherein the CHRNA3 peptide epitope is set forth in SEQ ID NO: 39.

[0035] In some implementations, the techniques described herein relate to a method, wherein the PC-CAR includes a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.Attorney Docket No. 11820-034W01YAR01-11PRO

[0036] In some implementations, the techniques described herein relate to a method, wherein the PC-CAR includes a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively.

[0037] In some implementations, the techniques described herein relate to a method, wherein the PC-CAR includes the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.

[0038] In some implementations, the techniques described herein relate to a method, wherein immune cell is a T cell, B cell, natural killer (NK) cell, NK T cell, or macrophage.

[0039] In some implementations, the techniques described herein relate to a method, wherein the cancer includes a neuroblastoma / glioblastoma.

[0040] In some implementations, the techniques described herein relate to a system including: at least one processor; and a memory having instructions thereon, wherein the instructions when executed by the processor, cause the at least one processor to: a) retrieve a first PC-CAR binding molecular model for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule; b) determine PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC-CAR molecules; c) iteratively model on-target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule; d) generate a relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules that bound to the second target peptide in step c) to increase molecular complex structural stability of the modified PC-CAR binding molecules; e) analyze binding of the generated relaxed structure models to identify the best on-target binders from step d); f) iteratively model off-target binding of the best on- target binders from the plurality of modified PC-CAR binding molecules of step e) to the first target peptide in the context of the first MHC molecule; g) identify, based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step f), wherein the candidate modified PC-CAR binding molecules bind the second target peptideAttorney Docket No. 11820-034W01YAR01-11PRO in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule, and exhibits affinity and specificity for the second peptide target.

[0041] In some implementations, a method for designing PC CARs is provided. The method can include: selecting a known binder structure; identifying peptide binding residues within a defined distance score threshold; mutating selected residues using Al-based protein design tools; modeling mutated binders for target peptide binding and off-target exclusion; iteratively refining binders based on computational scoring and structural relaxation; and selecting binders with specificity to the target peptide-MHC complex for in vitro validation.

[0042] In some implementations, the techniques described herein relate to a non- transitory computer readable medium including a memory having instructions stored thereon to cause a processor to perform any of the methods or systems described herein.

[0043] In one aspect, disclosed herein are PC-CAR specific for a CHRNA3 epitope (such as, for example, SEQ ID NO: 39).

[0044] Also disclosed herein are PC-CAR of any preceding aspect, wherein the PC-CAR (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)) comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.

[0045] In one aspect, disclosed herein are PC-CAR of any preceding aspect (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)), wherein the PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively.Attorney Docket No. 11820-034W01YAR01-11PRO

[0046] Also disclosed herein are PC-CAR of any preceding aspect (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)), wherein the PC-CAR comprise the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.

[0047] In one aspect, disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and / or preventing a cancer and / or metastasis (such as, for example, a neuroblastoma / glioblastoma) in a subject comprising administering to the subject the PC- CAR of any preceding aspect (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)). For example, disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and / or preventing a cancer and / or metastasis (such as, for example, a neuroblastoma / glioblastoma) in a subject comprising administering to the subject a PC-CAR immune cell (including, but not limited to a T cell, B cell, natural killer (NK) cell, NK T cell, or macrophage), wherein the CAR is specific for SEQ ID NO: 39.

[0048] Also disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and / or preventing a cancer and / or metastasis of any preceding aspect, wherein the PC-CAR (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)) comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively. In one aspect, disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and / or preventing a cancer and / or metastasis of any preceding aspect, wherein the PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ IDAttorney Docket No. 11820-034W01 YAR01-11PRONO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively. For example, disclosed herein are methods of treating, inhibiting, reducing, decreasing, ameliorating, and / or preventing a cancer and / or metastasis of any preceding aspect wherein the PC-CAR comprises the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.Brief Description of Drawings

[0049] Further objects, features and advantages of the present disclosure will become apparent from the following detailed description taken in conjunction with the accompanying Figures showing illustrative embodiments of the present disclosure, in which:

[0050] Figure 1 A is a schematic representation of workflow in accordance with certain embodiments described herein.

[0051] Figure IB shows the proposed AI-Redesign CAR (AIR CAR) strategy overview.

[0052] Figure 1C illustrates iterative modification of generated PC-CARs.

[0053] Figure ID is a schematic diagram depicting a generalizable approach for all pMHC binders.

[0054] Figure IE is a flowchart diagram showing an expanded processing pipeline in accordance with certain embodiments described herein.

[0055] It should be appreciated that the logical operations described herein with respect to the various figures may be implemented (1) as a sequence of computer-implemented acts or program modules (i.e., software) running on a computing device (e.g., the computing device described in Figure IF), (2) as interconnected machine logic circuits or circuit modules (i.e., hardware) within the computing device and / or (3) a combination of software and hardware of the computing device.

[0056] Figure IF is an example computing device.

[0057] Figure 2 is a diagram of an example PC-CAR design system configured to facilitate the development of PC-CARs for therapeutics targeting intracellular tumor driver via pMHC complexes (e.g., class I MHC).

[0058] Figure 3 is a flowchart diagram showing an example method in accordance with certain embodiments described herein.Attorney Docket No. 11820-034W01 YAR01-11PRO

[0059] Figure 4A, Figure 4B, Figure 4C, and Figure 4D, illustrate experimental results from a conducted study.

[0060] Figure 4E shows a sequence alignment of AIRed-PC-CAR mutated CDR sequences (CDRL3, CDRH2, CDRH3).

[0061] Figure 4F shows sequence alignment for the PC-CAR CDRL3.

[0062] Figure 4G shows CDRL3 oriented loop structure.

[0063] Figure 4H shows peptide interactions are broken down to mainchain-based hydrogen bonding networks.

[0064] Figure 41 shows an alignment of the CDRH2 for the PC-CARs 10LH (SEQ ID NO: 17), 2_6 (SEQ ID NO: 17), 19_9 (SEQ ID NO: 18), 4_8 (SEQ ID NO: 19), 17_3 (SEQ ID NO: 20), 13_9 (SEQ ID NO: 19), 12_3 (SEQ ID NO: 20), 14_1 (SEQ ID NO: 19), 9_1 (SEQ ID NO: 21), 10_4 (SEQ ID NO: 18), 1_5 (SEQ ID NO: 11), 10_2 (SEQ ID NO: 20), 10_3 (SEQ ID NO: 20), and 6_2 (SEQ ID NO: 19).

[0065] Figure 4J shows Both KGD (i.e, the motif in the CDRH2 SEQ ID NO: 18) and RGD (i.e, the motif in the CDRH2 SEQ ID NO: 19) bind to the MHC (grey) through hydrogen bonds, orient other parts of the loop to bind to the MHC (ST).

[0066] Figure 4K shows DGS motif is another solution orientating framework residues to (ser and tyr) to interact with the HLA.

[0067] Figure 4L shows a sequence alignment for the CDRH3 amino acid sequences for 10LH (SEQ ID NO: 22) and the shared CDRH3 amino acid sequence for the modified PC- CARs 2_6, 19_9, 4_8, 17_3, 13_9, 12_3, 14_1, 9_1 , 10_4, 1_5, 10_2, 13_3, and 6_2 (SEQ ID NO: 23).

[0068] Figure 4M demonstrates that the CDH3-Q function depends on other motifs.

[0069] Throughout the drawings, the same reference numerals and characters, unless otherwise stated, are used to denote features, elements, components, or portions of the illustrated embodiments. Moreover, while the present disclosure will now be described in detail with reference to the figures, it is done so in connection with the illustrative embodiments and is not limited by the particular embodiments illustrated in the figures and the appended paragraphs.Detailed DescriptionDefinitions

[0070] An "increase" can refer to any change that results in a greater amount of a symptom, disease, composition, condition or activity. An increase can be any individual,Attorney Docket No. 11820-034W01YAR01-11PRO median, or average increase in a condition, symptom, activity, composition in a statistically significant amount. Thus, the increase can be a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100% increase so long as the increase is statistically significant.

[0071] A "decrease" can refer to any change that results in a smaller amount of a symptom, disease, composition, condition, or activity. A substance is also understood to decrease the genetic output of a gene when the genetic output of the gene product with the substance is less relative to the output of the gene product without the substance. Also for example, a decrease can be a change in the symptoms of a disorder such that the symptoms are less than previously observed. A decrease can be any individual, median, or average decrease in a condition, symptom, activity, composition in a statistically significant amount. Thus, the decrease can be a 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, 95, or 100% decrease so long as the decrease is statistically significant.

[0072] Inhibit," "inhibiting," and "inhibition" mean to decrease an activity, response, condition, disease, or other biological parameter. This can include but is not limited to the complete ablation of the activity, response, condition, or disease. This may also include, for example, a 10% reduction in the activity, response, condition, or disease as compared to the native or control level. Thus, the reduction can be a 10, 20, 30, 40, 50, 60, 70, 80, 90, 100%, or any amount of reduction in between as compared to native or control levels.

[0073] By ‘ ‘reduce” or other forms of the word, such as “reducing” or “reduction,” is meant lowering of an event or characteristic (e.g., tumor growth). It is understood that this is typically in relation to some standard or expected value, in other words it is relative, but that it is not always necessary for the standard or relative value to be referred to. For example, “reduces tumor growth” means reducing the rate of growth of a tumor relative to a standard or a control.

[0074] By ‘ ‘prevent” or other forms of the word, such as “preventing” or “prevention,” is meant to stop a particular event or characteristic, to stabilize or delay the development or progression of a particular event or characteristic, or to minimize the chances that a particular event or characteristic will occur. Prevent does not require comparison to a control as it is typically more absolute than, for example, reduce. As used herein, something could be reduced but not prevented, but something that is reduced could also be prevented. Likewise, something could be prevented but not reduced, but something that is prevented could also be reduced. It is understood that where reduce or prevent are used, unless specifically indicated otherwise, the use of the other word is also expressly disclosed.Attorney Docket No. 11820-034W01YAR01-11PRO

[0075] The term “subject” refers to any individual who is the target of administration or treatment. The subject can be a vertebrate, for example, a mammal. In one aspect, the subject can be human, non-human primate, bovine, equine, porcine, canine, or feline. The subject can also be a guinea pig, rat, hamster, rabbit, mouse, or mole. Thus, the subject can be a human or veterinary patient. The term “patient” refers to a subject under the treatment of a clinician, e.g., physician.

[0076] The term “treatment” refers to the medical management of a patient with the intent to cure, ameliorate, stabilize, or prevent a disease, pathological condition, or disorder. This term includes active treatment, that is, treatment directed specifically toward the improvement of a disease, pathological condition, or disorder, and also includes causal treatment, that is, treatment directed toward removal of the cause of the associated disease, pathological condition, or disorder. In addition, this term includes palliative treatment, that is, treatment designed for the relief of symptoms rather than the curing of the disease, pathological condition, or disorder; preventative treatment, that is, treatment directed to minimizing or partially or completely inhibiting the development of the associated disease, pathological condition, or disorder; and supportive treatment, that is, treatment employed to supplement another specific therapy directed toward the improvement of the associated disease, pathological condition, or disorder.

[0077] "Biocompatible" generally refers to a material and any metabolites or degradation products thereof that are generally non-toxic to the recipient and do not cause significant adverse effects to the subject.

[0078] “Effective amount” of an agent refers to a sufficient amount of an agent to provide a desired effect. The amount of agent that is “effective” will vary from subject to subject, depending on many factors such as the age and general condition of the subject, the particular agent or agents, and the like. Thus, it is not always possible to specify a quantified “effective amount.” However, an appropriate “effective amount” in any subject case may be determined by one of ordinary skill in the art using routine experimentation. Also, as used herein, and unless specifically stated otherwise, an “effective amount” of an agent can also refer to an amount covering both therapeutically effective amounts and prophylactically effective amounts. An “effective amount” of an agent necessary to achieve a therapeutic effect may vary according to factors such as the age, sex, and weight of the subject. Dosage regimens can be adjusted to provide the optimum therapeutic response. For example, several divided doses may be administered daily or the dose may be proportionally reduced as indicated by the exigencies of the therapeutic situation.Attorney Docket No. 11820-034W01YAR01-11PRO

[0079] A "pharmaceutically acceptable" component can refer to a component that is not biologically or otherwise undesirable, i.e., the component may be incorporated into a pharmaceutical formulation provided by the disclosure and administered to a subject as described herein without causing significant undesirable biological effects or interacting in a deleterious manner with any of the other components of the formulation in which it is contained. When used in reference to administration to a human, the term generally implies the component has met the required standards of toxicological and manufacturing testing or that it is included on the Inactive Ingredient Guide prepared by the U.S. Food and Drug Administration.

[0080] "Pharmaceutically acceptable carrier" (sometimes referred to as a “carrier”) means a carrier or excipient that is useful in preparing a pharmaceutical or therapeutic composition that is generally safe and non-toxic and includes a carrier that is acceptable for veterinary and / or human pharmaceutical or therapeutic use. The terms "carrier" or "pharmaceutically acceptable carrier" can include, but are not limited to, phosphate buffered saline solution, water, emulsions (such as an oil / water or water / oil emulsion) and / or various types of wetting agents. As used herein, the term "carrier" encompasses, but is not limited to, any excipient, diluent, filler, salt, buffer, stabilizer, solubilizer, lipid, stabilizer, or other material well known in the art for use in pharmaceutical formulations and as described further herein.

[0081] “Pharmacologically active” (or simply “active”), as in a “pharmacologically active” derivative or analog, can refer to a derivative or analog (e.g., a salt, ester, amide, conjugate, metabolite, isomer, fragment, etc. ) having the same type of pharmacological activity as the parent compound and approximately equivalent in degree.

[0082] “Therapeutic agent” refers to any composition that has a beneficial biological effect. Beneficial biological effects include both therapeutic effects, e.g., treatment of a disorder or other undesirable physiological condition, and prophylactic effects, e.g., prevention of a disorder or other undesirable physiological condition (e.g., a non- immunogenic cancer). The terms also encompass pharmaceutically acceptable, pharmacologically active derivatives of beneficial agents specifically mentioned herein, including, but not limited to, salts, esters, amides, proagents, active metabolites, isomers, fragments, analogs, and the like. When the terms “therapeutic agent” is used, then, or when a particular agent is specifically identified, it is to be understood that the term includes the agent per se as well as pharmaceutically acceptable, pharmacologically active salts, esters, amides, proagents, conjugates, active metabolites, isomers, fragments, analogs, etc.Attorney Docket No. 11820-034W01 YAR01-11PRO

[0083] The term “therapeutically effective” refers to the amount of the composition used is of sufficient quantity to ameliorate one or more causes or symptoms of a disease or disorder. Such amelioration only requires a reduction or alteration, not necessarily elimination.

[0084] “Therapeutically effective amount” or “therapeutically effective dose” of a composition (e.g. a composition comprising an agent) refers to an amount that is effective to achieve a desired therapeutic result. In some embodiments, a desired therapeutic result is the control of type I diabetes. In some embodiments, a desired therapeutic result is the control of obesity. Therapeutically effective amounts of a given therapeutic agent will typically vary with respect to factors such as the type and severity of the disorder or disease being treated and the age, gender, and weight of the subject. The term can also refer to an amount of a therapeutic agent, or a rate of delivery of a therapeutic agent (e.g., amount over time), effective to facilitate a desired therapeutic effect, such as pain relief. The precise desired therapeutic effect will vary according to the condition to be treated, the tolerance of the subject, the agent and / or agent formulation to be administered (e.g., the potency of the therapeutic agent, the concentration of agent in the formulation, and the like), and a variety of other factors that are appreciated by those of ordinary skill in the art. In some instances, a desired biological or medical response is achieved following administration of multiple dosages of the composition to the subject over a period of days, weeks, or years.

[0085] A “control” is an alternative subject or sample used in an experiment for comparison purposes. A control can be "positive" or "negative."

[0086] The disclosed nucleic acids are made up of for example, nucleotides, nucleotide analogs, or nucleotide substitutes. Non-limiting examples of these and other molecules are discussed herein. It is understood that for example, when a vector is expressed in a cell, that the expressed mRNA will typically be made up of A, C, G, and U. Likewise, it is understood that if, for example, an antisense molecule is introduced into a cell or cell environment through for example exogenous delivery, it is advantageous that the antisense molecule be made up of nucleotide analogs that reduce the degradation of the antisense molecule in the cellular environment.Nucleotides and related molecules

[0087] A nucleotide is a molecule that contains a base moiety, a sugar moiety and a phosphate moiety. Nucleotides can be linked together through their phosphate moieties and sugar moieties creating an internucleoside linkage. The base moiety of a nucleotide can be adenin-9-yl (A), cytosin-l-yl (C), guanin-9-yl (G), uracil- 1-yl (U), and thymin-l-yl (T). TheAttorney Docket No. 11820-034W01YAR01-11PRO sugar moiety of a nucleotide is a ribose or a deoxyribose. The phosphate moiety of a nucleotide is pentavalent phosphate. An non- limiting example of a nucleotide would be 3'- AMP (3'-adenosine monophosphate) or 5'-GMP (5'-guanosine monophosphate). There are many varieties of these types of molecules available in the art and available herein.

[0088] A nucleotide analog is a nucleotide which contains some type of modification to either the base, sugar, or phosphate moieties. Modifications to nucleotides are well known in the art and would include for example, 5 -methylcytosine (5-me-C), 5 -hydroxymethyl cytosine, xanthine, hypoxanthine, and 2-aminoadenine as well as modifications at the sugar or phosphate moieties. There are many varieties of these types of molecules available in the art and available herein.

[0089] Nucleotide substitutes are molecules having similar functional properties to nucleotides, but which do not contain a phosphate moiety, such as peptide nucleic acid (PNA). Nucleotide substitutes are molecules that will recognize nucleic acids in a Watson- Crick or Hoogsteen manner, but which are linked together through a moiety other than a phosphate moiety. Nucleotide substitutes are able to conform to a double helix type structure when interacting with the appropriate target nucleic acid. There are many varieties of these types of molecules available in the art and available herein.

[0090] It is also possible to link other types of molecules (conjugates) to nucleotides or nucleotide analogs to enhance for example, cellular uptake. Conjugates can be chemically linked to the nucleotide or nucleotide analogs. Such conjugates include but are not limited to lipid moieties such as a cholesterol moiety. (Letsinger et al., Proc. Natl. Acad. Sci. USA, 1989, 86, 6553-6556). There are many varieties of these types of molecules available in the art and available herein.

[0091] A Watson-Crick interaction is at least one interaction with the Watson-Crick face of a nucleotide, nucleotide analog, or nucleotide substitute. The Watson-Crick face of a nucleotide, nucleotide analog, or nucleotide substitute includes the C2, Nl, and C6 positions of a purine based nucleotide, nucleotide analog, or nucleotide substitute and the C2, N3, C4 positions of a pyrimidine based nucleotide, nucleotide analog, or nucleotide substitute.

[0092] A Hoogsteen interaction is the interaction that takes place on the Hoogsteen face of a nucleotide or nucleotide analog, which is exposed in the major groove of duplex DNA. The Hoogsteen face includes the N7 position and reactive groups (NH2 or O) at the C6 position of purine nucleotides.SequencesAttorney Docket No. 11820-034W01YAR01-11PRO

[0093] There are a variety of sequences related to the PC-CARs and their respective CDRL1, CDRL2, CDRL3, CDRH1, CDRH2, and CDRH3 disclosed herein (i.e., SEQ ID Nos: 1-37), all of which are encoded by nucleic acids or are nucleic acids. The sequences for the human analogs of these genes, as well as other analogs, and alleles of these genes, and splice variants and other types of variants, are available in a variety of protein and gene databases, including Genbank. Those of skill in the art understand how to resolve sequence discrepancies and differences and to adjust the compositions and methods relating to a particular sequence to other related sequences. Primers and / or probes can be designed for any given sequence given the information disclosed herein and known in the art.Functional Nucleic Acids

[0094] Functional nucleic acids are nucleic acid molecules that have a specific function, such as binding a target molecule or catalyzing a specific reaction. Functional nucleic acid molecules can be divided into the following categories, which are not meant to be limiting. For example, functional nucleic acids include antisense molecules, aptamers, ribozymes, triplex forming molecules, and external guide sequences. The functional nucleic acid molecules can act as affectors, inhibitors, modulators, and stimulators of a specific activity possessed by a target molecule, or the functional nucleic acid molecules can possess a de novo activity independent of any other molecules.

[0095] In one aspect, disclosed herein are engineered cells (for example, T cells) comprising a nucleic acid encoding a chimeric antigen receptor that binds to any of the neoantigens disclosed herein, including, but not limited to SEQ ID NO: 38 and / or SEQ ID NO: 39. In one aspect, the PC-CAR can comprise light chain CDRs (i.e., CDRL1, CDRL2, and CDRL3) as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; or SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively and / or heavy chain CDRs (i.e., CDRH1, CDRH2, and CDRH3) as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 22, respectively; SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23,Attorney Docket No. 11820-034W01YAR01-11PRO respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively. For example, the PC-CAR can comprise light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 22 as shown in, for example in SEQ ID NO: 24 (i.e., PC-CAR 10LH); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23 as shown in SEQ ID NO: 25 (i.e., PC-CAR 02_26); light chain CDRs SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 5 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23 as shown in SEQ ID NO: 26 (i.e., PC-CAR 19_9); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 27 (PC-CAR 4_8); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 28 (PC-CAR 17_3); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 29 (i.e., PC-CAR 13_9); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 30 (i.e., PC-CAR 12_3); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 31 (i.e., PC-CAR 14_1); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23 as shown in SEQ ID NO: 32 (i.e., PC-CAR 9_1); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23 as shown in SEQ ID NO: 33 (i.e., PC-CAR 10_4); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 1 1 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 34 (i.e., PC-CAR 1_5); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 35 (i.e., PC-CAR 10_2); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 36 (i.e., PC-CAR 10_3); and light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 37 (i.e., PC-CAR 6_2).

[0096] It is further understood and herein contemplated that the disclosed neoantigens can not only serve as an acitve component of a vaccine, but can be a target for a tumorAttorney Docket No. 11820-034W01YAR01-11PRO infiltrating lymphocyte (TIL), T cell receptor (TCR), antibodies, scFv, bispecific T cell engagers (BiTEs), nanobodies, diabodies, and / or chimeric antigen receptor (CAR) including, but not limited to CAR T cells, CAR natural killer (NK) cells (CAR NK cells), CAR NK T cells, CAR macrophage (CARMA), and peptide-centric CARs (PC-CARs).Antibodies

[0097] The term “antibodies” is used herein in a broad sense and includes both polyclonal and monoclonal antibodies. In addition to intact immunoglobulin molecules, also included in the term “antibodies” are fragments or polymers of those immunoglobulin molecules, and human or humanized versions of immunoglobulin molecules or fragments thereof, as long as they are chosen for their ability to bind SEQ ID NO: 38, and / or SEQ ID NO: 39. The antibodies can be tested for their desired activity using the in vitro assays described herein, or by analogous methods, after which their in vivo therapeutic and / or prophylactic activities are tested according to known clinical testing methods. There are five major classes of human immunoglobulins: IgA, IgD, IgE, IgG and IgM, and several of these may be further divided into subclasses (isotypes), e.g., IgG-1, IgG-2, IgG-3, and IgG-4; IgA-1 and IgA-2. One skilled in the art would recognize the comparable classes for mouse. The heavy chain constant domains that correspond to the different classes of immunoglobulins are called alpha, delta, epsilon, gamma, and mu, respectively.

[0098] The term “monoclonal antibody” as used herein refers to an antibody obtained from a substantially homogeneous population of antibodies, i.e., the individual antibodies within the population are identical except for possible naturally occurring mutations that may be present in a small subset of the antibody molecules. The monoclonal antibodies herein specifically include "chimeric" antibodies in which a portion of the heavy and / or light chain is identical with or homologous to corresponding sequences in antibodies derived from a particular species or belonging to a particular antibody class or subclass, while the remainder of the chain(s) is identical with or homologous to corresponding sequences in antibodies derived from another species or belonging to another antibody class or subclass, as well as fragments of such antibodies, as long as they exhibit the desired antagonistic activity.

[0099] The disclosed monoclonal antibodies can be made using any procedure which produces mono clonal antibodies. For example, disclosed monoclonal antibodies can be prepared using hybridoma methods, such as those described by Kohler and Milstein, Nature, 256:495 (1975). In a hybridoma method, a mouse or other appropriate host animal is typically immunized with an immunizing agent to elicit lymphocytes that produce or are capable ofAttorney Docket No. 11820-034W01YAR01-11PRO producing antibodies that will specifically bind to the immunizing agent. Alternatively, the lymphocytes may be immunized in vitro.

[0100] The monoclonal antibodies may also be made by recombinant DNA methods. DNA encoding the disclosed monoclonal antibodies can be readily isolated and sequenced using conventional procedures (e.g., by using oligonucleotide probes that are capable of binding specifically to genes encoding the heavy and light chains of murine antibodies). Libraries of antibodies or active antibody fragments can also be generated and screened using phage display techniques, e.g., as described in U.S. Patent No. 5,804,440 to Burton et al. and U.S. Patent No. 6,096,441 to Barbas et al.

[0101] In vitro methods are also suitable for preparing monovalent antibodies. Digestion of antibodies to produce fragments thereof, particularly, Fab fragments, can be accomplished using routine techniques known in the art. For instance, digestion can be performed using papain. Examples of papain digestion are described in WO 94 / 29348 published Dec. 22, 1994 and U.S. Pat. No. 4,342,566. Papain digestion of antibodies typically produces two identical antigen binding fragments, called Fab fragments, each with a single antigen binding site, and a residual Fc fragment. Pepsin treatment yields a fragment that has two antigen combining sites and is still capable of cross-linking antigen.

[0102] As used herein, the term “antibody or fragments thereof’ encompasses chimeric antibodies and hybrid antibodies, with dual or multiple antigen or epitope specificities, diabodies, and fragments, such as F(ab’)2, Fab’, Fab, Fv, sFv, scFv, nanobodies, and the like, including hybrid fragments. Thus, fragments of the antibodies that retain the ability to bind their specific antigens are provided. For example, fragments of antibodies which maintain SEQ ID NO: 38 and / or SEQ ID NO: 39 binding activity are included within the meaning of the term “antibody or fragment thereof.” Such antibodies and fragments can be made by techniques known in the art and can be screened for specificity and activity according to the methods set forth in the Examples and in general methods for producing antibodies and screening antibodies for specificity and activity (See Harlow and Lane. Antibodies, A Laboratory Manual. Cold Spring Harbor Publications, New York, (1988)).

[0103] Also included within the meaning of “antibody or fragments thereof” are conjugates of antibody fragments and antigen binding proteins (single chain antibodies).

[0104] The fragments, whether attached to other sequences or not, can also include insertions, deletions, substitutions, or other selected modifications of particular regions or specific amino acids residues, provided the activity of the antibody or antibody fragment is not significantly altered or impaired compared to the non-modified antibody or antibodyAttorney Docket No. 11820-034W01YAR01-11PRO fragment. These modifications can provide for some additional property, such as to remove / add amino acids capable of disulfide bonding, to increase its bio-longevity, to alter its secretory characteristics, etc. In any case, the antibody or antibody fragment must possess a bioactive property, such as specific binding to its cognate antigen. Functional or active regions of the antibody or antibody fragment may be identified by mutagenesis of a specific region of the protein, followed by expression and testing of the expressed polypeptide. Such methods are readily apparent to a skilled practitioner in the art and can include site-specific mutagenesis of the nucleic acid encoding the antibody or antibody fragment. (Zoller, M.J. Curr. Opin. Biotechnol. 3:348-354, 1992).

[0105] As used herein, the term “antibody” or “antibodies” can also refer to a human antibody and / or a humanized antibody. Many non-human antibodies (e.g., those derived from mice, rats, or rabbits) are naturally antigenic in humans, and thus can give rise to undesirable immune responses when administered to humans. Therefore, the use of human or humanized antibodies in the methods serves to lessen the chance that an antibody administered to a human will evoke an undesirable immune response.Human antibodies

[0106] The disclosed human antibodies can be prepared using any technique. The disclosed human antibodies can also be obtained from transgenic animals. For example, transgenic, mutant mice that are capable of producing a full repertoire of human antibodies, in response to immunization, have been described (see, e.g., Jakobovits et al., Proc. Natl. Acad. Sci. USA, 90:2551-255 (1993); Jakobovits et al., Nature, 362:255-258 (1993);Bruggermann et al., Year in Immunol., 7:33 (1993)). Specifically, the homozygous deletion of the antibody heavy chain joining region (J(77)) gene in these chimeric and germ-line mutant mice results in complete inhibition of endogenous antibody production, and the successful transfer of the human germ-line antibody gene array into such germ-line mutant mice results in the production of human antibodies upon antigen challenge. Antibodies having the desired activity are selected using Env-CD4-co-receptor complexes as described herein.Humanized antibodies

[0107] Antibody humanization techniques generally involve the use of recombinant DNA technology to manipulate the DNA sequence encoding one or more polypeptide chains of an antibody molecule. Accordingly, a humanized form of a non-human antibody (or a fragment thereof) is a chimeric antibody or antibody chain (or a fragment thereof, such as an sFv, Fv, Fab, Fab’, F(ab’)2, or other antigen-binding portion of an antibody) which contains a portionAttorney Docket No. 11820-034W01YAR01-11PRO of an antigen binding site from a non-human (donor) antibody integrated into the framework of a human (recipient) antibody.

[0108] To generate a humanized antibody, residues from one or more complementarity determining regions (CDRs) of a recipient (human) antibody molecule are replaced by residues from one or more CDRs of a donor (non-human) antibody molecule that is known to have desired antigen binding characteristics (e.g., a certain level of specificity and affinity for the target antigen). In some instances, Fv framework (FR) residues of the human antibody are replaced by corresponding non-human residues. Humanized antibodies may also contain residues which are found neither in the recipient antibody nor in the imported CDR or framework sequences. Generally, a humanized antibody has one or more amino acid residues introduced into it from a source which is non-human. In practice, humanized antibodies are typically human antibodies in which some CDR residues and possibly some FR residues are substituted by residues from analogous sites in rodent antibodies. Humanized antibodies generally contain at least a portion of an antibody constant region (Fc), typically that of a human antibody (Jones et al., Nature, 321:522-525 (1986), Reichmann et al., Nature, 332:323-327 (1988), and Presta, Curr. Opin. Struct. Biol., 2:593-596 (1992)).

[0109] Methods for humanizing non-human antibodies are well known in the art. For example, humanized antibodies can be generated according to the methods of Winter and co-workers (Jones et al., Nature, 321:522-525 (1986), Riechmann et al., Nature, 332:323-327 (1988), Verhoeyen et al., Science, 239: 1534-1536 (1988)), by substituting rodent CDRs or CDR sequences for the corresponding sequences of a human antibody. Methods that can be used to produce humanized antibodies are also described in U.S. Patent No. 4,816,567 (Cabilly et al.), U.S. Patent No. 5,565,332 (Hoogenboom et al.), U.S. Patent No. 5,721,367 (Kay et al.), U.S. Patent No. 5,837,243 (Deo et al.), U.S. Patent No. 5, 939,598 (Kucherlapati et al.), U.S. Patent No. 6,130,364 (Jakobovits et al.), and U.S. Patent No. 6,180,377 (Morgan et al.).Chimeric antigen receptors

[0001] In one aspect, disclosed herein is chimeric antigen receptor (CAR) that binds to one or more peptides (i.e., a peptide centric (PC) CAR (PC-CAR)) (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)) selected from the group consisting of SEQ ID NO: 38 and / or SEQ ID NO: 39. In one aspect, the PC-CAR can comprise light chain CDRs (i.e., CDRL1, CDRL2, and CDRL3) as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively;Attorney Docket No. 11820-034W01YAR01-11PROSEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2,SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; or SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 15, respectively and / or heavy chain CDRs (i.e., CDRH1 , CDRH2, and CDRH3) as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 22, respectively; SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively. For example, the PC- CAR can comprise light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 22 as shown in, for example in SEQ ID NO: 24 (i.e., PC-CAR 10LH); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23 as shown in SEQ ID NO: 25 (i.e., PC-CAR 02_26); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23 as shown in SEQ ID NO: 26 (i.e., PC-CAR 19_9); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO:19, SEQ ID NO: 23 as shown in SEQ ID NO: 27 (PC-CAR 4_8); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO:20, SEQ ID NO: 23 as shown in SEQ ID NO: 28 (PC-CAR 17_3); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 29 (i.e., PC-CAR 13_9); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 30 (i.e., PC-CAR 12_3); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 31 (i.e., PC-CAR 14_1); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23 as shown in SEQ ID NO: 32 (i.e., PC-CAR 9_1); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23 as shown in SEQ ID NO: 33 (i.e., PC-Attorney Docket No. 11820-034W01YAR01-11PROCAR 10_4); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 34 (i.e., PC-CAR 1_5); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 35 (i.e., PC-CAR 10_2); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 36 (i.e., PC-CAR 10_3); and light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 37 (i.e., PC-CAR 6_2).

[0110] It is understood and herein contemplated that disclosed CAR can be expressed on any cell capable of expressing said CAR including, but not limited to CAR T cells, CAR natural killer (NK) cells (CAR NK cells), CAR NK T cells, CAR macrophage (CARMA). In some aspects the CAR is a peptide-centric CAR (PC-CAR).

[0111] The antigen recognition domain of the disclosed CAR is usually an scFv. There are however many alternatives. An antigen recognition domain from native T-cell receptor (TCR) alpha and beta single chains have been described, as have simple ectodomains (e.g. CD4 ectodomain to recognize HIV infected cells) and more exotic recognition components such as a linked cytokine (which leads to recognition of cells bearing the cytokine receptor). In fact almost anything that binds a given target with high affinity can be used as an antigen recognition region.

[0112] The endodomain is the business end of the CAR that after antigen recognition transmits a signal to the immune effector cell, activating at least one of the normal effector functions of the immune effector cell. Effector function of a T cell, for example, may be cytolytic activity or helper activity including the secretion of cytokines. Therefore, the endodomain may comprise the “intracellular signaling domain” of a T cell receptor (TCR) and optional co-receptors. While usually the entire intracellular signaling domain can be employed, in many cases it is not necessary to use the entire chain. To the extent that a truncated portion of the intracellular signaling domain is used, such truncated portion may be used in place of the intact chain as long as it transduces the effector function signal.

[0113] Cytoplasmic signaling sequences that regulate primary activation of the TCR complex that act in a stimulatory manner may contain signaling motifs which are known as immunoreceptor tyrosine -based activation motifs (IT AMs). Examples of IT AM containing cytoplasmic signaling sequences include those derived from CD8, CD3^, CD35, CD3y,Attorney Docket No. 11820-034W01YAR01-11PROCD3e, CD32 (Fc gamma Rlla), DAP10, DAP12, CD79a, CD79b, FcyRIy, FcyRIIIy, FcsRi(FCERIB), and FcsRIy (FCERIG).

[0114] In particular embodiments, the intracellular signaling domain is derived from CD3 zeta (CD3Q (TCR zeta, GenBank aceno. BAG36664.1). T-cell surface glycoprotein CD3 zeta (CD3Q chain, also known as T-cell receptor T3 zeta chain or CD247 (Cluster of Differentiation 247), is a protein that in humans is encoded by the CD247 gene.

[0115] First- generation CARs typically had the intracellular domain from the CD3 chain, which is the primary transmitter of signals from endogenous TCRs. Second-generation CARs add intracellular signaling domains from various costimulatory protein receptors (e.g., CD28, 41BB, ICOS) to the endodomain of the CAR to provide additional signals to the T cell. Preclinical studies have indicated that the second generation of CAR designs improves the antitumor activity of T cells. More recent, third-generation CARs combine multiple signaling domains to further augment potency. T cells grafted with these CARs have demonstrated improved expansion, activation, persistence, and tumor-eradicating efficiency independent of costimulatory receptor / ligand interaction (Imai C, et al. Leukemia 2004 18:676-84; Maher J, et al. Nat Biotechnol 2002 20:70-5).

[0116] For example, the endodomain of the CAR can be designed to comprise the CD3^ signaling domain by itself or combined with any other desired cytoplasmic domain(s) useful in the context of the CAR of the invention. For example, the cytoplasmic domain of the CAR can comprise a CD3^ chain portion and a costimulatory signaling region. The costimulatory signaling region refers to a portion of the CAR comprising the intracellular domain of a costimulatory molecule. A costimulatory molecule is a cell surface molecule other than an antigen receptor or their ligands that is required for an efficient response of lymphocytes to an antigen. Examples of such molecules include CD27, CD28, 4- IBB (CD 137), 0X40, CD30, CD40, ICOS, lymphocyte function-associated antigen-1 (LFA-1), CD2, CD7, LIGHT, NKG2C, B7-H3, and a ligand that specifically binds with CD83, CD8, CD4, b2c, CD80, CD86, DAP10, DAP12, MyD88, BTNL3, and NKG2D. Thus, while the CAR is exemplified primarily with CD28 as the co-stimulatory signaling element, other costimulatory elements can be used alone or in combination with other co-stimulatory signaling elements. Thus, specifically contemplated herein are CARs comprising any one or combination of two more co-stimulatory signaling elements for the group consisting of CD27, CD28, 4-1BB (CD137), 0X40, CD30, CD40, ICOS, LFA-1, CD2, CD7, LIGHT, NKG2C, B7-H3, and a ligand that specifically binds with CD83, CD8, CD4, b2c, CD80, CD86, DAP10, DAP12, MyD88, BTNL3, and NKG2DCD28 and 4-1BB, CD28 and 0X40, CD28 and LFA-1, CD28 andAttorney Docket No. 11820-034W01YAR01-11PROCD40. Thus, for example, specifically contemplated herein are CARs comprising costimulatory signaling elements for CD28 and CD40, CD28 and 4- IBB, CD28 and 0X40, and CD28 and LFA-1.

[0117] In some embodiments, the CAR comprises a hinge sequence. A hinge sequence is a short sequence of amino acids that facilitates antibody flexibility (see, e.g., Woof et al., Nat. Rev. Immunol., 4(2): 89-99 (2004)). The hinge sequence may be positioned between the antigen recognition moiety (e.g., anti-IL13Ra2 scFv) and the transmembrane domain. The hinge sequence can be any suitable sequence derived or obtained from any suitable molecule. In some embodiments, for example, the hinge sequence is derived from a CD8 alpha molecule or a CD28 molecule.

[0118] The transmembrane domain may be derived either from a natural or from a synthetic source. Where the source is natural, the domain may be derived from any membrane-bound or transmembrane protein. For example, the transmembrane region may be derived from (i.e. comprise at least the transmembrane region(s) of) the alpha, beta or zeta chain of the T-cell receptor, CD28, CD3 epsilon, CD45, CD4, CD5, CD8 (e.g., CD8 alpha, CD8 beta), CD9, CD16, CD22, CD33, CD37, CD64, CD80, CD86, CD134, CD137, or CD154, KIRDS2, 0X40, CD2, CD27, LFA-1 (CDl la, CD18) , ICOS (CD278) , 4-1BB (CD137) , GITR, CD40, BAFFR, HVEM (LIGHTR) , SLAMF7, NKp80 (KLRF1) , CD160, CD19, IL2R beta, IL2R gamma, IL7R a, TTGA1, VLA1, CD49a, ITGA4, IA4, CD49D, ITGA6, VLA-6, CD49f, ITGAD, CD1 Id, ITGAE, CD 103, ITGAL, CDl la, LFA-1, ITGAM, CDl lb, ITGAX, CDl lc, ITGB1, CD29, ITGB2, CD18, LFA-1, ITGB7, TNFR2, DNAM1 (CD226) , SLAMF4 (CD244, 2B4) , CD84, CD96 (Tactile) , CEACAM1, CRT AM, Ly9 (CD229) , CD160 (BY55) , PSGL1, CD100 (SEMA4D) , SLAMF6 (NTB-A, Lyl08) , SLAM (SLAMF1, CD 150, IPO-3) , BLAME (SLAMF8) , SELPLG (CD 162) , LTBR, and PAG / Cbp. Alternatively the transmembrane domain may be synthetic, in which case it will comprise predominantly hydrophobic residues such as leucine and valine. In some cases, a triplet of phenylalanine, tryptophan and valine will be found at each end of a synthetic transmembrane domain. A short oligo- or polypeptide linker, such as between 2 and 10 amino acids in length, may form the linkage between the transmembrane domain and the endoplasmic domain of the CAR. In some embodiments, the linker can be a spacer derived from the same source as the transmembrane domain. For example in some instances, the spacer can and the transmembrane domain are both derived from the CD28 or CD8 alpha, or from any other source for the transmembrane domain listed above including, but not limited to, the alpha, beta or zeta chain of the T-cell receptor, CD3 epsilon, CD45, CD4, CD5, CD8Attorney Docket No. 11820-034W01YAR01-11PRO beta, CD9, CD16, CD22, CD33, CD37, CD64, CD80, CD86, CD134, CD137, or CD154, KIRDS2, 0X40, CD2, CD27, LFA-1 (CDl la, CD18) , ICOS (CD278) , 4-1BB (CD137) , GITR, CD40, BAFFR, HVEM (LIGHTR) , SLAMF7, NKp80 (KLRF1) , CD160, CD19, IL2R beta, IL2R gamma, IL7R a, ITGA1, VLA1, CD49a, ITGA4, IA4, CD49D, ITGA6, VLA-6, CD49f, ITGAD, CDl ld, ITGAE, CD103, ITGAL, CDl la, LFA-1, ITGAM, CDl lb, ITGAX, CDl lc, ITGB1, CD29, ITGB2, CD18, LFA-1, ITGB7, TNFR2, DNAM1 (CD226) , SLAMF4 (CD244, 2B4) , CD84, CD96 (Tactile) , CEACAM 1, CRT AM, Ly9 (CD229) , CD 160 (BY55) , PSGL1 , CD100 (SEMA4D) , SLAMF6 (NTB-A, LylO8) , SLAM (SLAMF1, CD150, IPO-3) , BLAME (SLAMF8) , SELPLG (CD162) , LTBR, and PAG / Cbp. In other embodiments, the transmembrane domain and the liner (such as a spacer) can be derived from different sources, for example, a CD28 transmembrane domain and a CD8 alpha spacer or a CD8 alpha transmembrane domain and a CD28 spacer.

[0119] In some embodiments, the CAR has more than one transmembrane domain, which can be a repeat of the same transmembrane domain, or can be different transmembrane domains.

[0120] In some embodiments, the CAR is a multi-chain CAR, as described in WO2015 / 039523, which is incorporated by reference for this teaching. A multi-chain CAR can comprise separate extracellular ligand binding and signaling domains in different transmembrane polypeptides. The signaling domains can be designed to assemble in juxtamembrane position, which forms flexible architecture closer to natural receptors, that confers optimal signal transduction. For example, the multi-chain CAR can comprise a part of an FCERI alpha chain and a part of an FCERI beta chain such that the FCERI chains spontaneously dimerize together to form a CAR.Pharmaceutical carriers / Delivery of pharmaceutical products

[0121] As described above, the compositions can also be administered in vivo in a pharmaceutically acceptable carrier. By "pharmaceutically acceptable" is meant a material that is not biologically or otherwise undesirable, i.e., the material may be administered to a subject, along with the nucleic acid or vector, without causing any undesirable biological effects or interacting in a deleterious manner with any of the other components of the pharmaceutical composition in which it is contained. The carrier would naturally be selected to minimize any degradation of the active ingredient and to minimize any adverse side effects in the subject, as would be well known to one of skill in the art.

[0122] The compositions may be administered orally, parenterally (e.g., intravenously), by intramuscular injection, by intraperitoneal injection, transdermally, extracorporeally,Attorney Docket No. 11820-034W01YAR01-11PRO topically or the like, including topical intranasal administration or administration by inhalant.As used herein, "topical intranasal administration" means delivery of the compositions into the nose and nasal passages through one or both of the nares and can comprise delivery by a spraying mechanism or droplet mechanism, or through aerosolization of the nucleic acid or vector. Administration of the compositions by inhalant can be through the nose or mouth via delivery by a spraying or droplet mechanism. Delivery can also be directly to any area of the respiratory system (e.g., lungs) via intubation. The exact amount of the compositions required will vary from subject to subject, depending on the species, age, weight and general condition of the subject, the severity of the allergic disorder being treated, the particular nucleic acid or vector used, its mode of administration and the like. Thus, it is not possible to specify an exact amount for every composition. However, an appropriate amount can be determined by one of ordinary skill in the art using only routine experimentation given the teachings herein.

[0123] Parenteral administration of the composition, if used, is generally characterized by injection. Injectables can be prepared in conventional forms, either as liquid solutions or suspensions, solid forms suitable for solution of suspension in liquid prior to injection, or as emulsions. A more recently revised approach for parenteral administration involves use of a slow release or sustained release system such that a constant dosage is maintained. See, e.g., U.S. Patent No. 3,610,795, which is incorporated by reference herein.

[0124] The materials may be in solution, suspension (for example, incorporated into microparticles, liposomes, or cells). These may be targeted to a particular cell type via antibodies, receptors, or receptor ligands. The following references are examples of the use of this technology to target specific proteins to tumor tissue (Senter, et al., Bioconjugate Chem., 2:447-451, (1991); Bagshawe, K.D., Br. J. Cancer, 60:275-281, (1989); Bagshawe, et al., Br. J. Cancer, 58:700-703, (1988); Senter, et al., Bioconjugate Chem., 4:3-9, (1993); Battelli, et al., Cancer Immunol. Immunother., 35:421-425, (1992); Pietersz and McKenzie, Immunolog. Reviews, 129:57-80, (1992); and Roffler, et al., Biochem. Pharmacol, 42:2062-2065, (1991)). Vehicles such as "stealth" and other antibody conjugated liposomes (including lipid mediated drug targeting to colonic carcinoma), receptor mediated targeting of DNA through cell specific ligands, lymphocyte directed tumor targeting, and highly specific therapeutic retroviral targeting of murine glioma cells in vivo. The following references are examples of the use of this technology to target specific proteins to tumor tissue (Hughes et al., Cancer Research, 49:6214-6220, (1989); and Litzinger and Huang, Biochimica et Biophysica Acta, 1104: 179-187, (1992)). In general, receptors are involved in pathways of endocytosis, either constitutive or ligand induced. These receptors cluster in clathrin-coated pits, enter the cellAttorney Docket No. 11820-034W01YAR01-11PRO via clathrin-coated vesicles, pass through an acidified endosome in which the receptors are sorted, and then either recycle to the cell surface, become stored intracellularly, or are degraded in lysosomes. The internalization pathways serve a variety of functions, such as nutrient uptake, removal of activated proteins, clearance of macromolecules, opportunistic entry of viruses and toxins, dissociation and degradation of ligand, and receptor-level regulation. Many receptors follow more than one intracellular pathway, depending on the cell type, receptor concentration, type of ligand, ligand valency, and ligand concentration. Molecular and cellular mechanisms of receptor-mediated endocytosis has been reviewed (Brown and Greene, DNA and Cell Biology 10:6, 399-409 (1991)).Pharmaceutically Acceptable Carriers

[0125] The compositions, including antibodies, can be used therapeutically in combination with a pharmaceutically acceptable carrier.

[0126] Suitable carriers and their formulations are described in Remington: The Science and Practice of Pharmacy (19th ed.) ed. A.R. Gennaro, Mack Publishing Company, Easton, PA 1995. Typically, an appropriate amount of a pharmaceutically-acceptable salt is used in the formulation to render the formulation isotonic. Examples of the pharmaceutically- acceptable carrier include, but are not limited to, saline, Ringer's solution and dextrose solution. The pH of the solution is preferably from about 5 to about 8, and more preferably from about 7 to about 7.5. Further carriers include sustained release preparations such as semipermeable matrices of solid hydrophobic polymers containing the antibody, which matrices are in the form of shaped articles, e.g., films, liposomes or microparticles. It will be apparent to those persons skilled in the art that certain carriers may be more preferable depending upon, for instance, the route of administration and concentration of composition being administered.

[0127] Pharmaceutical carriers are known to those skilled in the art. These most typically would be standard carriers for administration of drugs to humans, including solutions such as sterile water, saline, and buffered solutions at physiological pH. The compositions can be administered intramuscularly or subcutaneously. Other compounds will be administered according to standard procedures used by those skilled in the art.

[0128] Pharmaceutical compositions may include carriers, thickeners, diluents, buffers, preservatives, surface active agents and the like in addition to the molecule of choice. Pharmaceutical compositions may also include one or more active ingredients such as antimicrobial agents, anti-inflammatory agents, anesthetics, and the like.Attorney Docket No. 11820-034W01YAR01-11PRO

[0129] The pharmaceutical composition may be administered in a number of ways depending on whether local or systemic treatment is desired, and on the area to be treated. Administration may be topically (including ophthalmically, vaginally, rectally, intranasally), orally, by inhalation, or parenterally, for example by intravenous drip, subcutaneous, intraperitoneal or intramuscular injection. The disclosed antibodies can be administered intravenously, intraperitoneally, intramuscularly, subcutaneously, intracavity, or transdermally.

[0130] Preparations for parenteral administration include sterile aqueous or non-aqueous solutions, suspensions, and emulsions. Examples of non-aqueous solvents are propylene glycol, polyethylene glycol, vegetable oils such as olive oil, and injectable organic esters such as ethyl oleate. Aqueous carriers include water, alcoholic / aqueous solutions, emulsions or suspensions, including saline and buffered media. Parenteral vehicles include sodium chloride solution, Ringer's dextrose, dextrose and sodium chloride, lactated Ringer's, or fixed oils. Intravenous vehicles include fluid and nutrient replenishers, electrolyte replenishers (such as those based on Ringer's dextrose), and the like. Preservatives and other additives may also be present such as, for example, antimicrobials, anti-oxidants, chelating agents, and inert gases and the like.

[0131] Formulations for topical administration may include ointments, lotions, creams, gels, drops, suppositories, sprays, liquids and powders. Conventional pharmaceutical carriers, aqueous, powder or oily bases, thickeners and the like may be necessary or desirable.

[0132] Compositions for oral administration include powders or granules, suspensions or solutions in water or non-aqueous media, capsules, sachets, or tablets. Thickeners, flavorings, diluents, emulsifiers, dispersing aids or binders may be desirable.

[0133] Some of the compositions may potentially be administered as a pharmaceutically acceptable acid- or base- addition salt, formed by reaction with inorganic acids such as hydrochloric acid, hydrobromic acid, perchloric acid, nitric acid, thiocyanic acid, sulfuric acid, and phosphoric acid, and organic acids such as formic acid, acetic acid, propionic acid, glycolic acid, lactic acid, pyruvic acid, oxalic acid, malonic acid, succinic acid, maleic acid, and fumaric acid, or by reaction with an inorganic base such as sodium hydroxide, ammonium hydroxide, potassium hydroxide, and organic bases such as mono-, di-, trialkyl and aryl amines and substituted ethanolamines.Therapeutic Uses

[0134] Effective dosages and schedules for administering the compositions may be determined empirically, and making such determinations is within the skill in the art. TheAttorney Docket No. 11820-034W01YAR01-11PRO dosage ranges for the administration of the compositions are those large enough to produce the desired effect in which the symptoms of the disorder are effected. The dosage should not be so large as to cause adverse side effects, such as unwanted cross-reactions, anaphylactic reactions, and the like. Generally, the dosage will vary with the age, condition, sex and extent of the disease in the patient, route of administration, or whether other drugs are included in the regimen, and can be determined by one of skill in the art. The dosage can be adjusted by the individual physician in the event of any counterindications. Dosage can vary, and can be administered in one or more dose administrations daily, for one or several days. Guidance can be found in the literature for appropriate dosages for given classes of pharmaceutical products. For example, guidance in selecting appropriate doses for antibodies can be found in the literature on therapeutic uses of antibodies, e.g., Handbook of Monoclonal Antibodies, Ferrone et al., eds., Noges Publications, Park Ridge, N.J., (1985) ch. 22 and pp. 303-357; Smith et al., Antibodies in Human Diagnosis and Therapy, Haber et al., eds., Raven Press, New York (1977) pp. 365-389. A typical daily dosage of the antibody used alone might range from about 1 pg / kg to up to 100 mg / kg of body weight or more per day, depending on the factors mentioned above.Method of treating cancer

[0135] The disclosed compositions can be used to treat any disease where uncontrolled cellular proliferation occurs such as cancers. A representative but non-limiting list of cancers that the disclosed compositions can be used to treat is the following: lymphomas such as B cell lymphoma and T cell lymphoma; mycosis fungoides; Hodgkin’s Disease; myeloid leukemia (including, but not limited to acute myeloid leukemia (AML) and / or chronic myeloid leukemia (CML)); bladder cancer; brain cancer; nervous system cancer; head and neck cancer; squamous cell carcinoma of head and neck; renal cancer; lung cancers such as small cell lung cancer, non-small cell lung carcinoma (NSCLC), lung squamous cell carcinoma (LUSC), and Lung Adenocarcinomas (LU AD); neuroblastoma / glioblastoma; ovarian cancer; pancreatic cancer; prostate cancer; skin cancer; hepatic cancer; melanoma; squamous cell carcinomas of the mouth, throat, larynx, and lung; cervical cancer; cervical carcinoma; breast cancer including, but not limited to triple negative breast cancer; genitourinary cancer; pulmonary cancer; esophageal carcinoma; head and neck carcinoma; large bowel cancer; hematopoietic cancers; testicular cancer; and colon and rectal cancers.

[0136] In one aspect, also disclosed herein are methods of treating, decreasing, reducing, inhibiting, ameliorating, and / or preventing a cancer (such as, for example neuroblastoma / glioblastoma), cancer recurrence, and / or metastasis in a subject comprisingAttorney Docket No. 11820-034W01YAR01-11PRO administering to the subject a cell therapy comprising a chimeric antigen receptor (CAR)(including, but not limited to administration of CAR expressing T cells (CAR T cells), natural killer (NK) cells (CAR NK cells), CAR NK T cells, CAR macrophage (CARMA), and / or peptide-centric CAR) that binds to one or more antigens selected from the group consisting of SEQ ID NO: 38, and / or SEQ ID NO: 39. In one aspect, the PC-CAR (including, but not limited to a CAR that recognizes the same peptide across two or more HSL alleles or a single peptide in the context of a single HLA (i.e., TCR mimics)) can comprise light chain CDRs (i.e., CDRL1, CDRL2, and CDRL3) as set forth in SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 3, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; or SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively and / or heavy chain CDRs (i.e., CDRH1, CDRH2, and CDRH3) as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 22, respectively; SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively. For example, the PC- CAR can comprise light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 3 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 22 as shown in, for example in SEQ ID NO: 24 (i.e., PC-CAR 10LH); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23 as shown in SEQ ID NO: 25 (i.e., PC-CAR 02_26); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23 as shown in SEQ ID NO: 26 (i.e., PC-CAR 19_9); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO:19, SEQ ID NO: 23 as shown in SEQ ID NO: 27 (PC-CAR 4_8); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO:20, SEQ ID NO: 23 as shown in SEQ ID NO: 28 (PC-CAR 17_3); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO:Attorney Docket No. 11820-034W01YAR01-11PRO19, SEQ ID NO: 23 as shown in SEQ ID NO: 29 (i.e., PC-CAR 13_9); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 30 (i.e., PC-CAR 12_3 ); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 31 (i.e., PC-CAR 14_1); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23 as shown in SEQ ID NO: 32 (i.e., PC-CAR 9_1); light chain CDRs SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 12 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23 as shown in SEQ ID NO: 33 (i.e., PC- CAR 10_4); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 34 (i.e., PC-CAR 1_5); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 35 (i.e., PC-CAR 10_2); light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23 as shown in SEQ ID NO: 36 (i.e., PC-CAR 10_3); and light chain CDRs SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15 and heavy chain CDRs SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23 as shown in SEQ ID NO: 37 (i.e., PC-CAR 6_2).

[0137] It is understood and herein contemplated that the disclosed treatment regimens can used alone or in combination with any anti-cancer therapy known in the art including, but not limited to Abemaciclib, Abiraterone Acetate, ABITREXATE® (Methotrexate), ABRAXANE® (Paclitaxel Albumin-stabilized Nanoparticle Formulation), ABVD, ABVE, ABVE-PC, AC, AC-T, ADCETRIS® (Brentuximab Vedotin), ADE, Ado-Trastuzumab Emtansine, ADRIAMYCIN® (Doxorubicin Hydrochloride), Afatinib Dimaleate, AFINITOR® (Everolimus), AKYNZEO® (Netupitant and Palonosetron Hydrochloride), ALDARA® (Imiquimod), Aldesleukin, ALECENSA® (Alectinib), Alectinib, Alemtuzumab, ALIMTA® (Pemetrexed Disodium), ALIQOPA® (Copanlisib Hydrochloride), ALKERAN™ for Injection (Melphalan Hydrochloride), ALKERAN™ Tablets (Melphalan), ALOXI® (Palonosetron Hydrochloride), ALUNBRIG® (Brigatinib), AMBOCHLORIN® (Chlorambucil), AMBOCLORIN® (Chlorambucil), Amifostine, Aminolevulinic Acid, Anastrozole, Aprepitant, AREDIA® (Pamidronate Disodium), ARIMIDEX® (Anastrozole), AROMASIN® (Exemestane),ARRANON® (Nelarabine), Arsenic Trioxide, ARZERRA® (Ofatumumab), Asparaginase Erwinia chrysanthemi, Atezolizumab, AVASTIN® (Bevacizumab), Avelumab, Axitinib, Azacitidine, BAVENCIO® (Avelumab), BEACOPP,Attorney Docket No. 11820-034W01YAR01-11PROBECENUM® (Carmustine), BELEODAQ® (Belinostat), Belinostat, Bendamustine Hydrochloride, BEP, BESPONSA® (Inotuzumab Ozogamicin) , Bevacizumab, Bexarotene, BEXXAR® (Tositumomab and Iodine 1 131 Tositumomab), Bicalutamide, BICNU® (Carmustine), Bleomycin, Blinatumomab, BLINCYTO® (Blinatumomab), Bortezomib, BOSULIF® (Bosutinib), Bosutinib, Brentuximab Vedotin, Brigatinib, BuMel, Busulfan, BUSULFEX® (Busulfan), Cabazitaxel, CABOMETYX® (Cabozantinib-S-Malate), Cabozantinib-S-Malate, CAF, CAMPATH® (Alemtuzumab), CAMPTOSAR® (Irinotecan Hydrochloride), Capecitabine, CAPOX, CARAC® (Fluorouracil-Topical), Carboplatin, CARBOPLATIN-TAXOL, Carfilzomib, CARMUBRIS® (Carmustine), Carmustine, Carmustine Implant, CASODEX® (Bicalutamide), CEM, Ceritinib, CERUBIDINE® (Daunorubicin Hydrochloride), CERVARIX® (Recombinant HPV Bivalent Vaccine), Cetuximab, CEV, Chlorambucil, CHLORAMBUCIL-PREDNISONE, CHOP, Cisplatin, Cladribine, CLAFEN® (Cyclophosphamide), Clofarabine, CLOFAREX® (Clofarabine), CLOLAR® (Clofarabine), CMF, Cobimetinib, COMETRIQ® (Cabozantinib-S-Malate), Copanlisib Hydrochloride, COPDAC, COPP, COPP-AB V, COSMEGEN® (Dactinomycin), COTELLIC® (Cobimetinib), Crizotinib, CVP, Cyclophosphamide, CYFOS® (Ifosfamide), CYRAMZA® (Ramucirumab), Cytarabine, Cytarabine Liposome, CYTOSAR-U® (Cytarabine), CYTOXAN® (Cyclophosphamide), Dabrafenib, Dacarbazine, DACOGEN® (Decitabine), Dactinomycin, Daratumumab, DARZALEX® (Daratumumab), Dasatinib, Daunorubicin Hydrochloride, Daunorubicin Hydrochloride and Cytarabine Liposome, Decitabine, Defibrotide Sodium, DEFITELIO® (Defibrotide Sodium), Degarelix, Denileukin Diftitox, Denosumab, DEPOCYT® (Cytarabine Liposome), Dexamethasone, Dexrazoxane Hydrochloride, Dinutuximab, Docetaxel, DOXIL® (Doxorubicin Hydrochloride Liposome), Doxorubicin Hydrochloride, Doxorubicin Hydrochloride Liposome, DOX-SL® (Doxorubicin Hydrochloride Liposome), DTIC-DOME® (Dacarbazine), Durvalumab, EFUDEX® (Fluorouracil— Topical), ELITEK® (Rasburicase), ELLENCE® (Epirubicin Hydrochloride), Elotuzumab, ELOXATIN® (Oxaliplatin), Eltrombopag Olamine, EMEND® (Aprepitant), EMPLICITI® (Elotuzumab), Enasidenib Mesylate, Enzalutamide, Epirubicin Hydrochloride , EPOCH, ERBITUX® (Cetuximab), Eribulin Mesylate, ERIVEDGE® (Vismodegib), Erlotinib Hydrochloride, ERWINAZE® (Asparaginase Erwinia chrysanthemi), ETHYOL® (Amifostine), Etopophos ETOPOPHOS® (Etoposide Phosphate), Etoposide, Etoposide Phosphate, EV ACET® (Doxorubicin Hydrochloride Liposome), Everolimus, EVISTA® (Raloxifene Hydrochloride), EVOMELA® (Melphalan Hydrochloride), Exemestane, 5-FU® (Fluorouracil Injection), 5-FU® (Fluorouracil-Topical), FARESTON® (Toremifene),Attorney Docket No. 11820-034W01YAR01-11PROFARYDAK® (Panobinostat), FASLODEX® (Fulvestrant), FEC, FEMARA® (Letrozole), Filgrastim, FLUDARA® (Fludarabine Phosphate), Fludarabine Phosphate, FLUOROPLEX® (Fluorouracil— Topical), Fluorouracil Injection, Fluorouracil— Topical, Flutamide, FOLEX® (Methotrexate), FOLEX PFS® (Methotrexate), FOLFIRI, FOLFIRI-BEVACIZUMAB, FOLFIRLCETUXIMAB, FOLFIRINOX, FOLFOX, FOLOTYN® (Pralatrexate), FU-LV, Fulvestrant, GARDASIL® (Recombinant HPV Quadrivalent Vaccine), GARDASIL 9® (Recombinant HPV Nonavalent Vaccine), GAZYVA® (Obinutuzumab), Gefitinib, Gemcitabine Hydrochloride, GEMCITABINE-CISPLATIN, GEMCITABINEOXALIPLATIN, Gemtuzumab Ozogamicin, GEMZAR® (Gemcitabine Hydrochloride), GILOTRIF® (Afatinib Dimaleate), GLEEVEC® (Imatinib Mesylate), GLIADEL® (Carmustine Implant), GLIADEL WAFER® (Carmustine Implant), Glucarpidase, Goserelin Acetate, HALAVEN® (Eribulin Mesylate), HEMANGEOL® (Propranolol Hydrochloride), HERCEPTIN® (Trastuzumab), HPV Bivalent Vaccine, Recombinant, HPV Nonavalent Vaccine, Recombinant, HPV Quadrivalent Vaccine, Recombinant, HYCAMTIN® (Topotecan Hydrochloride), HYDREA® (Hydroxyurea), Hydroxyurea, Hyper-CVAD, IB RANCE® (Palbociclib), Ibritumomab Tiuxetan, Ibrutinib, ICE, 1CLUS1G® (Ponatinib Hydrochloride), IDAMYCIN® (Idarubicin Hydrochloride), Idarubicin Hydrochloride, Idelalisib, IDHIFA® (Enasidenib Mesylate), IFEX® (Ifosfamide), Ifosfamide, IFOSFAMIDUM® (Ifosfamide), IL-2 (Aldesleukin), Imatinib Mesylate, IMBRUVICA® (Ibrutinib), IMFINZI® (Durvalumab), Imiquimod, IMLYGIC® (Talimogene Laherparepvec), INLYTA® (Axitinib), Inotuzumab Ozogamicin, Interferon Alfa-2b, Recombinant, Interleukin-2 (Aldesleukin), INTRON A® (Recombinant Interferon Alfa-2b), Iodine I 131 Tositumomab and Tositumomab, Ipilimumab, IRESSA® (Gefitinib), Irinotecan Hydrochloride, Irinotecan Hydrochloride Liposome, ISTODAX® (Romidepsin), Ixabepilone, Ixazomib Citrate, IXEMPRA® (Ixabepilone), JAKAFI® (Ruxolitinib Phosphate), JEB, JEVTANA® (Cabazitaxel), KADCYLA® (Ado-Trastuzumab Emtansine), KEOXIFENE® (Raloxifene Hydrochloride), KEPIVANCE® (Palifermin), KEYTRUDA® (Pembrolizumab), KISQALI® (Ribociclib), KYMRIAH® (Tisagenlecleucel), KYPROLIS® (Carfilzomib), Lanreotide Acetate, Lapatinib Ditosylate, LARTRUVO® (Olaratumab), Lenalidomide, Lenvatinib Mesylate, LENVIMA® (Lenvatinib Mesylate), Letrozole, Leucovorin Calcium, LEUKERAN® (Chlorambucil), Leuprolide Acetate, LEUSTATIN® (Cladribine), LEVULAN® (Aminolevulinic Acid), LINFOLIZIN® (Chlorambucil), LIPODOX® (Doxorubicin Hydrochloride Liposome), Lomustine, LONSURF® (Trifluridine and Tipiracil Hydrochloride), LUPRON® (Leuprolide Acetate), LUPRON DEPOT® (LeuprolideAttorney Docket No. 11820-034W01YAR01-11PROAcetate), LUPRON DEPOT-PED® (Leuprolide Acetate), LYNPARZA® (Olaparib), MARQIBO® (Vincristine Sulfate Liposome), MATULANE® (Procarbazine Hydrochloride), Mechlorethamine Hydrochloride, Megestrol Acetate, MEKINIST® (Trametinib), Melphalan, Melphalan Hydrochloride, Mercaptopurine, Mesna, MESNEX® (Mesna), METHAZOLASTONE® (Temozolomide), Methotrexate, METHOTREXATE LPF® (Methotrexate), Methylnaltrexone Bromide, MEXATE® (Methotrexate), MEXATE-AQ® (Methotrexate), Midostaurin, Mitomycin C, Mitoxantrone Hydrochloride, MITOZYTREX® (Mitomycin C), MOPP, MOZOBIL® (Plerixafor), MUSTARGEN® (Mechlorethamine Hydrochloride) , MUTAMYCIN® (Mitomycin C), MYLERAN® (Busulfan), MYLOSAR® (Azacitidine), MYLOTARG® (Gemtuzumab Ozogamicin), NANOPARTICLE PACLITAXEL® (Paclitaxel Albumin-stabilized Nanoparticle Formulation), NAVELBINE® (Vinorelbine Tartrate), Necitumumab, Nelarabine, NEOSAR® (Cyclophosphamide), Neratinib Maleate, NERLYNX® (Neratinib Maleate), Netupitant and Palonosetron Hydrochloride, NEULASTA® (Pegfilgrastim), NEUPOGEN® (Filgrastim), NEXAVAR® (Sorafenib Tosylate), NILANDRON® (Nilutamide), Nilotinib, Nilutamide, NINLARO® (Ixazomib Citrate), Niraparib Tosylate Monohydrate, Nivolumab, NOLVADEX® (Tamoxifen Citrate), NPLATE® (Romiplostim), Obinutuzumab, ODOMZO® (Sonidegib), OEPA, Ofatumumab, OFF, Olaparib, Olaratumab, Omacetaxine Mepesuccinate, ONCASPAR® (Pegaspargase), Ondansetron Hydrochloride, ONIVYDE® (Irinotecan Hydrochloride Liposome), ONTAK® (Denileukin Diftitox), OPDIVO® (Nivolumab), OPPA, Osimertinib, Oxaliplatin, Paclitaxel, Paclitaxel Albumin-stabilized Nanoparticle Formulation, PAD, Palbociclib, Palifermin, Palonosetron Hydrochloride, Palonosetron Hydrochloride and Netupitant, Pamidronate Disodium, Panitumumab, Panobinostat, PARAPLAT® (Carboplatin), PARAPLATIN® (Carboplatin), Pazopanib Hydrochloride, PCV, PEB, Pegaspargase, Pegfilgrastim, Peginterferon Alfa-2b, PEG-INTRON® (Peginterferon Alfa-2b), Pembrolizumab, Pemetrexed Disodium, PERIETA® (Pertuzumab), Pertuzumab, PLATINOL® (Cisplatin), PLATINOL-AQ® (Cisplatin), Plerixafor, Pomalidomide, POMALYST® (Pomalidomide), Ponatinib Hydrochloride, PORTRAZZA® (Necitumumab), Pralatrexate, Prednisone, Procarbazine Hydrochloride, PROLEUKIN® (Aldesleukin), PROLIA® (Denosumab), PROMACTA® (Eltrombopag Olamine), Propranolol Hydrochloride, PROVENGE® (SipuleuceLT), PURINETHOL® (Mercaptopurine), PURIXAN® (Mercaptopurine), Radium 223 Dichloride, Raloxifene Hydrochloride, Ramucirumab, Rasburicase, R-CHOP, R-CVP, Recombinant Human Papillomavirus (HPV) Bivalent Vaccine, Recombinant Human Papillomavirus (HPV)Attorney Docket No. 11820-034W01YAR01-11PRONonavalent Vaccine, Recombinant Human Papillomavirus (HPV) Quadrivalent Vaccine, Recombinant Interferon Alfa-2b, Regorafenib, RELISTOR® (Methylnaltrexone Bromide), R-EPOCH, REVLIMID® (Lenalidomide), RHEUMATREX® (Methotrexate), Ribociclib, R-ICE, RITUXAN® (Rituximab), RITUXAN HYCELA® (Rituximab and Hyaluronidase Human), Rituximab, Rituximab and , Hyaluronidase Human, ,Rolapitant Hydrochloride, Romidepsin, Romiplostim, RUBIDOMYCIN® (Daunorubicin Hydrochloride), RUBRACA® (Rucaparib Camsylate), Rucaparib Camsylate, Ruxolitinib Phosphate, RYDAPT® (Midostaurin), Sclerosol Intrapleural Aerosol (Talc), Siltuximab, SipuleuceLT, SOMATULINE DEPOT® (Lanreotide Acetate), Sonidegib, Sorafenib Tosylate, SPRYCEL® (Dasatinib), STANFORD V, Sterile Talc Powder (Talc), STERITALC® (Talc), STIVARGA® (Regorafenib), Sunitinib Malate, SUTENT® (Sunitinib Malate), SYLATRON® (Peginterferon Alfa-2b), SYLVANT® (Siltuximab), Synribo SYNRIBO® (Omacetaxine Mepesuccinate), TABLOID® (Thioguanine), TAC, TAFINLAR® (Dabrafenib), TAGRISSO® (Osimertinib), Talc, Talimogene Laherparepvec, Tamoxifen Citrate, TARABINE PFS® (Cytarabine), TARCEVA® (Erlotinib Hydrochloride), TARGRETIN® (Bexarotene), TAS1GNA® (Nilotinib), TAXOL® (Paclitaxel), TAXOTERE® (Docetaxel), TECENTRIQ® (Atezolizumab), TEMODAR® (Temozolomide), Temozolomide, Temsirolimus, Thalidomide, THALOMID® (Thalidomide), Thioguanine, Thiotepa, Tisagenlecleucel, TOLAK® (Fluorouracil— Topical), Topotecan Hydrochloride, Toremifene, TORISEL® (Temsirolimus), Tositumomab and Iodine I 131 Tositumomab, TOTECT® (Dexrazoxane Hydrochloride), TPF, Trabectedin, Trametinib, Trastuzumab, TREANDA® (Bendamustine Hydrochloride), Trifluridine and Tipiracil Hydrochloride, TRISENOX® (Arsenic Trioxide), TYKERB® (Lapatinib Ditosylate) , UNITUXIN® (Dinutuximab), Uridine Triacetate, VAC, Vandetanib, VAMP, VARUBI® (Rolapitant Hydrochloride), VECTIBIX® (Panitumumab), VelP, VELBAN® (Vinblastine Sulfate), VELCADE® (Bortezomib), VELSAR® (Vinblastine Sulfate), Vemurafenib, VENCLEXTA® (Venetoclax), Venetoclax, VERZENIO® (Abemaciclib), VIADUR® (Leuprolide Acetate), VID AZA® (Azacitidine), Vinblastine Sulfate, VINCASAR PFS® (Vincristine Sulfate), Vincristine Sulfate, Vincristine Sulfate Liposome, Vinorelbine Tartrate, VIP, Vismodegib, VISTOGARD® (Uridine Triacetate), VORAXAZE® (Glucarpidase), Vorinostat, VOTRIENT® (Pazopanib Hydrochloride), VYXEOS® (Daunorubicin Hydrochloride and Cytarabine Liposome), WELLCOVORIN® (Leucovorin Calcium), XALKORI® (Crizotinib), XELODA® (Capecitabine), XELIRI, XELOX, XGEVA® (Denosumab), XOFIGO® (Radium 223 Dichloride), XT ANDI®Attorney Docket No. 11820-034W01 YAR01-11PRO(Enzalutamide), YERVOY® (Ipilimumab), YONDELIS® (Trabectedin), ZALTRAP® (Ziv- Aflibercept), ZARXIO® (Filgrastim), ZEJULA® (Niraparib Tosylate Monohydrate), ZELBORAF® (Vemurafenib), ZEVALIN® (Ibritumomab Tiuxetan), ZINECARD® (Dexrazoxane Hydrochloride), Ziv-Aflibercept, ZOFRAN® (Ondansetron Hydrochloride), ZOLADEX® (Goserelin Acetate), Zoledronic Acid, ZOLINZA® (Vorinostat), ZOMETA® (Zoledronic Acid), ZYDELIG® (Idelalisib), ZYKADIA® (Ceritinib), and / or ZYTIGA® (Abiraterone Acetate). The treatment methods can include or further include checkpoint inhibitors including, but are not limited to antibodies that block PD-1 (such as, for example, Nivolumab (BMS-936558 or MDX1106), pembrolizumab, cemiplimab , CT-011, MK-3475), PD-L1 (such as, for example, atezolizumab, avelumab, durvalumab, MDX-1105 (BMS- 936559), MPDL3280A, or MSB0010718C), PD-L2 (such as, for example, rHIgM12B7), CTLA-4 (such as, for example, Ipilimumab (MDX-010), Tremelimumab (CP-675,206)), IDO, B7-H3 (such as, for example, MGA271, MGD009, omburtamab), B7-H4, B7-H3, T ceil immunoreceptor with Ig and ITIM domains (TIGIT)(such as, for example BMS-986207, OMP-313M32, MK-7684, AB-154, ASP-8374, MTIG7192A, or PVSRIPO), CD96, B- and T-lymphocyte attenuator (BTLA), V-domain 1g suppressor of T cell activation (VlSTA)(such as, for example, JNJ-61610588, CA-170), TIM3 (such as, for example, TSR-022, MBG453, Sym023, INCAGN2390, LY3321367, BMS-986258, SHR-1702, RO7121661), LAG-3 (such as, for example, BMS-986016, LAG525, MK-4280, REGN3767, TSR-033, BI754111, Sym022, FS118, MGD013, and Immutep).

[0138] The following description of exemplary embodiments provides non-limiting representative examples referencing numerals to particularly describe features and teachings of different exemplary aspects and exemplary embodiments of the present disclosure. The exemplary embodiments described should be recognized as capable of implementation separately, or in combination, with other exemplary embodiments from the description of the exemplary embodiments. A person of ordinary skill in the art reviewing the description of the exemplary embodiments should be able to leam and understand the different described aspects of the present disclosure. The description of the exemplary embodiments should facilitate understanding of the exemplary embodiments of the present disclosure to such an extent that other implementations, not specifically covered but within the knowledge of a person of skill in the art having read the description of embodiments, would be understood to be consistent with an application of the exemplary embodiments of the present disclosure.

[0139] To overcome the challenges detailed above, the exemplary systems, methods, and computer-accessible medium according to the exemplary embodiments of the presentAttorney Docket No. 11820-034W01YAR01-11PRO disclosure provide an exhaustive search engine to comprehensively profile (e.g., 11) classes of genetic aberrations from RNA-Seq, encompassing all known tumor-specific events. The exemplary systems, methods, and computer-accessible medium according to the exemplary embodiments of the present disclosure can generate a cancer-specific molecular catalogue of (e.g., 11) classes of molecular alterations across (e.g., 21) histologies, and then can utilize this catalogue as a search space to interrogate (e.g., 1,564) immunopeptidomics datasets, revealing a multitude of actionable immunotherapy targets across cancers.

[0140] T-cell-based immunotherapies have revolutionized cancer treatment, offering cures to subsets of patients who have historically had limited effective therapeutic options. Treatments such as CAR T cell therapies have shown remarkable efficacy, particularly in hematologic malignancies such as acute lymphoblastic leukemia and non-Hodgkin lymphoma. While targeting lineage specific proteins shared between malignant and healthy B cells has proven clinically manageable in blood cancers as patients can tolerate the loss of healthy B cells, such on-target off-tumor effects are unacceptable in solid tumors, where off- tumor reactivity to essential healthy tissues could be catastrophic. This limitation necessitates the identification of antigens with substantial therapeutic windows. Currently, targeting strategies predominantly focus on membrane proteins, which, while promising, often lack sufficient tumor specificity, contributing to on-target, off-tumor side effects. Indeed, a recent report suggests we may be approaching the saturation point for identifying optimal membrane targets for CAR-T therapy, indicating a critical need for innovative targeting strategies that can distinguish between malignant and healthy tissues more effectively.

[0141] Human Leukocyte Antigen (HLA) molecules present a snapshot of the cellular proteome on the membrane of tumor cells, exposing potential tumor-specific antigens on the cell surface. Multiple therapeutic strategies that exert their therapeutic effects through peptides presented on HLA have delivered curative responses in the clinic, including immune checkpoint inhibitors (ICIs), adaptive transfer of Tumor Infiltrating Lymphocytes (TILs), TCR therapies as well as recent complete response from neoantigen vaccines. Immunotherapies such as ICIs and TILs often rely on high mutational burden, therefore the majority of curative responses to these therapies are applicable only to a limited number of highly mutated tumors. Our group and others have recently demonstrated new approaches, such as peptide-centric chimeric antigen receptors (PC-CARs), that can enable the targeting of any peptide on HLA, expanding the targeting of intracellular antigens to low-to-medium mutational tumors. Central to the efficacy of such immunotherapies is the identification of tumor- specific HLA-presented peptides (pHLAs), which can be derived from a broad rangeAttorney Docket No. 11820-034W01YAR01-11PRO of genetic aberrations including both tumor dependency genes that underpin the biology of various cancers or accompanying passenger mutations. Elucidating the landscape of pHLAs derived from these various cancer processes could reveal additional tumor vulnerabilities. Exemplary Systems and Methods

[0142] Figure 1A is a schematic representation of workflow in accordance with certain embodiments described herein. Peptide-MHC (pMHC) receptor proteins with solved crystal structures of modeled complex structures are redesigned by: analyzing peptide-contacts; generating possible mutations against a new target; modeling the new receptor-pMHC complex against on-target and off-target pMHCs; removing those with off-target binding and repeating the process. Redesigned receptors are tested individually and as a scaffold for protein libraries.

[0143] Figure IB shows the proposed AI-Redesign CAR (AIR CAR) strategy overview. As illustrated in Figure IB, this disclosure contemplates that existing binders that peptide- MHC specific contacts can be modified to bind to other peptides. By making mutations to peptide binding residues, we can change the specificity of the original binder to recognize a new peptide in the context of the same MHC. A study was conducted in which mutations were made to the peptide binding residues, then mutations were made to both MHC and peptide binding residues in a second iteration. As shown in Figure IB, an existing structure or model of PC-CAR to PHOX2B peptide-MHC complex as set forth in SEQ ID NO: 38 (e.g. 10LH-PHOX2B-MHC) is used as a starting point. A model or crystal structure of the new target peptide in the context of the same MHC complex (CHRNA3-peptide as set forth in SEQ ID NO: 39) is used as the target molecule. The original PC-CAR (10LH) is superimposed onto the model of the new structure. The Al algorithms and scripts redesigns the original PC-CAR (10LH) against the new peptide MHC complex (CHRNA3-MHC (SEQ ID NO: 39)).

[0144] Figure 1C illustrates iterative modification of generated PC-CARs. A generated PC-CAR from a previous iteration can be used as the starting point of another iteration (with or without in vitro testing as a binder). Here, the output of the previous iteration is a model of an AIRed-PC-CAR and the target pMHC complex. Al and scripts are used to redesign contacts within a distance threshold. Top PC-CARs can be tested in vitro, and following this, can undergo another iteration.

[0145] Figure ID is a schematic diagram depicting a generalizable approach for all pMHC binders. The proposed pipeline can be run for more than just PC-CARs to target pMHCs and can be expanded to other receptor molecules. This starts with PC-CARs (10LHAttorney Docket No. 11820-034W01 YAR01-11PRO or 3M4E5), alternative scaffolds like protein A z-domains (affibodies), or de novo generated proteins (undergoing testing) in a model or crystal structure with their original target proteins. General specifics about the pipeline. Prior to redesign, the original binder structure (crystal structure or model) is analyzed by our script to identify peptide only binding residues (missing from the figure). Then the original binding complex structure must be superimposed onto a model or crystal structure of the new target pMHC, the old pMHC is removed from this model to generate a model with 1 ) the original receptor and 2) a new target pMHC. This model is then redesigned by proteinMPNN generating amino acid sequences of potential AIRed-PC-CARs. The top AIRed-PC-CARs with lowest proteinMPNN score (best score) and a few of the most frequent PC-CAR sequences is then chosen for modeling. The structure is then relaxed to a lower predicted energy state by a structural relaxation function like Rosetta fastrelax. We then score these AIRed-PC-CAR models by the type and number of peptide-bonds to the new pMHC found in the AF2-relaxed model. Top PC-CARs having a peptide-binding score over a threshold are then modeled with an off-target pMHC (like the original target pMHC), following this, the model is relaxed and rescored. PC-CARs showing low / no off-target peptide binding scores and low MHC binding scores can be tested or the top scoring PC-CAR can be chosen for another iteration through the pipeline. A general trend so far from optimization results is that the first iteration breaks peptide specificity and the second iteration lowers affinity but improves specificity. This disclosure contemplates that a third iteration or subsequent iteration can further optimize results.

[0146] Figure IE is a flowchart diagram showing an expanded processing pipeline 100E in accordance with certain embodiments described herein. In some implementations, the pipeline 100E includes optional preliminary steps / operations. For example, as shown, the pipeline 100E includes optional preliminary Steps -2, -1, and 0.

[0147] At Step -2, an original PC-CAR pMHC complex structure is analyzed for peptide only binding residues. The constraint here may be a true / predicted binding interaction within a distance within 0-6 Angstroms.

[0148] At Step -1, a new peptide-MHC target structure / model is generated.

[0149] At Step 0, the original PC-CAR-pMHC complex structure is superimposed onto new peptide-MHC target structure from Step -1 and then the original pMHC is removed. In one example, the preliminary steps are performed using python scripts or manually in PyMOL.Attorney Docket No. 11820-034W01YAR01-11PRO

[0150] At Step 1, using the structural model generated in the above preliminary steps, step 0, and residues identified from Step -2, ProteinMPNN is run to make mutations to the original PC-CAR, generating 100,000 new sequences with matched ProteinMPNN scores.

[0151] At Step 2, ProteinMPNN generated AIRed-PC-CAR amino acid sequences are analyzed for the most frequently repeated sequences and lowest ProteinMPNN score. 5 most frequent sequences and top 95 scoring AIRed-PC-CARs are chosen.

[0152] At Step 3, Alphfold2 is used to model the 100 AIRed-PC-CAR sequences with the new target pMHC (on-target pMHC).

[0153] At Step 4, the 100 models are then relaxed with Rosetta fastrelax, generating 100 relaxed complex structures.

[0154] At Step 5, the proposed protein complex analysis script analyzes models, scoring AIRed-PC-CARs by their number and type of bonds with the pMHC model. Best binders above a peptide- scoring threshold are chosen.

[0155] At step 6, AIRed-PC-CARs are then modeled with an off-target pMHC using Alphafold2.

[0156] At Step 7, the models are relaxed, for example, with Rosetta fastrelax.

[0157] At Step 8, the models are rescored using the proposed scoring function. Binders having a high peptide or MHC only score are removed from further testing. Best scoring AIRed-PC-CAR here (Step 5) that pass screening (Steps 6-8) is tested in vitro.

[0158] At Step 9, the top scoring PC-CAR is also redesigned through a second iteration of the pipeline. The AIRed-PC-CAR-on-target pMHC model is used as an input. The residues chosen for mutation in the AIRed-PC-CAR are residues that are 0-4 Angstroms away from the on-target pMHC.

[0159] Steps 10-16 mirror Steps 2-8 above.

[0160] At Step 17, DNA corresponding to top AIRed-PC-CAR(s) from iteration 1 and 2 as shown in Figure 1 E are ordered, cloned, and tested as PC-CARs for binding in vitro on cells.

[0161] Exemplary Process: The amino acids mutated for the first iteration depicted in Figure IE are always the same 4 residues; these were identified via lOLH's crystal structure. These 4 residues are amino acids that are only binding the PHOX2b peptide and no interactions to the MHC. The goal here is to break initial specificity to the PHOX2B peptide. For the second iteration in Figure IE, we generated a script to take the best binder from the first iteration and identify residues on the PC-CAR within a predetermined distance threshold (e.g., 4 Angstroms or less) from the peptide (CHRNA3). Buffer residues can be added, whichAttorney Docket No. 11820-034W01YAR01-11PRO means selecting residues whose positions are + or - 1 from the selected residue’s position. For instance, if we identified that the amino acid residue at position 15 was within 4 Angstroms from CHRNA3, the residues that we would mutate for the second iteration was 14, 15, and 16. But one important limitation is that these residues are limited to the CDRs of the scFv. Staying consistent with the previous example, and by way of example only, if the CDR range was known to be at positions 13-15, then the amino acid at position 16 would not be included despite being a buffer residue. This ensures that elements of the scFv scaffold that might be important for overall stability of the PC-CAR are not impacted.

[0162] Example Computing Device

[0163] It should be appreciated that the logical operations described herein with respect to the various figures may be implemented (1) as a sequence of computer- implemented acts or program modules (i.e., software) running on a computing device (e.g., the computing device described in Figure IF), (2) as interconnected machine logic circuits or circuit modules (i.e., hardware) within the computing device and / or (3) a combination of software and hardware of the computing device. Thus, the logical operations discussed herein are not limited to any specific combination of hardware and software. The implementation is a matter of choice dependent on the performance and other requirements of the computing device. Accordingly, the logical operations described herein are referred to variously as operations, structural devices, acts, or modules. These operations, structural devices, acts and modules may be implemented in software, in firmware, in special purpose digital logic, and any combination thereof. It should also be appreciated that more or fewer operations may be performed than shown in the figures and described herein. These operations may also be performed in a different order than those described herein.

[0164] Referring to Figure IF, an example computing device 1000 upon which embodiments of the invention may be implemented is illustrated. This disclosure contemplates that the controller(s) for operating the flexure elements and / or imaging apparatus can be implemented using computing device 1000. It should be understood that the example computing device 1000 is only one example of a suitable computing environment upon which embodiments of the invention may be implemented. Optionally, the computing device 1000 can be a well-known computing system including, but not limited to, personal computers, servers, handheld or laptop devices, multiprocessor systems, microprocessorbased systems, network personal computers (PCs), minicomputers, mainframe computers, embedded systems, and / or distributed computing environments including a plurality of any of the above systems or devices. Distributed computing environments enable remote computingAttorney Docket No. 11820-034W01YAR01-11PRO devices, which are connected to a communication network or other data transmission medium, to perform various tasks. In the distributed computing environment, the program modules, applications, and other data may be stored on local and / or remote computer storage media.

[0165] In its most basic configuration, computing device 1000 typically includes at least one processing unit 1006 and system memory 1004. Depending on the exact configuration and type of computing device, system memory 1004 may be volatile (such as random access memory (RAM)), non-volatile (such as read-only memory (ROM), flash memory, etc.), or some combination of the two. This most basic configuration is illustrated in Figure IF by dashed line 1002. The processing unit 1006 may be a standard programmable processor that performs arithmetic and logic operations necessary for operation of the computing device 1000. The computing device 1000 may also include a bus or other communication mechanism for communicating information among various components of the computing device 1000.

[0166] Computing device 1000 may have additional features / functionality. For example, computing device 1000 may include additional storage such as removable storage 1008 and non-removable storage 1010 including, but not limited to, magnetic or optical disks or tapes. Computing device 1000 may also contain network connection(s) 1016 that allow the device to communicate with other devices. Computing device 1000 may also have input device(s) 1014 such as a keyboard, mouse, touch screen, etc. Output device(s) 1012 such as a display, speakers, printer, etc. may also be included. The additional devices may be connected to the bus in order to facilitate communication of data among the components of the computing device 1000. All these devices are well known in the art and need not be discussed at length here.

[0167] The processing unit 1006 may be configured to execute program code encoded in tangible, computer-readable media. Tangible, computer-readable media refers to any media that is capable of providing data that causes the computing device 1000 (i.e., a machine) to operate in a particular fashion. Various computer-readable media may be utilized to provide instructions to the processing unit 1006 for execution. Example tangible, computer-readable media may include, but is not limited to, volatile media, non-volatile media, removable media and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. System memory 1004, removable storage 1008, and non-removable storage 1010 are all examples of tangible, computer storage media. Example tangible, computer-readableAttorney Docket No. 11820-034W01YAR01-11PRO recording media include, but are not limited to, an integrated circuit (e.g., field- programmable gate array or application- specific IC) , a hard disk, an optical disk, a magnetooptical disk, a floppy disk, a magnetic tape, a holographic storage medium, a solid-state device, RAM, ROM, electrically erasable program read-only memory (EEPROM), flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices.

[0168] In an example implementation, the processing unit 1006 may execute program code stored in the system memory 1004. For example, the bus may carry data to the system memory 1004, from which the processing unit 1006 receives and executes instructions. The data received by the system memory 1004 may optionally be stored on the removable storage 1008 or the non-removable storage 1010 before or after execution by the processing unit 1006.

[0169] It should be understood that the various techniques described herein may be implemented in connection with hardware or software or, where appropriate, with a combination thereof. Thus, the methods and apparatuses of the presently disclosed subject matter, or certain aspects or portions thereof, may take the form of program code (i.e., instructions) embodied in tangible media, such as floppy diskettes, CD-ROMs, hard drives, or any other machine-readable storage medium wherein, when the program code is loaded into and executed by a machine, such as a computing device, the machine becomes an apparatus for practicing the presently disclosed subject matter. In the case of program code execution on programmable computers, the computing device generally includes a processor, a storage medium readable by the processor (including volatile and non-volatile memory and / or storage elements), at least one input device, and at least one output device. One or more programs may implement or utilize the processes described in connection with the presently disclosed subject matter, e.g., through the use of an application programming interface (API), reusable controls, or the like. Such programs may be implemented in a high-level procedural or object-oriented programming language to communicate with a computer system. However, the program(s) can be implemented in assembly or machine language, if desired. In any case, the language may be a compiled or interpreted language and it may be combined with hardware implementations.

[0170] Example PC-CAR Design System

[0171] Figure 2 is a diagram of an example PC-CAR design system 200 configured to facilitate the development of PC-CARs for therapeutics targeting intracellular tumor driverAttorney Docket No. 11820-034W01YAR01-11PRO via pMHC complexes (e.g., class I MHC). In one implementation, starting from a known binder (e.g., 10LH), residues are mutated to target new peptides (e.g., chRNA3), followed by modeling and scoring for specificity and off-target filtering. The process is iterative, involving multiple rounds of refinement. A proprietary script selects residues for mutation based on distance scores (e.g., 6 A in iteration 1, 4 A in iteration 2), interfaces with third- party software locally, and filters binders based on binding scores and off-target modeling. The system 200 can be used to determine one or more immunotherapy targets from sequence data 202 obtained from one of more data sources or databases (e.g., B-cell antibody libraries). The sequence data 202 may be sequence data from one or more subjects (e.g., thousands of patients). The system 200 can be configured to integrate data from multiple sources, for example a first data entity 221a, a second data entity 221b, and a third data entity 221c. The plurality of data entities 221a, 221b, 221c can be or comprise databases or datasets associated with research institutions, data management providers and / or the like. The system 200 can analyze the sequence data 202 to determine immunotherapy targets and / or additional data (e.g., user interface data) as described in more detail herein.

[0172] As depicted in Figure 2, the system 200 comprises one or more machine learning model(s) 205, a modeling component 214, filtering component 216, analyzing component 218, and a visualization engine 220. In some implementations, as illustrated, the machine learning model(s) 205 can include one or more redesigning components 211 (e.g., ProteinMPNN), one or more sequence generating components 213, one or more modeling components 215 (e.g., AlphaFold2), one or more relaxation components 217 (also referred to as low-energy modeling components (e.g., Rosetta: fastrelax)), and one or more scoring components 219. The machine learning model(s) 205 can be or comprise deep-learning models configured to predict and generate three-dimensional models of protein structures from sequence data. An example relaxation component 217 can be configured to optimize and / or refine protein structures by identifying low-energy conformations in order to eliminate unrealistic (high-energy) conformations in crystal structure models.

[0173] This disclosure contemplates that the sequence generating component(s) 213 can be or comprise ProteinMPNN, Ablang, ThermoMPNN, AbMPNN, SolMPNN, combinations thereof, and / or the like. In various embodiments, the modeling component 215 can be or comprise SimpleFold, AlphaFold2, AlphaFold3, ESMFold, RosettaFold, RosettaFold2, RosettaFold3, AntiFold, EquiFold, AlphaFlow, ABodyBuilderl, ABodyBuilder2, ABodyBuilder3, combinations thereof, and / or the like. Additionally, the system 200 / machineAttorney Docket No. 11820-034W01YAR01-11PRO learning models 205 can be or comprise full pipelines such as Boltz- 1, Boltz-2, BindCraft, AlphaProteo, CHAI-1, CHAI-2, combinations thereof, and / or the like.

[0174] The visualization engine 220 can be configured to generate user interface data for display to an end user (e.g., a report, summary, and / or data object(s) describing genetic aberrations and / or a list of antigens). In some implementations, output data (e.g., immunotherapy targets or additional data) can be used as an input to a search engine 225 to identify tumor-specific antigens. In some embodiments, the analyzing component 218 can process, pre-process and / or transform sequence data 202 for downstream operations and may also select binders in different steps of the process described in connection with Figure 3, for example. The filtering component 216 can filter on-target and / or off-target binders and the modeling component 214 can supplement or enhance operations of the machine- learning models 205 (see method 300 described in connection with Figure 3). In some implementations, at least a portion of the received / generated data can be transferred to other computing entities or devices as needed to increase processing speed or efficiently handle large amounts of data. Workflow allocation can be optimized based on time and memory constraints while considering internal dependencies.

[0175] Example Method

[0176] Referring now to Figure 3, a flowchart of an example computer- implemented method 300 for modifying, designing, and / or redesigning PC-CARs is provided. In some implementations, the method 300 can be performed by a processing circuitry (for example, but not limited to, an application-specific integrated circuit (ASIC), or a central processing unit (CPU)). In some examples, the processing circuitry may be electrically coupled to and / or in electronic communication with other circuitries of an example computing device, such as, but not limited to, the example computing device 1000 described above in connection with Figure IF. In some examples, embodiments may take the form of a computer program product on a non-transitory computer-readable storage medium storing computer-readable program instruction (e.g., computer software). Any suitable computer-readable storage medium may be utilized, including non-transitory hard disks, CD-ROMs, flash memory, optical storage devices, or magnetic storage devices. This disclosure contemplates that some or all of the steps / operations below can be implemented using machine learning models and artificial intelligence-based techniques, such as, but not limited to, deep learning models as described in more detail below.

[0177] Optionally, at step 301, the method 300 includes aligning a known PC-CAR structure model of known specificity with a target to generate the first PC-CAR bindingAttorney Docket No. 11820-034W01YAR01-11PRO molecular model. In some embodiments, step / operation 301 comprises one or more sub- steps / operations. For example, step / operation 301 can include, using the known PC-CAR structure or model of known specificity, identifying peptide-binding residues (e.g., within 6 Angstroms for proteinMPNN), modeling a new target pMHC molecule separately without the PC-CAR (e.g., CHRNA3-pMHC molecule), superimposing the PC-CAR-pMHC structure (step 1 in Figure ID) onto the modeled pMHC molecule (step 2 in Figure ID), removing the old pMHC and saving this as a model (PC-CAR superimposed on CHRNA3-pMHC) as input into proteinMPNN, then using ProteinMPNN to design more PC-CARs.

[0178] At step / operation 302, the method 300 includes retrieving a first PC-CAR binding molecular model (e.g., computer structure model or crystal structure model) specific for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule. In some implementations, the first PC-CAR binding molecular model is selected from a plurality of sequences that includes most frequent sequences and best scoring (e.g., lowest or highest) sequences. In one example, the first target peptide comprises a PHOX2B epitope. The PHOX2B epitope can comprise SEQ ID NO: 38. In some embodiments, the first PC-CAR comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, and SEQ ID NO: 3, respectively. In some embodiments, the first PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, and SEQ ID NO: 22, respectively. The first peptide can comprise a CHRNA3 epitope, and the CHRNA3 epitope comprises SEQ ID NO: 39.

[0179] At step / operation 304, the method 300 includes determining PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC-CAR molecules. In some embodiments, generating the plurality of modified PC-CAR binding molecules comprises using a deep learning model to predict a three-dimensional protein structures from a sequence corresponding with each molecule. In some examples, the PC-CAR residues are determined based on binding residues within a predefined distance threshold. The distance threshold can be between 0-6 A.

[0180] At step / operation 306, the method 300 includes iteratively modeling on-target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule. In one example, the applied distance threshold after iteratively modeling on-target binding of the plurality of modified PC-CAR binding molecules is 5-7 A.Attorney Docket No. 11820-034W01YAR01-11PRO

[0181] At step / operation 308, the method 300 includes generating a relaxed structure model (e.g., using a relaxation operation / function or by modeling each PC-CAR binding molecule in a lower-energy state) for one or more of the plurality of modified PC-CAR binding molecules that bound to the second target peptide in step / operation 306 to increase structural stability of the modified PC-CAR binding molecules. Generating at least one relaxed structure model improves the end results by eliminating unrealistic (high-energy) conformations in the generated crystal structure models. The experimental results demonstrate the effectiveness of the approach shown in Figure ID which includes a first relaxation operation and a second relaxation operation.

[0182] At step / operation 310, the method 300 includes analyzing, by the at least one processor, binding of the generated relaxed structure models to identify the best on-target binders. In some implementations, step / operation 310 includes determining a specificity score for each molecule and selecting the plurality of candidate modified PC-CAR binding molecules to the second target peptide based on the determined specificity scores. The specificity score for each molecule is determined based on possible bonds (e.g., interactions between a respective PC-CAR and pMHC molecule) within the respective model that are between 0-4 A.

[0183] At step / operation 312, the method 300 optionally further includes iteratively modeling, by the at least one processor, off-target binding of the best on-target binders from the plurality of modified PC-CAR binding molecules to the first target peptide in the context of the first MHC molecule. In some implementations, subsequent to iteratively modeling off- target binding of the best on-target binders from the plurality of modified PC-CAR binding molecules, the method 300 includes generating a second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules to increase stability of the modified PC-CAR binding molecules that did not bind to the first target peptide. In one example, the distance threshold applied after iteratively modeling off-target binding of the best on-target binders is 3-5 A.

[0184] At step / operation 314, the method 300 includes identifying, based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step / operation 312. In some implementations, the candidate modified PC- CAR binding molecules bind the second target peptide in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule and exhibits affinity and specificity for the second peptide target.Attorney Docket No. 11820-034W01YAR01-11PRO

[0185] Optionally, at step / operation 315, the method 300 includes identifying, by the at least one processor and based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from the previous step.

[0186] At step / operation 316, the method 300 optionally includes testing the plurality of candidate modified PC-CAR binding molecules, for example, by generating additional computer-based models or in vitro testing.

[0187] Optionally, at step / operation 318, the method 300 includes generating a report, summary, and / or data object describing at least a portion of the analysis. For example, step / operation 318 can include outputting a report describing some or all of the candidate modified PC-CAR binding molecules. In some implementations, the output of the method 300 is provided via an interactive web portal, allowing end users to directly explore the generated predictions / predictive outputs. Alternatively or additionally, step / operation 318 optionally further includes generating display data for the report. Alternatively or additionally, the method 300 optionally further includes transmitting the report over a network. This disclosure contemplates that operations related to generation of the report can be performed using one or more computing devices / systems (e.g., at least the configuration illustrated in Figure IF).

[0188] Artificial Intelligence and Machine Learning

[0189] Embodiments of the present disclosure utilize machine learning models and artificial intelligence for various data processing operations to, for example, refine results to enhance sensitivity and to enhance the accuracy of subsequent searches.

[0190] The term “artificial intelligence” is defined herein to include any technique that enables one or more computing devices or comping systems (i.e., a machine) to mimic human intelligence. Artificial intelligence (Al) includes, but is not limited to, knowledge bases, machine learning, representation learning, and deep learning. The term “machine learning” is defined herein to be a subset of Al that enables a machine to acquire knowledge by extracting patterns from raw data. Machine learning techniques include, but are not limited to, logistic regression, support vector machines (SVMs), decision trees, Naive Bayes classifiers, and artificial neural networks. The term “representation learning” is defined herein to be a subset of machine learning that enables a machine to automatically discover representations needed for feature detection, prediction, or classification from raw data. Representation learning techniques include, but are not limited to, autoencoders. The term “deep learning” is defined herein to be a subset of machine learning that that enables aAttorney Docket No. 11820-034W01YAR01-11PRO machine to automatically discover representations needed for feature detection, prediction, classification, etc. using layers of processing. Deep learning techniques include, but are not limited to, artificial neural network or multilayer perceptron (MLP).

[0191] Machine learning models include supervised, semi-supervised, and unsupervised learning models. In a supervised learning model, the model learns a function that maps an input (also known as feature or features) to an output (also known as target or targets) during training with a labeled data set (or dataset). In an unsupervised learning model, the model learns patterns (e.g., structure, distribution, etc.) within an unlaheled data set. In a semisupervised model, the model learns a function that maps an input (also known as feature or features) to an output (also known as target or target) during training with both labeled and unlabeled data.

[0192] An artificial neural network (ANN) is a computing system including a plurality of interconnected neurons (e.g., also referred to as “nodes”). This disclosure contemplates that the nodes can be implemented using a computing device (e.g., a processing unit and memory as described herein). The nodes can be arranged in a plurality of layers such as input layer, output layer, and optionally one or more hidden layers. An ANN having hidden layers can be referred to as deep neural network or multilayer perceptron (MLP). Each node is connected to one or more other nodes in the ANN. For example, each layer is made of a plurality of nodes, where each node is connected to all nodes in the previous layer. The nodes in a given layer are not interconnected with one another, i.e., the nodes in a given layer function independently of one another. As used herein, nodes in the input layer receive data from outside of the ANN, nodes in the hidden layer(s) modify the data between the input and output layers, and nodes in the output layer provide the results. Each node is configured to receive an input, implement an activation function (e.g., binary step, linear, sigmoid, tanH, or rectified linear unit (ReLU) function), and provide an output in accordance with the activation function. Additionally, each node is associated with a respective weight. ANNs are trained with a dataset to maximize or minimize an objective function. In some implementations, the objective function is a cost function, which is a measure of the ANN’s performance (e.g., error such as LI or L2 loss) during training, and the training algorithm tunes the node weights and / or bias to minimize the cost function. This disclosure contemplates that any algorithm that finds the maximum or minimum of the objective function can be used for training the ANN. Training algorithms for ANNs include, but are not limited to, backpropagation. It should be understood that an artificial neural network is provided only as an example machine learning model. This disclosure contemplates that theAttorney Docket No. 11820-034W01YAR01-11PRO machine learning model can be any supervised learning model, semi-supervised learning model, or unsupervised learning model. Optionally, the machine learning model is a deep learning model. Machine learning models are known in the art and are therefore not described in further detail herein.

[0193] A convolutional neural network ( CNN) is a type of deep neural network that has been applied, for example, to image analysis applications. Unlike a traditional neural networks, each layer in a CNN has a plurality of nodes arranged in three dimensions (width, height, depth). CNNs can include different types of layers, e.g., convolutional, pooling, and fully-connected (also referred to herein as “dense”) layers. A convolutional layer includes a set of filters and performs the bulk of the computations. A pooling layer is optionally inserted between convolutional layers to reduce the computational power and / or control overfitting (e.g., by downsampling). A fully-connected layer includes neurons, where each neuron is connected to all of the neurons in the previous layer. The layers are stacked similar to traditional neural networks.

[0194] Experimental Results

[0195] A study was conducted to evaluate the proposed system and method.

[0196] Figure 4A are graphs showing results from testing PC-CARs for on-target binding, where HEK293T cells were transfected with PC-CAR expression vectors and illustrate the gating strategy for the conducted binding experiments. Transfected cells are first gated for live cells and then singlets. Our expression vectors also have expression of the fluorescent protein BFP. Cells are gated for BFP positive cells. Cells are then co-stained with fluorescently tagged pMHC tetramers.

[0197] Figure 4B shows that our original PC-CAR, 10LH shows specificity for only PHOX2B pMHC tetramer (Left) and AIRed- PC-CAR (2_6) from Iteration 1 (see Figure IE) showing specificity for both PHOX2B pMHC and CHRNA3 pMHC tetramers (Right).

[0198] Figure 4C illustrate results from the second iteration (see Figure IE) showing that 2_6 was the starting point for a second computation iteration. As illustrated, AIRed-PC- CARs from the second iteration show slight binding to CHRNA3 (Left) and no binding to PHOX2B (Right).

[0199] Figure 4D illustrates results from the second iteration showing that AIRed PC- CAR 19_9 show greater binding to CHRNA3 (Left). The same cells transfected with PC- CAR 19_9 were co-stained with anti-V5 antibody (receptor expression) and CHRNA3 pMHC tetramer (Right). PC-CAR 19_9 shows binding only at higher receptor expression.Attorney Docket No. 11820-034W01YAR01-11PRO

[0200] Figure 4E shows a sequence alignment of AIRed-PC-CAR mutated CDR sequences (CDRL3, CDRH2, CDRH3). Shown are CDRL3 amino acid sequences for 10LH (SEQ ID NO: 3), 2_6 (SEQ ID NO: 4), 19_9 (SEQ ID NO: 5), 4_8 (SEQ ID NO: 6), 17_3 (SEQ ID NO: 7), 13_9 (SEQ ID NO: 8), 12_3 (SEQ ID NO: 9), 14_1 (SEQ ID NO: 10), 9_1 (SEQ ID NO: 11), 10_4 (SEQ ID NO: 12), 1_5 (SEQ ID NO: 11), 10_2 (SEQ ID NO: 13), 10_3 (SEQ ID NO: 14), and 6_2 (SEQ ID NO: 15); the CDRH2 amino acid sequences for 10LH (SEQ ID NO: 17), 2_6 (SEQ ID NO: 17), 19_9 (SEQ ID NO: 18), 4_8 (SEQ ID NO: 19), 17_3 (SEQ ID NO: 20), 13_9 (SEQ ID NO: 19), 12_3 (SEQ ID NO: 20), 14_1 (SEQ ID NO: 19), 9_1 (SEQ ID NO: 21), 10_4 (SEQ ID NO: 18), 1_5 (SEQ ID NO: 11), 10_2 (SEQ ID NO: 20), 10_3 (SEQ ID NO: 20), and 6_2 (SEQ ID NO: 19); and the CDRH3 amino acid sequences for 10LH (SEQ ID NO: 22) and the shared CDRH3 amino acid sequence for the modified PC-CARs 2_6, 19_9, 4_8, 17_3, 13_9, 12_3, 14_1, 9_1, 10_4, 1_5, 10_2, 13_3, and 6_2 (SEQ ID NO: 23). AIRed-PC-CARs were ordered by iteration, then by specificity of in vitro binding (ratio of CHRN A3 -binding to PHOX2B). Mutations corresponding to when their first appeared are colored orange (iteration 1), and blue (iteration 2), respectively.

[0201] Figure 4F shows sequence alignment for the PC-CAR CDRL3. Shown are CDRL3 amino acid sequences for 10LH (SEQ ID NO: 3), 2_6 (SEQ ID NO: 4), 19_9 (SEQ ID NO: 5), 4_8 (SEQ ID NO: 6), 17_3 (SEQ ID NO: 7), 13_9 (SEQ ID NO: 8), 12_3 (SEQ ID NO: 9), 14_1 (SEQ ID NO: 10), 9_1 (SEQ ID NO: 11), 10_4 (SEQ ID NO: 12), 1_5 (SEQ ID NO: 11), 10_2 (SEQ ID NO: 13), 10_3 (SEQ ID NO: 14), and 6_2 (SEQ ID NO: 15). Conserved CDRL3 motifs are apparent: TDP or TDF. Then there is (S / A)(N / A)GLN motif (SEQ ID NO: 40).

[0202] Figure 4G shows CDRL3 oriented loop structure. Shown are (S / A)(N / A)GLN motif (SEQ I NO: 40) with TDF or (S / A)(N / A)GLN (SEQ I NO: 40) with RDP both orient the CDRL3 loop (i.e., 19 9 CAR CDLR3 QATDFSNGLNVV (SEQ ID NO: 5) and 4_6 CAR CDRL3 QARDPAAGLNVV) against the peptide

[0203] Figure 4H shows peptide interactions are broken down to mainchain-based hydrogen bonding networks. Shown is the interaction of the 19_9 CAR CDLR3 QATDFSNGLNVV (SEQ ID NO: 5) with the CHRNA3 peptide epitope IYPDITYSL ( SEQ ID NO: 39) and the 4_6 CAR CDRL3 QARDPAAGLNVV with the CHRN A3 peptide epitope IYPDITYSL ( SEQ ID NO: 39).

[0204] Figure 41 shows an alignment of the CDRH2 for the PC-CARs 10LH (SEQ ID NO: 17), 2_6 (SEQ ID NO: 17), 19_9 (SEQ ID NO: 18), 4_8 (SEQ ID NO: 19), 17_3 (SEQ ID NO: 20), 13 9 (SEQ ID NO: 19), 12 3 (SEQ ID NO: 20), 14_1 (SEQ ID NO: 19), 9_1Attorney Docket No. 11820-034W01YAR01-11PRO(SEQ ID NO: 21), 10_4 (SEQ ID NO: 18), 1_5 (SEQ ID NO: 11), 10_2 (SEQ ID NO: 20), 10_3 (SEQ ID NO: 20), and 6_2 (SEQ ID NO: 19). The alignment shows that the CDRH2 motifs are either: KGD, RGD, or DGS.

[0205] Figure 41 shows Both KGD (i.e, the motif in the CDRH2 SEQ ID NO: 18) and RGD (i.e, the motif in the CDRH2 SEQ ID NO: 19) bind to the MHC (grey) through hydrogen bonds, orient other parts of the loop to bind to the MHC (ST).

[0206] Figure 4K shows DGS motif is another solution orientating framework residues to (ser and tyr) to interact with the HLA.

[0207] Figure 4L shows a sequence alignment for the CDRH3 amino acid sequences for 10LH (SEQ ID NO: 22) and the shared CDRH3 amino acid sequence for the modified PC- CARs 2_6, 19_9, 4_8, 17_3, 13_9, 12_3, 14_1, 9_1, 10_4, 1_5, 10_2, 13_3, and 6_2 (SEQ ID NO: 23). The CDRH3 Q mutation appears in iteration 1 and is sustained.

[0208] Figure 4M shows The CDH3-Q function depends on other motifs. In the TDF CDRL3 motif, it just binds the MHC. In the RDP CDRL3 motif, it binds MHC, orients the R in CDRL3 to contact the peptide and stabilizes the mainchain of a Tyrosine to engage with the peptide as well.

[0209] The foregoing merely illustrates the principles of the disclosure. Various modifications and alterations to the described embodiments will be apparent to those skilled in the art in view of the teachings herein. It will thus be appreciated that those skilled in the art will be able to devise numerous systems, arrangements, and procedures which, although not explicitly shown or described herein, embody the principles of the disclosure and can be thus within the spirit and scope of the disclosure. Various different exemplary embodiments can be used together with one another, as well as interchangeably therewith, as should be understood by those having ordinary skill in the art. In addition, certain terms used in the present disclosure, including the specification and drawings, can be used synonymously in certain instances, including, but not limited to, for example, data and information. It should be understood that, while these words, and / or other words that can be synonymous to one another, can be used synonymously herein, that there can be instances when such words can be intended to not be used synonymously. Further, to the extent that the prior art knowledge has not been explicitly incorporated by reference herein above, it is explicitly incorporated herein in its entirety. All publications referenced are incorporated herein by reference in their entireties.

[0210] Throughout the disclosure, the following terms take at least the meanings explicitly associated herein, unless the context clearly dictates otherwise. The term “or” isAttorney Docket No. 11820-034W01YAR01-11PRO intended to mean an inclusive “or.” Further, the terms “a,” “an,” and “the” are intended to mean one or more unless specified otherwise or clear from the context to be directed to a singular form.

[0211] This written description uses examples to disclose certain implementations of the disclosed technology, including the best mode, and also to enable any person skilled in the art to practice certain implementations of the disclosed technology, including making and using any devices or systems and performing any incorporated methods. The patentable scope of certain implementations of the disclosed technology is defined in the appended paragraphs, and may include other examples that occur to those skilled in the art. Such other examples are intended to be within the scope of the appended paragraphs if they have structural elements that do not differ from the literal language of the appended paragraphs, or if they include equivalent structural elements with insubstantial differences from the literal language of the appended paragraphs.

[0212] Exemplary Aspects

[0213] In view of the described device and processes, herein are described certain more particularly described aspects of the disclosures. These particularly recited aspects should not, however, be interpreted to have any limiting effect on any different claims containing different or more general teachings described herein, or that the “particular” aspects are somehow limited in some way other than the inherent meanings of the language and formulas literally used therein.

[0214] Further exemplary aspects of the disclosure are provided by one or more of the following examples:

[0215] Example 1. A computer- implemented method for generating a peptide centric (PC) chimeric antigen receptor (CAR) (PC-CAR) binding molecule, the method comprising: a) retrieving, by at least one processor, a first PC-CAR binding molecular model for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule; b) determining, by the at least one processor, PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC- CAR molecules; c) iteratively modeling, by the at least one processor, on-target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule; d) generating, by the at least one processor, a relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules that bound to the second target peptide in step c) to increase molecular complex structural stability of the modified PC-CAR binding molecules; e) analyzing, by the at least oneAttorney Docket No. 11820-034W01YAR01-11PRO processor, binding of the generated relaxed structure models to identify the best on-target binders from step d); f) iteratively modeling, by the at least one processor, off-target binding of the best on-target binders from the plurality of modified PC-CAR binding molecules of step e) to the first target peptide in the context of the first MHC molecule; g) identifying, by the at least one processor and based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step f), wherein the candidate modified PC-CAR binding molecules bind the second target peptide in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule, and exhibits affinity and specificity for the second peptide target.

[0216] Example 2. The method of Example 1 , further comprising: subsequent to iteratively modeling off-target binding, generating a second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules to increase stability of the modified PC-CAR binding molecules that did not bind to the first target peptide in step f).

[0217] Example 3. The method of Example 1 or 2, further comprising: aligning, by the at least one processor, a known PC-CAR structure model of known specificity with a target to generate the first PC-CAR binding molecular model.

[0218] Example 4. The method of Example 3, wherein aligning the known PC-CAR structure model to generate the first PC-CAR binding molecular model comprises: identifying, by the at least one processor, peptide-binding residues within 6 Angstroms of the known PC-CAR structure model, modeling, by the at least one processor, a new target pMHC molecule separately without the known PC-CAR structure model, modeling, by the at least one processor, the first PC-CAR binding molecular model or crystal structure, and superimposing, by the at least one processor, the PC-CAR-pMHC structure of the known PC- CAR structure model onto the modeled pMHC molecule, removing, by the at least one processor, the known pMHC from the new target pMHC molecule (PC-CAR superimposed on CHRNA3-pMHC), wherein the new target pHMC is used as an input to generate the plurality of modified PC-CAR molecules.

[0219] Example 5. The method of any one of Example 1-4, wherein analyzing binding of the generated relaxed structure models comprises: determining a specificity score for each molecule and selecting the plurality of candidate modified PC-CAR binding molecules to the second target peptide based on the determined specificity scores.Attorney Docket No. 11820-034W01YAR01-11PRO

[0220] Example 6. The method of Example 5, wherein the specificity score for each molecule is determined based on possible bonds (e.g., interactions between a respective PC- CAR and pMHC molecule) within the respective model that are between 0-4 Angstroms (A).

[0221] Example 7. The method of any one of Example 1-6, wherein generating the plurality of modified PC-CAR binding molecules comprises using a deep learning model to predict a three-dimensional protein structures from a sequence corresponding with each molecule.

[0222] Example 8. The method of any one of Example 1 -7, wherein the first PC-CAR binding molecular model comprises a computer structure model or crystal structure model.

[0223] Example 9. The method of any one of Example 1-8, wherein the PC-CAR residues that facilitate binding to a second target peptide are determined based on binding residues within a predefined distance threshold.

[0224] Example 10. The method of Example 9, wherein the predefined distance threshold is between 0-6 A.

[0225] Example 11. The method of Example 9, wherein the predefined distance threshold after step c is 5-7 A.

[0226] Example 12. The method of Example 9, wherein the predefined distance threshold after step f is 3-5 A.

[0227] Example 13. The method of any one of Example 2-12, wherein generating the first or second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules comprises performing a relaxation operation or modeling each PC-CAR binding molecule in a lower-energy state.

[0228] Example 14. The method of any one of Example 1-13, wherein the first PC-CAR binding molecular model is selected from a plurality of sequences that includes most frequent sequences and best scoring (e.g., lowest or highest) sequences.

[0229] Example 15. The method of any one of Example 1-14, wherein the plurality of candidate modified PC-CAR binding molecules are used for in vitro testing.

[0230] Example 16. The method of any one of Example 1-15, wherein the first target peptide comprises a PHOX2B epitope.

[0231] Example 17. The method of Example 16, wherein the PHOX2B epitope comprises SEQ ID NO: 38.

[0232] Example 18. The method of Example 16, wherein the first PC-CAR comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, and SEQ ID NO: 3, respectively.Attorney Docket No. 11820-034W01YAR01-11PRO

[0233] Example 20. The method of Example 16, wherein the first PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, and SEQ ID NO: 22, respectively.

[0234] Example 21. The method of any one of Example 1-20, wherein the first peptide comprises a CHRNA3 epitope.

[0235] Example 22. The method of Example 21, wherein the CHRNA3 epitope comprises SEQ ID NO: 39.

[0236] Example 23. A method of creating an HLA matched PC-CAR for a subject comprising performing the method of any one of Example 1 -22, wherein the first MHC is HLA-matched to the HLA of the subject.

[0237] Example 24. A PC-CAR specific for a CHRNA3 epitope comprising a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively;SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.

[0238] Example 25. The PC-CAR of Example 24, wherein the PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively.

[0239] Example 26. The PC-CAR of Example 24 or 25, wherein the PC-CAR comprise the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.

[0240] Example 27. A method of treating a cancer in a subject comprising administering to the subject the PC-CAR immune cell of any one of Example 24-26.Attorney Docket No. 11820-034W01 YAR01-11PRO

[0241] Example 28. A method of treating a cancer in a subject comprising administering to the subject a peptide centric (PC) chimeric antigen receptor (CAR) (PC-CAR) immune cell comprising a CAR specific for a CHRNA3 peptide epitope to the subject.

[0242] Example 29. The method of Example 28, wherein the CHRNA3 peptide epitope is set forth in SEQ ID NO: 39.

[0243] Example 30. The method of Example 28 or 29, wherein the PC-CAR comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.

[0244] Example 31. The method of any one of Example 28-30, wherein the PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively.

[0245] Example 32. The method of any one of Example 28-31 , wherein the PC-CAR comprises the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.

[0246] Example 33. The method of any one of Example 27-32, wherein immune cell is a T cell, B cell, natural killer (NK) cell, NK T cell, or macrophage.

[0247] Example 34. The method of any one of Example 27-33, wherein the cancer comprises a neuroblastoma / glioblastoma.

[0248] Example 35. A system comprising: at least one processor; and a memory having instructions thereon, wherein the instructions when executed by the processor, cause the at least one processor to: a) retrieve a first PC-CAR binding molecular model for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule; b)Attorney Docket No. 11820-034W01YAR01-11PRO determine PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC-CAR molecules; c) iteratively model on- target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule; d) generate a relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules that bound to the second target peptide in step c) to increase molecular complex structural stability of the modified PC- CAR binding molecules; e) analyze binding of the generated relaxed structure models to identify the best on-target binders from step d); f) iteratively model off-target binding of the best on-target binders from the plurality of modified PC-CAR binding molecules of step e) to the first target peptide in the context of the first MHC molecule; g) identify, based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step f), wherein the candidate modified PC-CAR binding molecules bind the second target peptide in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule, and exhibits affinity and specificity for the second peptide target.

[0249] Example 36. A a method for designing PC CARs, the method comprising: selecting a known binder structure; identifying peptide binding residues within a defined distance score threshold; mutating selected residues using Al-based protein design tools; modeling mutated binders for target peptide binding and off-target exclusion; iteratively refining binders based on computational scoring and structural relaxation; and selecting binders with specificity to the target peptide-MHC complex for in vitro validation.

[0250] Example 37. A non- transitory computer readable medium comprising a memory having instructions stored thereon to cause a processor to perform any of the method of examples 1-34, the system of claim 35, or the method of Example 36.SEQUENCESSEQ ID NO: 1 amino acid sequence of PC-CAR CDRL1SLGNKYSEQ ID NO: 2 amino acid sequence of PC-CAR CDRL2QDSSEQ ID NO: 3 amino acid sequence of 10LH CAR CDRL3Attorney Docket No. 11820-034W01YAR01-11PROQAWDSSRGYTVVSEQ ID NO: 4 amino acid sequence of 02_26 CAR CDRL3QARDPSRGYTVVSEQ ID NO: 5 amino acid sequence of 19_9 CAR CDRL3QATDFSNGLNVVSEQ ID NO: 6 amino acid sequence of 4_8 CAR CDRL3QARDPAAGLNVVSEQ ID NO: 7 amino acid sequence of 17_3 CAR CDRL3QATDFANGLNVVSEQ ID NO: 8 amino acid sequence of 13_9 CAR CDRL3QARDPASGLNVVSEQ ID NO: 9 amino acid sequence of 12_3 CAR CDRL3QAQDFANGYNVVSEQ ID NO: 10 amino acid sequence of 14_1 CAR CDRL3QATDPAAGYNVVSEQ ID NO: 11 amino acid sequence of 9_1CAR CDRL3 and 1_5 CAR CDRL3QARDFANGLNVVSEQ ID NO: 12 amino acid sequence of 10_4 CAR CDRL3QARDPANGLNVVSEQ ID NO: 13 amino acid sequence of 10_2 CAR CDRL3QATDPANGLNVVSEQ ID NO: 14 amino acid sequence of 10_3 CAR CDRL3QALDFSNGLNVVAttorney Docket No. 11820-034W01YAR01-11PROSEQ ID NO: 15 amino acid sequence of 6_2 CAR CDRL3QATDPAAGLNVVSEQ ID NO: 16 amino acid sequence of PC-CAR CDRH1GFTFDSYASEQ ID NO: 17 amino acid sequence of 10LH CDRH2 and 02_26 CDRH2ISGYGGSTSEQ ID NO: 18 amino acid sequence of 19_9 CDRH2 and 10_4 CDRH2ISGKGDSTSEQ ID NO: 19 amino acid sequence of 4_8 CDRH2, 13_9 CDRH2, 14_1 CDRH2, and1_5 CDRH2, and 6_2 CDRH2ISGRGDSTSEQ ID NO: 20 amino acid sequence of 17_3 CDRH2, 12_3 CDRH2, 10_2 CDRH2, and10_3 CDRH2ISGDGSSTSEQ ID NO: 21 amino acid sequence of 9_1 CDRH2ISGKGDATSEQ ID NO: 22 amino acid sequence of 10LH CDRH3AKYTYFLDAFDISEQ ID NO: 23 amino acid sequence of PC-CAR CDRH3AKYTYFLQAFDISEQ ID NO: 24 amino acid sequence for PC-CAR 10LHQSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQAWDSSRGYTVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAttorney Docket No. 11820-034W01YAR01-11PROAPGKGLEWVSAISGYGGSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLDAFDIWGQGTMVTVSSSEQ ID NO: 25 amino acid sequence for PC-CAR 02_26QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQARDPSRGYTVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGYGGSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 26 amino acid sequence for PC-CAR 19_9QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQATDFSNGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGKGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYC AKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 27 amino acid sequence for PC-CAR 4_8QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQARDPAAGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGRGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYY CAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 28 amino acid sequence for PC-CAR 17_3QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQATDFANGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQ APGKGLEWVS AIS GDGS ST YY ADS VKGRFTISRDNS KNTLYLQMNSLRAEDT A V Y Y CAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 29 amino acid sequence for PC-CAR 13_9QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLT1SGTQAMDEADYYCQARDPASGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGRGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYY CAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 30 amino acid sequence for PC-CAR 12_3QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQAQDFANGYNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQ APGKGLEWVS AIS GDGS ST YY ADS VKGRFTISRDNS KNTLYLQMNSLRAEDT AV Y Y CAKYTYFLQAFDIWGQGTMVTVSSAttorney Docket No. 11820-034W01YAR01-11PROSEQ ID NO: 31 amino acid sequence for PC-CAR 14_1QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQATDPAAGYNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGRGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 32 amino acid sequence for PC-CAR 9_1QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQARDFANGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVS AIS GKGD ATYYADS VKGRFTISRDNS KNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 33 amino acid sequence for PC-CAR 10_4QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQARDPANGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGKGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 34 amino acid sequence for PC-CAR 1_5QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQARDFANGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGRGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 35 amino acid sequence for PC-CAR 10_2QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQATDPANGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGDGSSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 36 amino acid sequence for PC-CAR 10_3QSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQALDFSNGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGDGSSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 37 amino acid sequence for PC-CAR 6 2Attorney Docket No. 11820-034W01YAR01-11PROQSVLTQPPSVSVSPGQTASITCSGDSLGNKYACWYQQKPGQSPVLVIYQDSKRPSGIPERFSGSNSGNTATLTISGTQAMDEADYYCQATDPAAGLNVVFGTGTKVTVSSQTGGSGGGGSGGGGSGGGGSEVQLLESGGGLVQPGGSLRLSCAASGFTFDSYAMSWVRQAPGKGLEWVSAISGRGDSTYYADSVKGRFTISRDNSKNTLYLQMNSLRAEDTAVYYCAKYTYFLQAFDIWGQGTMVTVSSSEQ ID NO: 38 PHOX2B peptideQYNPIRTTFSEQ ID NO: 39 CHRNA3peptideIYPDITYSLSEQ ID NO: 40 motifX1X2GLN where Xi can be S or A and X2 can be N or A

Claims

Attorney Docket No. 11820-034W01YAR01-11PROWhat is claimed:

1. A computer-implemented method for generating a peptide centric (PC) chimeric antigen receptor (CAR) (PC-CAR) binding molecule, the method comprising: a) retrieving, by at least one processor, a first PC-CAR binding molecular model for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule; b) determining, by the at least one processor, PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC- CAR molecules; c) iteratively modeling, by the at least one processor, on-target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule; d) generating, by the at least one processor, a relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules that bound to the second target peptide in step c) to increase molecular complex structural stability of the modified PC-CAR binding molecules; e) analyzing, by the at least one processor, binding of the generated relaxed structure models to identify the best on-target binders from step d); f) iteratively modeling, by the at least one processor, off-target binding of the best on- target binders from the plurality of modified PC-CAR binding molecules of step e) to the first target peptide in the context of the first MHC molecule; g) identifying, by the at least one processor and based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step f), wherein the candidate modified PC-CAR binding molecules bind the second target peptide in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule, and exhibits affinity and specificity for the second peptide target.

2. The method of claim 1 , further comprising: subsequent to iteratively modeling off-target binding, generating a second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules to increase stability of the modified PC-CAR binding molecules that did not bind to the first target peptide in step f).Attorney Docket No. 11820-034W01YAR01-11PRO3. The method of claim 1 or 2, further comprising: aligning, by the at least one processor, a known PC-CAR structure model of known specificity with a target to generate the first PC-CAR binding molecular model.

4. The method of claim 3, wherein aligning the known PC-CAR structure model to generate the first PC-CAR binding molecular model comprises: identifying, by the at least one processor, peptide-binding residues within 6 Angstroms of the known PC-CAR structure model, modeling, by the at least one processor, a new target pMHC molecule separately without the known PC-CAR structure model, modeling, by the at least one processor, the first PC-CAR binding molecular model or crystal structure, and superimposing, by the at least one processor, the PC-CAR-pMHC structure of the known PC-CAR structure model onto the modeled pMHC molecule, removing, by the at least one processor, the known pMHC from the new target pMHC molecule (PC-CAR superimposed on CHRNA3-pMHC), wherein the new target pHMC is used as an input to generate the plurality of modified PC-CAR molecules.

5. The method of any one of claims 1-4, wherein analyzing binding of the generated relaxed structure models comprises: determining a specificity score for each molecule and selecting the plurality of candidate modified PC-CAR binding molecules to the second target peptide based on the determined specificity scores.

6. The method of claim 5, wherein the specificity score for each molecule is determined based on possible bonds (e.g., interactions between a respective PC-CAR and pMHC molecule) within the respective model that are between 0-4 Angstroms (A).

7. The method of any one of claims 1-6, wherein generating the plurality of modified PC-CAR binding molecules comprises using a deep learning model to predict a three- dimensional protein structures from a sequence corresponding with each molecule.Attorney Docket No. 11820-034W01YAR01-11PRO8. The method of any one of claims 1-7, wherein the first PC-CAR binding molecular model comprises a computer structure model or crystal structure model.

9. The method of any one of claims 1-8, wherein the PC-CAR residues that facilitate binding to a second target peptide are determined based on binding residues within a predefined distance threshold.

10. The method of claim 9, wherein the predefined distance threshold is between 0-6 A.

11. The method of claim 9, wherein the predefined distance threshold after step c is 5-7A.

12. The method of claim 9, wherein the predefined distance threshold after step f is 3-5 A.

13. The method of any one of claims 2-12, wherein generating the first or second relaxed structure model for one or more of the plurality of modified PC-CAR binding molecules comprises performing a relaxation operation or modeling each PC-CAR binding molecule in a lower-energy state.

14. The method of any one of claims 1-13, wherein the first PC-CAR binding molecular model is selected from a plurality of sequences that includes most frequent sequences and best scoring (e.g., lowest or highest) sequences.

15. The method of any one of claims 1-14, wherein the plurality of candidate modified PC-CAR binding molecules are used for in vitro testing.

16. The method of any one of claims 1-15, wherein the first target peptide comprises a PHOX2B epitope.

17. The method of claim 16, wherein the PHOX2B epitope comprises SEQ ID NO: 38.

18. The method of claim 16, wherein the first PC-CAR comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, and SEQ ID NO: 3, respectively.Attorney Docket No. 11820-034W01YAR01-11PRO19. The method of claim 16, wherein the first PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, and SEQ ID NO: 22, respectively.

20. The method of any one of claims 1-19, wherein the first peptide comprises a CHRNA3 epitope.

21. The method of claim 20, wherein the CHRNA3 epitope comprises SEQ ID NO: 39.

22. A method of creating an HLA matched PC-CAR for a subject comprising performing the method of any one of claims 1-21, wherein the first MHC is HLA-matched to the HLA of the subject.

23. A PC-CAR specific for a CHRNA3 epitope comprising a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.

24. The PC-CAR of claim 23, wherein the PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively.

25. The PC-CAR of claim 23 or 24, wherein the PC-CAR comprise the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28,Attorney Docket No. 11820-034W01YAR01-11PROSEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.

26. A method of treating a cancer in a subject comprising administering to the subject the PC-CAR immune cell of any one of claims 23-25.

27. A method of treating a cancer in a subject comprising administering to the subject a peptide centric (PC) chimeric antigen receptor (CAR) (PC-CAR) immune cell comprising a CAR specific for a CHRNA3 peptide epitope to the subject.

28. The method of claim 27, wherein the CHRNA3 peptide epitope is set forth in SEQ ID NO: 39.

29. The method of claim 27 or 28, wherein the PC-CAR comprises a light chain complementarity determining region (CDR) 1 (CDRL1), CDRL2, and CDRL3 as set forth in SEQ ID NO: 1 , SEQ ID NO: 2, SEQ ID NO: 4, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 5, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 6, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 7, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 8, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 9, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 10, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 11, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 12, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 13, respectively; SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 14, respectively; and SEQ ID NO: 1, SEQ ID NO: 2, SEQ ID NO: 15, respectively.

30. The method of any one of claims 28-29, wherein the PC-CAR comprises a heavy chain complementarity determining region (CDR) 1 (CDRH1), CDRH2, and CDRH3 as set forth in SEQ ID NO: 16, SEQ ID NO: 17, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 18, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 19, SEQ ID NO: 23, respectively; SEQ ID NO: 16, SEQ ID NO: 20, SEQ ID NO: 23, respectively; and SEQ ID NO: 16, SEQ ID NO: 21, SEQ ID NO: 23, respectively.

31. The method of any one of claims 28-30, wherein the PC-CAR comprises the amino acid sequence as set forth in SEQ ID NO: 25, SEQ ID NO: 26, SEQ ID NO: 27, SEQ ID NO: 28, SEQ ID NO: 29, SEQ ID NO: 30, SEQ ID NO: 31, SEQ ID NO: 32, SEQ ID NO: 33, SEQ ID NO: 34, SEQ ID NO: 35, SEQ ID NO: 36, or SEQ ID NO: 37.Attorney Docket No. 11820-034W01YAR01-11PRO32. The method of any one of claims 27-31, wherein immune cell is a T cell, B cell, natural killer (NK) cell, NK T cell, or macrophage.

33. The method of any one of claims 27-32, wherein the cancer comprises a neuroblastoma / glioblastoma.

34. A system comprising: at least one processor; and a memory having instructions thereon, wherein the instructions when executed by the processor, cause the at least one processor to: a) retrieve a first PC-CAR binding molecular model for a first target peptide in the context of a first Major Histocompatibility Complex (MHC) molecule; b) determine PC-CAR residues that facilitate binding to a second target peptide and modifying said residues to generate a plurality of modified PC-CAR molecules; c) iteratively model on-target binding of the plurality of modified PC-CAR binding molecules to the second target peptide in the context of the first MHC molecule; d) generate a relaxed structure model for one or more of the plurality of modified PC- CAR binding molecules that bound to the second target peptide in step c) to increase molecular complex structural stability of the modified PC-CAR binding molecules; e) analyze binding of the generated relaxed structure models to identify the best on- target binders from step d); f) iteratively model off-target binding of the best on-target binders from the plurality of modified PC-CAR binding molecules of step e) to the first target peptide in the context of the first MHC molecule; g) identify, based at least in part on the off-target binding, a plurality of candidate modified PC-CAR binding molecules to the second target that did not bind to the first target peptide in the context of the first MHC molecule from step f), wherein the candidate modified PC-CAR binding molecules bind the second target peptide in the context of the MHC molecule, but not the first target peptide in the context of the MHC molecule, and exhibits affinity and specificity for the second peptide target.

35. A method for designing peptide-centric chimeric antigen receptors (PC CARs), comprising: selecting a known binder structure;Attorney Docket No. 11820-034W01YAR01-11PRO identifying peptide binding residues within a defined distance score threshold; mutating selected residues using Al-based protein design tools; modeling mutated binders for target peptide binding and off-target exclusion; iteratively refining binders based on computational scoring and structural relaxation; and selecting binders with specificity to the target peptide-MHC complex for in vitro validation.

36. A non-transitory computer readable medium comprising a memory having instructions stored thereon to cause a processor to perform any of the method of claims 1-33, the system of claim 34, or the method of claim 35.

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