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Viral delivery of neoantigens

An antigen, adenovirus technology, applied in the direction of viruses, cancer antigen components, viruses/phages, etc., can solve the problems of missing candidate neoantigen somatic mutations, inefficient use of vaccines or autoimmune risks.

Pending Publication Date: 2019-12-06
GRITSTONE BIO INC
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  • Abstract
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Problems solved by technology

[0010] Furthermore, previous approaches have only used cis-acting mutations to generate candidate neoantigens and have largely neglected to consider other sources of neo-ORFs, including mutations in splicing factors that occur in multiple tumor types and lead to aberrant splicing of many genes 13 , and mutations that create or remove protease cleavage sites
[0011] Finally, standard approaches to tumor genome and transcriptome profiling may miss somatic mutations that generate candidate neoantigens due to suboptimal conditions in library construction, exome and transcriptome capture, sequencing, or data analysis
Likewise, standard tumor profiling methods may inadvertently promote sequence artifacts or germline polymorphisms as neoantigens, leading to inefficient use of vaccines or risk of autoimmunity, respectively
[0012] In addition to the challenges of current neoantigen prediction methods, there are certain challenges with the available vector systems for neoantigen delivery in humans, many of which are of human origin

Method used

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  • Viral delivery of neoantigens
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Examples

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example 1

[0657] X.C.1. Example 1: Maximum value of independent allele model

[0658] In one embodiment, the training module 316 makes the peptide p associated with a set of multiple alleles H k Estimated probability of presentation u k With the presentation probability u of each MHC allele h in the set H determined based on cells expressing a single allele k h∈H The change in is modeled as described above in conjunction with equations (2)-(11). Specifically, the possibility of presentation u k Can be u k h ∈ H Any function. In one embodiment, as shown in equation (12), the function is the maximum function, and the probability u k It can be determined as the maximum presentation probability of each MHC allele h in the set H.

[0659]

[0660] X.C.2. Example 2.1: Function-of-Sums model of sum

[0661] In one embodiment, the training module 316 makes the peptide p k Estimated probability of presentation u k Modeling:

[0662]

[0663] Where element a h k For peptide sequence p k Multiple assoc...

example 22

[0673] X.C.3. Example 2.2: A functional model using the sum of allelic non-interacting variables In one embodiment, the training module 316 incorporates the allelic non-interacting variables and makes the peptide p by the following formula k Estimated probability of presentation u k Modeling:

[0674]

[0675] Where w k Indicates the encoded related peptide p k The allelic non-interacting variable. Specifically, the parameter set θ of each MHC allele h h And related allelic non-interacting variable parameter set θ w The value of can be determined by h And θ w The loss function of i is minimized to determine each instance of the subset S of the training data 170 generated by cells expressing a single MHC allele and / or cells expressing multiple MHC alleles. Correlation function g w It can be the correlation function g introduced in section X.B.3 above w In any form.

[0676] Therefore, according to equation (14), the peptide sequence p k The probability of presentation that will be p...

example 31

[0687] X.C.4. Example 3.1: Model using implicit independent allele likelihood

[0688] In another embodiment, the training module 316 makes the peptide p k Estimated probability of presentation u k Modeling:

[0689]

[0690] Where element a h k For peptide sequence p k The associated multiple MHC alleles h∈H are 1, Is the implicit independent allele presentation possibility of MHC allele h, vector v is element v h Corresponds to The vector of s(·) is a function of the mapping element v, and r(·) is a clipping function, which reduces the input value to a given range. As described in more detail below, s(·) may be a summation function or a second-order function, but it should be understood that in other embodiments, s(·) may be any function, such as a maximum function. The value of the parameter set θ related to the possibility of implicit independent alleles can be determined by minimizing the loss function related to θ, where i is determined by cells expressing a single MHC alle...

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Abstract

Disclosed herein are chimpanzee adenoviral vectors that include neo-antigen encoding nucleic acid sequences derived from a tumor of a subject. Also disclosed are nucleotides, cells, and methods associated with the vectors including their use as vaccines.

Description

[0001] Cross references to related applications [0002] This application requires U.S. Provisional Application No. 62 / 425,996 filed on November 23, 2016; U.S. Provisional Application No. 62 / 435,266 filed on December 16, 2016; U.S. Provisional Application No. 62 / 435,266 filed on May 8, 2017 Application No. 62 / 503,196; and U.S. Provisional Application No. 62 / 523,212 filed on June 21, 2017, each of which is incorporated herein by reference in its entirety. [0003] Sequence Listing [0004] This application contains a sequence listing, which has been submitted by EFS-Web and is incorporated herein by reference in its entirety. The ASCII copy created in XX, 20XX is named XXXXXUS_sequencelisting.txt, and the size is X,XXX,XXX bytes. Background technique [0005] Therapeutic vaccines based on tumor-specific neoantigens have great prospects as the next generation of personalized cancer immunotherapy. 1-3 Considering that the possibility of new antigen production is relatively greater, canc...

Claims

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Application Information

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IPC IPC(8): A61K31/404A61K31/7088A61K39/00A61K39/395A61K45/06C12N7/00
CPCA61K39/0011A61K45/06A61K31/7088A61K31/713C12N7/00A61K2039/55544A61K2039/57A61K2039/585C12N2710/10043C12N2710/10071C12N2710/16134C12N2710/16234C12N2710/14034A61K39/001188A61K39/001191A61P35/00A61P35/02A61P37/04A61K2300/00C12N15/86A61K35/761A61K39/39541A61K2039/505A61K2039/5256C07K14/70539C07K16/2818C12N2710/10034
Inventor W·布莱尔B·布里克-沙利文J·巴斯比A·德里蒂L·吉特林G·格罗腾布雷格K·朱斯C·D·斯卡伦R·耶冷斯凯
Owner GRITSTONE BIO INC
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