# US 10,501,801 B2 · Identification of tumor-protective epitopes for the treatment of cancers

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- Number: US 10,501,801 B2
- Document ID: US10501801B2
- Status: Granted
- Kind: B2
- Application number: 14/431,093
- Filed: 2013-09-27
- Published: 2015-09-10
- Granted: 2019-12-10
- Earliest claimed: 2012-09-28
- Assignees: University of Connecticut
- Applicants: The University of Connecticut
- Inventors: Pramod K. Srivastava; Ion Mandoiu; Fei Duan
- Web page: https://patentgrep.com/patent/US10501801B2

## CPC

- C12Q 1/6886: for cancer (immunoassay for cancer G01N33/575)
- A61K 39/0011: {Cancer antigens}
- A61P 35/00: Antineoplastic agents
- A61P 37/02: Immunomodulators
- A61P 37/04: Immunostimulants
- A61P 43/00: Drugs for specific purposes, not provided for in groups A61P1/00-A61P41/00
- G16H 50/20: for computer-aided diagnosis, e.g. based on medical expert systems
- A61K 2039/55561: {CpG containing adjuvants; Oligonucleotide containing adjuvants}
- C12Q 2600/106: Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
- C12Q 2600/112: Disease subtyping, staging or classification
- C12Q 2600/158: Expression markers
- C12Q: MEASURING OR TESTING PROCESSES INVOLVING ENZYMES, NUCLEIC ACIDS OR MICROORGANISMS (immunoassay G01N33/53); COMPOSITIONS OR TEST PAPERS THEREFOR; PROCESSES OF PREPARING SUCH COMPOSITIONS; CONDITION-RESPONSIVE CONTROL IN MICROBIOLOGICAL OR ENZYMOLOGICAL PROCESSES
- A61K: PREPARATIONS FOR MEDICAL, DENTAL OR TOILETRY PURPOSES (devices or methods specially adapted for bringing pharmaceutical products into particular physical or administering forms A61J3/00; chemical aspects of, or use of materials for deodorisation of air, for disinfection or sterilisation, or for bandages, dressings, absorbent pads or surgical articles A61L; soap compositions C11D)
- A61P: SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- G16H: HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA

## Abstract

Described herein are methods of identifying tumor-specific epitopes from the cancer tissue DNA of cancer patients using both DNA sequencing and bioinformatics techniques. The identification of tumor-specific epitopes provides pharmaceutical compositions with a limited number of tumor-specific peptides suitable for personalized genomics-driven immunotherapy of human cancer. Specifically disclosed herein is a novel index called the Differential Agretopic Index (DAI) for the epitope which allows prediction of whether immunization with a particular epitope will be protective against the tumor. Pharmaceutical compositions and methods of administration are also included.

## Claims

### Claim 1

A method of identifying tumor epitopes in a cancer patient, comprising
sequencing at least a portion of the cancer patient's RNA or DNA in both a healthy tissue and a cancer tissue, to produce a healthy tissue RNA or DNA sequence and a cancer tissue RNA or DNA sequence,
comparing the healthy tissue RNA or DNA sequence and the cancer tissue RNA or DNA sequence and identifying differences between the healthy tissue RNA or DNA sequence and the cancer tissue RNA or DNA sequence to produce a difference DNA marker set,
analyzing the difference DNA marker set to produce a tumor-specific epitope set, wherein the tumor-specific epitope set comprises one or more tumor-specific epitopes, and wherein analyzing the difference DNA marker set to produce a tumor-specific epitope set is independent of whether one or more tumor-specific epitopes are related to cancer-causing pathways,
calculating a numerical value called the Differential Agretopic Index for each tumor-specific epitope in the tumor-specific epitope set by subtracting a numerical score for a non-mutated amino acid sequence of the healthy tissue corresponding to the mutated amino acid sequence of the tumor-specific epitope from a numerical score for the tumor-specific epitope, wherein the numerical scores are calculated using an epitope predictive algorithm that predicts the binding of epitope peptides to MHC molecules,
ranking the tumor-specific epitope set by the Differential Agretopic Index for each epitope in the set to identify a subset of 10 to 50 top-ranked tumor-specific epitopes,
producing a pharmaceutical composition comprising a pharmaceutically acceptable carrier and one or more peptides comprising one or more tumor-specific epitopes selected from the subset of 10 to 50 top-ranked tumor-specific epitopes, or one or more polypeptides containing one or more tumor-specific epitopes selected from the subset 10 to 50 top-ranked tumor-specific epitopes, or one or more polynucleotides encoding one or more peptides comprising one or more tumor-specific epitopes selected from the subset of 10 to 50 top-ranked tumor specific epitopes, and wherein a non-mutated amino acid sequence of the healthy tissue corresponding to at least one of the one or more tumor-specific epitopes selected from the subset of 10 to 50 top-ranked tumor-specific epitopes has a negative numerical score, and
optionally administering the pharmaceutical composition to the cancer patient.

### Claim 2 (depends on 1)

The method of claim 1, wherein the sequencing is transcriptome sequencing.

### Claim 3 (depends on 1)

The method of claim 1, wherein the sequencing is high-throughput sequencing.

### Claim 4 (depends on 1)

The method of claim 1, wherein the pharmaceutical composition comprises one or more peptides comprising 1 to 100 tumor-specific epitopes from the tumor-specific epitope set, one or more polypeptides containing 1 to 100 tumor-specific epitopes from the tumor-specific epitope set, or one or more polynucleotides encoding 1 to 100 peptides comprising tumor-specific epitopes from the tumor-specific epitope set.

### Claim 5 (depends on 1)

The method of claim 1, wherein the pharmaceutical composition comprises one or more peptides comprising 3 to 20 tumor-specific epitopes from the tumor-specific epitope set, one or more polypeptides containing 3 to 20 tumor-specific epitopes from the tumor-specific set, or one or more polynucleotides encoding 3 to 20 tumor-specific peptides comprising tumor-specific epitopes from the tumor-specific epitope set.

### Claim 6 (depends on 1)

The method of claim 1, wherein the pharmaceutical composition further comprises an adjuvant.

### Claim 7 (depends on 6)

The method of claim 6, comprising administering the pharmaceutical composition to the cancer patient.

### Claim 8 (depends on 1)

The method of claim 1, wherein the pharmaceutical composition further comprises one or more immune-modulating agents.

### Claim 9 (depends on 7)

The method of claim 7, wherein the immune-modulating agent is a TLR ligand or an antibody.

### Claim 10 (depends on 1)

The method of claim 1, wherein the cancer patient is suffering from a solid cancer.

### Claim 11 (depends on 1)

The method of claim 1, wherein the epitope predictive algorithm predicts the binding of epitope peptides of MHC molecules using artificial neural networks and weight matrices.

### Claim 12 (depends on 11)

The method of claim 11, comprising administering the pharmaceutical composition to the cancer patient.

### Claim 13 (depends on 1)

The method of claim 1, comprising administering the pharmaceutical composition to the cancer patient.

### Claim 14 (depends on 13)

The method of claim 13, further comprising treating the cancer patient with radiation therapy, chemotherapy, surgery, or a combination thereof.

### Claim 15 (depends on 13)

The method of claim 13, which further comprises mixing or pulsing the peptides, polypeptides, or polynucleotides with cells from the cancer patient, and wherein said administering further comprises administering the mixed or pulsed cells to the cancer patient.

### Claim 16 (depends on 1)

The method of claim 1, which comprises, prior to the step of calculating the numerical value called the Differential Agretopic Index, a step of calculating (i) the numerical score for each tumor-specific epitope within the tumor-specific epitope set, and (ii) the numerical score for each non-mutated amino acid sequence of the healthy tissue corresponding to the mutated amino acid sequence of the tumor-specific epitope within the tumor-specific epitope set.

### Claim 17 (depends on 1)

The method of claim 1, wherein the cancer patient is suffering from a liquid cancer.