# US 10,501,807 B2 · Cancer biomarkers

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- Number: US 10,501,807 B2
- Document ID: US10501807B2
- Status: Granted
- Kind: B2
- Application number: 15/919,394
- Filed: 2018-03-13
- Published: 2018-09-20
- Granted: 2019-12-10
- Earliest claimed: 2009-01-07
- Assignees: Myriad Genetics, Inc.
- Applicants: Myriad Genetics, Inc.
- Inventors: Steven Stone; Alexander Gutin; Susanne Wagner; Julia Reid
- Web page: https://patentgrep.com/patent/US10501807B2

## CPC

- C12Q 1/6886: for cancer (immunoassay for cancer G01N33/575)
- A61P 35/00: Antineoplastic agents
- G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B 20/10: Ploidy or copy number detection
- G16B 20/20: Allele or variant detection, e.g. single nucleotide polymorphism [SNP] detection
- G16B 40/30: Unsupervised data analysis
- C12Q 2600/106: Pharmacogenomics, i.e. genetic variability in individual responses to drugs and drug metabolism
- C12Q 2600/118: Prognosis of disease development
- C12Q 2600/158: Expression markers
- G16B 40/00: ICT specially adapted for biostatistics; ICT specially adapted for bioinformatics-related machine learning or data mining, e.g. knowledge discovery or pattern finding
- 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
- A61P: SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY

## Abstract

Biomarkers and methods using the biomarkers for the prediction of the recurrence risk of cancer in a patient are provided.

## Claims

### Claim 1

A method for treating prostate cancer in a patient, the method comprising:
(1) obtaining a sample comprising prostate cancer tumor tissue from said patient;
(2) determining the expression of a panel of genes comprising NUSAP1 and UBE2C in said sample comprising prostate cancer tumor tissue;
(3) prognosing said patient as having a decreased likelihood of prostate cancer progression when the expression of the genes NUSAP1 and UBE2C in said sample is lower than the expected expression of the genes NUSAP1 and UBE2C in prostate cancer tumor tissue from a reference population;
(4) administering to said patient active surveillance based on the prognosis for a period of time until symptoms develop or there are signs that the cancer growth is accelerating; and
(5) administering active treatment based on the developed symptoms or accelerated growth, wherein the active treatment is one or more of hormonal therapy, chemotherapy, radiation therapy and surgery.

### Claim 2 (depends on 1)

The method of claim 1, wherein said prognosing step further comprises incorporating into a statistical model the expression of the genes NUSAP1 and UBE2C in said sample.

### Claim 3 (depends on 1)

The method of claim 1, wherein said reference population comprises patients with similar clinical parameters.

### Claim 4 (depends on 3)

The method of claim 3, wherein said clinical parameters are Gleason score and tumor stage.

### Claim 5

A method for treating prostate cancer in a patient, the method comprising:
(1) obtaining a sample comprising prostate cancer tumor tissue from said patient;
(2) determining the expression of a panel of genes comprising NUSAPI and UBE2C in said sample comprising prostate cancer tumor tissue;
(3) prognosing said patient as having an increased likelihood of prostate cancer progression when the expression of the genes NUSAPI and UBE2C in said sample is higher than the expected expression of the genes NUSAPI and UBE2C in prostate cancer tumor tissue from a reference population; and
(4) administering to said patient one or more of hormonal therapy, chemotherapy, radiation therapy and surgery based on the prognosis.

### Claim 6 (depends on 5)

The method of claim 5, wherein said prognosing step further comprises incorporating into a statistical model the expression of the genes NUSAPI and UBE2C in said sample.

### Claim 7 (depends on 5)

The method of claim 5, wherein said reference population comprises patients with similar clinical parameters.

### Claim 8 (depends on 7)

The method of claim 7, wherein said clinical parameters are Gleason score and tumor stage.