# US 2019/0376115 A1 · Activity sensor design

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- Number: US 2019/0376115 A1
- Document ID: US20190376115A1
- Status: Published application
- Kind: A1
- Application number: 16/434,785
- Filed: 2019-06-07
- Published: 2019-12-12
- Earliest claimed: 2018-06-08
- Assignees: Glympse Bio, Inc.
- Applicants: Glympse Bio, Inc.
- Inventors: Sangeeta Bhatia; Gabriel Kwong; Eric Huang; Sirshendu Roopom Banerjee; Andrew Warren; Sophie Cazanave
- Web page: https://patentgrep.com/patent/US20190376115A1

## CPC

- C12Q 1/37: involving peptidase or proteinase
- C12Q 1/6886: for cancer (immunoassay for cancer G01N33/575)
- G16B 20/00: ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
- G16B 25/10: Gene or protein expression profiling; Expression-ratio estimation or normalisation
- 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
- G16B 40/20: Supervised data analysis
- G16B 50/00: ICT programming tools or database systems specially adapted for bioinformatics
- C12Q 1/6883: for diseases caused by alterations of genetic material
- C12Q 2537/165: Mathematical modelling, e.g. logarithm, ratio
- 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
- G01N 2333/948: acting on peptide bonds (3.4)
- 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
- G16B: BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G01N: INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES (measuring or testing apparatus or processes other than immunoassay, involving enzymes or microorganisms C12M, C12Q)

## Abstract

Methods of the disclosure provide an analytical pipeline for mapping activity in a disease-specific manner. Any of a variety of diseases or medical conditions may be mapped using the analytical pipeline. In preferred embodiments, the pipeline uses expression data (e.g., from RNA-Seq) to identify proteases that are active in disease tissue and subject to differential expression relative to normal tissue. A machine learning classifier selects a subset of the proteases that identify the disease with a threshold sensitivity and specificity, in which the subset is small enough that a corresponding set of protease substrates may be assembled into a nanoparticle activity sensor that, when administered to a patient, are cleaved in the presence of disease tissue to release detectable analytes signifying presence of the disease.

## Claims

### Claim 1

A method for designing an activity sensor, the method comprising:
analyzing gene expression of tissue in a disease state to identify enzymes expressed in the tissue under a specific physiological state or health condition;
selecting a subset of the enzymes that correlates with the physiological state or health condition to a predefined performance metric; and
creating an activity sensor comprising cleavable reporters that are released as analytes in vivo upon exposure to the subset of enzymes.

### Claim 2 (depends on 1)

The method of claim 1, wherein the enzymes are proteases.

### Claim 3 (depends on 2)

The method of claim 2, wherein when the activity sensor is administered to a subject, proteases cleave the activity sensor in the tissue under the physiological state to thereby release the analyte for collection in a bodily sample.

### Claim 4 (depends on 1)

The method of claim 1, wherein the subset of enzymes is selected by a machine learning classification algorithm that classifies subsets by whether they meet the performance metric, wherein the performance metric includes a defined threshold sensitivity or specificity.

### Claim 5 (depends on 4)

The method of claim 4, wherein the physiological state is a disease, and the classification algorithm outputs a heat map that gives an expression level of each enzyme for each of a plurality of substrates and/or stages of a disease condition.

### Claim 6 (depends on 5)

The method of claim 5, wherein the classification algorithm outputs a set of proteases predicted to classify the disease condition with sensitivity and specificity both greater than 0.90.

### Claim 7 (depends on 6)

The method of claim 6, further comprising selecting the cleavage targets as substrates for the proteases output by the classification algorithm.

### Claim 8 (depends on 1)

The method of claim 1, wherein analyzing the gene expression includes sequencing RNA from disease tissue samples to produce transcript sequences.

### Claim 9 (depends on 8)

The method of claim 8, further comprising comparing the transcript sequences, or translations thereof, to a gene or protein database to identify candidate proteases.

### Claim 10 (depends on 8)

The method of claim 8, wherein the samples comprise formalin-fixed slices from tumors.

### Claim 11 (depends on 1)

The method of claim 1, wherein the enzymes are proteases and creating the nanoparticles comprises linking a plurality of peptides to a polymer scaffold.

### Claim 12 (depends on 11)

The method of claim 11, wherein each of the peptides comprises a detectable analyte linked to the scaffold via a cleavage target of one of the signature proteases.

### Claim 13 (depends on 12)

The method of claim 12, wherein the polymer scaffold comprises a multi-arm PEG) structure.

### Claim 14 (depends on 1)

The method of claim 1, wherein administering the activity sensor to a subject yields a bodily sample from the subject that includes the analytes, indicating disease activity before other disease symptoms are exhibited by the subject.

### Claim 15 (depends on 1)

The method of claim 1, wherein the disease is nonalcoholic steatohepatitis (NASH), the enzymes comprise FAP, MMP2, ADAMTS2, FURIN, MMP14, GZMB, PRSS8, MMP8, ADAM12, CTSS, CTSA, CTSZ, CASP1, ADAMTS12, CTSD, CTSW, MMP11, MMP12, GZMA, MMP23B, MMP7, ST14, MMP9, MMP15, ADAMDEC1, ADAMTS1, GZMK, KLK11, MMP19, PAPPA, CTSE, PCSK5, and PLAU, and the subset of enzymes comprises a plurality of FAP, MMP2, ADAMTS2, FURIN, MMP14, MMP8, MMP11, CTSD, CTSA, MMP12, and MMP9.

### Claim 16 (depends on 1)

The method of claim 1, wherein the disease comprises lung cancer, and the subset of enzymes includes MMP13, MMP11, MMP12, MMP1, KLK6, and MMP3.

### Claim 17 (depends on 1)

The method of claim 1, wherein the disease comprises one selected from the group consisting of a cancer; osteoarthritis; and infection by a pathogen.

### Claim 18 (depends on 1)

The method of claim 1, wherein the enzymes are proteases and the method includes determining subsets of the proteases specific to disease stages, wherein administering the activity sensor to a subject yields a bodily sample with analytes indicative of a stage of the disease.

### Claim 19

A method for designing activity sensors, the method comprising:
analyzing gene expression data characteristic of a disease condition to identify candidate genes differentially expressed under the disease condition;
identifying a set of signature genes that classify the disease condition; and
creating a composition that, when administered to the subject, releases one or more detectable reporters in the presence of nucleic acid sequences of the signature genes.

### Claim 20 (depends on 19)

The method of claim 19, wherein the composition includes a Cas protein that exhibits collateral cleavage in the presence of the nucleic acid sequences of the signature genes.

### Claim 21 (depends on 20)

The method of claim 20, wherein the composition includes reporters that include quenched fluorophores that fluoresce in response to collateral cleavage by the Cas protein.

### Claim 22 (depends on 20)

The method of claim 20, wherein the composition includes a plurality of the Cas proteins, and the composition provides a fluorescent signature that classifies the disease based on exposure of the Cas proteins to the nucleic acid sequences of the signature genes.