IP Library Granted Patent US 11,842,797
Granted Patent B2
US 11,842,797 · App. 16/456,462 · Granted Dec 12, 2023

Systems and methods for predicting therapy efficacy from normalized biomarker scores

Inventors: Alexander Bagaev (Moscow, RU); Feliks Frenkel (Moscow, RU); Ravshan Ataullakhanov (Moscow, RU)
Assignee: BostonGene Corporation
G16B45/00C12Q1/6886G06F16/285G06F17/18G16B5/00G16B5/20G16B20/00G16B25/10G16B30/00G16B40/00G16B40/20G16B40/30G16B50/00G16B50/30G16H10/20G16H20/00G16H20/10G16H20/40G16H50/20G16H50/30G16H50/50G16H50/70G16H70/20C12Q2600/156C12Q2600/158
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Quick Facts
Patent No.
US 11,842,797
App. No.
16/456,462
Granted
Dec 12, 2023
Kind
B2
Abstract

Techniques for determining therapy scores for at least two of an anti-PD1 therapy, an anti-CTLA4 therapy, an IL-2 therapy, an IFN alpha therapy, an anti-cancer vaccine therapy, an anti-angiogenic therapy, and an anti-CD20 therapy. The techniques include determining, using sequencing data for the subject and information indicating distribution of biomarker values across one or more reference populations, a first set of normalized biomarker scores for a first set of biomarkers associated with a first therapy; and a second set of normalized biomarker scores for a second set of biomarkers associated with a second therapy; providing the first set of normalized biomarker scores as input to a statistical model to obtain a first therapy score for the first therapy; and providing the second set of normalized biomarker scores as input to the statistical model to obtain a second therapy score for the second therapy.

Claims (1544)

1. A system, comprising:

at least one computer hardware processor; and

at least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by the at least one computer hardware processor, cause the at least one computer hardware processor to perform:

obtaining sequencing data about at least one biological sample of a subject;

accessing, in at least one database, biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers, each biomarker in the reference subset of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies, the reference subset of the plurality of biomarkers including a first biomarker and a second biomarker, and the biomarker information including a first distribution of values for the first biomarker and a second distribution of values for the second biomarker;

determining, using both the sequencing data and the biomarker information, therapy scores for at least some therapies in the plurality of therapies, the determining comprising:

determining, using the sequencing data, a first set of un-normalized biomarker scores for a first set of biomarkers in the reference subset of the plurality of biomarkers, the first set of un-normalized biomarker scores including a first un-normalized biomarker score for the first biomarker and a second un-normalized biomarker score for the second biomarker, and the first set of biomarkers being associated with a first therapy in the at least some therapies;

determining a first set of normalized biomarker scores for the first set of biomarkers, the first set of normalized biomarker scores including a first normalized biomarker score for the first biomarker and a second normalized biomarker score for the second biomarker, and the determining comprising:

adjusting the first set of un-normalized biomarker scores for the first set of biomarkers to a common scale, the adjusting comprising adjusting the first and second un-normalized biomarker scores to the common scale using the first and second distributions of values respectively; and

determining a first therapy score for the first therapy using the first set of normalized biomarker scores,

wherein the first therapy is selected from the group consisting of: an anti-PD1 therapy, an anti-CTLA4 therapy, an IL-2 therapy, an IFN alpha therapy, an anti-cancer vaccine therapy, an anti-angiogenic therapy, and an anti-CD20 therapy, and

wherein the first set of biomarkers comprises at least three biomarkers selected from the group of biomarkers associated with the first therapy in Table 2; and

recommending, for the subject, at least one therapy of the at least some therapies based on the determined therapy scores,

wherein the Table 2 is:

Therapy

Biomarkers

aPD1

Affinity of

AXL

B2M LOF mutation

BRAF mutation

therapy

neontigens

BRCA2 mutation

Cancer gene panels

Cancer gene panels

CCL13

(CGPs) FM-CGP

(CGPs) HSL-CGP

CCL2

CCL7

CCL8

CD8+ cell density in

the tumor invasive

margin

CD8+ cell number

CDH1

CVEGFC

CX3CL1 expression

CXCR2 expression

Dendritic cell number

EGFR expression

Endothelial cells

Eosinophil number

ESRP1 expression

Fibroblasts

Granzyme B

expression

JAK1 LOF mutation

JAK2 LOF mutation

LDH level

Lymphocyte number

M1 macrophage

M1/M2 macrophage

MDSC %

MHC-II expression

number

ratio

MHC-II expression

Missmatch-repair

MITF expression

Mutational Burden

(HLA-DRA)

deficiency status

Pattern of distant

PD-L1 expression

PD-L1 expression on

PTEN loss

metastases

infiltrating leukocytes

Quantity of

ROR2

STAT1 expression

T reg cell %

neoantigen peptides

TAGLN

TCR clonality

TGFbeta level

TIL number in

tumor

TWIST2

VEGF level

VEGFA

aCTLA4

Absolute

CD8+ cell number

CXCL11 expression

CXCL9 expression

therapy

lymphocyte count

CXCR3 expression

Dendritic cell number

EOMES+ CD8+ cells

FOXP3+ cells

number

number

IDO expression

LDH expression

M1 macrophage

M1/M2 macrophage

number

ratio

MDSC %

Mutational Burden

NY-ESO-1 seropostive

PTEN loss

T reg cell %

TCR clonality

TGFbeta level

TIL number in

tumor

VEGF level

IL-2 therapy

Bone metastasis

concomitant regional

Leucocytes number

LNPEP expression

lymphadenopathy

C-reactive protein

Delta32 CCR5

BCAT2 expression

BDNFOS

level

Polymorphism

expression

IL-10 (−1082G -> A)

CAIX expression

LOC130576

CCR5 LOF

polymorphism

expression

mutation

ERCC1 (codon 118)

IFN-g (+874A -> T)

LOC399900

ATP6V0A2

polymorphism

polymorphism

expression

expression

Ki-67 expression

Alkaline phosphatase

ARHGAP10

CD56+ or CD57+

level

expression

cells number

Liver metastasis

CD83+ TIDC cells

CDNA FLJ37989

LDH level

number

expression

Fibronectin level

HLA-DQB1

GBF1 expression

amount of alveolar

expression

component

Albumin level

clear cell

FOXP3+ cells number

HLA-DQA1

histology

expression

granular features

MAP3K5 expression

MDSC number

Mediastinum

metastasis

MEF2A expression

MTUS1 expression

Neutrophil number

NK cell number

non clear cell

NR1H2 expression

NRAS mutations

Number of

histology

metastatic sites

papillary features

PH-4 expression

Platelets Number

RABL2B

expression

RC3H2 expression

rs12553173

Sedimentation rate

SUPT6H

expression

TACC1 expression

TDP1 expression

TFPI expression

Time from tumor to

occurrence of

metastases

Transferrin level

TSH level

VCAM1 expression

VEGF level

Weight loss

α-antitrypsin level

IFNa

CAIX level

Delta32 CCR5

Leucocytes count

LNPEP expression

therapy

Polymorphism

ERCC1 (codon 118)

GBF1 expression

Bone metastasis

Breslow thickness

polymorphism

IL-6 expression

CCR5 LOF mutation

LOC130576

CD4+ cells number

level

expression

Hepatic RIG-1

IL-1β expression

LOC399900

BDNFOS

expression

level

expression

expression

Interval from initial

ARHGAP10

BCAT2 expression

CD8+ CD57+ cells

diagnosis to

expression

number

treatment

Liver metastasis

CD83+ TIDC cells

CDNA FLJ37989 fis

Ki-67 expression

number

expression

HLA-Cw06 allele

IL-1α expression

HLA-DQB1

ATP6V0A2

level

expression

expression

Alkaline

collagen IV level

HLA-DQA1

IL-10 (−1082G -> A)

phosphatase level

expression

polymorphism

IFN-g (+874A -> T)

MAP3K5 expression

Mediastinum metastasis

MEF2A expression

polymorphism

MIP-1α expression

MIP-1β expression

MTAP gene expression

MTUS1 expression

level

level

Neutrophil count

NR1H2 expression

Number of metastatic

Osteopontin level

sites

Performance status

PH-4 expression

Platelets Number

RABL2B

expression

RC3H2 expression

Sedimentation rate

Serum calcium level

Serum hemoglobin

level

STAT1 gene

SUPT6H expression

TACC1 expression

TDP1 expression

expression

TFPI expression

Time from tumor to

TNF-α expression level

TRAIL level

occurrence of

metastases

Ulceration of

VCAM1 expression

VEGF level

VEGFR2 level

primary

Anti-cancer

Cancer-Testis

CD16+ CD56+

CD4+ CD45RO+ cell

CD4+ CTLA-4+

vaccine

Antigens' Genes

CD69+ lymphocytes

number

T cell number

therapy

expression

number

CD4+ PD-1+ T cell

C-reactive protein

ECOG performance

EGF level

number

level

score

I/II high-grade or III

IFN-gamma-induced

IgM for Blood Group A

IL-6 level

T1/2/3a low-grade

tumor cell apoptosis

trisaccharide level

disease intermediate

risk

Intratumoral versus

LDH level

Lin-CD14+ HLA-DR−/

lymphocyte number

peritumoral T cell

lo MDSC level

density

lymphocytes in

M1/M2 macrophage

MDSC number

Mean Corpuscular

PBMC %

ratio

Hemoglobin

Concentration

(MCHC)

Number of CD27−

Patient's age

Predictive gene

PTEN loss

CD45RA+ and

signature in MAGE A3

CD27− CD45RA−

antigen-specific cancer

and

immunotherapy

CD27+ CD45RA−

T-cells

Serum amyloid A

Serum S100B

Syndecan-4 mRNA

T reg cell %

level

concentration

expression level

TGFbeta level

Toll-like receptor 4

WT1 expression

gene polymorphism

Anti-

Acneiform rash

Adrenomedullin

angiopoietin-2

Bioactive Peptide

angiogenic

Repeat

expression levels

Induced Signaling

therapy

Polymorphism

Pathway

CD133 expression

CDC16 level

Child-Pugh class

CXCL10 plasma

level

CXCR1 rs2234671

CXCR2 C785T

CXCR2 rs2230054

ECOG Performance

G > C

T > C

Status

EGF A-61G

EGF rs444903 A > G

EGFR expression levels

EGFR rs2227983

G > A

Endothelin-1

Expression of CD31

Expression of

HBV status

expression levels

PDGFR-beta

HGF plasma level

History of alcohol

ICAM1 T469C

IFN-α2 plasma level

intake

IGF-1 rs6220 A > G

IL-12 plasma level

IL-16 plasma level

IL-2Rα plasma level

IL-3 plasma level

IL-6 plasma level

IL-8 251 T > A

IL-8 plasma level

Lck and Fyn

Liver metastasis

M-CSF plasma level

mucinous histology

tyrosine kinases in

initiation of TCR

Activation pathway

activation

NO2-dependent IL

Number of resting

Number of total

PIGF plasma level

12 Pathway

circulating

circulating endothelial

activation in NK

endothelial cells

cells

cells

portal vein

rs12505758 in

rs2286455

rs3130

thrombosis

VEGFR2

rs699946 in VEGFA

SDF-1α plasma level

Sex

sVEGFR1

T Cell Receptor

T Helper Cell Surface

TRAIL plasma level

VEGF-1154 A > G

Signaling Pathway

Molecules expression

activation

VEGF-1498 C > T

VEGF C936T

VEGF G-634C

VEGF-1154 G/A

VEGF-2578 C/A

VEGFR1 rs9582036

VEGFR-2 rs2305948

WNK1-rs11064560

C > T

Rituximab

BCL2 expression

BCL6 expression

Beclin-1 expression

ClqA Gene

level

Polymorphism

Carbohydrate

CD163-positive

CD20 expression

CD37 expression

antigen-125 level

macrophages

level

CD5 expression

CXCR4 expression

Cytotoxic T

FcγRIIIa 158H/H

level

level

lymphocyte-associated

genotypes

Granzyme B expression

level

Galectin-1

HIP1R mRNA level

IL-12 level

IL-1RA level

expression

Ki-67 expression

MARCO expression

Mast cell number 1

miR-155 expression

MYC expression

Number of

p21 protein expression

SLR11 level

macrophages

SMAD1 expression

STAT3

T cells

TAM number

mRNA level

TIM3 expression.

2. The system of claim 1 , wherein the processor-executable instructions further cause the at least one computer hardware processor to perform:

determining, using both the sequencing data and the biomarker information, a second set of normalized biomarker scores for a second set of biomarkers associated with a second therapy in the plurality of therapies; and

determining a second therapy score using the second set of normalized biomarker scores.

3. The system of claim 1 , wherein determining the first therapy score for the first therapy is performed using a statistical model selected from the group consisting of a linear model, a generalized linear model, a neural network model, a Bayesian regression model, an adaptive non-linear regression model, a mixture model, and a random forest regression model.

4. The system of claim 1 , wherein determining the first normalized biomarker score comprises:

determining the first un-normalized biomarker score for the first biomarker using the sequencing data;

determining a Z-score based on the first distribution of values for the first biomarker; and

determining the first normalized biomarker score for the first biomarker based on the first un-normalized biomarker score and the Z-score.

5. The system of claim 1 , wherein determining the first therapy score comprises:

determining weights for two or more scores in the first set of normalized biomarker scores for the subject; and

determining the first therapy score as a sum of the two or more scores, summands of the sum being weighted by the determined weights.

6. The system of claim 1 , wherein the first therapy score is indicative of response of the subject to administration of the first therapy.

7. The system of claim 1 , wherein the sequencing data comprises RNA sequencing data.

8. At least one non-transitory computer-readable storage medium storing processor-executable instructions that, when executed by at least one computer hardware processor, cause the at least one computer hardware processor to perform:

obtaining sequencing data about at least one biological sample of a subject;

accessing, in at least one database, biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers, each biomarker in the reference subset of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies, the reference subset of the plurality of biomarkers including a first biomarker and a second biomarker, and the biomarker information including a first distribution of values for the first biomarker and a second distribution of values for the second biomarker;

determining, using both the sequencing data and the biomarker information, therapy scores for at least some therapies in the plurality of therapies, the determining comprising:

determining, using the sequencing data, a first set of un-normalized biomarker scores for a first set of biomarkers in the reference subset of the plurality of biomarkers, the first set of un-normalized biomarker scores including a first un-normalized biomarker score for the first biomarker and a second un-normalized biomarker score for the second biomarker, and the first set of biomarkers being associated with a first therapy in the at least some therapies;

determining a first set of normalized biomarker scores for the first set of biomarkers, the first set of normalized biomarker scores including a first normalized biomarker score for the first biomarker and a second normalized biomarker score for the second biomarker, and the determining comprising:

adjusting the first set of un-normalized biomarker scores for the first set of biomarkers to a common scale, the adjusting comprising adjusting the first and second un-normalized biomarker scores to the common scale using the first and second distributions of values respectively; and

determining a first therapy score for the first therapy using the first set of normalized biomarker scores,

wherein the first therapy is selected from the group consisting of: an anti-PD1 therapy, an anti-CTLA4 therapy, an IL-2 therapy, an IFN alpha therapy, an anti-cancer vaccine therapy, an anti-angiogenic therapy, and an anti-CD20 therapy, and

wherein the first set of biomarkers comprises at least three biomarkers selected from the group of biomarkers associated with the first therapy in Table 2; and

recommending, for the subject, at least one therapy of the at least some therapies based on the determined therapy scores,

wherein the Table 2 is:

Therapy

Biomarkers

aPD1

Affinity of

AXL

B2M LOF mutation

BRAF mutation

therapy

neontigens

BRCA2 mutation

Cancer gene panels

Cancer gene panels

CCL13

(CGPs) FM-CGP

(CGPs) HSL-CGP

CCL2

CCL7

CCL8

CD8+ cell density in

the tumor invasive

margin

CD8+ cell number

CDH1

CVEGFC

CX3CL1 expression

CXCR2 expression

Dendritic cell number

EGFR expression

Endothelial cells

Eosinophil number

ESRP1 expression

Fibroblasts

Granzyme B

expression

JAK1 LOF mutation

JAK2 LOF mutation

LDH level

Lymphocyte number

M1 macrophage

M1/M2 macrophage

MDSC %

MHC-II expression

number

ratio

MHC-II expression

Missmatch-repair

MITF expression

Mutational Burden

(HLA-DRA)

deficiency status

Pattern of distant

PD-L1 expression

PD-L1 expression on

PTEN loss

metastases

infiltrating leukocytes

Quantity of

ROR2

STAT1 expression

T reg cell %

neoantigen peptides

TAGLN

TCR clonality

TGFbeta level

TIL number in

tumor

TWIST2

VEGF level

VEGFA

aCTLA4

Absolute

CD8+ cell number

CXCL11 expression

CXCL9 expression

therapy

lymphocyte count

CXCR3 expression

Dendritic cell number

EOMES+ CD8+ cells

FOXP3+ cells

number

number

IDO expression

LDH expression

M1 macrophage

M1/M2 macrophage

number

ratio

MDSC %

Mutational Burden

NY-ESO-1 seropostive

PTEN loss

T reg cell %

TCR clonality

TGFbeta level

TIL number in

tumor

VEGF level

IL-2 therapy

Bone metastasis

concomitant regional

Leucocytes number

LNPEP expression

lymphadenopathy

C-reactive protein

Delta32 CCR5

BCAT2 expression

BDNFOS

level

Polymorphism

expression

IL-10 (−1082G -> A)

CAIX expression

LOC130576

CCR5 LOF

polymorphism

expression

mutation

ERCC1 (codon 118)

IFN-g (+874A -> T)

LOC399900

ATP6V0A2

polymorphism

polymorphism

expression

expression

Ki-67 expression

Alkaline phosphatase

ARHGAP10

CD56+ or CD57+

level

expression

cells number

Liver metastasis

CD83+ TIDC cells

CDNA FLJ37989

LDH level

number

expression

Fibronectin level

HLA-DQB1

GBF1 expression

amount of alveolar

expression

component

Albumin level

clear cell

FOXP3+ cells number

HLA-DQA1

histology

expression

granular features

MAP3K5 expression

MDSC number

Mediastinum

metastasis

MEF2A expression

MTUS1 expression

Neutrophil number

NK cell number

non clear cell

NR1H2 expression

NRAS mutations

Number of

histology

metastatic sites

papillary features

PH-4 expression

Platelets Number

RABL2B

expression

RC3H2 expression

rs12553173

Sedimentation rate

SUPT6H

expression

TACC1 expression

TDP1 expression

TFPI expression

Time from tumor to

occurrence of

metastases

Transferrin level

TSH level

VCAM1 expression

VEGF level

Weight loss

α-antitrypsin level

IFNa

CAIX level

Delta32 CCR5

Leucocytes count

LNPEP expression

therapy

Polymorphism

ERCC1 (codon 118)

GBF1 expression

Bone metastasis

Breslow thickness

polymorphism

IL-6 expression

CCR5 LOF mutation

LOC130576

CD4+ cells number

level

expression

Hepatic RIG-1

IL-1β expression

LOC399900

BDNFOS

expression

level

expression

expression

Interval from initial

ARHGAP10

BCAT2 expression

CD8+ CD57+ cells

diagnosis to

expression

number

treatment

Liver metastasis

CD83+ TIDC cells

CDNA FLJ37989 fis

Ki-67 expression

number

expression

HLA-Cw06 allele

IL-1α expression

HLA-DQB1

ATP6V0A2

level

expression

expression

Alkaline

collagen IV level

HLA-DQA1

IL-10 (−1082G -> A)

phosphatase level

expression

polymorphism

IFN-g (+874A -> T)

MAP3K5 expression

Mediastinum metastasis

MEF2A expression

polymorphism

MIP-1α expression

MIP-1β expression

MTAP gene expression

MTUS1 expression

level

level

Neutrophil count

NR1H2 expression

Number of metastatic

Osteopontin level

sites

Performance status

PH-4 expression

Platelets Number

RABL2B

expression

RC3H2 expression

Sedimentation rate

Serum calcium level

Serum hemoglobin

level

STAT1 gene

SUPT6H expression

TACC1 expression

TDP1 expression

expression

TFPI expression

Time from tumor to

TNF-α expression level

TRAIL level

occurrence of

metastases

Ulceration of

VCAM1 expression

VEGF level

VEGFR2 level

primary

Anti-cancer

Cancer-Testis

CD16+ CD56+

CD4+ CD45RO+ cell

CD4+ CTLA-4+

vaccine

Antigens' Genes

CD69+ lymphocytes

number

T cell number

therapy

expression

number

CD4+ PD-1+ T cell

C-reactive protein

ECOG performance

EGF level

number

level

score

I/II high-grade or III

IFN-gamma-induced

IgM for Blood Group A

IL-6 level

T1/2/3a low-grade

tumor cell apoptosis

trisaccharide level

disease intermediate

risk

Intratumoral versus

LDH level

Lin-CD14+ HLA-DR−/

lymphocyte number

peritumoral T cell

lo MDSC level

density

lymphocytes in

M1/M2 macrophage

MDSC number

Mean Corpuscular

PBMC %

ratio

Hemoglobin

Concentration

(MCHC)

Number of CD27−

Patient's age

Predictive gene

PTEN loss

CD45RA+ and

signature in MAGE A3

CD27− CD45RA−

antigen-specific cancer

and

immunotherapy

CD27+ CD45RA−

T-cells

Serum amyloid A

Serum S100B

Syndecan-4 mRNA

T reg cell %

level

concentration

expression level

TGFbeta level

Toll-like receptor 4

WT1 expression

gene polymorphism

Anti-

Acneiform rash

Adrenomedullin

angiopoietin-2

Bioactive Peptide

angiogenic

Repeat

expression levels

Induced Signaling

therapy

Polymorphism

Pathway

CD133 expression

CDC16 level

Child-Pugh class

CXCL10 plasma

level

CXCR1 rs2234671

CXCR2 C785T

CXCR2 rs2230054

ECOG Performance

G > C

T > C

Status

EGF A-61G

EGF rs444903 A > G

EGFR expression levels

EGFR rs2227983

G > A

Endothelin-1

Expression of CD31

Expression of

HBV status

expression levels

PDGFR-beta

HGF plasma level

History of alcohol

ICAM1 T469C

IFN-α2 plasma level

intake

IGF-1 rs6220 A > G

IL-12 plasma level

IL-16 plasma level

IL-2Rα plasma level

IL-3 plasma level

IL-6 plasma level

IL-8 251 T > A

IL-8 plasma level

Lck and Fyn

Liver metastasis

M-CSF plasma level

mucinous histology

tyrosine kinases in

initiation of TCR

Activation pathway

activation

NO2-dependent IL

Number of resting

Number of total

PIGF plasma level

12 Pathway

circulating

circulating endothelial

activation in NK

endothelial cells

cells

cells

portal vein

rs12505758 in

rs2286455

rs3130

thrombosis

VEGFR2

rs699946 in VEGFA

SDF-1α plasma level

Sex

sVEGFR1

T Cell Receptor

T Helper Cell Surface

TRAIL plasma level

VEGF-1154 A > G

Signaling Pathway

Molecules expression

activation

VEGF-1498 C > T

VEGF C936T

VEGF G-634C

VEGF-1154 G/A

VEGF-2578 C/A

VEGFR1 rs9582036

VEGFR-2 rs2305948

WNK1-rs11064560

C > T

Rituximab

BCL2 expression

BCL6 expression

Beclin-1 expression

C1qA Gene

level

Polymorphism

Carbohydrate

CD163-positive

CD20 expression

CD37 expression

antigen-125 level

macrophages

level

CD5 expression

CXCR4 expression

Cytotoxic T

FcγRIIIa 158H/H

level

level

lymphocyte-associated

genotypes

Granzyme B expression

level

Galectin-1

HIP1R mRNA level

IL-12 level

IL-1RA level

expression

Ki-67 expression

MARCO expression

Mast cell number 1

miR-155 expression

MYC expression

Number of

p21 protein expression

SLR11 level

macrophages

SMAD1 expression

STAT3

T cells

TAM number

mRNA level

TIM3 expression.

9. The at least one non-transitory computer-readable storage medium of claim 8 , wherein the processor-executable instructions further cause the at least one computer hardware processor to perform:

determining, using both the sequencing data and the biomarker information, a second set of normalized biomarker scores for a second set of biomarkers associated with a second therapy in the plurality of therapies; and

determining a second therapy score using the second set of normalized biomarker scores.

10. The at least one non-transitory computer-readable storage medium of claim 8 , wherein determining the first therapy score for the first therapy is performed using a statistical model selected from the group consisting of a linear model, a generalized linear model, a neural network model, a Bayesian regression model, an adaptive non-linear regression model, a mixture model, and a random forest regression model.

11. The at least one non-transitory computer-readable storage medium of claim 8 , wherein determining the first normalized biomarker score comprises:

determining the first un-normalized biomarker score for the first biomarker using the sequencing data;

determining a Z-score based on the first distribution of values for the first biomarker; and

determining the first normalized biomarker score for the first biomarker based on the first un-normalized biomarker score and the Z-score.

12. The at least one non-transitory computer-readable storage medium of claim 8 , wherein determining the first therapy score comprises:

determining weights for two or more scores in the first set of normalized biomarker scores for the subject; and

determining the first therapy score as a sum of the two or more scores, summands of the sum being weighted by the determined weights.

13. The at least one non-transitory computer-readable storage medium of claim 8 , wherein the first therapy score is indicative of response of the subject to administration of the first therapy.

14. The at least one non-transitory computer-readable storage medium of claim 8 , wherein the sequencing data comprises RNA sequencing data.

15. A method, comprising:

using at least one computer hardware processor to perform:

obtaining sequencing data about at least one biological sample of a subject;

accessing, in at least one database, biomarker information indicating a distribution of values for each biomarker in at least a reference subset of a plurality of biomarkers, each biomarker in the reference subset of the plurality of biomarkers being associated with at least one therapy in a plurality of therapies, the reference subset of the plurality of biomarkers including a first biomarker and a second biomarker, and the biomarker information including a first distribution of values for the first biomarker and a second distribution of values for the second biomarker;

determining, using both the sequencing data and the biomarker information, therapy scores for at least some therapies in the plurality of therapies, the determining comprising:

determining, using the sequencing data, a first set of un-normalized biomarker scores for a first set of biomarkers in the reference subset of the plurality of biomarkers, the first set of un-normalized biomarker scores including a first un-normalized biomarker score for the first biomarker and a second un-normalized biomarker score for the second biomarker, and the first set of biomarkers being associated with a first therapy in the at least some therapies;

determining a first set of normalized biomarker scores for the first set of biomarkers, the first set of normalized biomarker scores including a first normalized biomarker score for the first biomarker and a second normalized biomarker score for the second biomarker, and the determining comprising:

adjusting the first set of un-normalized biomarker scores for the first set of biomarkers to a common scale, the adjusting comprising adjusting the first and second un-normalized biomarker scores to the common scale using the first and second distributions of values respectively; and

determining a first therapy score for the first therapy using the first set of normalized biomarker scores,

wherein the first therapy is selected from the group consisting of: an anti-PD1 therapy, an anti-CTLA4 therapy, an IL-2 therapy, an IFN alpha therapy, an anti-cancer vaccine therapy, an anti-angiogenic therapy, and an anti-CD20 therapy, and

wherein the first set of biomarkers comprises at least three biomarkers selected from the group of biomarkers associated with the first therapy in Table 2; and

recommending, for the subject, at least one therapy of the at least some therapies based on the determined therapy scores,

wherein Table 2 is:

Therapy

Biomarkers

aPD1

Affinity of

AXL

B2M LOF mutation

BRAF mutation

therapy

neontigens

BRCA2 mutation

Cancer gene panels

Cancer gene panels

CCL13

(CGPs) FM-CGP

(CGPs) HSL-CGP

CCL2

CCL7

CCL8

CD8+ cell density in

the tumor invasive

margin

CD8+ cell number

CDH1

CVEGFC

CX3CL1 expression

CXCR2 expression

Dendritic cell number

EGFR expression

Endothelial cells

Eosinophil number

ESRP1 expression

Fibroblasts

Granzyme B

expression

JAK1 LOF mutation

JAK2 LOF mutation

LDH level

Lymphocyte number

M1 macrophage

M1/M2 macrophage

MDSC %

MHC-II expression

number

ratio

MHC-II expression

Missmatch-repair

MITF expression

Mutational Burden

(HLA-DRA)

deficiency status

Pattern of distant

PD-L1 expression

PD-L1 expression on

PTEN loss

metastases

infiltrating leukocytes

Quantity of

ROR2

STAT1 expression

T reg cell %

neoantigen peptides

TAGLN

TCR clonality

TGFbeta level

TIL number in

tumor

TWIST2

VEGF level

VEGFA

aCTLA4

Absolute

CD8+ cell number

CXCL11 expression

CXCL9 expression

therapy

lymphocyte count

CXCR3 expression

Dendritic cell number

EOMES+ CD8+ cells

FOXP3+ cells

number

number

IDO expression

LDH expression

M1 macrophage

M1/M2 macrophage

number

ratio

MDSC %

Mutational Burden

NY-ESO-1 seropostive

PTEN loss

T reg cell %

TCR clonality

TGFbeta level

TIL number in

tumor

VEGF level

IL-2 therapy

Bone metastasis

concomitant regional

Leucocytes number

LNPEP expression

lymphadenopathy

C-reactive protein

Delta32 CCR5

BCAT2 expression

BDNFOS

level

Polymorphism

expression

IL-10 (−1082G -> A)

CAIX expression

LOC130576

CCR5 LOF

polymorphism

expression

mutation

ERCC1 (codon 118)

IFN-g (+874A -> T)

LOC399900

ATP6V0A2

polymorphism

polymorphism

expression

expression

Ki-67 expression

Alkaline phosphatase

ARHGAP10

CD56+ or CD57+

level

expression

cells number

Liver metastasis

CD83+ TIDC cells

CDNA FLJ37989

LDH level

number

expression

Fibronectin level

HLA-DQB1

GBF1 expression

amount of alveolar

expression

component

Albumin level

clear cell

FOXP3+ cells number

HLA-DQA1

histology

expression

granular features

MAP3K5 expression

MDSC number

Mediastinum

metastasis

MEF2A expression

MTUS1 expression

Neutrophil number

NK cell number

non clear cell

NR1H2 expression

NRAS mutations

Number of

histology

metastatic sites

papillary features

PH-4 expression

Platelets Number

RABL2B

expression

RC3H2 expression

rs12553173

Sedimentation rate

SUPT6H

expression

TACC1 expression

TDP1 expression

TFPI expression

Time from tumor to

occurrence of

metastases

Transferrin level

TSH level

VCAM1 expression

VEGF level

Weight loss

α-antitrypsin level

IFNa

CAIX level

Delta32 CCR5

Leucocytes count

LNPEP expression

therapy

Polymorphism

ERCC1 (codon 118)

GBF1 expression

Bone metastasis

Breslow thickness

polymorphism

IL-6 expression

CCR5 LOF mutation

LOC130576

CD4+ cells number

level

expression

Hepatic RIG-1

IL-1β expression

LOC399900

BDNFOS

expression

level

expression

expression

Interval from initial

ARHGAP10

BCAT2 expression

CD8+ CD57+ cells

diagnosis to

expression

number

treatment

Liver metastasis

CD83+ TIDC cells

CDNA FLJ37989 fis

Ki-67 expression

number

expression

HLA-Cw06 allele

IL-1α expression

HLA-DQB1

ATP6V0A2

level

expression

expression

Alkaline

collagen IV level

HLA-DQA1

IL-10 (−1082G -> A)

phosphatase level

expression

polymorphism

IFN-g (+874A -> T)

MAP3K5 expression

Mediastinum metastasis

MEF2A expression

polymorphism

MIP-1α expression

MIP-1β expression

MTAP gene expression

MTUS1 expression

level

level

Neutrophil count

NR1H2 expression

Number of metastatic

Osteopontin level

sites

Performance status

PH-4 expression

Platelets Number

RABL2B

expression

RC3H2 expression

Sedimentation rate

Serum calcium level

Serum hemoglobin

level

STAT1 gene

SUPT6H expression

TACC1 expression

TDP1 expression

expression

TFPI expression

Time from tumor to

TNF-α expression level

TRAIL level

occurrence of

metastases

Ulceration of

VCAM1 expression

VEGF level

VEGFR2 level

primary

Anti-cancer

Cancer-Testis

CD16+ CD56+

CD4+ CD45RO+ cell

CD4+ CTLA-4+

vaccine

Antigens' Genes

CD69+ lymphocytes

number

T cell number

therapy

expression

number

CD4+ PD-1+ T cell

C-reactive protein

ECOG performance

EGF level

number

level

score

I/II high-grade or III

IFN-gamma-induced

IgM for Blood Group A

IL-6 level

T1/2/3a low-grade

tumor cell apoptosis

trisaccharide level

disease intermediate

risk

Intratumoral versus

LDH level

Lin-CD14+ HLA-DR−/

lymphocyte number

peritumoral T cell

lo MDSC level

density

lymphocytes in

M1/M2 macrophage

MDSC number

Mean Corpuscular

PBMC %

ratio

Hemoglobin

Concentration

(MCHC)

Number of CD27−

Patient's age

Predictive gene

PTEN loss

CD45RA+ and

signature in MAGE A3

CD27− CD45RA−

antigen-specific cancer

and

immunotherapy

CD27+ CD45RA−

T-cells

Serum amyloid A

Serum S100B

Syndecan-4 mRNA

T reg cell %

level

concentration

expression level

TGFbeta level

Toll-like receptor 4

WT1 expression

gene polymorphism

Anti-

Acneiform rash

Adrenomedullin

angiopoietin-2

Bioactive Peptide

angiogenic

Repeat

expression levels

Induced Signaling

therapy

Polymorphism

Pathway

CD133 expression

CDC16 level

Child-Pugh class

CXCL10 plasma

level

CXCR1 rs2234671

CXCR2 C785T

CXCR2 rs2230054

ECOG Performance

G > C

T > C

Status

EGF A-61G

EGF rs444903 A > G

EGFR expression levels

EGFR rs2227983

G > A

Endothelin-1

Expression of CD31

Expression of

HBV status

expression levels

PDGFR-beta

HGF plasma level

History of alcohol

ICAM1 T469C

IFN-α2 plasma level

intake

IGF-1 rs6220 A > G

IL-12 plasma level

IL-16 plasma level

IL-2Rα plasma level

IL-3 plasma level

IL-6 plasma level

IL-8 251 T > A

IL-8 plasma level

Lck and Fyn

Liver metastasis

M-CSF plasma level

mucinous histology

tyrosine kinases in

initiation of TCR

Activation pathway

activation

NO2-dependent IL

Number of resting

Number of total

PIGF plasma level

12 Pathway

circulating

circulating endothelial

activation in NK

endothelial cells

cells

cells

portal vein

rs12505758 in

rs2286455

rs3130

thrombosis

VEGFR2

rs699946 in VEGFA

SDF-1α plasma level

Sex

sVEGFR1

T Cell Receptor

T Helper Cell Surface

TRAIL plasma level

VEGF-1154 A > G

Signaling Pathway

Molecules expression

activation

VEGF-1498 C > T

VEGF C936T

VEGF G-634C

VEGF-1154 G/A

VEGF-2578 C/A

VEGFR1 rs9582036

VEGFR-2 rs2305948

WNK1-rs11064560

C > T

Rituximab

BCL2 expression

BCL6 expression

Beclin-1 expression

C1qA Gene

level

Polymorphism

Carbohydrate

CD163-positive

CD20 expression

CD37 expression

antigen-125 level

macrophages

level

CD5 expression

CXCR4 expression

Cytotoxic T

FcγRIIIa 158H/H

level

level

lymphocyte-associated

genotypes

Granzyme B expression

level

Galectin-1

HIP1R mRNA level

IL-12 level

IL-1RA level

expression

Ki-67 expression

MARCO expression

Mast cell number 1

miR-155 expression

MYC expression

Number of

p21 protein expression

SLR11 level

macrophages

SMAD1 expression

STAT3

T cells

TAM number

mRNA level

TIM3 expression.

16. The method of claim 15 , further comprising:

determining, using both the sequencing data and the biomarker information, a second set of normalized biomarker scores for a second set of biomarkers associated with a second therapy in the plurality of therapies; and

determining a second therapy score using the second set of normalized biomarker scores.

17. The method of claim 15 , wherein determining the first therapy score for the first therapy is performed using a statistical model selected from the group consisting of a linear model, a generalized linear model, a neural network model, a Bayesian regression model, an adaptive non-linear regression model, a mixture model, and a random forest regression model.

18. The method of claim 15 , wherein determining the first normalized biomarker score comprises:

determining the first un-normalized biomarker score for the first biomarker using the sequencing data;

determining a Z-score based on the first distribution of values for the first biomarker; and

determining the first normalized biomarker score for the first biomarker based on the first un-normalized biomarker score and the Z-score.

19. The method of claim 15 , wherein determining the first therapy score comprises:

determining weights for two or more scores in the first set of normalized biomarker scores for the subject; and

determining the first therapy score as a sum of the two or more scores, summands of the sum being weighted by the determined weights.

20. The method of claim 15 , further comprising administering the first therapy to the subject.

Assignments (2)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Aug 28, 2019
From: BAGAEV, ALEXANDER; FRENKEL, FELIKS; ATAULLAKHANOV, RAVSHAN
To: BOSTONGENE, LLC
Reel/Frame 050194/0621 →
ENTITY CONVERSION Recorded Aug 28, 2019
From: BOSTONGENE, LLC
To: BOSTONGENE CORPORATION
Reel/Frame 050194/0891 →
Continuity (4)
Continuation 16006340 · Jun 12, 2018
Provisional Application 62598440 · Dec 13, 2017
Provisional Application 62518787 · Jun 13, 2017
Related Publication 20200135302A1 · Apr 30, 2020