Systems and methods for generating, visualizing and classifying molecular functional profiles

• US 10,395,761 B1
• Filed: 04/22/2019
• Issued: 08/27/2019
• Est. Priority Date: 06/13/2017
• Status: Active Grant

• Current Assignee: Bostongene Corporation
• Original Assignee: Bostongene Corporation
• Inventors: Bagaev, Alexander, Frenkel, Feliks, Kotlov, Nikita, Ataullakhanov, Ravshan
• Primary Examiner(s): Brusca, John S
• Application Number:
  US16/391,221
• Publication Number:
  US 20190252046A1
• Time in Patent Office: 127 Days
• Field of Search: None
• CPC Class Codes: C12Q 1/6886 for cancer immunoassay for cancer G01N33/574
• CPC Class Codes: C12Q 2600/156 Polymorphic or mutational markers
• CPC Class Codes: C12Q 2600/158 Expression markers
• CPC Class Codes: G06F 16/285 Clustering or classification
• CPC Class Codes: G06F 17/18 for evaluating statistical data , e.g. average values, frequency distributions, probability functions, regression analysis forecasting specially adapted for a specific administrative, business or logistic context G06Q10/04
• CPC Class Codes: G16B 20/00 ICT specially adapted for functional genomics or proteomics, e.g. genotype-phenotype associations
• CPC Class Codes: G16B 25/10 Gene or protein expression profiling; Expression-ratio estimation or normalisation
• CPC Class Codes: G16B 30/00 ICT specially adapted for sequence analysis involving nucleotides or amino acids
• CPC Class Codes: 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
• CPC Class Codes: G16B 40/20 Supervised data analysis
• CPC Class Codes: G16B 40/30 Unsupervised data analysis
• CPC Class Codes: G16B 45/00 ICT specially adapted for bioinformatics-related data visualisation, e.g. displaying of maps or networks
• CPC Class Codes: G16B 5/00 ICT specially adapted for modelling or simulations in systems biology, e.g. gene-regulatory networks, protein interaction networks or metabolic networks
• CPC Class Codes: G16B 5/20 Probabilistic models
• CPC Class Codes: G16B 50/00 ICT programming tools or database systems specially adapted for bioinformatics
• CPC Class Codes: G16B 50/30 Data warehousing; Computing architectures
• CPC Class Codes: G16H 10/20 for electronic clinical trials or questionnaires
• CPC Class Codes: G16H 20/00 ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/40 relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
• CPC Class Codes: G16H 50/20 : for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 : for calculating health indices; for individual health risk assessment
• CPC Class Codes: G16H 50/50 : for simulation or modelling of medical disorders
• CPC Class Codes: G16H 50/70 : for mining of medical data, e.g. analysing previous cases of other patients
• CPC Class Codes: G16H 70/20 : relating to practices or guidelines

Abstract

Various methods, systems, computer readable media, and graphical user interfaces (GUIs) are presented and described that enable a subject, doctor, or user to characterize or classify various types of cancer precisely. Additionally, described herein are methods, systems, computer readable media, and GUIs that enable more effective specification of treatment and improved outcomes for patients with identified types of cancer. Some embodiments of the methods, systems, computer readable media, and GUIs described herein comprise obtaining RNA expression data and/or whole exome sequencing (WES) data for biological samples; determining a respective plurality of molecular-functional (MF) profiles for a plurality of subjects; clustering the plurality of MF profiles to obtain MF profile clusters; determining a molecular-functional (MF) profile for an additional subject; and identifying, from among the MF profile clusters, a particular MF profile cluster with which to associate the MF profile for the subject.

Claims

1. A method comprising:

administering a first anti-cancer therapy to a subject,

wherein the first anti-cancer therapy was identified by identifying a molecular-functional (MF) profile cluster with which to associate an MF profile for the subject, the identifying comprising;

obtaining first RNA expression data for biological samples from a plurality of subjects;

determining a respective plurality of molecular-functional (MF) profiles for the plurality of subjects at least in part by, for each of the plurality of subjects,

determining, using the first RNA expression data, a respective gene group expression level for each group in a set of gene groups, the set of gene groups comprising gene groups associated with cancer malignancy and different gene groups associated with cancer microenvironment;

clustering the plurality of MF profiles to obtain MF profile clusters including;

a first MF profile cluster associated with inflamed and vascularized biological samples and/or inflamed and fibroblast-enriched biological samples,

a second MF profile cluster associated with inflamed and non-vascularized biological samples and/or inflamed and non-fibroblast-enriched biological samples,

a third MF profile cluster associated with non-inflamed and vascularized biological samples and/or non-inflamed and fibroblast-enriched biological samples, and

a fourth MF profile cluster associated with non-inflamed and non-vascularized biological samples and/or non-inflamed and non-fibroblast-enriched biological samples;

obtaining second RNA expression data for a biological sample from the subject, wherein the subject is not in the plurality of subjects;

determining a molecular-functional (MF) profile for the subject at least in part by determining, using the second RNA expression data, a gene group expression level for each group in the set of gene groups to obtain gene group expression levels for the subject; and

comparing the gene group expression levels for the subject to gene group expression levels associated with the MF profile clusters;

wherein the first anti-cancer therapy comprises a therapy selected from the group consisting of;

chemotherapy, radiotherapy, immunotherapy, and targeted therapy.

2. The method of claim 1,

(a) wherein the gene group associated with cancer malignancy is a tumor properties group;

and wherein determining the MF profile for the subject comprises determining a gene group expression level for the tumor properties group; and

/or

(b) wherein the gene groups associated with cancer microenvironment are a tumor-promoting immune microenvironment group, an anti-tumor immune microenvironment group, an angiogenesis group, and a fibroblasts group; and

wherein determining the MF profile for the subject comprises determining a gene group expression level for each of the tumor-promoting immune microenvironment group, the anti-tumor immune microenvironment group, the angiogenesis group, and the fibroblasts group.

3. The method of claim 2, wherein the gene groups associated with cancer malignancy comprise at least three genes from:

the tumor properties group;

MKI67, ESCO2, CETN3, CDK2, CCND1, CCNE1, AURKA, AURKB, CDK4, CDK6, PRC1, E2F1, MYBL2, BUB1, PLK1, CCNB1, MCM2, MCM6, PIK3CA, PIK3CB, PIK3CG, PIK3CD, AKT1, MTOR, PTEN, PRKCA, AKT2, AKT3, BRAF, FNTA, FNTB, MAP2K1, MAP2K2, MKNK1, MKNK2, ALK, AXL, KIT, EGFR, ERBB2, FLT3, MET, NTRK1, FGFR1, FGFR2, FGFR3, ERBB4, ERBB3, BCR-ABL, PDGFRA, PDGFRB, NGF, CSF3, CSF2, FGF7, IGF1, IGF2, IL7, FGF2, TP53, SIK1, PTEN, DCN, MTAP, AIM2, RB1, ESRP1, CTSL, HOXA1, SMARCA4, SNAI2, TWIST1, NEDD9, PAPPA, HPSE, KISS1, ADGRG1, BRMS1, TCF21, CDH1, PCDH10, NCAM1, MITF, APC, ARID1A, ATM, ATRX, BAP1, BRAF, BRCA2, CDH1, CDKN2A, CTCF, CTNNB1, DNMT3A, EGFR, FBXW7, FLT3, GATA3, HRAS, IDH1, KRAS, MAP3K1, MTOR, NAV3, NCOR1, NF1, NOTCH1, NPM1, NRAS, PBRM1, PIK3CA, PIK3R1, PTEN, RB1, RUNX1, SETD2, STAG2, TAF1, TP53, and VHL;

optionally wherein determining the MF profile comprises;

determining the gene group expression level for the tumor properties group using the gene expression level obtained from the RNA sequence data for at least three genes in the tumor properties group.

4. The method of claim 2, wherein the gene groups associated with cancer microenvironment comprise at least three genes from each of the following groups:

the anti-tumor immune microenvironment group;

HLA-A, HLA-B, HLA-C, B2M, TAP1, TAP2, HLA-DRA, HLA-DRB1, HLA-DOB, HLA-DPB2, HLA-DMA, HLA-DOA, HLA-DPA1, HLA-DPB1, HLA-DMB, HLA-DQB1, HLA-DQA1, HLA-DRB5, HLA-DQA2, HLA-DQB2, HLA-DRB6, CD80, CD86, CD40, CD83, TNFRSF4, ICOSLG, CD28, IFNG, GZMA, GZMB, PRF1, LCK, GZMK, ZAP70, GNLY, FASLG, TBX21, EOMES, CD8A, CD8B, NKG7, CD160, CD244, NCR1, KLRC2, KLRK1, CD226, GZMH, GNLY, IFNG, KIR2DL4, KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS4, KIR2DS5, CXCL9, CXCL10, CXCR3, CX3CL1, CCR7, CXCL11, CCL21, CCL2, CCL3, CCL4, CCL5, EOMES, TBX21, ITK, CD3D, CD3E, CD3G, TRAC, TRBC1, TRBC2, LCK, UBASH3A, TRAT1, CD19, MS4A1, TNFRSF13C, CD27, CD24, CR2, TNFRSF17, TNFRSF13B, CD22, CD79A, CD79B, BLK, NOS2, IL12A, IL12B, IL23A, TNF, IL1B, SOCS3, IFNG, IL2, CD40LG, IL15, CD27, TBX21, LTA, IL21, HMGB1, TNF, IFNB1, IFNA2, CCL3, TNFSF10, and FASLG;

the tumor-promoting immune microenvironment group;

PDCD1, CD274, CTLA4, LAGS, PDCD1LG2, BTLA, HAVCR2, VSIR, CXCL12, TGFB1, TGFB2, TGFB3, FOXP3, CTLA4, IL10, TNFRSF1B, CCL17, CXCR4, CCR4, CCL22, CCL1, CCL2, CCL5, CXCL13, CCL28, IDO1, ARG1, IL4R, IL10, TGFB1, TGFB2, TGFB3, NOS2, CYBB, CXCR4, CD33, CXCL1, CXCL5, CCL2, CCL4, CCL8, CCR2, CCL3, CCL5, CSF1, CXCL8, CXCL8, CXCL2, CXCL1, CCL11, CCL24, KITLG, CCL5, CXCL5, CCR3, CCL26, PRG2, EPX, RNASE2, RNASE3, IL5RA, GATA1, SIGLEC8, PRG3, CMA1, TPSAB1, MS4A2, CPA3, IL4, IL5, IL13, SIGLEC8, MPO, ELANE, PRTN3, CTSG, IL10, VEGFA, TGFB1, IDO1, PTGES, MRC1, CSF1, LRP1, ARG1, PTGS1, MSR1, CD163, CSF1R, IL4, IL5, IL13, IL10, IL25, GATA3, IL10, TGFB1, TGFB2, TGFB3, IL22, MIF, CFD, CFI, CD55, CD46, and CR1;

the fibroblasts group;

LGALS1, COL1A1, COL1A2, COL4A1, COL5A1, TGFB1, TGFB2, TGFB3, ACTA2, FGF2, FAP, LRP1, CD248, COL6A1, COL6A2, and COL6A3; and

the angiogenesis group;

VEGFA, VEGFB, VEGFC, PDGFC, CXCL8, CXCR2, FLT1, PIGF, CXCL5, KDR, ANGPT1, ANGPT2, TEK, VWF, CDH5, NOS3, KDR, VCAM1, MMRN1, LDHA, HIF1A, EPAS1, CA9, SPP1, LOX, SLC2A1, and LAMP3;

optionally wherein determining the MF profile comprises;

determining the gene group expression level for the anti-tumor immune microenvironment group using the gene expression level obtained from the RNA sequence data for at least three genes in the anti-tumor immune microenvironment group;

determining the gene group expression level for the tumor-promoting immune microenvironment group using the gene expression level obtained from the RNA sequence data for at least three genes in the tumor-promoting immune microenvironment group;

determining the gene group expression level for the fibroblasts group using the gene expression level obtained from the RNA sequence data for at least three genes in the fibroblasts group; and

determining the gene group expression level for the angiogenesis group using the gene expression level obtained from the RNA sequence data for at least three genes in the angiogenesis group.

5. The method of claim 1,

wherein the gene groups associated with cancer malignancy are:

a proliferation rate group, a PI3K/AKT/mTOR signaling group, a RAS/RAF/MEK signaling group, a receptor tyrosine kinases expression group, a tumor suppressors group, a metastasis signature group, an anti-metastatic factors group, and a mutation status group; and

wherein determining the MF profile for the subject comprises determining a gene group expression level for each of the proliferation rate group, the PI3K/AKT/mTOR signaling group, the RAS/RAF/MEK signaling group, the receptor tyrosine kinases expression group, the tumor suppressors group, the metastasis signature group, the anti-metastatic factors group, and the mutation status group; and

/or

wherein the gene groups associated with cancer microenvironment are;

a antigen presentation group, a cytotoxic T and NK cells group, a B cells group, an anti-tumor microenvironment group, a checkpoint inhibition group, a Treg group, a MDSC group, agranulocytes group, a cancer associated fibroblasts group, a angiogenesis group, and a tumor-promotive immune group; and

wherein determining the MF profile for the subject comprises determining a gene group expression level for each of the antigen presentation group, the cytotoxic T and NK cells group, the B cells group, the anti-tumor microenvironment group, the checkpoint inhibition group, the Treg group, the MDSC group, the granulocytes group, the cancer associated fibroblasts group, the angiogenesis group, and the tumor-promotive immune group.

6. The method of claim 5, wherein the gene groups associated with cancer malignancy comprise at least three genes from each of the following groups:

the proliferation rate group;

MKI67, ESCO2, CETN3, CDK2, CCND1, CCNE1, AURKA, AURKB, CDK4, CDK6, PRC1, E2F1, MYBL2, BUB1, PLK1, CCNB1, MCM2, and MCM6;

the PI3K/AKT/mTOR signaling group;

PIK3CA, PIK3CB, PIK3CG, PIK3CD, AKT1, MTOR, PTEN, PRKCA, AKT2, and AKT3;

the RAS/RAF/MEK signaling group;

BRAF, FNTA, FNTB, MAP2K1, MAP2K2, MKNK1, and MKNK2;

the receptor tyrosine kinases expression group;

ALK, AXL, KIT, EGFR, ERBB2, FLT3, MET, NTRK1, FGFR1, FGFR2, FGFR3, ERBB4, ERBB3, BCR-ABL, PDGFRA, and PDGFRB;

the tumor suppressors group;

TP53, SIK1, PTEN, DCN, MTAP, AIM2, and RB1;

the metastasis signature group;

ESRP1, CTSL, HOXA1, SMARCA4, SNAI2, TWIST1, NEDD9, PAPPA, and HPSE;

the anti-metastatic factors group;

KISS1, ADGRG1, BRMS1, TCF21, CDH1, PCDH10, NCAM1, and MITF; and

the mutation status group;

APC, ARID1A, ATM, ATRX, BAP1, BRAF, BRCA2, CDH1, CDKN2A, CTCF, CTNNB1, DNMT3A, EGFR, FBXW7, FLT3, GATA3, HRAS, 1DH1, KRAS, MAP3K1, MTOR, NAV3, NCOR1, NF1, NOTCH1, NPM1, NRAS, PBRM1, PIK3CA, PIK3R1, PTEN, RB1, RUNX1, SETD2, STAG2, TAF1, TP53, and VHL;

optionally wherein determining the MF profile comprises;

determining the gene group expression level for the proliferation rate group using the gene expression level obtained from the RNA sequence data for at least three genes in the proliferation rate group;

determining the gene group expression level for the PI3K/AKT/mTOR signaling group using the gene expression level obtained from the RNA sequence data for at least three genes in the PI3K/AKT/mTOR signaling group;

determining the gene group expression level for the RAS/RAF/MEK signaling group using the gene expression level obtained from the RNA sequence data for at least three genes in the RAS/RAF/MEK signaling group;

determining the gene group expression level for the receptor tyrosine kinases expression group using the gene expression level obtained from the RNA sequence data for at least three genes in the receptor tyrosine kinases expression group;

determining the gene group expression level for the tumor suppressors group using the gene expression level obtained from the RNA sequence data for at least three genes in the tumor suppressors group;

determining the gene group expression level for the metastasis signature group using the gene expression level obtained from the RNA sequence data for at least three genes in the metastasis signature group;

determining the gene group expression level for the anti-metastatic factors group using the gene expression level obtained from the RNA sequence data for at least three genes in the anti-metastatic factors group; and

determining the gene group expression level for the mutation status group using the gene expression level obtained from the RNA sequence data for at least three genes in the mutation status group.

7. The method of claim 5, wherein the gene groups associated with cancer microenvironment comprise at least three genes from each of the following groups:

the cancer associated fibroblasts group;

LGALS1, COL1A1, COL1A2, COL4A1, COL5A1, TGFB1, TGFB2, TGFB3, ACTA2, FGF2, FAP, LRP1, CD248, COL6A1, COL6A2, and COL6A3;

the angiogenesis group;

VEGFA, VEGFB, VEGFC, PDGFC, CXCL8, CXCR2, FLT1, PIGF, CXCL5, KDR, ANGPT1, ANGPT2, TEK, VWF, CDH5, NOS3, KDR, VCAM1, MMRN1, LDHA, HIF1A, EPAS1, CA9, SPP1, LOX, SLC2A1, and LAMPS;

the antigen presentation group;

HLA-A, HLA-B, HLA-C, B2M, TAP1, TAP2, HLA-DRA, HLA-DRB1, HLA-DOB, HLA-DPB2, HLA-DMA, HLA-DOA, HLA-DPA1, HLA-DPB1, HLA-DMB, HLA-DQB1, HLA-DQA1, HLA-DRB5, HLA-DQA2, HLA-DQB2, HLA-DRB6, CD80, CD86, CD40, CD83, TNFRSF4, ICOSLG, and CD28;

the cytotoxic T and NK cells group;

IFNG, GZMA, GZMB, PRF1, LCK, GZMK, ZAP70, GNLY, FASLG, TBX21, EOMES, CD8A, CD8B, NKG7, CD160, CD244, NCR1, KLRC2, KLRK1, CD226, GZMH, GNLY, IFNG, KIR2DL4, KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS4, KIR2DS5, CXCL9, CXCL10, CXCR3, CX3CL1, CCR7, CXCL11, CCL21, CCL2, CCL3, CCL4, CCL5, EOMES, TBX21, ITK, CD3D, CD3E, CD3G, TRAC, TRBC1, TRBC2, LCK, UBASH3A, and TRAT1;

the B cells group;

CD19, MS4A1, TNFRSF13C, CD27, CD24, CR2, TNFRSF17, TNFRSF13B, CD22, CD79A, CD79B, and BLK;

the anti-tumor microenvironment group;

NOS2, IL12A, IL12B, IL23A, TNF, IL1B, SOCS3, IFNG, IL2, CD40LG, IL15, CD27, TBX21, LTA, IL21, HMGB1, TNF, IFNB1, IFNA2, CCL3, TNFSF10, and FASLG;

the checkpoint inhibition group;

PDCD1, CD274, CTLA4, LAG3, PDCD1LG2, BTLA, HAVCR2, and VSIR;

the Treg group;

CXCL12, TGFB1, TGFB2, TGFB3, FOXP3, CTLA4, IL10, TNFRSF1B, CCL17, CXCR4, CCR4, CCL22, CCL1, CCL2, CCL5, CXCL13, and CCL28;

the MDSC group;

IDO1, ARG1, IL4R, IL10, TGFB1, TGFB2, TGFB3, NOS2, CYBB, CXCR4, CD33, CXCL1, CXCL5, CCL2, CCL4, CCL8, CCR2, CCL3, CCL5, CSF1, and CXCL8;

the granulocytes group;

CXCL8, CXCL2, CXCL1, CCL11, CCL24, KITLG, CCL5, CXCL5, CCR3, CCL26, PRG2, EPX, RNASE2, RNASE3, IL5RA, GATA1, SIGLEC8, PRG3, CMA1, TPSAB1, MS4A2, CPA3, IL4, IL5, IL13, SIGLEC8, MPO, ELANE, PRTN3, and CTSG;

the tumor-promotive immune group;

IL10, VEGFA, TGFB1, IDO1, PTGES, MRC1, CSF1, LRP1, ARG1, PTGS1, MSR1, CD163, CSF1R, IL4, IL5, IL13, IL10, IL25, GATA3, IL10, TGFB1, TGFB2, TGFB3, IL22, MIF, CFD, CFI, CD55, CD46, and CR1;

optionally wherein determining the MF profile comprises;

determining the gene group expression level for the cancer associated fibroblasts group using the gene expression level obtained from the RNA sequence data for at least three genes in the cancer associated fibroblasts group;

determining the gene group expression level for the angiogenesis group using the gene expression level obtained from the RNA sequence data for at least three genes in the angiogenesis group;

determining the gene group expression level for the antigen presentation group using the gene expression level obtained from the RNA sequence data for at least three genes in the antigen presentation group;

determining the gene group expression level for the cytotoxic T and NK cells group using the gene expression level obtained from the RNA sequence data for at least three genes in the cytotoxic T and NK cells group;

determining the gene group expression level for the B cells group using the gene expression level obtained from the RNA sequence data for at least three genes in the B cells group;

determining the gene group expression level for the anti-tumor microenvironment group using the gene expression level obtained from the RNA sequence data for at least three genes in the anti-tumor microenvironment group;

determining the gene group expression level for the checkpoint inhibition group using the gene expression level obtained from the RNA sequence data for at least three genes in the checkpoint inhibition group;

determining the gene group expression level for the Treg group using the gene expression level obtained from the RNA sequence data for at least three genes in the Treg group;

determining the gene group expression level for the MDSC group using the gene expression level obtained from the RNA sequence data for at least three genes in the MDSC group;

determining the gene group expression level for the granulocytes group using the gene expression level obtained from the RNA sequence data for at least three genes in the granulocytes group; and

determining the gene group expression level for the tumor-promotive immune group using the gene expression level obtained from the RNA sequence data for at least three genes in the tumor-promotive immune group.

8. The method of claim 1,

wherein the gene groups associated with cancer malignancy are:

a proliferation rate group, a PI3K/AKT/mTOR signaling group, a RAS/RAF/MEK signaling group, a receptor tyrosine kinases expression group, a growth factors group, a tumor suppressors group, a metastasis signature group, an anti-metastatic factors group, and a mutation status group; and

wherein determining the MF profile for the subject comprises determining a gene group expression level for each of the proliferation rate group, the PI3K/AKT/mTOR signaling group, the RAS/RAF/MEK signaling group, the receptor tyrosine kinases expression group, the growth factors group, the tumor suppressors group, the metastasis signature group, the anti-metastatic factors group, and the mutation status group; and

/or

wherein the gene groups associated with cancer microenvironment are;

a cancer associated fibroblasts group, an angiogenesis group, a MHCI group, a MHCII group, a coactivation molecules group, an effector cells group, a NK cells group, a T cell traffic group, a T cells group, a B cells group, a M1 signatures group, a Th1 signature group, a antitumor cytokines group, a checkpoint inhibition group, a Treg group, a MDSC group, a granulocytes group, a M2 signature group, a Th2 signature group, a protumor cytokines group, and a complement inhibition group; and

wherein determining the MF profile for the subject comprises determining a gene group expression level for each of the cancer associated fibroblasts group, the angiogenesis group, the MHCI group, the MHCII group, the coactivation molecules group, the effector cells group, the NK cells group, the T cell traffic group, the T cells group, the B cells group, the M1 signatures group, the Th1 signature group, the antitumor cytokines group, the checkpoint inhibition group, the Treg group, the MDSC group, the granulocytes group, the M2 signature group, the Th2 signature group, the protumor cytokines group, and the complement inhibition group.

9. The method of claim 8, wherein the gene groups associated with cancer malignancy comprise at least three genes from each of the following groups:

the proliferation rate group;

MKI67, ESCO2, CETN3, CDK2, CCND1, CCNE1, AURKA, AURKB, CDK4, CDK6, PRC1, E2F1, MYBL2, BUB1, PLK1, CCNB1, MCM2, and MCM6;

the PI3K/AKT/mTOR signaling group;

PIK3CA, PIK3CB, PIK3CG, PIK3CD, AKT1, MTOR, PTEN, PRKCA, AKT2, and AKT3;

the RAS/RAF/MEK signaling group;

BRAF, FNTA, FNTB, MAP2K1, MAP2K2, MKNK1, and MKNK2;

the receptor tyrosine kinases expression group;

ALK, AXL, KIT, EGFR, ERBB2, FLT3, MET, NTRK1, FGFR1, FGFR2, FGFR3, ERBB4, ERBB3, BCR-ABL, PDGFRA, and PDGFRB;

the growth factors group;

NGF, CSF3, CSF2, FGF7, IGF1, IGF2, IL7, and FGF2;

the tumor suppressors group;

TP53, SIK1, PTEN, DCN, MTAP, AIM2, and RB1;

the metastasis signature group;

ESRP1, CTSL, HOXA1, SMARCA4, SNAI2, TWIST1, NEDD9, PAPPA, and HPSE;

the anti-metastatic factors group;

KISS1, ADGRG1, BRMS1, TCF21, CDH1, PCDH10, NCAM1, and MITF; and

the mutation status group;

APC, ARID1A, ATM, ATRX, BAP1, BRAF, BRCA2, CDH1, CDKN2A, CTCF, CTNNB1, DNMT3A, EGFR, FBXW7, FLT3, GATA3, HRAS, IDH1, KRAS, MAP3K1, MTOR, NAV3, NCOR1, NF1, NOTCH1, NPM1, NRAS, PBRM1, PIK3CA, PIK3R1, PTEN, RB1, RUNX1, SETD2, STAG2, TAF1, TP53, and VHL;

optionally wherein determining the MF profile comprises;

determining the gene group expression level for the proliferation rate group using the gene expression level obtained from the RNA sequence data for at least three genes in the proliferation rate group;

determining the gene group expression level for the PI3K/AKT/mTOR signaling group using the gene expression level obtained from the RNA sequence data for at least three genes in the PI3K/AKT/mTOR signaling group;

determining the gene group expression level for the RAS/RAF/MEK signaling group using the gene expression level obtained from the RNA sequence data for at least three genes in the RAS/RAF/MEK signaling group;

determining the gene group expression level for the receptor tyrosine kinases expression group using the gene expression level obtained from the RNA sequence data for at least three genes in the receptor tyrosine kinases expression group;

determining the gene group expression level for the growth factors group using the gene expression level obtained from the RNA sequence data for at least three genes in the growth factors group;

determining the gene group expression level for the tumor suppressors group using the gene expression level obtained from the RNA sequence data for at least three genes in the tumor suppressors group;

determining the gene group expression level for the metastasis signature group using the gene expression level obtained from the RNA sequence data for at least three genes in the metastasis signature group;

determining the gene group expression level for the anti-metastatic factors group using the gene expression level obtained from the RNA sequence data for at least three genes in the anti-metastatic factors group; and

determining the gene group expression level for the mutation status group using the gene expression level obtained from the RNA sequence data for at least three genes in the mutation status group.

10. The method of claim 8, wherein the gene groups associated with cancer microenvironment comprise at least three genes from each of the following groups:

the cancer associated fibroblasts group;

LGALS1, COL1A1, COL1A2, COL4A1, COL5A1, TGFB1, TGFB2, TGFB3, ACTA2, FGF2, FAP, LRP1, CD248, COL6A1, COL6A2, and COL6A3;

the angiogenesis group;

VEGFA, VEGFB, VEGFC, PDGFC, CXCL8, CXCR2, FLT1, PIGF, CXCL5, KDR, ANGPT1, ANGPT2, TEK, VWF, CDH5, NOS3, KDR, VCAM1, MMRN1, LDHA, HIF1A, EPAS1, CA9, SPP1, LOX, SLC2A1, and LAMPS;

the MHCI group;

HLA-A, HLA-B, HLA-C, B2M, TAP1, and TAP2;

the MHCII group;

HLA-DRA, HLA-DRB1, HLA-DOB, HLA-DPB2, HLA-DMA, HLA-DOA, HLA-DPA1, HLA-DPB1, HLA-DMB, HLA-DQB1, HLA-DQA1, HLA-DRB5, HLA-DQA2, HLA-DQB2, and HLA-DRB6;

the coactivation molecules group;

CD80, CD86, CD40, CD83, TNFRSF4, ICOSLG, and CD28;

the effector cells group;

IFNG, GZMA, GZMB, PRF1, LCK, GZMK, ZAP70, GNLY, FASLG, TBX21, EOMES, CD8A, and CD8B;

the NK cells group;

NKG7, CD160, CD244, NCR1, KLRC2, KLRK1, CD226, GZMH, GNLY, IFNG, KIR2DL4, KIR2DS1, KIR2DS2, KIR2DS3, KIR2DS4, and KIR2DS5;

the T cell traffic group;

CXCL9, CXCL10, CXCR3, CX3CL1, CCR7, CXCL11, CCL21, CCL2, CCL3, CCL4, and CCL5;

the T cells group;

EOMES, TBX21, ITK, CD3D, CD3E, CD3G, TRAC, TRBC1, TRBC2, LCK, UBASH3A, and TRAT1;

the B cells group;

CD19, MS4A1, TNFRSF13C, CD27, CD24, CR2, TNFRSF17, TNFRSF13B, CD22, CD79A, CD79B, and BLK;

the M1 signatures group;

NOS2, IL12A, IL12B, IL23A, TNF, IL1B, and SOCS3;

the Th1 signature group;

IFNG, IL2, CD40LG, IL15, CD27, TBX21, LTA, and IL21;

the antitumor cytokines group;

HMGB1, TNF, IFNB1, IFNA2, CCL3, TNFSF10, and FASLG;

the checkpoint inhibition group;

PDCD1, CD274, CTLA4, LAG3, PDCD1LG2, BTLA, HAVCR2, and VSIR;

the Treg group;

CXCL12, TGFB1, TGFB2, TGFB3, FOXP3, CTLA4, IL10, TNFRSF1B, CCL17, CXCR4, CCR4, CCL22, CCL1, CCL2, CCL5, CXCL13, and CCL28;

the MDSC group;

IDOL ARG1, IL4R, IL10, TGFB1, TGFB2, TGFB3, NOS2, CYBB, CXCR4, CD33, CXCL1, CXCL5, CCL2, CCL4, CCL8, CCR2, CCL3, CCL5, CSF1, and CXCL8;

the granulocytes group;

CXCL8, CXCL2, CXCL1, CCL11, CCL24, KITLG, CCL5, CXCL5, CCR3, CCL26, PRG2, EPX, RNASE2, RNASE3, IL5RA, GATA1, SIGLEC8, PRG3, CMA1, TPSAB1, MS4A2, CPA3, IL4, IL5, IL13, SIGLEC8, MPO, ELANE, PRTN3, and CTSG;

the M2 signature group;

IL10, VEGFA, TGFB1, IDO1, PTGES, MRC1, CSF1, LRP1, ARG1, PTGS1, MSR1, CD163, and CSF1R;

the Th2 signature group;

IL4, IL5, IL13, IL10, IL25, and GATA3;

the protumor cytokines group;

IL10, TGFB1, TGFB2, TGFB3, IL22, and MIF; and

the complement inhibition group;

CFD, CFI, CD55, CD46, and CR1;

optionally wherein determining the MF profile comprises;

determining the gene group expression level for the cancer associated fibroblasts group using the gene expression level obtained from the RNA sequence data for at least three genes in the cancer associated fibroblasts group;

determining the gene group expression level for the angiogenesis group using the gene expression level obtained from the RNA sequence data for at least three genes in the angiogenesis group;

determining the gene group expression level for the MHCI group using the gene expression level obtained from the RNA sequence data for at least three genes in the MHCI group;

determining the gene group expression level for the MHCII group using the gene expression level obtained from the RNA sequence data for at least three genes in the MHCII group;

determining the gene group expression level for the coactivation molecules group using the gene expression level obtained from the RNA sequence data for at least three genes in the coactivation molecules group;

determining the gene group expression level for the effector cells group using the gene expression level obtained from the RNA sequence data for at least three genes in the effector cells group;

determining the gene group expression level for the NK cells group using the gene expression level obtained from the RNA sequence data for at least three genes in the NK cells group;

determining the gene group expression level for the T cell traffic group using the gene expression level obtained from the RNA sequence data for at least three genes in the T cell traffic group;

determining the gene group expression level for the T cells group using the gene expression level obtained from the RNA sequence data for at least three genes in the T cells group;

determining the gene group expression level for the B cells group using the gene expression level obtained from the RNA sequence data for at least three genes in the B cells group;

determining the gene group expression level for the M1 signatures group using the gene expression level obtained from the RNA sequence data for at least three genes in the M1 signatures group;

determining the gene group expression level for the Th1 signature group using the gene expression level obtained from the RNA sequence data for at least three genes in the Th1 signature group;

determining the gene group expression level for the antitumor cytokines group using the gene expression level obtained from the RNA sequence data for at least three genes in the antitumor cytokines group;

determining the gene group expression level for the checkpoint inhibition group using the gene expression level obtained from the RNA sequence data for at least three genes in the checkpoint inhibition group;

determining the gene group expression level for the Treg group using the gene expression level obtained from the RNA sequence data for at least three genes in the Treg group;

determining the gene group expression level for the MDSC group using the gene expression level obtained from the RNA sequence data for at least three genes in the MDSC group;

determining the gene group expression level for the granulocytes group using the gene expression level obtained from the RNA sequence data for at least three genes in the granulocytes group;

determining the gene group expression level for the M2 signature group using the gene expression level obtained from the RNA sequence data for at least three genes in the M2 signature group;

determining the gene group expression level for the Th2 signature group using the gene expression level obtained from the RNA sequence data for at least three genes in the Th2 signature group;

determining the gene group expression level for the protumor cytokines group using the gene expression level obtained from the RNA sequence data for at least three genes in the protumor cytokines group; and

determining the gene group expression level for the complement inhibition group using the gene expression level obtained from the RNA sequence data for at least three genes in the complement inhibition group.

11. The method of claim 1, wherein identifying a particular MF profile cluster with which to associate the MF profile for the subject comprises identifying the first MF profile cluster associated with inflamed and vascularized biological samples and/or inflamed and fibroblast-enriched biological samples, and

wherein identifying the first anti-cancer therapy comprises identifying one or more of:

immune checkpoint inhibitors;

blockaders of Treg, MDSC and immunosuppressive factors;

angiogenesis and CAF inhibitors; and

inhibitors of metastatic or growth-signaling activities of malignant cells or tumor growth factors.

12. The method of claim 1, wherein identifying a particular MF profile cluster with which to associate the MF profile for the subject comprises identifying the second MF profile cluster associated with inflamed and nonvascularized biological samples and/or inflamed and non-fibroblast-enriched biological samples, and

wherein identifying the first anti-cancer therapy comprises identifying one or more of:

immune checkpoint inhibitors;

blockaders of Treg, MDSC and immunosuppressive factors; and

inhibitors of metastatic or growth-signaling activities of malignant cells or tumor growth factors.

13. The method of claim 1, wherein identifying a particular MF profile cluster with which to associate the MF profile for the subject comprises identifying the third MF profile cluster associated with non-inflamed and vascularized biological samples and/or non-inflamed and fibroblast-enriched biological samples, and

wherein identifying the first anti-cancer therapy comprises identifying one or more of:

inhibitors of angiogenesis, inhibitors of CAFs and/or immunosuppressive factors, and molecules that target M2 macrophages and MDSC.

14. The method of claim 1, wherein identifying a particular MF profile cluster with which to associate the MF profile for the subject comprises identifying the fourth MF profile cluster associated with non-inflamed and nonvascularized biological samples and/or non-inflamed and non-fibroblast-enriched biological samples, and

wherein identifying the first anti-cancer therapy comprises identifying one or more of:

chemotherapeutic regimen, radiotherapy, targeted tyrosine kinases, cyclin-dependent kinase inhibitors, or a therapy targeting traffic of T cells, Th1, and NK cells into a tumor.

15. The method of claim 1, wherein the first anti-cancer therapy comprises an anti-cancer therapeutic agent, optionally wherein the anti-cancer therapeutic agent is a small molecule, a polynucleotide, an expression vector, a subgenomic polynucleotide, a polypeptide, a peptide, a protein, a vector, or a eukaryotic cell.

16. The method of claim 1, wherein the first anti-cancer therapy comprises a chemotherapy.

17. The method of claim 1, wherein the first anti-cancer therapy comprises a radiotherapy.

18. The method of claim 1, wherein the first anti-cancer therapy comprises an immunotherapy.

19. The method of claim 1, wherein the first anti-cancer therapy comprises a targeted therapy.

20. The method of claim 1, wherein identifying the first anti-cancer therapy comprises identifying a therapy selected from:

the group consisting of;

HGFR inhibitors, EGFR inhibitors, VEGF inhibitors, PDGF inhibitors, CXR2 inhibitors, CXCR4 inhibitors, DPP-4 inhibitors, galectin inhibitors, antifibrotic agents, LPR1 inhibitors, TGF-beta inhibitors, IL5 inhibitors, IL4 inhibitors, IL13 inhibitors, IL22 inhibitors, CSF1R inhibitors, IDO inhibitors, LPR1 inhibitors, CD25 inhibitors, GITR inhibitors, PD1 inhibitors, CTLA1 inhibitors, PDL1 inhibitors, LAG3 inhibitors, TIM3 inhibitors, vaccines, PRIMA-1 analogues, CD40 agonists, ICOS agonists, OX40 agonists, Bcl-2 inhibitors, AKT inhibitors, MYC-targeting siRNA, pan-tyrosine kinase inhibitors, CDK4/6 inhibitors, Aurora A inhibitors, vaccines, LAG3 inhibitors, and any antibody-drug conjugate;

the group consisting of;

HGFR inhibitors, EGFR inhibitors, VEGF inhibitors, PDGF inhibitors, CXR2 inhibitors, galectin inhibitors, antifibrotic agents, LPR1 inhibitors, TGF-beta inhibitors, IL5 inhibitors, IL4 inhibitors, IL13 inhibitors, IL22 inhibitors, CSF1R inhibitors, IDO inhibitors, CXCR4 inhibitors, CD25 inhibitors, GITR inhibitors, PD1 inhibitors, CTLA1 inhibitors, PDL1 inhibitors, LAG3 inhibitors, TIM3 inhibitors, and vaccines;

the group consisting of;

HGFR inhibitors, EGFR inhibitors, PRIMA-1 analogues, TGF-beta inhibitors, IL22 inhibitors, CSF1R inhibitors, IDO inhibitors, LPR1 inhibitors, CXCR4 inhibitors, CD25 inhibitors, GITR inhibitors, CD40 agonists, ICOS agonists, OX40 agonists, and vaccines;

the group consisting of;

Bcl-2 inhibitors, AKT inhibitors, MYC-targeting siRNA, PRIMA-1 analogues, VEGF inhibitors, PDGF inhibitors, CXR2 inhibitors, galectin inhibitors, antifibrotic agents, LPR1 inhibitors, TGF-beta inhibitors, IL5 inhibitors, IL4 inhibitors, IL13 inhibitors, CSF1R inhibitors, IDO inhibitors, CXCR4 inhibitors, and vaccines;

the group consisting of;

antibody-drug conjugates, HGFR inhibitors, EGFR inhibitors, VEGF inhibitors, PDGF inhibitors, CXCR2 inhibitors, galectin inhibitors, antifibrotic agents, LPR1 inhibitors, TGF-beta inhibitors, IL22 inhibitors, and CXCL10 disrupting inhibitors;

or the group consisting of;

Bcl-2 inhibitors, AKT inhibitors, MYC-targeting siRNA, chemotherapy, pan-tyrosine kinase inhibitors, CDK4/6 inhibitors, Aurora A inhibitors, and DPP-4 inhibitors.

21. A method comprising:

administering a first anti-cancer therapy to a subject,

wherein the first anti-cancer therapy was identified by identifying a molecular-functional (MF) profile cluster with which to associate an MF profile for the subject, the identifying comprising;

obtaining first RNA expression data for biological samples from a plurality of subjects;

determining a respective plurality of molecular-functional (MF) profiles for the plurality of subjects at least in part by, for each of the plurality of subjects,

determining, using the first RNA expression data, a respective gene group expression level for each group in a set of gene groups, the set of gene groups comprising gene groups associated with cancer malignancy and different gene groups associated with cancer microenvironment;

clustering the plurality of MF profiles to obtain MF profile clusters including;

a first MF profile cluster associated with inflamed and vascularized biological samples and/or inflamed and fibroblast-enriched biological samples,

a second MF profile cluster associated with inflamed and non-vascularized biological samples and/or inflamed and non-fibroblast-enriched biological samples,

a third MF profile cluster associated with non-inflamed and vascularized biological samples and/or non-inflamed and fibroblast-enriched biological samples, and

a fourth MF profile cluster associated with non-inflamed and non-vascularized biological samples and/or non-inflamed and non-fibroblast-enriched biological samples;

obtaining second RNA expression data for a biological sample from the subject, wherein the subject is not in the plurality of subjects;

determining a molecular-functional (MF) profile for the subject at least in part by determining, using the second RNA expression data, a gene group expression level for each group in the set of gene groups to obtain gene group expression levels for the subject; and

comparing the gene group expression levels for the subject to gene group expression levels associated with the MF profile clusters;

wherein the first anti-cancer therapy comprises a therapy selected from the group consisting of;

antibody drug conjugates, hormonal therapy, viral therapy, genetic therapy, non-immune protein therapy, antiangiogenic agents, anti-cancer vaccines, soluble receptor therapy, and cell based therapies.

22. The method of claim 21,

(a) wherein the gene group associated with cancer malignancy is a tumor properties group;

and wherein determining the MF profile for the subject comprises determining a gene group expression level for the tumor properties group; and

/or

(b) wherein the gene groups associated with cancer microenvironment are a tumor-promoting immune microenvironment group, an anti-tumor immune microenvironment group, an angiogenesis group, and a fibroblasts group; and

wherein determining the MF profile for the subject comprises determining a gene group expression level for each of the tumor-promoting immune microenvironment group, the anti-tumor immune microenvironment group, the angiogenesis group, and the fibroblasts group.

23. The method of claim 21, wherein the first anti-cancer therapy comprises an antibody drug conjugate.

24. The method of claim 21, wherein the first anti-cancer therapy comprises a hormonal therapy.

25. The method of claim 21, wherein the first anti-cancer therapy comprises a viral therapy.

26. The method of claim 21, wherein the first anti-cancer therapy comprises a genetic therapy.

27. The method of claim 21, wherein the first anti-cancer therapy comprises a non-immune protein therapy.

28. The method of claim 21, wherein the first anti-cancer therapy comprises an antiangiogenic agent.

29. The method of claim 21, wherein the first anti-cancer therapy comprises an anti-cancer vaccine.

30. The method of claim 21, wherein the first anti-cancer therapy comprises a soluble receptor therapy or a cell based therapy.