RELATED APPLICATIONS

This application claims the benefit of European Patent Application No. EP15181029.8, filed Aug. 14, 2015, the entirety of the specification and claims thereof is hereby incorporated by reference for all purposes.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON AS A TEXT FILE VIA THE OFFICE ELECTRONIC FILING SYSTEM (EFS-WEB)

A Sequence Listing associated with this application is provided in text format in lieu of a paper copy, and is hereby incorporated by reference into the specification. The name of the text file containing the Sequence Listing is 2015PF00604_2016-08-11_sequencelisting_ST25.txt. The text file is 143 KB, was created on Aug. 11, 2016, and is being submitted electronically via EFS-Web.

FIELD OF THE INVENTION

The present invention is in the field of systems biology, bioinformatics, genomic mathematical processing and proteomic mathematical processing. In particular, the invention includes a systems-based mathematical process for determining the activity of a NFkB cellular signaling pathway in a subject based on expression levels of a unique set of selected target genes in a subject. The invention further provides an apparatus that includes a digital processor configured to perform such a method, a non-transitory storage medium storing instructions that are executable by a digital processing device to perform such a method, and a computer program comprising a program code means for causing a digital processing device to perform such a method. The present invention also includes kits for the determination of expression levels of the unique combinations of target genes.

BACKGROUND OF THE INVENTION

As knowledge of tumors including cancers evolve, it becomes more clear that they are extraordinarily heterogeneous and multifactorial. Tumors and cancers have a wide range of genotypes and phenotypes, they are influenced by their individualized cell receptors (or lack thereof), micro-environment, extracellular matrix, tumor vascularization, neighboring immune cells, and accumulations of mutations, with differing capacities for proliferation, migration, stem cell properties and invasion. This scope of heterogeneity exists even among same classes of tumors. See generally:NatureInsight: Tumor Heterogeneity (entire issue of articles), 19 Sep. 2013 (Vol. 501, Issue 7467); Zellmer and Zhang, “Evolving concepts of tumor heterogeneity”,Cell and Bioscience2014, 4:69.

Traditionally, physicians have treated tumors, including cancers, as the same within class type (including within receptor type) without taking into account the enormous fundamental individualized nature of the diseased tissue. Patients have been treated with available chemotherapeutic agents based on class and receptor type, and if they do not respond, they are treated with an alternative therapeutic, if it exists. This is an empirical approach to medicine.

There has been a growing trend toward taking into account the heterogeneity of tumors at a more fundamental level as a means to create individualized therapies, however, this trend is still in its formative stages. What is desperately needed are approaches to obtain more metadata about the tumor to inform therapeutic treatment in a manner that allows the prescription of approaches more closely tailored to the individual tumor, and perhaps more importantly, avoiding therapies destined to fail and waste valuable time, which can be life-determinative.

A number of companies and institutions are active in the area of classical, and some more advanced, genetic testing, diagnostics, and predictions for the development of human diseases, including, for example: Affymetrix, Inc.; Bio-Rad, Inc; Roche Diagnostics; Genomic Health, Inc.; Regents of the University of California; Illumina; Fluidigm Corporation; Sequenom, Inc.; High Throughput Genomics; NanoString Technologies; Thermo Fisher; Danaher; Becton, Dickinson and Company; bioMerieux; Johnson & Johnson, Myriad Genetics, and Hologic.

Several companies have developed technology or products directed to gene expression profiling and disease classification. For example, Genomic Health, Inc. is the assignee of numerous patents pertaining to gene expression profiling, for example: U.S. Pat. Nos. 7,081,340; 8,808,994; 8,034,565; 8,206,919; 7,858,304; 8,741,605; 8,765,383; 7,838,224; 8,071,286; 8,148,076; 8,008,003; 8,725,426; 7,888,019; 8,906,625; 8,703,736; 7,695,913; 7,569,345; 8,067,178; 7,056,674; 8,153,379; 8,153,380; 8,153,378; 8,026,060; 8,029,995; 8,198,024; 8,273,537; 8,632,980; 7,723,033; 8,367,345; 8,911,940; 7,939,261; 7,526,637; 8,868,352; 7,930,104; 7,816,084; 7,754,431 and 7,208,470, and their foreign counterparts.

U.S. Pat. No. 9,076,104 to the Regents of the University of California titled “Systems and Methods for Identifying Drug Targets using Biological Networks” claims a method with computer executable instructions by a processor for predicting gene expression profile changes on inhibition of proteins or genes of drug targets on treating a disease, that includes constructing a genetic network using a dynamic Bayesian network based at least in part on knowledge of drug inhibiting effects on a disease, associating a set of parameters with the constructed dynamic Bayesian network, determining the values of a joint probability distribution via an automatic procedure, deriving a mean dynamic Bayesian network with averaged parameters and calculating a quantitative prediction based at least in part on the mean dynamic Bayesian network, wherein the method searches for an optimal combination of drug targets whose perturbed gene expression profiles are most similar to healthy cells.

Affymetrix has developed a number of products related to gene expression profiling. Non-limiting examples of U.S. patents to Affymetrix include: U.S. Pat. Nos. 6,884,578; 8,029,997; 6,308,170; 6,720,149; 5,874,219; 6,171,798; and 6,391,550.

Likewise, Bio-Rad has a number of products directed to gene expression profiling. Illustrative examples of U.S. patents to Bio-Rad include: U.S. Pat. Nos. 8,021,894; 8,451,450; 8,518,639; 6,004,761; 6,146,897; 7,299,134; 7,160,734; 6,675,104; 6,844,165; 6,225,047; 7,754,861 and 6,004,761.

Koninklijke Philips N. V. (NL) has filed a number of patent applications in the general area of assessment of cellular signaling pathway activity using various mathematical models, including U.S. Ser. No. 14/233,546 (WO 2013/011479), titled “Assessment of Cellular Signaling Pathway Using Probabilistic Modeling of Target Gene Expression”; U.S. Ser. No. 14/652,805 (WO 2014/102668) titled “Assessment of Cellular Signaling Pathway Activity Using Linear Combinations of Target Gene Expressions”; WO 2014/174003 titled “Medical Prognosis and Prediction of Treatment Response Using Multiple Cellular Signaling Pathway Activities”; and WO 2015/101635 titled “Assessment of the PI3K Cellular Signaling Pathway Activity Using Mathematical Modeling of Target Gene Expression”.

Despite this progress, more work is needed to definitively characterize tumor cellular behavior. In particular, there is a critical need to determine which pathways have become pathogenic to the cell. However, it is difficult to identify and separate abnormal cellular signaling from normal cellular pathway activity.

Nuclear factor-kappa B (NFkB or NFκB) is an inducible transcription factor that regulates the expression of many genes involved in the immune response. The NFkB cellular signaling pathway is a key cellular signaling pathway involved in immune, inflammatory, and acute phase response, but is also implicated in the control of cell survival, proliferation, and apoptosis. In healthy, non-activated cells, the NFkB cellular signaling pathway associated transcription factors that are composed of dimers originating from five genes (NFKB1 or p50/p105, NFKB2 or p52/p100, RELA or p65, REL, and RELB) are predominantly cytoplasmic due to their interaction with the inhibitors of NFkB (IkBs) and therefore remain transcriptionally inactive, thus keeping the NFkB cellular signaling pathway inactive. Upon activation of the upstream signaling cascade, the IkBs become phosphorylated and undergo ubiquitin-dependent degradation by the proteasome, and NFkB dimers are translocated to the nucleus where they act as transcription factors. Besides this canonical NFkB cellular signaling pathway there is also an alternative pathway that is able to initiate NFkB regulated transcription (seeFIG. 1; CP=canonical pathway; AP=alternative pathway; PS=proteasome; NC=nucleus). The term “NFkB cellular signaling pathway” herein preferably refers to any signaling process that leads to transcriptional activity of the above mentioned NFkB transcription factors.

Although activity of the NFkB cellular signaling pathway is known to be associated with different types of cancer and to support the pro-survival phenotypes of cancer cells, there is no clinical assay available to assess the activity of the NFkB cellular signaling pathway. Thus, it is desirable to be able to improve the possibilities of characterizing patients that have a cancer, e.g., a diffuse large B-cell lymphoma (DLBCL), a multiple myeloma, a cancer of another haematological origin, or a solid tumor, such as a breast, melanoma, or prostate tumor, which is at least partially driven by a deregulated NFkB cellular signaling pathway, and that are therefore likely to respond to inhibitors of the NFkB cellular signaling pathway.

It is therefore an object of the invention to provide a more accurate process to determine the tumorigenic propensity of the NFkB cellular signaling pathway in a cell, as well as associated methods of therapeutic treatment, kits, systems, etc.

SUMMARY OF THE INVENTION

The present invention includes methods and apparatuses for determining the activity level of a NFkB cellular signaling pathway in a subject, typically a human with diseased tissue such as a tumor or cancer, wherein the activity level of the NFkB cellular signaling pathway is determined by calculating a level of NFkB transcription factor element in a sample of the involved tissue isolated from the subject, wherein the level of the NFkB transcription factor element in the sample are determined by measuring the expression levels of a unique set of target genes controlled by the NFkB transcription factor element using a calibrated pathway model that compares the expression levels of the target genes in the sample with expression levels of the target genes in the calibrated pathway model.

In particular, the unique set of target genes whose expression level is analyzed in the model includes at least six target genes, at least seven target genes, at least eight target genes, at least nine target genes, at least ten or more target genes selected from BCL2L1, BIRC3, CCL2, CCL3, CCL4, CCL5, CCL20, CCL22, CX3CL1, CXCL1, CXCL2, CXCL3, ICAM1, IL1B, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKBIE, PTGS2, SELE, STAT5A, TNF, TNFAIP2, TNIP1, TRAF1, and VCAM1. In one embodiment, the unique set of target genes whose expression level is analyzed in the model is selected from BIRC3, CCL2, CCL5, CCL20, CXCL1, CXCL2, CXCL3, ICAM1, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKBIE, TNF, TNFAIP2, TRAF1, and VCAM1. In one embodiment, the unique set of target genes comprises at least three target genes, at least four target genes, at least five target genes, at least six or more target genes selected from CCL2, CCL5, CCL20, CXCL1, CXCL2, CXCL3, ICAM1, IL6, IL8, MMP9, NFKB2, NFKBIA, and TNFAIP2. In one embodiment, the unique set of target genes comprises at least three target genes, at least four target genes, at least five target genes, at least six or more target genes selected from CCL5, CXCL2, ICAM1, IL6, IL8, NFKBIA, and TNFAIP2.

Using this invention, health care providers will be able to more accurately assess the functional state of the NFkB cellular signaling pathway at specific points in disease progression. Without being bound by any particular theory, it is believed that the identified target genes of the present invention in combination with the analytical methods described herein reduces the noise associated with the use of large subsets of target genes as previously described in the literature. Furthermore, as described and exemplified below, the use of specific combinations of select target genes allows for the precise determination of cellular signaling activity, and allows for an increased accuracy in the determination of disease state and prognosis. Accordingly, such cellular signaling pathway status can be used to, for example but not limited to, identify the presence or absence of disease and/or particular disease state or advancement, identify the presence or absence of a disorder or disease state, identify a particular subtype within a disease or disorder based one the activity level of the NFkB cellular signaling pathway, derive a course of treatment based on the presence or absence of NFkB signaling activity for example by administering a NFkB inhibitor, and/or monitor disease progression in order to, for example, adjust therapeutic protocols based on a predicted drug efficacy in light of the determined activity of the NFkB cellular signaling pathway in the sample.

The term “NFkB transcriptional factor element” or “NFkB TF element” or “TF element” refers to a protein complex containing at least one or, preferably, a dimer of the NFkB members (NFKB1 or p50/p105, NFKB2 or p52/p100, RELA or p65, REL, and RELB), which is capable of binding to specific DNA sequences, thereby controlling transcription of target genes.

The present invention is based on the realization of the inventors that a suitable way of identifying effects occurring in the NFkB cellular signaling pathway can be based on a measurement of the signaling output of the NFkB cellular signaling pathway, which is—amongst others—the transcription of the unique target genes described herein by a NFkB transcription factor (TF) element controlled by the NFkB cellular signaling pathway. This realization by the inventors assumes that the TF level is at a quasi-steady state in the sample which can be detected by means of—amongst others—the expression values of the target genes. The NFkB cellular signaling pathway targeted herein is known to be associated with different types of cancer and to support the pro-survival phenotypes of cancer cells as the NFkB cellular signaling pathway is known to regulate genes that control cell proliferation and cell survival processes. Many different types of human tumors are found to have a deregulated activity of the NFkB cellular signaling pathway. Furthermore, studies have shown that the inhibition of constitutive NFkB cellular signaling pathway activity blocks the oncogenic potential of cancerous cells.

The present invention makes it possible to determine the activity of the NFkB cellular signaling pathway by (i) determining a level of an NFkB TF element in the sample, wherein the determining is based at least in part on evaluating a mathematical model relating expression levels of at least six target genes of the NFkB cellular signaling pathway, the transcription of which is controlled by the NFkB TF element, to the level of the NFkB TF element, and by (ii) inferring the activity of the NFkB cellular signaling pathway based on the determined level of the NFkB TF element in the sample. This preferably allows improving the possibilities of characterizing patients that have a cancer, e.g., a diffuse large B-cell lymphoma (DLBCL), a multiple myeloma, a cancer of another haematological origin, or a solid tumor, such as a breast, melanoma, or prostate tumor, which is at least partially driven by a deregulated NFkB cellular signaling pathway, and that are therefore likely to respond to inhibitors of the NFkB cellular signaling pathway. An important advantage of the present invention is that it makes it possible to determine the activity of the NFkB cellular signaling pathway using a single sample, rather than requiring a plurality of samples extracted at different points in time. In particular embodiments, treatment determination can be based on specific NFkB activity. In a particular embodiment the NFkB cellular signaling status can be set at a cutoff value of odds of the NFkB cellular signaling pathway being activate of, for example, 10:1, 5:1, 4:1, 2:1, 1:1, 1:2, 1:4, 1:5, or 1:10.

In one aspect of the invention, provided herein is a computer implemented method for determining the activity level of a NFkB cellular signaling pathway in a subject performed by a computerized device having a processor comprising:a. calculating an activity level of NFkB transcription factor element in a sample isolated from the subject, wherein the activity level of NFkB transcription factor element in the sample is calculated by:i. receiving data on the expression levels of at least six target genes derived from the sample, wherein the NFkB transcription factor element controls transcription of the at least six target genes, and wherein the at least six target genes are selected from BCL2L1, BIRC3, CCL2, CCL3, CCL4, CCL5, CCL20, CCL22, CX3CL1, CXCL1, CXCL2, CXCL3, ICAM1, IL1B, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKBIE, PTGS2, SELE, STAT5A, TNF, TNFAIP2, TNIP1, TRAF1, and VCAM1;ii. calculating the activity level of the NFkB transcription factor element in the sample using a calibrated pathway model, wherein the calibrated pathway model compares the expression levels of the at least six target genes in the sample with expression levels of the at least six target genes in the model which define an activity level of NFkB transcription factor element; and,b. calculating the activity level of the NFkB cellular signaling pathway in the sample based on the calculated activity levels of NFkB transcription factor element in the sample.

In one embodiment, the method further comprises assigning a NFkB cellular signaling pathway activity status to the calculated activity level of the NFkB cellular signaling pathway in the sample wherein the activity status is indicative of either an active NFkB cellular signaling pathway or a passive NFkB cellular signaling pathway.

In one embodiment, the at least six target genes are selected from BIRC3, CCL2, CCL5, CCL20, CXCL1, CXCL2, CXCL3, ICAM1, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKBIE, TNF, TNFAIP2, TRAF1, and VCAM1. In one embodiment, the at least six target genes comprise at least three target genes selected from CCL2, CCL5, CCL20, CXCL1, CXCL2, CXCL3, ICAM1, IL6, IL8, MMP9, NFKB2, NFKBIA, and TNFAIP2. In one embodiment, the at least three target genes are selected from CCL5, CXCL2, ICAM1, IL6, IL8, NFKBIA, and TNFAIP2.

In one embodiment, the status of the NFkB cellular signaling pathway is established by establishing a specific threshold for activity as described further below. In one embodiment, the threshold is set as a probability that the cellular signaling pathway is active, for example, a 10:1, 5:1, 4:1, 3:1, 2:1, 1:1, 1:2, 1:4, 1:5, or 1:10. In one embodiment, the activity status is based, for example, on a minimum calculated activity. In one embodiment, the method further comprises assigning to the calculated NFkB cellular signaling in the sample a probability that the NFkB cellular signaling pathway is active.

As contemplated herein, the level of the NFkB transcription factor element is determined using a calibrated pathway model executed by one or more computer processors, as further described below. The calibrated pathway model compares the expression levels of the at least six target genes in the sample with expression levels of the at least six target genes in the calibrated pathway model which define a level of a NFkB transcription factor element. In one embodiment, the calibrated pathway model is a probabilistic model incorporating conditional probabilistic relationships that compare the expression levels of the at least six target genes in the sample with expression levels of the at least six target genes in the model which define a level of a NFkB transcription factor element to determine the level of the NFkB transcription factor element in the sample. In one embodiment, the probabilistic model is a Bayesian network model. In an alternative embodiment, the calibrated pathway model can be a linear or pseudo-linear model. In an embodiment, the linear or pseudo-linear model is a linear or pseudo-linear combination model.

As contemplated herein, the expression levels of the unique set of target genes can be determined using standard methods known in the art. For example, the expression levels of the target genes can be determined by measuring the level of mRNA of the target genes, through quantitative reverse transcriptase-polymerase chain reaction techniques, using probes associated with a mRNA sequence of the target genes, using a DNA or RNA microarray, and/or by measuring the protein level of the protein encoded by the target genes. Once the expression level of the target genes is determined, the expression levels of the target genes within the sample can be utilized in the model in a raw state or, alternatively, following normalization of the expression level data. For example, expression level data can be normalized by transforming it into continuous data, z-score data, discrete data, or fuzzy data.

As contemplated herein, the calculation of NFkB signaling in the sample is performed on a computerized device having a processor capable of executing a readable program code for calculating the NFkB signaling in the sample according to the methods described above. Accordingly, the computerized device can include means for receiving expression level data, wherein the data is expression levels of at least six target genes derived from the sample, a means for calculating the level of a NFkB transcription factor element in the sample using a calibrated pathway model, wherein the calibrated pathway model compares the expression levels of the at least six target genes in the sample with expression levels of the at least six target genes in the model which define a level a NFkB transcription factor element; a means for calculating the NFkB cellular signaling in the sample based on the calculated levels of a NFkB transcription factor element in the sample; and a means for assigning a NFkB cellular signaling pathway activity probability or status to the calculated NFkB cellular signaling in the sample, and, optionally, a means for displaying the NFkB signaling pathway activity probability or status.

In accordance with another disclosed aspect, further provided herein is a non-transitory storage medium capable of storing instructions that are executable by a digital processing device to perform the method according to the present invention as described herein. The non-transitory storage medium may be a computer-readable storage medium, such as a hard drive or other magnetic storage medium, an optical disk or other optical storage medium, a random access memory (RAM), read only memory (ROM), flash memory, or other electronic storage medium, a network server, or so forth. The digital processing device may be a handheld device (e.g., a personal data assistant or smartphone), a notebook computer, a desktop computer, a tablet computer or device, a remote network server, or so forth.

Further contemplated herein are methods of treating a subject having a disease or disorder associated with an activated NFkB cellular signaling pathway, or a disorder whose advancement or progression is exacerbated or caused by, whether partially or wholly, an activated NFkB cellular signaling pathway, wherein the determination of the NFkB cellular signaling pathway activity is based on the methods described above, and administering to the subject a NFkB inhibitor if the information regarding the activity level of NFkB cellular signaling pathway is indicative of an active NFkB cellular signaling pathway. In one embodiment, the disorder is one of an auto-immune and other immune disorders, cancer, bronchial asthma, heart disease, diabetes, hereditary hemorrhagic telangiectasia, Marfan syndrome, Vascular Ehlers-Danlos syndrome, Loeys-Dietz syndrome, Parkinson's disease, Chronic kidney disease, Multiple Sclerosis, fibrotic diseases such as liver, lng, or kidney fibrosis, Dupuytren's disease, or Alzheimer's disease. In a particular embodiment, the subject is suffering from a cancer, for example, a breast cancer, lung cancer, a colon cancer, pancreatic cancer, brain cancer, or breast cancer. In a more particular embodiment, the cancer is a breast cancer.

Also contemplated herein is a kit for measuring the expression levels of at least six or more NFkB cellular signaling pathway target genes, for example, seven, eight, nine, ten, eleven, twelve, or more target genes as described herein. In one embodiment, the kit includes one or more components, for example probes, for example labeled probes, and/or PCR primers, for measuring the expression levels of at least six target genes, at least seven target genes, at least eight target genes, or at least nine or more target genes selected from BCL2L1, BIRC3, CCL2, CCL3, CCL4, CCL5, CCL20, CCL22, CX3CL1, CXCL1, CXCL2, CXCL3, ICAM1, IL1B, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKBIE, PTGS2, SELE, STAT5A, TNF, TNFAIP2, TNIP1, TRAF1, and VCAM1. In one embodiment, the kit includes one or more components for measuring the expression levels of at least six target genes, at least seven target genes, at least eight target genes, or at least nine or more target genes selected from BIRC3, CCL2, CCL5, CCL20, CXCL1, CXCL2, CXCL3, ICAM1, IL6, IL8, IRF1, MMP9, NFKB2, NFKBIA, NFKBIE, TNF, TNFAIP2, TRAF1, and VCAM1. In one embodiment, the one or more components comprise one or more components for measuring the expression levels of at least three target genes, at least four target genes, at least five target genes, or at least six or more target genes selected from CCL2, CCL5, CCL20, CXCL1, CXCL2, CXCL3, ICAM1, IL6, IL8, MMP9, NFKB2, NFKBIA, and TNFAIP2. In one embodiment, the one or more components comprise one or more components for measuring the expression levels of at least three target genes, at least four target genes, at least five target genes, or at least six or more target genes selected from CCL5, CXCL2, ICAM1, IL6, IL8, NFKBIA, and TNFAIP2.

As contemplated herein, the one or more components or means for measuring the expression levels of the particular target genes can be selected from the group consisting of: an DNA array chip, an oligonucleotide array chip, a protein array chip, an antibody, a plurality of probes, for example, labeled probes, a set of RNA reverser-transcriptase sequencing components, and/or RNA or DNA, including cDNA, amplification primers. In one embodiment, the kit includes a set of labeled probes directed to a portion of an mRNA or cDNA sequence of the targeted genes as described herein. In one embodiment, the kit includes a set of primers and probes directed to a portion of an mRNA or cDNA sequence of the targeted genes as described further below, wherein, for example, the set includes specific primers or probes selected from the sequences of Table 1. In one embodiment, the labeled probes are contained in a standardized 96-well plate. In one embodiment, the kit further includes primers or probes directed to a set of reference genes, for example, as represented in Table 2. Such reference genes can be, for example, constitutively expressed genes useful in normalizing or standardizing expression levels of the target gene expression levels described herein.

In one embodiment, the kit further includes a non-transitory storage medium containing instructions that are executable by a digital processing device to perform a method according to the present invention as described herein. In one embodiment, the kit includes an identification code that provides access to a server or computer network for analyzing the activity level of the NFkB cellular signaling pathway based on the expression levels of the target genes and the methods described herein.

